However, the role of socioeconomic status in explaining Asian-white differences is less clear, and it does not explain the relative health advantage of Hispanics. Taking these nonlinearities into account may help further explain black-white health differences. There also appear to be significant nonlinearities in the effects of income and wealth, as these factors have a much stronger effect on health in the bottom third of their respective distributions than in the top third. Good examples of large racial or ethnic differences that are not explained by socioeconomic status are hypertension among black men and diabetes among black and Hispanic men (Crimmins et al., 2004). When socioeconomic status is controlled, health differences between blacks and whites in mortality and functional limitations are sometimes eliminated (Kington and Smith, 1997), though differences may not disappear for specific diseases. Socioeconomic variations such as these, coupled with similar variations at younger ages, partly explain racial and ethnic differences in a number of health outcomes (Hayward et al., 2000 Smith and Kington, 1997). (1999).ġ990 household data suggest levels of poverty among American Indians similar to those for blacks, and levels for Alaska Natives similar to those for Asians (U.S.

SOURCES: Data from Federal Interagency Forum on Aging Related Statistics (2000) and Kramarow et al. TABLE 4-2 Socioeconomic Status by Race and Ethnicity Among Persons Aged 65 Years and Older (2003) argue that among the retired population, there may be no income However, Smith and Kington (1997) show that much of the correlation between current income and health among males in their 50s appears to be the effect of health on income, rather than the reverse, and Adams et al. Reciprocal causation has been one of the most difficult issues to deal with in this literature, and it is often ignored or dismissed as a minor factor. Though the table does not show it, smaller gains in wealth were associated with less favorable health outcomes.

Table 4-1 shows that those with “fair” or “poor” self-reported health in 1984 not only had much lower wealth in that year but also saw their wealth grow less than that of others over the next 10 years. After some age, changes in some aspects of socioeconomic status have diminishing effects on health it is unclear which changes in aspects of socioeconomic status continue to affect health in old age.Īssessing the effect of lifetime socioeconomic conditions on health is complicated by the fact that health also affects income and wealth, especially among adults (Smith, 1999). The health gradient by socioeconomic status widens through childhood and the adult working years and then contracts after retirement (Case et al., 2002 Crimmins et al., 2004 House et al., 1994). SOURCE: Data from Health and Retirement Survey, as reported by Crimmins et al. Better SES measures are needed in data sources, but improvements could be made by using existing information more thoughtfully and acknowledging its limitations.FIGURE 4-1 Death within 2 years and prevalence of various conditions, by years of education (in percent). We recommend an outcome- and social group–specific approach to SES measurement that involves (1) considering plausible explanatory pathways and mechanisms, (2) measuring as much relevant socioeconomic information as possible, (3) specifying the particular socioeconomic factors measured (rather than SES overall), and (4) systematically considering how potentially important unmeasured socioeconomic factors may affect conclusions. Evidence also shows that conclusions about nonsocioeconomic causes of racial/ethnic differences in health may depend on the measure-eg, income, wealth, education, occupation, neighborhood socioeconomic characteristics, or past socioeconomic experiences-used to “control for SES,” suggesting that findings from studies that have measured limited aspects of SES should be reassessed.

For example, marked racial/ethnic differences in income at a given educational level and in wealth at a given income level raise questions about the socioeconomic comparability of individuals who are similar on education or income alone. We critically examine standard SES measurement approaches, illustrating problems with examples from new analyses and the literature. Problems with measuring socioeconomic status (SES)-frequently included in clinical and public health studies as a control variable and less frequently as the variable(s) of main interest-could affect research findings and conclusions, with implications for practice and policy.

Socioeconomic status