Going upstream: Social inequality and children's health

This study explores the impact of income inequality on the health of children. We examine the direct effects of income inequality and the mediating effects of income inequality via poverty concentration at local levels. We use a multilevel study design incorporating individual level data from the 1988 Child Health Supplement to the National Health Interview Survey supplemented with aggregate data from the 1990 Census of Population STF3A economic/ demographic files. Measures of income inequality are constructed at the county level and poverty concentration at the county and neighbourhood level. Multiple indicators are used to examine child health including physiologic, functional status, and psychological measures and behavior and school problems. The association between income inequality and child health was examined using logistic regression models. Direct effects of income inequality were observed for school suspension and indirect effects for chronic conditions, learning disabilities, emotional and behavior problems, school suspension, health status and seeing a counsellor/psychiatrist. To assess whether income inequality works through challenging the integrity of local economic institutions, we also examine whether inequality and poverty concentration at the neighbourhood level or the larger administrative unit influence children's access to health insurance. Income inequality was found to exert both a direct and an indirect effect on children's health insurance status. These findings specifically provide evidence of the effects of income inequality on children's health, and more generally demonstrate that higher level contextual factors need to be incorporated into research in order to enhance our understanding of the determinants of children's health.     

The effect of income inequality on the health of selected US demographic groups

OBJECTIVES: This study assessed whether documented effects of income inequality on health are consistent across demographic subgroups of the US population. METHODS: Data from the National Health Interview Survey on White and Black non-Hispanics were used. Logistic regression models were estimated with SUDAAN software. Perceived health was the outcome variable. RESULTS: The results of the multivariate analysis, in which individual family income and county-level poverty rates were included, were not consistent with existing research. In the presence of covariates, the conditional effects of inequality were restricted to Whites aged 18-44 years in the 2 highest income inequality quartiles and middle-aged Whites in counties with the highest level of income inequality. The health of Blacks of all ages, elderly Whites, and middle-aged Whites outside of the areas of highest inequality was unaffected when controls for individual characteristics and county-level poverty were in place. CONCLUSIONS: For the United States, the independent and direct contribution of income inequality to the determination of self-perceived health net of individual income and county income levels is restricted to certain demographic groups.     

Using aggregate geographic data to proxy individual socioeconomic status: does size matter?

OBJECTIVES: This study assessed whether aggregate-level measures of socioeconomic status (SES) are less biased as proxies for individual-level measures if the unit of geographic aggregation is small in size and population. METHODS: National Health Interview Survey and census data were used to replicate analyses that identified the degree to which aggregate proxies of individual SES bias interpretations of the effects of SES on health. RESULTS: Ordinary least squares regressions on self-perceived health showed that the coefficients for income and education measured at the tract and block group levels were larger than those at the individual level but smaller than those estimated by Geronimus et al. at the zip code level. CONCLUSIONS: Researchers should be cautious about use of proxy measurement of individual SES even if proxies are calculated from small geographic units.     

The Health Effects of Rural-Urban Residence and Concentrated Poverty

This research quantifies the extent to which excess morbidity in rural areas is associated with individual characteristics, county income, and neighborhood poverty. Census geographic codes were assigned to people 25 to 64 years old (n = 176,930) from the National Health Interview Survey, 1989 to 1991, in order to link individuals to the U.S. Department of Agriculture's county urban-rural classification scheme and to 1990 county per capita income and poverty concentration in Census tracts. General health status and limitation of activity were analyzed in logistic and multinomial logit models. Residents of rural counties were at greater risk for health problems compared to residents of metropolitan and central core counties. In adjusted models, the health disadvantage of rural areas was partly explained by differences in population composition. The residual rural disadvantage was concentrated in people with less than a high school education. Tract poverty and county per capita income were also important independent predictors of morbidity. The results of this study suggest that special attention should be paid to improving education in disadvantaged places and to better understanding the ways in which economic growth and its benefits are distributed.     

Neighbourhood inequality, neighbourhood affluence and population health

While there is now considerable evidence that the neighbourhood income levels (poverty/affluence) exert an independent effect on health, there is little evidence that neighbourhood income inequality is consequential, net of individual-level socio-economic resources. We show that the usual explanation for the absence of an independent effect of neighbourhood inequality--the assumption of economic homogeneity at the neighbourhood level--cannot account for this result. The authors use hierarchical models that combine individual micro-data from Statistics Canada's 1996/97 National Population Health Survey (NPHS) with neighbourhood and city-level socio-economic characteristics from the 1996 Census of Canada to estimate the effects of neighbourhood affluence and income inequality on self-reported health status. The findings indicate that the negative "ecological" correlation between average neighbourhood health and neighbourhood income inequality is the result not only of compositional differences among individuals but also of contextual neighbourhood effects associated with low and high inequality neighbourhoods.     

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.     

Nonlinearity in Demographic and Behavioral Determinants of Morbidity

Objective. To examine nonlinearity of determinants of morbidity in the United States
Data Sources. A secondary analysis of data on individuals with dietary data from the Cancer Epidemiology Supplement and National Health Interview Survey (NHIS) 1987, a cross-sectional, stratified random sample of the U.S. population ( n =22,080).
Study Design. A statistical exploration using additive multiple regression models.
Methods. A Morbidity Index (0–30 points), derived from 1987 National Health Interview Survey data, combines number of conditions, hospitalizations, sick days, doctor visits, and degree of disability. Behavioral (health habits) variables were added to multivariate models containing demographic terms, with Morbidity Index and Self-assessed Health outcomes ( n =17,612). Tables and graphs compare models of morbidity with self-assessed health models, with and without behavioral terms. Graphs illustrate curvilinear relationships.
Principal Findings. Morbidity and health are associated nonlinearly with age, race, education, and income, as well as alcohol, diet change, vitamin supplement use, body mass index (BMI), marital status/living arrangement, and smoking. Diet change and supplement use, education, income, race/ethnicity, and age relate differently to self-assessed health status than to morbidity. Morbidity is strongly associated with income up to about $15,000 above poverty. Additional income predicts no further reduction in morbidity. Better health is strongly related to both higher income and education. After controlling for income, black race does not predict morbidity, but remains associated with lower self-assessed health.
Conclusions. Good health habits, as captured in these models, are associated with a 10–20-year delay in onset and progression of morbidity.     

Inequalities in Use of Health Services among Jews and Arabs in Israel

Objectives. To compare the levels of utilization of health services in Jews and Arabs taking into account differences in levels of socioeconomic status (SES) in a country with a National Health Insurance Law (NHIL).
Data Source/Study Setting. A cross-sectional National Health Interview Survey was carried out in Israel based on a random sample of telephone numbers as part of the EUROHIS project (WHO European Health Interview Survey 2003–2004).
Study Design. A random telephone survey included 9,352 interviews. Questions included use of health care services, health status, and socioeconomic variables.
Principal Findings. After adjusting for sex, age, income, education, marital status, and self-reported chronic diseases, Arabs more often reported visiting a family physician (odds ratio [OR]=1.56, 95 percent confidence interval [CI]=1.35–1.81) and less often reported visiting a specialist (OR=0.73, 95 percent CI=0.60–0.89) compared with Jews. In addition, the odds ratio for hospitalization was similar among Arabs and Jews (OR=1.16, 95 percent CI=0.97–1.38). SES was associated with utilization of health care services only in the Jewish population.
Conclusions. A different pattern of utilization of health care services was observed in Arabs and Jews. This was not explained by differences in socioeconomic levels. More research is needed regarding the distribution of services between Jews and Arabs.     

The independent contributions of socioeconomic status and health practices to health status

The objective of this study was to determine whether the much-repeated finding of a relationship between socioeconomic status and health status is explained by individuals' health practices. The investigation was carried out using data tapes from the 1977 Health Interview Survey in which a one-third subsample of adults was asked a series of questions related to the seven nonmedical health practices identified in the Alameda County Study. The group selected for analysis comprised 15,892 white, responding adults. With age controlled statistically, perceived health status was found to be associated with socioeconomic status, whether the indicator was educational level, family income, or occupation, and to number of positive health practices. When number of health practices, in addition to age and other socioeconomic indicators was controlled for, the association was still positive and significant. The finding of an independent contribution by socioeconomic status to health status emphasizes that individual health habits are not the only influence on health 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.     

State-level income inequality and individual mortality risk: a prospective, multilevel study

OBJECTIVES: Previous studies have linked state-level income inequality to mortality rates. However, it has been questioned whether the relationship is independent of individual-level income. The present study tests whether state-level income inequality is related to individual mortality risk, after adjustment for individual-level characteristics. METHODS: In this prospective, multilevel study design, the vital status of National Health Interview Survey (NHIS) respondents was ascertained by linkage to the National Death Index, with additional linkage of state-level data to individuals in the NHIS. The analysis included data for 546,888 persons, with 19,379 deaths over the 8-year follow-up period. The Gini coefficient was used as the measure of income inequality. RESULTS: Individuals living in high-income-inequality states were at increased risk of mortality (relative risk = 1.12; 95% confidence interval = 1.04, 1.19) compared with individuals living in low-income-inequality states. In stratified analyses, significant effects of state income inequality on mortality risk were found, primarily for near-poor Whites. CONCLUSIONS: State-level income inequality appears to exert a contextual effect on mortality risk, after income is adjusted for, providing further evidence that the distribution of income is important for health.     

The income-associated burden of disease in the United States

In this study, we estimate the total burden of disease associated with income in the US. We calculate the relationships between income and life expectancy, health-adjusted life expectancy, annual years of life lost (YLLs), and health adjusted life years (HALYs).We used the 2000 US Medical Expenditure Panel Survey to derive quality of life estimates by income and age, the 1990-1992 US National Health Interview Survey linked to National Death Index data through the end of 1995 to derive mortality risks by income and by age, and 2000 US mortality data from the National Center for Health Statistics to derive current mortality estimates for the US population by age-group. The bottom 80% of adult income earners' life expectancy is 4.3 years and 5.8 HALYs shorter relative to those in the top 20% of earnings. This translates into the loss of 11 million YLLs and 17.4 million HALYs each year. Compared with persons living above the poverty threshold, those living below the poverty threshold live an average of 3.2 million fewer HALYs per year-a difference of 8.5 HALYs per individual between age 18 and death. The income-associated burden of disease appears to be a leading cause of morbidity and mortality in the US.     

Rising U.S. income inequality and the changing gradient of socioeconomic status on physical functioning and activity limitations, 1984–2007

This study examines the interactive contextual effect of income inequality on health. Specifically, we hypothesize that income inequality will moderate the relationships between individual-level risk factors and health. Using National Health Interview Survey data 1984–2007 (n = 607,959) and U.S. Census data, this paper estimates the effect of the dramatic increase in income inequality in the U.S. over the past two decades on the gradient of socioeconomic status on two measures of health (i.e., physical functioning and activity limitations). Results indicate that increasing income inequality strengthens the protective effects of family income, employment, college education, and marriage on these two measures of health. In contrast, high school education's protective effect (relative to less than a high school education) weakens in the context of increasing income inequality. In addition, we find that increasing income inequality exacerbates men's disadvantages in physical functioning and activity limitations. These findings shed light on research about growing health disparities in the U.S. in the last several decades.     

New evidence on the relationship between income and health

Using data from the National Survey of Families and Households, the Survey of Income and Program Participation, and the National Health Interview Survey, I estimate the structural impact of income on the following measures of health: self-assessed health status, work and functional limitations, bed days, average daily consumption of alcohol, and scales of depressive symptoms and alcoholic behavior. Both ordinary and IV estimates indicate that increases in income significantly improve mental and physical health but increase the prevalence of alcohol consumption. Cost-benefit analyses of government policies that may reduce disposable income should take into account potential effects on morbidity.     

Income-related health inequalities in France in 2004: Decomposition and explanations

BackgroundThis analysis supplements existing work on social health inequalities at two levels: the measurement of health and the measurement of inequalities. Firstly, individual health status was measured using a subjective health indicator corrected within a promising cardinalisation method which had not yet been carried out on French data. Secondly, this study used an innovative methodology to measure income-related health inequalities, to understand the relationships between income, income inequality, various social determinants, and health.MethodsThe analysis was based on a sample of working-age adults from the 2004 Health and Health Insurance Survey. The methodology used in the study measures the total income-related health inequality using the concentration index. This index is based on a linear model explaining health according to several individual characteristics, such as age, sex, and various socioeconomic characteristics. The method thus takes into account both the causal relationships between the various explicative factors introduced in the model and their relationship with health. Furthermore, it concretely measures the contribution of the social determinants to income-related health inequalities.ResultsThe results show an income-related health inequality favouring individuals with a higher income. Moreover, income level, supplementary private health insurance, education level, and social class account for the main contributions to inequality. Therefore, the decomposition method highlights population groups that policies should target.ConclusionThe study suggests that reducing income inequality is not sufficient to lower income-related health inequalities in France in 2004 and needs to be supplemented with the reduction of the relationship between income and health and the reduction of income inequality over socioeconomic status.     

Les inégalités de santé selon le revenu en France en 2004 : décomposition et explications

BackgroundThis analysis supplements existing work on social health inequalities at two levels: the measurement of health and the measurement of inequalities. Firstly, individual health status was measured using a subjective health indicator corrected within a promising cardinalisation method which had not yet been carried out on French data. Secondly, this study used an innovative methodology to measure income-related health inequalities, to understand the relationships between income, income inequality, various social determinants, and health.MethodsThe analysis was based on a sample of working-age adults from the 2004 Health and Health Insurance Survey. The methodology used in the study measures the total income-related health inequality using the concentration index. This index is based on a linear model explaining health according to several individual characteristics, such as age, sex, and various socioeconomic characteristics. The method thus takes into account both the causal relationships between the various explicative factors introduced in the model and their relationship with health. Furthermore, it concretely measures the contribution of the social determinants to income-related health inequalities.ResultsThe results show an income-related health inequality favouring individuals with a higher income. Moreover, income level, supplementary private health insurance, education level, and social class account for the main contributions to inequality. Therefore, the decomposition method highlights population groups that policies should target.ConclusionThe study suggests that reducing income inequality is not sufficient to lower income-related health inequalities in France in 2004 and needs to be supplemented with the reduction of the relationship between income and health and the reduction of income inequality over socioeconomic status.     

A framework for testing the equality between the health concentration curve and the 45‐degree line

The health concentration curve is the standard graphical tool to depict socioeconomic health inequality in the literature on health inequality. This paper shows that testing for the absence of socioeconomic health inequality is equivalent to testing if the conditional expectation of health on income is a constant function that is equal to average health status. In consequence, any test for parametric specification of a regression function can be used to test for the absence of socioeconomic health inequality (subject to regularity conditions). Furthermore, this paper illustrates how to test for this equality using a test for parametric regression functional form and applies it to health‐related behaviors from the National Health Survey 2014.     

Independent and joint contributions of economic,social and physical environmental characteristics to mortality in the Detroit Metropolitan Area: A study of cumulative effects and pathways

ObjectivePrevious studies have demonstrated associations between race-based residential segregation, neighborhood socioeconomic and physical environmental characteristics, and mortality. Relatively few studies have examined independent and joint effects of these multiple neighborhood characteristics and mortality, including potential mediating pathways. In this study we examine the extent to which associations between race-based residential segregation and all-cause mortality may be explained by multiple socioeconomic indicators and exposure to air pollutants.MethodsDrawing on data from multiple sources, we assessed bivariate associations between race-based residential segregation (operationalized as percent non-Hispanic Black), education (percent with graduate equivalency degree), poverty (percent below poverty), income inequality (GINI coefficient) and air pollution (ambient PM2.5) and age adjusted all-cause, all race mortality (henceforth all cause mortality) at the census tract level in the Detroit Metropolitan Area. We used inequality curves to assess the (in)equitable distribution of economic and environmental characteristics by census tract racial composition. Finally, we used generalized estimating equations (GEE) to examine independent and joint associations among percent NHB, education, income inequality, and air pollution to all-cause mortality, and test for mediating effects.ResultsBivariate associations between racial composition, education, poverty, income inequality, PM2.5 and all-cause mortality were statistically significant. Census tracts with higher concentrations of NHB residents had significantly lower educational attainment, higher poverty, and greater exposure to PM2.5. In multivariate models, education, income inequality and PM2.5 fully attenuated associations between racial composition and all-cause mortality.ConclusionsResults are consistent with the hypothesis that race-based residential segregation is associated with heightened all-cause mortality, and that those effects are mediated by education, income inequality, and exposure to air pollution at the census tract level. Public health and cross-sector interventions to eliminate race-based residential segregation or to eliminate the maldistribution of educational and economic resources, and environmental exposures, across census tracts could substantially reduce regional inequities in all-cause mortality.     

Access to ambulatory care for poor persons.

Studies conducted during the 1970s have reported conflicting results concerning whether differences in use of physician services between poor and nonpoor persons have been eliminated. Using a sample of 92,737 persons from the 1982 National Health Interview Survey and a refined analytic method, this study reexamines utilization of ambulatory care services by persons above and below the poverty level. Before adjusting for health status, no differences were apparent in rates of physician contacts for persons above and below the poverty level. After adjusting for health status, persons below poverty were shown to have significantly fewer physician contacts than persons above poverty. Multivariate analysis revealed that Medicaid coverage can effectively counter the depressing effects of poverty on use of physician services. However, only 34 percent of the noninstitutionalized population below poverty level had Medicaid coverage in 1982. Public policy implications concerning Medicaid eligibility criteria are discussed.     

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.