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International Differences in Mortality at Older Ages: Dimensions and Sources 3 Are International Differences in Health Similar to International Differences in Life Expectancy? Eileen M. Crimmins, Krista Garcia, and Jung Ki Kim The question addressed in this chapter is whether people in countries with relatively low life expectancy after age 50 have worse health than those in countries with longer life expectancy. We begin with a short discussion of the theoretical relationships between mortality and population health and the potential complexity of the link between measures of health and mortality. We then examine how indicators of health vary across countries and how closely differences in a set of health indicators correspond to differences in mortality across 10 countries. We note at the outset that most of the data we examine reflect analysis of cross-sectional differences in health; without comparable longitudinal data, there is little we can say about how the differences arose. The countries compared include Australia, Canada, Denmark, England, France, Italy, Japan, the Netherlands, Spain, and the United States. MEASURES OF POPULATION HEALTH A number of people have addressed the question of whether populations that live longer are or should be “healthier.” Answers range from yes, because there is a “compression of morbidity” (Fries, 1980), to no, as there is a “failure of success” (Gruenberg, 1977), to no change, as there is dynamic equilibrium (Manton, 1982). It was probably true that improved health and increased life expectancy went together in the past, when mortality was highly related to death from infectious disease. It is not necessarily true when mortality is largely the result of chronic conditions that exist over long periods of the life span and are treated but not cured. Successful treat-
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International Differences in Mortality at Older Ages: Dimensions and Sources ment can leave more people with a condition surviving in the population. If more people survive with more health problems, it becomes difficult to know when one country is “healthier” than another. At the moment, most of the data available for cross-national comparisons indicate the prevalence of health problems in the population. The prevalence of a health problem at a given time depends on how many people have experienced the onset of the problem or condition and how long they survived with the problem. The onset rate or incidence of a problem depends on risk for the condition in the exposed population, whereas the survival rate can depend on whether the case is treatable and, if treated, whether death or the progression of severity of disease is delayed. Populations can be in better health because the incidence of a disease is lower, but they could also have a lower prevalence of poor health if those with diseases did not survive as long. For instance, if life expectancy among the diseased and disabled increases, population health as measured by disability could deteriorate. Two countries with the same level of disease incidence but different approaches to treatment could have differences in population health; where disease is aggressively treated and death prevented, the level of disease prevalence as well as life expectancy could be higher. So the health status of a population depends on a set of processes of onset and survival that cannot be inferred from one or more snapshots of the prevalence of health problems in the population. There can also be variation in the presence of diseases and conditions across countries and across time for a number of reasons. Diagnostic definitions can differ across countries and change over time. For instance, the blood pressure cutoff value indicating hypertension has gotten lower over time, so that diagnosis occurs at an earlier stage of severity in more recent years. Countries may adopt changes in definitions at different times, leading to variability of the definition of conditions at one time. Another example is differences in the diagnostic criteria for diabetes (DECODE Study Group, 1998; Wareham and O’Rahilly, 1998). Differences in national emphasis on screening for conditions can also affect variability in knowledge of the existence of diseases and reported prevalence. This is true for cancer, hypertension, high cholesterol, and diabetes (Ashworth, Medina, and Morgan, 2008; Gregg et al., 2004; Wareham and O’Rahilly, 1998). It is also possible that recognition of disease varies over time and across countries. For instance, Alzheimer’s disease (AD) is now a recognized cause of both morbidity and mortality but was virtually unknown and unrecognized in the 1950s. The timing of accepting AD as a cause of mortality and morbidity can differ across countries. It is also possible that there are national or cultural differences in the way doctors disclose conditions to patients (Asai, 1995). There are multiple dimensions of health to be considered in evaluating national differences in health. Health change with age in populations begins
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International Differences in Mortality at Older Ages: Dimensions and Sources with the onset of risk factors, progresses to diseases and impairments, and then to functioning loss and to the inability to perform expected tasks or disability, frailty, and death (Crimmins, Kim, and Vasunilashorn, 2010). This can be termed the “morbidity process.” No one individual needs to experience problems reflecting all of these dimensions, as some people die very suddenly with no warning that their health has begun to deteriorate. In addition, for individuals the process is not always unidirectional, but back and forth movement is possible (Crimmins, Hayward, and Saito, 1994). These dimensions of population health relate to mortality differently. For instance, many important causes of disability are not highly related to mortality, for instance, arthritis. In contrast, cancer is highly related to mortality but not disability. Heart disease tends to be a major cause of both mortality and disability. In this analysis, we examine self-reported indicators of functioning, disability, and disease presence and cancer incidence from registries. We also examine both self-reports and measured prevalence of high cholesterol and high blood pressure, along with body mass index based primarily on self-reports. DATA Where possible, our analysis uses information on health for the population ages 50 and older, or 65 and older, in the 10 countries. However, in some cases, we expand or limit the age range because of data unavailability. Most of the countries have conducted national surveys of their older populations, which provide individual-level data on a number of health indicators, risk factors, and drug usage. Many of the self-reported indicators of health status come from a family of surveys designed to be comparable: (1) the Health and Retirement Study (HRS) for 2004 for the United States (Health and Retirement Study, 2006); (2) the Surveys of Health, Ageing and Retirement in Europe (SHARE) for 2004 for Denmark, France, Italy, the Netherlands, and Spain (Börsh-Supan and Jurges, 2005; Börsch-Supan et al., 2005); and (3) the English Longitudinal Study of Ageing (ELSA) for England collected in 2002 (Marmot et al., 2007). Sometimes we employ information for England and Wales or the United Kingdom when we use other sources. All of these surveys use similar formats for their questionnaires and survey national samples of people ages 50+. The Nihon University Japanese Longitudinal Study on Aging (Nihon University Japanese Longitudinal Study on Aging, 2009) provides a representative sample of those ages 65+ for Japan, with most of the data used in this analysis from the 2003 wave. For Canada, much of the self-reported information comes from the 2003 Canadian Community Health Survey (CCHS), and for Australia, the source is often the National Health Survey 2004-2005. Our comparison of national cancer rates is not based on self-reports from surveys but is taken from the GLOBOCAN 2002 database from the
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International Differences in Mortality at Older Ages: Dimensions and Sources Descriptive Epidemiology Group of the International Agency for Research on Cancer (IARC), part of the World Health Organization (WHO). Cancer registries reflecting national populations or samples from selected regions of countries are the basis for these data (Ferlay et al., 2004). Our data on measured biological risk draw on resources from the WHO Global Infobase (World Health Organization, 2009), Organisation for Economic Co-operation and Development (OECD) (2008), the U.S. National Health and Nutrition Examination Survey (NHANES) (2001-2006), ELSA (2004) for England, and the Japanese Health and Nutrition Survey Report (2004) (Ministry of Health, Labour and Welfare of Japan, 2006). For Australia, data came from a report based on the Australian Diabetes, Obesity and Lifestyle Study (AusDiab) conducted in 1999-2000 (Dunstan et al., 2001). We link our health measures to estimates of life expectancy at age 50 and differences in life expectancy relative to those in the United States due to specified causes from Glei, Meslé, and Vallin (Chapter 2, in this volume) and to life expectancy at ages 50 and 65 in 2004 from the Human Mortality Database. After examining country differences in the prevalence of health conditions and risk factors, we use the microdata in a pooled equation for surveys designed to be comparable to examine country differences among individuals in health outcomes with controls for age, diseases, and health behaviors. CROSS-NATIONAL DIFFERENCES IN POPULATION HEALTH We begin our examination of health differences at the end of the morbidity process with indicators of loss of functioning and disability. We then examine diseases that are important causes of mortality. Finally, we turn to selected risk factors and bioindicators related to the diseases we have examined. Disability and Functioning Loss Many studies of health trends in older populations have focused on trends in disability and functioning loss. Trends in the United States have shown that there has been some improvement in functioning and reduction in disability over the past 25 years (Freedman et al., 2004). The improvement in less severe disability began earlier, and improvement in the most severe category of disability began later and has probably been the smallest. It should be noted that some recent studies have found that improvement in disability may no longer be occurring among the U.S. young-old population (Seeman et al., 2010). Time trends in disability have varied in the other countries we are comparing to the United States (Aijanseppa et al.,
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International Differences in Mortality at Older Ages: Dimensions and Sources 2005). A study comparing trends in severe disability in 12 OECD countries for people ages 65+ (Lafortune, Balestat, and the Disability Study Expert Group Members, 2007) found clear evidence of a decline in disability in Denmark, Italy, the Netherlands, and the United States; an increase in disability in Japan; and no clear direction of change in France or the United Kingdom. Not all studies of trends agree; Schoeni et al. (2006) find some recent improvement in disability in Japan. We examine two indicators of problems with functioning and disability self-reported in surveys collected in the first half of the decade: (1) having difficulty performing at least 1 of 10 functioning tasks known as Nagi functions and (2) having difficulty performing at least 1 of 6 activities of daily living (ADLs). Difficulties with functioning problems should reflect problems with strength, balance, mobility, and dexterity, and they are an indicator of less severe functioning loss. ADL difficulty reflects difficulty in performing tasks related to self-maintenance and more severe disability. Although some measures of disability can be influenced by the challenge of the environment, as well as the intrinsic health of the person, these measures should primarily reflect perceptions of intrinsic ability. An examination of the prevalence of functioning problems in the 50+ populations across countries in the early 2000s indicates that people in the United States report more functioning problems than any of the other countries (see Table 3-1). People in Denmark and the Netherlands report the fewest functioning problems. For men, the prevalence of functioning problems in these two countries is about half of the U.S. level; for women, it is about two-thirds of the U.S. level. When the sample is limited to persons ages 65+, the differences between the United States and other countries are not as great. From this, one can infer that U.S. functioning ability is worse relative to that in other countries in the 50-64 range than at older ages. Among women ages 65+, levels of functioning problems in France, Italy, England, and Spain are close to those among U.S. women; U.S. men exceed men in all countries in functioning problems. The country with the lowest level of reported functioning problems at ages 65+ is Japan, for which data were not available in the 50-64 age range. Among the older age group, Denmark and the Netherlands have relatively good functioning. Americans age 50 and over report more ADL difficulty than anyone except the British. In the older age range, ADL difficulties are fairly similar among Denmark, France, Italy, Spain, and the United States. Again, ADL functioning problems are greater among the English. Only in Japan and the Netherlands is the level of ADL disability notably lower. Differences between the United States and other countries in ADL difficulties also appear to be greater in the younger part of the age range than after age 65.
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International Differences in Mortality at Older Ages: Dimensions and Sources TABLE 3-1 Functioning Difficulty, Difficulty with Activities of Daily Living (ADLs), and Ratios to U.S. Level, by Gender and Country Country Ages 50+ Ages 65+ Men Women Men Women % Ratio/ U.S. % Ratio/ U.S. % Ratio/ U.S. % Ratio/ U.S. Functioning Difficulty United States 61.5 1.00 74.0 1.00 67.6 1.00 78.6 1.00 Denmark 34.2 0.56 50.3 0.68 48.5 0.72 63.5 0.81 France 38.3 0.62 59.0 0.80 53.9 0.80 74.4 0.95 Italy 43.8 0.71 60.2 0.81 56.7 0.84 72.1 0.92 Netherlands 31.7 0.52 51.5 0.70 43.4 0.64 62.8 0.80 Spain 43.1 0.70 64.9 0.88 57.8 0.86 77.5 0.99 England 49.2 0.80 64.0 0.86 61.3 0.91 75.3 0.96 Japan NA NA NA NA 31.4 0.46 46.0 0.59 ADL Difficulty United States 13.9 1.00 18.0 1.00 16.1 1.00 21.4 1.00 Denmark 9.9 0.71 11.0 0.61 15.4 0.96 16.7 0.78 France 12.8 0.92 12.5 0.69 19.3 1.20 19.7 0.92 Italy 10.1 0.73 13.9 0.77 15.5 0.96 21.7 1.01 Netherlands 6.4 0.46 10.7 0.59 9.0 0.56 16.7 0.78 Spain 10.2 0.73 15.1 0.84 14.7 0.91 22.5 1.05 England 19.5 1.40 21.8 1.21 25.3 1.57 30.2 1.41 Japan NA NA NA NA 11.2 0.70 15.0 0.70 NOTES: ADL = activities of daily living. NA = not available. Functioning tasks (10): walking blocks (100 meters, 100 yards); sitting 2 hrs; getting up from a chair; climbing one flight of stairs; climbing several flights of stairs; stooping, crouching, kneeling; reaching over head; pushing/pulling large objects; lifting or carrying 10 lbs (5 kilos); picking up a coin. ADL tasks (6): walking across room, dressing, bathing, eating, getting in or out of bed, using the toilet. In Japan, the functioning tasks do not include picking up a coin or pushing and pulling large objects, but they do include shaking hands and grasping with fingers. Survey question for the English Longitudinal Study of Ageing (ELSA) and the Surveys of Health, Ageing and Retirement in Europe (SHARE): “Please tell me if you have any difficulty with these because of a physical, mental, emotional or memory problem.” For the Health and Retirement Study (HRS): “Because of a health or memory problem do you have any difficulty with….” For the Nihon University Japanese Longitudinal Study on Aging (NUJLSOA): “Do you find it difficult to ___ due to your health or physical state?” SOURCES: Data from HRS (2004) for the United States; from ELSA (2002) for England; from SHARE (2004) for Denmark, France, Italy, the Netherlands, and Spain; and from NUJLSOA (2003) for Japan.
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International Differences in Mortality at Older Ages: Dimensions and Sources The relationship between national level of life expectancy at age 50 or 65 and the percentage of the population with functioning problems or ADL disability is not very strong. An example of the relationship between national levels of ADL disability and life expectancy at age 65 is shown in Figure 3-1, which displays a statistically insignificant relationship between lower life expectancy and worse ADL functioning. Differences in Disease Prevalence We examine cross-national differences in self-reports of three diseases from national surveys: heart disease, stroke, and diabetes (see Table 3-2). Heart disease accounts for more than half of the female gap in life expectancy at age 50 between the United States and nine other countries studied here (0.8 years out of 1.4) and the difference in the gap in life expectancy due to heart disease is greater than the overall male gap (0.8 out of 0.6) (Chapter 2, in this volume, see Table 2A-8). We also examine differences in stroke prevalence, as the U.S. ranking for cerebrovascular death rates relative to other countries has fallen recently, although Americans still have lower death rates than in the average of the nine countries (Chapter 2, in this volume, Table 2A-8). Diabetes deaths contribute to lower life expectancy in the United States compared with the average of the other nine countries of 0.1 year for both men and women at age 50 (Chapter 2, in this volume, see Table 2A-8). FIGURE 3-1 National percentage of activities of daily living (ADL) difficulty at ages 65+ and life expectancy at age 65 (LE65). SOURCES: Data on ADL difficulty from Table 3-1; data on life expectancy for 2004 from the Human Mortality Database (see http://www.mortality.org [accessed March 2009]). Life expectancy data extracted from country-specific life tables from the HMD.
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International Differences in Mortality at Older Ages: Dimensions and Sources TABLE 3-2 Prevalence of Self-Reported Disease in the 50+ and 65+ Populations Country Ages 50+ Ages 65+ Men Women Men Women % Ratio/ U.S. % Ratio/ U.S. % Ratio/ U.S. % Ratio/ U.S. (a) Heart Disease United States 28.4 1.00 22.1 1.00 36.4 1.00 28.0 1.00 Denmark 9.9 0.35 7.8 0.35 15.9 0.44 13.0 0.46 France 18.5 0.65 10.8 0.49 28.8 0.79 16.3 0.58 Italy 12.4 0.44 10.1 0.46 18.7 0.51 14.3 0.51 Netherlands 13.6 0.48 8.8 0.40 21.7 0.60 12.9 0.46 Spain 11.3 0.40 11 0.50 15.1 0.41 15.5 0.55 England 23.0 0.81 19.0 0.86 32.2 0.88 26.4 0.94 Japan NA NA NA NA 14.4 0.40 12.2 0.44 Canada 13.8 0.49 10.7 0.48 21.8 0.60 18.1 0.65 (b) Stroke United States 7.3 1.00 6.4 1.00 9.4 1.00 8.6 1.00 Denmark 6.0 0.82 4.9 0.77 9.9 1.05 7.3 0.85 France 3.5 0.48 3.8 0.59 5.5 0.59 5.8 0.67 Italy 3.7 0.51 2.7 0.42 5.8 0.62 4.0 0.47 Netherlands 4.4 0.60 4.8 0.75 7.1 0.76 7.8 0.91 Spain 2.4 0.33 1.9 0.30 2.9 0.31 2.8 0.33 England 4.9 0.67 4.0 0.63 8.2 0.87 6.4 0.74 Japan NA NA NA NA 9.3 0.99 6.0 0.70 Canada 2.8 0.38 2.4 0.38 5.2 0.55 3.9 0.45 (c) Diabetes United States 19.5 1.00 16.5 1.00 21.4 1.00 17.6 1.00 Denmark 8.2 0.42 6.8 0.41 11.1 0.52 8.7 0.49 France 10.9 0.56 8.6 0.52 13.0 0.61 10.8 0.61 Italy 12.8 0.66 11.4 0.69 17.6 0.82 15.7 0.89 Netherlands 7.8 0.40 9.2 0.56 10.6 0.50 12.2 0.69 Spain 15.3 0.78 13.9 0.84 20.4 0.95 17.1 0.97 England 8.6 0.44 6.2 0.38 11.2 0.52 8.0 0.45 Japan NA NA NA NA 10.1 0.47 7.5 0.43 Canada 11.9 0.61 9.1 0.55 15.6 0.73 11.9 0.68 Australia 16.2 0.76 11.5 0.65 NOTE: ADL = activities of daily living. NA = not available. SOURCE: Data on self-reported diseases from HRS (2004) for the United States; from ELSA (2002) for England; from SHARE (2004) for Denmark, France, Italy, the Netherlands, and Spain; for NUJLSOA (2003) for Japan; from CCHS (2003) for Canada; and from the Australian Bureau of Statistics (2006a) [http://www.abs.gov.au/ausstats, accessed December 5, 2009] and NHS (2004-2005) for Australia.
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International Differences in Mortality at Older Ages: Dimensions and Sources Heart Disease Americans ages 65+ report more heart disease than persons in any of the other countries. The prevalence is only slightly lower in England than in the United States. Denmark and Japan have prevalence values of only about half of the U.S. values (see Table 3-2[a]).1 Each country’s age-sex group ratio to the U.S. value is higher among the 50+ population than among the 65+ population, indicating larger differences at younger ages. National heart disease prevalence is not closely related to national life expectancy (see Figure 3-2[a]). A number of studies in the United States have reported increases over time in the prevalence of heart disease in the population (Crimmins and Saito, 2001; Cutler and Richardson, 1997), although a recent study reports that this increase may have ended after 1997 (Freedman et al., 2007). An increase in the proportion of the population with heart disease is perhaps not surprising in light of the fact that declining death rates from heart disease have been such a strong contributor to mortality trends (Jemal et al., 2005). Even in the short period from 2000 to 2006, U.S. cases of atrial fibrillation increased by 30 percent and heart failure cases increased by 8 percent among Medicare beneficiaries (Chronic Condition Data Warehouse, 2009).2 Stroke At ages 50+, Americans report the highest prevalence of stroke. For women, the Netherlands and Denmark have prevalences that are about three-fourths of the U.S. level. For the 65+ population, the prevalence of self-reported stroke is highest among Danish men. U.S. and Japanese men have levels very similar to those of the Danes, followed closely by English men (see Table 3-2[b]).3 This high level of stroke among Japanese men is not surprising, as high levels of stroke with low levels of heart disease have long characterized the Japanese (Reed, 1990). For women, the highest levels 1 The Organisation for Economic Co-operation and Development reports the number of hospital discharges per 100,000 population for acute myocardial infarction (AMI) and cerebrovascular disease. While these are not age-specific rates, they provide some comparison of the self-reports to other sources. The rate of hospital discharge for AMI is highest in Denmark and second in the United States (Organisation for Economic Co-operation and Development, 2008). 2 A recent paper based on the Framingham Study provides some explanation for the finding that heart attack rates have been relatively constant over recent decades (Parikh et al., 2009). Over the last four decades, improved methods of diagnosis of AMI have led to an increase in the number of cases; if diagnosis had remained the same as in the 1960s and 1970s, the rates of AMI would have declined. 3 Hospital discharge rates for cerebrovascular conditions are only weakly related to the level of self-reported stroke. Discharge rates are high among the Japanese and Danes but also among Italians, who self-report low stroke prevalence (Organisation for Economic Cooperation and Development, 2008).
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International Differences in Mortality at Older Ages: Dimensions and Sources FIGURE 3-2 National percentage self-reporting (SR) disease (65+) and life expectancy (LE) at age 65. SOURCES: Data on disease from Table 3-2; data on life expectancy for 2004 from the Human Mortality Database (HMD) (see http://www.mortality.org [accessed March 2, 2009]). Life-expectancy data extracted from country-specific life tables from HMD.
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International Differences in Mortality at Older Ages: Dimensions and Sources of stroke are reported among Americans; Japanese women have lower levels of stroke than Americans, Danes, the Dutch, and the English. This finding that Japanese women now have a lower prevalence of stroke than Americans fits with the observation that, in recent years, mortality related to stroke among Japanese women has been lower than that for U.S. women (Crimmins et al., 2008). National levels of mortality and stroke prevalence have a stronger association than that observed for heart disease. For women, it is the countries with adverse mortality trends—Denmark, the Netherlands, and the United States—that have relatively high levels of female stroke prevalence (see Figure 3-2[b]). Diabetes For those ages 50 and older, diabetes prevalence is reported to be the highest in the United States. For men, only Italy, France, and Spain have levels that exceed half of the U.S. value. Among women, Denmark and England have levels of diabetes only about 40 percent of that in the United States. At ages 65+, the United States has the highest level, followed closely by that of Spain and Italy (see Table 3-2[c]). In Denmark, England, and Japan, self-reported diabetes prevalence at ages 65+ is only about half of that of the United States (Table 3-2[c]).4 Again, the differences between the United States and other countries appear to be greater in the younger part of the age range examined, as the ratios to the U.S. values are higher at older ages in every case. The link between national levels of self-reported diabetes and mortality is not significant (see Figure 3-2[c]). In sum, self-reports of disease presence tend to place people in the United States in the high-prevalence group for each of these diseases. Although other countries tend to be high in only one of the three diseases, the United States tends to have high levels in all three. The differences between the United States and other countries in the prevalence of all three diseases are greater among those ages 50-64 than over age 65. Figure 3-3 shows the level of the three diseases self-reported in each country as related to country-level life expectancy differences from U.S. life expectancy due to heart disease (for heart disease), cerebrovascular disease (for stroke), and diabetes (for diabetes) from Glei, Meslé, and Vallin. (Chapter 2, in this volume). Neither heart disease nor stroke is significantly 4 We also examined diabetes prevalence for the age-standardized population ages 20-79 from OECD reports, which are based on a combination of measured biological markers and self-reports—and therefore are not truly comparable across countries. This is also true because the age groups for which data are available are quite different. The OECD prevalence of diabetes for ages 20-79 is highest in the United States (Organisation for Economic Co-operation and Development, 2008).
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International Differences in Mortality at Older Ages: Dimensions and Sources TABLE 3-8 Odds Ratios from Logistic Regressions of Country, Age, and Health Behaviors on Self-Reported Prevalence of Heart Disease, Stroke, and Diabetes Heart Disease Stroke Diabetes Men Women Men Women Men Women M1 M2 M1 M2 M1 M2 M1 M2 M1 M2 M1 M2 Age 1.06* 1.06* 1.05* 1.06* 1.05* 1.06* 1.06* 1.07* 1.02* 1.03* 1.02* 1.03* United States (ref) Denmark 0.34* 0.35* 0.31* 0.33* 1.01 0.97 0.84 0.82 0.41* 0.48* 0.38* 0.49* France 0.68* 0.72* 0.44* 0.50* 0.55* 0.57* 0.62* 0.72* 0.54* 0.63* 0.50* 0.60* Italy 0.40* 0.43* 0.42* 0.46* 0.58* 0.58* 0.44* 0.49* 0.65* 0.73* 0.66* 0.75* Netherlands 0.48* 0.50* 0.36* 0.38* 0.73* 0.70* 0.84 0.87 0.38* 0.45* 0.51* 0.60* Spain 0.36* 0.38* 0.43* 0.47* 0.33* 0.32* 0.31* 0.36* 0.75* 0.80* 0.82* 0.78* England 0.64* 0.63* 0.72* 0.68* 0.41* 0.40* 0.44* 0.41* 0.38* 0.36* 0.29* 0.25* Overweight 1.08 1.08 1.02 1.05 1.79* 2.02* Obese 1.47* 1.61* 1.12 1.32* 3.54* 5.20* Current smoker 0.90 0.98 1.34* 1.21 0.98 0.96 Ever smoker 1.36* 1.31* 1.47* 1.42* 1.24* 1.00 N 15,211 19,493 15,216 19,498 15,212 19,495 *p < 0.05. SOURCE: Data from HRS, SHARE, ELSA Countries, 50+ Sample, 2004.
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International Differences in Mortality at Older Ages: Dimensions and Sources TABLE 3-9 Odds Ratios from Logistic Regressions of Country, Age, and Health Behaviors on Self-Reported Prevalence of Functioning and ADL Difficulty Functioning Difficulty ADL Difficulty Men Women Men Women M1 M2 M1 M2 M1 M2 M1 M2 Age 1.06* 1.06* 1.05* 1.06* 1.05* 1.05* 1.06* 1.06* United States (ref) Denmark 0.39* 0.46* 0.39* 0.49* 0.82 1.00 0.60* 0.77* France 0.45* 0.53* 0.56* 0.74* 1.09 1.39* 0.70* 0.93 Italy 0.56* 0.69* 0.57* 0.72* 0.80* 1.02 0.80* 1.03 Netherlands 0.36* 0.41* 0.42* 0.50* 0.52* 0.64* 0.62* 0.77* Spain 0.53* 0.60* 0.66* 0.76* 0.73* 0.91 0.78* 0.93 England 0.69* 0.75* 0.73* 0.73* 1.50* 1.83* 1.31* 1.49* Heart disease 2.13* 2.42* 1.68* 1.87* Stroke 2.55* 2.51* 3.45* 3.11* Diabetes 1.68* 1.46* 1.62* 1.81* Overweight 1.22* 1.58* 1.00 1.19* Obese 2.43* 3.89* 1.93* 2.47* Current smoker 1.33* 1.30* 1.35* 1.42* Ever smoked 1.43* 1.10* 1.28* 1.05 N 15,204 19,478 15,203 19,484 *p < 0.05. SOURCE: Data from HRS, SHARE, ELSA Countries, 50+ Sample, 2004. Differences in ADL functioning between men in the United States and those in other countries are not so consistent as those found above for funtioning difficulty. Without controls, there is no difference in ADL functioning among men in Denmark, France, and the United States. English men have more ADL problems than Americans. Men in the United States have worse ADL functioning than men in Italy, Spain, and the Netherlands. If all the countries had the same presence of the three diseases, smoking, and obesity, U.S. men would only have more ADL functioning problems than men in the Netherlands. U.S. women have worse ADL functioning than those in all other countries except England. If the prevalence of the included diseases and the health behaviors were the same across countries, U.S. women would only fare worse than Dutch and Danish women. These results seem to indicate that the relatively poor ranking of Americans in terms of ADL functioning is largely due to the presence of more diseases, more overweight, and higher smoking levels.
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International Differences in Mortality at Older Ages: Dimensions and Sources DISCUSSION Reviewing this complex set of health differences, two conclusions stand out. For many indicators of health, the United States ranks as the country with the highest prevalence of problems. This includes functioning, heart disease, stroke at some ages, diabetes, and obesity. The other generalization is that Japan is often the country ranking as best in a number of health indicators. This includes functioning and ADL disability levels, prevalence of heart disease, diabetes, and obesity, and incidence of some cancers. Many other countries rank poorly in some health indicators but do not rank poorly in others, so it is hard to determine a clear ranking for other countries. Denmark and the Netherlands stand out as having relatively high levels of stroke and mortality from some cancers, yet these countries appear to have relatively good levels of physical functioning. The poor position of the United States and the good position of Japan provide some support for a link between levels of life expectancy and levels of population health, but the overall association is weak for many of the indicators. Banks and colleagues (2006) have pointed out that Americans in their 50s and 60s had more diseases and worse levels of a number of biomarkers than the English. Crimmins and colleagues (Crimmins et al., 2008; Reynolds et al., 2008) have noted that levels of functioning problems and disability, diseases, and a number of biomarkers are worse among Americans than the Japanese. Poor relative health appears to characterize comparisons of Americans with multiple additional countries. The diseases with higher prevalence among Americans are conditions that are related to health behaviors and lifestyle factors. For a number of indicators, the relatively poor position of the United States was more exaggerated among people ages 50-64 than in the group ages 65+. This included functioning and ADL disability, heart disease, stroke, and obesity. Although we do not have the ability to examine the effects of mortality and disease onset with these data, these findings could be compatible with earlier onset of disease among Americans. Obesity is a potential explanation of some of the poor health indicators in the United States, as it is related to each of the diseases we examined, and the diseases are, in turn, related to more functioning problems. Our microlevel analysis indicated the substantial effect of obesity on the presence of each of these diseases, functioning loss, and disability; however, our analysis controlling for overweight and obesity indicates that Americans would report more heart disease, stroke, diabetes, and functioning problems even if they had the same levels of overweight, obesity, and smoking patterns as in the SHARE countries and England. In further analysis, we replicated the regressions in Tables 3-8 and 3-9 after eliminating all obese persons, and the results are hardly changed: nonobese Americans are still likely to have more diseases and worse functioning problems. Both obese and the
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International Differences in Mortality at Older Ages: Dimensions and Sources nonobese Americans have more diseases and disabilities than persons in other countries. Our disease-specific analyses do not indicate the level of concentration of health problems in individuals. It is possible that the concentration of health problems in individuals differs across countries and is one explanation of why mortality is not strongly related to the prevalence of individual health problems. One hypothesis for why some countries do poorly is that health problems are concentrated in a smaller group in the population. For the countries for which we have individual data, we examined the occurrence of comorbidity of heart disease, stroke, and diabetes. We found dramatically higher levels of comorbidity in the United States than in other countries, indicating a larger portion of the population with multiple serious health risks in the United States (see Table 3-10). The proportion of people with more than one of the three conditions—heart disease, stroke, and diabetes—is generally at least twice as high in the United States as in the other countries. Further analysis should include better information on TABLE 3-10 Percentage Self-Reporting More Than One of the Three Conditions—Heart Disease, Stroke, and Diabetes Men Women Among 50+ United States (HRS 2004, SR) 10.7 8.7 Denmark (SHARE wave 1) 2.4 2.2 France 3.8 3.2 Italy 3.1 3.5 Netherlands 3.6 2.9 Spain 4.5 3.0 England (ELSA wave 2) 4.2 3.3 Japan NA NA Canada 4.2 3.1 Among 65+ United States (HRS 2004, SR) 13.7 11.1 Denmark 4.4 3.7 France 5.6 4.7 Italy 5.0 4.8 Netherlands 5.9 4.8 Spain 7.0 4.1 England (ELSA wave 2) 6.4 4.7 Japan 4.5 2.4 Canada 6.9 5.2 NOTE: NA = not available. SOURCES: Data from HRS (2004) for the United States; from SHARE (2004) for Denmark, France, Italy, the Netherlands, and Spain; from ELSA (2004) for England; from NUJLSOA (2003) for Japan; and from CCHS (2003) for Canada.
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International Differences in Mortality at Older Ages: Dimensions and Sources the concentration of risks and comorbid conditions among individuals. This chapter has not examined social differences in health risks across countries, but they are known to be relatively large in the United States (Avendano et al., 2009; Avendano et al., Chapter 11, in this volume). Both social disadvantages and health disadvantages may be more concentrated in the United States, while health disadvantage may be distributed more equally across the population in other countries. Our data also have some implications for assessing performance of the U.S. health care system relative to those in other countries. The United States does relatively well at diagnosing and treating hypertension and high cholesterol. Risk is reduced well below what it would be without the widespread use of drug treatment. It is hard to say how countries rank in the relative risk from hypertension and high cholesterol given that the United States has the highest diagnosed levels of these risks but almost the lowest measured levels of current risk, indicating high levels of control. This provides an indication of the role of the U.S. health care system in reducing the risk associated with hypertension and high cholesterol. However, the significantly worse health in the United States for people ages 50-64 occurs in an age group whose health care insurance availability is lower than at older ages. Cancer death rates, except for lung cancer among women, are relatively low in the United States (see also Preston and Ho, Chapter 9, in this volume). Cancer screening appears to identify a relatively high number of cases in the United States and to result in a lower rate of mortality among incident cases. This could reflect good treatment or the fact that extensive screening identifies cases that have a lower chance of dying. Again, it becomes somewhat difficult to determine relative cancer risk across countries, as our observations are so affected by screening. This high identification of screenable cancers is another indication of the positive role of the U.S. health care system. Can we rely on the results of our analyses of diseases and functioning problems based on self-reports? Research has shown relatively high agreement between the self-report and medical record report for some conditions: diabetes, stroke, and myocardial infarction (Bush et al., 1989; Goldman et al., 2003; Okura et al., 2004). Because our analysis relied on self-reports of diagnosed heart disease, not limited to myocardial infarction, it is possible that national differences in the prevalence of heart disease are affected by reporting and diagnostic differences. The level of agreement between self-report and medical records for hypertension is generally thought to be lower than that for some other conditions, and this may be the case for the European countries included in SHARE in our analysis. Functioning difficulties and disability are generally self-reported in surveys, not based on a doctor’s diagnosis. Two recent analyses of how Americans and the Dutch report disability
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International Differences in Mortality at Older Ages: Dimensions and Sources have come to different conclusions about relative reporting tendencies. Comparing responses to vignettes indicates that, with a given description of a disability, Americans are less likely than the Dutch to see a person as disabled (Kapteyn, Smith, and van Soest, 2007); however, another comparison of American and Dutch self-reports of disability to measured disabilities shows Dutch individuals have greater limitation when they report themselves disabled (Melzer et al., 2004). It is hard to know how to assess the overall effect of national differences in reporting or diagnostic tendencies; however, most of the differences we observe are quite large, and they are relatively consistent across many conditions. It is hard to believe that all differences arise from differential reporting. Additional sources of differential reporting include cultural context, sociodemographic characteristics, and environmental circumstances (Bago d’Uva, O’Donnell, and van Doorslaer, 2008; Bago d’Uva et al., 2008; Iburg et al., 2001; Melzer et al., 2004). Finally, to return to our initial discussion about population health, with prevalence data it is difficult to determine the process that resulted in the observed differences. It is obvious that current health status, including mortality, reflects past heath, health behaviors, and health care use. Thus, in order to understand the process leading to mortality, we need information on earlier health behaviors, incidence of, and survival from certain conditions. However, most of our data indicate current prevalence, cancer being the exception. While our results show higher levels of some conditions and risk factors in the United States, longitudinal data are required for a better understanding of the roles of incidence, treatment, and survival in creating current health, including mortality. As we mentioned earlier, increasing survival among people with diseases and functioning problems can lead to a higher prevalence of health problems in the population. Finally, our cross-sectional data are limited in making any connection between earlier risk factors, lifelong health behaviors, and lifetime circumstances that could affect later health. ACKNOWLEDGMENTS Support was provided by the U.S. National Institutes of Health (P30 AG17265) and the University of Southern California Humanities and Social Sciences Fund. This chapter uses data from the early release of SHARE 2004. SHARE data collection was primarily funded through the European Commission through the 5th framework program (Project QLK6-CT-2001-0060 in the thematic program “Quality of Life”). Additional funding came from the U.S. National Institute on Aging (U01 AG09740-13S2, P01 AG005842, P01 AG08291, P30 AG12816, Y1-AG-4553-01, and OGHA 04-064). Data collection in Austria, Belgium, and Switzerland was nationally funded. The collection of the Health and Retirement Study was supported by the U.S.
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International Differences in Mortality at Older Ages: Dimensions and Sources National Institute on Aging (U01 AG009740) and is conducted by the University of Michigan. ELSA was developed by a team of researchers based at the National Centre for Social Research, University College London, and the Institute for Fiscal Studies. The data were collected by the National Centre for Social Research and made available through the UK Data Archive. The funding is provided by the U.S. National Institute on Aging and a consortium of United Kingdom government departments coordinated by the Office for National Statistics. This analysis is based on Statistics Canada’s Canadian Community Health Survey, Cycle 2.1 (2003), Public Use Microdata File, which contains anonymized data. All computations on these microdata were prepared by University of Southern California, and the responsibility for the use and interpretation of these data is entirely that of the authors. The developers and funders of the data sets do not bear any responsibility for the analyses or interpretations presented here. REFERENCES Aijanseppa, S., Notkola, I.L., Tijhuis, M., van Stavern, W., Kromhout, D., and Nissinen, A. (2005). Physical functioning in elderly Europeans: 10-year changes in the north and south: The HALE project. Journal of Epidemiology and Community Health, 59(5), 413-419. Andreyeva, T., Michaud, P.C., and van Soest, A. (2007). Obesity and health in Europeans aged 50 years and older. Public Health, 121, 497-509. Asai, A. (1995). Should physicians tell patients the truth? Western Journal of Medicine, 163(1), 6-39. Ashworth, M., Medina, J., and Morgan, M. (2008). Effect of social deprivation on blood pressure monitoring and control in England. British Medical Journal, 337, a2030. Australian Bureau of Statistics. (2006a). Health of Older People in Australia: A Snapshot, 2004-2005. No. 4833.0.55.001. Canberra: Australian Bureau of Statistics. Available http://www.abs.gov.au/ausstats [accessed December 2009]. Australian Bureau of Statistics. (2006b). National Health Survey: Summary of Results, Australia 2004-2005. No. 4364.0. Canberra: Australian Bureau of Statistics. Available http://www.abs.gov.au/ausstats [accessed December 2009]. Australian Institute of Health and Welfare. (2006). Chronic Diseases and Associated Risk Factors in Australia, 2006. No. PHE 81. Canberra: Author. Avendano, M., Glymour, M., Banks, J., and Mackenbach, J.P. (2009). Health disadvantage in U.S. adults aged 50-74 years: A comparison of the health of rich and poor Americans with that of Europeans. American Journal of Public Health, 99, 540-548. Bago d’Uva, T., O’Donnell, O., and Van Doorslaer, E. (2008). Differential health reporting by education level and its impact on the measurement of health inequalities among older Europeans. International Journal of Epidemiology, 37, 1375-1383. Bago d’Uva, T., Van Doorslaer, E., Lindeboom, M., and O’Donnell, O. (2008). Does reporting heterogeneity bias the measurement of health disparities? Health Economics, 17, 351-375. Banks, J., Marmot, M., Oldfield, Z., and Smith, J.P. (2006). Disease and disadvantage in the United States and in England. Journal of the American Medical Association, 295, 2037-2045.
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