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Susan L. Ettner, PhD and Joseph G. Grzywacz, PhD

Susan L. Ettner is with the University of California at Los Angeles. Joseph G. Grzywacz is with the University of Northern Iowa, Cedar Falls.

Correspondence: All requests for reprints should be sent to Susan L. Ettner, UCLA School of Medicine, Division of General Internal Medicine and Health Services Research, 911 Broxton Plaza, Box 103, Los Angeles, CA 90095 (e-mail: settner{at}mednet.ucla.edu).

	INTRODUCTION

TOP INTRODUCTION METHODS RESULTS DISCUSSION References

 
Health inequalities manifest as a gradient, rather than as a distinction between "haves" and "have nots." Therefore, eliminating health inequalities will require targeting interventions at segments of the entire population, not just particular subgroups at the disadvantaged end of the social hierarchy. Developing such interventions, however, has been stymied by an unclear understanding of how socioeconomic status (SES) influences health. The literature offers 5 fundamental explanations, including 1) selection effects, 2) differences in lifestyle patterns, 3) differential exposure to life stresses, 4) differences in psychosocial resources, and 5) differential access to, and poorer quality health care resources.^1–9 A major limitation of this literature is that these explanations are frequently viewed as competing hypotheses, rather than complementary explanations representing the broad context of social experiences conditioned by location in the social structure.^1,10–13 Evidence indicates that no single explanation has accounted for as much variance as all of the explanations combined,^12,14,15 and different causal mechanisms for the SES–health relationship may be operative at different socioeconomic levels.

In this study, we examine the ability of different mediators to account for socioeconomic differences in health status at different points in the social hierarchy.

	METHODS

TOP INTRODUCTION METHODS RESULTS DISCUSSION References

 
Data and Study Cohort
Our data came from the 1998–2000 California Work and Health Survey (CWHS).¹³ Survey instruments and methodology can be found at the Web site of the Institute for Health Policy Studies at the University of California, San Francisco (http://medicine.ucsf.edu/programs/cwhs). Although the CWHS was designed to be longitudinal, attrition rates were high, so longitudinal sample sizes were inadequate. Thus, our analyses were based on pooled cross-sectional data from 1998 to 2000 for approximately 3000 US-born respondents between the ages of 25 and 69. Missing data for covariates other than education were imputed by using propensity scores to match respondents,¹⁶ and then using the data from a randomly selected matched data "donor" to impute the value of the missing variable.

Variables
Outcomes were whether the respondent (1) was obese, based on body mass index,¹⁷ (2) reported being in fair or poor health, and (3) reported experiencing at least 7 of 15 depressive symptoms from the Short Geriatric Depression Scale^18–20 during the past week. We chose respondent’s education as the SES measure, to attenuate problems of reverse causality and to allow greater comparability with earlier studies. Table 1 summarizes all of the other covariates.

	RESULTS

TOP INTRODUCTION METHODS RESULTS DISCUSSION References

 
Relative to having less than a high school education, having a bachelor’s or graduate degree was associated with about a onequarter and a one-third reduction in the probability of obesity, respectively, whereas having a high school degree was not significantly associated with obesity risk (Table 2). A comparison of the basic model with the mediated models suggested that the educational gradient in obesity could not be explained by any of the factors examined in this study.

In contrast to obesity, part of the educational gradient for self-assessed health did appear to be mediated by the study variables. Moreover, the proportion of the effect explained by the mediators increased for higher levels of educational attainment. For example, the difference in risk associated with high school education was reduced by 7% in the full model. The corresponding figures for bachelor’s and graduate degrees were 20% and 37%, respectively. Finally, financial strain and lifestyle behaviors seemed to have an additive effect in explaining the educational gradient for persons with college degrees and higher, but not for those with high school only, suggesting that these mediators may be more closely related among the latter group.

Although we detected a linear educational gradient in depression, none of the associations of high school education with depression achieved statistical significance. After controlling for potential mediating factors, especially health behaviors and financial strain, the strong association of bachelor’s degree with a reduced risk of depression became insignificant. Similarly, the relative risk of depression associated with having a graduate degree lost significance after controlling for potential mediators.

	DISCUSSION

TOP INTRODUCTION METHODS RESULTS DISCUSSION References

 
Our analyses showed a strong association of education with physical and mental health. More important, virtually none of the educational gradient for obesity and very little of the educational gradient for fair or poor health could be explained by a variety of mediating factors representing the domains of social relationships, health behaviors, financial strain, and health care access. In contrast, the strong educational gradient in depression was substantially reduced and lost statistical significance after controlling for differences in health behaviors and financial strain.

Our analyses were subject to certain limitations. The analyses were based on California residents, so the findings may not generalize. Statistical power may be low, and multiple comparisons were made, suggesting that interpretation should focus on broad patterns of findings rather than individually significant effects. The potential for reverse causality exists in many of these relationships. If physical activity, sleep impairment, or financial problems are endogenous to depression, then the education gradient is likely to be underestimated, and education itself may be endogenous to health. Finally, incomplete assessment of the mediating variables and measurement error may have resulted in an underestimate of the extent to which mediating factors may explain the association between educational attainment and health.

Earlier studies have also encountered this last limitation, suggesting the need for prospective studies with adequate measurement of a comprehensive array of mediators. For example, measures of diet and better measures of exercise might have attenuated the correlation between education and obesity, the only outcome for which the mediators did not seem to be important.

Population health inequalities are a persistent challenge for public health professionals. Clearly it is important to eliminate the disproportionate burden of poor health among the most disadvantaged Americans; however, our study suggests that important gains to population health can also be achieved by reducing the more modest health inequalities among the majority of Americans, who have not acquired the personal and social resources associated with high status, yet are not deprived. Our pattern of results suggests that financial strain and lifestyle behaviors may be more closely related among those with a lower level of educational attainment than among those with a college degree or more. Thus, practitioners need to recognize and address the financial obstacles associated with adopting and maintaining certain positive lifestyle behaviors among individuals with less education.²³ Finally, eliminating health inequalities in the population may require a coordinated effort targeting multiple individual and contextual factors, such as health behaviors and financial strain, that contribute to poor health.

	Acknowledgments

 
The authors gratefully acknowledge financial support from the California Wellness Foundation/University of California at San Francisco Institute for Health Policy Studies.

Human Participant Protection

No protocal approval was needed for this study.

	Footnotes

 
Both authors designed the study, interpreted the results, and contributed to writing the conclusions section. In addition, S. L. Ettner analyzed the data and wrote the methods and results sections, and J. G. Grzywacz formulated the conceptual model and wrote the introduction.

Peer Reviewed

Accepted for publication April 23, 2002.

	References

TOP INTRODUCTION METHODS RESULTS DISCUSSION References

 
1. Adler N, Ostrove J. Socioeconomic status and health: what we know and what we don’t. In: Adler NE, Marmot MG, McEwen BS, Stewart J, eds. Socioeconomic Status and Health in Industrial Nations: Social, Psychological, and Biological Pathways. New York, NY: New York Academy of Sciences; 1999:3–15.

2. Adler N, Matthews K. Health and psychology: why do some people get sick and some stay well? Annu Rev Psychol. 1994;45:229–259.[ISI][Medline]

3. Anderson NB, Armstead CA. Toward understanding the association of socioeconomic status and health: a new challenge for the biopsychosocial approach. Psychosom Med. 1995;57:213–225.[Abstract/Free Full Text]

4. Evans RG, Barer ML, Marmor TR. Why Are Some People Healthy and Others Not? The Determinants of Health of Populations. New York, NY: Aldine de Gruyter; 1994.

5. Feinstein J. The relationship between socioeconomic status and health: a review of the literature. Milbank Q. 1993;71:279–322.[ISI][Medline]

6. Mechanic D. Socioeconomic status and health: an examination of underlying processes. In: Bunker JP, Gomby DS, Kehrer BH, eds. Pathways to Health: The Role of Social Factors. Menlo Park, Calif: Henry J. Kaiser Family Foundation; 1989:9–26.

7. Syme S, Berkman L. Social class, susceptibility and sickness. Am J Epidemiol. 1976;104:1–8.[Free Full Text]

8. Wilkinson RG. Unhealthy Societies: The Afflictions of Inequality. New York, NY: Routledge; 1996.

9. Williams D. Socioeconomic differentials in health: a review and redirection. Soc Psychol Q. 1990;53:81–99.

10. House JS, Williams DR. Understanding and reducing socioeconomic and racial/ethnic disparities in health. In: Smedley BD, Syme SL, eds. Promoting Health: Intervention Strategies from Social and Behavioral Research. Washington, DC: National Academy Press; 2000:81–124.

11. Krieger N, Williams DR, Moss NE. Measuring social class in U.S. public health research: concepts, methodologies, and guidelines. Annu Rev Public Health. 1997;18:341–378.[ISI][Medline]

12. Marmot MG, Fuhrer R, Ettner SL, Marks NF, Bumpass LL, Ryff CD. Contribution of psychosocial factors to socioeconomic differences in health. Milbank Q. 1998;76:403–448.[ISI][Medline]

13. Ross C, Wu C. Education, age, and cumulative advantages in health. J Health Soc Behav. 1996;37:104–120.[ISI][Medline]

14. Cairney J, Arnold R. Social class, health and aging: socioeconomic determinants of self reported morbidity among the noninstitutionalized elderly in Canada. Can J Public Health. 1996;87:199–203.[Medline]

15. Lantz PM, House JS, Lepkowski JM, Williams DR, Mero RP, Chen J. Socioeconomic factors, health behaviors, and mortality: results from a nationally representative prospective study of US adults [see comments]. JAMA. 1998;279:1703–1708.[Abstract/Free Full Text]

16. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70(1):41–55.[Abstract/Free Full Text]

17. Healthy People 2000: National Health Promotion and Disease Prevention Objectives. Washington, DC: US Department of Health and Human Services; 1991. DHHS Publication PHS 91-50212.

18. Sheikh JI, Yesavage JA. Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. In: Brink T, ed. Clinical Gerontology: A Guide to Assessment and Intervention. New York, NY: The Haworth Press; 1986:165–173.

19. Rule B, Harvey H, Dobbs A. Reliability of the Geriatric Depression Scale for younger adults. Clin Gerontol. 1989;9:37–43.

20. Cwikel J, Ritchie K. Screening for depression among the elderly in Israel: an assessment of the Short Geriatric Depression Scale (S-GDS). Isr J Med Sci. 1989;25(3):131–137.[ISI][Medline]

21. Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous outcomes. Biometrics. 1986;42:121–130.[ISI][Medline]

22. Hosmer DW Jr, Lemeshow S. Applied Logistic Regression. New York, NY: John Wiley & Sons; 1989.

23. Mooney CZ, Duval RD. Bootstrapping: A Nonparametric Approach to Statistical Inference. Thousand Oaks, Calif: Sage Publications; 1993.

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