Socioeconomic disparities in health change in a longitudinal study of US adults: the role of health-risk behaviors

https://doi.org/10.1016/S0277-9536(00)00319-1Get rights and content

Abstract

This study investigated the hypothesis that socioeconomic differences in health status change can largely be explained by the higher prevalence of individual health-risk behaviors among those of lower socioeconomic position. Data were from the Americans’ Changing Lives study, a longitudinal survey of 3617 adults representative of the US non-institutionalized population in 1986. The authors examined associations between income and education in 1986, and physical functioning and self-rated health in 1994, adjusted for baseline health status, using a multinomial logistic regression framework that considered mortality and survey nonresponse as competing risks. Covariates included age, sex, race, cigarette smoking, alcohol consumption, physical activity, and Body Mass Index. Both income and education were strong predictors of poor health outcomes. The four health-risk behaviors under study statistically explained only a modest portion of the socioeconomic differences in health at follow-up. For example, after adjustment for baseline health status, those in the lowest income group at baseline had odds of moderate/severe functional impairment in 1994 of 2.11 (95% C.I.: 1.40, 3.20) in an unadjusted model and 1.89 (95% C.I.: 1.23, 2.89) in a model adjusted for health-risk behaviors. The results suggest that the higher prevalence of major health-risk behaviors among those in lower socioeconomic strata is not the dominant mediating mechanism that can explain socioeconomic disparities in health status among US adults.

Introduction

Morbidity and mortality rates vary greatly by markers of socioeconomic position, including education, income, and occupation (Davey Smith, Shipley & Rose, 1990; Sorlie, Backlund & Keller, 1995; Pappas, Queen, Hadden & Fisher, 1993). The strong negative association between socioeconomic factors and health status has been observed across a wide variety of historical contexts, geographic locations, and populations (Blaxter 1987; Haan, Kaplan & Syme, 1989; Link & Phelan, 1995; Lynch & Kaplan, in press). In addition, results from a number of population-based studies in more developed countries suggest that socioeconomic differences in health status occur over the life course, yet are the greatest in the adult years (House et al., 1994; Mustard, Derksen, Berthelot, Wolfson & Roos, 1997).

Empirical evidence from a number of longitudinal and cross-sectional studies demonstrates that health-risk behaviors such as tobacco use, alcohol consumption, having a sedentary lifestyle, and obesity are associated with a variety of health-risks and mortality (Healthy People 2000, 1990; McGinnis & Foege 1993; Fraser et al., 1997). There is also ample evidence that the prevalence of most health-risk behaviors is higher among those with lower levels of education and income (Liu et al., 1982; Winkleby, Fortman & Barrett, 1990; Lynch, Kaplan & Salonen, 1997; National Center for Health Statistics, 1998). Thus, a common yet also debated perspective is that the increased prevalence of major health-risk behaviors among people of lower socioeconomic position accounts for much of their increased risk for negative health outcomes. (Williams 1990; Krieger, Rowley, Herman, Avery, Phillips, 1993; McGinnis & Foege 1993; Blaxter 1997) In other words, a prominent hypothesis is that differences in personal health-risk behaviors (or “lifestyle choices”) across socioeconomic strata can largely explain observed socioeconomic disparities in health (Macintyre, 1997).

Previous longitudinal research has shown that selected health-risk behaviors account for only a modest proportion of socioeconomic differences in mortality (Davey Smith et al., 1990; Hirdes & Forbes, 1992; Lynch, Kaplan, Cohen, Tuomilehto & Salonen, 1996; Marmot et al., 1997; Lantz, House, Lepkowski, Williams, Maro, Chen, 1998). The role of major health-risk behaviors in mediating socioeconomic differences in health status, however, is less studied. Lynch, Kaplan and Shema (1997), using data from the Alameda County Study, found that those with incomes less than 200% of the poverty level in 1965, 1974 and 1983 had a significantly higher rate of problems with physical, and psychological functioning in 1994. After adjusting for baseline levels and changes in smoking, Body Mass Index, alcohol consumption, and physical activity level, the association between economic hardship and functioning attenuated somewhat, but was still strong and significant.

Similarly, in a study of Swedish men, Mansson, Rastam, Eriksson and Israelsson (1998) found that socioeconomic status was strongly associated with being granted a disability pension in the future, adjusting for working conditions and for body weight and other disease-risk factors. Vita, Terky, Hubert & Fries (1998) found that smoking, obesity and exercise patterns in both mid-life and later years were associated with subsequent disability, and that the absence of health-risk behaviors postponed and thus compressed disability into fewer years at the end of life. However, these researchers — while addressing the issue of health behaviors and subsequent health status — did not address socioeconomic differentials in disability. Overall, there does not appear to be much information on the contribution of major health-risk behaviors in explaining socioeconomic differentials in health status from longitudinal studies with nationally representative samples.

It is possible that, compared to mortality, individual health-risk behaviors play a stronger role in explaining socioeconomic disparities in individual health status. All-cause mortality is a more general health outcome, including many causes not known to be related to individual health-risk behaviors. Thus, certain measures of health status may be more proximately related to major behavioral risk factors than all-cause mortality and as such may account for more of the socioeconomic gradient in health status. In addition, the impact of some health-risk behaviors on health status is much stronger and clearer than their impact on mortality. For example, the impact of being overweight on mortality has not been demonstrated consistently across population-based studies, yet obesity has a strong and significant association with many chronic diseases and debilitating conditions, some of which are not necessarily life threatening (Anonymous, 1998; Bender, Trautner, Spraul & Berger, 1998). The role of individual health-risk behaviors in explaining socioeconomic disparities may vary across health outcomes.

The degree to which the higher prevalence of risky health practices among people of lower income and education levels explains or contributes to socioeconomic disparities in health status is an important issue for public health policy. A greater understanding of the potential for interventions focused on the health behaviors of individuals to reduce social inequalities in health is needed. Thus, the purpose of this study was to examine socioeconomic differences in health status among adults in the United States over a 7.5-year period, using two different measures of general health status (functional impairment regarding physical health and self-rated health), focusing on the degree to which major health-risk behaviors explain the observed association between socioeconomic characteristics and changes in health status over time. This research contributes to existing literature by employing a longitudinal study design and a nationally representative sample (including both males and females) to address issues that are of great importance both to epidemiological research and to public health policy.

Section snippets

Study population

The Americans changing lives (ACL) survey is a stratified, multistage area probability sample of noninstitutionalized civilian adults age 25 years and older living in the coterminous United States, with an oversampling of blacks and persons aged 60 years and older. The ACL wave 1 survey, conducted in 1986, interviewed 3617 persons face-to-face (representing 70% of sampled household and 68% of sampled individuals). Wave 2 was conducted in 1989, and involved face-to-face interviews with 83% (n

Results

At the time of the baseline (wave 1) survey, 84. 7% of the weighted sample (which represents the noninstitutionalized population of the United States in 1986) reported no functional impairment, 6.8% had low functional impairment, and 8.5% had moderate/severe functional impairment (Table 1). In addition, 64.2% of the weighted sample rated their own health to be “excellent” or “very good”, 20.6% rated their health to be “good”, and 15.2% rated their health to be “fair” or “poor” at the time of

Discussion

These results from a nationally representative sample of US adults show that both education and income have strong, graded associations with change in self-rated and functional health status in a 7.5 year prospective study. Men and women with less than 12 years of schooling, and those with incomes below $10,000 were two to three times more likely to have functional limitations and fair/poor self-rated health over time, compared to more advantaged men and women. Baseline levels of smoking,

Acknowledgements

This study was supported by Grants P01AG05561 and R01AG09978-01 from the National Institute on Aging, National Institutes of Health, Bethesda, MD, and by a Health Investigator Award (to Dr. House) from the Robert Wood Johnson Foundation, Princeton, NJ.

References (46)

  • M.A. Winkleby et al.

    Social class disparities in risk factors for diseaseEight-year prevalence patterns by level of education

    Preventive Medicine

    (1990)
  • Anonymous. (1998). Executive summary of the clinical guidelines on the identification, evaluation and treatment of...
  • K. Avlund

    Methodological challenges in measurements of functioning ability in gerontological researchA review

    Aging

    (1997)
  • R. Bender et al.

    Assessment of excess mortality in obesity

    American Journal of Epidemiology

    (1998)
  • L.F. Berkman et al.

    Health and ways of living

    (1983)
  • H.B. Bosworth et al.

    The association between self-rated health and mortality in a well-characterized sample of coronary artery disease patients

    Medical Care

    (1999)
  • G. Davey Smith et al.

    Magnitude and causes of socioeconomic differentials in mortalityFurther evidence from the Whitehall Study

    Journal of Epidemiology and Community Health

    (1990)
  • G. Davey Smith

    Income inequality and mortalityWhy are they related? Income inequality goes hand in hand with underinvestment in human resources

    British Medical Journal

    (1996)
  • G. Davey Smith et al.

    Adverse socioeconomic conditions in childhood and cause specific adult mortalityProspective observational study

    British Medical Journal

    (1998)
  • Davey Smith, G., Hart, C., Hole, D., et al. (1998). Education and occupational social class: Which is the more...
  • G.E. Fraser et al.

    Association among health habits, risk factors, and all-cause mortality in a black California population

    Epidemiology

    (1997)
  • M.N. Haan et al.

    Socioeconomic status and healthOld observations and new thoughts

  • Healthy People 2000. National health promotion and disease prevention objectives. Washington, DC: US Dept of Health and...
  • Cited by (309)

    • Parental preference for boys in childhood and the health of the elderly: Evidence from China

      2022, Social Science and Medicine
      Citation Excerpt :

      This is because with higher levels of education, people tend to develop healthier living habits, which helps to improve their health when they grow old (Ross and Mirowsky, 1999). Moreover, people with higher education usually have higher socioeconomic status and more economic ability to invest in health and improve the utilization of medical services (Lantz et al., 2001). This study also found that childhood health level significantly mediated the relationship between parents' preference for sons and health level among Chinese older adults.

    View all citing articles on Scopus
    View full text