¶ Adjusted for individual age, sex, marital status, years of education, equivalized household income categories, covered by health insurance, and state median income. The vertical axis (ordinate) then plots the proportion of the aggregate income within that community accruing to each group. Early reviews came to different interpretations of the evidence, though a large majority of studies reported that health tended to be worse in more unequal societies. (2002) ‘Income Inequality and Health Status in the United States: Evidence from the Current Population Survey’, Journal of Human Resources, 37: 510–39. Although the published evidence so far is by no means conclusive about the relation between income distribution and population health, our aim is to draw attention to some emerging patterns in the accumulated findings and to suggest future directions for research in this topic. Marginal models treat the variance structures (e.g., the variance that is explicitly attributable to states) as a nuisance while estimating the fixed effect for an exposure. (19) studied 205,245 subjects, Lochner et al. Blakely TA, Lochner K, Kawachi I. Of these, the Gini coefficient is frequently used. As shown in table 2, studies outside the United States have been primarily confined to smaller geographic scales (e.g., parishes within a single city (34)) at which one would not necessarily expect to find variations in political behavior or policy-making according to differences in income distribution. Income includes the revenue streams from wages, salaries, interest on a savings account, dividends from shares of stock, rent, and profits from selling something for more than you paid for it. The evidence at lower levels of aggregation, such as metropolitan areas (16), counties (26), and census tracts (20), is decidedly mixed. In: Boyle P, Curtis S, Graham E, eds. For example, the average annual salary in America in inflation-adjusted 1998 dollars increased from $32,522 in 1970 to $35,864 in 1999, that is, a modest 10 percent increase over three decades. Most multilevel studies on income inequality and health have not paid detailed attention to potential cross-level interactions, whereby state income inequality may affect the health of different population groups in different ways. The degree to which the Lorenz curve departs from the 45-degree line of equality is a measure of income inequality. Using the existing evidence, can we conclude that income inequality is a public health hazard? We use cookies to help provide and enhance our service and tailor content and ads. The authors thank Harvey Goldstein and Jim Ware for our exchanges with them with regard to comparisons of modeling strategies and Mah-J. While these studies may have lacked statistical power, we also hasten to add that the lack of an association between income inequality and health at levels below the US states may be attributable to a true absence of an association (a finding corroborated in studies that were adequately powered, for instance, at the metropolitan area level (16)). not reported), 144,692 adults nested within 39 US states, 18,547 respondents and adults nested within 232 US metropolitan areas and 216 counties, No (at both metropolitan and county levels), “Healthcare for Communities” telephone survey (1997–1998), 8,235 adults from US metropolitan areas (no. Metropolitan area income inequality and self rated health—a multilevel study. Social cohesion, social capital, and health. In: Berkman LF, Kawachi I, eds. Multilevel studies have the ability to simultaneously assess the associations of individual income and societal income inequality with individual health status. However, these studies have been criticized because of their inability to disentangle the effects of individual income (and income poverty) from the contextual effects of income inequality (6). The most probable channel is that the lower in the social pecking order, the more likely is it that status causes stress. Future studies should recognize and anticipate, a priori, this level contingency between income inequality and health outcomes. Indeed, as we show later, the majority of empirical work does not apply multilevel models to analyzing multilevel data. Subramanian SV. The individual health outcome measure available in this data set is self-rated health, based on the single item: “Would you say your health in general is excellent, very good, good, fair, or poor?” Following previous studies (16, 19, 24, 25), the five categories were dichotomized with 0 for “excellent, very good, or good” and 1 for “fair or poor.” While self-rated health is not the same as mortality or clinically diagnosed morbidity measures, a review of 27 prospective studies in the United States and elsewhere has established that self-reported health is highly predictive of subsequent mortality, independent of other medical, behavioral, and/or psychosocial factors (50). Indeed, some argue, on theoretical grounds, that any observed effect of absolute income on health already incorporates the effects of hierarchy (income rank) as well as relative income (63). Kawachi I. Using categories of income (model 7) yields an odds ratio of 1.30. Sturm R, Gresenz CR. Subramanian SV, Belli P, Kawachi I. Random parameter estimates of the between-state variation, % state-attributable variation, and % change in between-state variation with sequential introduction of predictors in the fixed part of a multilevel logistic model with self-rated fair/poor health as an outcome*. Consequently, researchers have posited that an aggregate relation between the average health status of a society and the level of income inequality in a society could be observed if the individual-level relation between income and health (within society) is concave. Neighborhood differences in social capital: compositional artifact or a contextual construct? While marginal models are robust (42) when our interest is only in estimating the “fixed” (average) effect of an exposure (e.g., income inequality), there may be problems of inefficiency (43). Milyo J. For full access to this pdf, sign in to an existing account, or purchase an annual subscription. (In figure 1, it takes the bottom half of the households to account for just 10 percent of the aggregate income.) Widening economic inequality in the USA has been accompanied by increasing disparities in health outcomes. Throughout the rest of this review, we shall refer to the independent contextual income inequality effect as the “pollution effect” of income inequality on health. These findings suggest that, while individual race, educational attainment, and income attenuate the baseline effect of state income inequality, they do not fully account for the observed association between self-rated poor health and state income inequality in the United States. S. V. Subramanian, Ichiro Kawachi, Income Inequality and Health: What Have We Learned So Far?, Epidemiologic Reviews, Volume 26, Issue 1, July 2004, Pages 78–91, https://doi.org/10.1093/epirev/mxh003. The term “marginal models” is used to represent models that treat the nested structure of the data and the potential clustering in individual observations as a necessary nuisance and accordingly adjust the standard errors associated with the regression estimates. Economic inequality grew in 90’s boom, Fed reports. Vol 1. We have demonstrated elsewhere that racial composition—whether measured as individual clustering of races within states or measured as proportion Black—does not account for the state income inequality-health relation (25, 58). * The term “single-level regression” is used in a generic sense to represent models that ignore the nested structure of the data and thereby the clustering in the individual observations; as such, the functional form of the outcome— whether it is linear, binary, or count—is not relevant. Second, studies conducted outside the United States have generally failed to find an association between income inequality and health (31–35). Being obese can have a serious impact on mental and physical health. Aberg YM, Fritzell J, Lundberg O, et al. These issues, nonetheless, raise important questions for interpreting context-attributable variation, in general. Pearce N, Davey Smith G. Is social capital the key to inequalities in health? Andrews EL. Wage poverty, earned income inequality, and health. By contrast, studies that found an association between state-level income inequality and mortality have tended to involve larger numbers. In this paper, we review the published multilevel studies of income inequality and health. Again, a systematic multilevel investigation of how the state-level social capital may mediate the relation between state income inequality and health is currently lacking. There is a very large literature examining income inequality in relation to health. Therefore, the population health impacts of income inequality are potentially widespread, much like the impacts of income poverty on health outcomes. The odds ratio of reporting poor health increases by 1.32 for every 5 percent increase in the state Gini coefficient when no account is taken of the individual income-health relation (model 1). Does the state you live in make a difference? Income distribution, socioeconomic status and self-rated health: a US multilevel analysis. Washington, DC: Income Statistics Branch/Housing and Household Economic Statistics Division, US Census Bureau, 2000. Typical single-level regression models are inadequate since they anticipate and model only a single source of variation (e.g., equations 1 and 2) and, as such, “multilevel regression models” (11) (also referred to as hierarchical (12), mixed and random-effects (13), covariance components (14), or random-coefficient regression (15) models) of the form specified in equation 3 are required to specify the income, income inequality, and health relation. Wagstaff A, van Doorslaer E. Income inequality and health: what does the literature tell us? Accordingly, not only the standard errors are adjusted to reflect the “true” sample size based on the extent of clustering but also state-attributable variation is explicitly modeled and estimated. Mellor JM, Milyo J. 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