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Weight Gain During Pregnancy: Reexaming the Guidelines APPENDIX E Results from the Evidence-Based Report* on Outcomes of Maternal Weight Gain The purpose of this systematic evidence-based review, requested by the Agency for Healthcare Research and Quality (AHRQ) and conducted by the RTI International—University of North Carolina at Chapel Hill Evidence-based Practice Center (RTI-UNC EPC), was to review the evidence on outcomes of gestational weight gain with specific attention to five key questions: KQ 1. What is the evidence that either total weight gain or rate of weight gain during pregnancy is associated with (1) birth outcomes, (2) infant health outcomes, and (3) maternal health outcomes? Does any evidence suggest that either total weight gain or rate of weight gain is a causal factor in infant or maternal health outcomes? KQ 2. What are the confounders and effect modifiers for the association between gestational weight gain (overall and patterns) and birth outcomes? Based on the findings in KQ 1, do these confounders and effect modifiers themselves contribute to antepartum or postpartum complications or to longer-term maternal and fetal complications, including development of adult obesity? KQ 3. What is the evidence that weight gains above or below thresholds defined in the 1990 IOM body mass index (BMI) guide- * Appendixes and evidence tables cited in this report are provided electronically at http://www.ahrq.gov/downloads/pub/evidence/pdf/admaternal/admaternalapp.pdf.
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Weight Gain During Pregnancy: Reexaming the Guidelines lines or weight loss in pregnancy contribute to antepartum or postpartum complications or longer-term maternal and fetal complications? How do these relationships vary by sociodemographic characteristics (i.e., race and age)? KQ 4. What are the harms or benefits of offering the same weight gain recommendations to all pregnant women, irrespective of age and body weight considerations (e.g., pregravid weight, actual body weight at a particular time point, or optimal body weight)? KQ 5. What are the anthropometric tools for determining adiposity and their appropriateness for the pregnancy state? What are the risks and benefits of measuring adiposity for (1) clinical management of weight gain during pregnancy and (2) evaluation of the relationship between weight gain and outcomes of pregnancy? The review focused on screening studies from 1990 to October 2007 that were published in English, and excluded studies with low sample size (case series < 100 and cohorts < 40) or failure to control for pregravid weight. In total, 150 studies were systematically reviewed and each was rated on quality and used to assess the strength of evidence for each outcome. The report, including appendices and evidence tables, can be accessed and viewed in its entirety at http://www.ahrq.gov/clinic/tp/admattp.htm. Literature published outside of the scope of the report (prior to 1990 and after October 2007) are reviewed in Appendix C of this report. The methods and results and of the evidence review (Chapter 3 of the report) are provided below. CHAPTER 2: METHODS In this chapter, we document the procedures that the RTI International-University of North Carolina Evidence-based Practice Center (RTI-UNC EPC) used to develop this comprehensive evidence report on outcomes of maternal weight gain. The team was led by a senior health services researcher (Meera Viswanathan, PhD, Study Director), a senior epidemiologist (Anna Maria Siega-Riz, PhD, RD, Scientific Director), and a senior nurse-researcher (Merry-K Moos, FNP, MPH, co-Scientific Director). We first describe our strategy for identifying articles relevant to our five key questions (KQs), our inclusion and exclusion criteria, and the process we used to abstract relevant information from the eligible articles and generate our evidence tables. We also discuss our criteria for grading the quality of individual articles and for rating the strength of the evidence as a whole. Finally, we explain the peer-review process.
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Weight Gain During Pregnancy: Reexaming the Guidelines TABLE 1. Inclusion/exclusion Criteria for Gestational Weight Gain Category Criteria Study population Women of any age with singleton pregnancies Study settings and geography KQ 1, KQ 2, KQ 4: Developed nations: United States, Canada, Western Europe, Japan, Australia, New Zealand KQ 3: United States KQ 5: All countries Time period January 1990 through October 2007 Publication languages English only Admissible evidence (study design and other criteria) Admissible designs Controlled trials (n ≥ 40), nonrandomized controlled trials (n ≥ 40), systematic reviews, meta-analyses, prospective trials with historical controls (n ≥ 40), prospective or retrospective observational cohort studies (n ≥ 40), and medium to large case series (n ≥ 100) Other criteria Original research studies must provide sufficient detail regarding methods and results to enable use and adjustment of the data and results. Relevant outcomes must be abstractable from data presented in the papers. Sample sizes must be appropriate for the study question addressed in the paper; single case reports or small case series (fewer than 100 subjects) are excluded. For KQ 1, 2, 3, and 4: prepregnancy body mass index (BMI) or weight must be accounted for in the relationship between maternal weight gain and outcome. Studies limited to women with preexisting health conditions only are excluded. Literature Review Methods Inclusion and Exclusion Criteria Our inclusion and exclusion criteria are documented in Table 1. As noted in Chapter 1, this systematic review focuses on outcomes of maternal weight gain with respect to the 1990 recommendations from the Institute of Medicine (IOM). Largely for that reason, we limited our searches to articles published in 1990 and thereafter. We also restricted our searches to developed countries so that we could have data generally relevant for maternal weight gain and health outcomes in the United States. We excluded studies that (1) were published in languages other than English (given the available time and resources); (2) did not report information pertinent to the key clinical questions; (3) had fewer than 40 subjects
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Weight Gain During Pregnancy: Reexaming the Guidelines for randomized controlled trials (RCTs) or nonrandomized cohorts with comparisons or fewer than 100 subjects for case series; and (4) were not original studies. For KQ 1, 2, 3, and 4, we required that the reported association between maternal weight gain and health outcomes accounted for prepregnancy body mass index (BMI) or weight, either through stratified univariate analysis or multivariate analysis. Literature Search and Retrieval Process Databases We used multifaceted search strategies to include current and valid research on the KQs, which we applied to four standard electronic databases—MEDLINE®, Cochrane Collaboration resources, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Embase. We also hand-searched the reference lists of relevant articles to make sure that we did not miss any relevant studies. We consulted with our Technical Expert Panel (TEP) about any studies or trials that are currently under way or that may not yet be published. Search terms. Based on the inclusion/exclusion criteria above, we generated a list of Medical Subject Heading (MeSH) search terms (Table 2 and Appendix A*). Our TEP also reviewed these terms to ensure that we were not missing any critical areas, and this list represents our collective decisions as to the MeSH terms used for all searches. TABLE 2. MEDLINE® Search Strategy and Unduplicated Results for February 2007 Search Terms Search Results #2 Search “Weight Gain”[MeSH] 13,220 #5 Search pregnancy [MeSH] 577,647 #6 Search #2 AND #5 1,808 #7 Search gestational weight gain 1,725 #8 Search #6 OR #7 3,023 #9 Search #6 OR #7 Limits: English, Humans 1,696 #15 Search (“Outcome Assessment (Health Care)”[MeSH] OR “Outcome and Process Assessment (Health Care)”[MeSH] OR “Pregnancy Outcome”[MeSH]) OR “Reproductive History”[MeSH] OR “birth outcomes” OR “infant health outcomes” OR “maternal health outcomes” Limits: English, Humans 332,914 #16 Search #9 AND #15 Limits: English, Humans 474 #19 Search (“Counseling”[MeSH] OR “Directive Counseling”[MeSH]) 23,091 #20 Search #9 AND #19 12 #25 Search “Body Weights and Measures”[MeSH] 279,399 #26 Search #9 AND #25 1,044 #29 Search “Anthropometry”[MeSH] 71,849 #30 Search #26 AND #29 359
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Weight Gain During Pregnancy: Reexaming the Guidelines Our searches in MEDLINE® produced 715 unduplicated records. Searches in other databases yielded in 190 new records from CINAHL and 4 from Embase. Similar searches in Cochrane did not produce any new citations. Following an update on October 3, 2007, and additional searches for KQ 5, we ultimately identified 1,082 unduplicated records. In addition, peer reviews suggested 3 new citations that met our inclusion criteria. Figure 1 presents the yield and results from our searches, which we conducted from February through October 3, 2007. Beginning with a yield FIGURE 1. Disposition of articles for gestational weight gain.
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Weight Gain During Pregnancy: Reexaming the Guidelines of 1,085 articles, we retained 150 articles that we determined were relevant to address our KQs and met our inclusion/exclusion criteria (Table 1). We reviewed titles and abstracts of the articles against the basic inclusion criteria above; we retained relevant articles, all published after our search cutoff date of January 1990, and used them as appropriate in the discussion in Chapter 4. Article selection process Once we had identified articles through the electronic database searches, review articles, and reference lists, we examined abstracts of articles to determine whether studies met our criteria. Each abstract was independently, dually reviewed for inclusion or exclusion, using an Abstract Review Form (Appendix B). If one reviewer concluded that the article should be included in the review, we retained it. Of this entire group of 1,085 articles, 479 required full review. For the full article review, one team member read each article and decided whether it met our inclusion criteria, using a Full Text Inclusion/Exclusion Form (Appendix B*). Reasons for article exclusion are listed in Appendix D. Literature Synthesis Development of Evidence Tables and Data Abstraction Process The senior staff who conducted this systematic review jointly developed the evidence tables. We designed the tables to provide sufficient information to enable readers to understand the studies and to determine their quality; we gave particular emphasis to essential information related to our KQs. We based the format of our evidence tables on successful designs that we have used for prior systematic reviews. We trained abstractors by having them abstract several articles into evidence tables and then reconvening as a group to discuss the utility of the table design. The abstractors repeated this process through several iterations until they decided that the tables included the appropriate categories for gathering the information contained in the articles. Three junior epidemiologists (Sunni Mumford, SM; Andrea Deierlein, MS, MPH; and Julie K. Knaack, MPH, RD, LDN) shared the task of initially entering information into the evidence tables. Senior staff reviewed the articles and edited all initial table entries for accuracy, completeness, and consistency. Abstractors reconciled all disagreements concerning the information reported in the evidence tables. The full research team met regularly during the article abstraction period and discussed global issues related to the data abstraction process. The final evidence tables are presented in their entirety in Appendix C. Studies are presented in the evidence tables alphabetically by the last name
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Weight Gain During Pregnancy: Reexaming the Guidelines of the first author. A list of abbreviations and acronyms used in the tables appears at the beginning of that appendix. Quality Rating of Individual Studies The evidence for this systematic review is based almost entirely on observational studies. This fact presents a challenge for rating individual studies. Quality rating forms for RCTs have been validated and in use for several years; a similarly well-validated form for observational studies does not exist. Thus, as a parallel effort, we developed a form to rate observational studies.35 This form, which can be used to rate the quality of a variety of observational studies, was based on a review of more than 90 AHRQ systematic reviews that included observational studies; we supplemented this review with other key articles identifying domains and scales.36,37 We structured the resultant form largely on the basis of the domains and subdomains suggested by Deeks and colleagues;36 we then adapted it for use in this systematic review (Appendix B*). The form currently includes review of nine key domains: background, sample selection, specification of exposure, specification of outcome, soundness of information, followup, analysis comparability, analysis of outcome, and interpretation. Each of these domains was further evaluated on aspects of quality of the study design or reporting that would influence the reader’s perception of internal validity of the journal article (Table 3). We note that variations in reporting could result in different scores for studies drawing from the same sample. As described in Table 3, we combined these elements to generate overall scores. We set the default as fair and then focused on the threshold required for good and poor studies; the algorithm is also described in Table 3. Fair studies, therefore, include studies that were predominantly fair (four to nine fair ratings on domains) and could not be rated either good (fewer than five good ratings for subdomains) or poor (fewer than three poor ratings for subdomains). Studies with more than five good ratings for domains that also received one or two poor ratings were downgraded to fair quality. Key methodological concerns in this literature relate to the source of information on weight gain and the timing of measurement of weight gain. Studies that relied solely on self-reported pregravid and final pregnancy weights suffer from well-documented issues of recall bias. In addition, women tend to misreport their weight, and this bias varies by weight status38 and ethnicity.39 The timing of weight measurement (for pregravid weight and final weight) can vary depending on the design of the study; when unreported, the total weight gain during pregnancy cannot be assumed to be collected at similar time points for all women within the study,
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Weight Gain During Pregnancy: Reexaming the Guidelines TABLE 3. Scoring Algorithm for Subdomains and Overall Quality Rating for Individual Studies Definition and Scoring Algorithm Rating Score algorithm for background (presented in the context of previous research, hypothesis clearly described) • Both elements present Good • Neither present Poor • One of two elements present Fair Score algorithm for sample definition (explicitly stated inclusion/exclusion criteria, uniform application of criteria, clear description of recruitment strategy, clear description of characteristics of the participants, power analysis or some other basis noted for determining the adequacy of study sample size) • > Three elements present Good • < Two elements present Poor • Two or three elements present Fair Score algorithm for exposure (clear definition of weight gain, check for plausibility of pregravid weight, clear explanation of actions taken on outliers) • All three elements present or clearly defined Good • Poor definition of weight gain Poor • Moderate or very clear definition of weight gain, one or more other elements present Fair Score algorithm for outcome (clear description of primary outcomes) • All essential details described Good • Few or no essential details described Poor • Some essential details described Fair Score algorithm for soundness of information (quality of source of information on exposure, confounders, and outcome) • Good for all three Good • Poor on source of information for exposure Poor • Any other score Fair Score algorithm for followup (adequate reporting of reasons for loss to followup) • Retrospective or prospective study with clear reporting on loss to followup Good • Prospective study, no reporting on followup Poor • Retrospective study with no reporting on loss to followup Fair Score algorithm for analysis comparability (comparability of cohorts through design, reasonable choice of control variables, clear description of confounders, adequate adjustment for confounders) • All elements present Good • Inadequate adjustment for confounding Poor • Any other score Fair Score algorithm for analysis outcome (withdrawals, lost to followup, and missing data adequately accounted for in the analysis, and appropriate statistical methods used)
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Weight Gain During Pregnancy: Reexaming the Guidelines Definition and Scoring Algorithm Rating • Both elements clearly present Good • Neither element present Poor • Any other score Fair Score algorithm for interpretation (results interpreted appropriately based on study design and statistics, clinically useful, appropriate presentation, presented in the context of prior research, and conclusion supported by results) • All elements clearly present Good • Conclusions not supported by results Poor • Any other score Fair Score algorithm for overall quality • 5 or more good ratings and no poor ratings on subdomains Good • 3 or more poor ratings on subdomains Poor • < 5 good ratings and < 3 poor ratings on subdomains; 5 or more good ratings and any poor ratings Fair resulting in further bias. Our rating algorithm, therefore, paid special attention to the source of data on gestational weight gain and the timing of measurement. Studies that relied solely on recalled prepregnancy and total pregnancy weight were rated poor on that domain, but if they defined their gestational weight variable clearly (providing details on the timing of measurement for pregravid and final weight measurements) and either checked for the biological plausibility of pregravid weight status or explained how outliers were dealt with, they could receive an overall fair rating (assuming that they received fewer than three poor ratings overall). Strength of Available Evidence Our scheme follows the criteria applied in an earlier RTI-UNC EPC systematic review of systems for rating the strength of a body of evidence.40 That system has three domains: quality of the research (as evaluated by the quality rating algorithm described above), quantity of studies (including number of studies and adequacy of the sample size), and consistency of findings. Two senior staff members assigned grades by consensus. We graded the body of literature for each KQ and present those ratings as part of the discussion in Chapter 4. The possible grades in our scheme are as follows: Strong: The evidence is from studies of sound design (good quality); results are both clinically important and consistent with minor exceptions at most; results are free from serious doubts about generalizability, bias, or
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Weight Gain During Pregnancy: Reexaming the Guidelines flaws in research design. Studies with negative results have sufficiently large samples to have adequate statistical power. Moderate: The evidence is from studies of sound design (good quality), but some uncertainty remains because of inconsistencies or concern about generalizability, bias, research design flaws, or adequate sample size. Alternatively, the evidence is consistent but derives from studies of weaker design (fair quality). Weak: The evidence is from a limited number of studies of weaker design (fair or poor quality). Studies with strong design (good quality) either have not been done or are inconclusive. No evidence: No published literature. External Peer Review As is customary for all evidence reports and systematic reviews done for AHRQ, the RTI-UNC EPC requested review of this report from a wide array of individual outside experts in the field, including our TEP, and from relevant professional societies and public organizations. AHRQ also requested review from its own staff. We sent 20 invitations for peer review: 6 TEP members, 6 relevant organizations, and 8 individual experts. Reviewers included clinicians (e.g., obstetrics and gynecology, women’s health/general health), representatives of federal agencies, advocacy groups, and potential users of the report. We charged peer reviewers with commenting on the content, structure, and format of the evidence report, providing additional relevant citations, and pointing out issues related to how we had conceptualized and defined the topic and KQs. We also asked them to complete a peer review checklist. We received comments from 11 of the invited peer reviewers in addition to comments from AHRQ staff. The individuals listed in Appendix E** gave us permission to acknowledge their review of the draft. We compiled all comments and addressed each one individually, revising the text as appropriate. CHAPTER 3: RESULTS This chapter presents the results of our evidence review for the following four key questions (KQs): KQ 1, outcomes of gestational weight gain; KQ 3, outcomes of gestational weight gain within or outside the recommendations of the Institute of Medicine (IOM); and KQ 5, anthropometrics of gestational weight gain. We note that KQ 2, on modifiers of outcomes, is derivative of KQ 1. KQ 4, on recommendations for weight gain, is derivative of KQ 3. Because we framed KQ 2 and KQ4 as synthesis questions, we cover them in Chapter 4.
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Weight Gain During Pregnancy: Reexaming the Guidelines Appendix C provides the detailed evidence tables for KQs 1, 3, and 5. Our summary tables below feature groups of studies addressing each outcome; we present these text tables only when we have three or more studies pertaining to that particular outcome. These tables are organized by quality (good, then fair, then poor), and then alphabetically. The summary tables generally provide information to identify the study (author and date), sample size, study quality, definition of gestational weight gain, definition of outcome, results, and confounders and effect modifiers. Unless otherwise noted, we use the metrics (e.g., grams, kilograms, pounds) that each study article used; we did not recalculate measures into the same metric. KQ 1: Outcomes of Gestational Weight Gain We present outcomes in the physiological order, beginning with maternal antepartum and intrapartum outcomes, then birth outcomes (neonatal outcomes at the time of birth), infant outcomes (< 1 year), child outcomes (≥ 1 year), and finally maternal short- and long-term outcomes. Evidence Tables 1-35 (Appendix C) include studies relevant for KQ 1, listed alphabetically by author. For each outcome, we describe study characteristics and then report an overview of results, followed by detailed results. When meaningful, we present results separately for varied measures of gestational weight gain (categorical measures of weight gain, rate of weight gain, total weight gain, and other). For some bodies of evidence, variations in the definition of the outcome and inconsistencies in the direction of effect may suggest that an overall assessment of the effect is more meaningful than separate assessments of outcomes associated with each measure of gestational weight gain. Summary tables and text include information on the confounders and effect modifiers accounted for in each study. Maternal Antepartum Outcomes Maternal discomforts of pregnancy Study characteristics Five studies (Evidence Table 1) investigated the relationship between weight gain and diverse maternal discomforts of pregnancy: a composite of pregnancy discomforts,41 physical energy and fatigue,42 stretch marks,43,44 and heartburn.45 Overview of results Two fair41,42 and three poor studies43-45 found no differences for women who gained an excessive amount of weight compared to those who did not, irrespective of body mass index (BMI) group,42 a higher frequency of symptoms from midpregnancy through the 36th week of gestation,46 no association between gestational weight gain
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Weight Gain During Pregnancy: Reexaming the Guidelines 25. SR Devader, HL Neeley, TD Myles, and TL Leet. Evaluation of gestational weight gain guidelines for women with normal prepregnancy body mass index Obstet Gynecol 2007. Oct. 110: (4) 745-51. (PubMed) 26. NE Stotland, JS Haas, P Brawarsky, RA Jackson, E Fuentes-Afflick, and GJ Escobar. Body mass index, provider advice, and target gestational weight gain Obstet Gynecol 2005. Mar. 105: (3) 633-8. (PubMed) 27. CM Olson and MS Strawderman. Modifiable behavioral factors in a biopsychosocial model predict inadequate and excessive gestational weight gain J Am Diet Assoc 2003. Jan. 103: (1) 48-54. (PubMed) 28. ME Cogswell, KS Scanlon, SB Fein, and LA Schieve. Medically advised, mother’s personal target, and actual weight gain during pregnancy Obstet Gynecol 1999. Oct. 94: (4) 616-22. (PubMed) 29. SM Taffel, KG Keppel, and GK Jones. Medical advice on maternal weight gain and actual weight gain. Results from the 1988 National Maternal and Infant Health Survey Ann N Y Acad Sci 1993. Mar 15. 678: 293-305. (PubMed) 30. P Brawarsky, NE Stotland, RA Jackson, E Fuentes-Afflick, GJ Escobar, and N Rubashkin, et al. Pre-pregnancy and pregnancy-related factors and the risk of excessive or inadequate gestational weight gain Int J Gynaecol Obstet 2005. Nov. 91: (2) 125-31. (PubMed) 31. CA Hickey, SP Cliver, RL Goldenberg, SF McNeal, and HJ Hoffman. Relationship of psychosocial status to low prenatal weight gain among nonobese black and white women delivering at term Obstet Gynecol 1995. Aug. 86: (2) 177-83. (PubMed) 32. CA Hickey. Sociocultural and behavioral influences on weight gain during pregnancy Am J Clin Nutr 2000. May. 71: (5 Suppl) 1364S-70S. (PubMed) 33. LO Walker and M Kim. Psychosocial thriving during late pregnancy: relationship to ethnicity, gestational weight gain, and birth weight J Obstet Gynecol Neonatal Nurs 2002. May-Jun. 31: (3) 263-74. 34. King JC. Maternal obesity, glucose intolerance, and inflammation in pregnancy. In: Packer L, Sies H, eds. Oxidative Stress and Inflammatory Mechanisms in Obesity, Diabetes, and the Metabolic Syndrome : Taylor & Francis CRC Press 2007:90-106. 35. Berkman N, Viswanathan M. Model Form for the Evaluation of Observational Studies Included in Systematic Literature Reviews. Durham, NC: RTI International 2007. 36. Deeks JJ, Dinnes J, D’Amico R, Sowden AJ, Sakarovitch C, Song F, et al. Evaluating non-randomised intervention studies. Health Technol Assess. 2003;7:iii-x. [PMID: 14499048]. 37. SH Downs and N Black. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions J Epidemiol Community Health 1998. 52: 377-84. (PubMed) (Full Text in PMC) 38. LR Brunner Huber. Validity of self-reported height and weight in women of reproductive age Matern Child Health J 2007. 11: 137-44. (PubMed) 39. RF Gillum and CT Sempos. Ethnic variation in validity of classification of overweight and obesity using self-reported weight and height in American women and men: the Third National Health and Nutrition Examination Survey Nutr J 2005. 4: 27. (PubMed) (Full Text in PMC) 40. West SL, King V, Carey TS, McKoy JN, Lohr K, Sutton SF, et al. Systems to rate the strength of scientific evidence. Evidence Report, Technology Assessment No. 47. Rockville, Md.: Agency for Healthcare Research and Quality. AHRQ Publication No. 02-E016 2002. 41. A Rodriguez, G Bohlin, and G Lindmark. Symptoms across pregnancy in relation to psychosocial and biomedical factors Acta Obstet Gynecol Scand 2001. Mar. 80: (3) 213-23. (PubMed)
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