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TOPIC 4. ECONOMIC STATUS AND HEALTH INEQUALITIES |
Maryland Population Research Center, Department of Sociology, University of Maryland, College Park.
Address correspondence to Joan R. Kahn, Department of Sociology, University of Maryland, College Park, MD 20742. E-mail: jkahn{at}umd.edu
Abstract
Objectives. Racial and socioeconomic disparities in health have become a prominent feature of American society, though our understanding of the processes leading to such persistent disparities is still relatively limited. In this study, we focus on the impact of social and economic advantages and disadvantages over the life course on health disparities at older ages. In particular, we look at the roles of both cumulative and current financial resources and financial strains as determinants of a range of subjective and objective health assessments of physical conditions, functional impairment, and mental health.
Methods. Our data come from the 2001 Aging, Stress, and Health Study, which interviewed over 1,100 White and African American adults aged 65 years and older living in the Washington, D.C., metropolitan area.
Results and Discussion. Our results show that although racial and socioeconomic disparities in health do not follow a simple explanation, we do provide strong support for the fundamental importance of social and economic resources. Unlike previous studies that emphasize the role of financial resources such as income and wealth, we show that the lack of these resources, as indicated by high levels of financial strain, provides an important clue to how economic resources influence health.
RACIAL and socioeconomic inequalities in health have been a prominent feature of American society and, in recent years, have surfaced as a major public health policy issue. The need to further understand and, it is hoped, reduce these disparities is evidenced by the recent establishment of the National Center for Minority Health and Health Disparities at the National Institutes of Health. Although much research has examined the relationships between race, socioeconomic status (SES), and health, our understanding of the processes that lead to such persistent disparities is still relatively limited.
The relationships between race, SES, and various dimensions of health are widely documented in the literature (Link & Phelan, 1995
; Lynch, 1996; Smith & Kington, 1997; Williams & Collins, 1995). Health surveys clearly show that rates of mortality, morbidity, and functional limitation continue to be substantially higher for racial and ethnic minorities as well as for persons with limited social and economic resources (Centers for Disease Control, 2002). Moreover, these disparities appear to have increased in recent decades, owing to more rapid gains in health for the advantaged and, in some cases, a worsening of conditions for the disadvantaged (Pappas, Queen, Hadden, & Fisher, 1993). Some argue that the driving force behind the widening disparities in health is the steady increase in income inequality in the general population. Also relevant are persistent differences in access, utilization, and quality of health care along both racial and socioeconomic lines (Williams & Collins, 1995).
Because race inequalities in health are so closely linked to socioeconomic inequalities, it is difficult to completely separate their effects when talking about health disparities (Hummer, 1996; Smith & Kington, 1997). Many studies show that most, if not all, of the race difference in a range of health outcomes are reduced after controlling for SES measures such as education and income (Huie, Kreger, Rogers, & Hummer, 2003; Mutchler & Burr, 1991; Williams & Collins, 1995). The fact that racial differences are often "explained away" by these controls places even greater importance on understanding how access to socioeconomic resources, especially financial ones, influences health. However, the persistence of racial differences in various aspects of health, even after controlling for SES, suggests that race and SES may still have independent effects.
Increasingly, researchers are looking across the life course for indications of the nature of advantages and disadvantages experienced by different subgroups, with the assumption that these past experiences may have long-lasting effects on well-being later in life (Berney, Blane, Smith, & Holland, 2001; Lynch, Kaplan, & Shema, 1997; Mirowsky & Ross, 2001; Smith & Kington, 1997). It is easy to see how financial advantages early in life protect against the risk of adversity by providing a safe and healthy environment as well as opportunities for educational and occupational achievement, which often lead to higher incomes, greater wealth, and further advantages in adulthood, including good health (O'Rand, 1996).
In contrast, financial hardship earlier in life makes it more difficult (though certainly not impossible) to gain access to the same social and economic resources later in life, which in turn reduces the chances for good health (Link & Phelan, 1995). Indeed, experiences of financial hardship early in life have been shown to have lasting health effects at older ages (Benzeval, Dilnot, Judge, & Taylor, 2001; Elo & Preston, 1992; Kahn & Pearlin, in press; Martikainen, Stansfeld, Hemingway, & Marmot, 1999). Seen within the life course framework, the effects of financial hardship can accumulate over time, producing chronic or recurrent strains that compromise the body's ability to resist health-damaging factors (Benzeval et al., 2001; Kahn & Pearlin, in press; Lynch et al., 1997; Singer & Ryff, 1999; Smith & Kington, 1997). Poor health, in turn, can negatively influence economic status by limiting earnings and depleting savings, thereby encouraging a cycle of decline (Benzeval et al., 2001; McDonough & Berglund, 2003; Mirowsky & Ross, 2001).
This article adds to the growing body of research into health disparities that explores the role of earlier social and economic advantage and disadvantage in influencing health status later in life. Although in some respects our study follows in the tradition of other studies of racial and socioeconomic disparities in health and mortality (e.g., Huie et al., 2003; Mutchler & Burr, 1991; Smith & Kington, 1997), we differ in several important ways. First, we use a broader definition of economic status and consider both income and cumulative wealth as well as explicit indicators of financial hardship. Whereas income and wealth are each clearly related to financial hardship, they are not perfect proxies. In other words, the same level of income may be sufficient for one person but totally inadequate for another. We argue, therefore, that the financial strain arising from inadequate income can be an important stressor with negative health impacts. Moreover, chronic economic strain experienced over the life course is likely to have a cumulative effect on health over time (Hayward, Crimmins, Miles, & Yang, 2000; Pearlin, Menaghan, Lieberman, & Mullan, 1981).
In the current study, we focus on race differences in a range of health outcomes for older adults and examine the impact of financial resources and financial strains. By focusing on multiple aspects of health, we recognize that health is multidimensional and that some aspects may be more influenced by SES than others. In considering financial resources and strains, we examine both current measures (e.g., current income and current financial strain) as well as retrospective measures reflecting the entire life course (e.g., accumulated wealth and past financial strain). We ask several different but related questions: (a) To what extent are race differences in health explained by socioeconomic characteristics? (b) Does financial hardship add to the explanation of health disparities, beyond the impact of financial resources? (c) Do financial resources protect Whites and Blacks equally against the risk of poor health? Similarly, (d) does financial strain have a more deleterious effect on the health of Blacks than of Whites?
In summary, our interest is in the accumulation of advantages and disadvantages over the life course and their impact on racial disparities in health at older ages. We argue that health differentials do not suddenly appear at older ages, but rather they evolve as a result of life course experiences that either raise or lower the risk of developing health problems. Financial circumstances are a crucial determinant of health because they influence so many aspects of people's lives (Link & Phelan, 1995). We argue that financial strain experienced over the life course has a cumulative effect on health that is independent of the effects of financial resources such as income or wealth.
DATA AND MEASURES
The data for this analysis come from the Aging, Stress, and Health Study, which conducted face-to-face interviews in 2001–2002 with a sample of 1,167 adults aged 65 years and older, living in Washington, D.C., and two adjacent counties in Maryland: Montgomery and Prince Georges. The original sampling frame, based on the complete Medicare Beneficiary lists for the three areas, allowed us to design a sample of approximately 1,200 adults living independently and able to complete the interview and that was equally divided among the three locales, African Americans and Whites, and women and men (i.e., 12 groups each with 100 respondents). Although clearly not representative of the Washington, D.C., metropolitan area or of the United States in general, our selection of residents in these three locales provides us with a broad diversity in SES within racial groups. While our ultimate goal is to understand the relationships among race, SES, and health, and not simply to produce population estimates of the levels of health or other individual variables, we nevertheless employ sample weights that correct for the differential probabilities of selection by race, gender, and locale.
Variables
Health outcomes
The dependent variables for the analysis are a set of current health measures reflecting both subjective and objective aspects of physical health, functional capabilities, and mental health. We begin with the familiar self-rated health question: "In general, would you say that your current health is excellent, very good, good, fair or poor?" This subjective appraisal is highly correlated with other health indicators and has been shown to be a powerful predictor of subsequent mortality, even after controlling for chronic illness and functional limitations (Idler & Angel, 1990; Wolinsky & Johnson, 1992).
Among the more objective indicators of physical health is a series of questions asking respondents if, in the last 5 years, a health care provider has told them that they have any from a list of five potentially fatal chronic conditions: cancer, stroke, heart disease, high blood pressure, and diabetes? We create the "number of chronic life-threatening conditions" as the sum of affirmative responses to these questions. Another measure reflecting illness, as distinct from disease, is derived from questions about the frequency with which each of nine symptoms has been experienced during the last month: headaches, back pain, muscle aches, indigestion, constipation/diarrhea, incontinence, feelings of weakness, heart palpitations, and shortness of breath. Responses are averaged into a "health symptoms" scale (
=.70).
A third health measure, reflecting the presence of functional limitations, is a composite score based on two questions that are designed to assess the strength and stamina of the respondent: "How long can you stand in line without sitting?" and "How far can you walk without resting?" The answers to these queries are standardized and combined into a "functional impairment" scale ( =.81), where higher values reflect greater impairment. Finally, we construct a "depressive symptoms" scale ( =.77), comprising six items derived from the longer Hopkins Checklist (Lipman, Rickles, Covi, Derogatis, & Uhlenhuth, 1969). For example, respondents were asked on how many days in the last week they felt downhearted or blue, lacked enthusiasm for doing anything, or felt bored or had little interest in anything.
Weighted means and distributions on the health measures are presented separately by race in Table 1. With several exceptions, African Americans generally report worse health than do Whites. They report lower levels of self-rated health, with over 30% reporting their health to be either fair or poor, compared with only 18% of Whites. Conversely, only 36% of African Americans report very good or excellent health compared with over 50% of Whites. We find similar racial disparities in both the number of fatal conditions and the level of functional impairment. Three fourths of African Americans report at least one fatal condition compared with only two thirds of Whites. However, the racial patterns vary substantially by type of condition; as noted in prior research, African Americans have a considerably higher prevalence of diabetes, high blood pressure, and stroke, whereas Whites have higher rates of heart disease and cancer (Smith & Kington, 1997). The fact that African Americans have a higher number of these fatal conditions indicates a higher level of co-morbidity and associated risks of mortality. With regard to their level of functioning, African Americans report greater difficulty standing and walking, as indicated by their higher average score on the functional impairment scale.
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). When we look at the specific symptoms in our scale, we see that African Americans are less likely to report experiencing seven of the nine symptoms on the scale (all except weakness/faintness and incontinence), though the differences are significant for only three symptoms: indigestion/heartburn (p <.01), back pain (p <.05), and shortness of breath (p <.10). Whites and African Americans report very similar levels of depressive symptoms, each with mean values of about 1.45. This pattern is consistent with prior research that shows minimal or variable race differences in most mental health measures (Brown, Sellers, Brown, & Jackson, 1999; Kessler & Neighbors, 1986; Smith & Kington, 1997).
Financial resources
The focus of our analysis centers around the lifetime economic circumstances of older adults. We consider two objective financial measures (e.g., current income and accumulated wealth) as well as two subjective reports of past and current financial hardship. Current income is determined from a question asking respondents to select 1 of 11 categories representing their total household income from the previous year (2000). Midpoints were assigned to categories in order to create a continuous measure (in thousands of dollars), which was then transformed by taking the natural logarithm. Imputation procedures for missing data are described below.
We measure wealth on the basis of several questions about different types of assets and debt: (a) "Do you own your home?" (b) "If you sold it today, how much money do you think you would get for it?" (c) "Suppose you needed money quickly and you cashed in all of your (and your spouse's) checking and savings accounts, and your stocks and bonds, and real estate (other than your principal home); if you added up what you got, about how much would that amount to?" (d) "If you had to estimate it, what do you think is the approximate total of what you owe on debts or loans (other than mortgage), such as credit card balances, car loans, or loans on other real estate?" From these questions, we again assigned midpoints to categories in order to create continuous measures of home equity, financial assets, and debt, all in thousands of dollars. We also summarized them with a net worth measure that equals financial assets plus home equity (if any) minus debt.
Not surprisingly, given the experiences of other sample surveys, there was considerable missing data on the financial measures: income (9%), home equity (15%), assets (28%), and debt (10%). Rather than omitting the missing data, thereby reducing the size of the sample and potentially introducing bias, we developed an imputation procedure that we applied prior to assigning midpoints to categories. Specifically, for each missing value on income, home equity, assets, or debt, we assigned the median category for other respondents in the same race, gender, and locale subgroup. Though not perfect, this procedure explicitly recognizes the vast inequalities in financial resources by race, gender, and locality. Imputation flags were created for all of the measures, including the summary measure of net worth.
In addition to these measures of financial resources, we also consider several subjective reports of past and current financial hardship. Respondents were asked about the financial difficulties they (or their family of origin) may have experienced during prior stages of the life course: childhood (under age 18 years), early adulthood (ages 18–35 years), early middle age (ages 35–50 years), and later middle age (ages 50–65 years). For the earliest period, respondents were asked: "Thinking back to your years up to age 18, how difficult was it for your family to meet expenses for basic needs like food, clothing and housing? Would you say: (1) Not at all difficult? (2) Somewhat difficult? (3) Very difficult?" The wording was slightly modified in asking about subsequent periods, in which the words "you yourself" were used in place of "your family." From the retrospective responses to these questions, we identified both the particular periods of life in which at least some financial strains were experienced (combining response categories 2 and 3) and the total number of periods in which such strains occurred. Our previous work has shown that these measures are powerful predictors of health at older ages (Kahn & Pearlin, in press).
An additional measure of current financial strain is derived from a question in which respondents are asked: "How do your finances usually work out by the end of the month? Would you say you have: (1) Money left over? (2) Just about enough to make ends meet? (3) Not enough to make ends meet?" This is very similar to the measure of economic strain used by Pearlin and colleagues (1981).
Race differences in the lifetime financial circumstances are presented in Table 2. It is clear that based on either median or mean values of either income or wealth, African Americans have considerably fewer financial resources than do Whites. Consistent with the findings of other studies, race differences in wealth are much greater than differences in income. The median White respondent has accumulated over three times as much wealth as the median African American but receives only twice as much income. Racial differences in wealth are due less to differences in home equity than to the accumulation of other economic assets. Moreover, debt plays only a minor role in the calculation of net worth, as one would expect for a sample of older adults. Median financial assets for Whites are 20 times the level for African Americans. Viewed another way, the median African American respondent has accumulated fewer financial (nonhouse) assets over his or her life time than he or she received as income in the last year. In contrast, the median White respondent has accumulated over five times as much in financial assets as compared with income received in the last year.
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Turning to patterns of current financial strain, we see that both groups are relatively free of this hardship, though Whites more than African Americans. Almost two thirds (62%) of African Americans report having money left over at the end of the month compared with almost four fifths (78%) of Whites. And fewer than 2% of Whites do not have enough money compared with almost 6% of African Americans.
In sum, we see very large race differences in income and wealth, paralleling the patterns reported by others and the realities of racial stratification. However, we find only minor racial differences in reports of past financial hardship (in spite of the large racial differences in accumulated wealth). Whites and African Americans in our sample are similar in their reports of the number of periods of hardship in the past, suggesting a possible race difference in how hardship is perceived (e.g., different reference groups). In terms of current financial well-being, Whites appear to enjoy greater financial security (certainly in terms of current income), and they are less likely to report financial strain.
Other variables
In addition to age, gender, and race, each analysis controls for conditions of early life that may have influenced later economic circumstances; these include urban/rural childhood residence and family structure while growing up. Also among controls are achieved statuses, those attained in adult life, namely, respondents' education, occupational status, and current marital status. Table 3 shows sample distributions on these characteristics, separately by race. Compared with Whites, African American respondents are more likely to have grown up in a rural area, are less likely to have grown up with two parents, have lower levels of education and occupational status, and are less likely to be currently married.
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RESULTS
The regression analyses for the five health outcome measures are structured in a way to allow us to address several different questions about the relationships among race, financial resources, and health. First, we examine the racial difference in health after adding different socioeconomic measures (e.g., education and occupational status, wealth, income, and financial strain) to a baseline model that just includes demographic characteristics. This format makes it possible to compare the relative effects of wealth, income, and financial strain on health. We then test for interactions between race and each of these economic measures, to determine whether Whites and African Americans are equally protected by these financial resources.
Table 4 shows the ordered logit results for models predicting self-rated health. In the baseline model with just demographic controls, we can see that the health ratings of African Americans are significantly lower than those of Whites. However, after controlling for education and occupational status (model 2), the race effect declines by half and is only marginally significant (p <.10). Consistent with previous findings, education has a strong positive impact on health, whereas occupational status has no apparent effect. Controlling for wealth (total net worth in model 3) again reduces the race differential by half, leaving it no longer significant. Accumulated wealth has a strong positive impact on health, denoting the advantages of financial security.
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In the final model (5), we add the two measures of financial hardship reflecting the number of periods of hardship experienced over the life course as well as current financial strain. Both measures are significantly associated with lower ratings of health (p <.01). The fact that past financial hardship is significantly related to health, even after controlling for wealth and current income, suggests that hardship has a powerfully noxious long-term impact on health, above and beyond the impact of dollars and cents. Finally, it is worth noting that controlling for financial strain serves to reduce the effect of income on health by almost 15%, suggesting that part of the impact of income works through the stress of not having enough money (and not just through the ability to purchase health care or a healthy lifestyle).
Table 5 shows results for the analysis of chronic fatal conditions. The top panel presents ordered logit results predicting the number of chronic fatal conditions, and the bottom panel shows ordinary logistic regression results for each of the five conditions separately. Rather than presenting all of the coefficients in these models, we only present results for the race and economic status variables, as they are the focus of our interest. We can report, however, that the effects of the demographic, childhood, and adult characteristics on these other four health outcomes were similar to what was found for self-rated health.
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). Whereas differences in accumulated wealth do not appear to be related to the number of fatal conditions, higher income is associated with fewer conditions, and the frequency of past financial hardship is associated with having more fatal conditions. In the bottom panel of Table 5, we present logistic regression results for each fatal condition separately. Several interesting findings stand out from these models, which also include all of the variables in Table 4. First, we note the significant race differences for all of the fatal conditions except for cancer. Even after controlling for all the variables in the models, African Americans have significantly higher levels of diabetes, high blood pressure, and stroke and significantly lower levels of heart disease. Higher levels of income are associated with a lower likelihood of heart disease or stroke but have no apparent effect on the likelihood of diabetes, high blood pressure, or cancer. In contrast, experience with persistent financial hardship over the life course appears to raise the risk of all conditions and significantly so for all except cancer. The different patterns of effects for income and hardship are striking and highlight the potentially profound impact of excessive stress and strain on health.
Results for the remaining health outcomes are presented in Table 6. Turning first to the results for functional impairment (top panel), we can see that a much weaker race difference in functioning disappears once we control for education (model 2). Both wealth and income have the expected negative effects on impairment (i.e., more money is associated with less impairment), though, again, the impact of income is much stronger than the effect of wealth. Finally, both past and current financial hardships are significantly associated with higher levels of functional impairment, even after controlling for income and wealth. Of course, it is possible that current financial strain may be exacerbated by severe functional impairment, especially if it involves costly treatments or professional caregiving.
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Turning now to the results for depression in the bottom panel of Table 6, we can see that what starts as a nonsignificant race differential in the baseline model (1) becomes an increasingly negative and significant effect as more social and economic variables are added to the model. Again, we interpret this to mean that African Americans would have significantly lower levels of depression than Whites if not for their social and economic characteristics that favored higher levels of depression. This unexplained pattern of resilience has puzzled mental health researchers for some time. Possible explanations include greater access on the part of Blacks to coping resources and religious involvement (Williams, 1996; Williams, Yu, Jackson, & Anderson, 1997).
In sum, we find that the economic status variables are important predictors of both physical and mental health. Higher levels of wealth and income and lower levels of past and current financial hardship are associated with higher ratings of overall health, lower numbers of fatal chronic conditions, lower levels of functional impairment, fewer physical symptoms, and lower levels of depression. However, the question remains as to whether the protective impact of financial security is comparable for Whites and African Americans. To address this question, we ran a series of models including race interactions with wealth, income, past financial hardship, and current financial strain (each taken one at a time). In general, the impacts on health of both wealth and financial hardship were found to be no different for Whites and African Americans. However, the findings are different in the case of current income. Here it can be seen that for all outcomes except for the number of fatal conditions, the protective impact of income is significantly greater for Whites.
Table 7 shows results for the models testing for race-by-income interactions. These models also include all the covariates used in the previous tables. We can see that the positive impact of income on self-rated health is significantly weaker for African Americans than for Whites. Similarly, the negative (i.e., protective) effects of income on the frequency of health symptoms, the level of functional impairment, and the extent of depressive symptoms are all significantly weaker for African Americans. These findings, which are consistent with prior studies (Huie et al., 2003; Mutchler & Burr, 1991), suggest that there are profound differences in the ability of Whites and Blacks to translate their resources into good health. This could reflect racial differences in a variety of factors including diet and lifestyle, access to high-quality health care, or the utilization of preventive screening tests. However, this may also reflect the selective nature of our sample. Because African Americans have higher mortality rates at younger ages, our sample of "survivors" may appear more resilient on average because the experiences of the least healthy are not included. Hence, race differences in health may be underestimated, and the weaker effects of financial resources on the health of African Americans may reflect their more truncated distribution on health outcomes.
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This article has examined racial disparities in health by focusing on the role of social and economic advantages and disadvantages over the life course. In particular, we have looked at the roles of both cumulative and current financial resources and financial strains as determinants of health disparities at older ages. We have looked at a wide range of health outcomes reflecting both subjective and objective assessments of physical conditions, functional impairment, and mental health.
Our findings are generally consistent with past research on health disparities, to the extent that we find that social and economic resources are important predictors of a variety of health outcomes. Reflecting back on the original questions that we raised, we find that some, but not all, racial disparities in health can be explained by socioeconomic factors: Race differences in self-rated health and functional impairment are completely explained after we control for education, wealth, and income. However, racial differences in the number of fatal conditions and health symptoms remain strong and significant, even after the controls. These remaining differences clearly deserve further investigation, perhaps with regard to the impact of lifestyle, health behaviors, diet, or the stresses related to racism or discrimination.
Contrary to expectations, accumulated wealth is not as strong a predictor of health as is current income. We had thought that, given the greater inequality in wealth than in income (especially at older ages), this measure of accumulated wealth would provide a better indication of lifetime living standards than would current income. However, in our data, income is more highly correlated with the health outcomes than is wealth. Perhaps this reflects the fact that many assets are not in liquid form and therefore do not provide individuals with money to spend on their immediate needs. The inflated value of housing, for example, does not ordinarily contribute to readily available assets. In contrast, it could also reflect measurement problems with one or more of the components of the net worth variable (e.g., assets, home equity, debt) or as a result of the imputation procedure.
Although accumulated wealth does not appear to influence health, net of income, we do find strong and consistent effects of past financial hardship on all health outcomes. Even if wealth does not help to explain health disparities (beyond the impact of income), persistent spells of hardship due to inadequate financial resources do appear to be important. This provides strong support for the "cumulative disadvantage" hypothesis whereby the impact of stressors accumulates over the life course. Recurrent financial strain appears to have a particularly noxious impact on well-being at older ages.
Financial resources, especially income, appear to protect the health of Whites significantly more than African Americans. That the same amount of income has a more protective effect for Whites than for African Americans suggests fundamental inequalities in the accessibility and utilization of high-quality health care. It may also reflect larger structural inequalities in education, employment, and neighborhood quality. However, as noted earlier, this may also reflect the selective survival of older African Americans in our sample who may have a more truncated distribution on health outcomes. Further research is clearly needed to better understand the linkages between race, income, and health.
The negative effect of financial strain, measured either cumulatively over the life course or currently, appears to be color-blind in its effect on health. Both Whites and African Americans seem to be equally impaired by the impact of hardship. The fact that both groups report similar amounts of past hardship, in spite of their dramatically different objective financial situations, suggests that they may be using different thresholds or reference groups when reporting hardship. Older African Americans may provide relatively more positive assessments of hardship precisely because their peers, many of whom have not survived, experienced even greater hardship. (Yngwe, Fritzell, Lundberg, Diderichsen, & Burstrom, 2003). In other words, the relative economic deprivation that African Americans feel may not mirror their absolute level of resources. Nonetheless, the similar impact of hardship on health for both Whites and African Americans implies that perceived hardship over the life course does take a physical toll on people's health at older ages.
Summary
We have shown that racial and socioeconomic disparities in health do not follow a simple explanation, but we provide strong support for the fundamental importance of social and economic resources. Unlike previous studies that emphasize the role of financial resources, such as income and wealth, we show that the lack of these resources, as indicated by subjective reports of financial hardship or strain, provides an important clue to how economic resources influence health. The consistency of our findings across multiple measures of health buttresses our argument about the importance of considering the impact of relative disadvantage. However, this analysis should be seen as only the first step toward a broader interdisciplinary understanding of the origins of health and health disparities.
Acknowledgments
An earlier version of this article was presented at the annual meeting of the Population Association of America, Boston, MA, April 1–3, 2004.
The authors gratefully acknowledge the helpful comments of Leonard Pearlin as well as research support provided by Kyle Kenney. This work is supported by NIA grant R01AG17461 (Leonard I. Pearlin, P.I.).
References
This article has been cited by other articles:
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  G.-S. Jeon, S.-N. Jang, S.-J. Rhee, I. Kawachi, and S.-I. Cho Gender Differences in Correlates of Mental Health Among Elderly Koreans J. Gerontol. B. Psychol. Sci. Soc. Sci., September 1, 2007; 62(5): S323 - S329. [Abstract] [Full Text] [PDF]
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