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

Does the impact of economic inequality on maternal and child health inequality exhibit a threshold effect? Evidence from China

When the economy (economic inequality) develops to a certain level, does the impact of economic inequality on health inequality change? Through threshold regression, this study analyses the impact of city-level economic inequality on the absolute and economic-related inequality in under-5 child mortality rate (U5MR) (2001-2012) and maternal mortality rate (MMR) (2001-2015), along with the threshold values for economic development stages and economic inequality. Findings show: For the relationship between economic inequality and absolute inequality in U5MR, as well as economic-related inequality, there exists an economic development threshold effect. For the relationship between economic inequality and absolute inequality in MMR, an economic inequality threshold effect is illustrated. The improvement of economic conditions contributes to alleviating inequality in U5MR. Economic development inequality has a significant impact on the equality of maternal health development, but for enhancing the equality of women's health, health promotion policies may be more feasible.

Material and social deprivation associated with public health actual causes of death among older people in Europe: longitudinal and multilevel results from the Survey of Health, Ageing and Retirement in Europe (SHARE)

Background

Adverse socioeconomic conditions at the individual and regional levels are associated with an increased risk of mortality. However, few studies have examined this relationship using multilevel analysis and, if so, only within a single country. This study aimed to examine this relationship using data from several European countries.

Methods

Individual-level data were obtained from Waves 5 to 9 of the Survey of Health, Ageing and Retirement in Europe, while regional-level data were obtained from the Luxembourg Income Study Database. Cox regression analysis with gamma-shared frailty and a random intercept for country of residence was used to examine the association between individual mortality from all causes, cancer, heart attack, and stroke and measures of socioeconomic deprivation at the individual level, including material and social deprivation indices, and at the area level, including the Gini index.

Results

The risk of mortality from all causes was increased for respondents with material deprivation (hazard ratio (HR) = 1.77, 95% CI = [1.60, 1.96]) and social deprivation (HR = 7.63, 95% CI = [6.42, 9.07]) compared with those without. A similar association was observed between individual deprivation and the risk of mortality from cancer, heart attack, or stroke. Regional deprivation had a modest contextual effect on the individual risk of death from all causes and cancer. However, when individual-level deprivation was included in the models, no contextual effects were found.

Conclusion

The results indicate that individual socioeconomic conditions significantly predict causes of death in older European adults, with those with material deprivation and social deprivation having a higher risk of death from all causes, including cancer, heart attack, and stroke, while the Gini index has a minimal effect, although the Gini index reflects regional disparities across Europe.

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.

Impact of income inequalities on subjective perception of older adult health: An analysis of healthy life expectancy in China from 1997 to 2006

AIM

Driven by rapid socioeconomic development over recent decades, there are widening income inequalities and subjective health disparities among older adults in China. This study explored the relationship between income inequalities and self-rated healthy life expectancy (HLE) considering potential sex-specific differences.

METHODS

From a cohort of 1760 individuals aged ≥60 years from the China Health and Nutrition Survey (1997-2006), we calculated age-specific life expectancy (LE), HLE and the proportion of HLE to LE (HLE/LE) by sex using the IMaCh software, incorporated time-varying income levels of older adults.

RESULTS

Although longevity has significantly improved, the well-being of Chinese older adults could be further enhanced by assessing HLE, as the results showed that at age 60 years, ~20% of their LE was characterized by unhealthiness. Discriminated by economic status, lower-income individuals experienced worse self-rated health compared with the general population and affluent counterparts. For instance, at age 60 years, the LE, HLE and HLE/LE of low-income men were 19.8 (95% CI 18.4-21.1), 16.2 years (95% CI 15.0-17.5) and 81.8%, respectively, lower than their general (21.7, 95% CI: 20.4-23.0; 18.0, 95% CI 16.8-19.2; and 82.9%) and high-income counterparts (25.1, 95% CI 23.1-27.2; 21.4, 95% CI 19.5-23.3; and 85.3%). Sex disparities were noticeable among low-income individuals in HLE/LE, with low-income women showing the most significant disadvantage.

CONCLUSIONS

Income inequalities exacerbated subjective health disparities among older adults, particularly among lower-income individuals and women. Our findings carry significant implications for formulating public health and social welfare strategies, especially in nations grappling with an aging population and undergoing parallel socioeconomic development. Geriatr Gerontol Int 2024; 24: 109-115.

Does Democracy Matter for Public Health?

This study examines the effect of democracy on public health by using panel data of 188 countries over the period 1972-2019. We use various regression methods, such as pooled ordinary least squares, fixed effects, dynamic generalized method of moments (GMM), a split-sample method, and a quadratic model to address econometric issues. The pooled regression supports the positive effect on health, but it does not exist in low-income countries, which can be explained by the threshold effect. The fixed effects regression confirms the positive impact on infant mortality but not on life expectancy, which illustrates the historical and cumulative effect of democracy on life expectancy. The non-linear regression finds a U-shaped relationship between democracy and infant mortality, which is consistent with the fixed effects regression result of the positive effect on mortality in the low-income group. The dynamic GMM regression shows the expected strong relationship between previous health and current health status. Overall, the regression analysis supports the positive effect of democracy on public health.

Comprehensive metrological and content analysis of the income inequality research in health field: A bibliometric analysis

The association between income inequality in a society and the poor health status of its people has attracted the attention of researchers from multiple disciplines. Based on the ISI Web of Science database, bibliometric methods were used to analyze 546 articles related to income inequality research in health field published between 1997 and 2021. We found that the USA contributed most articles, the Harvard Univ was the most influential institution, Social Science & Medicine was the most influential journal, and Kawachi I was the most influential author; the main hotspots included the income inequality, income, health inequality, mortality, socioeconomic factors, concentration index, social capital, self-rated health, income distribution, infant mortality, and population health in 1997-2021; the cardiovascular disease risk factor, social capital income inequality, individual mortality risk, income-related inequalities, understanding income inequalities, income inequality household income, and state income inequality had been the hot research topics in 1997-2003; the self-assessed health, achieving equity, income-related inequalities, oral health, mental health, European panel, occupational class, and cardiovascular diseases had been the hot research topics in 2004-2011; the adolescent emotional problem, South Africa, avoidable mortality, rising inequalities, results from world health survey, working-age adult, spatial aggregation change, prospective study, and mental health-empirical evidence had been the hot research topics in 2012-2021; there were 11 articles with strong transformation potential during 2012-2021. The research results of this paper are helpful to the scientific understanding of the current status of income inequality research in health field.

Income Inequality, Race/Ethnicity, and Obesity in U.S. Men 20 Years and Older: 1999 to 2016

Obesity is a significant public health problem globally and within the United States. It varies by multiple factors, including but not limited to income. The literature indicates little evidence of the association between income and obesity. We examined the association between income and obesity in U.S. adult men ages 20 years and older and tested racial and ethnic differences. We used data from the 1999 to 2016 National Health and Nutrition Examination Surveys for analyses. Obesity was determined using body mass index ≥30 kg/m2. We used poverty income ratio (PIR) as a proxy for income and calculated the Gini coefficient (GC) to measure income inequality. We then categorized low-, medium-, and high PIR to examine the relationship between income inequality and obesity. We used Modified Poisson regression in a sample of 17,238 adult men, including 9,511 White Non-Hispanic White (NHW), 4,166 Non-Hispanic Black (NHB), and 3,561 Mexican Americans (MA). We controlled the models for age category, racial and ethnic groups, marital status, education, health behaviors, health insurance coverage, self-reported health, comorbidity, and household structure. Results of our adjusted models suggested a positive and significant association between PIR and obesity among NHWs and NHBs in medium and high PIR; this association was not significant in MAs. Results of our analyses using GC in obese men indicate that compared with NHWs (GC: 0.306, SE: 0.004), MAs (GC: 0.368, SE: 0.005), and NHBs (GC: 0.328, SE: 0.005) had experienced higher-income inequality. In treating obesity, policymakers should consider race/ethnicity strategies to reduce inequality in income.

The intersection of welfare stigma, state contexts and health among mothers receiving public assistance benefits

The stigmatizing nature of the US welfare system is of particular importance not only because it has shown to deter eligible applicants from participating in public assistance programs despite facing economic hardship, but also because stigma is an important fundamental cause of health inequities. Although scholars agree stigma is shaped by individual and contextual dimensions, the role of context is often overlooked. Given the heterogeneous nature of US state welfare environments, it may be critical to consider the ways in which state policy, social and economic contexts condition the relationship between welfare stigma and health. Using a multilevel lens, this study first examined the impact of experienced and perceived welfare stigma on self-reported health among female public assistance recipients with children. Second, we assessed the moderating effect of uneven state TANF policies, income inequality, and negative public welfare attitudes in shaping these associations. Using data from the Fragile Families and Child Wellbeing Study merged with state-level economic and social measures, we employed a series of multilevel logit models with random effects. Findings show experiences and perceptions of welfare stigma are significantly linked to poor health regardless of state contexts, and outcomes vary markedly by race, ethnicity and education. States with strong anti-welfare attitudes amplified the relationship between experienced welfare stigma and poor health for Black and Hispanic mothers, and state economic contexts modified the relationship between experienced welfare stigma and poor health for mothers with less than a high school education. TANF generosity had no moderating effect on health suggesting state policy environments have limited ability to protect welfare recipients against the stigmatizing effects of the US welfare system. Results have implications for explaining stigma related disparities in health within the context of U.S. welfare environments and informing policies that may be key levers for reducing health inequities.

Rising childhood income inequality and declining Americans' health

Morbidity and mortality are on the rise among Baby Boomers and younger cohorts. This study investigates whether this unfavorable health trend across birth cohorts 1925-1999 is related to rising income inequality Americans face during childhood. We use two nationally representative datasets: National Health and Nutrition Examination Surveys (NHANES) 1988-2018 and Panel Studies of Income Dynamics (PSID) 1968-2013, and two health outcomes: biomarkers of physiological dysregulation, and a chronic disease index. Childhood income inequality is measured by the average of the Gini index at the national level each birth cohort is exposed to between birth and age 18, where the Gini index from 1925 to 2016 is computed based on Internal Revenue Service income data. By merging childhood income inequality to individual level data from NHANES or PSID based on birth cohort, we find childhood income inequality is positively associated with the risk of physiological dysregulation in adulthood for all gender and racial groups in the NHANES data. It is also significantly related to the risk of chronic disease in the PSID data. This association is robust to controls for individual level childhood health and family background, adulthood socioeconomic and marital status, and contemporary macro socioeconomic factors. More importantly, childhood income inequality exposure explains a substantial amount of variation in these two health outcomes across cohorts, a pattern not observed for other early life exposures that display negative temporal trends similar to those for childhood income inequality. This study provides important evidence that income inequality experienced during childhood may have a long-lasting negative consequence for adult health, which partially explains the adverse health trends experienced by Baby Boomers and younger cohorts in the United States.

Inequalities in Life Expectancy Across North Carolina: A Spatial Analysis of the Social Determinants of Health and the Index of Concentration at Extremes

Health inequalities are characterized by spatial patterns of social, economic, and political factors. Life expectancy (LE) is a commonly used indicator of overall population health and health inequalities that allows for comparison across different spatial and temporal regions. The objective of this study was to examine geographic inequalities in LE across North Carolina census tracts by comparing the performance of 2 popular geospatial health indices: Social Determinants of Health (SDoH) and the Index of Concentration at Extremes (ICE). A principal components analysis (PCA) was used to address multicollinearity among variables and aggregate data into components to examine SDoH, while the ICE was constructed using the simple subtraction of geospatial variables. Spatial regression models were employed to compare both indices in relation to LE to evaluate their predictability for population health. For individual SDoH and ICE components, poverty and income had the strongest positive correlation with LE. However, the common spatial techniques of adding PCA components together for a final SDoH aggregate measure resulted in a poor relationship with LE. Results indicated that both metrics can be used to determine spatial patterns of inequities in LE and that the ICE metric has similar success to the more computationally complex SDoH metric. Public health practitioners may find the ICE metric's high predictability matched with lower data requirements to be more feasible to implement in population health monitoring.

Assessing the causal relationship between income inequality and mortality and self-rated health: protocol for systematic review and meta-analysis

BACKGROUND

Income inequality has been linked to health and mortality. While there has been extensive research exploring the relationship, the evidence for whether the relationship is causal remains disputed. We describe the methods for a systematic review that will transparently assess whether a causal relationship exists between income inequality and mortality and self-rated health.

METHODS

We will identify relevant studies using search terms relating to income inequality, mortality, and self-rated health (SRH). Four databases will be searched: MEDLINE, ISI Web of Science, EMBASE, and the National Bureau of Economic Research. The inclusion criteria have been developed to identify the study designs best suited to assess causality: multilevel studies that have conditioned upon individual income (or a comparable measure, such as socioeconomic position) and natural experiment studies. Risk of bias assessment of included studies will be conducted using ROBINS-I. Where possible, we will convert all measures of income inequality into Gini coefficients and standardize the effect estimate of income inequality on mortality/SRH. We will conduct random-effects meta-analysis to estimate pooled effect estimates when possible. We will assess causality using modified Bradford Hill viewpoints and assess certainty using GRADE.

DISCUSSION

This systematic review protocol lays out the complexity of the relationship between income inequality and individual health, as well as our approach for assessing causality. Understanding whether income inequality impacts the health of individuals within a population has major policy implications. By setting out our methods and approach as transparently as we can, we hope this systematic review can provide clarity to an important topic for public policy and public health, as well as acting as an exemplar for other "causal reviews".

Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality

Background

Life expectancy is increasingly incorporated in evidence-based screening and treatment guidelines to facilitate patient-centered clinical decision-making. However, life expectancy estimates from standard life tables do not account for health status, an important prognostic factor for premature death. This study aims to address this research gap and develop life tables incorporating the health status of adults in the United States.

Methods

Data from the National Health Interview Survey (1986–2004) linked to mortality follow-up through to 2006 (age ≥ 40, n = 729,531) were used to develop life tables. The impact of self-rated health (excellent, very good, good, fair, poor) on survival was quantified in 5-year age groups, incorporating complex survey design and weights. Life expectancies were estimated by extrapolating the modeled survival probabilities.

Results

Life expectancies incorporating health status differed substantially from standard US life tables and by health status. Poor self-rated health more significantly affected the survival of younger compared to older individuals, resulting in substantial decreases in life expectancy. At age 40 years, hazards of dying for white men who reported poor vs. excellent health was 8.5 (95% CI: 7.0,10.3) times greater, resulting in a 23-year difference in life expectancy (poor vs. excellent: 22 vs. 45), while at age 80 years, the hazards ratio was 2.4 (95% CI: 2.1, 2.8) and life expectancy difference was 5 years (5 vs. 10). Relative to the US general population, life expectancies of adults (age < 65) with poor health were approximately 5–15 years shorter.

Conclusions

Considerable shortage in life expectancy due to poor self-rated health existed. The life table developed can be helpful by including a patient perspective on their health and be used in conjunction with other predictive models in clinical decision making, particularly for younger adults in poor health, for whom life tables including comorbid conditions are limited.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12332-0.

Neighborhood-Level Predictors of Age-at-First-Diagnosis of Psychotic Disorders: A Swedish Register-Based Cohort Study

The relationship between neighborhood-level factors and the incidence of psychotic disorders is well established. However, it is unclear whether neighborhood characteristics are also associated with age-at-first-diagnosis of these disorders. We used linked Swedish register data to identify a cohort of persons first diagnosed with an ICD-10 non-affective or affective psychotic disorder (F20-33) between 1997 and 2016. Using multilevel mixed-effect linear modelling, we investigated whether neighborhood deprivation and population density at birth were associated with age-at-first diagnosis of a psychotic disorder. Our final cohort included 13,440 individuals, with a median age-at-first-diagnosis of 21.8 years for women (interquartile range [IQR]: 19.0-25.5) and 22.9 years for men (IQR: 20.1-26.1; P < .0001). In an unadjusted model, we found no evidence of an association between neighborhood deprivation and age-at-first-diagnosis of psychotic disorder (P = .07). However, after multivariable adjustment, age-at-first-diagnosis increased by .13 years (95% CI: .05 to .21; P = .002) for a one standard deviation increase in neighborhood deprivation. This was equivalent to a later diagnosis of 47 days (95% CI: 18 to 77). We found no evidence of a different relationship for non-affective versus affective psychoses [LRT χ 2(1) = .14; P = .71]. Population density was not associated with age-at-first-diagnosis in unadjusted (P = .81) or adjusted (P = .85) models. Later age-at-first-diagnosis for individuals born in more deprived neighborhoods suggests structural barriers in accessing equitable psychiatric care.

How Income Inequality and Race/Ethnicity Drive Obesity in U.S. Adults: 1999-2016

Obesity is a major public health problem both globally and within the U.S. It varies by multiple factors, including but not limited to income and sex. After controlling for potential covariates, there is little evidence to determine the association between income and obesity and how obesity may be moderated by sex and family income. We examined the association between income and obesity in U.S. adults aged 20 years and older, and tested whether this relationship differs by race or ethnicity groups. For this analysis, we used data from the 1999-2016 National Health and Nutrition Examination Surveys (NHANES). Obesity was determined using Body Mass Index ≥ 30 kg/m2; the Gini coefficient (GC) was calculated to measure income inequality using the Poverty Income Ratio (PIR). We categorized the PIR into five quintiles to examine the relationship between income inequality and obesity. For the first set of analyses, we used a modified Poisson regression in a sample of 36,665 adults, with an almost equal number of men and women (women's ratio was 50.6%), including 17,303 white non-Hispanics (WNH), 7475 black non-Hispanics (BNHs), and 6281 Mexican Americans. The models included age, racial/ethnic groups, marital status, education, health behaviors (smoking and drinking status and physical activities), health insurance coverage, self-reported health, and household structure (live alone and size of household). Adjusting for potential confounders, our findings showed that the association between PIR and obesity was positive and significant more frequently among WNH and BNH in middle and top PIR quintiles than among lower-PIR quintiles; this association was not significant in Mexican Americans (MAs). Results of GC in obese women showed that in comparison with WNHs (GC: 0.34, S.E.: 0.002), BNHs (GC: 0.38, S.E.: 0.004) and MAs (GC: 0.41, S.E.: 0.006) experienced higher income inequality, and that BNH obese men experienced the highest income inequality (GC: 0.45, S.E.: 0.011). The association between PIR and obesity was significant among WNHs and BNHs men in the 3rd, 4th and 5th PIR quintiles. The same association was not found for women. In treating obesity, policymakers should consider not only race/ethnicity and sex, but also strategies to reduce inequality in income.

Family disability, poverty and parenting stress: Analysis of a cross-sectional study in Kenya

BACKGROUND

Households with a disabled member, be they a caregiver or a child, are poorer than households not affected by disability. Poverty, caregiving as a person with a disability and being the caregiver of a child with a disability can lead to increased parenting stress.

OBJECTIVES

The objective of this study was to examine whether parenting stress experienced by caregivers in a household with a disabled member is greater when the disabled member is the caregiver, or the child, and how much of these respective relationships is explained by poverty.

METHOD

We collected cross-sectional data using a demographic survey, the Washington Group Questions on adult disability, the 10 Questions on child disability and the Parenting Stress Index-Short Form, from 465 caregivers enrolled in a non-governmental child development programme in Kenya.

RESULTS

Households with a disabled member were poorer than households without a disabled member. Parenting stress of disabled caregivers was higher than parenting stress of non-disabled caregivers; however, this relationship disappeared when socio-economic status was controlled for. Caregivers of disabled children were more stressed than caregivers of non-disabled children, and this effect was not explained by differences in socio-economic status.

CONCLUSION

Our findings highlight the importance of developing a comprehensive understanding of the stressors facing households with a disabled member, particularly if that member is a child, so that supportive interventions can adequately cater to the needs of caregivers, and their children, in the context of poverty.

Anti-poverty policy and health: Attributes and diffusion of state earned income tax credits across U.S. states from 1980 to 2020

PURPOSE

The U.S. federal Earned Income Tax Credit (EITC) is often considered the most effective antipoverty program for families in the U.S., leading to a variety of improved outcomes such as educational attainment, work incentives, economic activity, income, and health benefits for mothers, infants and children. State EITC supplements to the federal credit can significantly enhance the magnitude of this intervention. In this paper we advance EITC and health research by: 1) describing the diffusion of state EITC policies over 40 years, 2) presenting patterns in important EITC policy dimensions across space and time, and 3) disseminating a robust data set to advance future research by policy analysts and scientists.

METHODS

We used current public health law research methods to systematically collect, conduct textual legal analysis, and numerically code all EITC legislative changes from 1980 through 2020 in the 50 states and Washington, D.C.

RESULTS

First, the pattern of diffusion across states and time shows initial introductions during the 1990s in the Midwest, then spreading to the Northeast, with more recent expansions in the West and South. Second, differences by state and time of important policy dimensions are evident, including size of credit and refundability. Third, state EITC benefits vary considerably by household structure.

CONCLUSION

Continued research on health outcomes is warranted to capture the full range of potential beneficial effects of EITCs on family and child wellbeing. Lawyers and policy analysts can collaborate with epidemiologists and economists on other high-quality empirical studies to assess the many dimensions of policy and law that potentially affect the social determinants of health.

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.

Income inequality and racial disparities in pregnancy-related mortality in the US

In this ecological study, we examined the associations between state-level income inequality and pregnancy-related mortality among non-Hispanic (NH) black and NH white populations across the US. We estimated total population and race-specific 5-year pregnancy-related mortality ratios in each state based on national death and live birth records from 2011 to 2015. We obtained data on Gini coefficients for income inequality and population-level characteristics from the US Census American Community Survey. Poisson regression with robust standard errors estimated pregnancy-related mortality rate ratios (RR) and 95% confidence intervals (CI) associated with a one unit increase in income inequality overall and separately within black and white populations. Adjusted linear regression models estimated the associations between income inequality and magnitude of the absolute and relative racial inequity in pregnancy-related mortality within states. Across all states, increasing contemporaneous income inequality was associated with a 15% and 5-year lagged inequality with 14% increase in pregnancy-related mortality among black women (aRR = 1.15, 95% CI = 1.05; 1.25 and aRR = 1.14, 95% CI = 1.04; 1.24, respectively) after controlling for states' racial compositions and socio-economic conditions. In addition, both lagged and contemporaneous income inequality were associated with larger absolute and relative racial inequities in pregnancy-related mortality. These findings highlight the role of contextual factors in contributing to pregnancy-related mortality among black women and the persistent racial inequity in maternal death in the US.

Characteristics of place and the rural disadvantage in deaths from highly preventable causes

Extensive research has documented higher mortality in rural parts of the United States compared to urban areas. Much of this work focuses on aggregate rates, documenting a rural mortality penalty that has been increasing over the last three decades. Advances in place-based analyses suggest the importance of community resources for individual mortality but have largely focused on urban spaces. We advance knowledge on rural-urban mortality disparities by focusing on differences for highly preventable causes of death. Using unique geocoded mortality records from Washington state, we match individual-level attributes with area-level measures of socioeconomic conditions to examine whether characteristics of place elucidate the rural mortality penalty. We find that rural decedents have greater odds of dying from highly preventable causes compared to their urban counterparts. Place-based socioeconomic measures, meanwhile, independently associate with the odds of dying from highly preventable causes. However, we find no evidence that the relationship between socioeconomic conditions and highly preventable death varies across geographic contexts.

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.

Neighborhood Deprivation and Risks of Autoimmune Disorders: A National Cohort Study in Sweden

Background: No study to date, as far as we know, has analyzed the potential effect of neighborhood-level deprivation on autoimmune disorders (ADs), when adjusted for individual-level characteristics. Methods: A total of 5.4 million individuals from 8363 neighborhoods, comprising the whole Swedish population (ages 25–74 years), were followed for the period 1 January 2000, until admission due to diagnosis of ADs during the period of the study, or the conclusion of the study (31 December 2010). We used a neighborhood deprivation index, constructed from variables such as low education, low income, unemployment, and social welfare assistance, to assess the level of neighborhood deprivation. Multilevel logistic regression was used in the analysis with individual level characteristics at the first level and level of neighborhood deprivation at the second level. Results: A significant association between level of neighborhood deprivation and ADs was found. The crude odds were 1.32 (95% confidence interval 1.27–1.36) for those residing in the high-deprived neighborhoods compared to those living in low-deprivation neighborhoods. In the full model, where individual level characteristics were taken into account, the odds of ADs were 1.18 (1.14–1.22) in the most deprived neighborhoods. Certain Ads—angiitis hypersensitive (5.14), ankylosing spondylitis (1.66), celiac disease (1.65), Crohn’s disease (1.21), diabetes mellitus type 1 (1.45), Graves’s disease (1.13), Hashimoto thyroiditis (1.51), psoriasis (1.15), rheumatoid arthritis (1.15), sarcoidosis (1.20), and systemic sclerosis (1.27)—remained significantly associated with high level of neighborhood deprivation after adjustment for the individual-level variables. Conclusion: This study is the largest to date analyzing the potential influence of neighborhood deprivation on ADs. Our results indicate that neighborhood deprivation may affect risk of ADs, independent of individual level sociodemographic characteristics. For health care policies, both individual and neighborhood level approaches seem to be of importance.

Local Area Variation in Morbidity Among Low-Income, Older Adults in the United States: A Cross-sectional Study

Background

Recent studies have reported that low-income adults living in more affluent areas of the United States have longer life expectancies. Less is known about the relationship between the affluence of a geographic area and morbidity of the low-income population.

Objective

To evaluate the association between the prevalence of chronic conditions among low-income, older adults and the economic affluence of a local area.

Design

Cross-sectional association study.

Setting

Medicare in 2015.

Participants

6 363 097 Medicare beneficiaries aged 66 to 100 years with a history of low-income support under Medicare Part D.

Measurements

Adjusted prevalence of 48 chronic conditions was computed for 736 commuting zones (CZs). Factor analysis was used to assess spatial covariation of condition prevalence and to construct a composite condition prevalence index for each CZ. The association between morbidity and area affluence was measured by comparing the average of condition prevalence index across deciles of median CZ house values.

Results

The mean age of study participants was 77.7 years (SD, 8.2); 67% were women, and 61% were white. The crude prevalence of 48 chronic conditions ranged from 72.5 per 100 for hypertension to 0.6 per 100 for posttraumatic stress disorder. The prevalence of these 48 chronic conditions was highly spatially correlated. Composite condition prevalence was on average substantially lower in more affluent CZs.

Limitation

Low-income status measured on the basis of receipt of Medicare Part D low-income subsidies and not capturing persons not enrolled in Medicare Part D.

Conclusion

Low-income, older adults living in more affluent areas of the country are healthier, and areas with poor health in the low-income, older adult population tend to have a high prevalence of most chronic conditions.

Primary Funding Source

National Institute on Aging.

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.

Assessing Temporal and Spatial Inequality of Water Footprint Based on Socioeconomic and Environmental Factors in Jilin Province, China

Freshwater resources are limited and uneven in their spatiotemporal distribution, and substantial increases in water demand from rapidly developing economies and concentrated populations place pressure on the available water. Research on the inequality of water footprint (WF) could provide countermeasures for the rational use and allocation of water resources. We evaluated the temporal and spatial inequality of WF using the Gini coefficient and imbalance index based on socioeconomic and environmental factors in Jilin Province. The results showed that from 2008 to 2015, the overall inequality of WF in Jilin Province was “relative equality”, and the inequalities between the WF and population, cultivated area were “high equality”; between the WF and gross domestic product (GDP) was “relative equality”; and between the WF and natural water endowment was “high inequality”. With respect to space, the differences of WF inequality were significant. In the west, the WF inequality changed greatly, from “relative equality” to “relative inequality” driven by population, GDP, cultivated area, and natural water endowment. In the middle, the WF inequality showed large internal differences with “high inequality” or “high equality” caused by GDP and natural water endowment. In the east, the WF inequality was relatively stable, at “high equality” or “neutral” affected by natural water endowment and population. The varied impact factors reflected the differences in natural resources and socioeconomic conditions in the various regions, and the results might provide a theoretical basis for guiding the rational allocation of water resources.

Urbanization, cities, and health: The challenges to Nigeria - A review

The Nigerian society is rapidly becoming urban as a result of a multitude of push and pull factors. This has generated urban health crises among city dwellers notably the urban poor. A systematic search of published literature in English was conducted between 1960 and 2015. Published peer review journals, abstracts, Gray literature (technical reports, government documents, reports, etc.), inaugural lectures, and internet articles were reviewed. Manual search of reference lists of selected articles were checked for further relevant studies. The review showed that the pace of urbanization is unprecedented with cities such as Lagos having annual urban growth rate of 5.8%. Urbanization in Nigeria is mainly demographically driven without commensurate socioeconomic dividends and benefits to the urban environment. This has created urban health crises of inadequate water safe supply, squalor and shanty settlements, sanitation, solid waste management, double burden of diseases and inefficient, congested, and risky transport system. In conclusion, when managed carefully, urbanization could reduce hardship and human suffering; on the other hand, it could also increase poverty and squalor. Some laws need to be amended to change the status of poor urban settlements. Urban health development requires intersectoral approach with political will and urban renewal program to make our urban societies sustainable that promote healthy living.

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.

Effect of Area-Level Deprivation on Cancer Survival Time: A Register-Based Follow-up Study of 145 585 Korean Subjects

Our goal is to evaluate the strengths of the associations between area-level deprivation and survival time for a variety of cancers. A total of 145 585 subjects were diagnosed with various cancers in Busan, Korea, and an area-level deprivation index constructed from several important socioeconomic variables. A multilevel Cox model was used in the analysis to investigate the effects of multiple risk factors. After adjusting for gender and age, an increased area-level deprivation index was found to be significantly associated with a higher hazard rate for major cancers. Estimated hazard ratios (95% confidence interval) were 1.08 (1.06, 1.11), 1.15 (1.13, 1.18), and 1.22 (1.18, 1.25) for the second, third, and fourth quartiles of deprivation index groups, respectively, when compared with the least deprived group. When compared with the least deprived group, the more deprived group showed significant decrease in survival time for major cancers. This finding highlights the importance of preventive and care services incorporating socioeconomic characteristics of areas.

Income disparity and mortality among patients with alcohol use disorder in South Korea

Problems related to alcohol consumption, particularly alcohol disorders, occur frequently in South Korea and are gradually increasing due to the drinking culture and social atmosphere. We analyzed the relationship between mortality and income among patients with alcohol disorders. We used data from the National Sampling Claim Data 2003-2013, which included medical claims filed for 10,593 patients newly diagnosed with alcohol disorders. We performed survival analyses using a Cox proportional hazards model. 12.79% died during the study period. Patients with lower incomes were more positively associated with the risk of mortality than those with higher incomes (0-30 percentile: hazard ratio [HR] = 1.432, 95% confidence interval [CI] = 1.155-1.777; 31-60 percentile: HR = 1.318, 95% CI = 1.065-1.633; 61-90 percentile: HR = 1.352, 95% CI = 1.097-1.665; 91-100 percentile: ref). Such associations were significant in males, patients with mild conditions, or those who lived in metropolitan areas. In conclusion, we found that income disparity was related to mortality among patients diagnosed with disorders due to alcohol use. Thus, healthcare professionals need to provide active intervention in the early phase of alcohol disorders, and consider policy that would improve healthcare accessibility for low-income populations in order to reduce income disparity.

Disparities by Age, Sex, Tumor Stage, Diagnosis Path, and Area-level Socioeconomic Status in Survival Time for Major Cancers: Results from the Busan Cancer Registry

Our goal was to examine the effect of area-level deprivation on patient survival time for seven major cancers - stomach, colon, liver, lung, breast, cervix, and thyroid cancer. Data on 10,902 subjects who were diagnosed with major cancers from 2010 and 2011 in Busan were collected regarding the survival time along with several important prognostic factors and an area-level deprivation index was constructed from education, income, unemployment, and welfare assistance, to assess the comprehensive area-level socioeconomic status. A multilevel Cox proportional hazard model was used to investigate the effects of multiple risk factors such as gender, age, tumor stage, diagnosis path, and the area-level deprivation. After adjusting for risk factors the area-level deprivation index was found to be significant in associating with higher hazard rate for several cancers. Estimated hazard ratios (95% CI) were 1.08 (0.99-1.18), 1.23 (1.12-1.36), 1.36 (1.21-1.53) for the second, the third, and the fourth quartile of deprivation index groups, respectively, when compared to the least deprived group. When compared with the least deprived group, the more deprived group showed significant decrease in survival time for major cancers. This novel finding may contribute to the literature regarding the association of area-level socioeconomic status and highlight the importance of careful monitoring of socioeconomic characteristics for cancer prevention and care services.

National income inequality and ineffective health insurance in 35 low- and middle-income countries

Global health policy efforts to improve health and reduce financial burden of disease in low- and middle-income countries (LMIC) has fuelled interest in expanding access to health insurance coverage to all, a movement known as Universal Health Coverage (UHC). Ineffective insurance is a measure of failure to achieve the intended outcomes of health insurance among those who nominally have insurance. This study aimed to evaluate the relation between national-level income inequality and the prevalence of ineffective insurance. We used Standardized World Income Inequality Database (SWIID) Gini coefficients for 35 LMICs and World Health Survey (WHS) data about insurance from 2002 to 2004 to fit multivariable regression models of the prevalence of ineffective insurance on national Gini coefficients, adjusting for GDP per capita. Greater inequality predicted higher prevalence of ineffective insurance. When stratifying by individual-level covariates, higher inequality was associated with greater ineffective insurance among sub-groups traditionally considered more privileged: youth, men, higher education, urban residence and the wealthiest quintile. Stratifying by World Bank country income classification, higher inequality was associated with ineffective insurance among upper-middle income countries but not low- or lower-middle income countries. We hypothesize that these associations may be due to the imprint of underlying social inequalities as countries approach decreasing marginal returns on improved health insurance by income. Our findings suggest that beyond national income, income inequality may predict differences in the quality of insurance, with implications for efforts to achieve UHC.

Associations of cause-specific mortality with area level deprivation and travel time to health care in France from 1990 to 2007, a multilevel analysis

Background

It is now widely accepted that social and physical environment participate in shaping health. While mortality is used to guide public health policies and is considered as a synthetic measure of population health, few studies deals with the contextual features potentially associated with mortality in a representative sample of an entire country. This paper investigates the possible role of area deprivation (FDep99) and travel time to health care on French cause-specific mortality in a proper multilevel setting.

Methods

The study population was a 1% sample representative of the French population aged from 30 to 79 years in 1990 and followed up until 2007. A frailty Cox model was used to measure individual, contextual effects and spatial variances for several causes of death. The chosen contextual scale was the Zone d’Emploi of 1994 (348 units) which delimits the daily commute of people. The geographical accessibility to health care score was constructed with principal component analysis, using 40 variables of hospital specialties and health practitioners’ travel time.

Results

The outcomes highlight a positive and significant association between area deprivation and mortality for all causes (HR = 1.24), cancers, cerebrovascular diseases, ischemic heart diseases, and preventable and amenable diseases (HR from 1.14 to 1.29). These contextual associations exhibit no substantial differences by sex except for premature ischemic heart diseases mortality which was much greater in women. Unexpectedly, mortality decreased as the time to reach health care resources increased. Only geographical disparities in cerebrovascular and ischemic heart diseases mortality were explained by compositional and contextual effects.

Discussion

The findings suggest the presence of confounding factors in the association between mortality and travel time to health care, possibly owing to population density and health-selected migration. Although the spatial scale considered to define the context of residence was relatively large, the associations with area deprivation were strong in comparison to the existing literature and significant for almost all the causes of deaths investigated.

Conclusion

The broad spectrum of diseases associated with area deprivation and individual education support the idea of a need for a global health policy targeting both individual and territories to reduce social and socio-spatial inequalities.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-017-4562-7) contains supplementary material, which is available to authorized users.

Examining Health Inequalities in Latvia: A Decade of Association between Socioeconomic Position and Perceived Health Status

The relationship between socioeconomic position (SEP) and population health is contextual. This study identifies the determinants of SEP producing health inequalities in the Latvian population. We also estimate the proportional contribution of different socioeconomic strata- (SES-) related determinants in Latvian health inequalities and measure the changes in the relative contributions of such determinants over the period 2005–2015. Using the household survey data (2005–2015), we construct a principal component analysis based SES index. A regression-based concentration index (CI) is our measure of health inequality to examine the distribution of perceived health status. Finally, we identify and estimate the contribution of predictors of health inequalities by decomposing CI with Oaxaca-Blinder decomposition. SES-related health inequalities have declined from 2005 (CI: 0.201) to 2015 (CI: 0.137) in Latvia—better-off Latvians enjoyed better perceived health during that period. The proportional contributions of education and working status have increased in 2015 compared to 2005. Although we have generated the first evidence to suggest policy relevant measures in addressing Latvian health inequalities, our decomposition method explains the extent of variation in perceived health instead of covariance between health and SEP.

Neighbourhood Deprivation, Individual-Level and Familial-Level Socio-demographic Factors and Risk of Congenital Heart Disease: A Nationwide Study from Sweden

OBJECTIVES

The purpose of the study is to examine whether there is an association between neighbourhood deprivation and incidence of congenital heart disease (CHD), after accounting for family- and individual-level potential confounders.

METHODS

All children aged 0 to 11 years and living in Sweden (n = 748,951) were followed between January 1, 2000 and December 31, 2010. Data were analysed by multilevel logistic regression, with family- and individual-level characteristics at the first level and level of neighbourhood deprivation at the second level.

RESULTS

During the study period, among a total of 748,951 children, 1499 (0.2%) were hospitalised with CHD. Age-adjusted cumulative hospitalisation rates for CHD increased with increasing level of neighbourhood deprivation. In the study population, 1.8 per 1000 and 2.2 per 1000 children in the least and most deprived neighbourhoods, respectively, were hospitalised with CHD. The incidence of hospitalisation for CHD increased with increasing neighbourhood-level deprivation across all family and individual-level socio-demographic categories. The odds ratio (OR) for hospitalisation for CHD for those living in high-deprivation neighbourhoods versus those living in low-deprivation neighbourhoods was 1.23 (95% confidence interval (CI) = 1.04-1.46). In the full model, which took account for age, paternal and maternal individual-level socio-economic characteristics, comorbidities (e.g. maternal type 2 diabetes, OR = 3.03; maternal hypertension, OR = 2.01), and family history of CHD (OR = 3.27), the odds of CHD were slightly attenuated but did not remain significant in the most deprived neighbourhoods (OR = 1.20, 95% CI = 0.99-1.45, p = 0.057).

CONCLUSIONS

This study is the largest so far on neighbourhood influences on CHD, and the results suggest that deprived neighbourhoods have higher rates of CHD, which represents important clinical knowledge. However, the association does not seem to be independent of individual- and family-level characteristics.

The Great Recession and America's Geography of Unemployment

BACKGROUND

The Great Recession of 2007-2009 was the most severe and lengthy economic crisis in the U.S. since the Great Depression. The impacts on the population were multi-dimensional, but operated largely through local labor markets.

OBJECTIVE

To examine differences in recession-related changes in county unemployment rates and assess how population and place characteristics shaped these patterns.

METHODS

We calculate and decompose Theil Indexes to describe recession-related changes in the distribution of unemployment rates between counties and states. We use exploratory spatial statistics to identify geographic clusters of counties that experienced similar changes in unemployment. We use spatial regression to evaluate associations between county-level recession impacts on unemployment and demographic composition, industrial structure, and state context.

RESULTS

The recession was associated with increased inequality between county labor markets within states, but declining between-state differences. Counties that experienced disproportionate recession-related increases in unemployment were spatially clustered and characterized by large shares of historically disadvantaged racial and ethnic minority populations, low educational attainment, and heavy reliance on pro-cyclical industries. Associations between these sources of vulnerability were partially explained by unobserved state-level factors.

CONCLUSIONS

The local consequences of macroeconomic trends are associated with county population characteristics, as well as the structural contexts and policy environments in which they are embedded. The recession placed upward pressure on within-state inequality between local labor market conditions.

CONTRIBUTION

To present new estimates of the recession's impact on local labor markets, quantify how heterogeneous impacts affected the distribution of unemployment prevalence, and identify county characteristics associated with disproportionately large recession-related increases in unemployment.

The Association Between Income and Life Expectancy in the United States, 2001-2014

IMPORTANCE

The relationship between income and life expectancy is well established but remains poorly understood.

OBJECTIVES

To measure the level, time trend, and geographic variability in the association between income and life expectancy and to identify factors related to small area variation.

DESIGN AND SETTING

Income data for the US population were obtained from 1.4 billion deidentified tax records between 1999 and 2014. Mortality data were obtained from Social Security Administration death records. These data were used to estimate race- and ethnicity-adjusted life expectancy at 40 years of age by household income percentile, sex, and geographic area, and to evaluate factors associated with differences in life expectancy.

EXPOSURE

Pretax household earnings as a measure of income.

MAIN OUTCOMES AND MEASURES

Relationship between income and life expectancy; trends in life expectancy by income group; geographic variation in life expectancy levels and trends by income group; and factors associated with differences in life expectancy across areas.

RESULTS

The sample consisted of 1,408,287,218 person-year observations for individuals aged 40 to 76 years (mean age, 53.0 years; median household earnings among working individuals, $61,175 per year). There were 4,114,380 deaths among men (mortality rate, 596.3 per 100,000) and 2,694,808 deaths among women (mortality rate, 375.1 per 100,000). The analysis yielded 4 results. First, higher income was associated with greater longevity throughout the income distribution. The gap in life expectancy between the richest 1% and poorest 1% of individuals was 14.6 years (95% CI, 14.4 to 14.8 years) for men and 10.1 years (95% CI, 9.9 to 10.3 years) for women. Second, inequality in life expectancy increased over time. Between 2001 and 2014, life expectancy increased by 2.34 years for men and 2.91 years for women in the top 5% of the income distribution, but by only 0.32 years for men and 0.04 years for women in the bottom 5% (P < .001 for the differences for both sexes). Third, life expectancy for low-income individuals varied substantially across local areas. In the bottom income quartile, life expectancy differed by approximately 4.5 years between areas with the highest and lowest longevity. Changes in life expectancy between 2001 and 2014 ranged from gains of more than 4 years to losses of more than 2 years across areas. Fourth, geographic differences in life expectancy for individuals in the lowest income quartile were significantly correlated with health behaviors such as smoking (r = -0.69, P < .001), but were not significantly correlated with access to medical care, physical environmental factors, income inequality, or labor market conditions. Life expectancy for low-income individuals was positively correlated with the local area fraction of immigrants (r = 0.72, P < .001), fraction of college graduates (r = 0.42, P < .001), and government expenditures (r = 0.57, P < .001).

CONCLUSIONS AND RELEVANCE

In the United States between 2001 and 2014, higher income was associated with greater longevity, and differences in life expectancy across income groups increased over time. However, the association between life expectancy and income varied substantially across areas; differences in longevity across income groups decreased in some areas and increased in others. The differences in life expectancy were correlated with health behaviors and local area characteristics.

Neighborhood Deprivation and Risk of Age-Related Eye Diseases: A Follow-up Study in Sweden

PURPOSE

To examine whether there is an association between neighborhood deprivation and age-related eye diseases, particularly macular degeneration, cataract, diabetes-related eye complications, and glaucoma.

METHODS

The study population comprised a nationwide sample of 2,060,887 men and 2,250,851 women aged 40 years or older living in Sweden who were followed from 1 January 2000 until the first hospitalization/outpatient registration for age-related eye disease during the study period, death, emigration, or the end of the study period on 31 December 2010. Multilevel logistic regression was used to estimate the association between neighborhood deprivation and age-related eye diseases.

RESULTS

In men, the odds ratio (OR) for age-related eye diseases for those living in high-deprivation neighborhoods compared to those living in low-deprivation neighborhoods remained significant after adjustment for potential confounding factors (macular degeneration, OR 1.08, 95% confidence interval [CI] 1.03-1.12; cataract, OR 1.31, 95% CI 1.26-1.35; diabetes-related eye complications, OR 1.36, 95% CI 1.30-1.43; glaucoma, OR 1.11, 95% CI 1.06-1.15). In women, similar patterns were observed (macular degeneration, OR 1.11, 95% CI 1.07-1.15; cataract, OR 1.36, 95% CI 1.31-1.40; diabetes-related eye complications, OR 1.50, 95% CI 1.42-1.59; glaucoma, OR 1.12, 95% CI 1.08-1.17).

CONCLUSION

Our results suggest that neighborhood deprivation is associated with age-related eye diseases in both men and women. These results implicate that individual- as well as neighborhood-level factors are important for preventing age-related eye diseases.

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.

Comparing and decomposing the determinants of multiple health outcomes in southern and northeastern US states using county data

Objectives

To investigate whether regional health disparities could explain health outcome differences between US regions.

Methods

The 2010–2012 County Level Raking database, which contains measures on health outcomes and factors for the US states, are used in this study. First, a regional comparison of the determinants of various health outcome measures (premature death rates, low birth weight rate and mean unhealthy days) is undertaken. Next, using the Blinder–Oaxaca decomposition method, the differences in health outcomes are partitioned into the portion explained by regional health factor endowments and the portion unexplained.

Key findings

Obesity rate and access to care determinants impact strongly each region's health outcomes. Half of the differences in clinically assessed (premature death rates and low birth weight rates) measures are unexplained by health endowments. The explained portion for the self-assessed (unhealthy days) outcomes is small.

Conclusions

Study findings both justify the imperatives of accounting for regional variations in order to strengthen policy inferences of research findings and suggest the prevalence of regional disparities in health outcomes. It is important to focus on region-specific preventive care. More effective public education and information strategies raising population awareness to the health hazards of obesity are in order. Greater access to various health services personnel should be provided to the relevant population. Implications are discussed for pharmaceutical care.

Inequalities of Income and Inequalities of Longevity: A Cross-Country Study

OBJECTIVES

We examined the effects of market income inequality (income inequality before taxes and transfers) and income redistribution via taxes and transfers on inequality in longevity.

METHODS

We used life tables to compute Gini coefficients of longevity inequality for all individuals and for individuals who survived to at least 10 years of age. We regressed longevity inequality on market income inequality and income redistribution, and we controlled for potential confounders, in a cross-sectional time-series sample of up to 28 predominantly Western developed countries and up to 37 years (1974-2011).

RESULTS

Income inequality before taxes and transfers was positively associated with inequality in the number of years lived; income redistribution (the difference between market income inequality and income inequality after taxes and transfers were accounted for) was negatively associated with longevity inequality.

CONCLUSIONS

To the extent that our estimated effects derived from observational data are causal, governments can reduce longevity inequality not only via public health policies, but also via their influence on market income inequality and the redistribution of incomes from the relatively rich to the relatively poor.

Are older adults living in more equal counties healthier than older adults living in more unequal counties? A propensity score matching approach

We assessed the potential contextual effect of income inequality on health by: 1) comparing individuals with similar socioeconomic status (SES) but who reside in counties with different levels of income inequality; and 2) examining whether the potential effect of county-level income inequality on health varies across SES groups. We used the Health and Retirement Study, a nationally representative study of Americans over the age of 50. Using propensity score matching, we selected SES-comparable individuals living in high-income inequality counties and in low-income inequality counties. We examined differences in self-rated overall health outcomes and in other specific physical/mental health outcomes between the two groups using logistic regression (n = 34,994) and imposing different sample restrictions based on residential duration in the area. We then used logistic regression with interactions to assess whether, and if so how, health outcomes differed among participants of different SES groups defined by wealth, income, and education. In bivariate analyses of the unmatched full sample, adults living in high-income inequality counties have worse health outcomes for most health measures. After propensity score matching, adults in high-income inequality counties had worse self-rated health status (AOR = 1.12; 95% CI 1.04-1.19) and were more likely to report diagnosed psychiatric problems (AOR = 1.08; 95% CI 0.99-1.19) than their matched counterparts in low-income inequality counties. These associations were stronger with longer-term residents in the area. Adverse health outcomes associated with living in high-income inequality counties were significant particularly for individuals in the 30(th) or greater percentiles of income/wealth distribution and those without a college education. In summary, after using more precise matching methods to compare individuals with similar characteristics and addressing measurement error by excluding more recently arrived county residents, adults living in high-income inequality counties had worse reported overall physical and mental health than adults living in low-income inequality counties.

The association between income inequality and all-cause mortality across urban communities in Korea

BACKGROUND

Korea has achieved considerable economic growth more rapidly than most other countries, but disparities in income level have increased. Therefore, we sought to assess the association between income inequality and mortality across Korean cities.

METHODS

Data on household income were obtained from the 2010-2012 Korean Community Health Survey and data on all-cause mortality and other covariates were obtained from the Korean Statistical Information Service. The Gini coefficient, Robin Hood index, and income share ratio between the 80th and 20th percentiles of the distribution were measured for each community. After excluding communities affected by changes in administrative districts between 2010 and 2012, a total of 157 communities and 172,398 urban residents were included in the analysis.

RESULTS

When we graphed income inequality measures versus all-cause mortality as scatter plots, the R square values of the regression lines for GC, RHI, and 80/20 ratios relative to mortality were 0.230, 0.238, and 0.152, respectively. After adjusting for other covariates and median household income, mean all-cause mortality increased significantly with increasing GC (P for trend = 0.014) and RHI (P for trend = 0.031), and increased marginally with 80/20 ratio (P for trend = 0.067).

CONCLUSIONS

Our data demonstrate that income inequality measures are significantly associated with all-cause mortality rate after adjustment for covariates, including median household income across urban communities in Korea.

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.

Social vulnerability from a social ecology perspective: a cohort study of older adults from the National Population Health Survey of Canada

Background

Numerous social factors, generally studied in isolation, have been associated with older adults’ health. Even so, older people’s social circumstances are complex and an approach which embraces this complexity is desirable. Here we investigate many social factors in relation to one another and to survival among older adults using a social ecology perspective to measure social vulnerability among older adults.

Methods

2740 adults aged 65 and older were followed for ten years in the Canadian National Population Health Survey (NPHS). Twenty-three individual-level social variables were drawn from the 1994 NPHS and five Enumeration Area (EA)-level variables were abstracted from the 1996 Canadian Census using postal code linkage. Principal Component Analysis (PCA) was used to identify dimensions of social vulnerability. All social variables were summed to create a social vulnerability index which was studied in relation to ten-year mortality.

Results

The PCA was limited by low variance (47%) explained by emergent factors. Seven dimensions of social vulnerability emerged in the most robust, yet limited, model: social support, engagement, living situation, self-esteem, sense of control, relations with others and contextual socio-economic status. These dimensions showed complex inter-relationships and were situated within a social ecology framework, considering spheres of influence from the individual through to group, neighbourhood and broader societal levels. Adjusting for age, sex, and frailty, increasing social vulnerability measured using the cumulative social vulnerability index was associated with increased risk of mortality over ten years in a Cox regression model (HR 1.04, 95% CI:1.01-1.07, p = 0.01).

Conclusions

Social vulnerability has important independent influence on older adults’ health though relationships between contributing variables are complex and do not lend themselves well to fragmentation into a small number of discrete factors. A social ecology perspective provides a candidate framework for further study of social vulnerability among older adults.

Neighborhood deprivation and childhood autism: a nationwide study from Sweden

OBJECTIVE

To examine whether there is an association between neighborhood deprivation and childhood autism, after accounting for family- and individual-level sociodemographic characteristics.

METHODS

An open cohort of all children aged 2-11 years was followed between January 1, 2000 and December 31, 2010. Childhood residential locations were geocoded and classified according to neighborhood deprivation (an index of low education, low income, unemployment, and receipt of welfare assistance). Data were analyzed by multilevel logistic regression, with family- and individual-level characteristics at the first level and level of neighborhood deprivation at the second level.

RESULTS

During the study period, among a total of 643,456 children, 1699 (0.3%) were diagnosed with childhood autism. Age-standardized cumulative incidence, defined as first registration for childhood autism during the study period, increased with increasing level of neighborhood deprivation. In the study population, 2.2 per 1000 and 3.6 per 1000 children in the least and most deprived neighborhoods, respectively, were diagnosed with childhood autism. Incidence of childhood autism increased with increasing neighborhood-level deprivation across all family and individual-level sociodemographic categories. The odds ratio (OR) for childhood autism for those living in high-deprivation neighborhoods versus those living in low-deprivation neighborhoods was 1.59 (95% confidence interval = 1.35-1.88). High neighborhood deprivation remained significantly associated with odds of childhood autism after adjustment for family- and individual-level sociodemographic characteristics (OR = 1.28, 95% confidence interval = 1.07-1.53, P = 0.007).

CONCLUSIONS

This study is the largest so far on potential neighborhood influences on childhood autism. Our results show that neighborhood deprivation is associated with childhood autism, independently of family- and individual-level sociodemographic characteristics.

Income inequality and child maltreatment in the United States

OBJECTIVE

To examine the relation between county-level income inequality and rates of child maltreatment.

METHODS

Data on substantiated reports of child abuse and neglect from 2005 to 2009 were obtained from the National Child Abuse and Neglect Data System. County-level data on income inequality and children in poverty were obtained from the American Community Survey. Data for additional control variables were obtained from the American Community Survey and the Health Resources and Services Administration Area Resource File. The Gini coefficient was used as the measure of income inequality. Generalized additive models were estimated to explore linear and nonlinear relations among income inequality, poverty, and child maltreatment. In all models, state was included as a fixed effect to control for state-level differences in victim rates.

RESULTS

Considerable variation in income inequality and child maltreatment rates was found across the 3142 US counties. Income inequality, as well as child poverty rate, was positively and significantly correlated with child maltreatment rates at the county level. Controlling for child poverty, demographic and economic control variables, and state-level variation in maltreatment rates, there was a significant linear effect of inequality on child maltreatment rates (P < .0001). This effect was stronger for counties with moderate to high levels of child poverty.

CONCLUSIONS

Higher income inequality across US counties was significantly associated with higher county-level rates of child maltreatment. The findings contribute to the growing literature linking greater income inequality to a range of poor health and well-being outcomes in infants and children.