Social Stratification of Health and Aging
Citation: House, et al. (1994) Social Stratification of Health and Aging.
Internet Archive Scholar (search for fulltext): Social Stratification of Health and Aging
Tagged: uw-madison (RSS), wisconsin (RSS), sociology (RSS), demography (RSS), prelim (RSS), qual (RSS), WisconsinDemographyPrelimAugust2009 (RSS)
Summary
Background: In a previous study, House et al. (1990) showed that both age and socioeconomic status have strong effects on health. Furthermore, the study showed that their effects are interactive rather than additive. "That is, SES significantly moderates the relation of age to health, with the upper socioeconomic strata approaching the ideal of relatively low levels of morbidity and functional limitations until quite late in life, whereas at lower socioeconomic levels morbidity and functional limitations rise steadily throughout middle and early old age" (p. 214). However, the previous study is cross-sectional and does not account for the possible mediating effects of psychosocial risk factors (e.g., risky health behaviors, lack of social support and stress). Therefore, House et al. attempt to improve on previous work by (1) decomposing SES measures into separate education and income effects, (2) assessing to what extent the relationship between SES and health is explained by differential exposure to and impact of psychosocial risk factors and (3) examining longitudinal changes in health over a 2.5 year span.
Methods: Data are from a longitudinal survey entitled Americans' Changing Lives. The dependent variables are two self-report indicators of physical health-namely the number of chronic conditions and an index of functional status. Measures of social stratification are years of education and income from the respondent and his/her spouse. Age is also included, as are sex and race (as control variables). Psychosocial risk factors include health behaviors (smoking, weight, drinking), social relationships and supports (marital status, informal social contacts, formal social contacts), acute and chronic stress (including indices of negative life events), and self esteem and mastery (each of which has its own index). Data were analyzed by ordinal logit models for the cross-sectional data and standard logistic models for the longitudinal data. Results: Cross-sectional analyses support previous research on SES and health by confirming that education and income have significant independent effects on health. Also, the results show "that the interaction between age and SES (i.e., education or income) in predicting health can be substantially explained by greater exposure of lower SES persons to a wide range of psychosocial risk factors to health, especially in middle and early old age, and, to a lesser degree, the greater impact of these risk factors on health with age" (from abstract). Finally, longitudinal analyses confirm the findings of the cross-sectional data-namely that education and income are important predictors of declines in health. When psychosocial risk factors are included in the longitudinal analyses, they reduce the effects of income and education become non-significant levels.
Discussion: Results are consistent with research showing that SES affects health (rather than the other way around) and SES "predicts and hence is a likely cause of most psychosocial risk factors" (p. 228). Longer-term longitudinal studies are needed to clarify these effects and lend understanding to the narrowing of socioeconomic differences in later life (e.g., selection effects?) Because the "preventable health problems of our society increasingly concentrated among persons of lower socioeconomic status in middle and early old age" (p. 229), it is important to consider strategies that narrow the gap between social classes. Furthermore, because it may prove quite difficult to modify psychosocial risk factors without a concomitant improvement of environment, policies which eliminate extreme deprivation and limit inequality may be required to reduce psychosocial risk factors.
