Is Income Inequality a Determinant of Population Health? Part 1. A Systematic Review

This article reviews 98 aggregate and multilevel studies examining the associations between income inequality and health. Overall, there seems to be little support for the idea that income inequality is a major, generalizable determinant of population health differences within or between rich countries. Income inequality may, however, directly influence some health outcomes, such as homicide in some contexts. The strongest evidence for direct health effects is among states in the United States, but even that is somewhat mixed. Despite little support for a direct effect of income inequality on health per se, reducing income inequality by raising the incomes of the most disadvantaged will improve their health, help reduce health inequalities, and generally improve population health.     

Income inequality and personality: Are less equal U.S. states less agreeable?

Richard Wilkinson's 'inequality hypothesis' describes the relationship between societal income inequality and population health in terms of the corrosive psychosocial effects of social hierarchy. An explicit component of this hypothesis is that inequality should lead individuals to become more competitive and self-focused, less friendly and altruistic. Together these traits are a close conceptual match to the opposing poles of the Big Five personality factor of Agreeableness; a widely used concept in the field of personality psychology. Based on this fact, we predicted that individuals living in more economically unequal U.S. states should be lower in Agreeableness than those living in more equal states. This hypothesis was tested in both ecological and multilevel analyses in the 50 states plus Washington DC, using a large Internet sample (N = 674,885). Consistent with predictions, ecological and multilevel models both showed a negative relationship between state level inequality and Agreeableness. These relationships were not explained by differences in average income, overall state socio-demographic composition or individual socio-demographic characteristics.     

Income Inequality and Mortality: Results From a Longitudinal Study of Older Residents of S?o Paulo,Brazil

Objectives. We determined whether community-level income inequality was associated with mortality among a cohort of older adults in São Paulo, Brazil.Methods. We analyzed the Health, Well-Being, and Aging (SABE) survey, a sample of community-dwelling older adults in São Paulo (2000–2007). We used survival analysis to examine the relationship between income inequality and risk for mortality among older individuals living in 49 districts of São Paulo.Results. Compared with individuals living in the most equal districts (lowest Gini quintile), rates of mortality were higher for those living in the second (adjusted hazard ratio [AHR] = 1.44, 95% confidence interval [CI] = 0.87, 2.41), third (AHR = 1.96, 95% CI = 1.20, 3.20), fourth (AHR = 1.34, 95% CI = 0.81, 2.20), and fifth quintile (AHR = 1.74, 95% CI = 1.10, 2.74). When we imputed missing data and used poststratification weights, the adjusted hazard ratios for quintiles 2 through 5 were 1.72 (95% CI = 1.13, 2.63), 1.41 (95% CI = 0.99, 2.05), 1.13 (95% = 0.75, 1.70) and 1.30 (95% CI = 0.90, 1.89), respectively.Conclusions. We did not find a dose–response relationship between area-level income inequality and mortality. Our findings could be consistent with either a threshold association of income inequality and mortality or little overall association.The distribution of incomes in society has been hypothesized to influence a population’s health status.1 Unequal societies tend to have a greater number of people in poverty who lack access to resources (e.g., health care and preventive measures) to achieve good health. Unequal conditions are also more apt to generate invidious social comparisons that lead to frustration and stress.2 A more contentious claim made by a growing number of researchers is that unequal societies are damaging to the health of everybody—the poor as well as the comfortably well-off.1 The putative mechanism for this effect is that income inequality erodes social solidarity. Reduced social cohesion in turn hampers a society’s ability to provide for many kinds of public goods, such as education, health care, and public health infrastructure.3 For example, when the wealthiest members of society begin to purchase education for their children through private means, or purchase their health care through private channels, there is a corresponding clamor to cut taxes on the rich (since they are no longer benefiting from subscribing to the publicly financed system). Falling tax revenues eventually lead to reduced social spending and declining quality of public institutions for the rest of society.Although the detailed mechanisms through which growing inequality harms society need to be sketched out more fully, considerable evidence has accumulated on the association between income inequality and the health of individuals. Multilevel analyses have demonstrated that there is an excess risk of morbidity and mortality associated with living in a society with high levels of income inequality, even after adjustment for the confounding effects of individual income.4 In other words, there appears to be a contextual influence of income inequality on the health of individuals, over and above their personal socioeconomic circumstances.Kondo et al.5 conducted a meta-analysis of all multilevel studies linking income distribution to health, which included 9 longitudinal studies and 18 cross-sectional studies. In the pooled analysis of the prospective cohort studies, the authors reported that each 0.05-unit increment in the Gini index (a summary measure of income inequality) was associated with a 7.8% excess risk of all-cause mortality. Nonetheless, data remain sparse from Latin America, where the degree of income inequality is among the highest in the world. Previous studies have looked at the association between income inequality and health in Chile6 and Brazil,7,8 but these have been cross-sectional or ecological. In addition, debate continues concerning what kinds of individuals are most vulnerable to the harmful effects of income inequality. In the US National Longitudinal Mortality Study,9 the association between higher income inequality and increased mortality risk was shown only among working-age individuals; among older individuals (> 65 years), there was no such association.We address 2 gaps in the literature. We provide a longitudinal test of the association between community-level income inequality and mortality in São Paulo, Brazil, a country with one of the highest degrees of income inequality in the world. We also provide a test of the income inequality hypothesis in a predominantly elderly population.     

Income and economic exclusion: do they measure the same concept?

Introduction  

In this paper, we create an index of economic exclusion based on validated questionnaires of economic hardship and material deprivation, and examine its association with health in Canada. The main study objective is to determine the extent to which income and this index of economic exclusion index are overlapping measurements of the same concept.     

Income and health: what is the nature of the relationship?

The aim of this article is to examine the relationship between income and morbidity, both before and after controlling for other socio-economic variables. We use data from the Health and Lifestyle Survey (first wave), a national sample survey of adults, aged 18 upwards, in England, Wales and Scotland, conducted in 1984-1985. In total, 9003 interviews were achieved. We examine the shape of the relationship between household equivalised income and height, waist-hip ratio, respiratory function (FEV1), malaise, limiting longterm illness. These indices of morbidity, both self-reported and measured, are approximately linearly related to the logarithm of income, in all except very high and low incomes (this means that increasing income is associated with better health, but that there are diminishing returns at higher levels of income). A doubling of income is associated with a similar effect on health, regardless of the point at which this occurs, providing this is within the central portion (10-90%) of the income distribution. The effect of income on the health measures is comparable to that of the other socio-economic variables in combination. The shape of the relationship found between income and health is compatible with worse health in countries with greater income inequality, without the need to postulate any direct effect of income inequality itself.     

Evidence into Policy and Practice? Measuring the Progress of U.S. and U.K. Policies to Tackle Disparities and Inequalities in U.S. and U.K. Health and Health Care

Health policy in both the United States and the United Kingdom has recently shifted toward a much greater concern with disparities and inequalities in health and health care. As evidence for these disparities and inequalities mounts, the different approaches in each country present specific challenges for policy and practice. These differences are most apparent in the mechanisms by which the progress of such policies is measured. This article compares the United States' and United Kingdom's strategies to gauge the challenges for policymakers in order to inform policy and practice. A cross-national comparison of selected measurement mechanisms identifies lessons for policy and practice in both countries.     

Income inequality and elderly self-rated health in São Paulo,Brazil

PurposeTo test the association between income inequality and elderly self-rated health and to propose a pathway to explain the relationship.MethodsWe analyzed a sample of 2143 older individuals (60 years of age and over) from 49 distritos of the Municipality of São Paulo, Brazil. Bayesian multilevel logistic models were performed with poor self-rated health as the outcome variable.ResultsIncome inequality (measured by the Gini coefficient) was found to be associated with poor self-rated health after controlling for age, sex, income and education (odds ratio, 1.19; 95% credible interval, 1.01–1.38). When the practice of physical exercise and homicide rate were added to the model, the Gini coefficient lost its statistical significance (P > .05). We fitted a structural equation model in which income inequality affects elderly health by a pathway mediated by violence and practice of physical exercise.ConclusionsThe health of older individuals may be highly susceptible to the socioeconomic environment of residence, specifically to the local distribution of income. We propose that this association may be mediated by fear of violence and lack of physical activity.     

Affluent-Born White Mother’s Descending Neighborhood Income and Infant Mortality: A Population-Based Study

Objectives To determine whether affluent-born White mother’s descending neighborhood income is associated with infant mortality rates (<?365 day, IMR). Methods Stratified and multilevel logistic regression analyses were completed on the Illinois transgenerational dataset of singleton births (1989–1991) to non-Latina White mothers (1956–1976) with an early-life residence in affluent neighborhoods (defined as the fourth quartile of income distribution). The breadth of descending neighborhood income was defined by mother’s neighborhood income at the time of delivery. Results Infants of White mothers (n?=?4890) who did not suffer descending neighborhood income by the time of delivery had a first-year mortality rate of 5.1/1,000. Infants of White mothers who experienced minor (n?=?5112), modest (n?=?2158), or extreme (n?=?339) descending neighborhood income had IMR of 6.5/1,000, 14.4/1,000, and 11.8/1,000, respectively; RR [95% CI]?=?1.3 [0.8, 2.1], 2.8 [1.7, 4.8], and 2.3 [0.8, 6.6], respectively. The incidence of young maternal age, inadequate prenatal care utilization, and cigarette smoking rose as descending neighborhood income increased, p?<?0.01. In multilevel logistic regression models, the adjusted (controlling for selected individual-level co-variates) OR [95% CI] of infant mortality for White women with an early-life residence in affluent neighborhoods who subsequently experienced minor or modest to extreme (versus absent) descending neighborhood income equaled 1.0 [0.6, 1.8] and 2.1 [1.1, 3.8] respectively. Conclusions White mother’s modest to extreme descending neighborhood income from early-life residence in affluent neighborhoods is associated with a twofold greater risk of infant mortality independent of selected biologic, medical, and behavioral characteristics.     

Income, income inequality and health: what can we learn from aggregate data?

It has been suggested that, especially in countries with high per capita income, there is an independent effect of income distribution on the health of individuals. One source of evidence in support of this relative income hypothesis is the analysis of aggregate cross-section data on population health, per capita income and income inequality. We examine the empirical robustness of cross-section analyses by using a new data set to replicate and extend the methodology in a frequently cited paper. The estimated relationship between income inequality and population health is not significant in any of our estimated models. We also argue there are serious conceptual difficulties in using aggregate cross-sections as a means of testing hypotheses about the effect of income, and its distribution, on the health of individuals.     

Inequality in health care utilization in Germany? Theoretical and empirical evidence for specialist consultation

Aim  

In view of increasing concern about a two-class system in the German health care sector, this study investigates the relevance of health insurance schemes and other socioeconomic characteristics to the level of specialist health care provision.     

Contemporaneous and long-term effects of children’s public health insurance expansions on Supplemental Security Income participation

This study explores the interplay between two important public programs for vulnerable children: Medicaid and the Supplemental Security Income (SSI) program. Children’s public health insurance eligibility increased dramatically during the late 1990s with the launch of the Children’s Health Insurance Program along with concurrent Medicaid expansions. We use a measure of simulated eligibility as an exogenous source of variation in Medicaid generosity to identify the effects of the eligibility expansions on SSI outcomes. Though increases in eligibility for public health insurance did not affect contemporaneous youth SSI applications or awards on average, expansions in coverage significantly decreased both applications and awards in states where SSI recipients did not automatically receive Medicaid. We attribute the difference in findings to the higher transactions costs associated with entering Medicaid via SSI in such states. In the long-term, increased public insurance eligibility during childhood reduces young adult SSI applications to some extent, consistent with recent findings that Medicaid coverage in youth improves adult health and economic outcomes.     

Does a Higher Income Have Positive Health Effects? Using the Earned Income Tax Credit to Explore the Income-Health Gradient

Context: The existence of a positive relationship between income and morbidity has been well documented in the literature. But it is unclear whether the relationship is positive because increased income allows individuals to purchase more health inputs that improve their health, because healthy individuals are more productive and thus can earn higher wages in the labor market, or because a third factor is improving health and increasing income. This article explores whether increases in income improve the health of the low‐income population. Methods: Because health status may affect income, this article uses an “instrumental variable” strategy that considers income variations over seventeen years of changes in the generosity of state and federal Earned Income Tax Credits (EITC, a measure that should be exogenous to health status). I measured health status using both the self‐reported health status and the functional limitations indicated on the Survey of Income and Program Participation (SIPP), as well as the self‐reported health status indicated on the March Current Population Survey (CPS). Findings: I found only limited support for the theory that the relationship between income and morbidity is derived from shifts in income. Although I did observe a correlation between income and self‐reported health, I found no evidence that increases in income significantly improve self‐reported health statuses. In addition, while increases in income appear to reduce the prevalence of hearing limitations when using corrective measures, these increases did not have a significant effect on most of the other functional limitations considered here. Conclusions: These findings suggest that the ability to improve short‐term health outcomes through public transfer payments may be limited. However, the lifetime effects on the health of people with higher incomes would still be a valuable avenue for future research.