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Women's Health Research: Progress, Pitfalls, and Promise (2010)

Chapter: Appendix C: Selected Studies of Women's Health

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Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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APPENDIX C
Selected Studies of Women’s Health

This appendix presents a selection of major studies that have looked at a wide variety of end points and issues related to women’s health. Much has been done over the years and this appendix is not a complete or comprehensive review. Rather, it is an overview of a few selected large ongoing multi-publication studies that look at a variety of risk factors and outcomes related to women’s health. The studies included here are all based in the United States and funded by the National Institutes of Health (NIH).

WOMEN’S HEALTH INITIATIVE

Study Objective and Design

The Women’s Health Initiative (WHI) included clinical trials, observational studies, and a community prevention study.

Three clinical trials were designed to test the effects of calcium and vitamin D supplements, diet modification, and postmenopausal hormone therapy on heart disease, fractures, and breast and colorectal cancer in healthy postmenopausal women 50–79 years old. Specific objectives of the trials were as follows:

  1. Calcium and vitamin D (CaD) study—To examine the effects of calcium plus vitamin D supplements (1,000 mg of calcium carbonate and 400 IU of vitamin D daily) compared with placebo on fractures and colorectal cancer in postmenopausal women. (The study also looked at effects of CaD on weight gain.)

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×
  1. Dietary-modification trial—To examine the effects of a low-fat diet (20% of daily calories from fat), increased fruit and vegetable consumption (5 or more servings per day), and increased grain consumption (6 or more servings per day) compared with usual diet on breast cancer, colorectal cancer, and heart disease in postmenopausal women. (The trial also looked at effects of this diet modification on Type 2 diabetes and ovarian cancer.)

  2. Hormone trial1—To examine the effects on coronary heart disease and osteoporotic fractures and associated risk of breast cancer of (1) estrogen plus progestin2 compared with placebo in postmenopausal women with a uterus, and (2) of estrogen alone3 compared with placebo in postmenopausal women without a uterus.

A prospective observational study was also conducted to produce reliable estimates of the extent to which known risk factors predict heart disease, cancers, and fractures; to identify “new” risk factors for these and other diseases in women; to compare risk factors, presence of disease at the start of the study, and new occurrences of disease during the WHI in all study components; and to create a future resource for identifying biologic indicators of disease, especially substances and factors found in blood.

A WHI Extension Study to encompass 5 years of additional followup (from 2005–2010) includes participants from both the clinical trial and observational WHI components. The purposes of the additional followup are to describe the longer-term effects of the original interventions, to document change in hormone use in participants from the hormone therapy trials, to expand the list of scientific questions that can be reliably addressed in the WHI, and to provide an infrastructure able to support additional investigations that require some of the unique features of a very large longitudinal study of postmenopausal women.

A community prevention study to develop carefully evaluated, model programs that could be implemented in a wide variety of communities throughout the United States was also conducted but will not be described here.

Participant Enrollment

Participants were recruited at 40 clinical centers around the United States over a 5-year period—September 1993–December 1998—with a planned average of 8 years of followup and 2 years for data analysis. A total of 161,808 generally healthy postmenopausal women 50–79 years old were enrolled.

1

The hormone trials have ended but the women who were enrolled in these trials participated in a followup phase, which concluded in 2010.

2

Consisting of 0.625 mg of conjugated equine estrogens plus 2.5 mg of medroxyprogesterone acetate.

3

Consisting of 0.625 mg of conjugated equine estrogens.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

A total of 68,132 women were enrolled in the clinical trials. Women could enroll in one or more of the clinical trials. The final enrollment breakdown was as follows:

  • CaD study, 36,282

  • Dietary-modification trial, 48,835

  • Hormone trial, 27,347; 16,608 women were enrolled in the estrogen-plus-progestin study and 10,739 in the estrogen-alone study

In both hormone trials and in the CaD trial there was a 1:1 randomized and double-blind allocation between active and placebo study pills. In the dietary-modification trial, 40% of enrollees were assigned to the low-fat eating pattern and 60% to the comparison group.4

The observational study enrolled 93,676 women who were determined to be ineligible or unwilling to participate in the clinical trials.

The WHI Extension Study enrolled 115,400 consenting participants from each of the original WHI study components for an additional 5 years of followup, from 2005 to 2010.

Data Collection5

Data on participants’ past hormone use at baseline, with current medications and current supplements, were collected for participants in both the clinical trial and the observational study through in-person interviews. Physical measurements and blood samples were taken at baseline, and thereafter physical measurements were taken annually for clinical-trial participants and at year 3 for observational-study participants. Data on clinical-trial patients’ current medications and supplements were assessed for clinical-trial participants at years 1, 3, 6, and 9, and on observational-study participants’ medications and supplements at year 3.

Twice a year, all clinical-trial participants completed a medical-history questionnaire to assess outcomes, such as hospitalizations, heart disease, stroke, fractures, and cancer. Observational-study participants completed a medical history questionnaire annually to assess outcomes. Observational-study participants also completed a self-administered followup survey each year except study year 2. The survey was modified each year. In general, it asked participants to provide information about their weight and any changes in weight; respond to questions about health behaviors, such as physical activity, alcohol and caffeine consump-

4

The imbalanced randomization was set to reduce the higher staff and material costs associated with implementing the intervention while maintaining statistical power for testing hypotheses.

5

See the frequency-of-data collection table at http://www.whiscience.org/data/collection_frequency_grid.pdf (accessed April 8, 2010) for a more detailed description of the data that were captured and when for each study component.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

tion, and smoking status; and provide information about exposures, such as use of hormone therapy and other medications.6

Both clinical-trial and observational-study participants completed a baseline food-frequency questionnaire (FFQ). A rotating sample of one-third of dietary-modification–trial participants completed annual followup FFQs and observational-study participants completed a followup FFQ at year 3.

For CaD participants, management and safety interviews to assess symptoms, adherence, and pill tolerance were conducted 4 weeks after randomization and repeated semi-annually thereafter while the participants were taking study pills. Management and safety interviews were conducted for hormone-therapy participants 6 weeks after randomization and semiannually thereafter. Physical and gynecological examination data were collected at annual clinic visits for hormone-therapy participants and reviewed for safety concerns. Hormonetherapy participants were also required to have a mammography annually, and study pills were not dispensed if a benign mammography report had not been received in the previous 18 months.

Participants in the CaD and dietary-modification trials were followed over an average of 7 years and 8.1 years, respectively. Participants in the estrogen-plus-progestin and the estrogen-only trials were followed over an average of 5.6 years and 7.1 years, respectively.

In the WHI Extension Study, annual updates on health outcomes are collected by mail from all enrolled participants. Women who report study outcomes that require documentation are contacted by field-center staff to document details of the outcome. All participants also receive an annual activities-of-daily-life assessment and complete a one-time medical-history–update addendum. A 4.6% subsample of women who were in the WHI dietary-modification–trial are asked to complete one 24-hour recall during the Extension Study. Half of the subsample completed the recall toward the start of the Extension Study (around 2006–2007) and half toward the end (2009–2010). Participants who were in the hormone-therapy trial also complete a “Hormone Use Update” form annually. For the first 2 years of extension followup, WHI field centers collected annual mammography reports for hormone therapy participants.

6

The annual followup response rate was over 94% each year for those who were due for a followup contact. At the year 3 clinic visit, 96% completed medical-history updates and 83% provided blood samples. At the end of the closeout period, 4.1% were either lost to followup or had stopped followup, and 6.1% were deceased.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Findings

The WHI has yielded numerous publications. The portions of the abstracts dealing with results, organized by study component and health condition, are presented in Tables C-1C-6.

TABLE C-1 Publications on Women’s Health Initiative Calcium and Vitamin D Study

Colorectal Cancer

Wactawski-Wende et al., 2006

A total of 322 women were diagnosed with invasive colorectal cancer during the study period. There were no significant differences in colorectal cancer diagnoses between participants who took the active CaD supplements and those who took placebo pills (168 and 154 cases; hazard ratio, 1.08; 95 percent CI, 0.86 to 1.34; P = 0.51). There were also no differences between the two groups in types of colorectal cancers or reported number of colon polyps. No differences were found when analysis was limited to participants taking most of their study pills and when taking into account participants’ personal calcium and vitamin D intakes.

Fractures

Jackson et al., 2006

“Calcium with vitamin D supplementation resulted in a small but significant improvement in hip bone density and did not significantly reduce hip fracture…. Hip bone density was 1.06 percent higher in the calcium plus vitamin D group than in the placebo group (P < 0.01). Intention-to-treat analysis indicated that participants receiving calcium plus vitamin D supplementation had a hazard ratio of 0.88 for hip fracture (95 percent confidence interval, 0.72 to 1.08), 0.90 for clinical spine fracture (0.74 to 1.10), and 0.96 for total fractures (0.91 to 1.02). The risk of renal calculi increased with calcium plus vitamin D (hazard ratio, 1.17; 95 percent confidence interval, 1.02 to 1.34). Censoring data from women when they ceased to adhere to the study medication reduced the hazard ratio for hip fracture to 0.71 (95 percent confidence interval, 0.52 to 0.97). Effects did not vary significantly according to prerandomization serum vitamin D levels.”

Weight Gain

Caan et al., 2007

At the end of the study, women in the group taking CaD supplements weighed an average of 0.28 pounds less than those taking the placebo pills, which is a small but statistically significant difference in weight change. Women taking active pills were also less likely to gain weight. The greatest benefits were seen in women whose total calcium intakes at the start of the study were below 1,200 mg/day, which is the current recommended dietary intake for women this age. These women, compared to women taking placebo, had a lower risk of gaining weight and had a higher likelihood of maintaining a stable weight (within 2.2 pounds of their starting weight) or losing weight (more than 2.2 pounds), after three years in the study.

ABBREVIATIONS: CaD, calcium plus vitamin D; CI, confidence interval.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

TABLE C-2 Publications on Women’s Health Initiative Dietary Modification Trial

Breast Cancer

Prentice et al., 2006

“Dietary fat intake was significantly lower in the dietary modification intervention group compared with the comparison group. The difference between groups in change from baseline for percentage of energy from fat varied from 10.7% at year 1 to 8.1% at year 6. Vegetable and fruit consumption was higher in the intervention group by at least 1 serving per day and a smaller, more transient difference was found for grain consumption. The number of women who developed invasive breast cancer (annualized incidence rate) over the 8.1-year average follow-up period was 655 (0.42%) in the intervention group and 1072 (0.45%) in the comparison group (hazard ratio, 0.91; 95% confidence interval, 0.83–1.01 for the comparison between the 2 groups). Secondary analyses suggest a lower hazard ratio among adherent women, provide greater evidence of risk reduction among women having a high-fat diet at baseline, and suggest a dietary effect that varies by hormone receptor characteristics of the tumor.”

Cardiovascular Disease (Heart Attack and Stroke)

Howard et al., 2006

“By year 6, mean fat intake decreased by 8.2% of energy intake in the intervention vs the comparison group, with small decreases in saturated (2.9%), monounsaturated (3.3%), and polyunsaturated (1.5%) fat; increases occurred in intakes of vegetables/fruits (1.1 servings/d) and grains (0.5 serving/d). Low-density lipoprotein cholesterol levels, diastolic blood pressure, and factor VIIc levels were significantly reduced by 3.55 mg/dL, 0.31 mm Hg, and 4.29%, respectively; levels of high-density lipoprotein cholesterol, triglycerides, glucose, and insulin did not significantly differ in the intervention vs comparison groups…. The numbers who developed CHD, stroke, and CVD (annualized incidence rates) were 1,000 (0.63%), 434 (0.28%), and 1,357 (0.86%) in the intervention and 1,549 (0.65%), 642 (0.27%), and 2,088 (0.88%) in the comparison group. The diet had no significant effects on incidence of CHD (hazard ratio [HR], 0.97; 95% confidence interval [CI], 0.90–1.06), stroke (HR, 1.02; 95% CI, 0.90–1.15), or CVD (HR, 0.98; 95% CI, 0.92–1.05). Excluding participants with baseline CVD (3.4%), the HRs (95% CIs) for CHD and stroke were 0.94 (0.86–1.02) and 1.02 (0.90–1.17), respectively. Trends toward greater reductions in CHD risk were observed in those with lower intakes of saturated fat or trans fat or higher intakes of vegetables/fruits.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Colorectal Cancer

Beresford et al., 2006

“A total of 480 incident cases of invasive colorectal cancer occurred during a mean follow-up of 8.1 (SD, 1.7) years. Intervention group participants significantly reduced their percentage of energy from fat by 10.7% more than did the comparison group at 1 year, and this difference between groups was mostly maintained (8.1% at year 6). Statistically significant increases in vegetable, fruit, and grain servings were also made. Despite these dietary changes, there was no evidence that the intervention reduced the risk of invasive colorectal cancer during the follow-up period. There were 201 women with invasive colorectal cancer (0.13% per year) in the intervention group and 279 (0.12% per year) in the comparison group (hazard ratio, 1.08; 95% confidence interval, 0.90–1.29)…. Secondary analyses suggested potential interactions with baseline aspirin use and combined estrogen-progestin use status (P = .01 for each). Colorectal examination rates, although not protocol defined, were comparable between the intervention and comparison groups. Similar results were seen in analyses adjusting for adherence to the intervention.”

Diabetes

Tinker et al., 2008

3,342 participants developed diabetes mellitus that was treated by insulin or medications over the study period. There was a 4% reduced risk (not statistically significant) of developing diabetes in the low-fat dietary change group compared to participants in the usual diet comparison group. Participants who reported greater reductions in fat intake after the first year had greater reductions in risk of diabetes (statistically significant). The trend of reduced risk was not statistically significant after accounting for weight loss.

Ovarian Cancer

Prentice et al., 2007

There were 160 cases of ovarian cancer reported during the 8.1 years of the study’s intervention phase, with statistically significant fewer new cases of ovarian cancer identified among the dietary change participants than usual diet participants. For the equivalent of every 100,000 low-fat dietary change participants per year there were 36 cases of ovarian cancer diagnosed, compared to 43 cases among usual diet participants. After the first four years of the study, there was a statistically significant 40% risk reduction in ovarian cancer among participants in the low-fat dietary change group compared to the usual diet group. The greatest reduction in cases was among dietary change participants who started with higher intakes of total fat as a percentage of calories and made the greatest reductions in fat intake. The reduced risk of ovarian cancer among the dietary change group compared to the usual diet group did not appear to be effected by the modest weight loss experienced by the dietary change group or by family history of ovarian cancer.

ABBREVIATIONS: CHD, coronary heart disease; CI, confidence interval; CVD, cardiovascular disease; d, day; R, hazard ratio; SD, standard deviation.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

TABLE C-3 Publications on Women’s Health Initiative Estrogen-Alone Triala

Main Findings

Anderson et al., 2004

“Estimated hazard ratios (HRs) (95% confidence intervals [CIs]) for CEE [conjugated equine estrogen] vs placebo for the major clinical outcomes available through February 29, 2004 (average follow-up 6.8 years), were: CHD [coronary heart disease], 0.91 (0.75–1.12) with 376 cases; breast cancer, 0.77 (0.59–1.01) with 218 cases; stroke, 1.39 (1.10–1.77) with 276 cases; PE [pulmonary embolism], 1.34 (0.87–2.06) with 85 cases; colorectal cancer, 1.08 (0.75–1.55) with 119 cases; and hip fracture, 0.61 (0.41–0.91) with 102 cases. Corresponding results for composite outcomes were: total cardiovascular disease, 1.12 (1.01–1.24); total cancer, 0.93 (0.81–1.07); total fractures, 0.70 (0.63–0.79); total mortality, 1.04 (0.88–1.22), and the global index, 1.01 (0.91–1.12). For the outcomes significantly affected by CEE, there was an absolute excess risk of 12 additional strokes per 10000 person-years and an absolute risk reduction of 6 fewer hip fractures per 10000 person-years. The estimated excess risk for all monitored events in the global index was a non-significant 2 events per 10,000 person-years.”

Breast Cancer and Abnormal Mammograms

Stefanick et al., 2006

“After a mean (SD) follow-up of 7.1 (1.6) years, the invasive breast cancer hazard ratio (HR) for women assigned to CEE vs placebo was 0.80 (95% confidence interval [CI], 0.62–1.04; P = .09) with annualized rates of 0.28% (104 cases in the CEE group) and 0.34% (133 cases in the placebo group). In exploratory analyses, ductal carcinomas (HR, 0.71; 95% CI, 0.52–0.99) were reduced in the CEE group vs placebo group; however, the test for interaction by tumor type was not significant (P = .054). At 1 year, 9.2% of women in the CEE group had mammograms with abnormalities requiring follow-up vs 5.5% in the placebo group (P < .001), a pattern that continued through the trial to reach a cumulative percentage of 36.2% vs 28.1%, respectively (P < .001); however, this difference was primarily in assessments requiring short interval follow-up.”

Cognitive Impairment and Dementiab

Shumaker et al., 2004

The results from the CEE part of WHIMS (n = 2,947, only women 65 to 79 years old enrolled) showed that 76 women in the CEE group developed mild cognitive impairment compared to 58 women in the placebo group.

CEE participants tested slightly worse over time on yearly cognitive function questions, although the differences were small. The greatest cognitive decline was seen in women who had lower cognitive function when WHIMS began.

Women taking CEE appeared to be at somewhat higher risk for developing dementia than those taking placebo. 47 women in WHIMS were found to have probable dementia—28 were taking CEE and 19 were taking placebo pills. An analysis of both CEE and CEE plus MPA (estrogen plus progestin) together showed that more women taking active hormones developed either dementia or mild cognitive impairment.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Coronary-Artery Calcification

Manson et al., 2007

Cardiac CT (computed tomography) scans were used to measure CAC in 1,064 participants in the estrogen-alone trial at 28 of 40 WHI centers an average of 8.7 years after joining (7.4 years after they started study pills and 1.3 years after study pills were stopped). CAC scores were lower in women in the CEE estrogen group compared to those in the placebo group. The mean CAC score was 83.1 for CEE and 123.1 for placebo. After taking into account other heart disease risk factors, the risk of having mild-to-moderate CAC was 20–30% lower and the risk of severe CAC was 40% lower in the CEE group compared to placebo. Among only women who were taking their study pills regularly (at least 80% of the time), the risk of mild-to-moderate CAC was 40–50% lower and the risk of severe CAC was 60% lower in the CEE group compared to placebo.

Diabetes

Bonds et al., 2006

“The cumulative incidence of treated diabetes was 8.3% in the oestrogen-alone group and 9.3% in the placebo group (hazard ratio 0.88, 95% CI 0.77–1.01, p=0.072). During the first year of follow-up, a significant fall in insulin resistance (homeostasis model assessment of insulin resistance) in actively treated women compared with the control subjects (Year 1 baseline between-group difference −00.53) as seen. However, there was no difference in insulin resistance at the 3- or 6-year follow-up.”

aNIH stopped the estrogen alone trial ahead of schedule in February 2004 primarily because of an increase in stroke risk in women taking study pills with estrogen alone.

bConducted as part of the Women’s Health Initiative Memory Study (WHIMS), an ancillary study to the WHI that included women 65 years old and older.

ABBREVIATIONS: CAC, coronary artery calcification; CEE, conjugated equine estrogen; CHD, coronary heart disease; CI, confidence interval; CT, computed tomography; HR, hazard ratio; MPA, medroxyprogesterone acetate; PE, pulmonary embolism; SD, standard deviation; WHIMS, Women’s Health Initiative Memory Study.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

TABLE C-4 Publications on Women’s Health Initiative Estrogen-Plus-Progestin Trial

Main Findings

Rossouw et al., 2002

“Estimated hazard ratios (HRs) (nominal 95% confidence intervals [CIs]) were as follows: CHD [coronary heart disease], 1.29 (1.02–1.63) with 286 cases; breast cancer, 1.26 (1.00–1.59) with 290 cases; stroke, 1.41 (1.07–1.85) with 212 cases; PE [pulmonary embolism], 2.13 (1.39–3.25) with 101 cases; colorectal cancer, 0.63 (0.43–0.92) with 112 cases; endometrial cancer, 0.83 (0.47–1.47) with 47 cases; hip fracture, 0.66 (0.45–0.98) with 106 cases; and death due to other causes, 0.92 (0.74–1.14) with 331 cases. Corresponding HRs (nominal 95% CIs) for composite outcomes were 1.22 (1.09–1.36) for total cardiovascular disease (arterial and venous disease), 1.03 (0.90–1.17) for total cancer, 0.76 (0.69–0.85) for combined fractures, 0.98 (0.82–1.18) for total mortality, and 1.15 (1.03–1.28) for the global index.

Absolute excess risks per 10,000 person-years attributable to estrogen plus progestin were 7 more CHD events, 8 more strokes, 8 more PE [pulmonary embolisms], and 8 more invasive breast cancers, while absolute risk reductions per 10,000 person-years were 6 fewer colorectal cancers and 5 fewer hip fractures. The absolute excess risk of events included in the global index was 19 per 10,000 person-years.”

3-Year Followup After Discontinuing Estrogen Plus Progestin

Heiss et al., 2008

“The risk of cardiovascular events after the intervention was comparable by initial randomized assignments, 1.97% (annualized rate) in the CEE plus MPA (343 events) and 1.91% in the placebo group (323 events). A greater risk of malignancies occurred in the CEE plus MPA than in the placebo group (1.56% [n = 281] vs 1.26% [n = 218]; hazard ratio [HR], 1.24; 95% confidence interval [CI], 1.04–1.48). More breast cancers were diagnosed in women who had been randomly assigned to receive CEE plus MPA vs placebo (0.42% [n = 79] vs 0.33% [n = 60]; HR, 1.27; 95% CI, 0.91–1.78) with a modest trend toward a lower HR during the follow-up after the intervention. All-cause mortality was somewhat higher in the CEE plus MPA than in the placebo group (1.20% [n = 233] vs 1.06% [n = 196]; HR, 1.15; 95% CI, 0.95–1.39). The global index of risks and benefits was unchanged from randomization through March 31, 2005 (HR, 1.12; 95% CI, 1.03–1.21), indicating that the risks of CEE plus MPA exceed the benefits for chronic disease prevention.”

Abnormal Mammograms and Breast Biopsies

Chlebowski et al., 2008

“Mammograms showing abnormal results were more common among women taking hormones than among women taking placebo (35% vs 23%). Women taking hormones had a 4% greater risk of having a mammogram with abnormalities after one year of starting the hormones and an 11% greater risk after five years. After the hormones were stopped, the adverse effect on mammograms decreased somewhat, but remained significantly different from that of placebo for at least 12 months after stopping.”

“Breast biopsies also were more common among women taking hormones than among those taking placebo (10% vs 6.1%). Breast cancers were significantly increased and were diagnosed at higher stages in the estrogen plus progestin group than in the placebo group; however, biopsies in the estrogen plus progestin group were less frequently diagnosed as cancer (14.8% vs 19.6%).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Cognitive Functioning and Dementiaa

Rapp et al., 2003

“A total of 4,381 participants provided at least 1 valid cognitive function score between June 1995 and July 8, 2002. …The mean total scores in both groups increased slightly over time (mean follow-up of 4.2 years). Women in the estrogen plus progestin group had smaller average increases in total scores compared with women receiving placebo (P = .03), but these differences were not clinically important. Removing women by censoring them after adjudicated dementia, mild cognitive impairment, or stroke, and nonadherence to study protocol, did not alter the findings. Prior hormone therapy use and duration of prior use did not affect the interpretation of the results, nor did timing of prior hormone therapy initiation with respect to the final menstrual period. More women in the estrogen plus progestin group had a substantial and clinically important decline (≥ 2 SDs) in total score (6.7%) compared with the placebo group (4.8%) (P = .008).”

Shumaker et al., 2004

Over an average of 4.05 years, 61 women were diagnosed with probable dementia, 40 (66%) in the estrogen plus progestin group compared with 21 (34%) in the placebo group. The hazard ratio (HR) for probable dementia was 2.05 (95% confidence interval [CI], 1.21–3.48; 45 vs 22 per 10,000 person-years; P = 0.01). This increased risk would result in an additional 23 cases of dementia per 10,000 women per year. Alzheimer disease was the most common classification of dementia in both study groups. Treatment effects on mild cognitive impairment did not differ between groups (HR, 1.07; 95% CI, 0.74–1.55; 63 vs 59 cases per 10,000 person-years; P = 0.72).

Diabetes

Margolis et al., 2004

After an average of 5.6 years, 277 of the 8,014 women in the intervention group (3.5%) and 324 of the 7,627 women taking placebo (4.2%) developed treated diabetes. This difference was not significant. Estrogen plus progestin produced a small decrease in glucose (blood sugar) and insulin levels in the blood and slightly reduced weight and waist size after one year in the study. Weight was not a major factor in the lower diabetes rate.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Gynecologic Cancers

Anderson et al., 2003

“In 5.6 years of follow-up, there were 32 cases of invasive ovarian cancer, 58 cases of endometrial cancer, 1 case of nonendometrial uterine cancer, 13 cases of cervical cancer, and 7 cases of other gynecologic cancers.” Women randomized to combined estrogen plus progestin experienced a 19% decrease in endometrial cancer rates and 58% increase in ovarian cancer rates. “The hazard ratio (HR) for invasive ovarian cancer in women assigned to estrogen plus progestin compared with placebo was 1.58 (95% confidence interval [CI], 0.77–3.24). The HR for endometrial cancer was 0.81 (95% CI, 0.48–1.36). No appreciable differences were found in the distributions of tumor histology, stage, or grade for either cancer site. The incidence of other gynecologic cancers was low and did not differ by randomization assignment. More women taking estrogen plus progestin required endometrial biopsies (33% vs 6%; P < .001).”

Lung Cancer

Chlebowski et al., 2009

In a secondary analyses of the placebo-controlled trial of daily estrogen plus progestin in 16,608 multi-ethnic postmenopausal women, cumulative risk for lung cancer was highest in current (0.51%), compared to past (0.14%) and never (0.04%), smokers. After 5.6 years on trial intervention and 2.4 years additional follow-up (median), small cell lung cancer incidence was comparable between randomization groups (total n = 26), as was subsequent small cell lung cancer mortality. Although a trend for more non-small cell lung cancer (NSCLC) diagnoses in the active hormone group was not significant (p = 0.12), an apparent divergence emerged after five years, with more diagnoses in the CEE + MPA group. In addition, mortality after NSCLC diagnosis was significantly higher for the CEE + MPA group (46.3% vs 27.0%, respectively, hazard ratio (HR) 1.59, 95% CI 1.03–2.46, p = 0.04). As a result, CEE + MPA group women were more likely to die from NSCLC than those on placebo (p = 0.02).

Peripheral Arterial Disease

Hsia et al., 2004

“The incidence of peripheral arterial events did not differ between treatment groups (hazard ratio [HR] 0.89, 95% confidence interval 0.63, 1.25). The risk was slightly greater among women assigned to active estrogen with progestin in years 1 (HR 1.33) and 2 (HR 1.27), and was slightly lower in later years (HR 0.85 and 0.87 in years 5 and ≥ 6). Among adherent participants, the hazard ratio for peripheral arterial events was 1.23 (95% confidence interval 0.79, 1.91) over the 5.6 years of follow up. Subgroup analysis identified no significant interactions between estrogen with progestin and baseline characteristics with regard to peripheral arterial disease risk.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Quality of Life

Hays et al., 2003

“Quality-of-life measures were collected at base line and at one year in all women and at three years in a subgroup of 1,511 women. Randomization to estrogen plus progestin resulted in no significant effects on general health, vitality, mental health, depressive symptoms, or sexual satisfaction. The use of estrogen plus progestin was associated with a statistically significant but small and not clinically meaningful benefit in terms of sleep disturbance, physical functioning, and bodily pain after one year (the mean benefit in terms of sleep disturbance was 0.4 point on a 20-point scale, in terms of physical functioning 0.8 point on a 100-point scale, and in terms of pain 1.9 points on a 100-point scale). At three years, there were no significant benefits in terms of any quality-of-life outcomes. Among women 50 to 54 years of age with moderate-to-severe vasomotor symptoms at base line, estrogen and progestin improved vasomotor symptoms and resulted in a small benefit in terms of sleep disturbance but no benefit in terms of the other quality-of-life outcomes.”

Symptoms After Discontinuing Estrogen Plus Progestin

Ockene et al., 2005

“Respondents’ mean (SD) age at trial stop date was 69.1 (6.7) years. They averaged 5.7 years of taking study pills. Moderate or severe vasomotor symptoms after discontinuing study pill use were reported by 21.2% of former CEE + MPA and 4.8% of placebo group respondents overall and by 55.5% and 21.3%, respectively, with these symptoms at baseline (randomization). Compared with respondents in the former placebo group, moderate or severe vasomotor symptoms (adjusted odds ratio [AOR] 5.82; 95% confidence interval [CI], 4.92–6.89) and pain or stiffness symptoms (AOR, 2.16; 95% CI, 1.95–2.40) were more likely in respondents in the former CEE + MPA group. Both vasomotor symptoms (AOR, 5.36; 95% CI, 4.51–6.38) and pain or stiffness symptoms (AOR, 3.21; 95% CI, 2.90–3.56) also were more likely in women with these symptoms at baseline. Women reported a wide range of strategies to manage symptoms.” Very few women started prescription hormones after stopping their study pills.

aConducted as part of the Women’s Health Initiative Memory Study (WHIMS), an ancillary study to the WHI that included women 65 and older.

ABBREVIATIONS: AOR, adjusted odds ratio; CEE, conjugated equine estrogen; CHD, coronary heart disease; CI, confidence interval; HR, hazard ratio; NSCLS, nonsmall–cell lung cancer; PE, pulmonary embolism, SD, standard deviation.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

TABLE C-5 Publications on Combined Analyses of Both Women’s Health Initiative Hormone Trials

Brain and Brain Ischemic Lesion Volume

Resnick et al., 2009

“Brain MRI scans were obtained in a subset of 1,403 women aged 71–89 years who participated in the Women’s Health Initiative Memory Study (WHIMS).” Women who had been assigned to take the hormone therapies had slightly smaller brains than those who had been assigned to take placebo. For most women, the amount of brain loss was small and would not be expected to noticeably affect memory or thinking. “Compared with placebo, covariate-adjusted mean frontal lobe volume was 2.37 cm3 lower among women assigned to HT (p = 0.004), mean hippocampal volume was slightly (0.10 cm3) lower (p = 0.05), and differences in total brain volume approached significance (p = 0.07). Results were similar for CEE + MPA and CEE-Alone. HT-associated reductions in hippocampal volumes were greatest in women with the lowest baseline Modified Mini-Mental State Examination scores (scores < 90).”

Coker et al., 2009

Brain MRI scans were obtained in a subset of 1,403 women aged 71–89 years who participated in the Women’s Health Initiative Memory Study. “Increased lesion volumes were significantly related to age, smoking, history of cardiovascular disease, hypertension, lower post-trial global cognition scores, and increased incident cases of on- or post-trial mild cognitive impairment or probable dementia. Mean ischemic lesion volumes were slightly larger for the CEE + MPA group vs placebo, except for the basal ganglia, but the differences were not significant. Women assigned to CEE-Alone had similar mean ischemic lesion volumes compared to placebo.”

Cardiovascular Disease

Rossouw et al., 2007

“In the combined trials, there were 396 cases of CHD and 327 cases of stroke in the hormone therapy group vs 370 [corrected] cases of CHD and 239 cases of stroke in the placebo group. For women with less than 10 years since menopause began, the hazard ratio (HR) for CHD was 0.76 (95% confidence interval [CI], 0.50–1.16); 10 to 19 years, 1.10 (95% CI, 0.84–1.45); and 20 or more years, 1.28 (95% CI, 1.03–1.58) (P for trend = .02). The estimated absolute excess risk for CHD for women within 10 years of menopause was –6 per 10,000 person-years; for women 10 to 19 years since menopause began, 4 per 10,000 person-years; and for women 20 or more years from menopause onset, 17 per 10,000 person-years. For the age group of 50 to 59 years, the HR for CHD was 0.93 (95% CI, 0.65–1.33) and the absolute excess risk was –2 per 10,000 person-years; 60 to 69 years, 0.98 (95% CI, 0.79–1.21) and –1 per 10,000 person-years; and 70 to 79 years, 1.26 (95% CI, 1.00–1.59) and 19 per 10,000 person-years (P for trend = .16). Hormone therapy increased the risk of stroke (HR, 1.32; 95% CI, 1.12–1.56). Risk did not vary significantly by age or time since menopause. There was a nonsignificant tendency for the effects of hormone therapy on total mortality to be more favorable in younger than older women (HR of 0.70 for 50–59 years; 1.05 for 60–69 years, and 1.14 for 70–79 years; P for trend = .06).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Urinary Incontinence (UI)

Hendrix et al., 2005

“Menopausal hormone therapy increased the incidence of all types of UI at 1 year among women who were continent at baseline. The risk was highest for stress UI (CEE + MPA: relative risk [RR], 1.87 [95% confidence interval (CI), 1.61–2.18]; CEE alone: RR, 2.15 [95% CI, 1.77–2.62]), followed by mixed UI (CEE + MPA: RR, 1.49 [95% CI, 1.10–2.01]; CEE alone: RR, 1.79 [95% CI, 1.26–2.53]). The combination of CEE + MPA had no significant effect on developing urge UI (RR, 1.15; 95% CI, 0.99–1.34), but CEE alone increased the risk (RR, 1.32; 95% CI, 1.10–1.58). Among women experiencing UI at baseline, frequency worsened in both trials (CEE + MPA: RR, 1.38 [95% CI, 1.28–1.49]; CEE alone: RR, 1.47 [95% CI, 1.35–1.61]). Amount of UI worsened at 1 year in both trials (CEE + MPA: RR, 1.20 [95% CI, 1.06–1.36]; CEE alone: RR, 1.59 [95% CI, 1.39–1.82]). Women receiving menopausal hormone therapy were more likely to report that UI limited their daily activities (CEE + MPA: RR, 1.18 [95% CI, 1.06–1.32]; CEE alone: RR, 1.29 [95% CI, 1.15–1.45]) and bothered or disturbed them (CEE + MPA: RR, 1.22 [95% CI, 1.13–1.32]; CEE alone: RR, 1.50 [95% CI, 1.37–1.65]) at 1 year.”

ABBREVIATIONS: CEE, conjugated equine estrogen; CHD, coronary heart disease; CI, confidence interval; HR, hazard ratio; HT, hormone therapy; MPA, medroxyprogesterone acetate; MRI, magnetic resonance imaging; RR, relative risk; UI, urinary incontinence; WHIMS, Women’s Health Initative Memory Study.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

TABLE C-6 Publications on Select Findings of Women’s Health Initiative Observational Study

Alcohol and Folate Intake and Breast Cancer Risk

Duffy et al., 2009

“1,783 breast cancer cases occurred over 5 years. Alcohol was associated with increased risk of breast cancer (RR = 1.005, 95% CI 1.001–1.009). Risk increased with consumption of alcohol (up to 5 g/d, adjusted HR = 1.10, 95%CI 0.96–1.32; > 5–15 g/d HR = 1.14, 95% CI 0.99–1.31; and > 15 g/d HR = 1.13 95% CI 0.96–1.32).” No significant interaction was found between alcohol and folate in an adjusted model.

Breast Cancer and Body Weight

Morimoto et al., 2002

“Anthropometric factors were not associated with breast cancer among women who had ever used hormone replacement therapy (HRT). Among HRT non-users, heavier women (baseline body mass index (BMI) > 31.1) had an elevated risk of postmenopausal breast cancer (relative risk (RR) = 2.52; 95% confidence interval (CI) = 1.62–3.93), compared to slimmer women (baseline BMI < 22.6). The elevation in risk associated with increasing BMI appeared to be most pronounced among younger postmenopausal women. Change in BMI since age 18, maximum BMI, and weight were also associated with breast cancer in HRT non-users. While both waist and hip circumference were associated with breast cancer risk, their ratio, a measure of fat distribution, was not (RR = 1.33; 95% CI = 0.88–2.01).”

Breast Cancer and Nonsteroidal Anti-Inflammatory Drugs

Harris et al., 2003

Among 1,392 participants with confirmed cases of breast cancer, “regular NSAID use (two or more tablets/week) for 5–9 years produced a 21% reduction in the incidence of breast cancer (RR, 0.79; 95% CI, 0.60–1.04); regular NSAID use for 10 or more years produced a 28% reduction (RR, 0.72; CI, 0.56–0.91), and there was a statistically significant inverse linear trend of breast cancer incidence with the duration of NSAID use (P < 0.01). The estimated risk reduction for long-term use of ibuprofen (RR, 0.51; CI, 0.28–0.96) was greater than for aspirin (RR, 0.79; CI, 0.60–1.03). Subgroup analysis by breast cancer risk factors did not result in effect modification. Regular use of acetaminophen (an analgesic agent with little or no anti-inflammatory activity) or low-dose aspirin (<100 mg) was unrelated to the incidence of breast cancer.”

Depression and Cardiovascular Sequelae

Wassertheil-Smoller et al., 2004

“Current depressive symptoms above the screening cutoff point were reported by 15.8% of women. Depression was significantly related to CVD risk and comorbidity (odds ratios ranging from 1.12 for hypertension to 1.60 for history of stroke or angina). Among women with no history of CVD, depression was an independent predictor of CVD death (relative risk, 1.50) and all-cause mortality (relative risk, 1.32) after adjustment for age, race, education, income, diabetes, hypertension, smoking, high cholesterol level requiring medication, body mass index, and physical activity. Taking antidepressant medications did not alter the depression-associated risks associated.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Exercise and Coronary Events

Manson et al., 2002

“An increasing physical-activity score had a strong, graded, inverse association with the risk of both coronary events and total cardiovascular events. There were similar findings among white women and black women. Women in increasing quintiles of energy expenditure measured in metabolic equivalents (the MET score) had age-adjusted relative risks of coronary events of 1.00, 0.73, 0.69, 0.68, and 0.47, respectively (P for trend, < 0.001). In multivariate analyses, the inverse gradient between the total MET score and the risk of cardiovascular events remained strong (adjusted relative risks for increasing quintiles, 1.00, 0.89, 0.81, 0.78, and 0.72, respectively; P for trend < 0.001). Walking and vigorous exercise were associated with similar risk reductions, and the results did not vary substantially according to race, age, or body-mass index. A brisker walking pace and fewer hours spent sitting daily also predicted lower risk.”

High Blood Pressure and Its Treatment

Wassertheil-Smoller et al., 2000

“Overall, 37.8% of participants had hypertension, which is defined as systolic blood pressure ≥ 140 mm Hg and/or diastolic blood pressure ≥ 90 mm Hg or being on medication for high blood pressure; 64.3% were treated with drugs, and blood pressure was controlled in only 36.1% of the hypertensive women, with lower rates of control in the oldest group. After adjustment for multiple covariates, current hormone users had higher prevalence than did nonusers (odds ratio 1.25). Hypertensive women had more comorbid conditions than did nonhypertensive women, and women with comorbidities were more likely to be treated pharmacologically. Diuretics were used by 44.3% of hypertensives either as monotherapy or in combination with other drug classes. As monotherapy, calcium channel blockers were used in 16%, angiotensin-converting enzyme inhibitors in 14%, β-blockers in 9%, and diuretics in 14% of the hypertensive women. Diuretics as monotherapy were associated with better blood pressure control than any of the other drug classes as monotherapy.”

Hormone Therapy and Inflammatory, Hemostatic, and Lipid Biomarkers of Coronary Heart Disease

Langer et al., 2005

Postmenopausal hormone therapy (PHT) “was associated with higher CRP, HDL and triglycerides, and lower tPA-antigen and homocysteine. CRP was highest in users of unopposed conjugated equine estrogen. Levels of IL-6, sICAM-1, D-dimer and total cholesterol did not differ between PHT users and non-users. Transdermal estrogen users had low levels of D-dimer and CRP. Among users of estrogen plus progestin (EP), CRP, IL-6, tPA-antigen, D-dimer, total cholesterol and triglycerides were higher in women with incident coronary events than controls. Estrogen alone (E) controls shared only the tPA-antigen association, but had higher HDL and lower LDL than E cases. In non-users CRP, tPA-antigen and D-dimer were associated with incident CHD. In summary, risk markers differed by PHT category. Some associations differed between women with and without incident CHD, especially for EP, where inflammatory and thrombotic markers were higher in cases.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Insurance Coverage and Cancer Screening

Hsia et al., 2000

“Positive determinants of reporting cancer screening were age, ethnic origin, household income, educational level, family history of cancer, having a usual care provider, time since last provider visit, and insurance status and type. Smoking, diabetes, and, among older women, prior cardiovascular events were negative determinants of cancer screening. Among women younger than 65, lacking health insurance or having fee-for-service insurance was strongly associated with failure to report cancer screening, independently of having or using a usual care provider and of demographics, self-perceived health, and health characteristics. Among women 65 and older, those with Medicare alone were less likely, whereas those with Medicare + prepaid insurance were more likely, to report cancer screening.”

Mammography Use

Bush and Langer, 1998

Among post-menopausal women at the San Diego Women’s Health Initiative center, “bivariate analysis indicated that the following factors were all strongly associated with women having had a mammogram in the previous two years: having health insurance, a regular medical provider, an annual household income greater than $20,000, and a high-school diploma, as well as being 65 years or older or white (P < 0.001). Multiple logistic regression analysis demonstrated that, when adjusting for all of these factors, having a medical provider (P < 0.001) was significant. Having insurance (P = 0.04) was suggestive, but did not meet the multiple-comparisons significance cutoff of P = 0.006. After adjusting for the above factors, it was found that ethnicity was not significant.”

Physical Activity and Breast Cancer Risk

McTiernan et al., 2003

“The study documented 1,780 newly diagnosed cases of breast cancer over a mean follow-up of 4.7 years. Compared with less active women, women who engaged in regular strenuous physical activity at age 35 years had a 14% decreased risk of breast cancer (relative risk [RR], 0.86; 95% confidence interval [CI], 0.78–0.95). Similar but attenuated findings were observed for strenuous physical activity at ages 18 years and 50 years. An increasing total current physical activity score was associated with a reduced risk for breast cancer (P = .03 for trend). Women who engaged in the equivalent of 1.25 to 2.5 hours per week of brisk walking had an 18% decreased risk of breast cancer (RR, 0.82; 95% CI, 0.68–0.97) compared with inactive women. Slightly greater reduction in risk was observed for women who engaged in the equivalent of 10 hours or more per week of brisk walking. The effect of exercise was most pronounced in women in the lowest tertile of body mass index (BMI) (< 24.1), but also was observed for women in the middle tertile of BMI (24.1–28.4).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Self-Reported Osteoarthritis, Ethnicity, Body-Mass Index, and Other Associated Risk Factors

Wright et al., 2008

“Forty-four percent of the participants reported OA. Older age (odds ratio (OR)(70–79 vs 50–59) = 2.69, 95% confidence interval (CI) = 2.60–2.78) and higher body mass index (BMI) (OR[BMI ≥ 40.0 vs < 24.9] = 2.80, 95% CI = 2.63–2.99) were found to be the strongest risk factors associated with self-reported OA. The prevalence of obesity (BMI ≥30.0) was 57.9% in African Americans, 51.0% in American Indians, 41.9% in Hispanic whites, and 32.9% in non-Hispanic whites. The prevalence of other major OA risk factors was higher in African-American, American-Indian, and Hispanic white women than in non-Hispanic white women. Non-Hispanic white women who were in the extreme obese category (BMI ≥ 40.0 kg/m(2)) had a 2.80 times (95% CI = 2.63, 2.99) greater odds of self-reported OA. The odds were even higher in American-Indian (OR = 4.22, 95% CI = 1.82, 9.77) and African-American (OR = 3.31, 95% CI = 2.79, 3.91) women, indicating a significant interactive effect of BMI and ethnicity on odds of OA.”

Sleep Habits

Kripke et al., 2001

Among a sample of observational study and clinical trial participants, less than 27 percent of women overall reported sleeping 8 hours or more each night. Women who reported they were retired or unemployed slept only 6 to 12 minutes more than those who were employed. The majority of participants reported waking up several times a night and waking up earlier than planned. Napping increased dramatically in postmenopausal women from age 50–54 to age 75–79, but other sleep symptoms were not strongly age-related. Participants who reported sleeping 9 or 10 hours a night, or 6 hours or less a night, were more obese and more depressed than participants who reported sleeping between 7 and 8 hours a night.

Statin Use, Broken Bones, and Bone Density

LaCroix et al., 2003

“Age-adjusted rates of hip, lower arm or wrist, and other clinical fractures were similar between statin users and nonusers regardless of duration of statin use. The multivariate-adjusted hazard ratios for current statin use were 1.22 (95% CI, 0.83 to 1.81) for hip fracture, 1.04 (CI, 0.85 to 1.27) for lower arm or wrist fracture, and 1.11 (CI, 1.00 to 1.22) for other clinical fracture. Bone density levels did not statistically differ between statin users and nonusers at any skeletal site after adjustment for age, ethnicity, body mass index, and other factors.”

ABBREVIATIONS: β, Beta; BMI, body mass index; CI, confidence interval; CRP, C-reactive protein; CVD, cardiovascular disease; E, estrogen alone; EP, estrogen plus progesterone; g/d, grams/day; HDL, high-density lipoprotein; Hg, mercury; HR, hazard ratio; HRT, hormone replacement therapy; LDL, low-density lipoprotein; MET, metabolic equivalents; NSAID, nonsteroidal anti-inflammatory drug; OA, older age; OR, odds ratio; PHT, postmenopausal hormone therapy; RR, relative risk; tPA, tissue plasminogen activator antigen.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

In the community prevention study, eight university-based prevention centers conducted and evaluated health programs that encouraged women of all races and socioeconomic backgrounds to adopt healthful behaviors, such as improved diet, nutritional supplementation, smoking cessation, exercise, and early detection of treatable health problems. Programs were in the following:

  1. reduction of cardiovascular-disease risk among black women,

  2. environmental and policy interventions to increase physical activity in minority-group women ages 40–75 years old,

  3. peer-support intervention for cardiovascular-disease risk in black women 40 years old and older,

  4. assessment of the effectiveness of a brief medical-provider educational intervention for osteoporosis in minority-group women 40 years old and older,

  5. improvement of the delivery of diabetes care to minority-group women, and

  6. assessment of moderate physical activity in women.

WOMEN’S HEALTH STUDY

Study Objective and Design

The Women’s Health Study (WHS) was a randomized, double-blind, placebo-controlled trial. Its purpose was to evaluate the effects of vitamin E and low-dose aspirin in primary prevention of cardiovascular disease and cancer in apparently healthy women. The primary end point was a reduction in the risk of all important vascular events (a combined end point of nonfatal myocardial infarction, nonfatal stroke, and total cardiovascular death) and a decrease in the incidence of total malignant neoplasms of epithelial-cell origin. Secondary end points were individual components of the combined end points.

The study began in September 1991 and the final data-collection date for the primary outcome measures was March 2009.

The WHS originally had a component to test the effects of beta-carotene. That was terminated in 1996, after an average of 22.8 months of followup, because results from the Physician’s Health Study (which included male physicians) and two other trials indicated no effect (benefit or harm) of long-term supplementation with beta-carotene with respect to the prevention of cancer or cardiovascular disease in the study participants.

Participant Enrollment

From September 1992 to May 1995, about 1.75 million female health professionals were contacted by mail to determine whether they were eligible for

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

the study. Eligible participants were women 45 years old and older who had no history of cardiovascular disease or cancer (other than nonmelanoma skin cancer) or contraindications to aspirin or vitamin E. The women either were postmenopausal or had no intention of becoming pregnant. A 3-month run-in phase was performed to screen out participants whose compliance was poor. Randomization, which began in February 1993 and ended in January 1996, was stratified on 5-year age groups. A total of 39,876 women were randomized into one of the four study arms:

  1. Experimental—vitamin E (600 IU every other day) and aspirin (100 mg every other day)

  2. Active comparator—vitamin E (600 IU every other day) and placebo

  3. Active comparator—placebo and aspirin (100 mg every other day)

  4. Placebo comparator—placebo and placebo

Data Collection

Information on baseline characteristics (such as age, profession, race or ethnicity, smoking, physical activity, and hormone and vitamin use) was ascertained from the baseline and run-in questionnaires. Thereafter, every 6–12 months, participants randomized into the study received a supply of pills in calendar packs containing, on alternate days, white tablets (100 mg of aspirin or placebo) and amber capsules (600 IU of vitamin E or placebo), and a followup questionnaire on compliance, the use of other medications, occurrence of major illnesses or adverse effects, and other risk-factor information. A baseline food-frequency questionnaire was completed and returned by 39,345 of the randomized participants.

Prerandomization blood samples from 28,345 women were frozen and stored for genetic analysis. Study investigators planned to use the blood to develop improved prediction scores for total and specific cardiovascular-disease outcomes based not only on traditional risk factors but on novel plasma and genetic markers. They also planned to develop prediction scores for health conditions that are major cardiovascular-disease risk factors (including type-2 diabetes, hypertension, and the metabolic syndrome) and to evaluate genotype–phenotype interactions and interactions between traditional and novel cardiovascular-disease risk factors in the prediction of cardiovascular-disease events.

Findings

The findings from the WHS are summarized in Tables C-7 and C-8.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

TABLE C-7 Publications on Main Findings of the Women’s Health Study

Low-Dose Aspirin

Cook et al., 2005

Cancer: During more than 10 years followup, a total of 2,865 cases of invasive cancer were confirmed. “Of these, 1,230 were breast cancer (43 percent), 269 were colorectal cancer (nine percent), and 205 were lung cancer (seven percent) with no statistically significant difference in occurrences between the aspirin and placebo groups except for a trend towards reduction in lung cancer in the active aspirin group.”

Cardiovascular Disease: “Regular, low-dose aspirin therapy reduced the risk of stroke by 17 percent, but did not decrease heart attacks or cardiovascular deaths among all women. However, in a subgroup of women 65 years and older, aspirin did reduce the risks of developing overall cardiovascular disease, ischemic stroke, and heart attack.”

Vitamin E

Lee et al., 2005

Cancer: “There was no significant effect on the incidences of total cancer (1,437 cases in the vitamin E group and 1,428 in the placebo group; RR, 1.01; 95% CI, 0.94–1.08; P = .87) or breast (RR, 1.00; 95% CI, 0.90–1.12; P = .95), lung (RR, 1.09; 95% CI, 0.83–1.44; P = .52), or colon cancers (RR, 1.00; 95% CI, 0.77–1.31; P = .99). Cancer deaths did not differ significantly between groups”

Cardiovascular Disease: “During follow-up, there were 482 major cardiovascular events in the vitamin E group and 517 in the placebo group, a nonsignificant 7% risk reduction (relative risk [RR], 0.93; 95% confidence interval [CI], 0.82–1.05; P = .26). There were no significant effects on the incidences of myocardial infarction (RR, 1.01; 95% CI, 0.82–1.23; P = .96) or stroke (RR, 0.98; 95% CI, 0.82–1.17; P = .82), as well as ischemic or hemorrhagic stroke. For cardiovascular death, there was a significant 24% reduction (RR, 0.76; 95% CI, 0.59–0.98; P = .03).

ABBREVIATIONS: CI, confidence interval; RR, relative risk.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

TABLE C-8 Publications on Findings of the Women’s Health Study by Outcome

Atrial Fibrillation (AF)

Conen et al., 2009

“A total of 34,221 women in the Women’s Health Study were prospectively followed up for incident AF. … During 12.4 years of follow-up, 644 incident AF events occurred. Using BP measurements at baseline, we discovered that the long-term risk of AF was significantly increased across categories of systolic and diastolic BP. Multivariable-adjusted hazard ratios for systolic BP categories (< 120, 120 to 129, 130 to 139, 140 to 159, and ≥ 160 mm Hg) were 1.0, 1.00 (95% CI, 0.78 to 1.28), 1.28 (95% CI, 1.00 to 1.63), 1.56 (95% CI, 1.22 to 2.01), and 2.74 (95% CI, 1.77 to 4.22) (P for trend < 0.0001). Adjusted hazard ratios across baseline diastolic BP categories (< 65, 65 to 74, 75 to 84, 85 to 89, 90 to 94, and ≥ 95 mm Hg) were 1.0, 1.17 (95% CI, 0.81 to 1.69), 1.18 (95% CI, 0.84 to 1.65), 1.53 (95% CI, 1.05 to 2.23), 1.35 (95% CI, 0.82 to 2.22), and 2.15 (95% CI, 1.21 to 3.84) (P for trend = 0.004). When BP changes over time were accounted for in updated models, multivariable-adjusted hazard ratios were 1.0, 1.14 (95% CI, 0.89 to 1.46), 1.37 (95% CI, 1.07 to 1.76), 1.71 (95% CI, 1.33 to 2.21), and 2.21 (95% CI, 1.45 to 3.36) (P for trend < 0.0001) for systolic BP categories and 1.0, 1.12 (95% CI, 0.82 to 1.52), 1.13 (95% CI, 0.83 to 1.52), 1.30 (95% CI, 0.89 to 1.88), 1.50 (95% CI, 1.01 to 1.88), and 1.54 (95% CI, 0.75 to 3.14) (P for trend = 0.026) for diastolic BP categories.”

Breast Cancer

Estrogen + Progestin Hormone Replacement Therapy and Breast Cancer

Porch et al., 2002

Breast cancer occurred in 411 of 17,835 postmenopausal women followed for an average of 5.9 years. “The multivariate relative risks of all breast cancer associated with never use of PMH, use of estrogen replacement therapy (ERT), and use of estrogen-progestin replacement therapy (HRT) were 1.00 (referent), 0.96 (95% CI 0.65–1.42), and 1.37 (95% CI 1.05–1.78). The increase in risk among users of HRT was largely limited to those women who had used estrogen-progestin replacement therapy for five years or more, and to those women who were on continuous rather than cyclic progestin combinations. Higher doses of estrogen, but not progestin, were associated with increased breast cancer risk, compared with lower doses.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Glycemic Load and Breast Cancer

Higginbotham et al., 2004a

“During a mean of 6.8 years of follow-up there were 946 confirmed cases of breast cancer” among 39,876 women. The authors “found no association between dietary GL [multivariable-adjusted relative risk (RR), 1.01; confidence interval (CI), 0.76–1.35, comparing extreme quintiles; P for trend = 0.96] or overall GI (corresponding RR, 1.03; CI, 0.84–1.28; P for trend = 0.66) and breast cancer risk in the cohort as a whole. Exploratory analyses stratified by baseline measurements of menopausal status, physical activity, smoking history, alcohol use, and history of diabetes mellitus, hypertension, or hypercholesterolemia showed no significant associations, except in the subgroup of women who were premenopausal and reported low levels of physical activity (GL multivariable-adjusted RR, 2.35; CI, 1.03–5.37; P for trend = 0.07; GI multivariable-adjusted RR, 1.56; CI, 0.88–2.78; P for trend = 0.02, comparing extreme quintiles).”

Lifetime Physical Activity and Breast Cancer

Lee et al., 2001a

Included 394 women with breast cancer and 788 control women. “After controlling for potential confounders, the odds ratios (95% confidence intervals) for increasing quartiles of lifetime physical activity were 1.00 (referent), 0.91 (0.60–1.37), 0.91 (0.60–1.39), and 1.10 (0.73–1.67), respectively; P, trend = 0.47. We also separately examined physical activity at ages 12–18, 19–34, 35–49 and ≥50 years; no significant trends were observed in any age group. These data do not support a role of physical activity in preventing breast cancer.”

Physical Activity and Breast Cancer

Lee et al., 2001b

Among 39,322 women followed for an average of 48 months, 411 “women developed breast cancer, with 222 positive for both estrogen and progesterone receptors. Among all women the multivariate relative risks of all breast cancer associated with < 840, 840–2519, 2520–6299, and ≥ 6300 kJ/week expended on recreational activities and stair climbing were 1.00 (referent), 1.04 (95% confidence interval, 0.77–1.40), 0.86 (0.64–1.17), and 0.80 (0.58–1.12), respectively; p-trend = 0.11. However, among postmenopausal women there was a significant inverse trend for all breast cancer; the corresponding relative risks were 1.0 (referent), 0.97 (0.68–1.4), 0.78 (0.54–1.1), and 0.67 (0.44–1.0), respectively; p-trend = 0.03. Physical activity was unrelated to breast cancers positive for both estrogen and progesterone receptors either among all or postmenopausal women (p-trend = 0.50 and 0.26, respectively). When we assessed only vigorous recreational activity, requiring ≥6 METs or multiples of resting metabolic rate, we observed no significant associations with all or steroid hormone receptor positive breast cancer, either among all or postmenospausal women.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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C-Reactive Protein

Alcohol and High-Sensitivity C-Reactive Protein

Levitan et al., 2005

“Plasma concentrations of hs-CRP were measured in 11,815 participants in the WHS who had never used postmenopausal hormones…. Alcohol consumption had an inverse association with geometric mean hs-CRP concentrations (nondrinkers 1.43 mg/L, 0.1 to 6 g alcohol/day 1.37 mg/L, 6.1 to 12 g alcohol/day 1.29 mg/L, > 12 g alcohol/day 1.28 mg/L, p for trend = 0.003). In age-adjusted analyses, beverage preference was a significant predictor of geometric mean hs-CRP concentration. However, after adjustment for body mass index (BMI), beer drinkers who consumed 6.1 to 12 g alcohol/day had a geometric mean hs-CRP concentration of 1.03 mg/L, wine drinkers 1.09 mg/L, liquor drinkers 1.28 mg/L, and combination drinkers 1.09 mg/L (p = 0.43). The association between alcohol and hs-CRP concentration appears to be mediated primarily by ethanol and was independent of the type of alcoholic beverage consumed once BMI was taken into account.”

C-Reactive Protein Levels in Various Ethnic Groups

Albert et al., 2004

“The distribution of C-reactive protein (CRP) levels was compared among 24,455 white, 475 black, 357 Asian, and 254 Hispanic Women’s Health Study participants. Median CRP levels were significantly higher among black women (2.96 mg/L, interquartile range [IQR] 1.19 to 5.86) than among their white (2.02 mg/L, IQR 0.81 to 4.37), Hispanic (2.06 mg/L, IQR 0.88 to 4.88), and Asian (1.12 mg/L, IQR 0.48 to 2.25) counterparts. As expected, women taking hormone replacement therapy had higher baseline CRP levels than women not taking hormone replacement therapy. No differences in low-density lipoprotein cholesterol or total cholesterol levels were observed between ethnic groups. In multivariate regression models, body mass index was a significant (p <0.001) predictor of elevated CRP concentrations among all race/ethnic groups, and control for body mass index substantially attenuated the differences noted in CRP levels across race/ethnic groups, particularly among black women. Control for all measured modifiable risk factors for cardiovascular disease did not entirely explain CRP differences. Among these women, the distribution of CRP levels varied significantly between the various race/ethnic groups.

Clinical Usefulness of Very High or Low C-Reactive Protein Concentrations Across Range of Framingham Risk Scores

Ridker and Cook, 2004

“Baseline levels of hsCRP were evaluated among 27,939 women who were followed up for myocardial infarction, stroke, coronary revascularization, or cardiovascular death. Crude and Framingham Risk Score (FRS)-adjusted relative risks (RRs) of incident cardiovascular events were calculated across a full range of hsCRP levels. Cardiovascular risks increased linearly from the very lowest (referent) to the very highest levels of hsCRP. Crude RRs for those with baseline hsCRP levels of < 0.5, 0.5 to < 1.0, 1.0 to < 2.0, 2.0 to < 3.0, 3.0 to < 4.0, 4.0 to < 5.0, 5.0 to < 10.0, 10.0 to < 20.0, and ≥ 20.0 mg/L were 1.0, 2.2, 2.5, 3.1, 3.7, 4.2, 4.9, 6.3, and 7.6, respectively (P for trend < 0.001). After adjustment for FRS, these risks were 1.0, 1.6, 1.6, 1.7, 1.9, 2.2, 2.3, 2.8, and 3.1 (P for trend < 0.001). All risk estimates remained significant in analyses stratified by FRS and after control for diabetes. Of the total cohort, 15.1% had hsCRP <0.50 mg/L, and 5.4% had hsCRP >10.0 mg/L.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Glycemic Load and High-Sensitivity C-Reactive Protein

Liu et al., 2002b

In 244 women, the authors “found a strong and statistically significant positive association between dietary glycemic load and plasma hs-CRP. The median hs-CRP concentration for the lowest quintile of dietary glycemic load was 1.9 mg/L and for the highest quintile was 3.7 mg/L; corresponding multivariate-adjusted geometric means were 1.4 and 3.8 mg/L, respectively (P for trend < 0.01). This association was significantly modified by BMI. Among women with a BMI ≥ 25, the multivariate-adjusted geometric mean hs-CRP concentration in the lowest quintile was 1.6 mg/L and in the highest quintile was 5.0 mg/L; however, among women with a BMI < 25, the corresponding means were 1.1 and 3.1 mg/L, respectively (P = 0.01 for interaction).”

Hormone Replacement Therapy and Plasma C-Reactive Protein

Ridker et al., 1999c

“CRP levels were evaluated in a cross-sectional survey of 493 healthy postmenopausal women; mean age was 51 years. Overall, median CRP levels were 2 times higher among women taking HRT than among women not taking HRT (0.27 versus 0.14 mg/dL; P = 0.001). This difference was present in all subgroups evaluated, including those with no history of hypertension, hyperlipidemia, obesity, diabetes, or cigarette consumption or a family history of premature coronary artery disease (all P< 0.01). Compared with nonusers of HRT, median CRP levels were higher among women using estrogen alone (P = 0.003) and women using estrogen plus progesterone (P = 0.03); however, there was no significant difference in CRP levels between users of different HRT preparations. In multivariate analysis, the relationship between HRT use and CRP remained significant after control for body mass index, age, diabetes, hypertension, hyperlipidemia, alcohol use, and cigarette consumption (P = 0.001).”

Sex Hormone-Binding Globulin and Serum Testosterone and C-Reactive Protein Concentrations

Joffe et al., 2006

C-reactive protein (CRP), sex hormone-binding globulin (SHBG), estradiol, and total testosterone were measured using baseline bloods of 221 hormone therapy (HT)-nonusers and 162 HT-users from a cross-sectional analysis in a nested case-control sample of the WHS. ln-SHBG (beta = –0.40; p < 0.01) and ln-testosterone (beta = –0.24; p = 0.04) were the only independent hormonal predictors of ln-CRP among HT-nonusers after adjusting for age, hypertension, smoking, body mass index, diabetes, exercise, HDL cholesterol, alcohol intake, and CVD occurrence during follow-up. Upon stratification, the association between ln-SHBG and ln-CRP persisted among HT nonusers who subsequently developed CVD (beta = –0.55; p = 0.01), but not among women who remained CVD-free (p = 0.28). The inverse relationship between ln-SHBG and ln-CRP was strongest among the leanest women. None of the sex-hormones predicted ln-CRP among HT-users.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Total and Abdominal Adiposity and C-Reactive Protein and Interleukin-6

Rexrode et al., 2003b

In a sample of 733 women in WHS, “BMI, WHR, and WC were all significantly correlated with C-reactive protein (CRP) and IL-6, throughout the anthropometric spectrum. After adjustment for risk factors, the odds ratios (ORs) were 12.2 (95% CI, 6.44–23.0) for elevated CRP (≥ 75th percentile) and 4.13 (95% CI, 2.37–7.18) for elevated IL-6 (≥ 75th percentile) in comparisons of extreme BMI quartiles. Among women in the highest WC quartile, the OR for elevated CRP and IL-6 were 8.57 (95% CI, 4.59–16.0) and 4.40 (95% CI, 2.46–7.89), while ORs for the highest WHR quartile were 2.88 (95% CI, 1.60–5.19) and 1.76 (95% CI, 1.03–3.01), respectively. Compared with lean nonusers, women in the highest BMI quartile who did not use hormone therapy (HT) had an OR for elevated CRP of 7.79 (95% CI, 2.08–29.2) vs 31.6 (95% CI, 7.97–125.6) for current hormone users.”

Cancer (All Sites)

Low-Dose Aspirin and Cancer

Cook et al., 2005

In 39,876 women “without previous history of cancer, cardiovascular disease, or other major chronic illness followed up for an average of 10.1 years. … No effect of aspirin was observed on total cancer (n = 2,865; relative risk [RR], 1.01; 95% confidence interval [CI], 0.94–1.08; P = .87), breast cancer (n = 1,230; RR, 0.98; 95% CI, 0.87–1.09; P = .68), colorectal cancer (n = 269; RR, 0.97; 95% CI, 0.77–1.24; P = .83), or cancer of any other site, with the exception of lung cancer for which there was a trend toward reduction in risk (n = 205; RR, 0.78; 95% CI, 0.59–1.03; P = .08). There was also no reduction in cancer mortality either overall (n = 583; RR, 0.95; 95% CI, 0.81–1.11; P = .51) or by site, except for lung cancer mortality (n = 140; RR, 0.70; 95% CI, 0.50–0.99; P = .04). No evidence of differential effects of aspirin by follow-up time or interaction with vitamin E was found.”

Cancer and Cardiovascular Disease

Beta-Carotene and Cancer and Cardiovascular Disease

Lee et al., 1999

Among women randomly assigned to receive beta-carotene (50 mg on alternate days; n = 19 939) or placebo (n = 19 937), there were no statistically significant differences in incidence of cancer, cardiovascular disease, or total mortality after a median of 4.1 years (2.1 years’ treatment plus another 2.0 years’ followup). There were 378 cancers in the beta-carotene group and 369 cancers in the placebo group (relative risk [RR] = 1.03; 95% confidence interval [CI] = 0.89–1. 18). There were no statistically significant differences for any site-specific cancer or during years 1 and 2 combined and years 3 and up combined. For cardiovascular disease, there were no statistically significant differences for myocardial infarction (42 in the beta-carotene group versus 50 in the placebo group), stroke (61 versus 43), deaths from cardiovascular causes (14 versus 12), or the combined end point of these three events (116 versus 102; among women with more than one event, only the first was counted). Deaths from any cause were similar in the two groups (59 versus 55). Among smokers at baseline (13% of all women), there were no statistically significant differences in overall incidence of cancer (RR = 1.11; 95% CI = 0.78–1.58) or cardiovascular disease (RR = 1.01; 95% CI = 0. 62–1.63).

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Lee et al., 2002

“In a nested case–control study of 513 women with cancer; 130 with cardiovascular disease and equal numbers of controls,” the authors “found no effect of randomised beta-carotene on risk of cancer or cardiovascular disease within any quartile of baseline plasma beta-carotene, nor was there a trend across quartiles (P for trend 0.15 and 0.62, respectively).”

Vitamin E and Cancer and Cardiovascular Disease

Lee et al., 2005

In 39,876 women followed up for an average of 10.1 years, “there were 482 major cardiovascular events in the vitamin E group and 517 in the placebo group, a nonsignificant 7% risk reduction (relative risk [RR], 0.93; 95% confidence interval [CI], 0.82–1.05; P = .26). There were no significant effects on the incidences of myocardial infarction (RR, 1.01; 95% CI, 0.82–1.23; P = .96) or stroke (RR, 0.98; 95% CI, 0.82–1.17; P = .82), as well as ischemic or hemorrhagic stroke. For cardiovascular death, there was a significant 24% reduction (RR, 0.76; 95% CI, 0.59–0.98; P = .03). There was no significant effect on the incidences of total cancer (1437 cases in the vitamin E group and 1428 in the placebo group; RR, 1.01; 95% CI, 0.94–1.08; P = .87) or breast (RR, 1.00; 95% CI, 0.90–1.12; P = .95), lung (RR, 1.09; 95% CI, 0.83–1.44; P = .52), or colon cancers (RR, 1.00; 95% CI, 0.77–1.31; P = .99). Cancer deaths also did not differ significantly between groups. There was no significant effect of vitamin E on total mortality (636 in the vitamin E group and 615 in the placebo group; RR, 1.04; 95% CI, 0.93–1.16; P = .53).”

Cardiovascular Disease

Baseline IgG Antibody Titers to Chlamydia neumoniae, Helicobacter pylori, Herpes Simplex Virus, and Cytomegalovirus and Cardiovascular Disease

Ridker et al., 1999a

“IgG antibody titers against C. pneumoniae, H. pylori, herpes simplex virus, and cytomegalovirus were measured in baseline blood samples obtained from 122 study participants who subsequently reported a first cardiovascular event (case–patients) and 244 participants matched for age and smoking status who did not report a cardiovascular event (controls) during 3 years of follow-up.” “Little evidence was found of an association between risk for cardiovascular events and baseline IgG seropositivity for antibodies against C. pneumoniae (rate ratio, 1.1 [95% CI, 0.7 to 1.8]), H. pylori (rate ratio, 0.90 [CI, 0.6 to 1.4]), herpes simplex virus (rate ratio, 1.2 [CI, 0.6 to 2.1]), and cytomegalovirus (rate ratio, 0.9 [CI, 0.6 to 1.5]). In addition, there was little evidence of an association between a participant’s total number of infections and subsequent cardiovascular risk (P > 0.2).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Blood Pressure, C-Reactive Protein, and Cardiovascular Events

Blake et al., 2003

“Among 15,215 women followed prospectively over a median of 8.1 years. In cross-sectional analyses at baseline, median levels of CRP for women with blood pressure < 120/75, 120 to 129/75 to 84, 130 to 139/85 to 89, 140 to 159/90 to 94, and ≥ 160/95 mm Hg were 0.96, 1.42, 2.20, 2.82, and 3.34 mg/L, respectively (P for trend < 0.0001). Increasing categories of blood pressure were significant predictors of CRP levels at baseline. In prospective analyses, both elevated CRP levels (≥ 3 mg/L) and increasing categories of blood pressure were independent determinants of future cardiovascular events, and CRP had incremental prognostic value at all levels of blood pressure. The adjusted hazard ratio for women with blood pressure ≥ 160/95 mm Hg and CRP levels ≥3 mg/L was 8.31 (95% CI, 4.44 to 15.55, P < 0.0001) compared with those with blood pressure <120/75 and CRP levels < 3 mg/L. After participants had been divided into 4 groups on the basis of CRP levels (< 3 or ≥ 3 mg/L) and blood pressure levels (< 130/85 or ≥ 130/85), the risk factor-adjusted hazard ratios were as follows: low CRP/low blood pressure, 1.0; high CRP/low blood pressure, 1.87 (P = 0.002); low CRP/high blood pressure, 2.54 (P < 0.0001); and high CRP/high blood pressure, 3.27 (P < 0.0001).”

C-Reactive Protein, Low-Density Lipoprotein, and First Cardiovascular Event

Ridker et al., 2002

“C-reactive protein and LDL cholesterol were measured at base line in 27,939 apparently health American women, who were then followed for a mean of eight years for the occurrence of myocardial infarction, ischemic stroke, coronary revascularization, or death from cardiovascular causes.” “Although C-reactive protein and LDL cholesterol were minimally correlated (r = 0.08), base-line levels of each had a strong linear relation with the incidence of cardiovascular events. After adjustment for age, smoking status, the presence or absence of diabetes mellitus, categorical levels of blood pressure, and use or nonuse of hormone-replacement therapy, the relative risks of first cardiovascular events according to increasing quintiles of C-reactive protein, as compared with the women in the lowest quintile, were 1.4, 1.6, 2.0, and 2.3 (P < 0.001), whereas the corresponding relative risks in increasing quintiles of LDL cholesterol, as compared with the lowest, were 0.9, 1.1, 1.3, and 1.5 (P < 0.001). Similar effects were observed in separate analyses of each component of the composite end point and among users and nonusers of hormone-replacement therapy. Overall, 77 percent of all events occurred among women with LDL cholesterol levels below 160 mg per deciliter (4.14 mmol per liter), and 46 percent occurred among those with LDL cholesterol levels below 130 mg per deciliter (3.36 mmol per liter). By contrast, because C-reactive protein and LDL cholesterol measurements tended to identify different high-risk groups, screening for both biologic markers provided better prognostic information than screening for either alone. Independent effects were also observed for C-reactive protein in analyses adjusted for all components of the Framingham risk score.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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C-Reactive Protein, Metabolic Syndrome, and Cardiovascular Events

Ridker et al., 2003

The study population was “14,719 apparently healthy women who were followed for an 8-year period for myocardial infarction, stroke, coronary revascularization, or cardiovascular death; 24% of the cohort had the metabolic syndrome at study entry. At baseline, median CRP levels for those with 0, 1, 2, 3, 4, or 5 characteristics of the metabolic syndrome were 0.68, 1.09, 1.93, 3.01, 3.88, and 5.75 mg/L, respectively (P(trend) < 0.0001). Over the 8-year follow-up, cardiovascular event-free survival rates based on CRP levels above or below 3.0 mg/L were similar to survival rates based on having 3 or more characteristics of the metabolic syndrome. At all levels of severity of the metabolic syndrome, however, CRP added prognostic information on subsequent risk. For example, among those with the metabolic syndrome at study entry, age-adjusted incidence rates of future cardiovascular events were 3.4 and 5.9 per 1000 person-years of exposure for those with baseline CRP levels less than or greater than 3.0 mg/L, respectively. Additive effects for CRP were also observed for those with 4 or 5 characteristics of the metabolic syndrome. The use of different definitions of the metabolic syndrome had minimal impact on these findings.”

C-Reactive Protein and Cardiovascular Events

Ridker et al., 1998a

“CRP was measured in baseline blood samples from 122 participants in the Women’s Health Study who subsequently suffered a first cardiovascular event and from 244 age- and smoking-matched control subjects who remained free of cardiovascular disease during a 3-year follow-up period. Women who developed cardiovascular events had higher baseline CRP levels than control subjects (P = 0.0001), such that those with the highest levels at baseline had a 5-fold increase in risk of any vascular event (RR = 4.8; 95% CI, 2.3 to 10.1; P = 0.0001) and a 7-fold increase in risk of MI or stroke (RR = 7.3; 95% CI, 2.7 to 19.9; P = 0.0001). Risk estimates were independent of other risk factors, and prediction models that included CRP provided a better method to predict risk than models that excluded CRP (all P values <0.01). In stratified analyses, CRP was a predictor among subgroups of women with low as well as high risk as defined by other cardiovascular risk factors.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Ridker et al., 2000

Among 28,262 women followed for a 3 year period, of “12 markers measured, hs-CRP was the strongest univariate predictor of the risk of cardiovascular events; the relative risk of events for women in the highest as compared with the lowest quartile for this marker was 4.4 (95 percent confidence interval, 2.2 to 8.9). Other markers significantly associated with the risk of cardiovascular events were serum amyloid A (relative risk for the highest as compared with the lowest quartile, 3.0), sICAM-1 (2.6), interleukin-6 (2.2), homocysteine (2.0), total cholesterol (2.4), LDL cholesterol (2.4), apolipoprotein B-100 (3.4), HDL cholesterol (0.3), and the ratio of total cholesterol to HDL cholesterol (3.4). Prediction models that incorporated markers of inflammation in addition to lipids were significantly better at predicting risk than models based on lipid levels alone (P < 0.001). The levels of hs-CRP and serum amyloid A were significant predictors of risk even in the subgroup of women with LDL cholesterol levels below 130 mg per deciliter (3.4 mmol per liter), the target for primary prevention established by the National Cholesterol Education Program. In multivariate analyses, the only plasma markers that independently predicted risk were hs-CRP (relative risk for the highest as compared with the lowest quartile, 1.5; 95 percent confidence interval, 1.1 to 2.1) and the ratio of total cholesterol to HDL cholesterol (relative risk, 1.4; 95 percent confidence interval, 1.1 to 1.9).”

C-Reactive Protein and Vascular Disease

Rifai et al., 2002

Study included “643 women who subsequently developed cancer or had cardiovascular events and 643 age- and smoking-matched women who remained free of either disease during 58-month follow-up.” “Little evidence showed that increasing quartiles of baseline CRP predicted incident cancer (adjusted relative risks, 1.0, 1.2, 1.1, and 1.3; P for trend > 0.2). In contrast, increasing quartiles of baseline CRP were a strong marker of risk for future cardiovascular disease (adjusted relative risks, 1.0, 2.9, 3.4, and 5.6; P for trend < 0.001).”

Fiber and Cardiovascular Disease

Liu et al., 2002a

“During 230,006 person-years of follow-up, 570 incident cases of CVD were documented, including 177 MI. After adjustment for age and randomized treatment status, a significant inverse association was observed between dietary fiber intake and CVD risk. Comparing the highest quintile of fiber intake (median: 26.3 g/day) with the lowest quintile (median: 12.5 g/day), the relative risks (RR) were 0.65 (95% confidence interval [CI]: 0.51, 0.84) for total CVD and 0.46 (95% CI: 0.30, 0.72) for MI. Additional adjustment for CVD risk factors reduced the RRs to 0.79 (95% CI: 0.58, 1.09) for total CVD and 0.68 (95% CI: 0.36, 1.22) for MI. The inverse trends across categories generally remained, although they were no longer statistically significant. Inverse relations were observed between both soluble and insoluble fiber and risk of CVD and MI, and among those who had never smoked and those with body mass index < 25.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Flavonoids and Cardiovascular Events

Sesso et al., 2003a

“Women (n = 38,445) free of CVD and cancer participated in a prospective study with a mean follow-up of 6.9 y. On the basis of a food-frequency questionnaire, total flavonoids and selected flavonols and flavones were categorized into quintiles, and food sources were categorized into 4 groups. Relative risks were computed for important vascular events (519 events; excluding revascularizations) and CVD (729 events), including myocardial infarction, stroke, revascularization, and CVD death. The mean flavonoid intake was 24.6 ± 18.5 mg/d, primarily as quercetin (70.2%). For both CVD and important vascular events, no significant linear trend was observed across quintiles of flavonoid intake (P = 0.63 and 0.80, respectively). No individual flavonol or flavone was associated with CVD. Broccoli and apple consumption were associated with nonsignificant reductions in CVD risk: 25–30% and 13–22%, respectively. A small proportion of women (n = 1185) consuming ≥4 cups (946 mL) tea/d had a reduction in the risk of important vascular events but with a nonsignificant linear trend (P = 0.07).”

Fruit and Vegetables and Cardiovascular Disease

Liu et al., 2000

After an average of 5 years followup (195,647 person-years) the authors documented 418 incident cases of CVD, including 126 myocardial infarctions. “After adjustment for age, randomized treatment status, and smoking, we observed a significant inverse association between fruit and vegetable intake and CVD risk. For increasing quintiles of total fruit and vegetable intake (median servings/d: 2. 6, 4.1, 5.5, 7.1, and 10.2), the corresponding relative risks (RRs) were 1.0 (reference), 0.78, 0.72, 0.68, and 0.68 (95% CI comparing the 2 extreme quintiles: 0.51, 0.92; P: for trend = 0.01). An inverse, though not statistically significant, trend remained after additional adjustment for other known CVD risk factors, with RRs of 1.0, 0.75, 0.83, 0.80, and 0.85 (95% CI for extreme quintiles: 0.61, 1.17). After excluding participants with a self-reported history of diabetes, hypertension, or high cholesterol at baseline, the multivariate-adjusted RR was 0.45 when extreme quintiles were compared (95% CI: 0.22, 0.91; P: for trend = 0.09). Higher fruit and vegetable intake was also associated with a lower risk of MI, with an adjusted RR of 0.62 for extreme quintiles (95% CI: 0.37, 1.04; P: for trend = 0.07).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Hemoglobin A1c Concentration and Cardiovascular Events

Blake et al., 2004

“The authors identified 464 case patients with incident myocardial infarction, stroke, or coronary revascularization and 928 unmatched control subjects who remained free of cardiovascular events at case diagnosis. The mean follow-up was 7 years. Of the overall study population, 136 had a history of diabetes mellitus or an overtly elevated baseline A(1c) level (>6.4%) and were excluded from the primary analyses. Among women without diabetes mellitus or an elevated baseline A(1c) level, mean ± SD baseline levels of A(1c) were significantly higher among future cases than controls (5.47% ± 0.27% vs 5.37% ± 0.22%; P < .001). The crude relative risks (RRs) of incident cardiovascular events for increasing quartiles of A(1c) were 1.00, 0.98, 1.33, and 2.25 (95% confidence interval [CI] for the highest vs the lowest quartile, 1.59–3.18). The A(1c) levels correlated with several other traditional cardiovascular risk factors, and in fully adjusted models, the predictive effect of A(1c) was attenuated and not significant (RR for the highest vs the lowest quartile, 1.00; 95% CI, 0.65–1.54). In contrast, in the population including women with diabetes mellitus at enrollment, diabetes mellitus (RR, 4.97; 95% CI, 2.81–8.77) remained a strong independent determinant of cardiovascular risk in fully adjusted analyses, while A(1c) levels did not (RR for the highest vs the lowest quartile, 1.11; 95% CI, 0.73–1.71).”

High Blood Pressure, Blood-Pressure Progression, and Cardiovascular Events

Conen et al., 2007

“39,322 initially healthy women were classified into four blood pressure categories according to self reported baseline blood pressure and followed for a median of 10.2 years.” “982 (2.5%) women developed a major cardiovascular event, and 8,686 (30.1%) women without baseline hypertension progressed to hypertension. The age adjusted event rate for the primary end point was 1.6/1000 person years among women with normal blood pressure, 2.9/1000 person years among those with high normal blood pressure, and 4.3/1000 person years among those with baseline hypertension. Compared with women with high normal blood pressure (reference group), those with normal blood pressure had a lower risk of a major cardiovascular event (adjusted hazard ratio 0.61, 95% confidence interval 0.48 to 0.76) and of incident hypertension (0.42, 0.40 to 0.44). The hazard ratio for a major cardiovascular event in women with baseline hypertension was 1.30 (1.08 to 1.57). Women who progressed to hypertension (reference group) during the first 48 months of the study had a higher cardiovascular risk than those who remained normotensive (adjusted hazard ratio 0.64, 0.50 to 0.81). Women with high normal blood pressure at baseline who progressed to hypertension (reference group) had similar outcome rates to women with baseline hypertension (adjusted hazard ratio 1.17, 0.88 to 1.55).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Homocysteine, 5,10-Methylenetetrahydrofolate Reductase 677C > T polymorphism, Nutrient Intake, and Cardiovascular Disease

Zee et al., 2007

This study “evaluated the associations of homocysteine, methylenetetrahydrofolate reductase (MTHFR) 677C>T genotype, and dietary intake of folate/B-vitamins with subsequent CVD events in 24,968 women followed for 10 years.” “In unadjusted analyses, homocysteine showed moderately strong linear associations with CVD, with hazard ratios (95% CI) comparing top with bottom quintiles for total CVD of 1.92 (1.55–2.37), myocardial infarction 2.32 (1.52–3.54), and ischemic stroke 2.25 (1.45–3.50), all P(trend) < 0.001. These ratios were markedly attenuated after adjusting for traditional risk factors and socioeconomic status to 1.08 (0.86–1.36), P(trend) = 0.12; 1.20 (0.76–1.87), P(trend) = 0.14; and 1.21 (0.75–1.94), P(trend) = 0.50, respectively. Homocysteine was associated with MTHFR genotype (1.4 micromol/L higher homocysteine for TT vs CC, P < 0.001) and inversely with intake of folate, vitamin B(2), B(6), and B(12), all P(trend) < 0.001. However, there was no association of MTHFR genotype or dietary folate/B-vitamins with CVD. In addition, there were no gene-diet or gene-homocysteine interactions in relation to CVD.”

Homocysteine and Cardiovascular Disease

Ridker et al., 1999b

“From a total cohort of 28,263 postmenopausal women with no history of cardiovascular disease or cancer at baseline, 122 women who subsequently experienced cardiovascular events were defined as cases, and 244 age- and smoking status-matched women who remained free of disease during follow-up were defined as controls…. Of the 122 cases, there were 85 events of MI or stroke and 37 coronary revascularizations. Case subjects had significantly higher baseline homocysteine levels than controls (14.1 vs 12.4 micromol/L; P = .02). Subjects with homocysteine levels in the highest quartile had a 2-fold increase in risk of any cardiovascular event (relative risk [RR], 2.0; 95% confidence interval [CI], 1.1–3.8). This effect was largely due to an excess of cases with high levels of homocysteine; the RR for those with homocysteine levels at or higher than the 95th percentile (20.7 micromol/L) was 2.6 (95% CI, 1.1–5.7). Risk estimates were independent of traditional risk factors and were greatest for the end points of MI and stroke (RR for those with baseline homocysteine levels in the top quartile, 2.2; 95% CI, 1.1–4.6). Self-reported multivitamin supplement use at study entry was associated with significantly reduced levels of homocysteine (P < .001). However, the association between increasing quartile of homocysteine level and risk of MI or stroke remained significant in analyses controlling for baseline multivitamin supplement use (P = .003 for trend), and subgroup analyses limited to women who were (P = .02 for trend) or were not (P = .04 for trend) taking multivitamin supplements.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Immunoassay-Measured Fibrinogen and High-Sensitivity C-reactive Protein Concentrations for Predicting Cardiovascular Events

Mora et al., 2006

Subjects were 27,742 women followed over a 10-year period. “Compared with women in the bottom biomarker quintile, age-adjusted hazard ratios (95% confidence intervals [CIs]) for incident CVD for quintiles 2 to 5 of fibrinogen were 1.10 (0.86 to 1.41), 1.30 (1.03 to 1.65), 1.46 (1.16 to 1.85), and 2.43 (1.95 to 3.02); for hs-CRP they were 1.48 (1.06 to 2.05), 1.70 (1.24 to 2.33), 2.20 (1.63 to 2.96), and 3.24 (2.43 to 4.31). After further adjustment for established risk factors, both biomarkers remained associated (P for trend < or = 0.001) with incident CVD (hazard ratio, 1.35; 95% CI, 1.07 to 1.71 for top fibrinogen quintile; and hazard ratio, 1.68; 95% CI, 1.22 to 2.29 for top hs-CRP quintile compared with the bottom quintiles). Further adjustment for the other biomarker resulted in hazard ratios of 1.23 and 1.56 (P for trend = 0.02 and 0.002), respectively. Although fibrinogen correlated positively with hs-CRP (rs = 0.41, P < 0.001), the highest CVD risk was associated with elevated levels of both fibrinogen and hs-CRP: age-adjusted hazard ratio of 3.45 (95% CI, 2.60 to 4.57) for women with fibrinogen > 393 mg/dL and hs-CRP > 3 mg/L compared with < 329 mg/dL and < 1 mg/L, respectively.”

Interleukin-18 and Cardiovascular Disease

Everett et al., 2009

The authors measured baseline plasma IL-18 levels in 253 WHS participants who developed cardiovascular disease (CVD) and in 253 healthy age- and smoking-matched controls. “IL-18 levels were higher at baseline among those who developed CVD (274.1pg/mL versus 233.8pg/mL, P < 0.001), and were associated with future CVD (relative risk (RR) for highest versus lowest quartile 2.53; 95% CI, 1.47–4.35, P < 0.001). While that risk was attenuated after adjustment for traditional cardiovascular risk factors (RR 1.60; 95% CI, 0.77–3.34, P = 0.13), those with IL-18 levels at or above a threshold of the 90th percentile (442pg/mL) remained at elevated risk after adjustment (RR 2.40; 95% CI, 1.05–5.56, P = 0.04). Levels of IL-18 above this threshold modify the fully adjusted risk of future CVD conferred by elevated levels of total cholesterol (P(interaction) = 0.02).”

Lipoprotein(a), Hormone-Replacement Therapy, and Cardiovascular Events

Suk Danik et al., 2008

“Lipoprotein(a) at baseline was measured among 27,736 healthy women, of whom 12,075 indicated active HT use at the time of blood draw at study initiation and 15,661 did not. The risk of first-ever major cardiovascular event (nonfatal myocardial infarction, nonfatal cerebrovascular event, coronary revascularization, or cardiovascular death) over a 10-year period was assessed with Cox proportional hazard models according to Lp(a) levels and HT status and adjusted for potential confounding variables. As anticipated, Lp(a) values were lower among women taking HT (median 9.4 mg/dl vs 11.6 mg/dl, p < 0.0001). In women not taking HT, the hazard ratio of future CVD for the highest Lp(a) quintile compared with the lowest was 1.8 (p trend < 0.0001), after adjusting for age, smoking, blood pressure, diabetes, body mass index, total cholesterol, high-density lipoprotein, C-reactive protein, and treatment arms of aspirin and vitamin E. In contrast, among women taking HT, there was little evidence of association with CVD (hazard ratio: 1.1, p trend = 0.18; interaction p value = 0.0009 between Lp(a) quintiles and HT on incident CVD).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Low-Density Lipoprotein Particle Concentration and Size and Cardiovascular Events

Blake et al., 2002

“Median baseline levels of LDL particle concentration (NMR) were higher (1597 vs 1404 nmol/L; P = 0.0001) and LDL particle size (NMR) was lower (21.5 vs 21.8 nm; P = 0.046) among women who subsequently had cardiovascular events (n = 130) than among those who did not (n = 130). Of these 2 factors, LDL particle concentration (NMR) was the stronger predictor (relative risk for the highest compared with the lowest quartile = 4.17, 95% CI 1.96–8.87). This compared with a relative risk of 3.11 (95% CI 1.55–6.26) for the ratio of total cholesterol to HDL cholesterol and a relative risk of 5.91 (95% CI 2.65–13.15) for C-reactive protein. The areas under the receiver operating characteristic curves for LDL particle concentration (NMR), total cholesterol to HDL cholesterol ratio, and C-reactive protein were 0.64, 0.64, and 0.66, respectively. LDL particle concentration (NMR) correlated with several traditionally assessed lipid and nonlipid risk factors, and thus adjustment for these tended to attenuate the magnitude of association between LDL particle concentration (NMR) and risk.”

Low-Dose Aspirin and Cardiovascular Events

Ridker et al., 2005a

“During follow-up, 477 major cardiovascular events were confirmed in the aspirin group, as compared with 522 in the placebo group, for a nonsignificant reduction in risk with aspirin of 9 percent (relative risk, 0.91; 95 percent confidence interval, 0.80 to 1.03; P = 0.13). With regard to individual end points, there was a 17 percent reduction in the risk of stroke in the aspirin group, as compared with the placebo group (relative risk, 0.83; 95 percent confidence interval, 0.69 to 0.99; P = 0.04), owing to a 24 percent reduction in the risk of ischemic stroke (relative risk, 0.76; 95 percent confidence interval, 0.63 to 0.93; P = 0.009) and a nonsignificant increase in the risk of hemorrhagic stroke (relative risk, 1.24; 95 percent confidence interval, 0.82 to 1.87; P = 0.31). As compared with placebo, aspirin had no significant effect on the risk of fatal or nonfatal myocardial infarction (relative risk, 1.02; 95 percent confidence interval, 0.84 to 1.25; P = 0.83) or death from cardiovascular causes (relative risk, 0.95; 95 percent confidence interval, 0.74 to 1.22; P = 0.68). Gastrointestinal bleeding requiring transfusion was more frequent in the aspirin group than in the placebo group (relative risk, 1.40; 95 percent confidence interval, 1.07 to 1.83; P = 0.02). Subgroup analyses showed that aspirin significantly reduced the risk of major cardiovascular events, ischemic stroke, and myocardial infarction among women 65 years of age or older.”

Lycopene, Carotenoids, and Retinol and Cardiovascular Disease

Sesso et al., 2004

Baseline blood samples were collected from 28,345 of 39,876 participants. During a mean of 4.8 y of followup, the authors “identified 483 CVD cases and 483 control subjects matched by age, smoking status, and follow-up time. In analyses matched for age and smoking, with adjustment for plasma cholesterol, the relative risks (RRs) and 95% CIs of CVD in increasing quartiles of plasma lycopene were 1.00 (referent), 0.78 (95% CI: 0.55, 1.11), 0.56 (0.39, 0.82), and 0.62 (0.43, 0.90). In multivariate models, the RRs were 1.00 (referent), 0.94 (0.60, 1.49), 0.62 (0.39, 1.00), and 0.67 (0.41, 1.11); those in the upper compared with the lower half of plasma lycopene had an RR of 0.66 (0.47, 0.95). For CVD, exclusive of angina, women in the upper 3 quartiles had a significant multivariate 50% risk reduction compared with those in the lowest quartile. The stepwise addition of individual plasma carotenoids did not affect the RRs.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Lycopene, Tomato-Based Foods, and CVD

Sesso et al., 2003b

“During 7.2 y of follow-up, 719 CVD cases (including myocardial infarction, stroke, revascularization and CVD death) occurred. Compared with women in the 1st quintile of lycopene, those in increasing quintiles had multivariate relative risks (RR) of CVD of 1.11, 1.14, 1.15 and 0.90 (P for trend = 0.34). For the consumption of tomato-based products, women consuming 1.5 to <4, 4 to <7, 7 to <10 and >or=10 servings/wk had RR (95% CI) of CVD of 1.02 (0.82–1.26), 1.04 (0.82–1.31), 0.68 (0.49–0.96) and 0.71 (0.42–1.17) (P for trend = 0.029) compared with women consuming <1.5 servings/wk. Among lycopene food sources, those in the highest levels of tomato sauce (>or = 2 servings/wk) and pizza intake (>or = 2 servings/wk), with multivariate RR of 0.76 (0.55–1.05) and 0.66 (0.37–1.18), respectively, had potential reductions in CVD risk. Dietary lycopene was not strongly associated with the risk of CVD. However, the possible inverse associations noted for higher levels of tomato-based products, particularly tomato sauce and pizza, with CVD suggest that dietary lycopene or other phytochemicals consumed as oil-based tomato products confer cardiovascular benefits.”

Migraine, Vascular Risk, and Cardiovascular Events

Kurth et al., 2008b

Subjects “were 27,519 women who were free from cardiovascular disease at baseline with available information on the Framingham risk score and migraine status.” “At baseline, 3,577 (13.0%) women reported active migraine, of whom 1418 (39.6%) reported migraine with aura. During 11.9 years of follow-up, there were 697 cardiovascular disease events. The authors stratified participants based on 10 year risk of coronary heart disease estimated from the Framingham risk score (<or=1%, 2–4%, 5–9%, and >or=10%). Compared with women without migraine, the age adjusted hazard ratios in women with active migraine with aura were 1.93 (95% confidence interval 1.45 to 2.56) for major cardiovascular disease, 1.80 (1.16 to 2.79) for ischaemic stroke, and 1.94 (1.27 to 2.95) for myocardial infarction. When stratified by Framingham risk score, the association between migraine with aura and major cardiovascular disease was strongest in the lowest risk score group. There was a diametric association pattern for ischaemic stroke and myocardial infarction. Compared with women without migraine, the age adjusted hazard ratios in women who reported migraine with aura in the lowest Framingham risk score group were 3.88 (1.87 to 8.08) for ischaemic stroke and 1.29 (0.40 to 4.21) for myocardial infarction. Hazard ratios in women with migraine with aura in the highest Framingham risk score group were 1.00 (0.24 to 4.14) for ischaemic stroke and 3.34 (1.50 to 7.46) for myocardial infarction. Women with migraine without aura were not at increased risk of ischaemic stroke or myocardial infarction in any of the Framingham risk score groups.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Non-HDL Cholesterol, Apolipoproteins A-I and B100, Standard Lipid Measures, Lipid Ratios, and C-Reactive Protein and Cardiovascular Disease

Ridker et al., 2005b

In 15,632 women followed up over a 10-year period for the occurrence of future cardiovascular events, after adjustment for age, smoking status, blood pressure, diabetes, and body mass index, the HRs for future cardiovascular events for those in the extreme “quintiles were 1.62 (95% CI, 1.17–2.25) for LDL-C, 1.75 (95% CI, 1.30–2.38) for apolipoprotein A-I, 2.08 (95% CI, 1.45–2.97) for total cholesterol, 2.32 (95% CI, 1.64–3.33) for HDL-C, 2.50 (95% CI, 1.68–3.72) for apolipoprotein B(100), 2.51 (95% CI, 1.69–3.72) for non-HDL-C, and 2.98 (95% CI, 1.90–4.67) for high-sensitivity CRP (P < .001 for trend across all quintiles). The HRs for the lipid ratios were 3.01 (95% CI, 2.01–4.50) for apolipoprotein B(100) to apolipoprotein A-I, 3.18 (95% CI, 2.12–4.75) for LDL-C to HDL-C, 3.56 (95% CI, 2.31–5.47) for apolipoprotein B(100) to HDL-C, and 3.81 (95% CI, 2.47–5.86) for the total cholesterol to HDL-C (P < .001 for trend across all quintiles). The correlation coefficients between high-sensitivity CRP and the lipid parameters ranged from –0.33 to 0.15, and the clinical cut points for CRP of less than 1, 1 to 3, and higher than 3 mg/L provided prognostic information on risk across increasing levels of each lipid measure and lipid ratio.”

Parental History of Myocardial Infarction and Risk of Cardiovascular Disease

Sesso et al., 2001

The study population included “22071 men from the Physicians’ Health Study and 39876 women from the Woman’s Health Study with data on parental history and age at MI. Among men, 2,654 CVD cases developed over 13.0 years; among women, 563 CVD cases occurred over 6.2 years. Compared with men with no parental history, only maternal, only paternal, and both maternal and paternal history of MI conferred relative risks (RRs) of CVD of 1.71, 1.40, and 1.85; among women, the respective RRs were 1.46, 1.15, and 2.05. For men, maternal age at MI of < 50, 50 to 59, 60 to 69, 70 to 79, and ≥80 years had RRs of 1.00, 1.88, 1.88, 1.67, and 1.17; for women, the RRs for maternal age at MI of < 50, 50 to 59, and ≥60 years were 2.57, 1.33, and 1.52. Paternal age at MI of < 50, 50 to 59, 60 to 69, 70 to 79, and ≥80 years in men had RRs of 2.19, 1.64, 1.42, 1.16, and 0.92; in women, for paternal age at MI of < 50, 50 to 59, and ≥60 years, the RRs were 1.63, 1.33, and 1.13.”

Plasma Macrophage Inhibitory Cytokine-1 and Cardiovascular Events

Brown et al., 2002

Among 27,628 women, the authors “established baseline concentrations of MIC-1 in 257 who subsequently had myocardial infarction, stroke, or died from a cardiovascular event (cases) and in 257 matched for age and smoking status, who did not report cardiovascular disease during 4-year follow-up (controls). The authors also assessed polymorphisms in the MIC-1 gene (MIC-1 H and MIC-1 D) in all 514 women. FINDINGS: MIC-1 concentrations were higher at baseline in women who subsequently had cardiovascular events than in those who did not (618 vs 538 pg/mL, p = 0.0002). Concentrations above the 90th percentile (>856 pg/mL) were associated with a 2.7-fold increase in risk (95% CI 1.6–4.9, p = 0.001). This effect was independent of traditional cardiovascular risk factors and at least additive to that of C-reactive protein. There was no significant association between MIC-1 polymorphism and vascular events.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Sex-Hormone Concentrations and Cardiovascular Events

Rexrode et al., 2003a

“Two hundred women who developed CVD were matched 1:1 by age, smoking, and postmenopausal hormone therapy (HT) to controls who remained free of CVD.” “Among hormone therapy (HT) nonusers, cases had significantly higher androgen profiles (higher median FAI and lower SHBG levels) than controls. After adjustment for age, smoking, use of aspirin, vitamin E, and alcohol, family history of myocardial infarction, and physical activity, nonusers in the lowest SHBG quartile had an OR of 2.25 (95% CI, 1.03 to 4.91) for CVD, and there were significant trends across FAI quartiles (P for trend = 0.03). Additional adjustment for body mass index, hypertension, diabetes, and elevated cholesterol eliminated associations with SHBG and FAI. Among women using HT, no significant differences in hormones or SHBG were observed among women who developed CVD and controls.”

Soluble CD40L and Cardiovascular Events

Schonbeck et al., 2001

“Mean concentrations of sCD40L at baseline were significantly higher among 130 participants who subsequently developed myocardial infarction, stroke, or cardiovascular death (cases), compared with 130 age- and smoking-matched women who remained free of cardiovascular disease (controls) during a 4-year follow-up (2.86 ng/mL for cases versus 2.09 ng/mL for controls; P = 0.02). Women with concentrations above the 95th percentile of the control distribution (>3.71 ng/mL) had a significantly increased relative risk (RR) of developing future cardiovascular events (RR, 3.3; 95% CI, 1.2 to 8.6; P = 0.01) that remained after adjustment for usual cardiovascular risk factors (multivariate RR, 2.8; 95% CI, 0.9 to 8.0; P = 0.05).”

Soluble P-Selectin and Cardiovascular Events

Ridker et al., 2001

The authors “measured baseline plasma concentration of soluble P-selectin among 115 participants who subsequently developed cardiovascular events and among 230 age- and smoking-matched participants who remained free of disease during 3.5 years of follow-up. Overall, mean levels of soluble P-selectin were significantly higher at baseline among women who subsequently experienced cardiovascular events compared with those who did not (83.2 versus 69.3 ng/mL; P = 0.003). The risk of future cardiovascular events increased with increasing quartiles of soluble P-selectin (P = 0.02), such that women in the highest quartile at study entry had an age- and smoking-matched relative risk 2.2 times higher than those in the lowest quartile (95% confidence interval, 1.2 to 4.2; P = 0.01). This effect was independent of traditional risk factors. For each quartile increase in soluble P-selectin, the risk of future cardiovascular events increased 28% (P= 0.03) after additional adjustment for obesity, hypertension, hyperlipidemia, diabetes, and exercise frequency. The highest risks were observed among women with the very highest levels of P-selectin (>137.3 ng/mL, the 95th percentile cut point of the control distribution).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Cataract

Beta-Carotene and Age-Related Cataract

Christen et al., 2004

There were 129 cataracts in the beta-carotene group and 133 in the placebo group (relative risk [RR] = 0.95, 95% CI 0.75–1.21). For cataract extraction, there were 94 cases in the beta-carotene group and 89 cases in the placebo group (RR = 1.04, 95% CI 0.78–1.39). Subgroup analyses suggested a possible beneficial effect of beta-carotene in smokers.

Fruit and Vegetables and Cataract

Christen et al., 2005

“A total of 35,724 of 39,876 women were free of a diagnosis of cataract at baseline and were followed for incident cataract and cataract extraction. During an average of 10 y of follow-up, 2,067 cataracts and 1,315 cataract extractions were confirmed. Compared with women in the lowest quintile of fruit and vegetable intake, women with higher intakes had modest 10–15% reduced risks of cataract (P for trend < 0.05). For cataract extraction, no significant inverse trend was observed (P for trend = 0.12).”

Colorectal Cancer

C-Reactive Protein Concentrations and Colorectal Cancer

Zhang et al., 2005

Included 27,913 women who had C-reactive protein (CRP) measured at entry into the a trial. “Maximum length of intervention and follow-up was 10.8 years. … 169 women developed colorectal adenocarcinomas during follow-up. Baseline CRP levels were not significantly associated with colorectal cancer risk. The multivariate hazard ratios according to cutoff points for CRP proposed in clinical guidelines were 0.79 (95% CI, 0.53 to 1.17) for the category of 1 to 3 mg/L and 0.66 (CI, 0.43 to 1.03) for the category of greater than 3 mg/L (P for trend = 0.09), as compared with the category of less than 1 mg/L. High CRP levels were also not associated with increased risk in analyses done according to tumor location and stage at diagnosis, according to alternative cutoff points for CRP, or in any of the subgroups evaluated. Despite multivariate analysis, residual confounding might still be present. Although this study was prospective, we cannot completely exclude undetected cancer at baseline. Measurements for CRP were available for only 71% of women in the cohort; however, the women who did and those who did not provide blood were mostly similar.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Calcium and Vitamin D and Colorectal Cancer

Lin et al., 2005a

During an average followup of 10 years, 223 of 36,976 women eligible for the present study developed colorectal cancer. “Intakes of calcium and vitamin D from dietary sources and supplements were assessed with a baseline food frequency questionnaire. … Cox proportional hazards regression was used to estimate relative risks and 95% confidence intervals. Intakes of total calcium and vitamin D were not associated with risk of colorectal cancer; multivariate relative risks comparing the highest with the lowest quintile were 1.20 (95% confidence interval: 0.79, 1.85; p for trend = 0.21) for total calcium and 1.34 (95% confidence interval: 0.84, 2.13; p for trend = 0.08) for total vitamin D. Intakes of both nutrients from specific types of sources, including diet and supplements, were also not significantly associated with colorectal cancer risk. Data provide little support for an association of calcium and vitamin D intake with colorectal cancer risk.”

Fat, Fatty Acids, and Colorectal Cancer

Lin et al., 2004

“Among the 37,547 women eligible for the present study, 202 developed colorectal cancer during an average follow-up period of 8.7 years (1993–2003). … Total fat intake was not related to colorectal cancer risk, nor were intakes of the different types of fat and major fatty acids. However, the authors observed a positive association between intake of fried foods away from home and colorectal cancer risk (highest quintile vs lowest: relative risk = 1.86, 95% confidence interval: 1.09, 3.16; p for trend = 0.01). These prospective cohort data provide little support for an association between dietary fat and colorectal cancer risk. However, intake of fried foods and/or other factors related to their intake may be associated with colorectal cancer development.”

Fruit and Vegetables and Colorectal Cancer

Lin et al., 2005b

“Among 39,876 healthy women aged ≥45 years at baseline, 36,976 with baseline self-reported” information on dietary intakes and other risk factors for colorectal cancer were included in the analyses. “During an average follow-up of 10 years, 223 women were diagnosed with colorectal cancer…. Intakes of fruit, vegetables, and the specific subgroups were not found to be associated with colorectal cancer risk. Multivariate relative risks (RRs) comparing the highest with lowest quintile were 0.79 (95% CI = 0.49–1.27,p for trend = 0.30) for fruit intake, and 0.88 (95% CI = 0.56–1.38, p for trend = 0.30) for vegetables intake. Similarly, intake of total fiber was not associated with colorectal cancer risk; the RR for the highest relative to lowest quintile was 0.75 (95% CI = 0.48–1.17, p for trend = 0.12). However, higher intake of legume fiber was associated with a lower risk of colorectal cancer; the RR for the highest versus slowest quintile was 0.60 (95% CI = 0.40–0.91, p for trend = 0.02).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Glycemic Load and Colorectal Cancer

Higginbotham et al., 2004b

“Subjects were 38,451 women followed for an average of 7.9 years.” During follow-up the authors identified 174 with incident colorectal cancer. “Dietary glycemic load was statistically significantly associated with an increased risk of colorectal cancer (adjusted RR = 2.85, 95% confidence interval [CI] = 1.40 to 5.80, comparing extreme quintiles of dietary glycemic load; P(trend) = .004) and was associated, although not statistically significantly, with overall glycemic index (corresponding RR = 1.71, 95% CI = 0.98 to 2.98; P(trend) = .04). Total carbohydrate (adjusted RR = 2.41, 95% CI = 1.10 to 5.27, comparing extreme quintiles of carbohydrate; P(trend) = .02), nonfiber carbohydrate (corresponding RR = 2.60, 95% CI = 1.22 to 5.54; P(trend) = .02), and fructose (corresponding RR = 2.09, 95% CI = 1.13 to 3.87; P(trend) = .08) were also statistically significantly associated with increased risk. Thus, our data indicate that a diet with a high dietary glycemic load may increase the risk of colorectal cancer in women.”

Common Cold

Smoking and Colds

Bensenor et al., 2001a

Among 39,876 women, “after adjustment for age, body-mass index, prevalence of asthma and chronic lung diseases, alcohol intake, physical activity, and multivitamin use, current heavy smokers had no appreciable increase in the frequency of colds (relative risk (RR) for ≥ 3 versus no colds in the past year, 1.05; 95% confidence interval (CI), 0.80–1.39), but a significantly increased risk of prolonged colds (RR for colds of > 7 vs 1–3 days, 2.53; 95% CI, 1.95–3.29). There was no difference in the number of days confined to home. Nonsmoking women passively exposed to cigarette smoke had a slightly increased risk of both more frequent colds (RR, 1.33; 95% CI, 1.18–1.51) and more prolonged colds during the previous year (RR, 1.12; 95% CI, 0.99–1.27).”

Connective Tissue Disease

Breast Implants and Connective-Tissue Disease

Hennekens et al., 1996

In a retrospective study of 395,543 women who completed mailed questionnaires for potential participation in WHS, “a total of 10,830 women reported breast implants and 11,805 reported connective-tissue diseases between 1962 and 1991. … Compared with women who did not report breast implants, the relative risk (RR) of the combined end point of any connective-tissue disease among those who reported breast implants was 1.24 (95% confidence interval, 1.08 to 1.41, P = .0015). With respect to the individual diseases, the finding for other connective-tissue diseases (including mixed) was statistically significant (P = .017), the findings for rheumatoid arthritis, Sjogren’s syndrome, dermatomyositis or polymyositis, or scleroderma were of borderline statistical significance (.05 < P < .10), and the finding for systemic lupus erythematosus was not statistically significant (P = .44). There were no clear trends in RR with increasing duration of breast implants.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Coronary Heart Disease

Migraine and Coronary Heart Disease

Cook et al.,2002

After adjusting for other CHD risk factors, female health professionals (from the WHS) and male physicians (from the Physician’s Health Study) reporting migraine were not at increased risk for subsequent major CHD (women: relative risk [RR], 0.83; 95% confidence interval [CI], 0.53 to 1.29; men: RR, 1.02; 95% Cl, 0.79 to 1.31) or total CHD (women: RR, 1.01; 95% Cl, 0.76 to 1.34; men: RR, 0.98; 95% Cl, 0.82 to 1.18). When considered separately, there was also no increase in risk of MI or angina.

Past and Current Physical Activity and Coronary Heart Disease

Conroy et al., 2005

“Among 37,169 eligible participants at baseline, the most active women (vigorous physical activity 10–12 months × yr) during high school and age 18–22 yr were more than twice as likely to meet physical activity recommendations at baseline than the least active women (no vigorous activity) during high school and age 18–22 yr (multivariate-adjusted odds ratio = 2.43; 95% C.I. 2.24, 2.63). At baseline, the most active women ≥ 1500 kcal × wk1) had a 39% lower risk of CHD during follow-up than the least active (< 200 kcal × wk–1) (multivariate-adjusted relative risk = 0.61; 95% C.I. 0.46, 0.81). However, physical activity during young adulthood was not associated with risk of CHD occurring during middle age and older.”

Physical Activity and Coronary Heart Disease

Lee et al., 2001c

A total of 244 cases of CHD occurred among 39,372 participants from September 1992 to March 1999. “Adjusting for potential confounders, the relative risks (RRs) of CHD for less than 200, 200–599, 600–1,499, and 1,500 or more kcal/wk expended on all activities were 1.00 (referent), 0.79 (95% confidence interval [CI], 0.56–1.12), 0.55 (95% CI, 0.37–0.82), and 0.75 (95% CI, 0.50–1.12), respectively (P for linear trend = .03). Vigorous activities were associated with lower risk (RR, 0.63; 95% CI, 0.38–1.04 comparing highest and lowest categories). Walking also predicted lower risk among women without vigorous activities. Among these women, the multivariate RRs for walking 1 to 59 min/wk, 1.0 to 1.5 h/wk, and 2 or more h/wk, compared with no regular walking, were 0.86 (95% CI, 0.57–1.29), 0.49 (95% CI, 0.28–0.86), and 0.48 (95% CI, 0.29–0.78), respectively. For walking paces of less than 3.2 km/h (2.0 mph), 3.2 to 4.7 km/h (2.0–2.9 mph), and 4.8 km/h (3.0 mph) or more, compared with no regular walking, RRs were 0.56 (95% CI, 0.32–0.97), 0.71 (95% CI, 0.47–1.05), and 0.52 (95% CI, 0.30–0.90), respectively. When analyzed simultaneously, time spent walking (P for linear trend = .01) but not walking pace (P for linear trend = .55) predicted lower risk. The inverse association between physical activity and CHD risk did not differ by weight or cholesterol levels (P for interaction = .95 and.71, respectively), but there were significant interactions by smoking and hypertension status. Physical activity was inversely related to risk in current smokers but not hypertensive women (P for interaction = .01 and.001, respectively).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Diabetes Melittus

Flavonoids and Type 2 Diabetes

Song et al., 2005a

The authors “calculated relative risks (RRs) of incident type-2 diabetes (1,614 events over 8.8 y of follow-up) according to dietary intake of total or individual flavonols and flavones and flavonoid-rich foods.” The authors “also measured and examined plasma concentrations of insulin, HbA(1C), CRP, and IL-6 in relation to total flavonol and flavone intake among 344 nondiabetic women. During 332,905 person-years of follow-up, none of total flavonols and flavones, quercetin, kaempferol, myricetin, apigenin, and luteolin was significantly associated with risk of type 2 diabetes. Among flavonoid-rich foods, apple and tea consumption was associated with diabetes risk. Women consuming ≥ 1 apple/d showed a significant 28% reduced risk of type 2 diabetes compared with those who consumed no apples (the multivariate-adjusted RR = 0.72, 95% CI: 0.56, 0.92; p = 0.006 for trend). Tea consumption was also inversely associated with diabetes risk but with a borderline significant trend (≥ 4 cups/d vs none: RR 0.73, 95% CI: 0.52–1.01; p for trend = 0.06). In 344 nondiabetic women, total intake of flavonols and flavones was not significantly related to plasma concentrations of fasting insulin, HbA(1C), CRP, or IL-6.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Fruit and Vegetables and Type 2 Diabetes

Liu et al., 2004

“Detailed diet information was provided by 38,018 of the participants without previously diagnosed diabetes at baseline and who completed a 131-item semiquantitative food frequency questionnaire.… At baseline, mean daily intake in servings (± SD) was 2.2 ± 1.6 for fruits, 3.9 ± 2.6 for vegetables, and 6.1 ± 3.6 for total fruits and vegetables. Median intake of total fruits and vegetables ranged from 2.5 servings/day in the lowest quintile to > 10 servings/day in the highest quintile. Women who consumed more fruits or vegetables tended to be older, exercised more, and had a lower BMI than those with lower intake. During an average 8.8 years of follow-up (332,905 person-years),” the authors “documented 1,614 incident cases of type 2 diabetes. In models adjusted for age, total calories, and smoking, we observed significant inverse relationships with diabetes risk for total fruit and vegetable intake, fruits, citrus fruits, green leafy vegetables, dark yellow vegetables, and legumes and a significant positive association with intake of potatoes. After adjusting for known diabetes risk factors, however, none of these associations remained statistically significant. Because BMI is an important risk factor for type 2 diabetes and has also been previously identified as an effect modifier of diet on diabetes risk, the authors performed subgroup analyses stratified by BMI (< 25 and ≥ 25 kg/m2). No significant findings were observed in the lower BMI group (~15% of case subjects) (data not shown). Among women with BMI ≥ 25 kg/m2, higher intake of green leafy or dark yellow vegetables was significantly associated with reduced risk of type 2 diabetes. Starchy vegetables such as potatoes did not appear to be beneficial.” The authors “observed a marginally significant interaction for BMI and intake of dark yellow vegetables (P = 0.06) but not for the interaction between BMI and intake of green leafy vegetables (P = 0.19). After fully adjusting for BMI, the inverse associations of green leafy and deep yellow vegetables were still observed among overweight women, although the trends were not statistically significant; the multivariate RRs across quintiles were 1.00, 0.94, 0.92, 0.85 and 0.90 (95% CI 0.76–1.08) for green leafy vegetables (P for trend = 0.09) and 1.00, 0.87, 0.90, 0.91 and 0.79 (0.65–0.97) for dark yellow vegetables (P for trend = 0.13). Since BMI may also reflect the impact of long-term fruit and vegetable intake, the addition of BMI into the model may be an overadjustment that could distort the underlying temporal relationship between fruit and vegetable intake and diabetes risk.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Insulin, Proinsulin, Proinsulin:Insulin Ratio and Type 2 Diabetes

Pradhan et al., 2003a

Of 27,628 participants, 126 women were diagnosed with diabetes during a 4-year followup period. These women were compared with 225 age-matched controls. “Fasting insulin level and proinsulin:insulin ratio were assessed in quartiles, and proinsulin level was assessed in categories (< or = 4.0 pmol/L, 4.01 to 6.99 pmol/L, > or = 7.0 pmol/L). The risk of developing type 2 diabetes was determined using conditional logistic regression analysis that adjusted for body mass index and other diabetes risk factors. RESULTS: Baseline insulin and proinsulin levels and proinsulin:insulin ratios were significantly higher among cases than among controls. Women with elevated insulin levels in the highest as compared with the lowest quartile were more likely to develop diabetes (odds ratio [OR] = 5.6; 95% confidence interval [CI]: 1.8 to 17.6), as were women with elevated (> or = 7.0 pmol/L vs < or = 4.0 pmol/L) proinsulin levels (OR = 16.4; 95% CI: 5.8 to 46.8) and women with proinsulin:insulin ratios in the highest quartile (OR = 9.6; 95% CI: 3.1 to 30.8). Similar results were observed among women with a baseline hemoglobin A(1c) level < or = 6.0%. In time-trend analyses, fasting insulin was a consistent predictor of long-term risk. Proinsulin and proinsulin:insulin ratio, although predictive throughout the study, were especially strong predictors of rapid progression to type 2 diabetes.”

Low-Dose Aspirin and Type 2 Diabetes

Pradhan et al., 2009

“38,716 women aged ≥ 45 years and free of clinical diabetes were randomly assigned to either low-dose aspirin or placebo…. Documented clinical type 2 diabetes was prospectively evaluated throughout the trial.” After a median follow-up of 10.2 years, “among women randomly assigned to receive aspirin (n = 19,326) or placebo (n = 19,390), there was no statistically significant difference in the incidence of type 2 diabetes. There were 849 cases of diabetes in the aspirin group and 847 in the placebo group (rate ratio 1.01 [95% CI 0.91–1.11]). Stratification by diabetes risk factors including age, BMI, family history of diabetes, physical activity, A1C, and high-sensitivity C-reactive protein did not support a modulating effect of these variables. Analyses accounting for treatment duration and adherence similarly found no beneficial effects.”

Magnesium and Plasma Insulin Concentrations and Type 2 Diabetes

Song et al., 2004a

“The study population was 39,345 women with no previous history of cardiovascular disease, cancer, or type 2 diabetes who completed validated semiquantitative food frequency questionnaires in 1993, followed for an average of 6 years. The authors documented 918 confirmed incident cases of type 2 diabetes over this period. There was a significant inverse association between magnesium intake and risk of type 2 diabetes, independent of age and BMI (P = 0.007 for trend). After further adjustment for physical activity, alcohol intake, smoking, family history of diabetes, and total calorie intake, the multivariate-adjusted RRs of diabetes from the lowest to highest quintiles of magnesium intake were attenuated at 1.0, 1.06, 0.81, 0.86, and 0.89 (P = 0.05 for trend). Among women with BMI ≥ 25 kg/m2, the inverse trend was significant; multivariate-adjusted RRs were 1.0, 0.96, 0.76, 0.84, and 0.78 (P = 0.02 for trend). Multivariate-adjusted geometric mean insulin levels for overweight women in the lowest quartile of magnesium intake was 53.5 compared with 41.5 pmol/l among those at the highest quartile (P = 0.03 for trend).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Physical Activity, Body-Mass Index, and Type 2 Diabetes

Weinstein et al., 2004

During 6.9 years mean followup, 1,361 cases of incident diabetes occurred among 37,878 women free of cardiovascular disease, cancer, and diabetes at baseline. “Individually, BMI and physical activity were significant predictors of incident diabetes. Compared with normal-weight individuals (BMI < 25), the multivariate-adjusted hazard ratio (HR) was 3.22 (95% confidence interval [CI], 2.69–3.87) for overweight (BMI 25 ≤ 30) individuals and 9.09 (95% CI, 7.62–10.8) for obese (BMA > 30) individuals. For overall activity (kilocalories expended per week), compared with the least active first quartile, the multivariate-adjusted HRs were 0.91 (95% CI, 0.79–1.06) for the second quartile, 0.86 (95% CI, 0.74–1.01) for the third, and 0.82 (95% CI, 0.70–0.97) for the fourth (P for trend = .01). In the combined analyses, overweight and obese participants, whether active or inactive, had significantly elevated risks, compared with normal-weight active individuals. The multivariate-adjusted HRs were 1.15 (95% CI, 0.83–1.59) for normal-weight inactive, 3.68 (95% CI, 2.63–5.15) for overweight active, 4.16 (95% CI, 3.05–5.66) for overweight inactive, 11.5 (95% CI, 8.34–15.9) for obese active, and 11.8 (95% CI, 8.75–16.0) for obese inactive participants.”

Red Meat and Type 2 Diabetes

Song et al., 2004b

Over an average of 8.8 years (326,876 person-years of followup), the authors documented 1,558 incident cases of type 2 diabetes among 37,309 participants. “After adjusting for age, BMI, total energy intake, exercise, alcohol intake, cigarette smoking, and family history of diabetes, the authors found positive associations between intakes of red meat and processed meat and risk of type 2 diabetes. Comparing women in the highest quintile with those in the lowest quintile, the multivariate-adjusted relative risks (RRs) of type 2 diabetes were 1.28 for red meat (95% CI 1.07–1.53, P < 0.001 for trend) and 1.23 for processed meat intake (1.05–1.45, P = 0.001 for trend). Furthermore, the significantly increased diabetes risk appeared to be most pronounced for frequent consumption of total processed meat (RR 1.43, 95% CI 1.17–1.75 for ≥ 5/week vs < 1/month, P < 0.001 for trend) and two major subtypes, which were bacon (1.21, 1.06–1.39 for ≥ 2/week vs <1/week, P = 0.004 for trend) and hot dogs (1.28, 1.09–1.50 for ≥ 2/week vs < 1/week, P = 0.003 for trend). These results remained significant after further adjustment for intakes of dietary fiber, magnesium, glycemic load, and total fat. Intakes of total cholesterol, animal protein, and heme iron were also significantly associated with a higher risk of type 2 diabetes.”

Sex Steroid Hormones and Type 2 Diabetes

Ding et al., 2007

“Among women not using hormone therapy and free of baseline cardiovascular disease, cancer and diabetes, 359 incident cases of type 2 diabetes were matched with 359 controls during an average follow-up of 10 years…. Oestradiol and testosterone were each strongly and positively associated with risk of type 2 diabetes. After adjustment for BMI, family history, lifestyle and reproductive variables, the multivariable relative risks (95% CI) comparing the highest vs lowest quintile were 12.6 (2.83–56.3) for total oestradiol (p = 0.002 for trend), 13.1 (4.18–40.8) for free oestradiol (p < 0.001 for trend), 4.15 (1.21–14.2) for total testosterone (p = 0.019 for trend) and 14.8 (4.44–49.2) for free testosterone (p < 0.001 for trend). These associations remained robust after adjusting and accounting for other metabolic syndrome components and baseline HbA 1c levels.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Sugar Intake and Type 2 Diabetes

Janket et al., 2003

“A validated semiquantitative food frequency questionnaire was completed by 39,345 women aged 45 years and older…. Compared with the lowest quintile of sugar intake, the RRs and 95% CIs for the highest quintiles were 0.84 (0.67–1.04) for sucrose, 0.96 (0.78–1.19) for fructose, 1.04 (0.85–1.28) for glucose, and 0.99 (0.80–1.22) for lactose, after adjustment for known risk factors for type 2 diabetes. Similar findings of no association were obtained in subgroup analyses stratified by BMI.”

Dry Eye Syndrome

Dry Eye Syndrome

Schaumberg et al., 2003

The authors surveyed 39,876 WHS participants about a history of diagnosed dry eye syndrome (DES) and dry eye symptoms. “The prevalence of DES increased with age, from 5.7% among women < 50 years old to 9.8% among women aged ≥ 75 years old. The age-adjusted prevalence of DES was 7.8%, or 3.23 million women aged ≥ 50 in the US. Compared with Whites, Hispanic (odds ratio [OR] = 1.81, confidence interval [CI] = 1.18–2.80) and Asian (OR = 1.77, CI = 1.17–2.69) women were more likely to report severe symptoms, but not clinically diagnosed DES. There were no significant differences by income (P([trend]) =.78), but more educated women were less likely to have DES (P([trend]) =.03). Women from the South had the highest prevalence of DES, though the magnitude of geographic differences was modest.”

Hormone-Replacement Therapy and Dry Eye Syndrome

Schaumberg et al., 2001

Study population was “25,665 postmenopausal women who provided information about use of HRT at baseline (1992), 12, and 36 months and dry eye syndrome at 48 months. . . . For the combined end point of either clinically diagnosed dry eye syndrome or severe symptoms, the multivariable-adjusted odds ratios were 1.69 (95% confidence interval [CI], 1.49–1.91) for estrogen use alone and 1.29 (95% CI, 1.13–1.48) for estrogen plus progesterone/progestin use compared with no HRT use. Each 3-year increase in the duration of HRT use was associated with a significant 15% (95% CI, 11%–19%) elevation in risk of clinically diagnosed dry eye syndrome or severe symptoms. Results were similar for the combined end point of clinically diagnosed dry eye syndrome and severe symptoms.”

Eye-Care Use

Demographic Predictors of Eye-Care Use

Schaumberg et al., 2000

Most of the 39,876 (83%) women reported having had an eye examination within the past 2 years. “The likelihood of having an eye examination in the past 2 years increased with age (odds ratio [OR] = 2.59 for age ≥ 75 years versus those <50 years; P [trend] <0.0001), higher education (OR = 1.27 for master’s degree versus licensed nurse training; P [trend] = 0.0004), and higher household income (OR = 1.85 for ≥$100,000 versus < $10,000; P [trend] <0.0001). Women from the south were less likely to have had an eye examination than those from the west (OR = 0.92; P = 0.03). Compared with whites, Asian/Pacific Islanders were less likely (OR = 0.76; P = 0.02) and blacks more likely (OR = 1.27; P = 0.02) to have had an eye examination within 2 years.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Factor V Leiden

Ethnic Distribution of Factor V Leiden

Ridker et al., 1997

Participants were 4,047 men and women participating in the Physicians’ Health Study (PHS, men) and the WHS (women) who were free of myocardial infarction, stroke, or venous thrombosis. “Prevalence of G1691A Leiden mutation in the gene coding for coagulation factor V was determined in the PHS group using polymerase chain reaction techniques and, in the WHS group, a second-generation activated protein C (APC)-resistance screening test with genetic confirmation of all borderline and low-value results…. In 2,468 Caucasian Americans, carrier frequency of factor V Leiden was 5.27% (95% confidence interval [CI], 4.42%–6.22%). Carrier frequency was 2.21% in 407 Hispanic Americans, 1.23% in 650 African Americans, 0.45% in 442 Asian Americans, and 1.25% in 80 Native Americans. Thus, prevalence of factor V Leiden was less among minority subjects (P = .001). Carrier frequencies were similar in Caucasian men and women (5.53% vs 4.85% respectively, P = .5).”

Fasting Insulin

C-Reactive Protein and Fasting Insulin

Pradhan et al., 2003b

In “349 healthy, nondiabetic women who remained free from clinically diagnosed type 2 diabetes mellitus during a 4-year period from biomarker assessment, fasting insulin was strongly associated with body mass index (BMI) (r = 0.53, P < 0.001), C-reactive protein (CRP) (r = 0.38, P < 0.001), and interleukin-6 (r = 0.33, P < 0.001). Physical activity level, alcohol consumption, and use of hormone replacement therapy were also related to fasting insulin. However, in multivariable linear regression analysis, BMI and CRP were the only independent correlates of log-normalized fasting insulin. Overall, the final model explained 32% of the variance in log insulin level. In multivariable logistic regression, the fully adjusted odds ratio (OR) for elevated fasting insulin (> or =51.6 pmol/L) increased with tertile of BMI, CRP, and IL-6, such that the ORs in the highest versus lowest tertile of each parameter were 9.0 (95% confidence interval [CI], 4.4 to 18.7), 4.4 (95% CI, 1.9 to 10.1), and 2.0 (95% CI, 0.9 to 4.2), respectively. Furthermore, increasing levels of CRP were associated with a stepwise gradient in odds for elevated fasting insulin among both lean and overweight women.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Hypertension

C-Reactive Protein and Hypertension

Sesso et al., 2003c

Among 20,525 women who provided baseline blood samples “with initially normal levels of blood pressure (BP) (systolic BP < 140 mm Hg and diastolic BP < 90 mm Hg, and no history of hypertension or antihypertensive medications) and then followed up for a median of 7.8 years,” 5,365 women developed incident hypertension. “In crude models, the relative risks (RRs) and 95% confidence intervals (CIs) of developing hypertension from the lowest (referent) to the highest levels of baseline C-reactive protein were 1.00, 1.25 (95% CI, 1.14–1.40), 1.51 (95% CI, 1.35–1.68), 1.90 (95% CI, 1.72–2.11), and 2.50 (95% CI, 2.27–2.75) (linear trend P < .001). In fully adjusted models for coronary risk factors, the RRs and 95% CIs were 1.00, 1.07 (95% CI, 0.95–1.20), 1.17 (95% CI, 1.04–1.31), 1.30 (95% CI, 1.17–1.45), and 1.52 (95% CI, 1.36–1.69) (linear trend P < .001). C-reactive protein was significantly associated with an increased risk of developing hypertension in all prespecified subgroups evaluated, including those with very low levels of baseline BP, as well as those with no traditional coronary risk factors. Similar results were found when treating C-reactive protein as a continuous variable and controlling for baseline BP.”

Lipid Concentrations and Hypertension

Sesso et al., 2005

In 16,130 women “who provided baseline blood samples and had no history of high cholesterol level (no treatment or diagnosis) or hypertension (no treatment, diagnosis, or elevated blood pressure)” followed up for 10.8 years, “incident hypertension developed in 4,593 women. In multivariate-adjusted models, the relative risks of development of hypertension from the lowest (referent) to the highest quintile of baseline total cholesterol level were 1.00, 0.96, 1.02, 1.09, and 1.12 (P = .002 for trend); for low-density lipoprotein cholesterol level, 1.00, 0.97, 1.00, 1.02, and 1.11 (P = .053 for trend); for high-density lipoprotein cholesterol level, 1.00, 0.93, 0.87, 0.87, and 0.81 (P < .001 for trend); for non-high-density lipoprotein cholesterol level, 1.00, 1.06, 1.11, 1.12, and 1.25 (P < .001 for trend); and for the ratio of total to high-density cholesterol, 1.00, 1.10, 1.14, 1.20, and 1.34 (P < .001 for trend). Similar relative risks were noted for Adult Treatment Panel III clinical cut points and after the exclusion of obese or diabetic women.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Life Expectancy

Blood-Pressure Lowering and Life Expectancy

Sesso et al., 2003d

Subjects were 57,573 men and women (men from the Physician’s Health Study, women from WHS and the Women’s Antioxidant Cardiovascular Study). “Seven patient states were defined, including (1) no cardiovascular disease, (2) stroke, (3) myocardial infarction, (4) revascularization, (5) history of cardiovascular disease, (6) noncardiovascular disease death, and (7) cardiovascular death.” At baseline the authors “assumed (1) hypothetical pretreatment blood pressures of 160/95 or 150/90 mm Hg; (2) strategies A and B lower blood pressure by 20/13 and 13/8 mm Hg, respectively; and (3) baseline age of 35 years. For subjects initially at 160/95 mm Hg, those with antihypertensive treatment, antihypertensive treatment and diabetes, or antihypertensive treatment, diabetes, and currently smoking had corresponding gains in life expectancy of 2.43, 2.80, and 2.43 years for Strategy A. An initial blood pressure of 150/90 mm Hg resulted in similar gains. Compared with Strategy B, with blood pressure reductions of 13/8 mm Hg, Strategy A provided additional gains in life expectancy of 0.84, 0.99, and 0.87 years for those with antihypertensive treatment, antihypertensive treatment and diabetes, or antihypertensive treatment, diabetes, and currently smoking. The initial blood pressure level did not affect the magnitude of life expectancy gains for equivalent blood pressure reductions. Greater gains in life expectancy among hypertensive and diabetic women suggest that blood pressure lowering may yield greater benefits in selected subgroups.”

Low-Dose Aspirin and Asthma (Adult Onset)

Kurth et al., 2008a

“Among 37,270 women with no reported history of asthma prior to randomisation and during 10 years of follow-up, there were 872 new cases diagnosed with asthma in the aspirin group and 963 in the placebo group (hazard ratio 0.90; 95% CI 0.82 to 0.99; p = 0.027). This apparent 10% lower relative risk of incident adult-onset asthma among those assigned to aspirin was significantly modified by body mass index, with no effect in women with a body mass index of ≥ 30 kg/m2” The effect of aspirin on adult-onset asthma was not significantly modified by “age, smoking status, exercise levels, postmenopausal hormone use or randomised vitamin E assignment.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Metabolic Syndrome

Magnesium, C-Reactive Protein, and Metabolic Syndrome

Song et al., 2005b

Subjects were 11,686 women “who were initially free of cardiovascular disease and cancer and had no use of postmenopausal hormones…. In age- and BMI-adjusted analyses, magnesium intake was inversely associated with plasma C-reactive protein (CRP) concentrations; CRP concentrations were 12% lower in the highest intake quintile than in the lowest (P for trend < 0.0001). This association was not appreciably altered by further adjustment for other potential confounding variables including dietary factors; the mean CRP concentrations for ascending quintiles of magnesium intake were 1.50, 1.39, 1.35, 1.34, and 1.31 mg/l (P for trend = 0.0003). This inverse association was stronger for women with a BMI > or = 25 kg/m(2) (P < 0.0001 for interaction) and those who were current or past smokers (P = 0.0009 for interaction). After adjustment for confounding lifestyle and dietary factors, women in the highest quintile of magnesium intake had 27% lower risk of the metabolic syndrome (defined according to the National Cholesterol Education Program criteria) compared with those in the lowest quintile of intake (odds ratio 0.73 [95% CI 0.60–0.88], P for trend = 0.0008).”

Migraine

Hormone Therapy and Migraine

Misakian et al., 2003

Analyses were restricted to the 17,107 of 21,788 postmenopausal women who were postmenopausal at baseline and who were never (38.5%) or current (61.5%) users of hormone therapy (HT). Of these, 1,909 (11.2%) experienced migraine headache within the last year. Women with migraine headache were significantly younger, had a younger age at menopause, were more likely to have had a surgical menopause, and were more likely to be current users of HT. After adjusting for age, race, smoking, alcohol use, ever use of oral contraception, age at menopause, and menopause type, the odds ratio (OR) for migraine headache was 1.42 (95% CI 1.24–1.62) for women who were current users of HT compared with never users. ORs were similar for users of estrogen alone (OR 1.39, 95% CI 1.14–1.69) and users of both estrogen and progestin (OR 1.41, 95% CI 1.22–1.63).

Low-Dose Aspirin to Prevent Migraine

Bensenor et al., 2001b

1,001 WHS participants “with frequent migraine attacks were assigned to 100 mg of aspirin every other day (n = 525) or aspirin placebo (n = 476). Migraine frequency, as well as severity, duration, and degree of incapacitation, were assessed by self-report on questionnaires 12 months and 36 months after randomization, and also by monthly diaries kept before and after randomization. Women assigned to aspirin reported small and consistent decreases in migraine frequency (59.6% vs 56.4% assigned to placebo reporting improvement at 36 months; odds ratio 1.13, 95% confidence interval, 0.86–1.48), as well as decreases in severity, duration, and migraine-related incapacitation. These reductions were not, however, statistically significant. These data are compatible with a small treatment effect of low-dose aspirin in the prophylaxis of migraine among middle-aged women.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Mortality

HbA1c Measured in Stored Erythrocytes and Mortality

Levitan et al., 2008

Of 27,210 women “over a median of 10 years of follow-up, 706 women died. Proportional hazards models adjusted for age, smoking, hypertension, blood lipids, exercise, postmenopausal hormone use, multivitamin use and C-reactive protein were used to estimate the relative risk of mortality. Among women without a diagnosis of diabetes and HbA1c < 5.60%, those in the top quintile (HbA1c 5.19–5.59%) had a relative risk of mortality of 1.28 (95% CI 0.98–1.69, p value for linear trend = 0.14) compared with those with HbA1c 2.27–4.79%. Women with HbA1c 5.60–5.99% and no diagnosis of diabetes had a 54% increased risk of mortality (95% CI 1–136%) compared with those with HbA1c 2.27–4.79%. HbA1c was significantly associated with mortality across the range 4.50–7.00% (p value for linear trend = 0.02); a test of deviation from linearity was not statistically significant (p = 0.67). Diabetic women had more than twice the mortality risk of non-diabetic women.”

Pregnancy Loss

Factor V Leiden and Pregnancy Loss

Ridker et al., 1998b

Subjects were “113 consecutive women referred for evaluation of recurrent spontaneous abortion (case-patients) and 437 postmenopausal women with at least one successful pregnancy and no history of pregnancy loss (controls). An additional survey of 387 postmenopausal women with at least one pregnancy loss was also conducted…. Prevalence of the factor V Leiden mutation was greater among case-patients (8.0%) than among controls (3.7%) (odds ratio, 2.3 [95% CI, 1.0 to 5.2]; P = 0.050). In the subgroup of case-patients with three or more pregnancy losses and no successful pregnancies, prevalence of the mutation was 9.0% (odds ratio, 2.6 [CI, 1.0 to 6.7]; P = 0.048). Among the additional women surveyed, the prevalence of the mutation in those with three or more pregnancy losses (7.5%) was almost identical to that in case-patients. Thus, in all evaluated women with several pregnancy losses, the prevalence of factor V Leiden was increased 2.2-fold (P = 0.026).”

Rheumatoid Arthritis

Smoking and Rheumatoid Arthritis

Karlson et al., 1999a

Subjects completed mailed questionnaires regarding demographics, health habits, including cigarette smoking history, and medical history, including rheumatoid arthritis (RA) diagnosis made by a physician and date of diagnosis. Of 7,697 women who self-reported RA, 3,416 reported seropositive RA. In multivariate analyses controlling for age, race, education, age at menarche, pregnancy history, menopausal status, and postmenopausal hormone use, duration of smoking was associated with a significantly increased risk of both RA and seropositive RA (both P < 0.01 for trend), after adjusting for smoking intensity. Women who smoked ≥ 25 cigarettes/day for more than 20 years experienced a 39% increased risk of RA and 49% increased risk of seropositive RA. However, smoking intensity (number of cigarettes/day) was unrelated to risk of RA or seropositive RA (both P = 0.3 for trend), after adjusting for duration of smoking.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Vitamin E and Rheumatoid Arthritis (RA)

Karlson et al., 2008

“After excluding women with self-reported RA at baseline, 39,144 women were included in the present study…. During an average follow-up of 10 years, 106 cases of definite RA occurred, 50 in the vitamin E group and 56 in the placebo group. Sixty-four (60%) RA cases were rheumatoid factor positive and 42 (40%) were rheumatoid factor negative. There was no significant association between vitamin E and risk of definite RA (relative risk [RR] 0.89, 95% confidence interval [95% CI] 0.61–1.31). There were also no significant risk reductions for either seropositive RA (RR 0.64, 95% CI 0.39–1.06) or seronegative RA (RR 1.47, 95% CI 0.79–2.72).”

Stroke

Body-Mass Index and Stroke

Kurth et al., 2005a

“This was a prospective cohort study among 39,053 women participating in the Women’s Health Study…. After a mean follow-up of 10 years, a total of 432 strokes (347 ischemic, 81 hemorrhagic, and 4 undefined) occurred.” The authors “found a statistically significant trend for increased risk of total and ischemic stroke across 7 BMI categories. With World Health Organization criteria, women who were obese (BMI ≥ 30 kg/m2) had hazard ratios of 1.50 (95% CI 1.16 to 1.94) for total stroke, 1.72 (95% CI 1.30 to 2.28) for ischemic stroke, and 0.82 (95% CI 0.43 to 1.58) for hemorrhagic stroke compared with women with BMI < 25 kg/m2. Additional control for history of hypertension, diabetes, and elevated cholesterol substantially attenuated the hazard ratios for total and ischemic stroke. There was no effect modification for age, exercise, or smoking.”

C-Reactive Protein and Lipid Concentrations vs Coronary Heart Disease as Determinants of Ischemic Stroke

Everett et al., 2006

“Among 15,632 initially healthy women who were followed for a 10-year period,” the authors “compared hs-CRP, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoproteins A-I and B100, and lipid ratios as determinants of ischemic stroke compared with CHD…. After adjustment for age, smoking status, blood pressure, diabetes, and obesity, the hazard ratios (HRs) and 95% confidence intervals (CIs) for the third versus the first tertile for future ischemic stroke compared with CHD were, respectively, 1.91 (95% CI 1.13 to 3.21) and 2.26 (95% CI 1.64 to 3.12) for TC, 1.29 (95% CI 0.83 to 2.02) and 2.09 (95% CI 1.53 to 2.85) for LDL-C, 0.57 (95% CI 0.36 to 0.92) and 0.38 (95% CI 0.27 to 0.52) for HDL-C, 1.72 (95% CI 1.03 to 2.86) and 2.93 (95% CI 2.04 to 4.21) for non-HDL-C, and 2.76 (95% CI 1.51 to 5.05) and 1.66 (95% CI 1.17 to 2.34) for hs-CRP. Of the lipid ratios, that of TC to HDL-C had the largest HR for both future ischemic stroke and CHD (HR 1.95 [95% CI 1.16 to 3.26] and 4.20 [95% CI 2.79 to 6.32], respectively).”

Interobserver Agreement in Classification of Stroke

Atiya et al., 2003

“During 7.0 years of follow-up, 271 incident strokes occurred, of which 133 were reclassified. There was excellent interrater agreement in the diagnosis of major stroke types, hemorrhagic subtypes, and degree of disability, as well as substantial agreement in the definition of the vascular territory involved. Only moderate agreement was reached in the classification of ischemic subtypes.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Lipid Concentrations and Ischemic Stroke

Kurth et al., 2007

Among 27,937 women who provided baseline blood samples, 282 ischemic strokes occurred during 11 years of followup. “All lipid levels were strongly associated with increased risk of ischemic stroke in age-adjusted models. The association attenuated particularly for HDL-C after adjustment for potential confounders. For the comparison of the highest to the lowest quintile, the multivariable-adjusted hazard ratios (95% CI; p for trend across mean quintile values) of ischemic stroke were 2.27 (1.43, 3.60; p(trend) < 0.001) for total cholesterol; 1.74 (1.14, 2.66; p(trend) = 0.003) for LDL-C; 0.78 (0.52, 1.17; p(trend) = 0.27) for HDL-C; 1.65 (1.06, 2.58; p(trend) = 0.02) for the total cholesterol to HDL-C ratio; and 2.45 (1.54, 3.91; p(trend) < 0.001) for non-HDL-C.”

Migraine, Headache, and Stroke

Kurth et al., 2005b

Among 39,754 women in WHS with an average follow-up of 9 years, “a total of 385 strokes (309 ischemic, 72 hemorrhagic, and 4 undefined) occurred. Compared with nonmigraineurs, participants who reported migraine overall or migraine without aura had no increased risk of any stroke type. Participants who reported migraine with aura had increased adjusted hazards ratios (HRs) of 1.53 (95% CI 1.02 to 2.31) for total stroke and 1.71 (95% CI 1.11 to 2.66) for ischemic stroke but no increased risk for hemorrhagic stroke. Participants with migraine with aura who were < 55 years old had a greater increase in risk of total (HR 1.75; 95% CI 1.02 to 3.00) and ischemic (HR 2.25; 95% CI 1.30 to 3.91) stroke. Compared with participants without headache, headache in general and nonmigraine headache were not associated with total, ischemic, or hemorrhagic stroke.”

Smoking and Hemorrhagic Stroke

Kurth et al., 2003

“During 9 years of follow up” of 39,783 women, “a total of 70 hemorrhagic strokes occurred, of which 40 were ICH and 29 were SAH. Never smokers and past smokers had equal rates of ICH and SAH. Current smokers of < 15 cigarettes per day had a multivariable-adjusted relative risk (RR) of 1.93 (95% CI, 0.75 to 5.02) for total hemorrhagic stroke, 2.15 (95% CI, 0.62 to 7.43) for ICH, and 1.70 (95% CI, 0.38 to 7.60) for SAH. Women who smoked ≥ 15 cigarettes per day had RR of 3.29 (95% CI, 1.72 to 6.29) for total hemorrhagic stroke, 2.67 (95% CI, 1.04 to 6.90) for ICH, and 4.02 (95% CI, 1.63 to 9.89) for SAH compared with never smokers.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Venous Thromboembolism

Low-Dose Aspirin and Venous Thromboembolism

Glynn et al., 2007

Among 26,779 WHS participants who gave blood samples that were evaluated for factor V Leiden, G20210A prothrombin, and MTHFR 677C > T polymorphisms, venous thromboembolism was found to have “occurred in 482 women during follow-up of approximately 10 years, an incidence higher than that of myocardial infarction and nearly equal to that of stroke. The incidence of VTE (per 1,000 person-years) was 1.18 among women randomly assigned to active aspirin, compared with 1.25 among women randomly assigned to placebo (relative hazard, 0.95 [95% CI, 0.79 to 1.13]; rate difference, –0.06 [CI, –0.28 to 0.16]). For unprovoked VTE, the relative hazard was 0.90 (CI, 0.70 to 1.16) and the rate difference was –0.06 (CI, –0.21 to 0.10). Relative hazards associated with aspirin use in higher-risk subgroups were 0.83 (CI, 0.50 to 1.39) among women with either factor V Leiden or the prothrombin mutation and 1.36 (CI, 0.77 to 2.41) among those with a history of VTE.” A limitation of this study was that “venous thromboembolism was a secondary end point in the Women’s Health Study.”

Other

Breast Implants and Serologic Outcomes

Karlson et al., 2001

“Subjects were chosen from women enrolled in the run-in phase” of the WHS, “and included 298 women without breast implants, 298 women with breast implants, and 52 diabetic patients diagnosed before age 30. Comparison groups were matched on age, race, date of blood provided to the WHS, and randomization status…. For 14 of the 16 serologic tests, the proportions with abnormal results among the 3 groups of women were not significantly different. Of the remaining tests, C3 levels were decreased in 8 (2.7%) women without breast implants and 22 (7.4%) women with breast implants (p = 0.003). C4 levels were decreased in 31 (10.4%) women without breast implants and 48 (16.1%) women with breast implants (p = 0.03). Women without breast implants and diabetic patients did not differ significantly in the proportions having decreased C3 and C4 levels. Women with breast implants did not have higher frequency of monoclonal immunoglobulins detected by electrophoresis.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Comparison of Self-Reported Connective-Tissue Disease and Medical Records

Karlson et al., 1999b

Among women considered for enrollment in WHS, “the authors identified 220 women with breast implants (exposed) who self-reported connective tissue disease (CTD).” These women were matched by age and date of diagnosis with a random sample of 879 women without breast implants (unexposed) who also self-reported CTD. “After up to three requests and a telephone call, 27.7% of the women provided consent for medical record review. Exposed women appeared somewhat more likely (33.2% vs 26.3%, p = 0.04) to provide consent. Using medical record reviews for 90% of the women who provided consent, confirmation rates of definite CTD were similar among the exposed and unexposed (22.7% vs 24.0%, p = 0.83). This study demonstrates the difficulty of obtaining consent for medical record review of CTD reported to have occurred years ago in women with and without breast implants. Confirmation rates were low but were similar in exposed and unexposed. Despite the fact that the study had low participation rates, the data suggest that relative risk estimates for any definite CTD among women with breast implants compared with women without breast implants would be similar in analyses of self-reported or medical record-confirmed cases.”

Interrelationships Among Circulating Interleukin-6, C-Reactive Protein, and Traditional Cardiovascular Risk Factors

Bermudez et al., 2002

In cross-sectional analysis of 340 women enrolled in WHS, higher levels of IL-6 and CRP were seen with increasing body mass index (BMI), systolic and diastolic blood pressure, and smoking exposure in unadjusted analysis. “IL-6 levels were related to the frequency of alcohol intake (P = 0.002) and showed an inverse relationship with exercise frequency and hormone replacement therapy (P < 0.0001 for both). CRP levels increased with hormone replacement therapy (P = 0.0002). Associations among IL-6, CRP, and lipid levels were minimal. Overall, mean levels of IL-6 and CRP increased with increasing numbers of clinical risk factors (P < 0.0001). In multivariate analyses, independent relationships were seen between levels of IL-6 and age, BMI, smoking, systolic blood pressure, alcohol use, presence of diabetes, and frequency of exercise. CRP was associated with age, BMI, systolic blood pressure, high density lipoprotein, smoking, and hormone replacement therapy in adjusted analyses.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Lipoprotein Particle Profiles by Nuclear Magnetic Resonance, Compared with Standard Lipids and Apolipoproteins in Predicting Cardiovascular Disease

Mora et al., 2009b

“Baseline lipoproteins were measured by NMR in 27,673 women followed up for incident cardiovascular disease (n = 1,015) over an 11-year period. After adjustment for nonlipid risk factors, hazard ratios and 95% confidence intervals for the top versus the bottom quintile of NMR-measured lipoprotein particle concentration (measured in particles per liter) were 2.51 (1.91 to 3.30) for low-density lipoprotein (LDL(NMR)), 0.91 (0.75 to 1.12) for high-density lipoprotein (HDL(NMR)), 1.71 (1.38 to 2.12) for very low-density lipoprotein (VLDL(NMR)), and 2.25 (1.80 to 2.81) for the LDL(NMR)/HDL(NMR) ratio. Similarly adjusted results for NMR-measured lipoprotein particle size (measured in nanometers) were 0.64 (0.52 to 0.79) for LDL(NMR) size, 0.65 (0.51 to 0.81) for HDL(NMR) size, and 1.37 (1.10 to 1.70) for VLDL(NMR) size. Hazard ratios for NMR measures were comparable but not superior to standard lipids (total cholesterol 2.08 [1.63 to 2.67], LDL cholesterol 1.74 [1.40 to 2.16], HDL cholesterol 0.52 [0.42 to 0.64], triglycerides 2.58 [1.95 to 3.41], non-HDL cholesterol 2.52 [1.95 to 3.25], total/HDL cholesterol ratio 2.82 [2.23 to 3.58]) and apolipoproteins (B(100) 2.57 [1.98 to 3.33], A-1 0.63 [0.52 to 0.77], and B(100)/A-1 ratio 2.79 [2.21 to 3.54]). Essentially no reclassification improvement was found with the addition of the LDL(NMR) particle concentration or apolipoprotein B(100) to a model that already included the total/HDL cholesterol ratio and nonlipid risk factors (net reclassification index 0% and 1.9%, respectively), nor did the addition of either variable result in a statistically significant improvement in the c-index.”

Low-Density Lipoprotein Cholesterol by Friedewald Calculation and Direct Measurement and Cardiovascular Events

Mora et al., 2009a

“In a study of 27,331 women with triglycerides ≤ 4.52 mmol/L (≤400 mg/dL), baseline fasting Friedewald LDL-C was compared with fasting and nonfasting direct homogenous measurement for incident CVD during an 11-year period.” “Fasting LDL-C measurements obtained by the 2 methods were highly correlated (r = 0.976, P < 0.001). Compared with fasting Friedewald LDL-C, mean fasting direct LDL-C was 0.15 mmol/L (5.6 mg/dL) lower and nonfasting direct LDL-C 0.30 mmol/L (11.5 mg/dL) lower, both P < 0.0001. The adjusted hazard ratio per 1-SD increment was 1.23 [95% CI 1.15–1.32; 1-SD 0.88 mmol/L (34.1 mg/dL)] for fasting direct LDL-C and 1.22 [95% CI 1.14–1.30; 1-SD 0.90 mmol/L (34.9 mg/dL)] for fasting Friedewald. Nonfasting LDL-C was not associated with CVD by either method. Fasting LDL-C measurements fell into the same NCEP risk category with either method for 79.3% of participants, whereas they differed by 1 NCEP category for 20.7% of participants, with most classified into a lower-risk category by direct LDL-C.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Predictive Models for Cardiovascular Risk Associated with Systolic and Diastolic Blood Pressure

Glynn et al., 2002

Study population consisted of 22,071 males from the Physicians’ Health Study (mean age, 53.2 years; median follow-up, 13.0 years), and 39,876 females from the Women’s Health Study (mean age, 53.8 years; median follow-up, 6.2 years). “In both populations, lower levels of blood pressure predicted lower event rates, with no evidence of a plateau or a J-shaped curve. In males, both systolic and diastolic blood pressures were significantly associated with events (P < 0.001), whereas in females, only systolic blood pressure (P < 0.001) predicted outcome after multivariate adjustment. Correction for measurement error in blood pressure increased risk estimates by ≈ 50%. Differences in systolic blood pressure yielded greater relative risk reductions than did differences in diastolic blood pressure in a combined population of males and females. These predictive models may be useful for risk estimation associated with hypertension in similar populations and may also be used to infer the benefits of antihypertensive therapy.”

ABBREVIATIONS: AF, atrial fibrillation; APC, activated protein C; BMI, body-mass index; BP, blood pressure; CHD, coronary heart disease; CI, confidence interval; CRP, C-reactive protein; CTD, connective tissue disease; CVD, cardiovascular disease; d, day; DES, dry eye syndrome; ERT, estrogen-replacement therapy; FAI, free androgen index; FRS, Framingham Risk Score; GI, glycemic index; GL, glycemic load; h, hour; HDL(-C), high-density lipoprotein (cholesterol); Hg, mercury; HRT, hormone-replacement therapy; HT, hormone therapy; ICH, intracerebral hemorrhage; IQR, interquartile range; LDL(-C), low-density lipoprotein (cholesterol); MET, metabolic equivalent; MI, myocardial infarction; MTHFR, methylenetetrahydrofolate reductase; NCEP, National Cholesterol Education Program; NMR, nuclear magnetic resonance; OR, odds ratio; PHS, Physicians’ Health Study; PMH, postmenopause hormone; RA, rheumatoid arthritis; RR, relative risk; SAH, subarachnoid hemorrhage; SHBG, sex hormone–binding globulin; TC, total cholesterol; VLDL, very lowdensity lipoprotein; VTE, venous thromboembolism; WC, waist circumference; WHR, waist-to-hip ratio; WHS, Women’s Health Study; y, year.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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STUDY OF WOMEN’S HEALTH ACROSS THE NATION

Study Objective and Design

Started in 1994, the Study of Women’s Health Across the Nation (SWAN) is a multisite longitudinal epidemiologic study designed to examine the health of women during their middle years. The study examines the physical, biologic, psychologic, and social changes during this transitional period. The goal of SWAN’s research is to help scientists, health-care providers and women learn how midlife experiences affect health and quality of life during aging.

SWAN was designed to be conducted in three phases: a focus-group phase, a cross-sectional survey phase, and a longitudinal phase. The focus-group phase was intended to help develop the most effective and culturally sensitive study design and protocols for recruiting and retaining diverse groups of women into SWAN. The cross-sectional survey to assess factors associated with age at natural menopause, the prevalence of surgical menopause, symptoms of menopause, health status, and health-care use. In the third phase, eligible premenopausal women who had completed the cross-sectional survey were enrolled into the longitudinal follow-up study, whose purposes were

  1. to characterize the symptomatology and hormonal and bleeding pattern characteristics related to the menopausal transition;

  2. to investigate the hormonal and menstrual bleeding patter characteristics related to change in bone mineral density, cardiovascular status markers, measures of carbohydrate metabolism, and body composition during the menopausal transition;

  3. to examine the relations of psychosocial factors, personality characteristics, and behaviors, including lifestyle behaviors, as they may relate to age at onset, symptoms, and physiologic changes of the menopausal transition;

  4. to discern what changes observed over time are related to the menopausal transition as compared with age-related changes, including those changes that appear to accelerate the aging process; and

  5. to describe and quantify cultural and ethnic differences among women with respect to midlife aging and the menopausal transition in the five racial or ethnic groups of the cohort.

The subjects of the study in the longitudinal cohort are

  • bone density and body composition,

  • cardiovascular measures/risk factors,

  • ovarian markers,

  • menstrual status,

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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  • symptoms,

  • psychosocial factors, and

  • epidemiologic issues.

Participant Enrollment

In 1996 and 1997, a total of 3,302 participants joined the SWAN longitudinal study through 7 designated research centers around the United States. They were drawn from the larger cross-sectional study sample, which included more than 16,000 women. Women who met the eligibility criteria for the longitudinal study were 42–52 years old, had a uterus and at least 1 intact ovary, reported a menstrual period within preceding 3 months, and had not taken hormone medications (such as birth-control pills or estrogen or progesterone preparations) in preceding 3 months.

SWAN placed special emphasis on recruitment of minority-group participants. Enrollees represented 5 racial or ethnic groups and a variety of backgrounds and cultures (1,550 non-Hispanic whites, 935 blacks, 286 Hispanics, 250 Chinese, and 281 Japanese).

Data Collection

Followup visits to research centers take place every year.7 The annual visit includes the following core components: physical measures (weight, height, hip, waist, and blood pressure), fasting morning blood draw, and interviewer-administered and self-administered questionnaires. Women are also given menstrual calendars to complete monthly over the next year. By the end of the funding period in 2009, 12 annual visits were to have been completed.

Factors measured at baseline included demographic descriptors, such as race or ethnicity, education, income, occupation (job title, activities, and industry) and marital status. Other factors assessed were health-care use, active and passive smoke exposure, physical activity, menstrual characteristics, pregnancy

7

Ten annual followup visits have been completed to date.

First annual followup visit (February 1997–January 1999): 2,882, (87%) of baseline cohort.

Second annual followup visit (March 1998–April 2000): 2,749 (83%) of baseline cohort.

Third annual followup visit (February 1999–January 2001): 2,711 (82%) of baseline cohort.

Fourth annual followup visit (February 2000–January 2002): 2,684 (81%) of baseline cohort.

Fifth annual followup visit (2001–2003): 2,617 (79%) of baseline cohort.

Sixth annual followup visit (March 2002–February 2004): 2,442 (74%) of baseline cohort.

Seventh annual followup visit (May 2003–January 2005): 2,406 (73%) of baseline cohort.

Eight annual followup visit (March 2004–January 2006): 2,272 (69%) of baseline cohort.

Ninth annual followup visit (February 2005–January 2007): 2,255 (68%) of baseline cohort.

Tenth annual followup visit (February 2006–January 2008): 2,245 (68%) of baseline cohort.

SWAN is currently fielding a non-funded interim visit 11 and expects to be complete by January 2009.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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or infertility and menstrual history (including cycle length and variability and premenstrual symptoms), family history, medical history (including chronic diseases, fractures, urinary incontinence, and surgeries), medication use, weight history, physical and psychological or emotional symptoms of midlife, initiation and discontinuation of hormone replacement therapy, and use of complementary and alternative therapies. Most of these factors, excluding ones (such as family history) that are unlikely to change, are assessed annually. Information pertaining to diet is obtained periodically.

Bone mineral density measurements are obtained annually at five of the study sites. They measures include low-energy x-rays of the lumbar spine, hip, and whole body, which will provide an indication of bone strength and predisposition to sustain fractures. Blood and urine samples that were obtained at baseline and at the first two annual followup visits are being studied to assess biochemical markers of bone turnover. Bone-turnover markers indicate how quickly bone breakdown and formation are taking place and may help to predict bone loss. Body composition (lean and fat mass) and its changes are also assessed annually in these same study participants.

Physical measurements (waist and hip measurements, height, and weight) and cardiovascular measurements are obtained annually at all seven study sites in all ethnic groups. Lipids, lipoproteins, glucose, insulin, and clotting factors are measured in blood samples every other year.

Markers of ovarian aging—including follicle-stimulating hormone, luteinizing hormone, estradiol, inhibin-B, and estrone—are being assessed. Additional biochemical determinations include dehydroepiandrosterone sulfate, sex hormone-binding globulin, and testosterone. All those assessments take place annually in all ethnic groups. Thyroid-stimulating hormone is also measured periodically but not at every visit. At each annual visit, participants are surveyed about psychosocial issues, such as quality of life, depression, stress, social support, and life events. Information pertaining to sexual function is obtained with a confidential self-administered questionnaire.

A biologic specimen bank for SWAN contains blood and urine specimens collected at each study participant’s annual visit. At the time of this writing, a deoxyribonucleic acid (DNA) repository, containing whole blood and sputum pellets and immortalized cells was being developed; about 50% of the anticipated samples had been collected.

Analysis

A mix of univariate, bivariate, and multivariate analyses using logistic regression and linear regression models are being conducted. A Cox proportional hazards model is being used to account for uneven followup.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Findings

Select findings from SWAN are summarized in Table C-9.

TABLE C-9 Select Findings (by outcome)a

Age at Natural Menopause

Gold et al., 2001

In a cross-sectional telephone survey of 14,620 SWAN participants, overall, median age at natural menopause was found to be 51.4 years, “after adjustment for smoking, education, marital status, history of heart disease, parity, race/ethnicity, employment, and prior use of oral contraceptives. Current smoking, lower educational attainment, being separated/widowed/divorced, nonemployment, and history of heart disease were all independently associated with earlier natural menopause, while parity, prior use of oral contraceptives, and Japanese race/ethnicity were associated with later age at natural menopause.”

Body-Mass Index and Menopause, Hormone Use, and Ethnicity

Matthews et al., 2001

In a cross-sectional telephone survey of participants at seven SWAN sites, “compared to premenopausal women (covariate adjusted M = 27.3), women reporting a surgical menopause (M = 28.2) or being in the perimenopausal transition (M = 27.7 for early and 27.9 for late perimenopause) had higher BMI. Women reporting a natural menopause (M = 27.4) did not have a higher BMI than premenopausal women, after adjusting for chronological age and other covariates. Hormone use was associated with lower BMI (M = 26.5 vs 27.3). A comparison of effect sizes showed that menopausal status (F = 13.1), followed by chronological age (F = 24.0), were the least powerful predictors of BMI, whereas the more powerful predictors were physical activity level (F = 1377.1) and ethnicity (F = 400.5).”

Bone Density

Association of Endogenous Hormone Concentrations with Bone Mineral Density

Sowers et al., 2003

In 2,336 women, “serum logFSH concentrations were inversely correlated with BMD (r = –10 for lumbar spine [95% confidence interval (CI): –0.13, –0.06] and r = –0.08 for femoral neck (95% CI: –0.11, –0.05). Lumbar spine BMD values were approximately 0.5% lower for each successive FSH quartile. There were no significant associations of BMD with serum estradiol, total testosterone, FEI or FAI, respectively, after adjusting for covariates. BMD tended to be lower (p values = 0.009 to 0.06, depending upon the skeletal site) in women classified as perimenopausal versus premenopausal, after adjusting for covariates.” Serum FSH, but not serum estradiol, testosterone, or SHBG, were significantly associated with BMD.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Ethnic Variation in Bone Density in Premenopause and Early Perimenopause

Finkelstein et al., 2002

Using dual-energy x-ray absorptiometry assessed lumbar spine and femoral neck BMD in 2,277 (for the lumbar spine) and 2,330 (for the femoral neck) SWAN participants. Before adjustment for covariates, “lumbar spine and femoral neck BMDs were highest in African-American women, next highest in Caucasian women, and lowest in Chinese and Japanese women. Unadjusted lumbar spine and femoral neck BMDs were 7–12% and 14–24% higher, respectively, in African–American women than in Caucasians, Japanese, or Chinese women. After adjustment, lumbar spine and femoral neck BMD remained highest in African–American women, and there were no significant differences between the remaining groups. When BMD was assessed in a subset of women weighing less than 70 kg and then adjusted for covariates, lumbar spine BMD became similar in African-American, Chinese, and Japanese women and was lowest in Caucasian women. Adjustment for bone size increased values for Chinese women to levels equal to or above those of Caucasian and Japanese women. Among women of comparable weights, there are no differences in lumbar spine BMD among African-American, Chinese, and Japanese women, all of whom have higher BMDs than Caucasians. Femoral neck BMD is highest in African-Americans and similar in Chinese, Japanese, and Caucasians.”

Sport and Home Physical Activity and Bone Density

Greendale et al., 2003

“BMD was measured with Hologic 2000 or 4500A densitometers. Physical activity was assessed with the Kaiser Physical Activity Scale, which rates each domain of activity between 1 (low) and 5 (high)…. The mean and median values of sport, home, work, and active living each approximated the midpoint of the scale and did not differ substantially among ethnic groups. Scores for each domain of activity were not highly correlated, with r values ranging between –0.03 and 0.33. Independent of age, body mass index, ethnic group, alcohol use, dietary calcium, smoking, menopause status, SWAN site, and other domains of physical activity, higher sport activity was statistically significantly associated with greater BMD at the lumbar spine (P = 0.008), femoral neck (P = 0.0002), and total hip ( P< 0.0001). More home physical activity was associated with higher BMD at the spine (P = 0.049) and femoral neck (P = 0.008).”

Vasomotor Symptoms and Bone Mineral Density

Crandall et al., 2009

In an analysis of data from baseline to annual followup visit 5 for 2,213 participants, “after controlling for age, time within each menopausal stage, race/ethnicity, study site, and baseline menopausal stage, postmenopausal women with any VMS had lower lumbar (0.008 g/cm2 lower, P = 0.001) and lower total hip (0.005 g/cm2 lower, P = 0.04) BMD than did postmenopausal women without VMS. Compared with early perimenopausal women without VMS, early perimenopausal women with any VMS had lower femoral neck BMD (0.003 g/cm2 lower, P = 0.0001). Premenopausal women with any VMS had lower femoral neck BMD (0.003 g/cm2 lower, P = 0.03) compared with premenopausal women without VMS.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Finkelstein et al., 2008

Assessment of bone mineral density (BMD) of the lumbar spine and total hip across a maximum of 6 annual visits was done in 1,902 participants. “There was little change in BMD during the pre- or early perimenopause. BMD declined substantially in the late perimenopause, with an average loss of 0.018 and 0.010 g/cm2·yr from the spine and hip, respectively (P < 0.001 for both). In the postmenopause, rates of loss from the spine and hip were 0.022 and 0.013 g/cm2·yr, respectively (P < 0.001 for both). During the late peri- and postmenopause, bone loss was approximately 35–55% slower in women in the top vs the bottom tertile of body weight. Apparent ethnic differences in rates of spine bone loss were largely explained by differences in body weight.”

Cancer Screening

Depressive-Symptom Burden as a Barrier to Screening for Breast and Cervical Cancers

Pirraglia et al., 2004

“At baseline, 75.6% (2493 of 3297) had a low depressive symptom burden (CES-D score <16, referent), 9.5% (312 of 3297) had a moderate burden (CES-D 16–20), and 14.9% (492/3297) had a high burden (CES-D ≥ 21). Women with a high depressive symptom burden had, in the subseqent year, significantly lower odds of mammography (OR 0.84, 95% CI 0.73–0.97) but not Pap smear (OR 0.88, 95% CI 0.76–1.03). There was not a significant dose-response relationship between depressive symptom burden and screening.”

Limited English Proficiency and Breast and Cervical Cancer Screening

Jacobs et al., 2005

“Reading and speaking only a language other than English and reading and speaking another language more fluently than English, were significantly and negatively associated with receipt of breast and cervical cancer screening in unadjusted models. Although these findings were attenuated in adjusted models, not speaking English well or at all remained negatively associated with receipt of cancer screening.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Cardiovascular

Application of National Screening Criteria for Blood Pressure and Cholesterol to Perimenopausal Women

Derby et al., 2006

“National screening guidelines for hypertension and cholesterol were applied to a sample of perimenopausal women (N = 1349) in the Study of Women Across the Nation (SWAN). To reduce low-density lipoprotein, lifestyle modification was indicated in 9.5% of patients and drug therapy in 5%. Chinese and Japanese women were least likely and African Americans were most likely to require interventions. Among all women, 27% were prehypertensive, 23% were hypertensive (blood pressure > 140/90 mm Hg or treated), and 9.1% were untreated hypertensive. Untreated hypertension was lowest among Japanese and Chinese and highest among Hispanic and African–American women. Among all hypertensives, 60.5% were treated and only 58.5% of those treated were controlled. Control rates were lowest among African Americans and Hispanics. In this relatively low-risk population, a significant proportion of women with hypertension or hypercholesterolemia were either not treated, not treated adequately, or had borderline risk factors that would benefit from lifestyle interventions to prevent the need for future drug treatment.”

Artery Calcification in Women with a History of Major Depression

Agatisa et al., 2005

In a sample of 210 participants from 1 SWAN study site, coronary calcification “using electron beam technology was found in 103 women (49%) and aorta calcification in 144 women (54%); high calcification scores were set at approximately 75% of the sample distribution (ie, at ≥ 10 for the coronary calcium score [n = 49 women] and at> 100 for the aorta calcium score [n = 53 women]). Women with a history of recurrent major depression (n = 53) were more likely to have any coronary calcification or calcification in the high category at either site compared with women with a history of a single episode of depression or no depression. After stepwise forward adjustment for cardiovascular risk factors and sociodemographic characteristics, a history of recurrent major depression, compared with a single episode or no history, was associated with odds ratios (ORs) of 2.46 (95% confidence interval [CI], 1.06–5.67) for any coronary calcification, 2.71 (95% CI, 1.08–6.81) for high coronary calcification, and 3.39 (95% CI, 1.34–8.63) for high aortic calcification. Further adjustments for waist-hip ratio reduced the association between history of recurrent depression and any calcification (OR, 2.24; 95% CI, 0.94–5.32) and high calcification (OR, 2.31; 95% CI, 0.89–5.99).”

Chronic Exposure to Everyday Discrimination and Coronary Artery Calcification in Black Women

Lewis et al., 2006

In a sample of 181 African American women, “chronic exposure to discrimination was significantly associated with the presence of CAC in unadjusted logistic regression analyses (p = .007) and after adjustment for demographics (p = .01), standard cardiovascular risk factors (p = .02), and Body Mass Index (BMI) (p = .05). In contrast, recent discrimination was only marginally associated with the presence of CAC in both unadjusted (p = .06) and fully adjusted logistic regression models (p = .08). Persistent exposure to racial/ethnic discrimination was not more strongly associated with CAC compared with other types of discrimination in either unadjusted or adjusted models.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Concentrations of Sex Steroid and Cardiovascular Disease Measures

Sowers et al., 2008

In a comparison of sex steroid and cardiovascular profiles at the 5-year followup visit, “users of HT had 50% higher levels of sex hormone-binding globulin (P < .001 for both HT groups), which limits binding of sex steroids to their receptors, and higher excreted estrone metabolites (more than 60%; P < .001 for both HT groups) than premenopausal or postmenopausal women. These findings were, in turn, associated with higher levels of F2a-isoprostanes, an oxidative stress measure, than in premenopausal women. The HT users had a more favorable ratio of high-density to low-density lipoprotein cholesterol than did premenopausal or postmenopausal women (P < .01), but higher triglyceride levels (P < .01).”

Effects of Race and Depressive Symptoms on Artery Calcification

Lewis et al., 2009

“In linear regression models adjusted for race, depressive symptoms were associated with a greater amount of aortic calcification (β = 0.03, p = .01), and there was a significant race × depressive symptoms interaction (β = 0.07, p = .006). Findings for depressive symptoms (odds ratio (OR) = 1.03, 95% Confidence Interval (CI) = 1.0–1.06, p = .07), and the race × depressive symptoms interaction (OR = 1.1, 95% CI = 1.01–1.18, p = .01) were similar in race-adjusted multinomial logistic regression models predicting high levels of aortic calcification. Race-specific models revealed a significant association between depressive symptoms and aortic calcification in African American, but not white women. Additional adjustments for education, study site, and CHD risk factors did not alter these results. Depressive symptoms were not associated with coronary calcification for women of either racial group.”

Ethnic Variation in Cardiovascular Risk-Factor Burden

Matthews et al., 2005

Framingham risk score and number of risk factors in the top quartile of the distribution of risk factors not included in the Framingham score (called composite burden) were calculated. “The unadjusted mean values for the two summary scores were higher among African Americans and Hispanics than other groups. Statistical adjustments for education and geographical site accounted for a majority of the ethnic differences, with an additional small effect of lifestyle for the composite burden score. Largest ethnic differences were apparent for waist circumference, lipoprotein(a), high-sensitivity C-reactive protein, and untreated blood pressure.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Ethnic Variation in Hypertension

Lloyd-Jones et al., 2005

“Examined the prevalence of hypertension (defined as systolic ≥140 or diastolic ≥90 mm Hg or receiving treatment), treatment, and control (to <140/<90 mm Hg) among 3,292 women, 46.9% were white, 28.3% were black, 8.7% were Hispanic, 7.6% were Chinese, and 8.5% were Japanese. Among these 5 ethnic groups, respectively, there was substantial variation in prevalence of normal blood pressure levels (<120/<80 mm Hg; 59.9%, 35.4%, 16.8%, 67.2%, and 63.7%) and hypertension (14.5%, 38.1%, 27.6%, 12.8%, and 11.0%). After multivariable adjustment, hypertension prevalence was 2 to 3x higher among black and Hispanic women but similar among Chinese and Japanese women compared with white women. Among hypertensive participants, prevalence of antihypertensive treatment was highest among blacks (58.9%) and whites (55.2%) and lowest among Chinese (34.4%). Prevalence of control to goal blood pressure levels was highest among whites (43.0%) and Japanese (38.7%) and markedly lower among Hispanic women (11.4%). Compared with whites, black and Hispanic women have significantly higher prevalence of hypertension independent of other factors, whereas Chinese and Japanese women have similar prevalence. Treatment and control rates vary considerably across ethnicities.”

Hot Flashes and Subclinical Cardiovascular Diseases

Thurston et al., 2008a

“Cross-sectional associations were evaluated with linear regression and partial proportional odds models. Hot flashes were associated with significantly lower flow-mediated dilation (β = –1.01; SE, 0.41; P = 0.01) and greater coronary artery (odds ratio, 1.48; 95% confidence interval, 1.04 to 2.12) and aortic (odds ratio, 1.55; 95% confidence interval, 1.10 to 2.19) calcification in age- and race-adjusted models. Significant associations between hot flashes and flow-mediated dilation (β = –0.97; SE, 0.44; P = 0.03) and aortic calcification (odds ratio, 1.63; 95% confidence interval, 1.07 to 2.49) remained in models adjusted for cardiovascular disease risk factors and estradiol.”

Lifetime History of Depression and Carotid Atherosclerosis

Jones et al., 2003

In 336 participants at one SWAN study site, “lifetime history of major depression was associated with plaque, and substance abuse was related to intima-media thickness. Lifetime history of an anxiety disorder was not associated with either measure. After controlling for standard cardiovascular risk factors, only the association between major depression and plaque was maintained. The risk of plaque was 2-fold in women with a lifetime history of recurrent major depressive episodes relative to women with no history of depression (odds ratio = 2.30; 95% confidence interval, 1.10–4.82). Lifetime history of a single major depressive episode was not associated with plaque.”

Cognitive Functioning

Cognitive Functioning in the Menopausal Transition

Meyer et al., 2003

In 803 participants for whom cognitive assessments were available, the authors found small but significant increases over time during the premenopausal and perimenopausal phases. “This trend was not accounted for by chronological age, education, family income, ethnicity, or baseline self-perceived health.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Depression

Depressive Symptoms During the Menopause Transition

Bromberger et al., 2007

“At baseline, 23% of the sample (N = 3302) had elevated CES-D scores (≥ 16). A woman was more likely to report CES-D ≥16 when she was early peri-, late peri-, postmenopausal or currently/formerly using hormone therapy (HT), relative to when she was premenopausal (OR range 1.30 to 1.71). Effects were somewhat stronger for women with low CES-D scores at baseline. Health and psychosocial factors increased the odds of having a high CES-D and in some cases, were more important than menopausal status.”

Predictors of First Lifetime Episodes of Major Depression in Midlife

Bromberger et al., 2009

Over 7 years of followup, 42 (15.8%) women met criteria for a diagnosis of major depression. Frequent vasomotor symptoms (VMS; hot flashes and/or night sweats) (HR 2.14, p = 0.03) were a significant predictor of major depression in univariate analyses. After simultaneous adjustment for multiple predictors in Cox proportional hazards analyses, frequent VMS were no longer significant; lifetime history of an anxiety disorder (HR 2.20, p = 0.02) and role limitations due to physical health (HR 1.88, p = 0.07) at baseline and a very stressful life event (HR 2.25, p = 0.04) prior to depression onset predicted a first episode of major depression.

Racial and Ethnic Differences in Prevalence of Depressive Symptoms

Bromberger et al., 2004

“Racial/ethnic differences in unadjusted and adjusted prevalence of significant depressive symptoms (score ≥ 16 on the Center for Epidemiologic Studies Depression [CES-D] Scale) were assessed with univariate and multiple logistic regressions. Twenty-four percent of the sample had a CES-D score of 16 or higher. Unadjusted prevalence varied by race/ethnicity (P < .0001). Hispanic and African American women had the highest odds, and Chinese and Japanese women had the lowest odds, for a CES-D score of 16 or higher. After adjustment for covariates, racial/ethnic differences overall were no longer significant.”

Eating Disorders

Prevalence and Selected Correlates of Eating Disorder Symptoms

Marcus et al., 2007

“The sample included 589 pre- and early perimenopausal African American, Hispanic, and White women…. Rates of regular binge eating, dissatisfaction with eating patterns, and marked fear of weight gain were 11, 29.3, and 9.2%, respectively. African Americans were more likely than were Whites to report fasting. In multivariable analyses, high body mass index (or waist circumference), depressive symptoms, past depression, and history of childhood/adolescence abuse were significantly associated with the Binge Eating and Preoccupation with Eating, Shape and Weight subscale scores.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Health-Related Quality of Life and Functioning

Association of Menopause with Physical Functioning

Sowers et al., 2001

In a cross-sectional study of 14,427 women, “80.8% of women reported no limitation in physical functioning, whereas 10% of women had some limitation, and 9.2% of women indicated having substantial limitation. Women with substantial limitation in physical functioning had double the prevalence odds ratio (POR = 2.02; 95% confidence interval (CI) = 1.64–2.49) of having surgical menopause and 76% greater odds (POR = 1.76; 95% CI = 1.38–2.24)) of using hormones, compared with women with no limitation. Compared with those without limitation, women with substantial limitation in physical functioning had 56% greater odds (POR = 1.56; 95% CI = 1.23–1.97)) of being naturally postmenopausal and a 41% greater odds (POR = 1.41; 95% CI = 1.17–1.70) of being perimenopausal, relative to being premenopausal and after adjusting for other variables.”

Dietary Intake and Functional Limitations

Tomey et al., 2008

Among 2,160 women, aged 42–52 years, from 6 SWAN study sites, the prevalence of moderate and substantial functional limitationsb was 31% and 10%, respectively. “Women in the highest quartile of cholesterol intake had 40% greater odds (odds ratio = 1.4, 95% confidence interval: 1.1, 1.8) of being more limited versus those in the lowest quartile. Women in the highest quartile of fat and saturated fat intakes were 50% and 60% more likely to be more limited, with respective odds ratios of 1.5 and 1.6 (95% confidence intervals: 1.2, 2.0 and 1.2, 2.1) versus those in the lowest quartiles. Lower fruit, vegetable, and fiber intakes were related to reporting greater functional limitations.”

Health-Related Quality of Life

Avis et al., 2003

“In unadjusted, but not adjusted, analyses, significantly more early perimenopausal women, as compared with premenopausal women, were classified as having impaired functioning on each of the 5 subscales … (HRQL was assessed with 5 subscales from the Short Form-36; impaired functioning was defined as being in the 25% most impaired on a subscale)…. For 4 of the subscales, the effect of menopausal status was explained by menopause-related symptoms. There were significant ethnic group differences across all 5 subscales in unadjusted analyses. Ethnicity was no longer significant for the Vitality or Role-Emotional subscales when adjusted for health variables or for the Role-Physical subscale when analyses were adjusted for socioeconomic status, health, lifestyle, or social circumstances. Ethnicity remained significant for the Bodily Pain and Social Functioning subscales, even in adjusted analyses.”

History of Depression and Current Health and Functioning

Bromberger et al., 2005

“Women (24.3%) had a history of major depression: 14.9% single episode, 9.4% recurrent and 12.6% had minor depression. In multivariable logistic regression analyses, compared to no history of depression, any past depression predicted high body pain [odds ratios (ORs), 1.8–2.3; 95% CIs, 1.05–4.02]. Recurrent depression predicted poor social functioning (OR, 2.1; 95% CI, 1.20–3.80) and current treatment for back pain (OR, 4.2; 95% CI, 1.78–9.82). Minor depression predicted mood symptoms (OR, 1.9; 95% CI, 1.16–3.20).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Hormone Therapy and Health-Related Quality of Life

Hess et al., 2008

“Of the 3,102 participants, 813 initiated HT during the 6-year follow-up period. At baseline, women who subsequently initiated HT were more likely to report poor role physical functioning, higher socioeconomic status, and frequent symptoms and to be white. In longitudinal analyses, women reporting poor role emotional and physical functioning at the visit before initiation were less likely to subsequently initiate (hazard ratio [95% CI]: 0.76 [0.62–0.91] and 0.58 [0.47–0.71]; P < 0.01 and < 0.0001, respectively), and initiation was associated with subsequent poorer role physical functioning (odds ratio [95% CI]: 1.26 [1.02–1.56]; P = 0.03). Among HT initiators, frequent symptom reporters showed improvements in vitality (+2.7) compared with other initiators (–2.9) (P < 0.01).”

Influence of Menopause, Health Status, and Psychosocial and Demographic Factors on Quality of Life

Avis et al., 2004

Based on analyses of data from 13,874 participants in the cross-sectional study, “in unadjusted analyses early perimenopausal women reported lower QOL compared with premenopausal women, but menopausal status was no longer associated with QOL when analyses were adjusted for other variables. In multivariable models, being married and having low levels of perceived stress were associated with better QOL across all racial/ethnic groups. While there were many consistencies across racial/ethnic groups,” the researchers “also found that the nature of the associations between QOL and education, marital status, perceived stress and social support varied across racial/ethnic groups.”

Role of Health Conditions and Behavioral and Environmental Factors in Functional Limitations

Pope et al., 2001

In a cross sectional study of 16,065, almost 20% reported physical-functioning limitations. “Functional limitations were associated with numerous disease conditions, including high blood pressure, diabetes, heart attack or angina, arthritis, osteoporosis, and cancer, and with several behavioral and environmental risk factors, including body mass index, difficulty paying for basics, and high levels of perceived stress. Consistent with findings in older women, this study shows that in addition to health conditions, potentially modifiable risk factors including high body mass index, difficulty paying for basics, and high levels of stress are associated with physical-functioning limitations of women at midlife.”

Hysterectomy

Ethnic Differences in Hysterectomy for Benign Conditions

Powell et al., 2005

“In a phone survey conducted at random on 15,160 women, ages 40–55, from seven US cities. Subjects were 49.9% Caucasian, 28.1% African American, 12.3% Hispanic, and 9.8% Asian American. Ethnicity was associated with past hysterectomy (odds ratio [OR]: Caucasian = 1.0, African American = 1.66; confidence interval [CI] = 1.46–1.88, Hispanic = 1.64, CI = 1.29–2.07; Asian American = 0.44, CI = 0.34–0.56), after adjustment for age, education, fibroids, body mass index, marital status, smoking, geographic site, and country of education.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Racial Differences in Hysterectomy for Benign Conditions

Weiss et al., 2009

“During 9 years of follow-up, 203 African-American and Caucasian women reported a hysterectomy, 90 with evidence of uterine leiomyomas. Women were surveyed regarding their overall perceived health before and after hysterectomy, presenting symptoms, and their motivations for surgery. Serum estradiol and testosterone levels were measured. Uterine weight at time of hysterectomy and clinical pathology were determined via medical record abstraction. Previously diagnosed leiomyomas were presenting symptoms more frequently in African–American women than Caucasian women (85% vs 63%; p = .02). African–American women had less prolapse than Caucasian women (0% vs 10%; p = 0.04). Chronic pain was a more frequent reason for hysterectomy in African–American women than in Caucasian women (49% vs 29%; p = .05). There were no differences between the groups in levels of estradiol or testosterone. African–American women had almost twice the uterine weight as that of Caucasian women (448 vs 240 g; p = .0005).”

Mammographic Density

Mammographic Density Among Racial and Ethnic Groups

Habel et al., 2007

“Age-adjusted mean percent density was highest for Chinese (52%) and lowest for African American (34%) women (n = 801). After additional adjustment for body mass index, menopause status, age at first birth, breast-feeding duration, waist circumference, and smoking, African Americans had the highest mean percent density (51%) and Japanese women had the lowest (39%). In contrast, the area of dense tissue was highest for African Americans and similar for white, Japanese, and Chinese women. Less acculturated Chinese and Japanese women tended to have a larger area of density and a higher percent density.”

Menstrual and Reproductive Factors in Relation to Mammographic Density

Butler et al., 2008

“From multivariable linear regression, the following menstrual or reproductive factors were independently associated with percent mammographic density (area of dense breast/breast area): older age at menarche (beta = 10.3, P < 0.01, for > 13 vs < 12 years), premenstrual cravings and bloating (beta = –3.36, P = 0.02), younger age at first full-term birth (beta = –8.12, P < 0.01 for <or = 23 years versus no births), greater number of births (beta = –6.80, P < 0.01 for >or = 3 births versus no births), and premenopausal status (beta = 3.78, P < 0.01 versus early perimenopausal). Only number of births remained associated with percent density after adjustment for age, race/ethnicity, study site, body mass index (BMI), and smoking. In addition, stratified analyses revealed that the association with number of births was confined to women within the lowest BMI tertile (beta = –12.2, P < 0.01 for >or = 3 births versus no births).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Physical Activity and Mammographic Density

Oestreicher et al., 2008

In a cohort 772 pre- and early perimenopausal women, “multivariable linear regression was used to examine the association between two measures of mammographic density (percent density and area of density) and mutually exclusive components of recent physical activity (sports, household/caregiving and work activity, active living). After adjusting for race/ethnicity, menopausal status, parity, past use of hormones, body mass index, waist circumference and education, nonsignificant inverse associations for percent mammographic density and the highest versus the lowest category of each of the physical activity domains were observed. For example, the adjusted beta for active living = –2.62, 95% confidence interval (Cl) (–5.84, 0.60). Nonsignificant inverse associations also were observed for area of density and each physical activity domain except work activity. However, most associations were nonlinear.”

Markers of Ovarian Aging

Effects of Age, Ethnicity, and Body-Mass Index on Change in Estradiol and Follicle-Stimulating Hormone During the Menopausal Transition

Randolph et al., 2004

“Serum E2 concentrations decreased significantly with age, with a steeper decline at higher ages. FSH concentrations increased significantly with age, with a steeper increase at higher ages. Similar patterns in the decline of E2 and the increase in FSH with age were found across ethnic groups, but the levels of these hormones differed by race/ethnicity. Specifically, over time, Chinese and Japanese women had lower E2 concentrations but similar FSH levels, compared with Caucasian women, and African American women had higher FSH concentrations but comparable E2 levels with those of Caucasian women. These ethnic differences in E2 and FSH were independent of menopausal status. The effect of BMI on serum E2 and FSH levels varied by menopausal status. Increasing BMI was associated with decreasing concentrations of E2 among premenopausal and early perimenopausal women but was associated with increasing concentrations of E2 among late perimenopausal and postmenopausal women. Increasing BMI was associated with decreasing concentrations of FSH, with the effect of BMI becoming larger as women transitioned through menopause.”

Factors Related to Declining Luteal Function

Santoro et al., 2008

In 848 women, ovulatory-appearing cycles declined from 80.9% at baseline to 64.7% by the third assessment (H3). “Cycles presumed anovulatory and not ending with bleeding by 50 d (anovulatory/nonbleeding) increased from 8.4 to 24% by H3 and were associated with progress to early perimenopause [odds ratio (OR) = 2.66; confidence interval (CI) = 1.17–6.04] or late perimenopause (OR = 56.21; CI = 18.79–168.12; P < 0.0001), African-American ethnicity (OR = 1.91; CI = 1.06–3.43), and less than high school education (OR = 3.51; CI = 1.62–7.62). Anovulatory cycles ending with bleeding remained at about 10% from baseline to H3; compared with ovulatory cycles, they were associated with obesity (OR = 4.68; CI = 1.33–16.52) and more than high school education (OR = 2.12; CI = 1.22–3.69; P = 0.02). Serum estradiol in both the highest and lowest categories was associated with anovulatory/nonbleeding collections. Pregnanediol glucuronide decreased 6.6% for each year on study. Insulin sensitivity measures did not relate strongly to menstrual cycle hormones.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Predictors of Onset of Final Menses

Santoro et al., 2007

“A total of 2,662 women, of whom 706 had an observed FMP, were included. Age, menstrual cycles that had become farther apart (HR = 2.56, 95% CI = 1.94–3.39) or more variable (HR = 1.79, 95% CI = 1.45–2.21), and current smoking (HR = 1.68, 95% CI = 1.35–2.08) were all associated with shorter time to the FMP. Higher (log) follicle-stimulating hormone (HR = 2.32, 95% CI = 2.02–2.67) was related to a shorter time to the FMP, but the highest estradiol category (≥ 100 pg/mL [367 pmol/L]) was associated with an earlier onset of the FMP (HR = 2.16, 95% CI = 1.63–2.89). The number of vasomotor symptoms was related to an earlier FMP, whereas higher physical activity and educational levels were associated with a later FMP.”

Relationship of Bleeding Patterns to Daily Reproductive Hormones

Van Voorhis et al., 2008

In a sample of 804 women, “approximately 20% of all cycles were anovulatory. Short cycle intervals (fewer than 21 days) were common early in the menopause transition and were associated with anovulation (44%). Long cycle intervals (more than 36 days) also were associated with anovulatory cycles (65%). Both short (1–3 days) and long (more than 8 days) duration of menstrual bleeding were associated with anovulation (18% and 23%, respectively). Women with anovulatory cycles were less likely to report heavy menstrual bleeding as compared with those with ovulatory cycles. Heavy bleeding was not associated with steroid hormone concentrations but was associated with obesity and with the self-reported presence of leiomyomata.”

Vasomotor Symptoms and Hypothalamic and Ovarian Function

Skurnick et al., 2009

In 159 women with anovulatory cycles anovulation did not predict menopause within 2 years. Vasomotor symptoms occur before menopause, as experienced by 73% of the women. Vasomotor symptoms were not related to cycle pattern.

Menopause Symptoms

Abdominal Adiposity and Hot Flashes

Thurston et al., 2008b

“Every 1-SD increase in total (odds ratio [OR] = 1.28; 95% CI: 1.06–1.55) and subcutaneous (OR = 1.30; 95% CI: 1.07–1.58) abdominal adiposity was associated with increased odds of hot flashes in age- and site-adjusted models. Visceral adiposity was not associated with hot flashes. Associations were not reduced when models included reproductive hormone concentrations.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Adiposity and Vasomotor Symptoms

Thurston et al., 2008d

Among 1,776 participants aged 47–59 years with an intact uterus and at least one ovary who completed bioelectrical impedance analysis for assessment of body composition at the sixth annual study visit (2002–2004), “a higher percentage of body fat was associated with increased odds of reporting vasomotor symptoms (per standard deviation increase in percent body fat, odds ratio = 1.27, 95% confidence interval: 1.14, 1.42) in age- and site-adjusted models. Associations persisted in fully adjusted models and were not reduced when models included reproductive hormones.”

Childhood Abuse or Neglect and Vasomotor Symptoms

Thurston et al., 2008c

Childhood abuse and neglect were measured once with the Child Trauma Questionnaire among 322 white and African American SWAN participants. “Vasomotor symptoms (any/none hot flashes, night sweats) were reported annually over 8 years…. Childhood abuse or neglect was associated with increased reporting of hot flashes (odds ratio = 1.73, 95% CI: 1.23–2.43) and night sweats (odds ratio = 1.75, 95% CI: 1.26–2.43) in age-adjusted models. Results persisted in multivariable models and across several types of abuse and neglect.”

Differences in Symptoms of Menopause by Race and Ethnicity

Green and Santoro, 2009

“Most [menopause] symptoms varied by ethnicity. Vasomotor symptoms (hot flashes) were more prevalent in African-American (46.5%) and Hispanic (49.4%) women than non-Hispanic white and Asian women, and were also more common in women with greater BMI, challenging the widely held belief that obesity is protective against vasomotor symptoms. Vaginal dryness was present in 30–40% of SWAN participants at baseline, and was most prevalent in Hispanic women. Among Hispanic women, menopause symptoms varied by country of origin. Acculturation appeared to play a complex role in menopausal symptomatology,” with less acculturated Hispanic women reporting more menopause symptoms.

Lifestyle and Demographic Factors in Relation to Vasomotor Symptoms

Gold et al., 2004

“With the exception of age and follicle-stimulating hormone levels, all covariates varied significantly by race/ethnicity. Despite similar age distributions, fewer Chinese (37.7 percent) and Japanese (42.6 percent) women were in the early perimenopause than African-American (50.2 percent), Caucasian (46.9 percent), or Hispanic (43.5 percent) women at baseline, consistent with findings from SWAN’s screening data regarding ethnic differences in age at menopause (56). In addition, significantly more African-American (46.5 percent) and Hispanic (49.4 percent) women reported vasomotor symptoms, and fewer Japanese (34.3 percent) and Chinese (28.9 percent) women reported vasomotor symptoms than did Caucasian (36.6 percent) women (p < 0.0001). Previously SWAN showed that nutrient intakes also varied considerably by race/ethnicity, with dietary antioxidant and fiber intake highest in Chinese women, phytoestrogen intake highest in Japanese women, fat and total calorie intake highest in African–American women, and any alcohol intake highest in Caucasian and lowest in Chinese women.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Relation of Demographic and Lifestyle Factors to Menopausal Symptoms

Gold et al., 2000

A cross-sectional survey was conducted during 1995–1997. “The largest adjusted prevalence odds ratios for all symptoms, particularly hot flashes or night sweats (odds ratios = 2.06–4.32), were for women who were peri- or postmenopausal. Most symptoms were reported least frequently by Japanese and Chinese (odds ratios = 0.47–0.67 compared with Caucasian) women. African-American women reported vasomotor symptoms and vaginal dryness more (odds ratios = 1.17–1.63) but urine leakage and difficulty sleeping less (odds ratios = 0.64–0.72) than Caucasians. Hispanic women reported urine leakage, vaginal dryness, heart pounding, and forgetfulness more (odds ratios = 1.22–1.85). Hot flashes or night sweats, urine leakage, and stiffness or soreness were associated with a high body mass index (odds ratios = 1.15–2.18 for women with a body mass index > or = 27 vs 19–26.9 kg/m2). Most symptoms were reported most frequently among women who had difficulty paying for basics (odds ratios = 1.15–2.05), who smoked (odds ratios = 1.21–1.78), and who rated themselves less physically active than other women their age (odds ratios = 1.24–2.33).”

Vasomotor Symptoms Among Racial and Ethnic Groups

Gold et al., 2006

In 3,198 women during 1996 through 2002, “rates of reports of any vasomotor symptoms and any symptoms for 6 or more days in the previous 2 weeks showed similar patterns according to race/ethnicity and change in menopausal status, although rates for the former were generally higher. The highest rates were observed among African American women across all stages of the perimenopausal transition [adjusted odds ratio [OR] = 1.63; 95% confidence interval [CI]=1.21, 2.20]. Asian women had the lowest rates in most stages of the transition. For all women combined, the transition to late perimenopause exhibited the strongest association with vasomotor symptoms (adjusted OR = 6.64; 95% CI = 4.80, 9.20). “Other risk factors were age (adjusted OR = 1.17; 95% CI=1.13, 1.21), having less than a college education (adjusted OR = 1.91; 95% CI = 1.40, 2.61), increasing body mass index (adjusted OR=1.03 per unit of increase; 95% CI = 1.01, 1.04), smoking (adjusted OR = 1.63; 95% CI = 1.25, 2.12), and anxiety symptoms at baseline (adjusted OR = 3.10; 95% CI = 2.33, 4.12).”

Metabolic Syndrome and Diabetes

Lifetime History of Major Depression and Development of Metabolic Syndrome

Goldbacher et al., 2009

“Participants were 429 (34.5% African-American) women.… Longitudinal generalized estimating equations (GEE) models indicated that, in women who were free of the metabolic syndrome at baseline, a lifetime major depression history or current major depressive episode at baseline was significantly associated with the onset and presence of the metabolic syndrome during the follow-up (odds ratio = 1.82; 95% Confidence Interval (CI) = 1.06–3.14). Survival analyses showed that, in women who were free of the metabolic syndrome at baseline, a lifetime major depression history or current major depressive episode at baseline predicted increased risk of developing the metabolic syndrome during the follow-up (hazard ratio = 1.66; 95% CI = 0.99–3.75). Lifetime history of alcohol abuse or dependence predicted incident metabolic syndrome and attenuated the association between depression and the metabolic syndrome in both models.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Menopause and the Metabolic Syndrome

Janssen et al., 2008

“By the final menstrual period, 13.7% of the women had new-onset MetS. Longitudinal analyses, centered at the final menstrual period, were adjusted for age at menopause, ethnicity, study site, marital status, education, body mass index, smoking, and aging. Odds of developing the MetS per year in perimenopause were 1.45 (95% confidence interval, 1.35–1.56); after menopause, 1.24 (95% confidence interval, 1.18–1.30). These odds were significantly different (P < .001). An increase in bioavailable testosterone or a decrease in sex hormone–binding globulin levels increased the odds.”

MetS, metabolic syndrome

Depressive Symptoms, Insulin Resistance, and Risk of Diabetes

Everson-Rose et al., 2004

“Mean baseline HOMA-IR was 1.31 (SD 0.86) and increased 0.05 units per year for all women (P < 0.0001). A total of 97 incident cases of diabetes occurred. Depression was associated with absolute levels of HOMA-IR (P < 0.04) but was unrelated to changes in HOMA-IR; associations did not vary by race. The association between depression and HOMA-IR was eliminated after adjustment for central adiposity (P = 0.85). Depression predicted a 1.66-fold greater risk of diabetes (P < 0.03), which became nonsignificant after adjustment for central adiposity (P = 0.12). We also observed a depression-by-race interaction (P < 0.05) in analyses limited to Caucasians and African Americans, the only groups with enough diabetes cases to reliably test this interaction. Race-stratified models showed that depression predicted 2.56-fold greater risk of diabetes in African Americans only, after risk factor adjustment (P = 0.008).”

Education and Ethnicity in Predicting the Development of Metabolic Syndrome

Scuteri et al., 2008

“At baseline, the prevalence of the metabolic syndrome was 21% (n = 673). Among 2,512 women without metabolic syndrome at baseline, 12.8% (n = 321) developed the metabolic syndrome during 5 years of follow-up. Both ethnicity and SES were significant univariate predictors of incident metabolic syndrome. In multivariate logistic regression models that included age at baseline, menopausal status and site, baseline smoking and alcohol consumption at follow-up visit 1, as well as baseline values of each of the components of the metabolic syndrome, only education was an independent predictor of incident metabolic syndrome.”

Musculoskeletal Pain

Musculoskeletal Pain and Menopausal Status

Dugan et al., 2006

“Participants were 2,218 women assessed from the Study of Women’s Health Across the Nation at the time of their third annual follow-up exam…. Prevalence of aches and pains was high, with 1 in 6 women reporting daily symptoms. Compared with premenopausal women, those who were early perimenopausal (P = 0.002), late perimenopausal (P = 0.002), or postmenopausal (P < 0.0001) reported significantly more aches and pains in age-adjusted analysis. With complete risk factor adjustment, postmenopausal women still reported significantly greater pain symptoms (P = 0.03) than did premenopausal women. Menopausal status was marginally related to consulting a healthcare provider for back pain.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Premenstrual Symptoms

Diet and Lifestyle Factors and Premenstrual Symptoms

Gold et al., 2007

Among 3,302 women, “most dietary factors were not related to PMSx. Fat intake was negatively associated with craving and bloating (adjusted odds ratio [AOR] = 0.56, p = 0.024), and fiber intake was positively associated with breast pain (AOR =1.39, p = 0.037). Alcohol intake was negatively associated with anxiety and mood changes (AOR = 0.63, p = 0.045) and headaches (AOR = 0.50, p = 0.009). Current smoking (AOR = 1.60, p = 0.028) and passive smoke exposure (AOR = 1.56, p = 0.050) were positively associated with cramps and back pain. Symptom reporting differed significantly by race/ethnicity. PMSx were also associated with comorbidities, early perimenopausal status, depressive symptoms, and symptom sensitivity.”

Sexual Function

Changes in Sexual Functioning During Menopausal Transition

Avis et al., 2009

In 3,302 participants, “with adjustment for baseline age, chronological aging, and relevant social, health, and psychological parameters, the odds of reporting vaginal or pelvic pain increased and desire decreased by late perimenopause. Masturbation increased at early perimenopause but declined during postmenopause. The menopausal transition was unrelated to other outcomes. Health, psychological functioning, and importance of sex were related to all sexual function outcomes. Age, race/ethnicity, marital status, change in relationship, and vaginal dryness were also associated with sexual functioning.”

Correlates of Sexual Function During Menopausal Transition

Avis et al., 2005

In 3,167 women not using hormones, “early perimenopausal women reported greater pain with intercourse than premenopausal women (P = 0.01), but the two groups did not differ in frequency of sexual intercourse, desire, arousal, or physical or emotional satisfaction. Variables having the greatest association across all outcomes were relationship factors, the perceived importance of sex, attitudes toward aging, and vaginal dryness. Despite controlling for a wide range of variables, we still found ethnic differences for arousal (P < 0.0001), pain (P = 0.03), desire (P < 0.0001), and frequency of sexual intercourse (P = 0.0003). African American women reported higher frequency of sexual intercourse than white women; Hispanic women reported lower physical pleasure and arousal. Chinese women reported more pain and less desire and arousal than the white women, as did the Japanese women, although the only significant difference was for arousal.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Sleep

Day-to-Day Reproductive Hormone Concentrations and Sleep

Kravitz et al., 2005

Using data from a single menstrual cycle from 630 SWAN participants, “average adjusted odds of reporting trouble sleeping were 29% higher in perimenopausal than in premenopausal women. The highest percentages of women in both menopausal groups reported trouble sleeping in the beginning or at the end of their cycle. After controlling for covariates, pregnanediol glucuronide level was associated with increased trouble sleeping in perimenopausal women and follicle-stimulating hormone level was associated with increased trouble sleeping in premenopausal women. Mood and vasomotor symptoms were the strongest and most consistent cocontributors to trouble sleeping.”

Race, Financial Strain, and Sleep

Hall et al., 2009

“Sleep was worse in African American women than Caucasian participants as measured by self-report, visual sleep stage scoring, and NREM EEG power. Slow wave sleep differences were also observed between Chinese and Caucasian participants. Racial differences persisted after adjustment for indices of SES. Although educational attainment was unrelated to sleep, financial strain was associated with decreased sleep quality and lower sleep efficiency. Financial strain-by-race interactions were not statistically significant, suggesting that financial strain has additive effects on sleep, independent of race.”

Sleep and the Menopausal Transition

Kravitz et al., 2003

In a cross-sectional survey of 12,603 women, “difficulty sleeping [in the past two weeks] was reported by 38%. Age-adjusted rates were highest in the late perimenopausal (45.4%) and surgically postmenopausal (47.6%) groups. Among ethnic groups, rates ranged from 28% in Japanese women to 40% in Caucasian women. In the multivariate analysis, menopausal status was significantly associated with difficulty sleeping. Ethnicity, vasomotor and psychological symptoms, self-perceived health and health behaviors, arthritis, and education also were significantly associated with difficulty sleeping.”

Sleep Disturbance During the Menopausal Transition

Kravitz et al., 2008

“Self-reported number of nights of difficulty falling asleep, staying asleep, and early morning awakening during the previous 2 weeks were obtained at baseline and 7 annual assessments. Random effects logistic regression was used to model associations between each of the 3 sleep measures and the menopausal transition, defined by bleeding patterns, vasomotor symptoms (VMS), and estradiol (E2) and follicle stimulating hormone (FSH) serum levels. Adjusted odds ratios (ORs) for difficulty falling asleep and staying asleep increased through the menopausal transition, but decreased for early morning awakening from late perimenopause to postmenopause. Naturally and surgically postmenopausal women using hormones, compared with those who were not, generally had lower ORs for disturbed sleep. More frequent VMS were associated with higher ORs of each sleep difficulty. Decreasing E2 levels were associated with higher ORs of trouble falling and staying asleep, and increasing FSH levels were associated with higher ORs of trouble staying asleep. Racial/ethnic differences were found for staying asleep and early morning awakening.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Urinary Incontinence

Factors Associated with Prevalent and Incident Urinary Incontinence

Waetjen et al., 2007

“Prevalent incontinence was 46.7%, and the average incidence was 11.1% per year.d Most women reported stress, but a higher proportion developed urge incontinence (15.9% vs 7.6% at baseline). African Americans (29.5%) and Hispanics (27.5%) had the lowest prevalence of incontinence; African Americans (11.6%) and Caucasians (13.4%) had the highest average annual incidence. Parity, diabetes, fibroids, and poor social support were associated with prevalent incontinence, while high body mass index, high symptom sensitivity, and poor health were associated with incident incontinence.”

Factors Associated with Worsening and Improving Urinary Incontinence

Waetjen et al., 2008

Among 2,415 women who reported monthly or more incontinence in self-administered questionnaires at baseline and during the first 6 annual followup visits (1995–2002), “over 6 years, 14.7% of incontinent women reported worsening, 32.4% reported improvement, and 52.9% reported no change in the frequency of incontinence symptoms.c Compared with premenopause, perimenopause and postmenopause were not associated with worsening incontinence; for example, early perimenopause was associated with improvement (odds ratio [OR] 1.19; 95% confidence interval [CI] 1.06–1.35) and postmenopause reduced odds of worsening (OR 0.80; 95% CI 0.66–0.95). Meanwhile, each pound of weight gain increased odds of worsening (OR 1.04; 95% CI 1.03–1.05) and reduced odds of improving (OR 0.97; 95% CI 0.96–0.98) incontinence.”

Predictors of Urinary Incontinence and Life Impact

Sampselle et al., 2002

“Incontinence severity was derived by multiplying frequency by volume leaked. Incontinence prevalence was 57%, with nearly 15% categorized as moderate and 10% as severe. Biologic factors constituted the most important risk for severity, specifically perimenopausal compared with premenepausal status (odds ratio [OR] 1.35), body mass index (OR 1.04), diabetes mellitus (OR 1.55), and current smoking (OR 1.38). Nonwhite groups had lower risk, but the relationship of ethnicity is complex. Severity was associated with likelihood of discussing with a health care provider, with bothersomeness, and with likelihood of nighttime voiding.”

aFor a list of all publications on the SWAN visit, see http://www.edc.pitt.edu/swan/public/Documents/PublicationsPresentations/Publication_List.doc (accessed August 16, 2010).

bWomen with scores on the Medical Outcomes Study Short Form 36 below the population norm (that is under 50 points) were classified as having substantial functional limitations, those with scores of 51–85 points were classified as having moderate limitations, and those with scores of 86–100 points were considered not limited.

cWorsening was defined as a reported increase and improving as a reported decrease in frequency of incontinence between annual visits.

dCases were urinary incontinence that occurred at least monthly.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

ABBREVIATIONS: AOR, adjusted odds ratio; ß, beta; BMD, bone-mineral density; BMI, body-mass index; CAC, coronary artery calcification; CES-D, Center for Epidemiologic Studies Depression; CHD, coronary heart disease; CI, confidence interval; d, day; E2, estradiol; EEG, electroencephalography; FAI, free androgen index; FEI, free estradiol index; FMP, final menstrual period; FSH, follicle-stimulating hormone; GEE, generalized estimating equations; H3, third assessment; HOMA-IR, homeostatic model assessment of insulin resistance; HR, hazard ratio; HT, hormone therapy; MetS, metabolic syndrome; NREM, non-rapid eye movement; OR, odds ratio; PMSx, premenstrual symptoms; POR, prevalence odds ratio; QOL, quality of life; SD, standard deviation; SE, standard error; SES, socioeconomic status; SHBG, sex hormone–binding globulin; SWAN, Studies of Women’s Health Across the Nation; VMS, vasomotor symptoms.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

BLACK WOMEN’S HEALTH STUDY

Study Objective and Design

The Black Women’s Health Study (BWHS) is a longitudinal followup study, the largest such study of the health of American black women yet conducted. The BWHS began in 1994 and continues today. Its purpose is to identify and evaluate causes and prevention of cancers, hypertension, type 2 diabetes, uterine fibroids, systemic lupus erythematosus, and other outcomes in black women.

Participant Enrollment

In 1995, 59,000 black women in all parts of the United States were enrolled through postal questionnaires. Most of the participants were subscribers to magazines commonly read by black women. A small number of participants were members of the National Education Association, US government workers, and nurses. Black women who were US residents 21–69 years old were eligible to participate.

Data Collection

Participants provided demographic and health information on a baseline questionnaire in 1995. Information captured included weight, height, smoking, drinking, contraceptive use, use of selected other medications, illnesses, reproductive history, physical activity, diet, and use of health care. Participants have since completed followup questionnaires at 2-year intervals to assess the occurrence of cancers and other illnesses and to update information on risk factors. Participants may complete the questionnaire in hard copy or electronically via the Web. Completion of followup questionnaires by members of the 1995 cohort has exceeded 80% in each cycle of followup. Information on outcomes is validated through medical-record review.

In a genetic component of the BWHS, saliva samples are being obtained from participants; DNA from the samples will serve as a resource for testing hypotheses about gene–environment interactions.

Analysis

A mix of univariate, bivariate, and multivariate analyses using logistic regression and linear regression models are being conducted.

Findings

Select findings from the BWHS are summarized in Table C-10.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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TABLE C-10 Publications on Findings of the Black Women’s Health Study by Outcome

Alcohol Use

Patterns and Correlates of Alcohol Consumption

Rosenberg et al., 2002a

“The prevalence of current drinking was highest (37.1%) among women 40–49 years of age, and lowest (23.1%) among women aged 21–29. In every region, heavy drinking (at least 14 drinks a week), reported by about 8% of current drinkers, was associated with current smoking, lower educational attainment, commencement of drinking at younger ages and, particularly, consumption of greater amounts of alcohol in the early years of drinking.”

Asthma

Body-Mass Index and Asthma

Coogan et al., 2009

“During 403,394 person-years of follow-up, 1068 participants reported physician-diagnosed asthma and concurrent use of asthma medication. Compared with women with BMIs of 20 to 24, the multivariate incidence rate ratios for higher categories of BMI increased from 1.26 (95% CI, 1.05–1.51) for BMIs of 25 to 29 to 2.85 (95% CI, 2.19–3.72) for BMIs of 40 or greater, with a significant trend. The association of BMI with asthma risk was consistent across strata of smoking status, age, presence of sleep apnea, parental history of asthma, BMI at age 18 years, and energy expenditure and intake.”

Breast Cancer

Body Size and Breast Cancer

Palmer et al., 2007a

“In 10 years of follow-up, 1,062 incident cases of breast cancer occurred.” “BMI at age 18 years of ≥ 25 relative to < 20 was associated with a reduced risk of breast cancer among both premenopausal women (IRR, 0.68; 95% confidence interval, 0.46–0.98) and postmenopausal women (IRR, 0.53; 95% confidence interval, 0.35–0.81). There was an inverse association of current BMI with premenopausal breast cancer but no association with postmenopausal breast cancer, either overall or among never-users of hormone therapy. Weight gain was not associated with postmenopausal breast cancer risk. In analyses restricted to breast cancers that were estrogen and progesterone receptor positive, IRRs for current BMI and weight gain were elevated but not statistically significant.”

Dietary Patterns and Breast Cancer

Agurs-Collins et al., 2005

“On the 1995 health survey, BWHS participants answered more than 60 questions on what they ate. Preliminary analyses of this information suggest that women who ate a more “prudent” diet, which is high in fruits and vegetables, whole grains, fish and poultry, may have a lower risk of developing breast cancer, and women who ate more of a “Western” diet, high in meat, refined grains, and sweets, may have a higher risk.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Familial Breast Cancer

Palmer et al., 2007b

From 1995 through 2005, there were 1,063 incident breast cancers. 873 cancers were diagnosed in women with no family history of breast cancer. 190 cancers were diagnosed in women with a mother or sister who had breast cancer (incidence ratio 1.79 95% CI, 1.53–2.10). Eleven breast cancers were diagnosed in women with two first-degree relatives with breast cancer (incidence ratio 2.31 95% CI 1.27–4.19). Among women younger than 45 with a first-degree relative who was diagnosed before are 50 the incidence ratio was 3.04 (95% CI 2.12–4.36). A family history of lung, prostate, or colon cancer was not associated with increased risk of breast cancer.

Glycemic Index, Sweets, and Breast Cancer

Palmer et al., 2008a

“Based on 1,091 cases of breast cancer, there was weak evidence of an association. Women who ate at least one sweet a week had a higher risk of developing breast cancer than women who ate few sweets but there was not a trend of increasing risk with increasing sweet consumption.”

Hair Relaxers and Breast Cancer

Rosenberg et al., 2007a

“During 266,298 person-years of follow-up, 574 incident cases of breast cancer were ascertained. There were no increases in breast cancer risk associated with any categories of duration of hair relaxer use, frequency of use, age at first use, number of burns experienced during use, or type of relaxer used. The incidence rate ratio for use at least seven times a year for 20 or more years relative to use for less than a year was 0.98 (95% confidence interval, 0.78–1.39).”

Height and Breast Cancer

Palmer et al., 2001

“A total of 910 cases of breast cancer were analyzed: 700 prevalent cases reported at baseline and 210 incident cases that occurred during the first 2 years of followup. A comparison group of controls frequency-matched on 5-year category of birth year was chosen from among participants who had not developed breast cancer. Increased height was associated with an increased risk of breast cancer overall (p trend = 0.001); the OR for the highest category of height, > 69 inches (175 cm), was 1.6 (95% confidence interval 1.1–2.3). The association was stronger among premenopausal women and women who had less than 16 years of education. Results were similar for prevalent and incident cases.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Hormone Use and Breast Cancer

Rosenberg et al., 2006a

“Data on female hormone use, breast cancer risk factors, and the occurrence of breast cancer were collected from 1995 through 2003 in the Black Women’s Health Study, a follow-up study of US black women. During 182,629 person-years of follow-up 615 cases of breast cancer were reported. The incidence rate ratio for breast cancer in women recently using female hormone supplements relative to those who had never used female hormones, with control for confounding factors, increased with duration of use and was 1.58 (95% confidence interval [CI], 1.12–2.23) for 10 or more years of use; the incidence rate ratios were 1.41 (95% CI, 0.95–2.10) for 10 or more years of use of estrogen alone, and 1.45 (95% CI, 0.94–2.23) for 5 or more years of use of estrogen with progestin. The association of breast cancer with female hormone use was stronger among leaner women (body mass index [calculated as weight in kilograms divided by the square of height in meters] < 25) than among heavier women. Among the leaner women who recently used female hormone supplements for durations of 10 or more years, the incidence rate ratio was 3.08 (95% CI, 1.70–5.56); the corresponding estimates among women with body mass indexes of 25 to 29 and 30 or greater were 1.43 and 0.91, respectively, and neither was statistically significant.”

Induced Abortion and Breast Cancer

Palmer et al., 2004

“Participants reported 348 incident breast cancers during 205,983 person-years of follow-up.… Among nulliparous women, the IRR for any induced abortion relative to none was 0.9 (95% CI = 0.5–1.4), and among parous women, the comparable IRR was 1.1 (95% CI = 0.8–1.4). Risk did not vary by number of abortions, age at first abortion, age at diagnosis or a family history of breast cancer in either nulliparous or parous women.”

Meat, Fat, and Dairy Consumption and Breast Cancer

Rosenberg et al., 2008

No significant association between “intakes of total meat, red meat, white meat, total dairy fluids, or total dairy solids and breast cancer risk was found.… Categorical analyses suggested a J-shaped association for egg consumption where, compared to women who did not eat eggs, breast cancer risk was slightly decreased among women who consumed < 2 eggs per week but slightly increased among women who consumed ≥ 1 egg per day.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Obesity and Breast Cancer

Palmer et al., 2006

“After 8 years of follow-up, 809 women reported incident breast cancer, with about half the cases among premenopausal women and half among postmenopausal women. BMI at age 18 was associated with a decreased risk of breast cancer in both pre- and postmenopausal women: the IRR for BMI 25+ relative to BMI < 20 was 0.6 (95% confidence interval (CI) 0.5–1.0) among premenopausal women and 0.5 (95% CI 0.3–0.8) among postmenopausal women. Current BMI was also associated with a reduced risk among both pre- and postmenopausal women. Weight gain was associated with a small increase in risk among both menopausal groups, but the IRRs were compatible with 1.0. When we repeated the analysis among postmenopausal women who had never used female hormone supplements, a stronger association was observed, with an IRR of 1.8 (95% CI 0.9–3.5) for weight gain of 25+ kg relative to weight gain of < 10 kg. Waist circumference, a measure of central obesity, was weakly associated with postmenopausal breast cancer (IRR for highest vs lowest quintile 1.4 (95% CI 0.8–2.3)). Among never users of female hormones, the IRR for the same comparison was 1.7 (95% CI 0.6–4.2).”

Parity and Breast Cancer

Palmer et al., 2003a

“During 214,862 person-years of follow-up, participants reported 349 breast cancers, of which 128 were among women younger than 45 years and 221 were among women aged 45–70 years. Compared with primiparity, high parity was associated with an increased risk of breast cancer among women younger than 45 years (IRR for four or more births = 2.4, 95% CI = 1.1 to 5.1) and a decreased risk among women aged 45 years and older (IRR = 0.5, 95% CI = 0.3 to 0.9). The IRR for late age at first birth compared with early age was 2.5 (95% CI = 1.1 to 5.8) among the younger women and was not elevated among older women. We found no statistically significant association of time since last birth with breast cancer risk among either younger or older women.”

Physical Activity and Breast Cancer

Rosenberg et al., 1999a

“In these preliminary analyses, there was a trend of decreasing risk of breast cancer with increasing exercise during early reproductive life.”

Racial Discrimination and Breast Cancer

Taylor et al., 2007

“From 1997 to 2003, 593 incident cases of breast cancer were ascertained. In the total sample, there were weak positive associations between cancer incidence and everyday and major discrimination. These associations were stronger among the younger women. Among women aged less than 50 years, those who reported frequent everyday discrimination were at higher risk than were women who reported infrequent experiences. In addition, the incidence rate ratio was 1.32 (95% confidence interval: 1.03, 1.70) for those who reported discrimination on the job and 1.48 (95% confidence interval: 1.01, 2.16) for those who reported discrimination in all three situations—housing, job, and police—relative to those who reported none.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Smoking and Breast Cancer

Palmer et al., 2005

A few studies have reported that women who smoke heavily and who started smoking at a young age may have an increased risk of breast cancer. “In analyses of BWHS data collected from 1995 to 2003, cigarette smoking was not associated with breast cancer risk overall. However, there was a suggestion in the data that risk might be increased for women who smoked for many years and began at a young age. Further data will need to be collected to confirm whether this is so.”

Strenuous Physical Activity and Breast Cancer

Adams-Campbell et al., 2001

“The 704 women who reported breast cancer (cases) were matched on age and on menopausal status at the time of the breast cancer diagnosis with 1408 women who did not report breast cancer (controls). Odds ratios for > or =7 h per week relative to < 1 were significantly reduced for strenuous activity at age 21 for breast cancer overall and premenopausal breast cancer, at age 30 for breast cancer overall, and at age 40 for postmenopausal breast cancer. There was no evidence of a reduction associated with exercise in high school.”

Cervical Cancer

Socioeconomic Predictors of Cervical Cancer

Datta et al., 2006a

“In all, 8.3% of the 40,009 women in the analysis had not undergone a Pap smear examination within the previous 2 years (nonrecent screening). Lower educational attainment, older age, obesity, smoking, and neighborhood poverty were found to be independently related to increased risk of nonrecent screening. The adjusted odds ratio for nonrecent screening was 1.2 (95% confidence interval [95% CI], 1.1–1.4) for women residing in neighborhoods with 20% or more poverty compared with those in neighborhoods with less than 5% poverty. State of residence was also associated with nonrecent cervical carcinoma screening.”

Childhood Sexual Abuse

Childhood Abuse and Age at Menarche

Wise et al., 2009

Approximately 50% of participants reported having been subjected to childhood abuse. In adjusted analyses, sexual abuse was positively associated with early menarche, and the risk of early menarche increased with increasing frequency of sexual abuse incidents. The authors observed “a weak but statistically significant association between physical abuse and early menarche. Associations between sexual abuse and early menarche were stronger when we used a more stringent cutpoint for early menarche (age < 11 years).”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Colorectal Polyps

Anthropometric Risk Factors for Colorectal Polyps

Wise et al., 2008a

“After 211,797 person-years of follow-up, 1,189 cases of colorectal polyps were reported. The IRR comparing women with a current BMI ≥ 35 to < 25 kg/m(2) was 1.35 (95% CI = 1.12–1.62), after adjustment for covariates including waist-to-hip ratio (WHR). Women who gained ≥ 30 kg since age 18 were 1.76 times as likely as those who gained < 5 kg to report polyps (95% CI = 1.33–2.33). The IRR comparing the highest (≥ 0.87) to lowest (<0.71) quintiles of WHR was 1.26 (95% CI = 1.04–1.54), after adjustment for covariates including BMI. BMI at age 18, adult height, and waist circumference (BMI-adjusted) were not materially associated with risk. Results were similar among women with a recent endoscopy.”

Physical Activity and Colorectal Polyps

Rosenberg et al., 2006b

“During 287,029 person-years of follow-up, 1,390 women reported having been diagnosed with colorectal polyps. A review of medical records of 58 women who reported colorectal polyps indicated that 59% had adenomas and 41% had hyperplastic polyps.… For total MET-hours/wk spent in walking and vigorous exercise, the incidence rate ratio decreased from 0.94 for < 5 MET-hours/wk to 0.72 for ≥ 40 MET-hours/wk (Ptrend = 0.01). The inverse association was apparent among most subgroups examined, including women who may be at higher risk of colorectal adenomas because of being obese.”

Coronary Heart Disease

Neighborhood Socioeconomic Status and Serum Biomarkers of Heart Disease

Cozier et al., 2008

“Based on blood samples given by 486 BWHS participants, women living in the most disadvantaged neighborhoods had the least favorable levels of HDL cholesterol, triglycerides, and C-reactive protein.”

Risk Factors for Coronary Heart Disease

Rosenberg et al., 1999b

“The 352 women who reported having had a heart attack (cases) were frequency matched 5:1 on age with 1,760 women who had not (controls); medical record review for 35 cases indicated that two-thirds had had a heart attack and the remainder had other coronary heart disease. Odds ratios, obtained from multiple logistic regression analyses, were significantly elevated for cigarette smoking, drug-treated hypertension, drug-treated diabetes mellitus, elevated cholesterol level, and history of heart attack in a parent. High body mass index (kg/m2) was associated with coronary heart disease in the absence of control for hypertension, diabetes mellitus, and elevated cholesterol but not when they were controlled, suggesting that obesity may influence risk as a result of its effects on blood pressure, glucose tolerance, and cholesterol levels. Odds ratios increased with increasing parity and with decreasing age at first birth.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Depression

Leisure-Time Physical Activity and Depressive Symptoms

Wise et al., 2006

“Adult vigorous physical activity was inversely associated with depressive symptoms. Women who reported vigorous exercise both in high school (≥ 5 hr per week) and adulthood (≤ 2 hr per week) had the lowest odds of depressive symptoms (OR = 0.76, 95% CI = 0.71–0.82) relative to never active women; the OR was 0.90 for women who were active in high school but not adulthood (95% CI = 0.85–0.96) and 0.83 for women who were inactive in high school but became active in adulthood (95% CI = 0.77–0.91). Although walking for exercise was not associated with risk of depressive symptoms overall, there was evidence of a weak inverse relation among obese women (Body Mass Index ≤ 30).”

Sociodemographic Characteristics and Depression

Williams et al., 2004

“On the 1999 BWHS health survey, participants completed 20 questions, the “CES-D” scale which is a measure of feelings of depression. The present analysis found that older and younger women differed in the types of symptoms they reported, and that depression scores were lower for older women, married women, and those with higher levels of education.”

Diabetes

Dietary Calcium and Magnesium, Major Food Sources, and Type 2 Diabetes

van Dam et al., 2006

Based on 1,964 women who reported having been newly diagnosed with the illness during 1995–2003 and using dietary information reported by participants on the 1995 questionnaire, “the multivariate-adjusted hazard ratio of type 2 diabetes for the highest compared with the lowest quintile of intake was 0.69 (95% CI 0.59–0.81; P trend < 0.0001) for dietary magnesium and 0.86 (0.74–1.00; P trend = 0.01) for dietary calcium. After mutual adjustment, the association for calcium disappeared (hazard ratio 1.04 [95% CI 0.88–1.24]; P trend = 0.88), whereas the association for magnesium remained. Daily consumption of low-fat dairy (0.87 [0.76–1.00]; P trend = 0.04) and whole grains (0.69 [0.60–0.79]; P trend < 0.0001) were associated with a lower risk of type 2 diabetes compared with a consumption less than once a week. After mutual adjustment, the hazard ratio was 0.81 (0.68–0.97; P trend = 0.02) for magnesium and 0.73 (0.63–0.85; P trend < 0.0001) for whole grains.”

Fast Food and Type 2 Diabetes

Krishnan et al., 2008

The authors “found that frequent consumption of food from restaurants was associated with increased incidence of diabetes, based on 2,846 newly occurring cases.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Glycemic Index, Glycemic Load, Cereal Fiber and Type 2 Diabetes

Krishnan et al., 2007b

“During 8 years of follow-up, there were 1,938 incident cases of diabetes…. Glycemic index was positively associated with the risk of diabetes: the IRR for the highest quintile relative to the lowest was 1.23 (95% confidence interval [CI], 1.05–1.44). Cereal fiber intake was inversely associated with risk of diabetes, with an IRR of 0.82 (95% CI, 0.70–0.96) for the highest vs lowest quintiles of intake. Stronger associations were seen among women with a body mass index (calculated as weight in kilograms divided by height in meters squared) lower than 25: IRRs for the highest vs lowest quintile were 1.91 (95% CI, 1.16–3.16) for glycemic index (P value for interaction, .12) and 0.41 (95% CI, 0.24–0.72) for cereal fiber intake (P value for interaction, .05).”

Obesity and Type 2 Diabetes

Krishnan et al., 2007a

During 8 years of followup, 2,472 new occurrences of type 2 diabetes were reported. “Sixty-one percent of participants had a BMI ≥ 2 5 kg/m2 (WHO definition of overweight). Compared with a BMI of < 23 kg/m2, the IRR for a BMI of > 45 kg/m2 was 23 (95% confidence interval, 17.0 to 31.0). The IRR for the highest quintile of waist-to-hip ratio relative to the lowest was 2.3 (95% confidence interval, 2.0 to 2.7) after control for BMI. Furthermore, at every level of BMI, an increased risk was observed for high waist-to-hip ratio relative to low.” The incidence of type 2 diabetes was more than 20 times greater in women in the highest category of body mass index considered (≥ 45) than among lean women.

Physical Activity, Television Viewing, and Type 2 Diabetes

Krishnan et al., 2009

“During 10 years of follow-up, 2,928 incident cases of type 2 diabetes were identified. Vigorous activity was inversely associated with type 2 diabetes risk (Ptrend < 0.0001); the incidence rate ratio for ≥ 7 hours per week was 0.43 (95% confidence interval (CI): 0.31, 0.59) relative to no activity. Brisk walking for ≥ 5 hours per week was associated with reduced type 2 diabetes risk (incidence rate ratio = 0.67, 95% CI: 0.49, 0.92) relative to no walking. Television watching was associated with an increased type 2 diabetes risk: The incidence rate ratio was 1.86 (95% CI: 1.54, 2.24) for ≥ 5 hours relative to < 1 hour of television per day, independent of physical activity.”

Sugar-Sweetened Beverages and Type 2 Diabetes

Palmer et al., 2008b

There were “2,713 incident cases of type 2 diabetes mellitus during 338,884 person-years of follow-up…. The incidence of type 2 diabetes mellitus was higher with higher intake of both sugar-sweetened soft drinks and fruit drinks. After adjustment for confounding variables including other dietary factors, the incidence rate ratio for 2 or more soft drinks per day was 1.24 (95% confidence interval, 1.06–1.45). For fruit drinks, the comparable incidence rate ratio was 1.31 (95% confidence interval, 1.13–1.52). The association of diabetes with soft drink consumption was almost entirely mediated by body mass index, whereas the association with fruit drink consumption was independent of body mass index.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Hypertension

Neighborhood Median Housing Value and Hypertension Risk

Cozier et al., 2007a

“During 180,294 person-years of observation, 3,780 cases of hypertension were reported. A significant inverse, graded association was found between median housing value and hypertension. The incidence rate ratio for women living in low median housing value neighborhoods relative to high was 1.29 (95% confidence interval = 1.14, 1.45) after adjustment for individual risk factors. The association was evident even at higher individual levels of income and education.”

Neighborhood Socioeconomic Status and Hypertension

Cozier et al., 2004

“During 1995–2001 4,895 BWHS participants reported having been diagnosed with hypertension for the first time. After taking into account individual characteristics such as age, weight, education, smoking, and exercise, we found that lower neighborhood SES was associated with a higher occurrence of hypertension. This suggests that neighborhood environment may be contributing to the excess of hypertension among black women in the U.S.”

Obesity and Hypertension in College-Educated Women

Rosenberg et al., 1999c

The authors “compared 9,394 participants who reported a diagnosis of hypertension treated with a diuretic or antihypertensive drug (cases) with 9,259 participants of similar ages who did not have hypertension (controls). The odds ratio for treated hypertension increased with increasing body mass index at every educational level. Among college-educated women, the odds ratio for hypertension was 2.7 for overweight women (index 27.3–32.3) and 4.9 for severely overweight women (index > 32.3), relative to women with a body mass index < 22.8. The prevalences of obesity and hypertension were high among the college-educated women, although not as high as among women with fewer years of education. About a quarter of the difference in the prevalence of hypertension across educational levels was explained by the difference in the proportions who were overweight or severely overweight.”

Past-Year Strenuous Physical Activity and Hypertension

Kim et al., 1998

“Strenuous physical activity in the past year was associated with reduced risk of high blood pressure.”

Physical Activity and Hypertension

Cozier et al., 2006a

“Participation in vigorous physical activity was associated with a decreased occurrence of hypertension among BWHS participants. The effect of walking was much weaker.”

Racial Discrimination and Hypertension

Cozier et al., 2006b

“There were 2,316 incident cases of hypertension reported during 104,574 person-years of observation from 1997 to 2001. Most women reported experiences of racism. In the total sample, IRRs for the association of racism with incident hypertension were close to the null. However, some positive associations were observed for personally mediated racism in women born outside the United States.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Very High Body-Mass Index and Hypertension

Cozier et al., 2005

“The incidence of hypertension increased as women’s body mass index increased. The incidence of hypertension in women with a body mass index of 45 or more was 7.7 times greater than that among women with a body mass index of 20–22. A body mass index of 20–24 is considered to be a “healthy” weight; 25–29 is considered to be “overweight”; and 30 or greater is “obese”.”

Hysterectomy

Correlates of Hysterectomy

Palmer et al., 1999

“Analyses were conducted on participants aged 30–49 years; 5,163 had had a hysterectomy and 29,787 were still menstruating. Hysterectomy was associated with region of residence: Odds ratios for living in the South, Midwest, and West relative to the Northeast were 2.63 (95% confidence interval (Cl): 2.38, 2.91), 2.02 (95% Cl: 1.81, 2.25), and 1.89 (95% Cl: 1.68, 2.12), respectively. Hysterectomy was inversely associated with years of education and age at first birth: Odds ratios were 1.96 (95% Cl: 1.74, 2.21) for > 12 years of education relative to > 16 years and 4.33 (95% Cl: 3.60, 5.22) for first birth before age 20 relative to age 30 or older. Differences in the prevalence of major indications for hysterectomy did not explain the associations.”

Leiomyomata (Uterine Fibroids)

Age-Specific Incidence of Uterine Fibroids

Wise et al., 2005a

“During 76,711 woman-years of follow-up, 2,637 incident cases of uterine leiomyomata reported as confirmed by pelvic examination (n = 358), ultrasonography (n = 2,006), or hysterectomy (n = 273) were observed. Incidence rates per 1,000 woman-years were 34.4 (95% CI 33.1–35.7) for all cases combined, 29.7 (95% CI 28.5–30.9) for cases confirmed by ultrasonography or hysterectomy, and 3.6 (95% CI 3.2–4.0) for cases confirmed by hysterectomy. The incidence rate peaked at ages 40–44 years for all cases combined (incidence rate 45.6, 95% CI 42.0–49.5) and for cases confirmed by ultrasonography or hysterectomy (incidence rate 39.8, 95% CI 36.5–43.4), and peaked at ages 45–49 years for cases confirmed by hysterectomy (incidence rate 8.3, 95% CI 6.4–10.7).”

Body Size, Body Fat, and Uterine Fibroids

Wise et al., 2005b

The influence of body size and body fat distribution on the occurrence of uterine fibroids, using data from the BWHS collected from 1997 to 2001 was assessed. During that time period, 2,146 premenopausal women reported having been diagnosed with a fibroid through ultrasound or hysterectomy. All women with a body mass index (BMI) of 20 or greater had a higher risk of fibroids than women with a BMI < 20. (BMI < 20 is defined as thin, 20–24.9 as appropriate weight, 25–29.9 as overweight, and 30 or greater as obese). The risk of having a fibroid increased as BMI increased, to a peak at BMI 27.5–29.9 and then decreased. Weight gain since age 18 was positively associated with risk among women who had had children but not among women who had never had a child. Waist and hip circumference were not associated with risk of fibroids. These finding indicate that there is a complex relationship between BMI and risk of uterine fibroids, but that risk is lowest for thin women.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Perceived Racial Discrimination and Uterine Fibroids

Wise et al., 2007b

“During 107,127 person-years of follow-up, 3,440 new cases of uterine myomas confirmed by ultrasound (n = 2774) or surgery (n = 666) were reported. All IRRs for “lifetime” and “everyday” experiences of racism were above 1.0. Using a summary variable that averaged the responses from 5 “everyday” racism items, multivariable IRRs comparing quartiles 2, 3, and 4 to quintile 1 (lowest) were 1.16 (95% CI = 1.04–1.29), 1.19 (1.06–1.32), and 1.27 (1.14–1.43), respectively. Multivariable IRRs comparing women who reported 1, 2, or 3 lifetime occurrences of major discrimination (ie, job, housing, or police) relative to those who reported none were 1.04 (0.96–1.13), 1.17 (1.07–1.28), and 1.24 (1.10–1.39), respectively. Results did not vary according to case definition (ultrasound vs surgery) or health care utilization. Associations were weaker among foreign-born women and among women with higher coping skills.”

Polycystic Ovary Syndrome and Uterine Fibroids

Wise et al., 2007a

“During 114,373 person-years of follow-up, 3,631 new cases of UL confirmed by ultrasound (N = 2,926) or hysterectomy (N = 705) were reported. After adjustment for potential confounders, the incidence of UL was 65% higher among women with PCOS than women without PCOS (incidence rate ratio, 1.65; 95% confidence interval, 1.21–2.24). The incidence rate ratios remained constant with increasing time after the diagnosis of PCOS. Results were similar when analyses were confined to women reporting a recent Papanicolaou smear, a proxy for a pelvic examination.”

Reproductive Factors, Hormonal Contraception, and Uterine Fibroids

Wise et al., 2004a

“During 76,711 person-years of follow-up, 2,279 new cases of ultrasound- or hysterectomy-confirmed uterine leiomyomata were self-reported. After adjustment for age, body mass index, smoking, alcohol intake, and other reproductive covariates, the risk of ultrasound- or hysterectomy-confirmed leiomyomata was inversely associated with age at menarche, parity, and age at first birth and positively associated with years since last birth. Overweight or obesity appeared to attenuate the inverse association between parity and uterine leiomyomata. Current use of progestin-only injectables was inversely associated with risk. No consistent patterns were observed for other forms of hormonal contraception.”

Tobacco, Alcohol, Caffeine and Uterine Fibroids

Wise et al., 2004b

“21,885 premenopausal women with intact uteri and no prior myoma diagnosis” were followed from 1997 to 2001. “During 73,426 person-years of follow-up, 2,177 incident cases of uterine leiomyomata confirmed by ultrasound (n = 1920) or hysterectomy (n=257) were reported. Cigarette smoking was not associated with risk of uterine leiomyomata. Risk was positively associated with years of alcohol consumption and current consumption of alcohol, particularly beer. Relative to non-drinkers, multivariate IRRs for beer consumption of < 1, 1–6 and 7+ drinks/week were 1.11 (95% CI 0.98–1.27), 1.18 (95% CI 1.00–1.40) and 1.57 (95% CI 1.17–2.11), respectively. Heavy coffee and caffeine consumption were not associated with risk overall, but IRRs were increased among women aged < 35 years.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Lupus

Childhood Smoke Exposure and Lupus

McAlindon et al., 2000

“Adult smoking and exposure to the smoke of others were assessed in relation to systemic lupus erythematosus (SLE, lupus), based on 46 BWHS participants who developed the illness. Both smoking in adulthood and childhood exposure to smoke were associated with an increased risk of lupus.”

Reproductive Factors and Lupus

Boggs et al., 2007

“Positive associations of lupus with earlier age at starting to menstruate, shorter time between menstrual cycles, and use of postmenopausal female hormone supplements were found.”

Smoking, Alcohol, and Lupus

Formica et al., 2003

“Follow-up questionnaires in 1997 and 1999 ascertained incident cases of SLE. … Sixty-seven women reported a new diagnosis of SLE and use of appropriate medication for that illness. In multivariate analyses, the IRR for current and past smoking were 1.6 (both 95% CI 0.8–3.3). The risk was greater for women who began smoking before age 19 years (IRR 1.9, 95% CI 1.0–3.6). Neither current alcohol consumption (IRR 1.0, 95% CI 0.4–2.4) nor past alcohol consumption (IRR 0.9, 95% CI 0.3–2.7) was associated with SLE.”

Mammography

Predictors of Recent Mammography Use

Cozier et al., 2001

Information provided by BWHS participants in 1995 indicates that their rates of mammography use are high, and that a high proportion of women 40–49 made use of mammography even before new screening guidelines were introduced. “Seventy-three percent of women aged 40–49, and 82% of those aged 50–69, reported having had a mammogram within the previous three years. Use was greater among women with higher levels of education, and among those who had cystic breast disease or a mother or sister with breast cancer.”

Socioeconomic Predictors of Mammography Use

Rosenberg et al., 2005a

Among a sample of 14,706 participants, “most participants had health insurance and almost half had graduated college. Having health insurance was the socioeconomic variable most strongly associated with regular mammography use (odds ratio, 3.59; 95% confidence interval 3.02–4.28); the association was present at all levels of educational attainment, household income, and neighborhood socioeconomic status. Regular mammography use increased with individual household income: odds ratio, 2.00 (95% confidence interval, 1.58–2.53) for household income > $100,000 relative to < $15,001. Regular mammography use did not vary across level of education. Higher neighborhood socioeconomic status was significantly associated with regular mammography use before, but not after, control for household income.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Menopause

Age at Natural Menopause

Rosenberg et al., 2001

“Age at menopause influences the occurrence of osteoporosis, breast cancer, and other illnesses. Current smoking and a measure of racism (how often women thought about their race) were associated with an earlier natural menopause in preliminary analyses. The present results suggest that black and white women share an important determinant of the age at natural menopause, cigarette smoking.”

Predictors of Onset of Natural Menopause

Palmer et al., 2003b

“Among 17,070 women aged 35 to 55 years and premenopausal in 1995, the hazard ratio (HR) was 1.43 for current smokers (95% confidence interval [CI] = 1.24, 1.66) and 1.21 (95% CI = 1.06, 1.38) for ex-smokers and significantly less for obese women and oral contraceptive users. Hazard ratios for most questions about racism were elevated by 10% to 30% but were not statistically significant.”

Mortality

Lifestyle Factors and Mortality

Rosenberg et al., 2007b

“Mortality rates from many causes are higher in African–American women than white women. Preliminary analyses showed that mortality is increased in women who smoke and drink heavily, and it is decreased in women who exercise vigorously.”

Neighborhood Socioeconomic Status and Mortality

Cozier et al., 2007b

In preliminary analyses, the authors “found that the risk of dying among BWHS participants who lived in disadvantaged neighborhoods was slightly higher than the risk among women who lived in wealthier neighborhoods after taking into account personal factors and habits, such as education and smoking.”

Multiple Sclerosis

Geographic Variation in Multiple Sclerosis Incidence

Wise et al., 2007c

“In preliminary analyses, the incidence of multiple sclerosis (MS) in the BWHS is higher in northern regions than in southern regions, based on 149 new diagnoses of MS reported by BWHS participants from 1995 to 2005. This finding is in agreement with observations made in other racial/ethnic groups.”

Myocardial Infarction (MI)

Risk Factors for Myocardial Infarction

Rosenberg et al., 1997a

“Cigarette smoking, high blood pressure, diabetes, high cholesterol levels, family history of heart attack, and overweight were associated with a higher risk of heart attack.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Obesity

Demographic and Personal Factors and Obesity

Kumanyika et al., 2000

“Obesity as an adult was strongly associated with obesity at age 18 and with physical inactivity. These findings suggest a need to emphasize obesity prevention in childhood and adolescence and to promote participation in physical activity.”

Perceived Racism

Neighborhood Racial Composition and Perceptions of Racial Discrimination

Hunt et al., 2007

Using data from 42,445 women collected during the 1997 follow-up wave, women in neighborhoods with the highest percent of black residents reported the least discrimination, while women in more mixed neighborhoods reported intermediate amounts of racism and women in neighborhoods with the lowest percent of black residents reported the most discrimination. While racial integration can have social and economic benefits, these results indicate that there is a price to pay in terms of racial discrimination.

Perceptions and Experiences of Racism

Cozier et al., 2000

“The frequency of reporting experiences and perceptions of racism was greater among younger women. The frequency was also higher among women with higher levels of education. The latter suggests that experiences and perceptions of racism do not diminish with increasing socioeconomic status as measured by level of education.”

Physical Activity

Epidemiology of Physical Activity

Adams-Campbell et al., 2000

There were low levels of physical activity among study participants: “57% reported an hour or less per week walking for exercise, 18% reported moderate activity, and 61% reported strenuous physical activity. Strenuous physical activity increased with education. Higher levels of walking for exercise and moderate and strenuous activity were associated with higher levels of participation in strenuous exercise in high school.”

Influence of Urban Form on Walking

Coogan et al., 2008

“For three cities, Los Angeles, Chicago, and New York, detailed data on “urban form,” such as the presence of sidewalks and the distance to bus stops were obtained.” The authors “found that BWHS participants in those cities who lived in pedestrian-friendly neighborhoods were found to spent more time walking for transport (to work, shops, church, etc) than women in less pedestrian-friendly neighborhoods. Results such as these are important for persuading city planners to ensure that neighborhoods are constructed to be pedestrian-friendly.”

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Postmenopausal Female Hormone Use

Correlates of Postmenopausal Hormone Use

Rosenberg et al., 1998

Among the 13,352 women who had ceased menstruating, 49.2% reported ever use of female hormone supplements and 33.3% were using them currently. Unopposed oral estrogens accounted for 63.4% of the medications being used currently. The use of supplements was highest in the western US and lowest in the Northeast. The strongest correlate of use was menopause due to bilateral oophorectomy. Use peaked at 50–54 years of age and then declined, and also was associated positively with lower body mass index, greater years of education, participation in vigorous exercise, and past oral contraceptive use. Use was associated inversely with having a positive history of diabetes, heart attack, or breast cancer. Some of the drug use reported was at variance with suggested guidelines: unopposed estrogen was taken by some women who had a uterus, and estrogen together with a progestin was taken by some women who had had a hysterectomy.

Preterm Birth

Hair-Relaxer Use and Preterm Birth

Rosenberg et al., 2005b

Among 6,130 singleton births reported by women < 45 years of age during followup, 497 were preterm (< 37 weeks gestation) because of premature rupture of membranes or spontaneous preterm labor for no known reason. In a case–control comparison of the 497 preterm births with 5,633 births of longer gestation with control for confounding factors, the odds ratio for preterm birth among ever users of hair relaxers relative to never users was 1.0 (95% confidence interval, 0.6–1.8). No elevations were seen in risk for use started at a young age or for frequent use for long durations.

Maternal Anthropometric Risk Factors for Preterm Birth

Wise et al., 2008b

Based on information given by BWHS participants on 7,324 births, we found that the risk of spontaneous preterm birth was increased among women who were thin (body mass index less than 20) or obese (body mass index of 30 or more) before the pregnancy, compared with women who had a body mass index of 20–24.

Racial Discrimination and Preterm Birth

Rosenberg et al., 2002b

Comparing mothers of 422 babies born 3 or more weeks early (because of premature labor for unknown reasons or rupture of membranes) with mothers of 4,544 babies of longer gestation, the adjusted ORs for preterm birth were 1.3 (95% confidence interval [CI] = 1.1–1.6) for women who reported unfair treatment on the job and 1.4 (1.0–1.9) for women who reported that people acted afraid of them at least once a week. Overall ORs for the seven other racism questions were close to 1.0. Among 491 women with </=12 years of education, ORs were 2.0 or greater for four racism variables.

Risk Factors for Preterm Birth

Rosenberg et al., 2000

In these preliminary analyses, preterm birth was most strongly associated with having had a previous preterm birth, the mother having been preterm herself, and the mother having had no previous children. Preterm birth was less common among women with higher levels of education.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Sarcoidosis

Frequency and Characteristics of Sarcoidosis in Black Women

Cozier et al., 2007c

Sarcoidosis is an illness that affects African American women more than other women. The causes are largely unknown. The BWHS has begun to study this illness, and a comparison of medical records with reports of the illness by BWHS participants shows a high level of accuracy of reporting by participants.

Smoking

Individual, Neighborhood, and State-Level Predictors of Smoking

Datta et al., 2006b

Neighborhood characteristics of 41,726 never and current smokers were obtained by linking participants’ addresses with census tract data from the 1990 US Census. In a multilevel logistic regression model, higher neighborhood poverty was associated with increased smoking prevalence after adjusting for age, education, marital status, and occupation at the individual level, and percent high school graduate, percent college graduate, and percentage black at the neighborhood level. Relative to women residing in neighborhoods with less than 5% of the residents below the poverty line, the odds ratio was 1.1 (95% confidence interval: 1.0–1.2) for women in neighborhoods with 5–9.9% of the residents below the poverty line, 1.3 (1.2–1.4) for women in neighborhoods with 10–19.9% of the residents below the poverty line, and 1.6 (1.5–1.8) for women in neighborhoods with 20% or more of the residents below poverty. State of residence was also significantly associated with prevalence of current smoking.

Venous Thrombosis

Female Hormone Use and Venous Thrombosis

Rosenberg et al., 1997b

Recent studies suggest that the risk of clots in the legs or lung may be higher among women who are using postmenopausal female hormones than among nonusers. Data from the BWHS support this possibility. These findings have been confirmed by data from randomized studies.

Weight Gain

Change in Diet Patterns and Weight Gain

Boggs et al., 2008

Participants provided food intake information in 1995 and 2001. Two diet patterns, “prudent” (high in fruits and vegetables) and “western” (high in meat and high-fat dairy) were assessed. Decreased intake of a prudent diet and increased intake of a western diet were associated with more weight gain.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Childbearing and Weight Gain

Rosenberg et al., 2003

During 4 years of followup, the BMI of participants increased by an average of 1.6 kg/m2, equivalent to a weight gain of ~4.4 kg. Women who had a child during followup gained more weight than women who remained nulliparous, and those who had a first child gained more than those who had a second or later child. The weight gain associated with childbearing increased with increasing baseline BMI and was appreciable among heavier women. For example, among women with a baseline index of 36, the increase in BMI for women who bore a first child was 1.1 kg/m2 more than that of nulliparous women, equivalent to a difference in weight gain of ~3.0 kg.

Perceived Racism and Weight Gain

Cozier et al., 2009

The association of perceived racism with weight change between 1997 and 2005 was assessed. Weight gain increased as levels of everyday and lifetime racism increased. The mean multivariable-adjusted difference in weight change between the highest and the lowest quartile of everyday racism was 0.56 kg. The mean difference comparing the highest category of lifetime racism to the lowest was 0.48 kg.

ABBREVIATIONS: BMI, body-mass index; BWHS, Black Women’s Health Study; CES-D, Center for Epidemiologic Studies Depression; CI, confidence interval; h, hour; HDL, high-density lipoprotein; HR, hazard ratio; IRR, incidence rate ratio; MET, metabolic equivalent; MI, myocardial infarction; MS, multiple sclerosis; OR, odds ratio; PCOS, polycystic ovary syndrome; SES, socioeconomic status; SLE, systemic lupus erythematosus; UL, uterine leiomyomata; WHO, World Health Organization; WHR, waist-to-hip ratio.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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THE NURSES’ HEALTH STUDY

Study Design and Methods

The Nurses’ Health Study (NHS) is a 3-part study that began in 1976 with funding from NIH. The initial interest was in the effects of oral contraceptives on women; they were being widely prescribed at the time with no solid data on their long term effects. Registered nurses were selected and followed prospectively. The researchers chose nurses because their level of education and knowledge of health-related issues would ensure accurate responses to technical questions. The response rates to NHS I and NHS II questionnaires are at 90% for each 2-year cycle, and the third portion of the study began in 2008.

For part I, about 122,000 nurses in 11 states out of the 170,000 contacted by mail responded. The nurses were 30–55 years old in 1976 and all were married. Followup questionnaires were sent out every 2 years, and the participants were asked to respond to questions about diseases, lifestyle and other health-related topics, including smoking, hormone use, and menopausal status. The first questionnaire regarding food was issued in 1980 and later ones in 1984, 1986, and every 4 years since. Questions related to quality-of-life issues were added in 1992 and repeated every 4 years.

Aside from questionnaires, the study used laboratory tests to get more detailed information for case–control analysis; 68,000 sets of toenail clippings were collected in 1982–1984 to identify minerals and nutrient information that could not be gleaned from the questionnaires alone, and 33,000 blood samples were collected in 1989–1990 and 18,700 in 2000–2001 to examine hormone concentrations and genetic markers.

Part II of the NHS began in 1989, and looked at a younger population of women. There are 116,686 women aged 25–42 years old in the NHS II. The objective of the NHS II was to study oral contraceptives, diet, and lifestyle risk factors in a population younger than the original NHS cohort. The younger generation provides information on women who began using oral contraceptives much earlier in life and therefore had greater exposure. The type of oral contraceptive used was also looked at; this was not done in the NHS I.

As in NHS I, surveys were sent out at the beginning and then every 2 years. Food and diet surveys and quality-of-life questionnaires were also included in later followups. Blood and urine samples were collected from about 30,000 subjects in the late 1990’s for analysis.

The NHS III will recruit a new cohort of female nurses, 22–42 years old, and examine hormones, dietary patterns, and occupational exposures in relation to health. The study format differs in that it will be entirely Web-based. It will look more closely at fertility and pregnancy, and at adolescent diet and breast-cancer risk. The NHS III is also taking care to include women with diverse ethnic backgrounds.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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For more information regarding specific findings and publications from the NHS, please go to the following project link: https://sites.google.com/a/channing. harvard.edu/nhs-publications/Home/nhs---nhs-ii.

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Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Cozier, Y., C. Jones, J. Palmer, R. Rao, L. Adams-Campbell, and L. Rosenberg. 2000. Perceptions and experiences of racism among African–American women. American Journal of Epidemiology 151:S24.

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Cozier, Y. C., J. R. Palmer, and L. Rosenberg. 2006a. The relation of physical activity to risk of hypertension in the Black Women’s Health Study. American Journal of Epidemiology 163(Suppl.): S42.

Cozier, Y. C., J. R. Palmer, N. J. Horton, L. Fredman, L. A. Wise, and L. Rosenberg. 2006b. Racial discrimination and the incidence of hypertension in US black women. Annals of Epidemiology 16(9):681–687.

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Cozier, Y., M. Albert, J. Palmer, and L. Rosenberg. 2007b. Relation between neighborhood socioeconomic characteristics and mortality in US Black women. American Journal of Epidemiology 165:S78.

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Cozier, Y. C., M. A. Albert, J. R. Palmer, and L. Rosenberg. 2008. Neighborhood socioeconomic status in relation to serum biomarkers in the Black Women’s Health Study. American Journal of Epidemiology 167(Suppl.):S520.

Cozier, Y. C., L. A. Wise, J. R. Palmer, and L. Rosenberg. 2009. Perceived racism in relation to weight change in the Black Women’s Health Study. Annals of Epidemiology 19(6):379–387.

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Datta, G. D., G. A. Colditz, I. Kawachi, S. V. Subramanian, J. R. Palmer, and L. Rosenberg. 2006a. Individual-, neighborhood-, and state-level socioeconomic predictors of cervical carcinoma screening among US black women: A multilevel analysis. Cancer 106(3):664–669.

Datta, G. D., S. V. Subramanian, G. A. Colditz, I. Kawachi, J. R. Palmer, and L. Rosenberg. 2006b. Individual, neighborhood, and state-level predictors of smoking among US black women: A multilevel analysis. Social Science and Medicine 63(4):1034–1044.

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Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Finkelstein, J. S., M. L. Lee, M. Sowers, B. Ettinger, R. M. Neer, J. L. Kelsey, J. A. Cauley, M. H. Huang, and G. A. Greendale. 2002. Ethnic variation in bone density in premenopausal and early perimenopausal women: Effects of anthropometric and lifestyle factors. Journal of Clinical Endocrinology and Metabolism 87(7):3057–3067.

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Formica, M. K., J. R. Palmer, L. Rosenberg, and T. E. McAlindon. 2003. Smoking, alcohol consumption, and risk of systemic lupus erythematosus in the Black Women’s Health Study. Journal of Rheumatology 30(6):1222–1226.

Glynn, R. J., G. J. L’Italien, H. D. Sesso, E. A. Jackson, and J. E. Buring. 2002. Development of predictive models for long-term cardiovascular risk associated with systolic and diastolic blood pressure. Hypertension 39(1):105–110.

Glynn, R. J., P. M. Ridker, S. Z. Goldhaber, and J. E. Buring. 2007. Effect of low-dose aspirin on the occurrence of venous thromboembolism: A randomized trial. Annals of Internal Medicine 147(8):525–533.

Gold, E. B., B. Sternfeld, J. L. Kelsey, C. Brown, C. Mouton, N. Reame, L. Salamone, and R. Stellato. 2000. Relation of demographic and lifestyle factors to symptoms in a multi-racial/ethnic population of women 40–55 years of age. American Journal of Epidemiology 152(5):463–473.

Gold, E. B., J. Bromberger, S. Crawford, S. Samuels, G. A. Greendale, S. Harlow, and J. Skurnick. 2001. Factors associated with age at natural menopause in a multiethnic sample of midlife women. American Journal of Epidemiology 153(9):865–874.

Gold, E. B., G. Block, S. Crawford, L. Lachance, G. FitzGerald, H. Miracle, and S. Sherman. 2004. Lifestyle and demographic factors in relation to vasomotor symptoms: Baseline results from the Study of Women’s Health Across the Nation. American Journal of Epidemiology 159(12):1189–1199.

Gold, E. B., A. Colvin, N. Avis, J. Bromberger, G. A. Greendale, L. Powell, B. Sternfeld, and K. Matthews. 2006. Longitudinal analysis of the association between vasomotor symptoms and race/ethnicity across the menopausal transition: Study of Women’s Health Across the Nation. American Journal of Public Health 96(7):1226–1235.

Gold, E. B., Y. Bair, G. Block, G. A. Greendale, S. D. Harlow, S. Johnson, H. M. Kravitz, M. O. Rasor, A. Siddiqui, B. Sternfeld, J. Utts, and G. Zhang. 2007. Diet and lifestyle factors associated with premenstrual symptoms in a racially diverse community sample: Study of Women’s Health Across the Nation (SWAN). Journal of Women’s Health 16(5):641–656.

Goldbacher, E. M., J. Bromberger, and K. A. Matthews. 2009. Lifetime history of major depression predicts the development of the metabolic syndrome in middle-aged women. Psychosomatic Medicine 71(3):266–272.

Green, R., and N. Santoro. 2009. Menopausal symptoms and ethnicity: The Study of Women’s Health Across the Nation. Womens Health 5(2):127–133.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Habel, L. A., A. M. Capra, N. Oestreicher, G. A. Greendale, J. A. Cauley, J. Bromberger, C. J. Crandall, E. B. Gold, F. Modugno, M. Salane, C. Quesenberry, and B. Sternfeld. 2007. Mammographic density in a multiethnic cohort. Menopause 14(5):891–899.

Hall, M. H., K. A. Matthews, H. M. Kravitz, E. B. Gold, D. J. Buysse, J. T. Bromberger, J. F. Owens, and M. Sowers. 2009. Race and financial strain are independent correlates of sleep in midlife women: The Swan Sleep Study. Sleep 32(1):73–82.

Harris, R. E., R. T. Chlebowski, R. D. Jackson, D. J. Frid, J. L. Ascenseo, G. Anderson, A. Loar, R. J. Rodabough, E. White, and A. McTiernan. 2003. Breast cancer and nonsteroidal antiinflammatory drugs: Prospective results from the Women’s Health Initiative. Cancer Research 63(18):6096–6101.

Hays, J., J. K. Ockene, R. L. Brunner, J. M. Kotchen, J. E. Manson, R. E. Patterson, A. K. Aragaki, S. A. Shumaker, R. G. Brzyski, A. Z. LaCroix, I. A. Granek, and B. G. Valanis. 2003. Effects of estrogen plus progestin on health-related quality of life. New England Journal of Medicine 348(19):1839–1854.

Heiss, G., R. Wallace, G. Anderson, A. Aragaki, S. Beresford, R. Brzyski, R. Chlebowski, M. Gass, A. LaCroix, J. Manson, R. Prentice, J. Rossouw, and M. L. Stefanick. 2008. Health risks and benefits 3 years after stopping randomized treatment with estrogen and progestin. Journal of the American Medical Association 299(9):1036–1045.

Hendrix, S. L., B. B. Cochrane, I. E. Nygaard, V. L. Handa, V. M. Barnabei, C. Iglesia, A. Aragaki, M. J. Naughton, R. B. Wallace, and S. G. McNeeley. 2005. Effects of estrogen with and without progestin on urinary incontinence. Journal of the American Medical Association 293(8):935–948.

Hennekens, C. H., I. M. Lee, N. R. Cook, P. R. Hebert, E. W. Karlson, F. LaMotte, J. E. Manson, and J. E. Buring. 1996. Self-reported breast implants and connective-tissue diseases in female health professionals. A retrospective cohort study. Journal of the American Medical Association 275(8):616–621.

Hess, R., A. Colvin, N. E. Avis, J. T. Bromberger, M. Schocken, J. M. Johnston, and K. A. Matthews. 2008. The impact of hormone therapy on health-related quality of life: Longitudinal results from the Study of Women’s Health Across the Nation. Menopause 15(3):422–428.

Higginbotham, S., Z. F. Zhang, I. M. Lee, N. R. Cook, J. E. Buring, and S. Liu. 2004a. Dietary glycemic load and breast cancer risk in the Women’s Health Study. Cancer Epidemiology, Biomarkers and Prevention 13(1):65–70.

Higginbotham, S., Z. F. Zhang, I. M. Lee, N. R. Cook, E. Giovannucci, J. E. Buring, and S. Liu. 2004b. Dietary glycemic load and risk of colorectal cancer in the Women’s Health Study. Journal of the National Cancer Institute 96(3):229–233.

Howard, B. V., L. Van Horn, J. Hsia, J. E. Manson, M. L. Stefanick, S. Wassertheil-Smoller, L. H. Kuller, A. Z. LaCroix, R. D. Langer, N. L. Lasser, C. E. Lewis, M. C. Limacher, K. L. Margolis, W. J. Mysiw, J. K. Ockene, L. M. Parker, M. G. Perri, L. Phillips, R. L. Prentice, J. Robbins, J. E. Rossouw, G. E. Sarto, I. J. Schatz, L. G. Snetselaar, V. J. Stevens, L. F. Tinker, M. Trevisan, M. Z. Vitolins, G. L. Anderson, A. R. Assaf, T. Bassford, S. A. Beresford, H. R. Black, R. L. Brunner, R. G. Brzyski, B. Caan, R. T. Chlebowski, M. Gass, I. Granek, P. Greenland, J. Hays, D. Heber, G. Heiss, S. L. Hendrix, F. A. Hubbell, K. C. Johnson, and J. M. Kotchen. 2006. Low-fat dietary pattern and risk of cardiovascular disease: The Women’s Health Initiative Randomized Controlled Dietary Modification Trial. Journal of the American Medical Association 295(6):655–666.

Hsia, J., E. Kemper, C. Kiefe, J. Zapka, S. Sofaer, M. Pettinger, D. Bowen, M. Limacher, L. Lillington, and E. Mason. 2000. The importance of health insurance as a determinant of cancer screening: Evidence from the Women’s Health Initiative. Preventive Medicine 31(3):261–270.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Hsia, J., M. H. Criqui, R. J. Rodabough, R. D. Langer, H. E. Resnick, L. S. Phillips, M. Allison, D. E. Bonds, K. Masaki, P. Caralis, and J. M. Kotchen. 2004. Estrogen plus progestin and the risk of peripheral arterial disease: The Women’s Health Initiative. Circulation 109(5):620–626.

Hunt, M. O., L. A. Wise, M. C. Jipguep, Y. C. Cozier, and L. Rosenberg. 2007. Neighborhood racial composition and perceptions of racial discrimination: Evidence from the Black Women’s Health Study. Social Psychology Quarterly 70(3):272–289.

Jackson, R. D., A. Z. LaCroix, M. Gass, R. B. Wallace, J. Robbins, C. E. Lewis, T. Bassford, S. A. Beresford, H. R. Black, P. Blanchette, D. E. Bonds, R. L. Brunner, R. G. Brzyski, B. Caan, J. A. Cauley, R. T. Chlebowski, S. R. Cummings, I. Granek, J. Hays, G. Heiss, S. L. Hendrix, B. V. Howard, J. Hsia, F. A. Hubbell, K. C. Johnson, H. Judd, J. M. Kotchen, L. H. Kuller, R. D. Langer, N. L. Lasser, M. C. Limacher, S. Ludlam, J. E. Manson, K. L. Margolis, J. McGowan, J. K. Ockene, M. J. O’Sullivan, L. Phillips, R. L. Prentice, G. E. Sarto, M. L. Stefanick, L. Van Horn, J. Wactawski-Wende, E. Whitlock, G. L. Anderson, A. R. Assaf, and D. Barad. 2006. Calcium plus vitamin D supplementation and the risk of fractures. New England Journal of Medicine 354(7):669–683.

Jacobs, E. A., K. Karavolos, P. J. Rathouz, T. G. Ferris, and L. H. Powell. 2005. Limited English proficiency and breast and cervical cancer screening in a multiethnic population. American Journal of Public Health 95(8):1410–1416.

Janket, S. J., J. E. Manson, H. Sesso, J. E. Buring, and S. Liu. 2003. A prospective study of sugar intake and risk of type 2 diabetes in women. Diabetes Care 26(4):1008–1015.

Janssen, I., L. H. Powell, S. Crawford, B. Lasley, and K. Sutton-Tyrrell. 2008. Menopause and the metabolic syndrome: The Study of Women’s Health Across the Nation. Archives of Internal Medicine 168(14):1568–1575.

Joffe, H. V., P. M. Ridker, J. E. Manson, N. R. Cook, J. E. Buring, and K. M. Rexrode. 2006. Sex hormone-binding globulin and serum testosterone are inversely associated with C-reactive protein levels in postmenopausal women at high risk for cardiovascular disease. Annals of Epidemiology 16(2):105–112.

Jones, D. J., J. T. Bromberger, K. Sutton-Tyrrell, and K. A. Matthews. 2003. Lifetime history of depression and carotid atherosclerosis in middle-aged women. Archives of General Psychiatry 60(2):153–160.

Karlson, E. W., I. M. Lee, N. R. Cook, J. E. Manson, J. E. Buring, and C. H. Hennekens. 1999a. A retrospective cohort study of cigarette smoking and risk of rheumatoid arthritis in female health professionals. Arthritis and Rheumatism 42(5):910–917.

———. 1999b. Comparison of self-reported diagnosis of connective tissue disease with medical records in female health professionals: The Women’s Health Cohort Study. American Journal of Epidemiology 150(6):652–660.

Karlson, E. W., I. M. Lee, N. R. Cook, J. E. Buring, C. H. Hennekens, and K. J. Bloch. 2001. Serologic evaluations of women exposed to breast implants. Journal of Rheumatology 28(7): 1523–1530.

Karlson, E. W., N. A. Shadick, N. R. Cook, J. E. Buring, and I. M. Lee. 2008. Vitamin E in the primary prevention of rheumatoid arthritis: The Women’s Health Study. Arthritis and Rheumatism 59(11):1589–1595.

Kim, K. S., L. Adams-Campbell, J. R. Palmer, and L. Rosenberg. 1998. Physical activity and high blood pressure: Black Women’s Health Study. Ethnicity and Disease 8:272.

Kravitz, H. M., P. A. Ganz, J. Bromberger, L. H. Powell, K. Sutton-Tyrrell, and P. M. Meyer. 2003. Sleep difficulty in women at midlife: A community survey of sleep and the menopausal transition. Menopause 10(1):19–28.

Kravitz, H. M., I. Janssen, N. Santoro, J. T. Bromberger, M. Schocken, S. A. Everson-Rose, K. Karavolos, and L. H. Powell. 2005. Relationship of day-to-day reproductive hormone levels to sleep in midlife women. Archives of Internal Medicine 165(20):2370–2376.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Kravitz, H. M., X. Zhao, J. T. Bromberger, E. B. Gold, M. H. Hall, K. A. Matthews, and M. R. Sowers. 2008. Sleep disturbance during the menopausal transition in a multi-ethnic community sample of women. Sleep 31(7):979–990.

Kripke D.F., R. Brunner, R. Freeman, S. Hendrix, R. D. Jackson, K. Masaki, and R. A. Carter. 2001. Sleep complaints of postmenopausal women. Clinical Journal of Women’s Health 1:244–252.

Krishnan, S., L. Rosenberg, L. Djousse, L. A. Cupples, and J. R. Palmer. 2007a. Overall and central obesity and risk of type 2 diabetes in U.S. Black women. Obesity 15(7):1860–1866.

Krishnan, S., L. Rosenberg, M. Singer, F. B. Hu, L. Djousse, L. A. Cupples, and J. R. Palmer. 2007b. Glycemic index, glycemic load, and cereal fiber intake and risk of type 2 diabetes in US black women. Archives of Internal Medicine 167(21):2304–2309.

Krishnan, S., L. Rosenberg, and J. R. Palmer. 2008. Fast food consumption and risk of type 2 diabetes in the Black Women’s Health Study. American Journal of Epidemiology 167(Suppl.):S313.

———. 2009. Physical activity and television watching in relation to risk of type 2 diabetes: The Black Women’s Health Study. American Journal of Epidemiology 169(4):428–434.

Kumanyika, S., L. Rosenberg, J. Palmer, R. Rao, and L. Adams-Campbell. 2000. Demographic and personal factors associated with obesity in the Black Women’s Health Study (BWHS) cohort. American Journal of Epidemiology 151:S52.

Kurth, T., C. S. Kase, K. Berger, J. M. Gaziano, N. R. Cook, and J. E. Buring. 2003. Smoking and risk of hemorrhagic stroke in women. Stroke 34(12):2792–2795.

Kurth, T., J. M. Gaziano, K. M. Rexrode, C. S. Kase, N. R. Cook, J. E. Manson, and J. E. Buring. 2005a. Prospective study of body mass index and risk of stroke in apparently healthy women. Circulation 111(15):1992–1998.

Kurth, T., M. A. Slomke, C. S. Kase, N. R. Cook, I. M. Lee, J. M. Gaziano, H. C. Diener, and J. E. Buring. 2005b. Migraine, headache, and the risk of stroke in women: A prospective study. Neurology 64(6):1020–1026.

Kurth, T., B. M. Everett, J. E. Buring, C. S. Kase, P. M. Ridker, and J. M. Gaziano. 2007. Lipid levels and the risk of ischemic stroke in women. Neurology 68(8):556–562.

Kurth, T., R. G. Barr, J. M. Gaziano, and J. E. Buring. 2008a. Randomised aspirin assignment and risk of adult-onset asthma in the Women’s Health Study. Thorax 63(6):514–518.

Kurth, T., M. Schurks, G. Logroscino, J. M. Gaziano, and J. E. Buring. 2008b. Migraine, vascular risk, and cardiovascular events in women: Prospective cohort study. British Medical Journal 337:a636.

LaCroix, A. Z., J. A. Cauley, M. Pettinger, J. Hsia, D. C. Bauer, J. McGowan, Z. Chen, C. E. Lewis, S. G. McNeeley, M. D. Passaro, and R. D. Jackson. 2003. Statin use, clinical fracture, and bone density in postmenopausal women: Results from the Women’s Health Initiative Observational Study. Annals of Internal Medicine 139(2):97–104.

Langer, R. D., A. D. Pradhan, C. E. Lewis, J. E. Manson, J. E. Rossouw, S. L. Hendrix, A. Z. LaCroix, and P. M. Ridker. 2005. Baseline associations between postmenopausal hormone therapy and inflammatory, haemostatic, and lipid biomarkers of coronary heart disease. The Women’s Health Initiative Observational Study. Thrombosis and Haemostasis 93(6):1108–1116.

Lee, I. M., N. R. Cook, J. E. Manson, J. E. Buring, and C. H. Hennekens. 1999. Beta-carotene supplementation and incidence of cancer and cardiovascular disease: The Women’s Health Study. Journal of the National Cancer Institute 91(24):2102–2106.

Lee, I. M., N. R. Cook, K. M. Rexrode, and J. E. Buring. 2001a. Lifetime physical activity and risk of breast cancer. British Journal of Cancer 85(7):962–965.

Lee, I. M., K. M. Rexrode, N. R. Cook, C. H. Hennekens, and J. E. Burin. 2001b. Physical activity and breast cancer risk: The Women’s Health Study (United States). Cancer Causes and Control 12(2):137–145.

Lee, I. M., K. M. Rexrode, N. R. Cook, J. E. Manson, and J. E. Buring. 2001c. Physical activity and coronary heart disease in women: Is “no pain, no gain” passe? Journal of the American Medical Association 285(11):1447–1454.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Lee, I. M., N. R. Cook, J. E. Manson, and J. E. Buring. 2002. Randomised beta-carotene supplementation and incidence of cancer and cardiovascular disease in women: Is the association modified by baseline plasma level? British Journal of Cancer 86(5):698–701.

Lee, I. M., N. R. Cook, J. M. Gaziano, D. Gordon, P. M. Ridker, J. E. Manson, C. H. Hennekens, and J. E. Buring. 2005. Vitamin E in the primary prevention of cardiovascular disease and cancer: The Women’s Health Study: A randomized controlled trial. Journal of the American Medical Association 294(1):56–65.

Levitan, E. B., P. M. Ridker, J. E. Manson, M. J. Stampfer, J. E. Buring, N. R. Cook, and S. Liu. 2005. Association between consumption of beer, wine, and liquor and plasma concentration of high-sensitivity c-reactive protein in women aged 39 to 89 years. American Journal of Cardiology 96(1):83–88.

Levitan, E. B., S. Liu, M. J. Stampfer, N. R. Cook, K. M. Rexrode, P. M. Ridker, J. E. Buring, and J. E. Manson. 2008. HBA1C measured in stored erythrocytes and mortality rate among middle-aged and older women. Diabetologia 51(2):267–275.

Lewis, T. T., S. A. Everson-Rose, L. H. Powell, K. A. Matthews, C. Brown, K. Karavolos, K. Sutton-Tyrrell, E. Jacobs, and D. Wesley. 2006. Chronic exposure to everyday discrimination and coronary artery calcification in African–American women: The SWAN Heart Study. Psychosomatic Medicine 68(3):362–368.

Lewis, T. T., S. A. Everson-Rose, A. Colvin, K. Matthews, J. T. Bromberger, and K. Sutton-Tyrrell. 2009. Interactive effects of race and depressive symptoms on calcification in African American and white women. Psychosomatic Medicine 71(2):163–170.

Lin, J., S. M. Zhang, N. R. Cook, I. M. Lee, and J. E. Buring. 2004. Dietary fat and fatty acids and risk of colorectal cancer in women. American Journal of Epidemiology 160(10):1011–1022.

Lin, J., S. M. Zhang, N. R. Cook, J. E. Manson, I. M. Lee, and J. E. Buring. 2005a. Intakes of calcium and vitamin D and risk of colorectal cancer in women. American Journal of Epidemiology 161(8):755–764.

Lin, J., S. M. Zhang, N. R. Cook, K. M. Rexrode, S. Liu, J. E. Manson, I. M. Lee, and J. E. Buring. 2005b. Dietary intakes of fruit, vegetables, and fiber, and risk of colorectal cancer in a prospective cohort of women (United States). Cancer Causes and Control 16(3):225–233.

Liu, S., J. E. Manson, I. M. Lee, S. R. Cole, C. H. Hennekens, W. C. Willett, and J. E. Buring. 2000. Fruit and vegetable intake and risk of cardiovascular disease: The Women’s Health Study. American Journal of Clinical Nutrition 72(4):922–928.

Liu, S., J. E. Buring, H. D. Sesso, E. B. Rimm, W. C. Willett, and J. E. Manson. 2002a. A prospective study of dietary fiber intake and risk of cardiovascular disease among women. Journal of the American College of Cardiology 39(1):49–56.

Liu, S., J. E. Manson, J. E. Buring, M. J. Stampfer, W. C. Willett, and P. M. Ridker. 2002b. Relation between a diet with a high glycemic load and plasma concentrations of high-sensitivity C-reactive protein in middle-aged women. American Journal of Clinical Nutrition 75(3):492–498.

Liu, S., M. Serdula, S. J. Janket, N. R. Cook, H. D. Sesso, W. C. Willett, J. E. Manson, and J. E. Buring. 2004. A prospective study of fruit and vegetable intake and the risk of type 2 diabetes in women. Diabetes Care 27(12):2993–2996.

Lloyd-Jones, D. M., K. Sutton-Tyrrell, A. S. Patel, K. A. Matthews, R. C. Pasternak, S. A. Everson-Rose, A. Scuteri, and C. U. Chae. 2005. Ethnic variation in hypertension among premenopausal and perimenopausal women: Study of Women’s Health Across the Nation. Hypertension 46(4):689–695.

Manson, J. E., P. Greenland, A. Z. LaCroix, M. L. Stefanick, C. P. Mouton, A. Oberman, M. G. Perri, D. S. Sheps, M. B. Pettinger, and D. S. Siscovick. 2002. Walking compared with vigorous exercise for the prevention of cardiovascular events in women. New England Journal of Medicine 347(10):716–725.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Manson, J. E., M. A. Allison, J. E. Rossouw, J. J. Carr, R. D. Langer, J. Hsia, L. H. Kuller, B. B. Cochrane, J. R. Hunt, S. E. Ludlam, M. B. Pettinger, M. Gass, K. L. Margolis, L. Nathan, J. K. Ockene, R. L. Prentice, J. Robbins, and M. L. Stefanick. 2007. Estrogen therapy and coronary-artery calcification. New England Journal of Medicine 356(25):2591–2602.

Marcus, M. D., J. T. Bromberger, H. L. Wei, C. Brown, and H. M. Kravitz. 2007. Prevalence and selected correlates of eating disorder symptoms among a multiethnic community sample of midlife women. Annals of Behavioral Medicine 33(3):269–277.

Margolis, K. L., D. E. Bonds, R. J. Rodabough, L. Tinker, L. S. Phillips, C. Allen, T. Bassford, G. Burke, J. Torrens, and B. V. Howard. 2004. Effect of oestrogen plus progestin on the incidence of diabetes in postmenopausal women: Results from the Women’s Health Initiative Hormone Trial. Diabetologia 47(7):1175–1187.

Matthews, K. A., B. Abrams, S. Crawford, T. Miles, R. Neer, L. H. Powell, and D. Wesley. 2001. Body mass index in mid-life women: Relative influence of menopause, hormone use, and ethnicity. International Journal of Obesity and Related Metabolic Disorders 25(6):863–873.

Matthews, K. A., M. F. Sowers, C. A. Derby, E. Stein, H. Miracle-McMahill, S. L. Crawford, and R. C. Pasternak. 2005. Ethnic differences in cardiovascular risk factor burden among middle-aged women: Study of Women’s Health Across the Nation (SWAN). American Heart Journal 149(6):1066–1073.

McAlindon, T. E., M. K. Formica, J. R. Palmer, and L. Rosenberg. 2000. Is childhood smoke exposure a risk factor for SLE? Results from the Black Women’s Health Study (BWHS). Arthritis and Rheumatism 43(Suppl.):S237.

McTiernan, A., C. Kooperberg, E. White, S. Wilcox, R. Coates, L. L. Adams-Campbell, N. Woods, and J. Ockene. 2003. Recreational physical activity and the risk of breast cancer in postmenopausal women: The Women’s Health Initiative Cohort Study. Journal of the American Medical Association 290(10):1331–1336.

Meyer, P. M., L. H. Powell, R. S. Wilson, S. A. Everson-Rose, H. M. Kravitz, J. L. Luborsky, T. Madden, D. Pandey, and D. A. Evans. 2003. A population-based longitudinal study of cognitive functioning in the menopausal transition. Neurology 61(6):801–806.

Misakian, A. L., R. D. Langer, I. M. Bensenor, N. R. Cook, J. E. Manson, J. E. Buring, and K. M. Rexrode. 2003. Postmenopausal hormone therapy and migraine headache. Journal of Women’s Health 12(10):1027–1036.

Mora, S., N. Rifai, J. E. Buring, and P. M. Ridker. 2006. Additive value of immunoassay-measured fibrinogen and high-sensitivity C-reactive protein levels for predicting incident cardiovascular events. Circulation 114(5):381–387.

Mora, S, N. Rifai, J. E. Buring, and P.M. Ridker. 2009a. Comparison of LDL cholesterol concentrations by Friedewald calculation and direct measurement in relation to cardiovascular events in 27,331 women. Clinical Chemistry 55(5):888–894.

Mora, S., J. D. Otvos, N. Rifai, R. S. Rosenson, J. E. Buring, and P. M. Ridker. 2009b. Lipoprotein particle profiles by nuclear magnetic resonance compared with standard lipids and apolipoproteins in predicting incident cardiovascular disease in women. Circulation 119(7):931–939.

Morimoto, L. M., E. White, Z. Chen, R. T. Chlebowski, J. Hays, L. Kuller, A. M. Lopez, J. Manson, K. L. Margolis, P. C. Muti, M. L. Stefanick, and A. McTiernan. 2002. Obesity, body size, and risk of postmenopausal breast cancer: The Women’s Health Initiative (United States). Cancer Causes and Control 13(8):741–751.

Ockene, J. K., D. H. Barad, B. B. Cochrane, J. C. Larson, M. Gass, S. Wassertheil-Smoller, J. E. Manson, V. M. Barnabei, D. S. Lane, R. G. Brzyski, M. C. Rosal, J. Wylie-Rosett, and J. Hays. 2005. Symptom experience after discontinuing use of estrogen plus progestin. Journal of the American Medical Association 294(2):183–193.

Oestreicher, N., A. Capra, J. Bromberger, L. M. Butler, C. J. Crandall, E. B. Gold, G. A. Greendale, F. Modugno, B. Sternfeld, and L. A. Habel. 2008. Physical activity and mammographic density in a cohort of midlife women. Medicine & Science in Sports & Exercise 40(3):451–456.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Palmer, J. R., R. S. Rao, L. L. Adams-Campbell, and L. Rosenberg. 1999. Correlates of hysterectomy among African–American women. American Journal of Epidemiology 150(12):1309–1315.

———. 2001. Height and breast cancer risk: Results from the Black Women’s Health Study (United States). Cancer Causes and Control 12(4):343–348.

Palmer, J. R., L. A. Wise, N. J. Horton, L. L. Adams-Campbell, and L. Rosenberg. 2003a. Dual effect of parity on breast cancer risk in African–American women. Journal of the National Cancer Institute 95(6):478–483.

Palmer, J. R., L. Rosenberg, L. A. Wise, N. J. Horton, and L. L. Adams-Campbell. 2003b. Onset of natural menopause in African American women. American Journal of Public Health 93(2):299–306.

Palmer, J. R., L. A. Wise, L. L. Adams-Campbell, and L. Rosenberg. 2004. A prospective study of induced abortion and breast cancer in African–American women. Cancer Causes and Control 15(2):105–111.

———. 2005. Cigarette smoking and risk of breast cancer in the Black Women’s Health Study. American Journal of Epidemiology 161:S55.

Palmer, J. R., L. L. Adams-Campbell, D. A. Boggs, L. A. Wise, and L. Rosenberg. 2006. The relation of overall and central obesity to risk of breast cancer in African–American women. Proceedings of the American Association for Cancer Research 47:2024.

———. 2007a. A prospective study of body size and breast cancer in black women. Cancer Epidemiology, Biomarkers and Prevention 16(9):1795–1802.

Palmer, J. R., L. L. Adams-Campbell, D. A. Boggs, and L. Rosenberg. 2007b. Familial Breast Cancer in a Cohort of 59,000 African–American Women: The Black Women’s Health Study. Paper read at American Association for Cancer Research Annual Meeting: Proceedings; 2007, Los Angeles, CA. Philadelphia, PA.

Palmer, J. R., D. Boggs, L. Adams-Campbell, and L. Rosenberg. 2008a. Glycemic index, sweets, and breast cancer risk in the Black Women’s Health Study. American Journal of Epidemiology 167(Suppl.):S235.

Palmer, J. R., D. A. Boggs, S. Krishnan, F. B. Hu, M. Singer, and L. Rosenberg. 2008b. Sugar-sweetened beverages and incidence of type 2 diabetes mellitus in African American women. Archives of Internal Medicine 168(14):1487–1492.

Pirraglia, P. A., P. Sanyal, D. E. Singer, and T. G. Ferris. 2004. Depressive symptom burden as a barrier to screening for breast and cervical cancers. Journal of Women’s Health 13(6):731–738.

Pope, S. K., M. F. Sowers, G. W. Welch, and G. Albrecht. 2001. Functional limitations in women at midlife: The role of health conditions, behavioral and environmental factors. Women’s Health Issues 11(6):494–502.

Porch, J. V., I. M. Lee, N. R. Cook, K. M. Rexrode, and J. E. Burin. 2002. Estrogen-progestin replacement therapy and breast cancer risk: The Women’s Health Study (United States). Cancer Causes and Control 13(9):847–854.

Powell, L. H., P. Meyer, G. Weiss, K. A. Matthews, N. Santoro, J. F. Randolph, Jr., M. Schocken, J. Skurnick, M. G. Ory, and K. Sutton-Tyrrell. 2005. Ethnic differences in past hysterectomy for benign conditions. Women’s Health Issues 15(4):179–186.

Pradhan, A. D., J. E. Manson, J. B. Meigs, N. Rifai, J. E. Buring, S. Liu, and P. M. Ridker. 2003a. Insulin, proinsulin, proinsulin:Insulin ratio, and the risk of developing type 2 diabetes mellitus in women. American Journal of Medicine 114(6):438–444.

Pradhan, A. D., N. R. Cook, J. E. Buring, J. E. Manson, and P. M. Ridker. 2003b. C-reactive protein is independently associated with fasting insulin in nondiabetic women. Arteriosclerosis, Thrombosis, and Vascular Biology 23(4):650–655.

Pradhan, A. D., N. R. Cook, J. E. Manson, P. M. Ridker, and J. E. Buring. 2009. A randomized trial of low-dose aspirin in the prevention of clinical type 2 diabetes in women. Diabetes Care 32(1):3–8.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Prentice, R. L., B. Caan, R. T. Chlebowski, R. Patterson, L. H. Kuller, J. K. Ockene, K. L. Margolis, M. C. Limacher, J. E. Manson, L. M. Parker, E. Paskett, L. Phillips, J. Robbins, J. E. Rossouw, G. E. Sarto, J. M. Shikany, M. L. Stefanick, C. A. Thomson, L. Van Horn, M. Z. Vitolins, J. Wactawski-Wende, R. B. Wallace, S. Wassertheil-Smoller, E. Whitlock, K. Yano, L. Adams-Campbell, G. L. Anderson, A. R. Assaf, S. A. Beresford, H. R. Black, R. L. Brunner, R. G. Brzyski, L. Ford, M. Gass, J. Hays, D. Heber, G. Heiss, S. L. Hendrix, J. Hsia, F. A. Hubbell, R. D. Jackson, K. C. Johnson, J. M. Kotchen, A. Z. LaCroix, D. S. Lane, R. D. Langer, N. L. Lasser, and M. M. Henderson. 2006. Low-fat dietary pattern and risk of invasive breast cancer: The Women’s Health Initiative Randomized Controlled Dietary Modification Trial. Journal of the American Medical Association 295(6):629–642.

Prentice, R. L., C. A. Thomson, B. Caan, F. A. Hubbell, G. L. Anderson, S. A. Beresford, M. Pettinger, D. S. Lane, L. Lessin, S. Yasmeen, B. Singh, J. Khandekar, J. M. Shikany, S. Satterfield, and R. T. Chlebowski. 2007. Low-fat dietary pattern and cancer incidence in the Women’s Health Initiative Dietary Modification Randomized Controlled Trial. Journal of the National Cancer Institute 99(20):1534–1543.

Randolph, J. F., Jr., M. Sowers, I. V. Bondarenko, S. D. Harlow, J. L. Luborsky, and R. J. Little. 2004. Change in estradiol and follicle-stimulating hormone across the early menopausal transition: Effects of ethnicity and age. Journal of Clinical Endocrinology and Metabolism 89(4):1555–1561.

Rapp, S. R., M. A. Espeland, S. A. Shumaker, V. W. Henderson, R. L. Brunner, J. E. Manson, M. L. Gass, M. L. Stefanick, D. S. Lane, J. Hays, K. C. Johnson, L. H. Coker, M. Dailey, and D. Bowen. 2003. Effect of estrogen plus progestin on global cognitive function in postmenopausal women: The Women’s Health Initiative Memory Study: A randomized controlled trial. Journal of the American Medical Association 289(20):2663–2672.

Resnick, S. M., M. A. Espeland, S. A. Jaramillo, C. Hirsch, M. L. Stefanick, A. M. Murray, J. Ockene, and C. Davatzikos. 2009. Postmenopausal hormone therapy and regional brain volumes: The WHIMS-MRI Study. Neurology 72(2):135–142.

Rexrode, K. M., J. E. Manson, I. M. Lee, P. M. Ridker, P. M. Sluss, N. R. Cook, and J. E. Buring. 2003a. Sex hormone levels and risk of cardiovascular events in postmenopausal women. Circulation 108(14):1688–1693.

Rexrode, K. M., A. Pradhan, J. E. Manson, J. E. Buring, and P. M. Ridker. 2003b. Relationship of total and abdominal adiposity with CRP and IL-6 in women. Annals of Epidemiology 13(10):674–682.

Ridker, P. M., and N. Cook. 2004. Clinical usefulness of very high and very low levels of C-reactive protein across the full range of Framingham risk scores. Circulation 109(16):1955–1959.

Ridker, P. M., J. P. Miletich, C. H. Hennekens, and J. E. Buring. 1997. Ethnic distribution of factor V leiden in 4047 men and women. Implications for venous thromboembolism screening. Journal of the American Medical Association 277(16):1305–1307.

Ridker, P. M., J. E. Buring, J. Shih, M. Matias, and C. H. Hennekens. 1998a. Prospective study of Creactive protein and the risk of future cardiovascular events among apparently healthy women. Circulation 98(8):731–733.

Ridker, P. M., J. P. Miletich, J. E. Buring, A. A. Ariyo, D. T. Price, J. E. Manson, and J. A. Hill. 1998b. Factor V leiden mutation as a risk factor for recurrent pregnancy loss. Annals of Internal Medicine 128(12 Pt. 1):1000–1003.

Ridker, P. M., C. H. Hennekens, J. E. Buring, R. Kundsin, and J. Shih. 1999a. Baseline IgG antibody titers to Chlamydia pneumoniae, Helicobacter pylori, herpes simplex virus, and cytomegalovirus and the risk for cardiovascular disease in women. Annals of Internal Medicine 131(8):573–577.

Ridker, P. M., J. E. Manson, J. E. Buring, J. Shih, M. Matias, and C. H. Hennekens. 1999b. Homocysteine and risk of cardiovascular disease among postmenopausal women. Journal of the American Medical Association 281(19):1817–1821.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Ridker, P. M., C. H. Hennekens, N. Rifai, J. E. Buring, and J. E. Manson. 1999c. Hormone replacement therapy and increased plasma concentration of C-reactive protein. Circulation 100(7): 713–716.

Ridker, P. M., C. H. Hennekens, J. E. Buring, and N. Rifai. 2000. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. New England Journal of Medicine 342(12):836–843.

Ridker, P. M., J. E. Buring, and N. Rifai. 2001. Soluble P-selectin and the risk of future cardiovascular events. Circulation 103(4):491–495.

Ridker, P. M., N. Rifai, L. Rose, J. E. Buring, and N. R. Cook. 2002. Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events. New England Journal of Medicine 347(20):1557–1565.

Ridker, P. M., J. E. Buring, N. R. Cook, and N. Rifai. 2003. C-reactive protein, the metabolic syndrome, and risk of incident cardiovascular events: An 8-year follow-up of 14,719 initially healthy American women. Circulation 107(3):391–397.

Ridker, P. M., N. R. Cook, I. M. Lee, D. Gordon, J. M. Gaziano, J. E. Manson, C. H. Hennekens, and J. E. Buring. 2005a. A randomized trial of low-dose aspirin in the primary prevention of cardiovascular disease in women. New England Journal of Medicine 352(13):1293–1304.

Ridker, P. M., N. Rifai, N. R. Cook, G. Bradwin, and J. E. Buring. 2005b. Non-HDL cholesterol, apolipoproteins A-I and B100, standard lipid measures, lipid ratios, and CRP as risk factors for cardiovascular disease in women. Journal of the American Medical Association 294(3):326–333.

Rifai, N., J. E. Buring, I. M. Lee, J. E. Manson, and P. M. Ridker. 2002. Is C-reactive protein specific for vascular disease in women? Annals of Internal Medicine 136(7):529–533.

Rosenberg, L., R. Rao, L. Adams-Campbell, and J. Palmer. 1997a. Risk factors for myocardial infarction among African–American women. American Journal of Epidemiology 145:S45.

Rosenberg, L., J. R. Palmer, and L. L. Adams-Campbell. 1997b. Postmenopausal female hormone use and venous thromboembolic disease in black women. American Journal of Obstetrics and Gynecology 177(5):1275.

Rosenberg, L., J. R. Palmer, R. S. Rao, and L. L. Adams-Campbell. 1998. Correlates of postmenopausal female hormone use among black women in the United States. Obstetrics and Gynecology 91(3):454–458.

Rosenberg, L., L. L. Adams-Campbell, K. S. Kim, and J. R. Palmer. 1999a. Physical activity and breast cancer among African–American women. American Journal of Epidemiology 149:S53.

Rosenberg, L, J. R. Palmer, R. S. Rao, and L. L. Adams-Campbell. 1999b. Risk factors for coronary heart disease in African American women. American Journal of Epidemiology 150(9): 904–909.

Rosenberg, L., J. R. Palmer, L. L. Adams-Campbell, and R. S. Rao. 1999c. Obesity and hypertension among college-educated black women in the United States. Journal of Human Hypertension 13(4):237–241.

Rosenberg, L., J. Palmer, R. Rao, and M. Corwin. 2000. Risk factors for preterm birth among women in the Black Women’s Health Study. American Journal of Epidemiology 151:S13.

Rosenberg, L., R. Rao, J. Palmer, and L. Adams-Campbell. 2001. Age at natural menopause among African–American women. American Journal of Epidemiology 153:S92.

Rosenberg, L., J. R. Palmer, R. S. Rao, and L. L. Adams-Campbell. 2002a. Patterns and correlates of alcohol consumption among African–American women. Ethnicity and Disease 12(4): 548–554.

Rosenberg, L., J. R. Palmer, L. A. Wise, N. J. Horton, and M. J. Corwin. 2002b. Perceptions of racial discrimination and the risk of preterm birth. Epidemiology 13(6):646–652.

Rosenberg, L., J. R. Palmer, L. A. Wise, N. J. Horton, S. K. Kumanyika, and L. L. Adams-Campbell. 2003. A prospective study of the effect of childbearing on weight gain in African–American women. Obesity Research 11(12):1526–1535.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
×

Rosenberg, L., L. A. Wise, J. R. Palmer, N. J. Horton, and L. L. Adams-Campbell. 2005a. A multilevel study of socioeconomic predictors of regular mammography use among African–American women. Cancer Epidemiology, Biomarkers & Prevention 14(11 Pt. 1):2628–2633.

Rosenberg, L., L. A. Wise, and J. R. Palmer. 2005b. Hair-relaxer use and risk of preterm birth among African–American women. Ethnicity and Disease 15(4):768–772.

Rosenberg, L., J. R. Palmer, L. A. Wise, and L. L. Adams-Campbell. 2006a. A prospective study of female hormone use and breast cancer among black women. Archives of Internal Medicine 166(7):760–765.

Rosenberg, L., D. Boggs, L. A. Wise, J. R. Palmer, M. H. Roltsch, K. H. Makambi, and L. L. Adams-Campbell. 2006b. A follow-up study of physical activity and incidence of colorectal polyps in African–American women. Cancer Epidemiology, Biomarkers and Prevention 15(8):1438–1442.

Rosenberg, L., D. A. Boggs, L. L. Adams-Campbell, and J. R. Palmer. 2007a. Hair relaxers not associated with breast cancer risk: Evidence from the Black Women’s Health Study. Cancer Epidemiology, Biomarkers and Prevention 16(5):1035–1037.

Rosenberg, L., D. A. Boggs, J. Palmer, and L. Adams-Campbell. 2007b. The influence of life-style factors on mortality in the Black Women’s Health Study. American Journal of Epidemiology 165:S84.

Rosenberg, L., D. Boggs, J. Palmer, and L. Adams-Campbell. 2008. Meat, fat, and dairy intake in relation to breast cancer incidence in the Black Women’s Health Study. American Journal of Epidemiology 167 (Suppl.):S520.

Rossouw, J., G. Anderson, R. Prentice, A. LaCroix, C. Kooperberg, M. Stefanick, R. Jackson, S. Beresford, B. Howard, K. Johnson, J. Kotchen, and J. Ockene. 2002. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: Principal results from the Women’s Health Initiative Randomized Controlled Trial. Journal of the American Medical Association 288:321–333.

Rossouw, J. E., R. L. Prentice, J. E. Manson, L. Wu, D. Barad, V. M. Barnabei, M. Ko, A. Z. LaCroix, K. L. Margolis, and M. L. Stefanick. 2007. Postmenopausal hormone therapy and risk of cardiovascular disease by age and years since menopause. Journal of the American Medical Association 297(13):1465–1477.

Sampselle, C. M., S. D. Harlow, J. Skurnick, L. Brubaker, and I. Bondarenko. 2002. Urinary incontinence predictors and life impact in ethnically diverse perimenopausal women. Obstetrics and Gynecology 100(6):1230–1238.

Santoro, N., S. Brockwell, J. Johnston, S. L. Crawford, E. B. Gold, S. D. Harlow, K. A. Matthews, and K. Sutton-Tyrrell. 2007. Helping midlife women predict the onset of the final menses: SWAN, The Study of Women’s Health Across the Nation. Menopause 14(3 Pt. 1):415–424.

Santoro, N., S. L. Crawford, W. L. Lasley, J. L. Luborsky, K. A. Matthews, D. McConnell, J. F. Randolph, Jr., E. B. Gold, G. A. Greendale, S. G. Korenman, L. Powell, M. F. Sowers, and G. Weiss. 2008. Factors related to declining luteal function in women during the menopausal transition. Journal of Clinical Endocrinology and Metabolism 93(5):1711–1721.

Schaumberg, D. A., W. G. Christen, R. J. Glynn, and J. E. Buring. 2000. Demographic predictors of eye care utilization among women. Medical Care 38(6):638–646.

Schaumberg, D. A., J. E. Buring, D. A. Sullivan, and M. R. Dana. 2001. Hormone replacement therapy and dry eye syndrome. Journal of the American Medical Association 286(17):2114–2119.

Schaumberg, D. A., D. A. Sullivan, J. E. Buring, and M. R. Dana. 2003. Prevalence of dry eye syndrome among US women. American Journal of Ophthalmology 136(2):318–326.

Schonbeck, U., N. Varo, P. Libby, J. Buring, and P. M. Ridker. 2001. Soluble CD40L and cardiovascular risk in women. Circulation 104(19):2266–2268.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Scuteri, A., M. Vuga, S. S. Najjar, V. Mehta, S. A. Everson-Rose, K. Sutton-Tyrrell, K. Matthews, and E. G. Lakatta. 2008. Education eclipses ethnicity in predicting the development of the metabolic syndrome in different ethnic groups in midlife: The Study of Women’s Health Across the Nation (SWAN). Diabetic Medicine 25(12):1390–1399.

Sesso, H. D., I. M. Lee, J. M. Gaziano, K. M. Rexrode, R. J. Glynn, and J. E. Buring. 2001. Maternal and paternal history of myocardial infarction and risk of cardiovascular disease in men and women. Circulation 104(4):393–398.

Sesso, H. D., J. M. Gaziano, S. Liu, and J. E. Buring. 2003a. Flavonoid intake and the risk of cardiovascular disease in women. American Journal of Clinical Nutrition 77(6):1400–1408.

Sesso, H. D., S. Liu, J. M. Gaziano, and J. E. Buring. 2003b. Dietary lycopene, tomato-based food products and cardiovascular disease in women. Journal of Nutrition 133(7):2336–2341.

Sesso, H. D., J. E. Buring, N. Rifai, G. J. Blake, J. M. Gaziano, and P. M. Ridker. 2003c. C-reactive protein and the risk of developing hypertension. Journal of the American Medical Association 290(22):2945–2951.

Sesso, H. D., R. S. Chen, G. J. L’Italien, P. Lapuerta, W. C. Lee, and R. J. Glynn. 2003d. Blood pressure lowering and life expectancy based on a Markov model of cardiovascular events. Hypertension 42(5):885–890.

Sesso, H. D., J. E. Buring, E. P. Norkus, and J. M. Gaziano. 2004. Plasma lycopene, other carotenoids, and retinol and the risk of cardiovascular disease in women. American Journal of Clinical Nutrition 79(1):47–53.

Sesso, H. D., J. E. Buring, M. J. Chown, P. M. Ridker, and J. M. Gaziano. 2005. A prospective study of plasma lipid levels and hypertension in women. Archives of Internal Medicine 165(20):2420–2427.

Shumaker, S. A., C. Legault, L. Kuller, S. R. Rapp, L. Thal, D. S. Lane, H. Fillit, M. L. Stefanick, S. L. Hendrix, C. E. Lewis, K. Masaki, and L. H. Coker. 2004. Conjugated equine estrogens and incidence of probable dementia and mild cognitive impairment in postmenopausal women: Women’s Health Initiative Memory Study. Journal of the American Medical Association 291(24):2947–2958.

Skurnick, J. H., G. Weiss, L. T. Goldsmith, N. Santoro, and S. Crawford. 2009. Longitudinal changes in hypothalamic and ovarian function in perimenopausal women with anovulatory cycles: Relationship with vasomotor symptoms. Fertility and Sterility 91(4):1127–1134.

Song, Y., J. E. Manson, J. E. Buring, and S. Liu. 2004a. Dietary magnesium intake in relation to plasma insulin levels and risk of type 2 diabetes in women. Diabetes Care 27(1):59–65.

———. 2004b. A prospective study of red meat consumption and type 2 diabetes in middle-aged and elderly women: The Women’s Health Study. Diabetes Care 27(9):2108–2115.

Song, Y., J. E. Manson, J. E. Buring, H. D. Sesso, and S. Liu. 2005a. Associations of dietary flavonoids with risk of type 2 diabetes, and markers of insulin resistance and systemic inflammation in women: A prospective study and cross-sectional analysis. Journal of the American College of Nutrition 24(5):376–384.

Song, Y., P. M. Ridker, J. E. Manson, N. R. Cook, J. E. Buring, and S. Liu. 2005b. Magnesium intake, C-reactive protein, and the prevalence of metabolic syndrome in middle-aged and older U.S. women. Diabetes Care 28(6):1438–1444.

Sowers, M., S. Pope, G. Welch, B. Sternfeld, and G. Albrecht. 2001. The association of menopause and physical functioning in women at midlife. Journal of the American Geriatrics Society 49(11):1485–1492.

Sowers, M. R., J. S. Finkelstein, B. Ettinger, I. Bondarenko, R. M. Neer, J. A. Cauley, S. Sherman, and G. A. Greendale. 2003. The association of endogenous hormone concentrations and bone mineral density measures in pre- and perimenopausal women of four ethnic groups: SWAN. Osteoporosis International 14(1):44–52.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Sowers, M. R., J. Randolph, Jr., M. Jannausch, B. Lasley, E. Jackson, and D. McConnell. 2008. Levels of sex steroid and cardiovascular disease measures in premenopausal and hormone-treated women at midlife: Implications for the “timing hypothesis.” Archives of Internal Medicine 168(19):2146–2153.

Stefanick, M. L., G. L. Anderson, K. L. Margolis, S. L. Hendrix, R. J. Rodabough, E. D. Paskett, D. S. Lane, F. A. Hubbell, A. R. Assaf, G. E. Sarto, R. S. Schenken, S. Yasmeen, L. Lessin, and R. T. Chlebowski. 2006. Effects of conjugated equine estrogens on breast cancer and mammography screening in postmenopausal women with hysterectomy. Journal of the American Medical Association 295(14):1647–1657.

Suk Danik, J., N. Rifai, J. E. Buring, and P. M. Ridker. 2008. Lipoprotein(A), hormone replacement therapy, and risk of future cardiovascular events. Journal of the American College of Cardiology 52(2):124–131.

Taylor, T. R., C. D. Williams, K. H. Makambi, C. Mouton, J. P. Harrell, Y. Cozier, J. R. Palmer, L. Rosenberg, and L. L. Adams-Campbell. 2007. Racial discrimination and breast cancer incidence in US black women: The Black Women’s Health Study. American Journal of Epidemiology 166(1):46–54.

Thurston, R. C., K. Sutton-Tyrrell, S. A. Everson-Rose, R. Hess, and K. A. Matthews. 2008a. Hot flashes and subclinical cardiovascular disease: Findings from the Study of Women’s Health Across the Nation Heart Study. Circulation 118(12):1234–1240.

Thurston, R. C., M. R. Sowers, K. Sutton-Tyrrell, S. A. Everson-Rose, T. T. Lewis, D. Edmundowicz, and K. A. Matthews. 2008b. Abdominal adiposity and hot flashes among midlife women. Menopause 15(3):429–434.

Thurston, R. C., J. Bromberger, Y. Chang, E. Goldbacher, C. Brown, J. M. Cyranowski, and K. A. Matthews. 2008c. Childhood abuse or neglect is associated with increased vasomotor symptom reporting among midlife women. Menopause 15(1):16–22.

Thurston, R. C., M. R. Sowers, Y. Chang, B. Sternfeld, E. B. Gold, J. M. Johnston, and K. A. Matthews. 2008d. Adiposity and reporting of vasomotor symptoms among midlife women: The Study of Women’s Health Across the Nation. American Journal of Epidemiology 167(1):78–85.

Tinker, L. F., D. E. Bonds, K. L. Margolis, J. E. Manson, B. V. Howard, J. Larson, M. G. Perri, S. A. Beresford, J. G. Robinson, B. Rodriguez, M. M. Safford, N. K. Wenger, V. J. Stevens, and L. M. Parker. 2008. Low-fat dietary pattern and risk of treated diabetes mellitus in postmenopausal women: The Women’s Health Initiative Randomized Controlled Dietary Modification Trial. Archives of Internal Medicine 168(14):1500–1511.

Tomey, K. M., M. R. Sowers, C. Crandall, J. Johnston, M. Jannausch, and M. Yosef. 2008. Dietary intake related to prevalent functional limitations in midlife women. American Journal of Epidemiology 167(8):935–943.

van Dam, R. M., F. B. Hu, L. Rosenberg, S. Krishnan, and J. R. Palmer. 2006. Dietary calcium and magnesium, major food sources, and risk of type 2 diabetes in US black women. Diabetes Care 29(10):2238–2243.

Van Voorhis, B. J., N. Santoro, S. Harlow, S. L. Crawford, and J. Randolph. 2008. The relationship of bleeding patterns to daily reproductive hormones in women approaching menopause. Obstetrics and Gynecology 112(1):101–108.

Wactawski-Wende, J., J. M. Kotchen, G. L. Anderson, A. R. Assaf, R. L. Brunner, M. J. O’Sullivan, K. L. Margolis, J. K. Ockene, L. Phillips, L. Pottern, R. L. Prentice, J. Robbins, T. E. Rohan, G. E. Sarto, S. Sharma, M. L. Stefanick, L. Van Horn, R. B. Wallace, E. Whitlock, T. Bassford, S. A. Beresford, H. R. Black, D. E. Bonds, R. G. Brzyski, B. Caan, R. T. Chlebowski, B. Cochrane, C. Garland, M. Gass, J. Hays, G. Heiss, S. L. Hendrix, B. V. Howard, J. Hsia, F. A. Hubbell, R. D. Jackson, K. C. Johnson, H. Judd, C. L. Kooperberg, L. H. Kuller, A. Z. LaCroix, D. S. Lane, R. D. Langer, N. L. Lasser, C. E. Lewis, M. C. Limacher, and J. E. Manson. 2006. Calcium plus vitamin D supplementation and the risk of colorectal cancer. New England Journal of Medicine 354(7):684–696.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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Waetjen, L. E., S. Liao, W. O. Johnson, C. M. Sampselle, B. Sternfield, S. D. Harlow, and E. B. Gold. 2007. Factors associated with prevalent and incident urinary incontinence in a cohort of midlife women: A longitudinal analysis of data: Study of Women’s Health Across the Nation? American Journal of Epidemiology 165(3):309–318.

Waetjen, L. E., W. Y. Feng, J. Ye, W. O. Johnson, G. A. Greendale, C. M. Sampselle, B. Sternfield, S. D. Harlow, and E. B. Gold. 2008. Factors associated with worsening and improving urinary incontinence across the menopausal transition? Obstetrics and Gynecology 111(3):667–677.

Wassertheil-Smoller, S., G. Anderson, B. M. Psaty, H. R. Black, J. Manson, N. Wong, J. Francis, R. Grimm, T. Kotchen, R. Langer, and N. Lasser. 2000. Hypertension and its treatment in postmenopausal women: Baseline data from the Women’s Health Initiative? Hypertension 36(5):780–789.

Wassertheil-Smoller, S., S. Shumaker, J. Ockene, G. A. Talavera, P. Greenland, B. Cochrane, J. Robbins, A. Aragaki, and J. Dunbar-Jacob. 2004. Depression and cardiovascular sequelae in postmenopausal women. The Women’s Health Initiative (WHI)? Archives of Internal Medicine 164(3):289–298.

Weinstein, A. R., H. D. Sesso, I. M. Lee, N. R. Cook, J. E. Manson, J. E. Buring, and J. M. Gaziano. 2004. Relationship of physical activity vs body mass index with type 2 diabetes in women? Journal of the American Medical Association 292(10):1188–1194.

Weiss, G., D. Noorhasan, L. L. Schott, L. Powell, J. F. Randolph, Jr., and J. M. Johnston. 2009. Racial differences in women who have a hysterectomy for benign conditions? Women’s Health Issues 19(3):202–210.

Williams, C. D., L. L. Adams-Campbell, T. R. Taylor, J. R. Palmer, and L. Rosenberg. 2004. Depressive symptoms by socio-demographic characteristics in the Black Women’s Health Study? Annals of Behavioral Medicine 24(Suppl.):S146.

Wise, L. A., J. R. Palmer, B. L. Harlow, D. Spiegelman, E. A. Stewart, L. L. Adams-Campbell, and L. Rosenberg. 2004a. Reproductive factors, hormonal contraception, and risk of uterine leiomyomata in African–American women: A prospective study? American Journal of Epidemiology 159(2):113–123.

———. 2004b. Risk of uterine leiomyomata in relation to tobacco, alcohol and caffeine consumption in the Black Women’s Health Study? Human Reproduction 19(8):1746–1754.

Wise, L. A., J. R. Palmer, E. A. Stewart, and L. Rosenberg. 2005a. Age-specific incidence rates for self-reported uterine leiomyomata in the Black Women’s Health Study? Obstetrics and Gynecology 105(3):563–568.

Wise, L. A., J. R. Palmer, D. Spiegelman, B. L. Harlow, E. A. Stewart, L. L. Adams-Campbell, and L. Rosenberg. 2005b. Influence of body size and body fat distribution on risk of uterine leiomyomata in U.S. black women? Epidemiology 16(3):346–354.

Wise, L. A., L. L. Adams-Campbell, J. R. Palmer, and L. Rosenberg. 2006. Leisure time physical activity in relation to depressive symptoms in the Black Women’s Health Study? Annals of Behavioral Medicine 32(1):68–76.

Wise, L. A., J. R. Palmer, E. A. Stewart, and L. Rosenberg. 2007a. Polycystic ovary syndrome and risk of uterine leiomyomata? Fertility and Sterility 87(5):1108–1115.

Wise, L. A., J. R. Palmer, Y. C. Cozier, M. O. Hunt, E. A. Stewart, and L. Rosenberg. 2007b. Perceived racial discrimination and risk of uterine leiomyomata? Epidemiology 18(6):747–757.

Wise, L., J. Palmer, C. Poser, M. Ronthal, and L. Rosenberg. 2007c. Geographic variation of MS incidence in the Black Women’s Health Study? American Journal of Epidemiology 165:S68.

Wise, L. A., L. Rosenberg, J. R. Palmer, and L. L. Adams-Campbell. 2008a. Anthropometric risk factors for colorectal polyps in African–American women? Obesity 16(4):859–868.

Wise, L., J. Palmer, L. Heffner, and L. Rosenberg. 2008b. Maternal anthropometric risk factors for preterm birth in the Black Women’s Health Study? American Journal of Epidemiology 167 (Suppl.):S79.

Suggested Citation:"Appendix C: Selected Studies of Women's Health." Institute of Medicine. 2010. Women's Health Research: Progress, Pitfalls, and Promise. Washington, DC: The National Academies Press. doi: 10.17226/12908.
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