Income inequality and population health

Heterogeneity in health funding and disparities in health outcome: a comparison between high focus and non-high focus states in India

BACKGROUND

The Central Government of India introduced the National Health Mission (NHM) in 2005 to improve health outcomes by enhancing publicly financed (government) health expenditure and health infrastructure at the state level. This study aims to examine the effects of the state-level heterogeneity in publicly financed spending on health services on major health outcomes such as life expectancy, infant mortality rate, child mortality rate, the incidence of malaria, and immunization coverage (i.e., BCG, Polio, Measles, and Tetanus).

METHODS

This study investigates the relationships between publicly financed health expenditure and health outcomes by controlling income and infrastructure levels across 28 Indian States from 2005 to 2016. Along with all states, the empirical analysis has also been carried out for high-focus and non-high-focus states as per the NHM fund flow criteria. It has applied panel fixed-effects and random effects model wherever required based on the Hausman test.

RESULTS

The empirical results show that publicly financed health expenditure reduces infant mortality, child mortality, and malaria cases. At the same time, it improves life expectancy and immunization coverage in India. It also finds that the relationship between publicly financed health expenditure and health outcomes is weak, especially in the high-focus states.

CONCLUSIONS

Given the healthcare need for achieving desirable health outcomes, Indian States should enhance publicly financed expenditure on health services. This study augments essential guidance for implementing public health policies in developing countries.

Knowledge mapping of population health: A bibliometric analysis

In recent years, population health has aroused great interest, especially after the outbreak of Covid-19. The related research increases substantially year by year. There are many kinds of research about population health, but few scholars use the bibliometric method to discuss them. Motivated by keeping abreast of emerging trends and critical turns in population health, this study adopts the bibliometric method to analyze the development history and status quo of population health, providing a summary description for it. This study adopts CiteSpace to conduct a bibliometric analysis of publications related to population health in Web of Science from 1971 to 2021. The most productive countries, authors, institutions, and research direction changes are analyzed. The research results show that: First, the number of publications and citations related to population health increases for years, especially in Canada, the United States, the United Kingdom, and Australia. Second, the number of publications by different countries or institutions in population health varies greatly, and they cooperate closely. Third, the co-occurrence of disciplines and keywords in population health is displayed. Finally, this study reveals the primary research force, the major themes, significant milestones, landmarks, and the evolution of the hot fronts. In all, the comprehensive analysis of this study would provide some enlightenment for future research.

Socioeconomic status and ADL disability of the older adults: Cumulative health effects, social outcomes and impact mechanisms

INTRODUCTION

Socioeconomic status (SES) is one of the important indicators affecting individual's social participation and resource allocation, and it also plays an important role in the health shock of individuals. Faced by the trend of aging society, more and more nations across the world began to pay attention to prevent the risk of health shock of old adults.

METHODS

Based on the data of China Health and Retirement Longitudinal Study (CHARLS) in 2013, 2015 and 2018, this study uses path analysis and ologit model to empirically estimate the effects of SES and health shock on the activities of daily living (ADL) disability of old adults.

RESULTS

As a result, first, it was found that SES has significant impact on the disability of old adults. Specifically, economic conditions (income) plays dominant role. Economic status affects the risk of individual disability mainly through life security and health behavior. Secondly, SES significantly affecting health shock, with education and economic status showing remarkable impact, and there is an apparent group inequality. Furthermore, taking high education group as reference, the probability of good sight or hearing ability of the low education group was only 49.76% and 63.29% of the high education group, respectively, while the rates of no pain and severe illness were 155.50% and 54.69% of the high education group. At last, the estimation of path effect of SES on ADL disability indicates evident group inequality, with health shock plays critical mediating role.

CONCLUSIONS

SES is an important factor influencing residents' health shock, and health shocks like cerebral thrombosis and cerebral hemorrhage will indirectly lead to the risk of individual ADL disability. Furthermore, among the multi-dimensional indicators of SES, individual income and education are predominant factors affecting health shock and ADL disability, while occupation of pre-retirement have little impact.

Does the augmentation of monetary and non-monetary factors prerequisite for the improvement of health outcomes? Evidence from the Indian states

The present study was conducted in Indian states to examine the effect of monetary and non-monetary factors on Infant Mortality Rate (IMR) and Life Expectancy at Birth (LEB) by using the panel regression model. In addition, an attempt was also made to analysis the unequal pattern of health infrastructure and services across states over time with the help of a composite index on health infrastructure and services. It was found that the index value of the best performing state Chhattisgarh is more than fourth six times that of the worst performing state. The study also showed that, despite the higher level of average per capita public health expenditure and moderately better health infrastructure, the COVID 19 induced death rate was high in Punjab, Sikkim, Delhi and Goa. The panel regression results revealed that, an average increase of 1% in the monetary factor, public health expenditure to Gross State Domestic Product ratio (PHEGSDPR), would decrease the average of IMR by about 10%. Moreover, the elasticity of IMR with respect to non-monetary factor, health infrastructure and services per 0.1 million population (HISPLP), was negative and significant. Likewise, the explanatory variables, HISPLP and PHEGSDPR have a positive and significant effect on the LEB.

Understanding Trends in the Concentration of Infant Mortality Among Disadvantaged White and Black Mothers in the United States, 1983-2013: A Decomposition Analysis

The United States compares unfavorably with other high-income countries in infant mortality, which recent literature has attributed to the poor birth outcomes among disadvantaged (i.e., unmarried and less-educated) mothers. Describing and decomposing the trend of the concentration of infant mortality among disadvantaged mothers thus provides important clues for improving birth outcomes. We develop the infant mortality disadvantage index (IMDI) to measure such concentration. Using the 1983-2013 Birth Cohort Linked Birth and Infant Death data, we show that although the IMDI-as a measure of mortality inequality-was persistently higher for Blacks than Whites, the trends were different between the two groups. The IMDI declined for Black women; for White women, however, it increased in the 1980s, then plateaued until the early 2000s, and declined thereafter. We then use Das Gupta's decomposition method to assess the contribution of five demographic/social factors (age, education, marriage, fertility, and infant mortality) to the IMDI trend. Nonmarital fertility among women with less than 12 years of education contributed most to Whites' changing IMDI; for Blacks, a shrinking proportion of the less-educated group and declines in infant mortality among disadvantaged mothers contributed to their declining IMDI. These findings explicate links between population-level compositional changes and infant mortality inequality.

A "Swiss paradox" in the United States? Level of spatial aggregation changes the association between income inequality and morbidity for older Americans

Although a preponderance of research indicates that increased income inequality negatively impacts population health, several international studies found that a greater income inequality was associated with better population health when measured on a fine geographic level of aggregation. This finding is known as a “Swiss paradox”. To date, no studies have examined variability in the associations between income inequality and health outcomes by spatial aggregation level in the US. Therefore, this study examined associations between income inequality (Gini index, GI) and population health by geographic level using a large, nationally representative dataset of older adults. We geographically linked respondents’ county data from the 2012 Behavioral Risk Factor Surveillance System to 2012 American Community Survey data. Using generalized linear models, we estimated the association between GI decile on the state and county levels and five population health outcomes (diabetes, obesity, smoking, sedentary lifestyle and self-rated health), accounting for confounders and complex sampling. Although state-level GI was not significantly associated with obesity rates (b = − 0.245, 95% CI − 0.497, 0.008), there was a significant, negative association between county-level GI and obesity rates (b = − 0.416, 95% CI − 0.629, − 0.202). State-level GI also associated with an increased diabetes rate (b = 0.304, 95% CI 0.063, 0.546), but the association was not significant for county-level GI and diabetes rate (b = − 0.101, 95% CI − 0.305, 0.104). Associations between both county-level GI and state-level GI and current smoking status were also not significant. These findings show the associations between income inequality and health vary by spatial aggregation level and challenge the preponderance of evidence suggesting that income inequality is consistently associated with worse health. Further research is needed to understand the nuances behind these observed associations to design informed policies and programs designed to reduce socioeconomic health inequities among older adults.

Impact of Political Economy on Population Health: A Systematic Review of Reviews

Background. Although there is a large literature examining the relationship between a wide range of political economy exposures and health outcomes, the extent to which the different aspects of political economy influence health, and through which mechanisms and in what contexts, is only partially understood. The areas in which there are few high-quality studies are also unclear. Objectives. To systematically review the literature describing the impact of political economy on population health. Search Methods. We undertook a systematic review of reviews, searching MEDLINE, Embase, International Bibliography of the Social Sciences, ProQuest Public Health, Sociological Abstracts, Applied Social Sciences Index and Abstracts, EconLit, SocINDEX, Web of Science, and the gray literature via Google Scholar. Selection Criteria. We included studies that were a review of the literature. Relevant exposures were differences or changes in policy, law, or rules; economic conditions; institutions or social structures; or politics, power, or conflict. Relevant outcomes were any overall measure of population health such as self-assessed health, mortality, life expectancy, survival, morbidity, well-being, illness, ill health, and life span. Two authors independently reviewed all citations for relevance. Data Collection and Analysis. We undertook critical appraisal of all included reviews by using modified Assessing the Methodological Quality of Systematic Reviews (AMSTAR) criteria and then synthesized narratively giving greater weight to the higher-quality reviews. Main Results. From 4912 citations, we included 58 reviews. Both the quality of the reviews and the underlying studies within the reviews were variable. Social democratic welfare states, higher public spending, fair trade policies, extensions to compulsory education provision, microfinance initiatives in low-income countries, health and safety policy, improved access to health care, and high-quality affordable housing have positive impacts on population health. Neoliberal restructuring seems to be associated with increased health inequalities and higher income inequality with lower self-rated health and higher mortality. Authors' Conclusions. Politics, economics, and public policy are important determinants of population health. Countries with social democratic regimes, higher public spending, and lower income inequalities have populations with better health. There are substantial gaps in the synthesized evidence on the relationship between political economy and health, and there is a need for higher-quality reviews and empirical studies in this area. However, there is sufficient evidence in this review, if applied through policy and practice, to have marked beneficial health impacts. Public Health Implications. Policymakers should be aware that social democratic welfare state types, countries that spend more on public services, and countries with lower income inequalities have better self-rated health and lower mortality. Research funders and researchers should be aware that there remain substantial gaps in the available evidence base. One such area concerns the interrelationship between governance, polities, power, macroeconomic policy, public policy, and population health, including how these aspects of political economy generate social class processes and forms of discrimination that have a differential impact across social groups. This includes the influence of patterns of ownership (of land and capital) and tax policies. For some areas, there are many lower-quality reviews, which leave uncertainties in the relationship between political economy and population health, and a high-quality review is needed. There are also areas in which the available reviews have identified primary research gaps such as the impact of changes to housing policy, availability, and tenure.

The Relationship Between Public Sector Employment and Population Health: Evidence From the 1980s and Its Contemporary Implications

This article explores the relationship between public sector employment and population health both theoretically and quantitatively. First, we build a theoretical framework to situate public employment in the literature that explores the link between politics and health. We argue that public employment, as an instrument of pro-redistributive policies in both the labor market and the welfare state, improves equality and ultimately health. Second, based on a cross-country dataset from the 1980s, and by applying regression analysis and outlier identification techniques, we find that population health measured by life expectancy improves with the size of public employment. The association is stronger for countries with lower income and for women. When policymakers contemplate downsizing state enterprises and government functions, they should consider the health effect of public employment.

Physical Social Capital and Psychosocial Social Capital as Mediators Between Socio-economic Inequality and Expressions of Well-being and Health in Israeli Kibbutz Populations

A large number of studies show that degree of socio-economic inequality ‘within’ a social entity negatively determines levels of well-being and life expectancy, and is positively associated with morbidity and mortality. This relationship holds over and above the impact of average income level. This initially suggested model put forward a causal flow with mediating variables of ‘relative deprivation’ and followed it up with the expressions of ‘social capital’ in the social psychological sense. This article tests, besides these, the role of an additional (relatively little referred to) mediating set of variables between economic inequality and measures of well-being and health, namely levels of physical investments by society (physical social capital [PHSC]) for fulfilling its individual members’ needs. It is proposed that the higher the level of inequality, the lower would be a society’s investments in PHSC (such as in education, health services, job creation, ecology conservation, public transportation and the like) that contribute to health, well-being and survival. The proposition is tested out in two kinds of kibbutz communities: one, ‘traditional’ with strong adherence to social and economic equality among members; and another, ‘transformed’ kibbutzim, where salaries are differential and are based on position or occupation. The two groups of kibbutzim were roughly equated on size, years since settlement, political belonging, economic standing and geographical location. Findings show that the degree of inequality is associated with the level of both psychosocial social capital and PHSC, which in turn contribute independently and cumulatively to levels of peoples’ health and well-being. Transformed kibbutzim are seen as an expression of neoliberal ideology results in the negative effects on health and well-being of individuals and their communities.

Income inequality, life expectancy and cause-specific mortality in 43 European countries, 1987-2008: a fixed effects study

Whether income inequality is related to population health is still open to debate. We aimed to critically assess the relationship between income inequality and mortality in 43 European countries using comparable data between 1987 and 2008, controlling for time-invariant and time-variant country-level confounding factors. Annual data on income inequality, expressed as Gini index based on net household income, were extracted from the Standardizing the World Income Inequality Database. Data on life expectancy at birth and age-standardized mortality by cause of death were obtained from the Human Lifetable Database and the World Health Organization European Health for All Database. Data on infant mortality were obtained from the United Nations World Population Prospects Database. The relationships between income inequality and mortality indicators were studied using country fixed effects models, adjusted for time trends and country characteristics. Significant associations between income inequality and many mortality indicators were found in pooled cross-sectional regressions, indicating higher mortality in countries with larger income inequalities. Once the country fixed effects were added, all associations between income inequality and mortality indicators became insignificant, except for mortality from external causes and homicide among men, and cancers among women. The significant results for homicide and cancers disappeared after further adjustment for indicators of democracy, education, transition to national independence, armed conflicts, and economic freedom. Cross-sectional associations between income inequality and mortality seem to reflect the confounding effects of other country characteristics. In a European context, national levels of income inequality do not have an independent effect on mortality.

A Swiss paradox? Higher income inequality of municipalities is associated with lower mortality in Switzerland

It has long been surmised that income inequality within a society negatively affects public health. However, more recent studies suggest there is no association, especially when analyzing small areas. This study aimed to evaluate the effect of income inequality on mortality in Switzerland using the Gini index on municipality level. The study population included all individuals >30 years at the 2000 Swiss census (N = 4,689,545) living in 2,740 municipalities with 35.5 million person-years of follow-up and 456,211 deaths over follow-up. Cox proportional hazard regression models were adjusted for age, gender, marital status, nationality, urbanization, and language region. Results were reported as hazard ratios (HR) with 95% confidence intervals. The mean Gini index across all municipalities was 0.377 (standard deviation 0.062, range 0.202-0.785). Larger cities, high-income municipalities and tourist areas had higher Gini indices. Higher income inequality was consistently associated with lower mortality risk, except for death from external causes. Adjusting for sex, marital status, nationality, urbanization and language region only slightly attenuated effects. In fully adjusted models, hazards of all-cause mortality by increasing Gini index quintile were HR = 0.99 (0.98-1.00), HR = 0.98 (0.97-0.99), HR = 0.95 (0.94-0.96), HR = 0.91 (0.90-0.92) compared to the lowest quintile. The relationship of income inequality with mortality in Switzerland is contradictory to what has been found in other developed high-income countries. Our results challenge current beliefs about the effect of income inequality on mortality on small area level. Further investigation is required to expose the underlying relationship between income inequality and population health.

The social determinants of infant mortality and birth outcomes in Western developed nations: a cross-country systematic review

Infant mortality (IM) and birth outcomes, key population health indicators, have lifelong implications for individuals, and are unequally distributed globally. Even among western industrialized nations, striking cross-country and within-country patterns are evident. We sought to better understand these variations across and within the United States of America (USA) and Western Europe (WE), by conceptualizing a social determinants of IM/birth outcomes framework, and systematically reviewing the empirical literature on hypothesized social determinants (e.g., social policies, neighbourhood deprivation, individual socioeconomic status (SES)) and intermediary determinants (e.g., health behaviours). To date, the evidence suggests that income inequality and social policies (e.g., maternal leave policies) may help to explain cross-country variations in IM/birth outcomes. Within countries, the evidence also supports neighbourhood SES (USA, WE) and income inequality (USA) as social determinants. By contrast, within-country social cohesion/social capital has been underexplored. At the individual level, mixed associations have been found between individual SES, race/ethnicity, and selected intermediary factors (e.g., psychosocial factors) with IM/birth outcomes. Meanwhile, this review identifies several methodological gaps, including the underuse of prospective designs and the presence of residual confounding in a number of studies. Ultimately, addressing such gaps including through novel approaches to strengthen causal inference and implementing both health and non-health policies may reduce inequities in IM/birth outcomes across the western developed world.

Income inequality and health: lessons from a refugee residential assignment program

This paper examines the effect of income inequality on health for a group of particularly disadvantaged individuals: refugees. Our analysis draws on longitudinal hospitalization records coupled with a settlement policy where Swedish authorities assigned newly arrived refugees to their first area of residence. The policy was implemented in a way that provides a source of plausibly random variation in initial location. The results reveal no statistically significant effect of income inequality on the risk of being hospitalized. This finding holds also for most population subgroups and when separating between different types of diagnoses. Our estimates are precise enough to rule out large effects of income inequality on health.

Wealth Inequality and Health: A Political Economy Perspective

Despite a plethora of studies on income inequality and health, researchers have been unable to make any firm conclusions as a result of methodological and theoretical limitations. Within this body of research, there has been a call for studies of wealth inequality and health. Wealth is far more unequally distributed than income and is conceptually unique from income. This paper discusses the results of bivariate cross-sectional analyses of the relationship between wealth inequality (Gini coefficient) and population health (life expectancy and infant mortality) in 14 wealthy countries. The results confirm that wealth inequality is associated with poor population health. Both unweighted and weighted correlations between wealth inequality and health are strong and significant, even after controlling for a variety of potential aggregate-level confounders, including gross domestic product per capita, and after excluding the United States, the most unequal country. The results are strongest for female life expectancy and infant mortality. The author outlines potential pathways through which wealth inequality might affect health, using specific countries to illustrate. The article concludes with policy recommendations that could contribute to a more equitable distribution of wealth and, ultimately, decreased health disparities.

The role of geographic scale in testing the income inequality hypothesis as an explanation of health disparities

This study re-examined the role of geographic scale in measuring income inequality and testing the income inequality hypothesis (IIH) as an explanation of health disparities. We merged Behavioral Risk Factor Surveillance System (BRFSS) 2000 data with income inequality indices constructed at different geographic scales to test the association between income inequality and four different health indicators, i.e., self-assessed health status as a morbidity measure, vaccination against influenza as a measure of use of preventive healthcare, having any kind of health insurance as a measure of access, and obesity as a modifiable health risk factor measure. Multilevel models are used in our regression of the health indicators on measures of income inequalities and control variables. Our analysis suggests that because income inequality is a contextual variable, income inequalities measured at different geographic scales have different interpretations and relate to societal characteristics at different levels. Therefore, a rejection of the IIH at one level does not necessarily negate the possibility that income inequality affects health at another level. Assessment across a variety of scales is needed to have a comprehensive picture of the IIH in any given study. Empirical results also show that whether the IIH holds could depend on the sex group examined and the health indicator used, which implies different mechanisms of IIH exist for different sex groups and health indicators, in addition to the geographic scale. The role of geographic scale should be more rigorously considered in social determinants of health research.

Income inequality and population health in Islamic countries

OBJECTIVES

To undertake a fresh examination of the relationship between income inequality and population health for a group of Islamic countries using recent information derived from data resource sites from the World Bank and Islamic countries.

STUDY DESIGN

Cross-sectional data on different measures of income distribution (prosperity, health care, women's role and environment) and indicators of population health were used to illuminate this issue.

METHODS

The relationship between income inequality and population health for a group of Islamic countries was tested using recent information derived from data resource sites from the World Bank and Islamic countries. After consideration of previous studies, seven dependent variables were determined and tested in six equation formats.

RESULTS

According to the equations, the urban population percentage and gross domestic product are the most important significant variables that affect life expectancy and the infant mortality rate in Islamic countries. The income distribution coefficient, regardless of the type of measure, was almost insignificant in all equations.

CONCLUSIONS

In selected Islamic countries, income level has a positive effect on population health, but the level of income distribution is not significant. Among the other dependent variables (e.g. different measures of income distribution, health care, role of women and environment), only environment and education had significant effects. Most of the Islamic countries studied are considered to be poorly developed.

Social determinants of state variation in special education participation among preschoolers with developmental delays and disabilities

Children with developmental disabilities are at risk for secondary complications and lower academic performance, which contributes to lower health and well-being and may be ameliorated by access to special education services. This paper examines state variability in preschool special education participation among a United States population-based cohort with parent-reported developmental delays and disabilities. Analyses explore the extent to which observed variability can be explained by state socio-economic attributes and special education policy and funding. Rates of special education varied significantly across states and were highest in states with least income inequality and lowest in states with most income inequality. Place variation in preschool special education participation stems, in part, from child characteristics, but to a larger extent, from state socio-economic attributes.

Economic inequality and child stunting in Bangladesh and Kenya: an investigation of six hypotheses

Consistent with the increasing focus on issues of equity in developing countries, I extend the literature analyzing the relationship between economic inequality and individual health to the developing world. Using survey data from Bangladesh and Kenya with economic status measured by a wealth index and with three different geographic definitions of community, I analyze six competing hypotheses for how economic inequality may be related to stunting among children younger than 5 years old. I find little support for the predominant hypothesis that economic inequality as measured by a Gini index is an important predictor of individual health. Instead, I find that the difference between a household's wealth and the mean household wealth in the community is the measure of economic inequality that is most closely related to stunting in these countries. In particular, a 1 standard deviation increase in household wealth relative to the community mean is associated with a 30–32 percent decrease in the odds of stunting in Bangladesh and a 16–21 percent decrease in the odds of stunting in Kenya.

The impact of social status and risk behaviors on health status among elderly individuals in Korea

Little attention has been paid to health status issues among elderly individuals in Korea. The purpose of this secondary data analysis was to develop a better understanding of relationship between a number of socioeconomic factors and subjective social status affecting risk behaviors and health status among Korean elderly. Path analyses of 9,585 Korean elderly provided findings that those who reported a higher level of socioeconomic status were less likely to engage in risk behaviors and thus more likely to have better health status. Further, those who reported a higher level of socio-economic status were more likely to have a higher level of subjective social status and thus have better health status. Implications for policy and practice are discussed.

Income inequality and self-rated health status: evidence from the European Community Household Panel

We examine the effect of income inequality on individuals' self-rated health status in a pooled sample of 11 countries, using longitudinal data from the European Community Household Panel survey. Taking advantage of the longitudinal and cross-national nature of our data, and carefully modeling the self-reported health information, we avoid several of the pitfalls suffered by earlier studies on this topic. We calculate income inequality indices measured at two standard levels of geography (NUTS-0 and NUTS-1) and find consistent evidence that income inequality is negatively related to self-rated health status in the European Union for both men and women, particularly when measured at national level. However, despite its statistical significance, the magnitude of the impact of inequality on health is very small.

Socioeconomic instability and the availability of health resources: their effects on infant mortality rates in Macau from 1957-2006

AIM

To investigate the effects of socioeconomic instability and the availability of health resources on infant mortality rate.

BACKGROUND

In 1960, the infant mortality rate was 46.3 infants per 1000 live births in Macau but by 2006 it had declined to 2.7 infants per 1000 live births.

DESIGN

A retrospective design collecting yearly data for the Macau covering the period from 1957-2006. The infant mortality rate was the dependent variable and demographics, socioeconomic status and health resources are three main explanatory variables to determine the mortality rate.

METHODS

Regression modelling.

RESULTS

Results show that higher birth (Beta = 0.029, p = 0.004) and unemployment rates (Beta = -0.120, p = 0.036) and more public expenditure on health (Beta = -0.282, p < 0.001) were significantly more likely to reduce the infant mortality rate.

CONCLUSIONS

These results indicate that the socioeconomically disadvantaged are at a significantly higher risk for infant mortality. In contrast, more public expenditure on health resources significantly reduces the risk for infant mortality. This study provides further international evidence that suggests that improving aspects of the healthcare system may be one way to compensate for the negative effects of social inequalities on health outcomes.

RELEVANCE TO CLINICAL PRACTICE

The implication of these results is that more effort, particularly during economic downturns, should be put into removing the barriers that impede access to healthcare services and increasing preventive care for the population that currently has less access to health care in communities where there is a scarcity of medical resources. In addition, efforts should be made to expand and improve the coverage of prenatal and infant healthcare programmes to alleviate regional differences in the use of health care and improve the overall health status of infants in Macau.

Does government provision of healthcare explain the relationship between income inequality and low birthweight?

This paper estimates the relationship between state and county income inequality and low birthweight (LBW) in the U.S. It examines whether more unequal societies are also less healthy because such societies have lower investment in population health. The model includes an extensive list of community and individual controls and community fixed-effects. Results show that unequal states in fact have greater social investments, and absent these investments children born in such states would be more likely to be LBW. Using alternate measures of inequality reveals that income inequality in the upper tail of the income distribution is not related to LBW; but inequality in the lower tail of the income distribution is associated with increased LBW where the supply of healthcare mitigates the effect of income inequality. Consistent with prior findings, county income inequality is not significantly related to LBW.

What can alienation theory contribute to an understanding of social inequalities in health?

This article examines both the contribution and the limitations of research that has sought to develop a causal understanding of the psychosocial dimension of inequalities in health. The article seeks to revive interest in Marx's theory of alienation in developing the case for an alternative materialist conceptualization that is able to postulate the pathways from alienation as a psychosocial generative structure to social inequalities in health outcomes within late modern societies.

The Cost of Uncertain Life Span

A considerable amount of uncertainty surrounds the length of human life. The standard deviation in adult life span is about 15 years in the U.S., and theory and evidence suggest it is costly. I calibrate a utility-theoretic model of preferences over length of life and show that one fewer year in standard deviation is worth about half a mean life year. Differences in the standard deviation exacerbate cross-sectional differences in life expectancy between the U.S. and other industrialized countries, between rich and poor countries, and among poor countries. Accounting for the cost of life-span variance also appears to amplify recently discovered patterns of convergence in world average human well-being. This is partly for methodological reasons and partly because unconditional variance in human length of life, primarily the component due to infant mortality, has exhibited even more convergence than life expectancy.

Ecologic Studies Revisited

Ecologic studies use data aggregated over groups rather than data on individuals. Such studies are popular because they use existing databases and can offer large exposure variation if the data arise from broad geographical areas. Unfortunately, the aggregation of data that define ecologic studies results in an information loss that can lead to ecologic bias. Specifically, ecologic bias arises from the inability of ecologic data to characterize within-area variability in exposures and confounders. We describe in detail particular forms of ecologic bias so that their potential impact on any particular study may be assessed. The only way to overcome such bias, while avoiding uncheckable assumptions concerning the missing information, is to supplement the ecologic with individual-level information, and we outline a number of proposals that may achieve this aim.

Income inequality and population health: correlation and causality

A large literature now exists on the cross-national correlation between income inequality and population health, but existing studies suffer from sparse data, poor operationalization of income inequality, and the use of low-power statistical models. This paper sets out to estimate the ecological correlation between income inequality and indicators of population health in a very broad panel of countries, to demonstrate that this relationship is largely non-artifactual, and to test whether this relationship might be causal. Gini coefficients of national income inequality in 1970 and 1995 are correlated with life expectancy, infant mortality rates, and murder rates, controlling for national income per capita. In cross-sectional analyses, inequality is significantly correlated with life expectancy, infant mortality, and (inconsistently) the murder rate. The health correlations are shown to be not primarily due to the "convexity effect" of the non-linear relationship between individual income and individual health, which seems to account for no more than one-third of the relationship between inequality and health, and likely much less. Change in inequality 1970-1995 is significantly related to change in life expectancy and infant mortality, suggesting a causal relationship, but these correlations are not robust with respect to sample or controls. It can be concluded that there is a strong, consistent, statistically significant, non-artifactual correlation between national income inequality and population health, but though there is some evidence that this relationship is causal, the relative stability of income inequality over time in most countries makes causality difficult to test.

The Combination of Ecological and Case-Control Data

Ecological studies, in which data are available at the level of the group, rather than at the level of the individual, are susceptible to a range of biases due to their inability to characterize within-group variability in exposures and confounders. In order to overcome these biases, we propose a hybrid design in which ecological data are supplemented with a sample of individual-level case-control data. We develop the likelihood for this design and illustrate its benefits via simulation, both in bias reduction when compared to an ecological study, and in efficiency gains relative to a conventional case-control study. An interesting special case of the proposed design is the situation where ecological data are supplemented with case-only data. The design is illustrated using a dataset of county-specific lung cancer mortality rates in the state of Ohio from 1988.

Income productivity in China: on the role of health

This study provides empirical evidence regarding the income productivity of health human capital in China. We appeal to concepts from human capital theory to support a basic model that treats health as a form of human capital in the income production process. Our model examines the economic return at the household level from the health of its individual members. We estimate this with a longitudinal sample drawn from the China Health and Nutrition Survey (CHNS), allowing us to exploit "within" variation in health and income to address possible unobservables biasing estimates of the impact of health on income in the simple cross-sectional setting. Household income is strongly influenced by the health of its members, particularly in rural areas. These findings could have important implications for health and economic policy-making aimed at reducing the long-standing urban-rural economic gap and more comprehensively insuring the rural population against health and economic risk.

Socioeconomic determinants of infant mortality: a worldwide study of 152 low-, middle-, and high-income countries

BACKGROUND

To reach the Millennium Development Goals for health, influential international bodies advocate for more resources to be directed to the health sector, in particular medical treatment. Yet, health has many determinants beyond the health sector that are less evident than proximate predictors.

AIM

To assess the relative importance of major socioeconomic determinants of population health, measured as infant mortality rate (IMR), at country level.

METHODS

National-level data from 152 countries based on World Development Indicators 2003 were used for multivariate linear regression analyses of five socioeconomic predictors of IMR: public spending on health, GNI/capita, poverty rate, income equality (Gini index), and young female illiteracy rate. Analyses were performed on a global level and stratified for low-, middle-, and high-income countries.

RESULTS

In order of importance, GNI/capita, young female illiteracy, and income equality predicted 92% of the variation in national IMR whereas public spending on health and poverty rate were non-significant determinants when adjusted for confounding. In low-income countries, female illiteracy was more important than GNI/capita. Income equality (Gini index) was an independent predictor of IMR in middle-income countries only. In high-income countries none of these predictors was significant.

CONCLUSIONS

The relative importance of major health determinants varies between income levels, thus extrapolating health policies from high- to low-income countries is problematic. Since the size, per se, of public health spending does not independently predict health outcomes, functioning health systems are necessary to make health investments efficient. Potential health gains from improved female education and economic growth should be considered in low- and middle-income countries.

Inequality and mortality: long-run evidence from a panel of countries

We investigate whether changes in economic inequality affect mortality in rich countries. To answer this question we use a new source of data on income inequality: tax data on the share of pretax income going to the richest 10% of the population in Australia, Canada, France, Germany, Ireland, the Netherlands, New Zealand, Spain, Sweden, Switzerland, the UK, and the US between 1903 and 2003. Although this measure is not a good proxy for inequality within the bottom half of the income distribution, it is a good proxy for changes in the top half of the distribution and for the Gini coefficient. In the absence of country and year fixed effects, the income share of the top decile is negatively related to life expectancy and positively related to infant mortality. However, in our preferred fixed-effects specification these relationships are weak, statistically insignificant, and likely to change their sign. Nor do our data suggest that changes in the income share of the richest 10% affect homicide or suicide rates.

Infant mortality in Armenia, 1992-2003

Health system reforms have been taken in Armenia during a time of dramatic economic and fiscal distress. It is important to assess trends in health indicators and ascertain if the changes in socio-economic systems affected the health status of infants as the most vulnerable part of the population. We find that infant mortality has fallen during the period c. 1992-2003 in spite of the difficult economic circumstances because of health-care procedures that were introduced. Particular attention is paid to the underreporting of infants' death cases in the state registration system as well as to estimating the role of different factors influencing infant mortality in Armenia.

The effects of economic deprivation on psychological well-being among the working population of Switzerland

BACKGROUND

The association between poverty and mental health has been widely investigated. There is, however, limited evidence of mental health implications of working poverty, despite its representing a rapidly expanding segment of impoverished populations in many developed nations. In this study, we examined whether working poverty in Switzerland, a country with substantial recent growth among the working poor, was correlated with two dependent variables of interest: psychological health and unmet mental health need.

METHODS

This cross-sectional study used data drawn from the first 3 waves (1999-2001) of the Swiss Household Panel, a nationally representative sample of the permanent resident population of Switzerland. The study sample comprised 5453 subjects aged 20-59 years. We used Generalized Estimating Equation models to investigate the association between working poverty and psychological well-being; we applied logistic regression models to analyze the link between working poverty and unmet mental health need. Working poverty was represented by dummy variables indicating financial deficiency, restricted standard of living, or both conditions.

RESULTS

After controlling other factors, restricted standard of living was significantly (p < .001) negatively correlated with psychological well-being; it was also associated with approximately 50% increased risk of unmet mental health need (OR = 1.55; 95% CI 1.17-2.06).

CONCLUSION

The findings of this study contribute to our understanding of the potential psychological impact of material deprivation on working Swiss citizens. Such knowledge may aid in the design of community intervention programs to help reduce the individual and societal burdens of poverty in Switzerland.

Income inequality and population health: A review and explanation of the evidence

Whether or not the scale of a society's income inequality is a determinant of population health is still regarded as a controversial issue. We decided to review the evidence and see if we could find a consistent interpretation of both the positive and negative findings. We identified 168 analyses in 155 papers reporting research findings on the association between income distribution and population health, and classified them according to how far their findings supported the hypothesis that greater income differences are associated with lower standards of population health. Analyses in which all adjusted associations between greater income equality and higher standards of population health were statistically significant and positive were classified as "wholly supportive"; if none were significant and positive they were classified as "unsupportive"; and if some but not all were significant and supportive they were classified as "partially supportive". Of those classified as either wholly supportive or unsupportive, a large majority (70 per cent) suggest that health is less good in societies where income differences are bigger. There were substantial differences in the proportion of supportive findings according to whether inequality was measured in large or small areas. We suggest that the studies of income inequality are more supportive in large areas because in that context income inequality serves as a measure of the scale of social stratification, or how hierarchical a society is. We suggest three explanations for the unsupportive findings reported by a minority of studies. First, many studies measured inequality in areas too small to reflect the scale of social class differences in a society; second, a number of studies controlled for factors which, rather than being genuine confounders, are likely either to mediate between class and health or to be other reflections of the scale of social stratification; and third, the international relationship was temporarily lost (in all but the youngest age groups) during the decade from the mid-1980s when income differences were widening particularly rapidly in a number of countries. We finish by discussing possible objections to our interpretation of the findings.

Peripherality, income inequality, and life expectancy: revisiting the income inequality hypothesis

BACKGROUND

Recent criticisms of the income inequality and health hypothesis have stressed the lack of consistent significant evidence for the stronger effects of income inequality among rich countries. Despite such criticisms, little attention has been devoted to the income-based criteria underlying the stratification of countries into rich/poor groups and whether trade patterns and world-system role provide an alternative means of stratifying groups.

METHODS

To compare income-based and trade-based criteria, 107 countries were grouped into four typologies: (I) high/low income, (II) OECD membership/non-membership, (III) core/non-core, and (IV) non-periphery/periphery. Each typology was tested separately for significant differences in the effects of income inequality between groups. Separate group comparison tests and regression analyses were conducted for each typology using Rodgers (1979) specification of income, income inequality, and life expectancy. Interaction terms were introduced into Rodgers specification to test whether group classification moderated the effects of income inequality on health.

RESULTS

Results show that the effects of income inequality are stronger in the periphery than non-periphery (IV) (-0.76 vs -0.23; P < 0.05). An incremental F-test confirmed significant differences in the coefficient subsets between the two groups (F(2,101) = 6.31; P < 0.01).

CONCLUSIONS

Cross-national analyses of income inequality and population health have assumed (i) income differences between countries best capture global stratification and (ii) the negative effects of income inequality are stronger in high-income countries. However, present findings emphasize (i) the importance of measuring global stratification according to trading patterns and (ii) the strong, negative effects of income inequality on life expectancy among peripheral populations.

Distribution of education and population health: an ecological analysis of New York City neighborhoods

OBJECTIVES

We assessed the relationship between distribution of education and health indicators in a large urban area to determine if distribution of education may be a determinant of population health.

METHODS

We studied the association between distribution of education, measured with the education Gini coefficient, and rates of 8 health indicators in 59 neighborhoods in New York City.

RESULTS

In separate adjusted ecological models, neighborhoods with more poorly distributed education had better population health indicators that might plausibly be associated with short-term changes in the social environment (e.g., homicide and infant mortality rate); there was no association between education distribution and health indicators more likely to be associated with long-term accumulation of social and behavioral stressors (e.g., cardiovascular disease and chronic lung disease mortality rates). These findings were robust to measures of income and to adjustment for several potential confounders (e.g., gender and race/ethnicity).

CONCLUSIONS

The presence in a neighborhood of highly educated people may be salutary for all residents, independent of the potentially deleterious consequences of income maldistribution.

Further examination of the cross-country association between income inequality and population health

Several scholars have put forward the view that the estimates by Rodgers [(1979). Income and inequality as determinants of mortality: An international cross-section analysis. Population Studies, 33 (2), 343-351], Flegg [(1982). Inequality of income, illiteracy and medical care as determinants of infant mortality in underdeveloped countries. Population Studies, 36 (3), 441-458] and Waldmann [(1992). Income distribution and infant mortality. Quarterly Journal of Economics, 107 (4), 1283-1302] showing a negative cross-country association between income inequality and population health, cannot be replicated from recent data. In view of the importance of this matter, the present study further examines the issue from the most recent, and probably more accurate, data for the largest cross-country sample used in this line of research. The main conclusion is that the negative cross-country association between income inequality and good health, reported by Rodgers, Flegg, and Waldmann, is replicated very well. The different findings indicated by some scholars may have been due to their samples or the models being unusual. Therefore, the recent skepticism about the existence of such a negative association needs to be reconsidered. Several additional points are also noted. First, income inequality shows significance even after an index of ethnic heterogeneity is included. Second, ethnic heterogeneity itself has a negative association with population health. Third, income inequality retains significance in the presence of a measure of social capital. Fourth, however, the association between the measure of social capital and population health appears weak. Fifth, a simple analysis does not support the view that the positive association between income inequality and infant mortality in less developed countries (LDCs) may just be a reflection of the role of poverty. Finally, there is some support for the proposition that while income may be relatively more important for health in LDCs, the role of income inequality may be stronger in developed economies.

Some mechanisms linking economic inequality and infant mortality

We use data from the 1985, 1987 and 1991 United States Vital Statistics Linked Infant Birth and Death Records to assess the relationship between state-level economic inequality and an infant's probability of death. We find that economic inequality is associated with higher neonatal mortality even after we control mother's age and race and state characteristics that are likely to be associated with both inequality and infant death. Inequality is not associated with post-neonatal mortality. We assess three mechanisms that could link income inequality and infant deaths: non-linearity in the relationship between parental income and infant death, economic segregation, and state health care spending. Our evidence suggests that non-linearity in the relationship between family income and infant health accounts for little of the relationship between inequality and infant death. However inequality is associated with greater economic segregation, which in turn is associated with a higher probability of infant death. This effect is partially offset by the fact that inequality is also associated with state spending on health care, which is in turn associated with lower death rates. The increase in economic segregation increased infant deaths more than the increase in health care spending reduces them, so the net effect of economic inequality is to increase infant deaths especially in the first month after birth.

Contextual effect of income inequality on birth outcomes

BACKGROUND

Though associations between income inequality and birth outcome have been suggested, mechanisms underlying this relationship are not known. In this analysis, we examined the relationship between income inequality and preterm birth (PTB) and post-neonatal mortality (PNM) to explore two potential mechanisms-the proposed psychosocial stress and neo-material pathways.

METHODS

Data on singleton births from 1998 to 2000 were obtained from the CDC's National Center for Health Statistics' Linked Birth and Infant Death files. The Gini Index was utilized to measure income inequality and was divided into tertiles representing high, medium, and low county-level inequality. To determine the association between the birth outcomes and county income inequality and to account for clustering within counties, we employed generalized estimating equation (GEE) modelling.

RESULTS

PTB increased from 8.3% in counties with low income inequality to 10.0% in counties with high inequality. The Gini Index remained modestly associated with PTB after adjusting for individual level variables and mean county-level per capita income within the total population (AOR: 1.06; 95% CI 1.03-1.09) as well as within most of the racial/ethnic groups. PNM increased from 1.15 deaths per 1000 live births in low inequality counties to 1.32 in high-inequality counties. However, after adjustment, income inequality was only associated with PNM within the non-Hispanic black population (AOR: 1.20; 95% CI 1.03-1.39).

CONCLUSIONS

These findings may provide some support for the association between income inequality and PTB. Further research is required to elucidate the biological mechanisms of income inequality.

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.

Location, location, location: contextual and compositional health effects of social capital in British Columbia, Canada

After decades of epidemiological exploration into individual-level risk factors for ill health, a recent surge of interest in the health effects of socially patterned attributes of geographically defined 'places' has given the structural side of the agency-structure debate new prominence in population health research. Utilizing two original data sets, one pertaining to features of communities in British Columbia, Canada and the other to characteristics of individuals living in them, this article distinguishes the health effects of socially patterned attributes of communities, including the social capital of communities, from the health effects of characteristics of residents that contribute to social capital, e.g., trust and participation in voluntary associations. Results from multilevel analysis demonstrated that, of three different individual-level measures of health and well-being (and including measures of long-term limiting illness and self-rated health), only a measure of depressive symptoms had variability that could be reasonably attributed to the level of the community. The social capital of communities in the form of the availability of public spaces explained some of this variability, but in the direction contrary to expectations. Overall, location (community of residence) did little to explicate health inequalities in this context. The strongest predictors of health in multivariate and multilevel models were characteristics of individual survey respondents, namely, income, trust in politicians and governments, and trust in other members of the community. Breadth of participation in networks of voluntary association was not significantly related to health in multivariate models.

Making sense of social capital, health and policy

This paper summarizes current knowledge about social capital and its application to health policy. There is a consensus that social capital is a characteristic of social groups, rather than individuals, and is born of shared experience which fosters mutual trust and reciprocity. It is a collective resource that may accumulate over time and facilitates the accomplishment of objectives that would otherwise be unlikely. The theoretical articulation of social capital remains under-theorized, and its measurement is subject to considerable debate. Health researchers, searching for a pathway to explain the adverse health outcomes associated with income inequality, as well as to understand the results of multi-level analyses that demonstrate an independent etiological role for community of residence, may find social capital an attractive notion. Despite professions of interest, the utility of social capital for health policy formation remains problematic; however, as a theoretical paradigm for policy it may have particular appeal to exponents of the "Third Way".

Does income inequality harm health? New cross-national evidence

The provocative hypothesis that income inequality harms population health has sparked a large body of research, some of which has reported strong associations between income inequality and population health. Cross-national evidence is frequently cited in support of this important hypothesis, but the hypothesis remains controversial, and the cross-national work has been criticized for several methodological shortcomings. This study replicates previous work using a larger sample (692 observations from 115 countries over the 1947-1996 period), a wider range of statistical controls, and fixed-effects models that address heterogeneity bias. The relationship between health and inequality shrinks when controls are included. In fixed-effects models that capture unmeasured heterogeneity, the association between income inequality and health disappears. The null findings hold for two measures of income inequality: the Gini coefficient and the share of income received by the poorest quintile of the population. Analysis of a sample of wealthy countries also fails to support the hypothesis.