Metropolitan area income inequality and self-rated health--a multi-level study

We examined the association of income inequality measured at the metropolitan area (MA) and county levels with individual self-rated health. Individual-level data were drawn from 259,762 respondents to the March Current Population Survey in 1996 and 1998. Income inequality and average income were calculated from 1990 census data, the former using Gini coefficients. Multi-level logistic regression models were used. Controlling for sex, age, race, and individual-level household income, respondents living in high, medium-high, and medium-low income inequality MAs had odds ratios of fair/poor self-rated health of 1.20 (95% confidence interval 1.04-1.38), 1.07 (0.95-1.21), and 1.02 (0.91-1.15), respectively, compared to people living in the MAs with the lowest income inequality. However, we found only a small association of MA-level income inequality with fair/poor health when controlling further for average MA household income: odds ratios were 1.10 (0.95-1.28), 1.01 (0.89-1.14), and 1.00 (0.89-1.12), respectively. Likewise, we found only a small association of county-level income inequality with self-rated health although only 40.7% of the sample had an identified county on CPS data. Regarding the association of state-level income inequality with fair/poor health, we found the association to be considerably stronger among non-metropolitan (i.e. rural) compared to metropolitan residents.     

The association between state income inequality and worse health is not confounded by race

BACKGROUND: The relationship between income inequality and health across US states has been challenged recently on grounds that this relationship may be confounded by the effect of racial composition, measured as the proportion of the state's population who are black. METHODS: Using multilevel statistical models, we examined the association between state income inequality and poor self-rated health. The analysis was based on the pooled 1995 and 1997 Current Population Surveys, comprising 201 221 adults nested within 50 US states. RESULTS: Controlling for the individual effects of age, sex, race, marital status, education, income, health insurance coverage, and employment status, we found a significant effect of state income inequality on poor self-rated health. For every 0.05-increase in the Gini coefficient, the odds ratio (OR) of reporting poor health increased by 1.39 (95% CI: 1.26, 1.51). Additionally controlling for the proportion of the state population who are black did not explain away the effect of income inequality (OR = 1.30; 95% CI: 1.15, 1.45). While being black at the individual level was associated with poorer self-rated health, no significant relationship was found between poor self-rated health and the proportion of black residents in a state. CONCLUSION: Our finding demonstrates that neither race, at the individual level, nor racial composition, as measured at the state level, explain away the previously reported association between income inequality and poorer health status in the US.     

Income inequality and weight status in US metropolitan areas

Prior empirical studies have demonstrated an association between income inequality and general health endpoints such as mortality and self-rated health, and findings have been taken as support for the hypothesis that inequality is detrimental to individual health. Unhealthy weight statuses may function as an intermediary link between inequality and more general heath endpoints. Using individual-level data from the 1996-98 Behavioral Risk Factor Surveillance System, we examine the relationship between individual weight status and income inequality in US metropolitan areas. Income inequality is calculated with data from the 1990 US Census 5% Public Use Microsample. In analyses stratified by race-sex groups, we do not find a positive association between income inequality and weight outcomes such as body mass index, the odds of being overweight, and the odds of being obese. Among white women, however, we do find a statistically significant inverse association between inequality and each of these weight outcomes, despite adjustments for individual-level covariates, metropolitan-level covariates, and census region. We also find that greater inequality is associated with higher odds for trying to lose weight among white women, even adjusting for current weight status. Although our findings are suggestive of a contextual effect of metropolitan area income inequality, we do not find an increased risk for unhealthy weight outcomes, adding to recent debates surrounding this topic.     

Rising U.S. income inequality,gender and individual self-rated health, 1972–2004

The effect of income inequality on health has been a contested topic among social scientists. Most previous research is based on cross-sectional comparisons rather than temporal comparisons. Using data from the General Social Survey and the U.S. Census Bureau, this study examines how rising income inequality affects individual self-rated health in the U.S. from 1972 to 2004. Data are analyzed using hierarchical generalized linear models. The findings suggest a significant association between income inequality and individual self-rated health. The dramatic increase in income inequality from 1972 to 2004 increases the odds of worse self-rated health by 9.4 percent. These findings hold for three measures of income inequality: the Gini coefficient, the Atkinson Index, and the Theil entropy index. Results also suggest that overall income inequality and gender-specific income inequality harm men's, but not women's, self-rated health. These findings also hold for the three measures of income inequality. These findings suggest that inattention to gender composition may explain apparent discrepancies across previous studies.     

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.     

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.     

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 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.     

Socioeconomic disparities and health: impacts and pathways

Growing socioeconomic disparity is a global concern, as it could affect population health. The author and colleagues have investigated the health impacts of socioeconomic disparities as well as the pathways that underlie those disparities. Our meta-analysis found that a large population has risks of mortality and poor self-rated health that are attributable to income inequality. The study results also suggested the existence of threshold effects (ie, a threshold of income inequality over which the adverse impacts on health increase), period effects (ie, the potential for larger impacts in later years, specifically after the 1990s), and lag effects between income inequality and health outcomes. Our other studies using Japanese national representative survey data and a large-scale cohort study of Japanese older adults (AGES cohort) support the relative deprivation hypothesis, namely, that invidious social comparisons arising from relative deprivation in an unequal society adversely affect health. A study with a natural experiment design found that the socioeconomic gradient in self-rated health might actually have become shallower after the 1997-98 economic crisis in Japan, due to smaller health improvements among middle-class white-collar workers and middle/upper-income workers. In conclusion, income inequality might have adverse impacts on individual health, and psychosocial stress due to relative deprivation may partially explain those impacts. Any study of the effects of macroeconomic fluctuations on health disparities should also consider multiple potential pathways, including expanding income inequality, changes in the labor market, and erosion of social capital. Further studies are needed to attain a better understanding of the social determinants of health in a rapidly changing society.     

Income inequality and self-rated health in Stockholm, Sweden: a test of the 'income inequality hypothesis' on two levels of aggregation

The number of studies analysing income inequality and health are voluminous. However, when empirically testing the income inequality hypothesis, the level of aggregation could be crucial for whether we find an association or not and for the mechanisms we believe are active. This study hence investigates: (1) the two-year lagged effect by income inequality on health at two levels of aggregation; municipalities and neighbourhoods in Sweden; (2) whether spending on social goods accounts for the association between income inequality and health; (3) the effect by income inequality among the affluent and the disadvantaged in municipalities and neighbourhoods, respectively. The empirical data is based on a Swedish public health survey in 2002 and includes residents of Stockholm aged 18-84 years. The sample consists of 28,092 individuals nested within 22 municipalities and 709 neighbourhoods in the county of Stockholm with a non-response rate of 37 percent. A total population register (HSIA) is further used for the construction of contextual-level indicators. Primary method used is multi-level logistic regression. The findings indicate a moderate effect by high and very high income inequality on self-rated poor health at the municipality-level. The association, however, ceases after adjustment for spending on social goods. No detrimental effect by income inequality on self-rated health at the neighbourhood-level is found. The results further suggest that poor individuals residing in high inequality neighbourhoods do not have poorer health than those residing in low inequality contexts while high inequality is most deleterious for poor individuals at the municipality-level. In sum, the findings suggest that reduced spending on social goods could account for the association between income inequality and health at the municipality-level. The contrasting findings at the neighbourhood- and municipality-level indicate that it is important to consider the level of aggregation when studying health effects by income inequality.     

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.     

Rural/urban differences in self-rated health: Examining the roles of county size and metropolitan adjacency

This research explored the roles of 'rurality' - nonmetropolitan county population size and adjacency to metropolitan areas - on self-rated health among a nationally representative sample of US adults. Using seven years of pooled individual level data from the Behavioral Risk Factor Surveillance System and county-level data from the County Characteristics survey, we found that residents of remote rural counties have the greatest odds of reporting bad health and that the significant differences in self-rated health between metropolitan residents and residents of rural areas can be entirely explained by rural structural disadvantage, including higher rates of unemployment and population loss and lower levels of educational attainment.     

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.     

Income inequality,area-level poverty,perceived aversion to inequality,and self-rated health in Japan

In this study we conduct a multilevel analysis to investigate the association between regional income inequality and self-rated health in Japan, based on two nationwide surveys. We confirm that there is a significant association between area-level income inequality and individual-level health assessment. We also find that health assessment tends to be more sensitive to income inequality among lower income individuals, and to degree of area-level poverty, than income inequality for the society as a whole. In addition, we examine how individuals are averse to inequality, based on the observed association between inequality and self-rated health.     

Extending the income inequality hypothesis: ecological results from the 2005 and 2009 Argentine National Risk Factor Surveys

A consensus on income inequality as a social determinant of health is yet to be reached. In particular, we know little about the cross-sectional versus lagged effect of inequality and the robustness of the relationship to indicators that are sensitive to varying parts of the income spectrum. We test these issues with data from Argentina's 2005 and 2009 National Risk Factor Surveys. Inequality was operationalised at the provincial level with the Gini coefficient and the Generalised Entropy (GE) index. Population health was defined as the age-standardised percentage of adults with poor/fair self-rated health by province. Our cross-sectional results indicate a significant relationship between inequality (Gini) and poor health (r=0.58, p<0.01) in 2005. Using the GE index, a gradient pattern emerges in the correlation, and the r values increase as the index becomes sensitive to the top of the distribution. The relationship between 2005 inequality and 2009 health displays a similar pattern, but with generally smaller correlations than the 2005 cross-sectional results. Further advances in the income inequality and health literature require new theoretical models to account for how inequalities in different parts of the income spectrum may influence population health in different ways.     

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.     

The neighborhood context of relative position, trust, and self-rated health

The relative position hypothesis proposes that an individual's relative position in a community or population influences their health because (1) unfavorable comparisons lead those with a lower position to experience negative emotions that cause stress and detrimentally impact health and well-being, and (2) individuals with different statuses are less likely to develop trust and cohesion with one another. These processes are important for individual health and also because their results may detract from community level social resources. Surprisingly little work has investigated this hypothesis within small units of analysis such as neighborhoods. In this research, logistic regression analyses were conducted on data from the Los Angeles Family and Neighborhood Survey to test the relative position hypothesis as it applies to distrust of neighbors and fair or poor self-rated health, and whether the relationship varies across neighborhood income inequality. Results indicate that relative position significantly predicts distrust, such that those with higher local position are more likely to distrust their comparatively lower income neighbors. Relative position was not significantly associated with self-rated health, but lack of trust of neighbors was significantly and positively associated with below average self-rated health. The effect of relative position did not vary across neighborhood income inequality for either outcome. Implications for theories of income inequality and health are discussed.     

Extending the income inequality hypothesis: Ecological results from the 2005 and 2009 Argentine National Risk Factor Surveys

Abstract

A consensus on income inequality as a social determinant of health is yet to be reached. In particular, we know little about the cross-sectional versus lagged effect of inequality and the robustness of the relationship to indicators that are sensitive to varying parts of the income spectrum. We test these issues with data from Argentina's 2005 and 2009 National Risk Factor Surveys. Inequality was operationalised at the provincial level with the Gini coefficient and the Generalised Entropy (GE) index. Population health was defined as the age-standardised percentage of adults with poor/fair self-rated health by province. Our cross-sectional results indicate a significant relationship between inequality (Gini) and poor health (r=0.58, p<0.01) in 2005. Using the GE index, a gradient pattern emerges in the correlation, and the r values increase as the index becomes sensitive to the top of the distribution. The relationship between 2005 inequality and 2009 health displays a similar pattern, but with generally smaller correlations than the 2005 cross-sectional results. Further advances in the income inequality and health literature require new theoretical models to account for how inequalities in different parts of the income spectrum may influence population health in different ways.     

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.     

Socioeconomic Inequalities in Self-Rated Health Among Middle-Aged and Older Adults

Despite increased attention to health disparities in the United States, few studies have examined the impact of socioeconomic inequalities on self-rated health over time. Using data from the Health and Retirement Study, this article investigates socioeconomic inequalities in self-rated health among middle-aged and older adults. The findings indicated that higher level of income, assets, and education, and having private health insurance predicted better self-rated health. In particular, increases in income or assets predicted slower decline in self-rated health. Interestingly, economic status had greater impact on females' decline in self-rated health. Blacks were less likely to suffer rapid decline in self-rated health than were whites. The findings led to the conclusion that health disparities should be understood as the interplay of socioeconomic status, gender, and race/ethnicity.