Income inequality and mortality: a multilevel prospective study of 521 248 individuals in 50 US states

Causal Assessment of Income Inequality on Self-Rated Health and All-Cause Mortality: A Systematic Review and Meta-Analysis

Policy Points Income is thought to impact a broad range of health outcomes. However, whether income inequality (how unequal the distribution of income is in a population) has an additional impact on health is extensively debated. Studies that use multilevel data, which have recently increased in popularity, are necessary to separate the contextual effects of income inequality on health from the effects of individual income on health. Our systematic review found only small associations between income inequality and poor self-rated health and all-cause mortality. The available evidence does not suggest causality, although it remains methodologically flawed and limited, with very few studies using natural experimental approaches or examining income inequality at the national level.

CONTEXT

Whether income inequality has a direct effect on health or is only associated because of the effect of individual income has long been debated. We aimed to understand the association between income inequality and self-rated health (SRH) and all-cause mortality (mortality) and assess if these relationships are likely to be causal.

METHODS

We searched Medline, ISI Web of Science, Embase, and EconLit (PROSPERO: CRD42021252791) for studies considering income inequality and SRH or mortality using multilevel data and adjusting for individual-level socioeconomic position. We calculated pooled odds ratios (ORs) for poor SRH and relative risk ratios (RRs) for mortality from random-effects meta-analyses. We critically appraised included studies using the Risk of Bias in Nonrandomized Studies - of Interventions tool. We assessed certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework and causality using Bradford Hill (BH) viewpoints.

FINDINGS

The primary meta-analyses included 2,916,576 participants in 38 cross-sectional studies assessing SRH and 10,727,470 participants in 14 cohort studies of mortality. Per 0.05-unit increase in the Gini coefficient, a measure of income inequality, the ORs and RRs (95% confidence intervals) for SRH and mortality were 1.06 (1.03-1.08) and 1.02 (1.00-1.04), respectively. A total of 63.2% of SRH and 50.0% of mortality studies were at serious risk of bias (RoB), resulting in very low and low certainty ratings, respectively. For SRH and mortality, we did not identify relevant evidence to assess the specificity or, for SRH only, the experiment BH viewpoints; evidence for strength of association and dose-response gradient was inconclusive because of the high RoB; we found evidence in support of temporality and plausibility.

CONCLUSIONS

Increased income inequality is only marginally associated with SRH and mortality, but the current evidence base is too methodologically limited to support a causal relationship. To address the gaps we identified, future research should focus on income inequality measured at the national level and addressing confounding with natural experiment approaches.

Association Between Socioeconomic Status and Prevalence of Cardio-Metabolic Risk Factors: A Cross-Sectional Study on Residents in North China

Studies have found associations between cardio-metabolic disorders and socioeconomic status (SES) in developed areas. However, little epidemiological data are available on residents of less developed areas in North China. A cross-sectional study that consisted of 2,650 adults randomly selected from local residents was conducted on a developing province, Hebei. SES was assessed in terms of education, personal income per year, and occupation. The association between SES and metabolic syndrome (MetS) was determined by multivariate logistic regression. The weighted prevalence of MetS was 26.8% among residents of Hebei province. The lower prevalence of MetS and abdominal obesity was associated with increase in SES groups. After adjustments regarding age, sex, body mass index, living area, smoking, salt intake, and family history of diabetes, odds ratio (OR) for elevated blood pressure (BP) of individuals with higher SES level was 0.71 [95% confidence interval (CI): 0.542–0.921] compared with those with lower SES level. Cardio-metabolic risk factors were commonly identified among residents of Hebei province in north China and were associated with SES conditions. This study indicated that from a public health perspective, more attention should be paid to screening of cardio-metabolic disorders in less developed areas.

Socioeconomic Classes among Oldest-Old Women in South Korea: A Latent Class Analysis

Oldest-old women are known to live at the intersection of multiple socioeconomic disadvantages in South Korean society. This study classified oldest-old Korean women into several socioeconomically homogeneous classes based on various socioeconomic status (SES) risks and compared health characteristics among the identified classes. This cross-sectional study utilized the 2019 Korean Community Health Survey, including data from 11,053 women (≥80 years). Latent class analysis determined the number of underlying socioeconomic classes based on nine selected SES variables. Four distinct socioeconomic classes were identified: “Urban, living alone, recipient of NBLSS, moderate education, leisure activity” (Class 1), “Rural, traditional house, living with others, not financially deprived, low education, employed” (Class 2), “Urban, living with family, financially affluent, not employed, no barriers to healthcare” (Class 3), “Rural, traditional house, living alone, financially deprived, uneducated, employed, barriers to healthcare” (Class 4). Depressive symptoms, subjective stress, and the prevalence of sleep disorder and diabetes were higher in Class 1 compared to other classes. Health-related quality of life, perceived health, and self-rated oral health were the poorest in Class 4. Class 3 reported the best health status. Understanding the intersecting SES risk factors in this group can aid in developing targeted interventions.

Inequality in Place: Effects of Exposure to Neighborhood-Level Economic Inequality on Mortality

This study contributes to the debate on whether income inequality is harmful for health by addressing several analytical weaknesses of previous studies. Using the Panel Study of Income Dynamics in combination with tract-level measures of income inequality in the United States, we estimate the effects of differential exposure to income inequality during three decades of the life course on mortality. Our study is among the first to consider the implications of income inequality within U.S. tracts for mortality using longitudinal and individual-level data. In addition, we improve upon prior work by accounting for the dynamic relationship between local areas and individuals' health, using marginal structural models to account for changes in exposure to local income inequality. In contrast to other studies that found no significant relation between income inequality and mortality, we find that recent exposure to higher local inequality predicts higher relative risk of mortality among individuals at ages 45 or older.

Temperature-mortality relationship in North Carolina, USA: Regional and urban-rural differences

BACKGROUND

Health disparities exist between urban and rural populations, yet research on rural-urban disparities in temperature-mortality relationships is limited. As inequality in the United States increases, understanding urban-rural and regional differences in the temperature-mortality association is crucial.

OBJECTIVE

We examined regional and urban-rural differences of the temperature-mortality association in North Carolina (NC), USA, and investigated potential effect modifiers.

METHODS

We applied time-series models allowing nonlinear temperature-mortality associations for 17 years (2000-2016) to generate heat and cold county-specific estimates. We used second-stage analysis to quantify the overall effects. We also explored potential effect modifiers (e.g. social associations, greenness) using stratified analysis. The analysis considered relative effects (comparing risks at 99th to 90th temperature percentiles based on county-specific temperature distributions for heat, and 1st to 10th percentiles for cold) and absolute effects (comparing risks at specific temperatures).

RESULTS

We found null effects for heat-related mortality (relative effect: 1.001 (95% CI: 0.995-1.007)). Overall cold-mortality risk for relative effects was 1.019 (1.015-1.023). All three regions had statistically significant cold-related mortality risks for relative and absolute effects (relative effect: 1.019 (1.010-1.027) for Coastal Plains, 1.021 (1.015-1.027) for Piedmont, 1.014 (1.006-1.023) for Mountains). The heat mortality risk was not statistically significant, whereas the cold mortality risk was statistically significant, showing higher cold-mortality risks in urban areas than rural areas (relative effect for heat: 1.006 (0.997-1.016) for urban, 1.002 (0.988-1.017) for rural areas; relative effect for cold: 1.023 (1.017-1.030) for urban, 1.012 (1.001-1.023) for rural areas). Findings are suggestive of higher relative cold risks in counties with the less social association, higher population density, less green-space, higher PM_2.5, lower education level, higher residential segregation, higher income inequality, and higher income (e.g., Ratio of Relative Risks 1.72 (0.68, 4.35) comparing low to high education).

CONCLUSION

Results indicate cold-mortality risks in NC, with potential differences by regional, urban-rural areas, and community characteristics.

Trends of biomarkers of cardiovascular disease in the United States by income: Disparities between the richest 20% and the poorest 80%,1999-2018

INTRODUCTION

Income inequality between the richest 20% and the poorest 80% in the United States has been increasing over the past two decades. Emerging evidence indicates widening disparities between the two groups in cardiovascular disease prevalence as well. However, the mechanisms behind this trend remains unclear. This analysis examines whether a similar trend exists in the levels of biomarkers and risk factors of cardiovascular disease in the United States.

METHODS

We conducted a serial cross-sectional analysis of a nationally representative data from the National Health and Nutrition Examination Survey (NHANES) for participants age 20 or older between 1999 and 2018. We calculated trends in age-standardized means of body mass index (BMI), systolic blood pressure (SBP), and high-density lipoproteins (HDL) and the trend in prevalence of obesity, high SBP, and low HDL by income group.

RESULTS

This analysis included 49,764 participants. Age-standardized mean BMI increased every two years by an average of 0.15 kg/m 2 among the richest 20% and by an average of 0.21 kg/m 2 among the poorest 80%. Age-standardized mean SBP decreased every two years by an average of 0.13 mm Hg among the richest 20% and by an average of 0.10 mm Hg among the poorest 80%. Age-standardized mean HDL increased every two years by an average of 0.39 mg/dL among the richest 20% and by an average of 0.19 mg/dL among the poorest 80%. When adjusted for demographic factors and time, the richest 20% had lower mean BMI (OR = -0.67, 95% CI: -0.89, - 0.44), lower mean SBP (OR = -0.72, 95% CI: -1.24, -0.20), and higher mean HDL (OR = 3.04, 95% CI: 2.46, 3.62) compared to the poorest 80.

CONCLUSION

There are increasing disparities in cardiovascular disease biomarkers by income in the US. Between 1999 and 2018, improvement in biomarkers overwhelmingly occurred among the richest 20.

Where and When: Sharpening the lens on geographic disparities in mortality

Life course theories suggest that geographic disparities in mortality may reflect a history of place-based exposures rather than (or in addition to) contemporaneous exposures; yet, few studies examined early life place exposures and later life mortality in the US due to data limitations. The aim of this study is to assess and compare the importance of state of birth and state of residence in predicting mortality for adults over age 50 in the US. Using nationally representative data of nearly 100,000 adults over age 50 from the National Longitudinal Mortality Study, we estimated individual mortality risk using multi-level logistic regression with state of birth and state of residence as second-level random effects. We assessed whether state of residence and state of birth contributed to the variation in adult mortality. We also decomposed state-of-residence random effects to compare “movers” and “stayers.” Our results indicate that state of birth is a stronger predictor of age-, race/ethnicity- and sex-adjusted mortality in the US than state of residence at the time of death. The adult mortality profiles of many states are substantially impacted by the composition of “movers.” Failing to account for residential mobility has clouded our understanding of the patterns and causes of geographic differences in adult mortality. Measures of geographic residence across the life course can improve models of adult mortality in the US and inform interventions to address geographic disparities in longevity.

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State of birth is a stronger predictor of later age mortality than state of residence.

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Geographic inequalities in mortality are results from complex groupings of “movers” and “stayers”.

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Incorporating geographic residence across the life course improves models of adult mortality.

Do Individual and Geographical Deprivation Have the Same Impact on the Risk of Dementia? A 25-Year Follow-up Study

OBJECTIVES

To determine the impact of both individual psychosocioeconomic precariousness and geographical deprivation on risk of dementia in older adults followed-up for 25 years.

METHOD

The sample consisted of 3,431 participants aged 65 years or over from the PAQUID cohort study. Individual psychosocioeconomic precariousness was measured computing eight economic and psychosocial indicators. Geographical deprivation was assessed by the FDep99 index, consisting of four community socioeconomic variables. For both measures, the fourth quartile of the distribution was considered as the more precarious or deprived category, while the first quartile was considered as the less precarious or deprived one. Clinical dementia diagnosis was assessed all along study follow-up. The association between individual psychosocioeconomic precariousness, geographical deprivation and risk of dementia was assessed using illness-death regression models adjusted for age, sex, depression, psychotropic drug consumption, comorbidities, disability, and body mass index, while accounting for death as a competing event.

RESULTS

The risk of dementia was higher for the more psychosocioeconomic precarious participants (HR = 1.51; 95% CI: 1.24-1.84). No increased risk of dementia was found for those living in communities with high index of deprivation.

DISCUSSION

Psychosocioeconomic precariousness, but not geographical deprivation, is associated with a higher risk of dementia.

Economic growth, income inequality and life expectancy in China

China had made dramatic health gains before its economic reform that began in 1978 produced rapid economic growth in the ensuing years. Since the economic reform, China's income inequality has substantially increased, and health gains have stagnated. This article investigates the extent to which China's health stagnation may be attributable to the rise in income inequality in China. By simulating the improvement in life expectancy that could have resulted if, ceteris paribus, income inequality had stayed constant at the lowest level after the founding of the People's Republic of China in 1949, we find that the sharply increasing income inequality in China has contributed to life loss in China's population, about 0.6 years for men and 0.4 years for women. These findings suggest that redistribution of income from rich to poor may be one of the most important policy levers for improving population health in China.

Utilisation of social determinants of health to improve education among youth in Dominican baseball academies

Traditional youth baseball academies in the Dominican Republic, along with the potential of a major league baseball contract, are viewed by many parents as the best option to pull a child and family out of poverty. These academies advance the child's athletic abilities yet fail to provide formal education. Unfortunately, 97% of athletes leave the academy without a contract and are left with little education, job skills, or stable job prospects which ultimately returns them to the life of poverty they had hoped to escape through baseball. A faith-based organisation in Santiago, Dominican Republic, offers a high-level baseball academy inclusive of supportive academics. The purpose of this research project was to describe the perspectives of stakeholders involved with the faith-based missional organisation to discern the components and effectiveness of the efforts to support student growth in and beyond athletic abilities. Utilising a community-based research approach with a social determinants of health theoretical framework, researchers held in-country focus group discussions (Spring, 2019) with the organisation's stakeholders (coaches, parents, community leaders, N = 33). Researchers collaboratively coded data, triangulating within and across sources, to identify themes. Qualitative data suggest stakeholders within this organisation perceive the academy as instrumental in keeping kids off the streets, encouraging self-discipline in sports, church and school. The stakeholders perceived the inclusion of academic expectations into the sports academies improved long-term educational and economic success for the athletes. Inclusion of academic requirements within sports academies may improve long-term outcomes of youth in the Dominican Republic.

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.

A Prospective Analysis of Genetic Variants Associated with Human Lifespan

We present a massive investigation into the genetic basis of human lifespan. Beginning with a genome-wide association (GWA) study using a de-identified snapshot of the unique AncestryDNA database – more than 300,000 genotyped individuals linked to pedigrees of over 400,000,000 people – we mapped six genome-wide significant loci associated with parental lifespan. We compared these results to a GWA analysis of the traditional lifespan proxy trait, age, and found only one locus, APOE, to be associated with both age and lifespan. By combining the AncestryDNA results with those of an independent UK Biobank dataset, we conducted a meta-analysis of more than 650,000 individuals and identified fifteen parental lifespan-associated loci. Beyond just those significant loci, our genome-wide set of polymorphisms accounts for up to 8% of the variance in human lifespan; this value represents a large fraction of the heritability estimated from phenotypic correlations between relatives.

Inequality within a community at the neighborhood level and the incidence of mood disorders in Japan: a multilevel analysis

PURPOSE

This study analyzes whether income inequality within a community at the neighborhood level is associated with incidence of mood disorder in Japan.

METHODS

A retrospective cohort study was performed using the data of 116,658 National Health Insurance beneficiaries aged between 20 and 69 in Chiba City, Japan. To evaluate income inequality within a community, the Gini coefficient within a 30-min walking distance from an individual's residence was calculated using income distribution estimated by the National Census and the Housing and Land Survey 2013. Incidence of mood disorder was determined through insurance claims submitted from April 1, 2013, to March 31, 2016. A multilevel logistic analysis with three levels-the individual, household, and residential district-was performed to evaluate the association.

RESULTS

Income inequality within a community at the neighborhood level was not associated with incidence of mood disorder in the models with and without equivalent household income (p for trend = 0.856 and 0.947, respectively). No difference was observed in the impact of the Gini coefficient among income levels, lower versus higher income groups (p for interaction between Gini coefficient and household income = 0.967). In contrast, lower equivalent income at the household level was significantly associated with higher incidence of mood disorder (p for trend < 0.001).

CONCLUSIONS

While we confirmed that lower income at the household level itself had an adverse effect on mental health, income inequality within a community at the neighborhood level was not a significant factor for incidence of mood disorder in Japan.

Double disadvantage: income inequality, spatial polarization and mortality rates in Taiwan

Background

Previous studies have suggested that social and economic spatial polarization is associated with various health outcomes. However, few studies have examined the joint effect of income inequality and spatial polarization on health.

Methods

Data on mortality in 2008-12 were from the Ministry of Health and Welfare. We constructed economic spatial polarization using the Index of Concentration at the Extremes (ICE) by tax data from the Ministry of Finance. The Gini coefficient was from the Family Income and Expenditure Survey. Using multilevel datasets of 352 townships nested within 20 cities in Taiwan, we examined the association between township-level ICE and mortality, and further examined whether city-level income inequality moderate this association.

Results

In 2008-12, the average age-standardized mortality in Taiwan was 470.5 per 100 000 populations. As compared to the highest income-based ICE quintile, the lowest ICE quintile was associated with an excess 171.7 deaths per 100 000 people (95% CI = 116.1, 227.3) after controlling for income inequality and population size. One unit rise in the Gini coefficient further increased 29.9 deaths (95% CI = 12.4, 47.5) for the lowest ICE quintile, as compared to the highest.

Conclusion

The joint effect of income inequality and small-scale economic polarization may shed light on how inequalities increase mortality.

Income Inequality and US Children's Secondhand Smoke Exposure: Distinct Associations by Race-Ethnicity

Introduction

Prior studies have found considerable racial and ethnic disparities in secondhand smoke (SHS) exposure. Although a number of individual-level determinants of this disparity have been identified, contextual determinants of racial and ethnic disparities in SHS exposure remain unexamined. The objective of this study was to examine disparities in serum cotinine in relation to area-level income inequality among 14 649 children from the National Health and Nutrition Examination Survey.

Methods

We fit log-normal regression models to examine disparities in serum cotinine in relation to Metropolitan Statistical Areas level income inequality among 14 649 nonsmoking children aged 3-15 from the National Health and Nutrition Examination Survey (1999-2012).

Result

Non-Hispanic black children had significantly lower serum cotinine than non-Hispanic white children (-0.26; 95% CI: -0.38, -0.15) in low income inequality areas, but this difference was attenuated in areas with high income inequality (0.01; 95% CI: -0.16, 0.18). Serum cotinine declined for non-Hispanic white and Mexican American children with increasing income inequality. Serum cotinine did not change as a function of the level of income inequality among non-Hispanic black children.

Conclusions

We have found evidence of differential associations between SHS exposure and income inequality by race and ethnicity. Further examination of environments which engender SHS exposure among children across various racial/ethnic subgroups can foster a better understanding of how area-level income inequality relates to health outcomes such as levels of SHS exposure and how those associations differ by race/ethnicity.

Implications

In the United States, the association between children's risk of SHS exposure and income inequality is modified by race/ethnicity in a manner that is inconsistent with theories of income inequality. In overall analysis this association appears to be as predicted by theory. However, race-specific analyses reveal that higher levels of income inequality are associated with lower levels of SHS exposure among white children, while levels of SHS exposure among non-Hispanic black children are largely invariant to area-level income inequality. Future examination of the link between income inequality and smoking-related health outcomes should consider differential associations across racial and ethnic subpopulations.

Association of Socioeconomic Status, Race and Insurance Status with Chronic Rhinosinusitis Patient-Reported Outcome Measures

Objective Disparities in health and health care access are widely prevalent. However, disparities among patients with chronic rhinosinusitis (CRS) are poorly understood. We investigated if CRS severity at presentation according to socioeconomic factors. Study Design Cross-sectional study. Setting Tertiary rhinology center. Subjects and Methods Three hundred prospectively recruited patients presenting with CRS were included. Outcome variables included CRS symptomatology, as reflected by the 22-item Sinonasal Outcome Test (SNOT-22); general health status, as reflected by the EuroQol 5-dimensional visual analog scale (EQ-5D VAS); and CRS-related antibiotic and systemic corticosteroid use. Race/ethnicity, zip code income bracket, education level, and insurance status were used as predictor variables. Regression, controlling for clinical and demographic characteristics, was used to determine associations between predictor and outcome variables. Results Mean SNOT-22 score was 33.8 (SD, 23.2), and mean EQ-5D VAS score was 74.2 (SD, 18.9). On multivariable analysis, presenting SNOT-22 and EQ-5D VAS scores were not associated with nonwhite patient race/ethnicity ( P = .634 and P = .866), education ( P = .106 and P = .586), or the percentage of households in zip code with incomes <$50,000 per year ( P = .917 and P = .979, respectively). SNOT-22 scores did not differ by insurance type, but patients receiving Medicare reported worse general health status. Use of oral antibiotics or oral steroids for CRS was not associated with predictor variables. Conclusion Patients with CRS presented to a tertiary rhinology center with similar metrics for CRS severity and pre-presentation medical management regardless of race/ethnicity, education status, or zip code income level. Patients with Medicare had worse general health status. Further research should investigate potential disparities in diagnosis of CRS, specialist referral, and treatment outcomes.

Bring out your dead!: A study of income inequality and life expectancy in the United States, 2000-2010

We test whether income inequality undermines female and male life expectancy in the United States. We employ data for all 50 states and the District of Columbia and two-way fixed effects to model state-level average life expectancy as a function of multiple income inequality measures and time-varying characteristics. We find that state-level income inequality is inversely associated with female and male life expectancy. We observe this general pattern across four measures of income inequality and under the rigorous conditions of state-specific and year-specific fixed effects. If income inequality undermines life expectancy, redistribution policies could actually improve the health of states.

The Association Between Neighborhood Environment and Mortality: Results from a National Study of Veterans

BACKGROUND

As the largest integrated US health system, the Veterans Health Administration (VHA) provides unique national data to expand knowledge about the association between neighborhood socioeconomic status (NSES) and health. Although living in areas of lower NSES has been associated with higher mortality, previous studies have been limited to higher-income, less diverse populations than those who receive VHA care.

OBJECTIVE

To describe the association between NSES and all-cause mortality in a national sample of veterans enrolled in VHA primary care.

DESIGN

One-year observational cohort of veterans who were alive on December 31, 2011. Data on individual veterans (vital status, and clinical and demographic characteristics) were abstracted from the VHA Corporate Data Warehouse. Census tract information was obtained from the US Census Bureau American Community Survey. Logistic regression was used to model the association between NSES deciles and all-cause mortality during 2012, adjusting for individual-level income and demographics, and accounting for spatial autocorrelation.

PARTICIPANTS

Veterans who had vital status, demographic, and NSES data, and who were both assigned a primary care physician and alive on December 31, 2011 (n = 4,814,631).

MAIN MEASURES

Census tracts were used as proxies for neighborhoods. A summary score based on census tract data characterized NSES. Veteran addresses were geocoded and linked to census tract NSES scores. Census tracts were divided into NSES deciles.

KEY RESULTS

In adjusted analysis, veterans living in the lowest-decile NSES tract were 10 % (OR 1.10, 95 % CI 1.07, 1.14) more likely to die than those living in the highest-decile NSES tract.

CONCLUSIONS

Lower neighborhood SES is associated with all-cause mortality among veterans after adjusting for individual-level socioeconomic characteristics. NSES should be considered in risk adjustment models for veteran mortality, and may need to be incorporated into strategies aimed at improving veteran health.

The associations between US state and local social spending, income inequality, and individual all-cause and cause-specific mortality: The National Longitudinal Mortality Study

OBJECTIVE

To investigate government state and local spending on public goods and income inequality as predictors of the risks of dying.

METHODS

Data on 431,637 adults aged 30-74 and 375,354 adults aged 20-44 in the 48 contiguous US states were used from the National Longitudinal Mortality Study to estimate the impacts of state and local spending and income inequality on individual risks of all-cause and cause-specific mortality for leading causes of death in younger and middle-aged adults and older adults. To reduce bias, models incorporated state fixed effects and instrumental variables.

RESULTS

Each additional $250 per capita per year spent on welfare predicted a 3-percentage point (-0.031, 95% CI: -0.059, -0.0027) lower probability of dying from any cause. Each additional $250 per capita spent on welfare and education predicted 1.6-percentage point (-0.016, 95% CI: -0.031, -0.0011) and 0.8-percentage point (-0.008, 95% CI: -0.0156, -0.00024) lower probabilities of dying from coronary heart disease (CHD), respectively. No associations were found for colon cancer or chronic obstructive pulmonary disease; for diabetes, external injury, and suicide, estimates were inverse but modest in magnitude. A 0.1 higher Gini coefficient (higher income inequality) predicted 1-percentage point (0.010, 95% CI: 0.0026, 0.0180) and 0.2-percentage point (0.002, 95% CI: 0.001, 0.002) higher probabilities of dying from CHD and suicide, respectively.

CONCLUSIONS

Empirical linkages were identified between state-level spending on welfare and education and lower individual risks of dying, particularly from CHD and all causes combined. State-level income inequality predicted higher risks of dying from CHD and suicide.

Tract- and county-level income inequality and individual risk of obesity in the United States

OBJECTIVES

We tested three alternative hypotheses regarding the relationship between income inequality and individual risk of obesity at two geographical scales: U.S. Census tract and county.

METHODS

Income inequality was measured by Gini coefficients, created from the 2000 U.S. Census. Obesity was clinically measured in the 2003-2008 National Health and Nutrition Examination Survey (NHANES). The individual measures and area measures were geo-linked to estimate three sets of multi-level models: tract only, county only, and tract and county simultaneously. Gender was tested as a moderator.

RESULTS

At both the tract and county levels, higher income inequality was associated with lower individual risk of obesity. The size of the coefficient was larger for county-level Gini than for tract-level Gini; and controlling income inequality at one level did not reduce the impact of income inequality at the other level. Gender was not a significant moderator for the obesity-income inequality association.

CONCLUSIONS

Higher tract and county income inequality was associated with lower individual risk of obesity, indicating that at least at the tract and county levels and in the context of cross-sectional data, the public health goal of reducing the rate of obesity is in line with anti-poverty policies of addressing poverty through mixed-income development where neighborhood income inequality is likely higher than homogeneous neighborhoods.

Inequalities in mortality by socioeconomic factors and Roma ethnicity in the two biggest cities in Slovakia: a multilevel analysis

Background

The socioeconomic and ethnic composition of urban neighbourhoods may affect mortality, but evidence on Central European cities is lacking. The aim of this study was to assess the associations between socioeconomic and ethnic neighbourhood indicators and the mortality of individuals aged 20–64 years old in the two biggest cities of the Slovak Republic.

Methods

We obtained data on the characteristics of neighbourhoods and districts (educational level, unemployment, income and share of Roma) and on individual mortality of residents aged 20–64 years old, for the two largest cities in the Slovak Republic (Bratislava and Kosice) in the period 2003–2005. We performed multilevel Poisson regression analyses adjusted for age and gender on the individual (mortality), neighbourhood (education level and share of Roma in population) and district levels (unemployment and income).

Results

The proportions of Roma and of low-educated residents were associated with mortality at the neighbourhood level in both cities. Mutually adjusted, only the association with the proportion of Roma remained in the model (risk ratio 1.02; 95 % confidence interval 1.01–1.04). The area indicators – high education, income and unemployment – were not associated with mortality.

Conclusion

The proportion of Roma is associated with early mortality in the two biggest cities in the Slovak Republic.

A multilevel analysis of mortality following acute myocardial infarction in Norway: do municipal health services make a difference?

OBJECTIVES

Studies link area features such as neighbourhood socioeconomic deprivation to poor health outcomes. However, there is a paucity of research based on representative data investigating the effects of area-level health services on mortality. This study examines the extent to which municipal health services account for municipal variation in all-cause and cardiovascular disease (CVD) mortality. We hypothesise that unfavourable municipal features (eg, fewer available places for rehabilitation) are associated with higher risk of mortality after accounting for patients' characteristics.

DESIGN

Population data from Norwegian national/municipal registrars are analysed using multilevel logistic regression in this prospective cohort study.

SETTING AND PARTICIPANTS

The analytic sample (9412 patients aged 18+ from 336 municipalities) constitutes 87.7% of the nationwide population of Norwegian adults who were hospitalised for acute myocardial infarction (AMI) in 2009 and discharged alive.

PRIMARY OUTCOME MEASURES

All-cause and CVD mortality occurring within 365 days after the first day of hospitalisation for AMI.

RESULTS

There was a small but significant variation at the municipal level in all-cause mortality (0.5%; intraclass correlation coefficient=0.005) but not CVD mortality. There were no significant fixed effects of municipal health services on mortality in bivariate models. Patients' characteristics (eg, gender, comorbidities) fully accounted for the observed municipal variation in mortality. Being male versus female (OR=1.21, 95% CI 1.02 to 1.43), or having been previously diagnosed with dementia versus not (OR=2.06, 95% CI 1.53 to 2.77) were also linked to higher odds of death.

CONCLUSIONS

Municipal variation in all-cause mortality for Norwegian patients with AMI appears to be driven not by differences across municipalities in health service levels, but by differences across municipalities in the composition of patients. Focusing on chronic disease prevention and treatment, and tackling personal and structural risk factors embedded within patients' sociodemographic characteristics, may be especially beneficial for longevity.

Distinguishing the race-specific effects of income inequality and mortality in U.S. metropolitan areas

In the United States, the association between income inequality and mortality has been fairly consistent. However, few studies have explicitly examined the impact of race. Studies that have either stratified outcomes by race or conducted analyses within race-specific groups suggest that the income inequality/mortality relation may differ for blacks and whites. The factors explaining the association may also differ for the two groups. Multivariate ordinary least squares regression analysis was used to examine associations between study variables. We used three measures of income inequality to examine the association between income inequality and age-adjusted all-cause mortality among blacks and whites separately. We also examined the role of racial residential segregation and concentrated poverty in explaining associations among groups. Metropolitan areas were included if they had a population of at least 100,000 and were at least 10 percent black. There was a positive income inequality/mortality association among blacks and an inverse association among whites. Racial residential segregation completely attenuated the income inequality/mortality relationship for blacks, but was not significant among whites. Concentrated poverty was a significant predictor of mortality rates in both groups but did not confound associations. The implications of these findings and directions for future research are discussed.

Divergence in age patterns of mortality change drives international divergence in lifespan inequality

In the past six decades, lifespan inequality has varied greatly within and among countries even while life expectancy has continued to increase. How and why does mortality change generate this diversity? We derive a precise link between changes in age-specific mortality and lifespan inequality, measured as the variance of age at death. Key to this relationship is a young-old threshold age, below and above which mortality decline respectively decreases and increases lifespan inequality. First, we show for Sweden that shifts in the threshold's location have modified the correlation between changes in life expectancy and lifespan inequality over the last two centuries. Second, we analyze the post-World War II (WWII) trajectories of lifespan inequality in a set of developed countries-Japan, Canada, and the United States-where thresholds centered on retirement age. Our method reveals how divergence in the age pattern of mortality change drives international divergence in lifespan inequality. Most strikingly, early in the 1980s, mortality increases in young U.S. males led to a continuation of high lifespan inequality in the United States; in Canada, however, the decline of inequality continued. In general, our wider international comparisons show that mortality change varied most at young working ages after WWII, particularly for males. We conclude that if mortality continues to stagnate at young ages yet declines steadily at old ages, increases in lifespan inequality will become a common feature of future demographic change.

Income inequality and mortality: results from a longitudinal study of older residents of São 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.

Metropolitan social environments and pre-HAART/HAART era changes in mortality rates (per 10,000 adult residents) among injection drug users living with AIDS

Background

Among the largest US metropolitan areas, trends in mortality rates for injection drug users (IDUs) with AIDS vary substantially. Ecosocial, risk environment and dialectical theories suggest many metropolitan areas characteristics that might drive this variation. We assess metropolitan area characteristics associated with decline in mortality rates among IDUs living with AIDS (per 10,000 adult MSA residents) after highly active antiretroviral therapy (HAART) was developed.

Methods

This is an ecological cohort study of 86 large US metropolitan areas from 1993–2006. The proportional rate of decline in mortality among IDUs diagnosed with AIDS (as a proportion of adult residents) from 1993–1995 to 2004–2006 was the outcome of interest. This rate of decline was modeled as a function of MSA-level variables suggested by ecosocial, risk environment and dialectical theories. In multiple regression analyses, we used 1993–1995 mortality rates to (partially) control for pre-HAART epidemic history and study how other independent variables affected the outcomes.

Results

In multivariable models, pre-HAART to HAART era increases in ‘hard drug’ arrest rates and higher pre-HAART income inequality were associated with lower relative declines in mortality rates. Pre-HAART per capita health expenditure and drug abuse treatment rates, and pre- to HAART-era increases in HIV counseling and testing rates, were weakly associated with greater decline in AIDS mortality.

Conclusions

Mortality among IDUs living with AIDS might be decreased by reducing metropolitan income inequality, increasing public health expenditures, and perhaps increasing drug abuse treatment and HIV testing services. Given prior evidence that drug-related arrest rates are associated with higher HIV prevalence rates among IDUs and do not seem to decrease IDU population prevalence, changes in laws and policing practices to reduce such arrests while still protecting public order should be considered.

Socioeconomic status and metabolic syndrome in the general population of China: a cross-sectional study

Background

Individual socioeconomic status (SES) has been found to be associated with cardiovascular diseases in developed countries, but the association between individual SES and metabolic syndrome (MetS) is still unclear in China. The objective of this study was to investigate the association between individual SES and MetS in China.

Methods

A cross-sectional study of 10054 community residents was performed from May to August 2007 using multistage stratified random sampling. SES was assessed in terms of education, personal monthly income, and household monthly income. The association between SES and MetS was determined by logistic regression models.

Results

After the adjustments regarding age, marital status, smoking, drinking, physical activity, body mass index (BMI), and community type, odds ratios (ORs) for MetS of individuals with education level of 7~12 years and >12 years were 0.87 (95% confidence interval [CI]: 0.75 to 0.99) and 0.83 (95% CI: 0.62 to 0.91) respectively compared with those with education level of <7 years in women. Following the adjustments as above, ORs for MetS of individuals with household monthly income level of middle and higher were 0.94 (95% CI: 0.86 to 0.97), and 0.72 (95% CI: 0.65 to 0.88) respectively compared with those with lower household monthly income level in women. The association between SES and MetS was not significant in men.

Conclusions

Gender had an influence on the association between individual SES and MetS. Lower education and household monthly income level were associated with higher risk of MetS among community residents in women, while such association was not significant in men.

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

PURPOSE

To test the association between income inequality and elderly self-rated health and to propose a pathway to explain the relationship.

METHODS

We 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.

RESULTS

Income 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.

CONCLUSIONS

The 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.

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.

Portrait of socio-economic inequality in childhood morbidity and mortality over time, Québec, 1990-2005

AIM

To determine the age and cause groups contributing to absolute and relative socio-economic inequalities in paediatric mortality, hospitalisation and tumour incidence over time.

METHODS

Deaths (n= 9559), hospitalisations (n= 834,932) and incident tumours (n= 4555) were obtained for five age groupings (<1, 1-4, 5-9, 10-14, 15-19 years) and four periods (1990-1993, 1994-1997, 1998-2001, 2002-2005) for Québec, Canada. Age- and cause-specific morbidity and mortality rates for males and females were calculated across socio-economic status decile based on a composite deprivation score for 89 urban communities. Absolute and relative measures of inequality were computed for each age and cause.

RESULTS

Mortality and morbidity rates tended to decrease over time, as did absolute and relative socio-economic inequalities for most (but not all) causes and age groups, although precision was low. Socio-economic inequalities persisted in the last period and were greater on the absolute scale for mortality and hospitalisation in early childhood, and on the relative scale for mortality in adolescents. Four causes (respiratory, digestive, infectious, genito-urinary diseases) contributed to the majority of absolute inequality in hospitalisation (males 85%, females 98%). Inequalities were not pronounced for cause-specific mortality and not apparent for tumour incidence.

CONCLUSIONS

Socio-economic inequalities in Québec tended to narrow for most but not all outcomes. Absolute socio-economic inequalities persisted for children <10 years, and several causes were responsible for the majority of inequality in hospitalisation. Public health policies and prevention programs aiming to reduce socio-economic inequalities in paediatric health should account for trends that differ across age and cause of disease.

Alcohol consumption and social inequality at the individual and country levels--results from an international study

BACKGROUND

International comparisons of social inequalities in alcohol use have not been extensively investigated. The purpose of this study was to examine the relationship of country-level characteristics and individual socio-economic status (SES) on individual alcohol consumption in 33 countries.

METHODS

Data on 101,525 men and women collected by cross-sectional surveys in 33 countries of the GENACIS study were used. Individual SES was measured by highest attained educational level. Alcohol use measures included drinking status and monthly risky single occasion drinking (RSOD). The relationship between individuals' education and drinking indicators was examined by meta-analysis. In a second step the individual level data and country data were combined and tested in multilevel models. As country level indicators we used the Purchasing Power Parity of the gross national income, the Gini coefficient and the Gender Gap Index.

RESULTS

For both genders and all countries higher individual SES was positively associated with drinking status. Also higher country level SES was associated with higher proportions of drinkers. Lower SES was associated with RSOD among men. Women of higher SES in low income countries were more often RSO drinkers than women of lower SES. The opposite was true in higher income countries.

CONCLUSION

For the most part, findings regarding SES and drinking in higher income countries were as expected. However, women of higher SES in low and middle income countries appear at higher risk of engaging in RSOD. This finding should be kept in mind when developing new policy and prevention initiatives.

Geographic and racial variation in premature mortality in the U.S.: analyzing the disparities

Life expectancy at birth, estimated from United States period life tables, has been shown to vary systematically and widely by region and race. We use the same tables to estimate the probability of survival from birth to age 70 (S(70)), a measure of mortality more sensitive to disparities and more reliably calculated for small populations, to describe the variation and identify its sources in greater detail to assess the patterns of this variation. Examination of the unadjusted probability of S(70) for each US county with a sufficient population of whites and blacks reveals large geographic differences for each race-sex group. For example, white males born in the ten percent healthiest counties have a 77 percent probability of survival to age 70, but only a 61 percent chance if born in the ten percent least healthy counties. Similar geographical disparities face white women and blacks of each sex. Moreover, within each county, large differences in S(70) prevail between blacks and whites, on average 17 percentage points for men and 12 percentage points for women. In linear regressions for each race-sex group, nearly all of the geographic variation is accounted for by a common set of 22 socio-economic and environmental variables, selected for previously suspected impact on mortality; R(2) ranges from 0.86 for white males to 0.72 for black females. Analysis of black-white survival chances within each county reveals that the same variables account for most of the race gap in S(70) as well. When actual white male values for each explanatory variable are substituted for black in the black male prediction equation to assess the role explanatory variables play in the black-white survival difference, residual black-white differences at the county level shrink markedly to a mean of -2.4% (+/-2.4); for women the mean difference is -3.7% (+/-2.3).

Losses of expected lifetime in the United States and other developed countries: methods and empirical analyses

Patterns of diversity in age at death are examined using e (†), a dispersion measure that equals the average expected lifetime lost at death. We apply two methods for decomposing differences in e (†). The first method estimates the contributions of average levels of mortality and mortality age structures. The second (and newly developed) method returns components produced by differences between age- and cause-specific mortality rates. The United States is close to England and Wales in mean life expectancy but has higher life expectancy losses and lacks mortality compression. The difference is determined by mortality age structures, whereas the role of mortality levels is minor. This is related to excess mortality at ages under 65 from various causes in the United States. Regression on 17 country-series suggests that e (†) correlates with income inequality across countries but not across time. This result can be attributed to dissimilarity between the age- and cause-of-death structures of temporal mortality reduction and intercountry mortality variation. It also suggests that factors affecting overall mortality decrease differ from those responsible for excess lifetime losses in the United States compared with other countries. The latter can be related to weaknesses of health system and other factors resulting in premature death from heart diseases, amenable causes, accidents and violence.

Do people die from income inequality of a decade ago?

The long-term impact of income inequality on health has not been fully explored in the current literature. Until now, 4 studies have examined the lagged effect on population/group mortality rate at the aggregate level, and 7 studies have investigated the effect of income inequality on subsequent individual mortality risk within a restricted time period. These 11 studies suffer from the same limitation: they do not simultaneously control for a series of preceding income inequalities. The results of these studies are also mixed. Using the U.S. National Health Interview Survey data 1986-2004 with mortality follow-up data 1986-2006 (n = 701,179), this study investigates the lagged effects of national-level income inequality on individual mortality risk. These effects are tested by using a discrete-time hazard model where contemporaneous and preceding income inequalities are treated as time-varying person-specific covariates, which then track a series of income inequalities that a respondent faces from the survey year until s/he dies or is censored. Findings suggest that income inequality did not have an instantaneous detrimental effect on individual mortality risk, but began exerting its influence 5 years later. This effect peaked at 7 years, and then diminished after 12 years. This pattern generally held for three measures of income inequality: the Gini coefficient, the Atkinson index, and the Theil entropy index. The findings suggest that income inequality has a long-term detrimental impact on individual mortality risk. This study also explains discrepancies in the existant literature.

Cardiovascular inflammation in healthy women: multilevel associations with state-level prosperity, productivity and income inequality

BACKGROUND

Cardiovascular inflammation is a key contributor to the development of atherosclerosis and the prediction of cardiovascular events among healthy women. An emerging literature suggests biomarkers of inflammation vary by geography of residence at the state-level, and are associated with individual-level socioeconomic status. Associations between cardiovascular inflammation and state-level socioeconomic conditions have not been evaluated. The study objective is to estimate whether there are independent associations between state-level socioeconomic conditions and individual-level biomarkers of inflammation, in excess of individual-level income and clinical covariates among healthy women.

METHODS

The authors examined cross-sectional multilevel associations among state-level socioeconomic conditions, individual-level income, and biomarkers of inflammation among women (n = 26,029) in the Women's Health Study, a nation-wide cohort of healthy women free of cardiovascular diseases at enrollment. High sensitivity C-reactive protein (hsCRP), soluble intercellular adhesion molecule-1 (sICAM-1) and fibrinogen were measured between 1993 and 1996. Biomarker levels were examined among women within quartiles of state-level socioeconomic conditions and within categories of individual-level income.

RESULTS

The authors found that favorable state-level socioeconomic conditions were correlated with lower hsCRP, in excess of individual-level income (e.g. state-level real per capital gross domestic product fixed effect standardized Βeta coefficient [Std B] -0.03, 95% CI -0.05, -0.004). Individual-level income was more closely associated with sICAM-1 (Std B -0.04, 95% CI -0.06, -0.03) and fibrinogen (Std B -0.05, 95% CI -0.06, -0.03) than state-level conditions.

CONCLUSIONS

We found associations between state-level socioeconomic conditions and hsCRP among healthy women. Personal household income was more closely associated with sICAM-1 and fibrinogen than state-level socioeconomic conditions. Additional research should examine these associations in other cohorts, and investigate what more-advantaged states do differently than less-advantaged states that may influence levels of cardiovascular inflammation among healthy women.

Do neighborhoods affect individual mortality? A systematic review and meta-analysis of multilevel studies

There has been increasing interest in investigating whether inhabitants in socially or physically deprived neighborhoods have higher mortality when individual socioeconomic status is adjusted for. Results so far appear ambiguous and the objective of this study was to conduct a systematic literature review of previous studies and to quantify the association between area-level socioeconomic status (ALSES) and all-cause mortality in a meta-analysis. Current guidelines for systematic reviews and meta-analyses were followed. Articles were retrieved from Medline, Embase, Social Sciences Citation Index and PsycInfo and individually evaluated by two researchers. Only peer-reviewed multilevel studies from high-income countries, which analyzed the influence of at least one area-level indicator and which controlled for individual SES, were included. The ALSES estimates in each study were first combined into a single estimate using weighted linear regression. In the meta-analysis we calculated combined estimates with random effects to account for heterogeneity between studies. Out of the 40 studies found eligible for the systematic review 18 studies were included in the meta-analysis. The systematic review suggests that there is an association between social cohesion and mortality but found no evidence for a clear association for area-level income inequality or for social capital. Studies including more than one area level suggest that characteristics on different area levels contribute to individual mortality. In the meta-analysis we found significantly higher mortality among inhabitants living in areas with low ALSES. Associations were stronger for men and younger age groups and in studies analyzing geographical units with fewer inhabitants.

An Examination of the Relationship between Neighborhood Income Inequality, Social Resources, and Obesity in Los Angeles County

Purpose.

This study examines whether local income inequality is associated with an increased likelihood of obesity among Los Angeles County residents and whether collective efficacy mediates the relationship.

Design.

A cross-sectional study of 2875 adults in 65 neighborhoods that took part in wave 1 of the Los Angeles Family and Neighborhood Survey in 2000-2001. Neighborhood measures are taken from the Los Angeles Neighborhood Services and Characteristics Database and decennial census.

Measures.

Obesity is defined as a body mass index over 30. Income inequality is operationalized with the Gini coefficient. Collective efficacy is a neighborhood-level measure comprised of aggregated responses to items that capture trust, cohesion, and the willingness to intervene for the common good among residents. Controls are included at the individual level for demographics and health characteristics, and at the neighborhood level for median household income.

Analysis.

Logistic regression models of individuals within neighborhoods.

Results.

When neighborhood economic well-being is controlled, income inequality is associated with a significant reduction in the likelihood of obesity while also controlling for individual demographic and health-related characteristics. Collective efficacy exerts an independent and beneficial effect but does not mediate the relationship between inequality and obesity.

Conclusion.

Neighborhood social resources and economic heterogeneity are associated with a lower likelihood of obesity. It may be that economically heterogeneous neighborhoods, perhaps especially in Los Angeles County, contain characteristics that promote health.

Early-life antecedents of atrial fibrillation: place of birth and atrial fibrillation-related mortality

PURPOSE

Recent evidence suggests early-life factors correlate with atrial fibrillation (AF). We hypothesized that AF-related mortality, similar to stroke mortality, is elevated for individuals born in the southeastern United States.

METHODS

We estimated 3-year (1999-2001) average AF-related mortality rates by using U.S. vital statistics for 55- to 89-year-old white (136,573 AF-related deaths) and black subjects (8,288 AF-related deaths). We estimated age- and sex-adjusted odds of AF-related (contributing cause) mortality associated with birth state, and birth within the U.S. stroke belt (SB), stratified by race. SB results were replicated with the use of 1989-1991 data.

RESULTS

Among black subjects, four contiguous birth states were associated with statistically significant odds ratios ≥ 1.25 compared with the national average AF-related mortality. The four highest-risk birth states for blacks also predicted elevated AF-related mortality among white subjects, but patterns were attenuated. The odds ratio for AF-related mortality associated with SB birth was 1.19 (confidence interval 1.13-1.25) for black and 1.09 (CI 1.07-1.12) for white subjects when we adjusted for SB adult residence.

CONCLUSIONS

Place of birth predicted AF-related mortality, after we adjusted for place of adult residence. The association of AF-related mortality and SB birth parallels that of other cardiovascular diseases and may likewise indicate an importance of early life factors in the development of AF.

Income Inequality and Tooth Loss in the United States

This study explored the relationship between state income inequality and individual tooth loss among 386,629 adults in the United States who participated in the 2008 Behavioral and Risk Factor Surveillance System. Multilevel models were used to test the association of the state Gini coefficient with tooth loss after sequential adjustment for state- (median household income) and individual-level confounders (sex, age, race, education, and household income), as well as state- (percent receiving fluoridated water and dentist-to-population ratio) and individual-level mediators (marital status and last dental visit). The state Gini coefficient was significantly associated with tooth loss even after adjustment for state- and individual-level confounders and potential mediators (Odds Ratio, 1.17; 95% Confidence Interval, 1.05 to 1.30). This study provides support for the relationship between state income inequality and individual tooth loss in the United States.

Racial segregation, income inequality, and mortality in US metropolitan areas

Evidence of the association between income inequality and mortality has been mixed. Studies indicate that growing income inequalities reflect inequalities between, rather than within, racial groups. Racial segregation may play a role. We examine the role of racial segregation on the relationship between income inequality and mortality in a cross-section of US metropolitan areas. Metropolitan areas were included if they had a population of at least 100,000 and were at least 10% black (N = 107). Deaths for the time period 1991-1999 were used to calculate age-adjusted all-cause mortality rates for each metropolitan statistical area (MSA) using direct age-adjustment techniques. Multivariate least squares regression was used to examine associations for the total sample and for blacks and whites separately. Income inequality was associated with lower mortality rates among whites and higher mortality rates among blacks. There was a significant interaction between income inequality and racial segregation. A significant graded inverse income inequality/mortality association was found for MSAs with higher versus lower levels of black-white racial segregation. Effects were stronger among whites than among blacks. A positive income inequality/mortality association was found in MSAs with higher versus lower levels of Hispanic-white segregation. Uncertainty regarding the income inequality/mortality association found in previous studies may be related to the omission of important variables such as racial segregation that modify associations differently between groups. Research is needed to further elucidate the risk and protective effects of racial segregation across groups.

Does the socioeconomic context explain both mortality and income inequality? Prospective register-based study of Norwegian regions

Background

Studies from various countries have observed worse population health in geographical areas with more income inequality. The psychosocial interpretation of this association is that large income disparities are harmful to health because they generate relative deprivation and undermine social cohesion. An alternative explanation contends that the association between income inequality and ill health arises because the underlying social and economic structures will influence both the level of illness and disease and the size of income differences. This paper examines whether the observed association between mortality and income inequality in Norwegian regions can be accounted for by the socioeconomic characteristics of the regions.

Methods

Norwegian register data covering the entire population were utilised. An extensive set of contextual and individual predictors were included in multilevel Poisson regression analyses of mortality 1994-2003 among 1.6 millions individuals born 1929-63, distributed across 35 residential regions.

Results

Mean income, composition of economic branches, and percentage highly educated in the regions were clearly connected to the level of income inequality. These social and economic characteristics of the regions were also markedly related to regional mortality levels, after adjustment for population composition, i.e., the individual-level variables. Moreover, regional mortality was significantly higher in regions with larger income disparities. The regions' social and economic structure did not, however, account for the association between regional income inequality and mortality. A distinct independent effect of income inequality on mortality remained after adjustment for regional-level social and economic characteristics.

Conclusions

The results indicate that the broader socioeconomic context in Norwegian regions has a substantial impact both on mortality and on the level of income disparities. However, the results also suggest, in a way compatible with the psychosocial interpretation, that on top of the general socioeconomic influences, a higher level of income inequality adds independently to higher mortality levels.

Previous publication

This article is a reworked version of the study 'Er inntektsforskjeller dødelige?' [Are income inequalities lethal?] which was published in Norwegian in Tidsskrift for velferdsforskning [Journal for welfare research], Vol. 13 (4), 2010.

Impact of income and income inequality on infant health outcomes in the United States

OBJECTIVES

The goal was to investigate the relationships of income and income inequality with neonatal and infant health outcomes in the United States.

METHODS

The 2000-2004 state data were extracted from the Kids Count Data Center. Health indicators included proportion of preterm births (PTBs), proportion of infants with low birth weight (LBW), proportion of infants with very low birth weight (VLBW), and infant mortality rate (IMR). Income was evaluated on the basis of median family income and proportion of federal poverty levels; income inequality was measured by using the Gini coefficient. Pearson correlations evaluated associations between the proportion of children living in poverty and the health indicators. Linear regression evaluated predictive relationships between median household income, proportion of children living in poverty, and income inequality for the 4 health indicators.

RESULTS

Median family income was negatively correlated with all birth outcomes (PTB, r = -0.481; LBW, r = -0.295; VLBW, r = -0.133; IMR, r = -0.432), and the Gini coefficient was positively correlated (PTB, r = 0.339; LBW, r = 0.398; VLBW, r = 0.460; IMR, r = 0.114). The Gini coefficient explained a significant proportion of the variance in rate for each outcome in linear regression models with median family income. Among children living in poverty, the role of income decreased as the degree of poverty decreased, whereas the role of income inequality increased.

CONCLUSIONS

Both income and income inequality affect infant health outcomes in the United States. The health of the poorest infants was affected more by absolute wealth than relative wealth.

DataSHIELD: resolving a conflict in contemporary bioscience--performing a pooled analysis of individual-level data without sharing the data

BACKGROUND

Contemporary bioscience sometimes demands vast sample sizes and there is often then no choice but to synthesize data across several studies and to undertake an appropriate pooled analysis. This same need is also faced in health-services and socio-economic research. When a pooled analysis is required, analytic efficiency and flexibility are often best served by combining the individual-level data from all sources and analysing them as a single large data set. But ethico-legal constraints, including the wording of consent forms and privacy legislation, often prohibit or discourage the sharing of individual-level data, particularly across national or other jurisdictional boundaries. This leads to a fundamental conflict in competing public goods: individual-level analysis is desirable from a scientific perspective, but is prevented by ethico-legal considerations that are entirely valid.

METHODS

Data aggregation through anonymous summary-statistics from harmonized individual-level databases (DataSHIELD), provides a simple approach to analysing pooled data that circumvents this conflict. This is achieved via parallelized analysis and modern distributed computing and, in one key setting, takes advantage of the properties of the updating algorithm for generalized linear models (GLMs).

RESULTS

The conceptual use of DataSHIELD is illustrated in two different settings.

CONCLUSIONS

As the study of the aetiological architecture of chronic diseases advances to encompass more complex causal pathways-e.g. to include the joint effects of genes, lifestyle and environment-sample size requirements will increase further and the analysis of pooled individual-level data will become ever more important. An aim of this conceptual article is to encourage others to address the challenges and opportunities that DataSHIELD presents, and to explore potential extensions, for example to its use when different data sources hold different data on the same individuals.