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.     

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.     

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.     

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.     

An investigation of the longitudinal relationship between neighbourhood income inequality and individual self-rated health in England

There are mixed findings on whether neighbourhood income inequality leads to better self-rated health (SRH) or not. This study considers two hypotheses: individuals living in more unequal neighbourhoods have better SRH and the level of neighbourhood income inequality and its impact on SRH is moderated by household and neighbourhood level income related variables. Data from Waves 8–10 of the UK Household Longitudinal Study for respondents living in England at wave 8 were used. Neighbourhood income inequality was measured using Gini coefficients of household income from the Pay As You Earn and benefits systems for Lower Super Output Areas. Longitudinal ordinal multilevel models predicted self-rated health in 2016–18, 2017–19 and 2019-20 by income inequality and its interaction with household income, neighbourhood median income and neighbourhood deprivation, conditional on individual educational attainment, age, sex, ethnic group, years lived in current residence, region of residence and study wave. There were 24,889 respondents analysed over three waves. SRH was worse for those living in more income equal neighbourhoods. There was no indication that neighbourhood inequality was moderated by household income, neighbourhood median income or neighbourhood deprivation. These findings are in line with the balance of existing evidence and support policy interventions that aim to create mixed communities for the purpose of improving population health.     

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.     

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.     

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.     

Income inequality, primary care, and health indicators

BACKGROUND: The significant association of income inequality with a variety of health indicators is receiving increasing attention. There has also been increasing evidence of a link between primary care and improved health status. We examined the joint relationship between income inequality, availability of primary care, and various health indicators to determine whether primary care has an impact on health indicators by modifying the adverse effect of income inequality. METHODS: Our ecologic study used the US states as the units of analysis. In analyzing the data, we looked at the associations among income inequality, primary care, specialty care, smoking, and health indicators, using Pearson's correlation coefficients for intercorrelations and the adjusted multiple regression procedure. To examine the effect of inequality and primary care on health outcome indicators, we conducted path analyses according to a causal model in which inequality affects health both directly and indirectly through its impact on primary care. RESULTS: Our study indicates that both primary care and income inequality exerted a strong and significant direct influence on life expectancy and total mortality (P <.01). Primary care also exerted a significant direct influence on stroke and postneonatal mortality (P <.01). Although levels of smoking are also influential, the effect of income inequality and primary care persists after controlling for smoking. Primary care serves as one pathway through which income inequality influences population-level mortality and at least some other health outcome indicators. CONCLUSIONS: It appears possible that a primary care orientation may, in part, overcome the severe adverse effects on health of income inequalities.     

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.     

Primary care,self-rated health,and reductions in social disparities in health

OBJECTIVE: To examine the extent to which good primary-care experience attenuates the adverse association of income inequality with self-reported health. DATA SOURCES: Data for the study were drawn from the Robert Wood Johnson Foundation sponsored 1996-1997 Community Tracking Study (CTS) Household Survey and state indicators of income inequality and primary care. STUDY DESIGN: Cross-sectional, mixed-level analysis on individuals with a primary-care physician as their usual source of care. The analyses were weighted to represent the civilian noninstitutionalized population of the continental United States. DATA COLLECTION/EXTRACTION METHODS: Principal component factor analysis was used to explore the stricture of the primary-care indicators and examine their construct validity. Income inequality for the state in which the community is located was measured by the Gini coefficient, calculated using income distribution data from the 1996 current population survey. Stratified analyses compared proportion of individuals reporting had health and feeling depressed with those with good and bad primary-care experiences for each of the four income-inequality strata. A set of logistic regressions were performed to examine the relation between primary-care experience, income inequality, and self-rated health. PRINCIPAL FINDINGS: Good primary-care experience, in particular enhanced accessibility and continuity, was associated with better self-reported health both generally and mentally. Good primary-care experience was able to reduce the adverse association of income inequality with general health although not with mental health, and was especially beneficial in areas with highest income inequality. Socioeconomic status attenuated, but did not eliminate, the effect of primary-care experience on health. In conclusion, good primary-care experience is associated not only with improved self-rated overall and mental health but also with reductions in disparities between more- and less-disadvantaged communities in ratings of overall health.     

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.     

Self-rated health and associated factors in adults: a population survey in Rio Branco, Acre State, Brazil, 2007-2008

The subjective concept of health included in the self-rated health process allows identifying factors associated with good self-rated health in populations. This cross-sectional population-based study in 2007-2008 focused on self-rated health and associated factors among adults (n = 1,516) in Rio Branco, Acre State, Brazil. The multivariate analysis used Poisson regression, with fair/poor self-rated health as the dependent variable. Differences in gender, age group, level of schooling, and income negatively affected individuals' self-rated health. After adjusting for age, gender, and self-reported illness, the estimated risks for fair/poor health were higher for the unemployed, obese, and those with some self-reported illness. The results suggest that differences in living conditions for adults in Rio Branco are associated with precarious self-rated 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.     

Socioeconomic factors, material inequalities, and perceived control in self-rated health: cross-sectional data from seven post-communist countries

This study examined the association between perceived control and several socioeconomic variables and self-rated health in seven post-communist countries (Russia, Estonia, Lithuania, Latvia, Hungary, Poland, Czech Republic). Questionnaire interviews were used to collect data on self-rated health in the last 12 months, education, marital status, perceived control based on nine questions, and material deprivation based on availability of food, clothing and heating. For each population, two ecological measures of material inequalities were available: an inequality score estimated from the survey data as the distance between the 90th and 10th percentiles of material deprivation, and Gini coefficient from published sources. Data on 5330 men and women aged 20-60 were analysed. Prevalence of poor health (worse than average) varied between 8% in Czechs and 19% in Hungarians. The age-sex-adjusted odds ratio for university vs primary education was 0.36 (0.26-0.49); odds ratios per 1 standard deviation increase in perceived control and in material deprivation were 0.58 (95% CI 0.48-0.69) and 1.51 (1.40-1.63), respectively. The odds ratio for an increase in inequality equivalent to the difference between the most and the least unequal populations was 1.49 (0.88-2.52) using the material inequality score and 1.41 (0.91-2.20) using the Gini coefficient. No indication of an effect of either inequality measure was seen after adjustment for individuals' deprivation or perceived control. The results suggest that, as in western populations, education and material deprivation are strongly related to self-rated health. Perceived control appeared statistically to mediate some of the effects of material deprivation. The non-significant effects of both ecological measures of inequality were eliminated by controlling for individuals' characteristics.     

An exploratory multilevel analysis of income,income inequality and self-rated health of the elderly in China

In the last three decades, China has experienced rapid economic development and growing economic inequality, such that economic disparities between rural and urban areas, as well as coastal and interior areas have deepened. Since the late 1990s China has also experienced an ageing population which has attracted attention to the wellbeing of the rapidly growing number of elderly. This research aims to characterise province differences in health and to explore the effects of individual income and economic disparity in the form of income inequality on health outcomes of the elderly. The study is based on the Chinese Longitudinal Healthy Longevity Survey data collected in 2008 for 23 provinces. Multilevel logistic models are employed to investigate the relationship between income, income inequality and self-rated health for the elderly using both individual and province-level variables. Results are presented as relative odds ratios, and for province differentials as Median Odds Ratios. The analysis is deliberately exploratory so as to find evidence of income effects if they exist and particular attention is placed on how province-level inequality (contemporaneous and lagged) may moderate individual relationships. The results show that the health of the elderly is not only affected by individual income (the odds of poor health are 3 times greater for the elderly with the lowest income compared to those at the upper quartile) but also by a small main effect for province-level income inequality (odds ratio of 1.019). There are significant cross-level interactions such that where inequality is high there are greater differences between those with and without formal education, and between men and women with the latter experiencing poorer 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.     

Social capital and self-rated health: a contextual analysis.

OBJECTIVES: Social capital consists of features of social organization--such as trust between citizens, norms of reciprocity, and group membership--that facilitate collective action. This article reports a contextual analysis of social capital and individual self-rated health, with adjustment for individual household income, health behaviors, and other covariates. METHODS: Self-rated health ("Is your overall health excellent, very good, good, fair, or poor?") was assessed among 167,259 individuals residing in 39 US states, sampled by the Behavioral Risk Factor Surveillance System. Social capital indicators, aggregated to the state level, were obtained from the General Social Surveys. RESULTS: Individual-level factors (e.g., low income, low education, smoking) were strongly associated with self-rated poor health. However, even after adjustment for these proximal variables, a contextual effect of low social capital on risk of self-rated poor health was found. For example, the odds ratio for fair or poor health associated with living in areas with the lowest levels of social trust was 1.41 (95% confidence interval = 1.33, 1.50) compared with living in high-trust states. CONCLUSIONS: These results extend previous findings on the health advantages stemming from social capital.     

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.