Whose health is affected by income inequality? A multilevel interaction analysis of contemporaneous and lagged effects of state income inequality on individual self-rated health in the United States

The empirical relationship between income inequality and health has been much debated and discussed. Recent reviews suggest that the current evidence is mixed, with the relationship between state income inequality and health in the United States (US) being perhaps the most robust. In this paper, we examine the multilevel interactions between state income inequality, individual poor self-rated health, and a range of individual demographic and socioeconomic markers in the US. We use the pooled data from the 1995 and 1997 Current Population Surveys, and the data on state income inequality (represented using Gini coefficient) from the 1990, 1980, and 1970 US Censuses. Utilizing a cross-sectional multilevel design of 201,221 adults nested within 50 US states we calibrated two-level binomial hierarchical mixed models (with states specified as a random effect). Our analyses suggest that for a 0.05 change in the state income inequality, the odds ratio (OR) of reporting poor health was 1.30 (95% CI: 1.17-1.45) in a conditional model that included individual age, sex, race, marital status, education, income, and health insurance coverage as well as state median income. With few exceptions, we did not find strong statistical support for differential effects of state income inequality across different population groups. For instance, the relationship between state income inequality and poor health was steeper for whites compared to blacks (OR=1.34; 95% CI: 1.20-1.48) and for individuals with incomes greater than $75,000 compared to less affluent individuals (OR=1.65; 95% CI: 1.26-2.15). Our findings, however, primarily suggests an overall (as opposed to differential) contextual effect of state income inequality on individual self-rated poor health. To the extent that contemporaneous state income inequality differentially affects population sub-groups, our analyses suggest that the adverse impact of inequality is somewhat stronger for the relatively advantaged socioeconomic groups. This pattern was found to be consistent regardless of whether we consider contemporaneous or lagged effects of state income inequality on health. At the same time, the contemporaneous main effect of state income inequality remained statistically significant even when conditioned for past levels of income inequality and median income of states.     

Income inequality and physical and mental health: testing associations consistent with proposed causal pathways

OBJECTIVES: To test associations between individual health outcomes and ecological variables proposed in causal models of relations between income inequality and health. DESIGN: Regression analysis of a large, nationally representative dataset, linked to US census and other county and state level sources of data on ecological covariates. The regressions control for individual economic and demographic covariates as well as relevant potential ecological confounders. SETTING: The US population in the year 2000. PARTICIPANTS: 4817 US adults about age 40, representative of the US population. MAIN OUTCOME MEASURES: Two outcomes were studied: self reported general health status, dichotomised as "fair" or "poor" compared with "excellent", "very good", or "good", and depression as measured by a score on the Center for Epidemiologic Studies depression instrument >16. RESULTS: State generosity was significantly associated with a reduced odds of reporting poor general health (OR 0.84, 95%CI: 0.71 to 0.99), and the county unemployment rate with reduced odds of reporting depression (OR 0.91, 95%CI: 0.84 to 0.97). The measure of income inequality is a significant risk factor for reporting poor general health (OR 1.98, CI: 1.08 to 3.62), controlling for all ecological and individual covariates. In stratified models, the index of social capital is associated with reduced odds of reporting poor general health among black people and Hispanics (OR 0.40, CI: 0.18 to 0.90), but not significant among white people. The inequality measure is significantly associated with reporting poor general health among white people (OR 2.60, CI: 1.22 to 5.56) but not black people and Hispanics. CONCLUSIONS: The effect of income inequality on health may work through the influence of invidious social comparisons (particularly among white subjects) and (among black subjects and Latinos) through a reduction in social capital. Researchers may find it fruitful to recognise the cultural specificity of any such effects.     

Are racial disparities in health conditional on socioeconomic status?

Racial health inequality is related to socioeconomic status (SES), but debate ensues on the nature of the relationship. Using the US National Health and Nutrition Examination Survey I and the subsequent follow-up interviews, this research examines health disparities between white and black adults and whether the SES/health gradient differs across the two groups in the USA. Two competing mechanisms for the conditional or interactive relationship between race and SES on health are examined during a 20-year period for black and white Americans. Results show that black adults began the study with more serious illnesses and poorer self-rated health than white adults and that the disparity continued over the 20 years. Significant interactions were found between race and education as well as race and employment status on health outcomes. The interaction effect of race and education showed that the racial disparity in self-rated health was largest at the higher levels of SES, providing some evidence for the "diminishing returns" hypothesis; as education levels increased, black adults did not have the same improvement in self-rated health as white adults. Overall, the findings provide evidence for the continuing significance of both race and SES in determining health status over time.     

Racial residential segregation and geographic heterogeneity in black/white disparity in poor self-rated health in the US: a multilevel statistical analysis

Existing evidence demonstrating a relationship between racial residential segregation and health has been based on aggregate analysis. Using a multilevel analytical framework, we assess the extent of geographic variation in black/white disparities in self-rated health across US metropolitan areas, and whether racial residential segregation accounts for such variation. We estimated multilevel regression models of poor self-rated health among 51,316 non-Hispanic white and non-Hispanic black adults nested within 207 metropolitan areas to assess the multilevel relationship between segregation and racial disparities in health. We found statistically significant variation in the black/white disparity in poor self-rated health across metropolitan areas, after controlling for individual level factors (age, sex, marital status, education and income) and residential segregation. High black isolation was associated with increased odds of reporting poor health among blacks (p<0.05). While a similar pattern was observed for white/black dissimilarity and white isolation, they were not statistically significant. Our multilevel analysis only partially supports the previously reported aggregate findings linking segregation to health. Additional multilevel statistical investigations across different health outcomes are required to draw firmer conclusions regarding the adverse effects of segregation on health.     

Socioeconomic inequality in voting participation and self-rated health

OBJECTIVES: This study tested the hypothesis that disparities in political participation across socioeconomic status affect health. Specifically, the association of voting inequality at the state level with individual self-rated health was examined. METHODS: A multilevel study of 279,066 respondents to the Current Population Survey (CPS) was conducted. State-level inequality in voting turnout by socioeconomic status (family income and educational attainment) was derived from November CPS data for 1990, 1992, 1994, and 1996. RESULTS: Individuals living in the states with the highest voting inequality had an odds ratio of fair/poor self-rated health of 1.43 (95% confidence interval [CI] = 1.22, 1.68) compared with individuals living in the states with the lowest voting inequality. This odds ratio decreased to 1.34 (95% CI = 1.14, 1.56) when state income inequality was added and to 1.27 (95% CI = 1.10, 1.45) when state median income was included. The deleterious effect of low individual household income on self-rated health was most pronounced among states with the greatest voting and income inequality. CONCLUSIONS: Socioeconomic inequality in political participation (as measured by voter turnout) is associated with poor self-rated health, independently of both income inequality and state median household income.     

Income inequality and health: multilevel analysis of Chilean communities

STUDY OBJECTIVE: The evidence supporting the effect of income inequality on health has been largely observed in societies far more egalitarian than the US. This study examines the cross sectional multilevel associations between income inequality and self rated poor health in Chile; a society more unequal than the US. DESIGN: A multilevel statistical framework of 98 344 people nested within 61 978 households nested within 285 communities nested within 13 regions. SETTING: The 2000 National Socioeconomic Characterization Survey (CASEN) data from Chile. PARTICIPANTS: Adults aged 18 and above. The outcome was a dichotomised self rated health (0 if very good, good or average; 1 if poor, or very poor). Individual level exposures included age, sex, ethnicity, marital status, education, employment status, type of health insurance, and household level exposures include income and residential setting (urban/rural). Community level exposures included the Gini coefficient and median income. Main results: Controlling for individual/household predictors, a significant gradient was observed between income and poor self rated health, with very poor most likely to report poor health (OR: 2.94) followed by poor (OR: 2.77), low (OR: 2.06), middle (OR: 1.73), high (OR: 1.38) as compared with the very high income earners. Controlling for household and community effects of income, a significant effect of community income inequality was observed (OR:1.22). CONCLUSIONS: Household income does not explain any of the between community differences; neither does it account for the effect of community income inequality on self rated health, with more unequal communities associated with a greater probability of reporting poor health.     

Global variations in health: Evaluating Wilkinson's income inequality hypothesis using the World Values Survey

This international comparative study analyses individual-level data derived from the World Values Survey to evaluate Wilkinson's [(1996). Unhealthy societies: The afflictions of inequality. London: Routledge; (1998). Mortality and distribution of income. Low relative income affects mortality [letter; comment]. British Medical Journal, 316, 1611–1612] income inequality hypothesis regarding variations in health status. Random-coefficient, multilevel modelling provides a direct test of Wilkinson's hypothesis using micro-data on individuals and macro-data on income inequalities analysed simultaneously. This overcomes the ecological fallacy that has troubled previous research into links between individual self-rated health, individual income, country income and income inequality data. Logic regression analysis reveals that there are substantial differences between countries in self-rated health after taking account of age and gender, and individual income has a clear effect in that poorer people report experiencing worse health. The Wilkinson hypothesis is not supported, however, since there is no significant relationship between health and income inequality when individual factors are taken into account. Substantial differences between countries remain even after taking account of micro- and macro-variables; in particular the former communist countries report high levels of poor health.     

Income inequality and health in Ontario: a multilevel analysis

OBJECTIVE: To examine the association of income inequality at the public health unit level with individual health status in Ontario. METHODS: Cross-sectional multilevel study carried out among subjects aged 25 years or older residing in 42 public health units in Ontario. Individual-level data drawn from 30,939 respondents in 1996-97 Ontario Health Survey. Median area income and income inequality (Gini coefficient) calculated from 1996 census. Self-rated health status (SRH) and Health Utilities Index (HUI-3) scores were used as main outcomes. RESULTS: Controlling for individual-level factors including income, respondents living in public health units in the highest tercile of income inequality had odds ratios of 1.20 (95% CI 1.04 - 1.38) for fair/poor self-rated health, and 1.11 (95% CI 1.01 - 1.22) for HUI score below the median, compared with people living in public health units in the lowest tercile. Controlling further for median area income had little effect on the association. CONCLUSION: Income inequality was significantly associated with individual self-reported health status at public health unit level in Ontario, independent of individual income.     

Bonding versus bridging social capital and their associations with self rated health: a multilevel analysis of 40 US communities

STUDY OBJECTIVE: Few studies have distinguished between the effects of different forms of social capital on health. This study distinguished between the health effects of summary measures tapping into the constructs of community bonding and community bridging social capital. DESIGN: A multilevel logistic regression analysis of community bonding and community bridging social capital in relation to individual self rated fair/poor health. SETTING: 40 US communities. PARTICIPANTS: Within community samples of adults (n = 24 835), surveyed by telephone in 2000-2001. MAIN RESULTS: Adjusting for community sociodemographic and socioeconomic composition and community level income and age, the odds ratio of reporting fair or poor health was lower for each 1-standard deviation (SD) higher community bonding social capital (OR = 0.86; 95% = 0.80 to 0.92) and each 1-SD higher community bridging social capital (OR = 0.95; 95% CI = 0.88 to 1.02). The addition of indicators for individual level bonding and bridging social capital and social trust slightly attenuated the associations for community bonding social capital (OR = 0.90, 95% CI = 0.84 to 0.97) and community bridging social capital (OR = 0.96, 95% CI = 0.89 to 1.03). Individual level high formal bonding social capital, trust in members of one's race/ethnicity, and generalised social trust were each significantly and inversely related to fair/poor health. Furthermore, significant cross level interactions of community social capital with individual race/ethnicity were seen, including weaker inverse associations between community bonding social capital and fair/poor health among black persons compared with white persons. CONCLUSIONS: These results suggest modest protective effects of community bonding and community bridging social capital on health. Interventions and policies that leverage community bonding and bridging social capital might serve as means of population health improvement.     

Does the state you live in make a difference? Multilevel analysis of self-rated health in the US

This paper investigates the different sources of variation between US states in self-rated health using multilevel statistical procedures. The different sources that are considered are based on individual- and state-level factors. Data for the analysis comes from the 1993-94 Behavioral Risk Factor Surveillance System and the 1986-90 General Social Surveys. Results show that individual-level factors (such as low income, being black, smoking) are strongly associated with self-rated poor health. Significant variation, however, remain between states after allowing for individual characteristics. Crucially, between-state variation in self-rated health is different for different income groups. State-level contextual effects are found for per-capita median-income and 'social capital'. While not strong, there seems to be a differential impact of state income-inequality on high-income groups, such that the affluent report better health from living in high inequality states. The paper substantiates the need to connect individual health to their macro socioeconomic context. Importantly, it is argued that without adopting an explicitly multilevel approach, the debate on linkages between individual health and income-inequality/social capital cannot be adequately addressed.     

Self-Rated Health and Race Among Hispanic and Non-Hispanic Adults

Objective To investigate the association between race and self-rated health among Hispanics and non-Hispanics using data from the National Health Interview Survey 2000–2003. Methods This analysis was limited to Hispanic and non-Hispanic whites and blacks ≥18 years of age. The outcome was self-rated health. The main independent variable was race/ethnicity, and potential confounders included sociodemographic characteristics, access to care, health behaviors, and comorbidities. Results Non-Hispanic blacks exhibited the highest prevalence of fair/poor self-rated health compared to their white counterparts. In the adjusted analyses, compared to non-Hispanic whites, non-Hispanic blacks (OR: 1.21; 95% CI: 1.16–1.43), Hispanic whites (OR: 1.32; 95% CI: 1.14–1.52) and blacks (OR: 2.19; 95% CI: 1.07–4.49) were more likely to rate their health as fair/poor. There was no difference in self-rated health between Hispanic and non-Hispanic blacks. Discussion This study underscores the importance of accounting for the racial heterogeneity among Hispanics when presenting health data. Ignoring race could mask health variations among Hispanics.     

Income inequality and mortality: a multilevel prospective study of 521 248 individuals in 50 US states

BACKGROUND: Some of the most consistent evidence in favour of an association between income inequality and health has been among US states. However, in multilevel studies of mortality, only two out of five studies have reported a positive relationship with income inequality after adjustment for the compositional characteristics of the state's inhabitants. In this study, we attempt to clarify these mixed results by analysing the relationship within age-sex groups and by applying a previously unused analytical method to a database that contains more deaths than any multilevel study to date. METHODS: The US National Longitudinal Mortality Study (NLMS) was used to model the relationship between income inequality in US states and mortality using both a novel and previously used methodologies that fall into the general framework of multilevel regression. We adjust age-sex specific models for nine socioeconomic and demographic variables at the individual level and percentage black and region at the state level. RESULTS: The preponderance of evidence from this study suggests that 1990 state-level income inequality is associated with a 40% differential in state level mortality rates (95% CI = 26-56%) for men 25-64 years and a 14% (95% CI = 3-27%) differential for women 25-64 years after adjustment for compositional factors. No such relationship was found for men or women over 65. CONCLUSIONS: The relationship between income inequality and mortality is only robust to adjustment for compositional factors in men and women under 65. This explains why income inequality is not a major driver of mortality trends in the United States because most deaths occur at ages 65 and over. This analysis does suggest, however, the certain causes of death that occur primarily in the population under 65 may be associated with income inequality. Comparison of analytical techniques also suggests coefficients for income inequality in previous multilevel mortality studies may be biased, but further research is needed to provide a definitive answer.     

Income inequality,household income,and health status in Canada: a prospective cohort study

OBJECTIVES: This study sought to determine whether income inequality, household income, and their interaction are associated with health status. METHODS: Income inequality and area income measures were linked to data on household income and individual characteristics from the 1994 Canadian National Population Health Survey and to data on self-reported health status from the 1994, 1996, and 1998 survey waves. RESULTS: Income inequality was not associated with health status. Low household income was consistently associated with poor health. The combination of low household income and residence in a metropolitan area with less income inequality was associated with poorer health status than was residence in an area with more income inequality. CONCLUSIONS: Household income, but not income inequality, appears to explain some of the differences in health status among Canadians.     

Income inequality and self-rated health in US metropolitan areas: A multi-level analysis

Income inequality has been found to affect health in a number of international and cross-national studies. Using data from a telephone survey of adults in the United States, this study analyzed the effect of metropolitan level income inequality on self-rated health. It combined individual data from the 2000 Behavioral Risk Factor Surveillance System with metropolitan level income data from the 2000 Census. After controlling for smoking, age, education, Black race, Hispanic ethnicity, sex, household income, and metropolitan area per capita income, this study found that for each 1 point rise in the GINI index (on a hundred point scale) the risk of reporting Fair or Poor self-rated health increased by 4.0% (95% confidence interval 1.6–6.5%). Given that self-rated health is a good predictor of morbidity and mortality, this suggests that metropolitan area income inequality is affecting the health of US adults.     

Poor health is associated with episodic heavy alcohol use: evidence from a National Survey

OBJECTIVES: The objective of this study was to examine the relationship between self-rated health and episodic heavy drinking in a representative sample of American adults. We also sought to determine ethnic and gender differences in the association between self-rated health and episodic heavy drinking. METHODS: Data (n=4649) from the Third US National Health and Nutrition Examination Survey were utilized for this investigation. Episodic heavy drinking was defined as the consumption of five or more and four or more alcoholic beverages on one occasion for men and women, respectively. Poor health was defined as answering fair or poor to the question: "Would you say your health in general is excellent, very good, good, fair or poor?" Odds ratio from the logistic linear regression analysis was used to estimate the risk for poor health that was associated with episodic heavy drinking. Statistical adjustments were made for age, hypertension, diabetes, current smoking, body mass index and race/ethnicity. RESULTS: Overall, episodic heavy drinking was associated with increased odds of poor self-rated health in men and women. In men, episodic heavy drinking was independently associated with 1.28 (95% CI: 1.07-1.82) increased odds of poor health. The corresponding value in women was 1.86 (95% CI: 1.05-2.28). In men, being Black was associated with approximately two-fold (OR=1.96; 95% CI: 1.33, 2.89), and being Hispanic was associated with approximately four-fold (OR=3.59; 95% CI: 2.50, 5.14) increased odds of poor self-rated health relative to being White. The corresponding odds ratios in women were 2.97 (95% CI: 1.90, 4.64) and 5.18 (95% CI: 3.23, 8.30). Associations were greater among blacks (adjusted OR=2.41; 95% CI: 1.81-3.22) and Hispanics (adjusted OR=4.15; 95% CI: 3.12-5.52) than among whites. CONCLUSIONS: Poor health is associated with episodic heavy alcohol consumption. Public health strategies to curb alcohol abuse may improve self-reported health status in these at-risk populations.     

Income inequality, social capital and self-rated health and dental status in older Japanese

The erosion of social capital in more unequal societies is one mechanism for the association between income inequality and health. However, there are relatively few multi-level studies on the relation between income inequality, social capital and health outcomes. Existing studies have not used different types of health outcomes, such as dental status, a life-course measure of dental disease reflecting physical function in older adults, and self-rated health, which reflects current health status. The objective of this study was to assess whether individual and community social capital attenuated the associations between income inequality and two disparate health outcomes, self-rated health and dental status in Japan. Self-administered questionnaires were mailed to subjects in an ongoing Japanese prospective cohort study, the Aichi Gerontological Evaluation Study Project in 2003. Responses in Aichi, Japan, obtained from 5715 subjects and 3451 were included in the final analysis. The Gini coefficient was used as a measure of income inequality. Trust and volunteering were used as cognitive and structural individual-level social capital measures. Rates of subjects reporting mistrust and non-volunteering in each local district were used as cognitive and structural community-level social capital variables respectively. The covariates were sex, age, marital status, education, individual- and community-level equivalent income and smoking status. Dichotomized responses of self-rated health and number of remaining teeth were used as outcomes in multi-level logistic regression models. Income inequality was significantly associated with poor dental status and marginally significantly associated with poor self-rated health. Community-level structural social capital attenuated the covariate-adjusted odds ratio of income inequality for self-rated health by 16% whereas the association between income inequality and dental status was not substantially changed by any social capital variables. Social capital partially accounted for the association between income inequality and self-rated health but did not affect the strong association of income inequality and dental status.     

Relative deprivation in income and self-rated health in the United States

Absolute income is robustly associated with health status. Few studies have, however, examined if relative income is independently associated with health. We examined if, over and above the effects of absolute income, individual relative deprivation in income as well as position in the income hierarchy is associated with individual poor health in the U.S. Using three rounds of the Current Population Surveys (CPS), we analyzed the association between self-rated health (1 = fair/poor, 0 = otherwise) and the Yitzhaki index of relative deprivation in income and percentile position in the income hierarchy across 17 reference groups. Over and above the effects of absolute income, the odds ratio for reporting poor health among individuals in the highest quintile of relative deprivation compared to the lowest quintile ranged between 2.18 and 3.30, depending on the reference groups used. A 10 percentile increase in income position within reference groups was associated with an odds ratio of poor health of 0.89. Relative deprivation appeared to explain between 33 and 94% of the association between individual income and self-rated health. Relative deprivation in income is independently associated with poor health over and above the well established effects of absolute income on health. Relative deprivation may partly explain the association between income inequality and worse population health status.     

Do social comparisons explain the association between income inequality and health?: Relative deprivation and perceived health among male and female Japanese individuals

Relative deprivation has been hypothesized as one of the pathways accounting for the link between income inequality and health. We tested this hypothesis in a large national sample of men and women in Japan. Our survey included a probability sample of 22,871 men and 24,243 women aged 25-64, from whom information was gathered on demographic variables, household income, occupation or employment status, and self-rated health. Our measure of relative deprivation was the Yitzhaki Index, which calculates the deprivation suffered by each individual as a function of the aggregate income shortfall for each person relative to everyone else with higher incomes in that person's reference group. We modeled several alternative reference groups, including others with the same occupation, others of the same age group, and others living in the same geographic area (prefecture), as well as combinations of these. Generalized estimating equations demonstrated that higher relative deprivation was associated with worse self-rated health. Even after controlling for absolute income as well as other sociodemographic factors, the odds ratio and its 95% confidence intervals (CI) for poor health ranged from 1.09 (95% CI: 1.02-1.16) to 1.18 (95% CI: 1.11-1.26) for men and from 1.10 (95% CI: 1.04-1.16) to 1.16 (95% CI: 1.09-1.23) for women per 1 million increase in the Yitzhaki Index. As such, relative income deprivation is associated with poor self-rated health independently of absolute income, and relative deprivation may be a mechanism underlying the link between income inequality and population health.     

Aggregation and the measurement of income inequality: effects on morbidity

This is a cross-sectional study using records from the National Health Interview Survey linked to Census geography. The sample is restricted to white males ages 25-64 in the United States from three years (1989-1991) of the National Health Interview Survey. Perceived health is used to measure morbidity. Individual covariates include income-to-needs ratio, education and occupation. Contextual level measures of income inequality, median household income and percent in poverty are constructed at the US census county and tract level. The association between inequality and morbidity is examined using logistic regression models. Income inequality is found to exert an independent adverse effect on self-rated health at the county level, controlling for individual socioeconomic status and median income or percent poverty in the county. This corresponding effect at the tract level is reduced. Median income or percent poverty and individual socioeconomic status are the dominant correlates of perceived health status at the tract level. These results suggest that the level of geographic aggregation influences the pathways through which income inequality is actualized into an individuals' morbidity risk. At higher levels of aggregation there are independent effects of income inequality, while at lower levels of aggregation, income inequality is mediated by the neighborhood consequences of income inequality and individual processes.     

Mortality,inequality and race in American cities and states

A number of studies have found that mortality rates are positively correlated with income inequality across the cities and states of the US. We argue that this correlation is confounded by the effects of racial composition. Across states and Metropolitan Statistical Areas (MSAs), the fraction of the population that is black is positively correlated with average white incomes, and negatively correlated with average black incomes. Between-group income inequality is therefore higher where the fraction black is higher, as is income inequality in general. Conditional on the fraction black, neither city nor state mortality rates are correlated with income inequality. Mortality rates are higher where the fraction black is higher, not only because of the mechanical effect of higher black mortality rates and lower black incomes, but because white mortality rates are higher in places where the fraction black is higher. This result is present within census regions, and for all age groups and both sexes (except for boys aged 1-9). It is robust to conditioning on income, education, and (in the MSA results) on state fixed effects. Although it remains unclear why white mortality is related to racial composition, the mechanism working through trust that is often proposed to explain the effects of inequality on health is also consistent with the evidence on racial composition and mortality.