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

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

Modelling health,income and income inequality: the impact of income inequality on health and health inequality

A framework is developed to analyse the impact of the distribution of income on individual health and health inequality, with individual health modelled as a function of income and the distribution of income. It is demonstrated that the impact of income inequality can generate non-concave health production functions resulting in a non-concave health production possibility frontier. In this context, the impact of different health policies are considered and it is argued that if the distribution of income affects individual health, any policy aimed at equalising health, which does not account for income inequality, will lead to unequal distributions of health. This is an important development given current UK government attention to reducing health inequality.     

The effects of U.S. county and state income inequality on self-reported happiness and health are equivalent to zero

Quality of Life Research - A popular idea in the social sciences is that contexts with high income inequality undermine people’s well-being and health. However, existing studies documenting...     

Aggregation and the measurement of income inequality: effects on morbidity

This is a cross-sectional study using records from the National Health Interview Survey linked to Census geography. The sample is restricted to white males ages 25-64 in the United States from three years (1989-1991) of the National Health Interview Survey. Perceived health is used to measure morbidity. Individual covariates include income-to-needs ratio, education and occupation. Contextual level measures of income inequality, median household income and percent in poverty are constructed at the US census county and tract level. The association between inequality and morbidity is examined using logistic regression models. Income inequality is found to exert an independent adverse effect on self-rated health at the county level, controlling for individual socioeconomic status and median income or percent poverty in the county. This corresponding effect at the tract level is reduced. Median income or percent poverty and individual socioeconomic status are the dominant correlates of perceived health status at the tract level. These results suggest that the level of geographic aggregation influences the pathways through which income inequality is actualized into an individuals' morbidity risk. At higher levels of aggregation there are independent effects of income inequality, while at lower levels of aggregation, income inequality is mediated by the neighborhood consequences of income inequality and individual processes.     

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

ObjectiveTo investigate government state and local spending on public goods and income inequality as predictors of the risks of dying.MethodsData 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.ResultsEach 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.ConclusionsEmpirical 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.     

The association between state income inequality and worse health is not confounded by race

BACKGROUND: The relationship between income inequality and health across US states has been challenged recently on grounds that this relationship may be confounded by the effect of racial composition, measured as the proportion of the state's population who are black. METHODS: Using multilevel statistical models, we examined the association between state income inequality and poor self-rated health. The analysis was based on the pooled 1995 and 1997 Current Population Surveys, comprising 201 221 adults nested within 50 US states. RESULTS: Controlling for the individual effects of age, sex, race, marital status, education, income, health insurance coverage, and employment status, we found a significant effect of state income inequality on poor self-rated health. For every 0.05-increase in the Gini coefficient, the odds ratio (OR) of reporting poor health increased by 1.39 (95% CI: 1.26, 1.51). Additionally controlling for the proportion of the state population who are black did not explain away the effect of income inequality (OR = 1.30; 95% CI: 1.15, 1.45). While being black at the individual level was associated with poorer self-rated health, no significant relationship was found between poor self-rated health and the proportion of black residents in a state. CONCLUSION: Our finding demonstrates that neither race, at the individual level, nor racial composition, as measured at the state level, explain away the previously reported association between income inequality and poorer health status in the US.     

Social context and depression after a disaster: the role of income inequality

STUDY OBJECTIVE: To examine the association between neighbourhood income inequality and depression, both overall and among those with different levels of income, in the post-disaster context. DESIGN: A representative cross sectional random digit dial telephone survey was conducted. SETTING: New York City (NYC) six months after September 11, 2001. PARTICIPANTS: 1570 respondents were interviewed, of whom 1355 provided residence information permitting their inclusion in this analysis. Past six month depression was assessed using a lay administered instrument consistent with DSM-IV criteria. Income inequality was measured with the Gini coefficient. MAIN RESULTS: The sample was demographically representative of NYC (56.2% female, 35.7% white, 6.3% Asian 24.2% African American, 29.7% Hispanic, and 4.2% other race or ethnicity) and the prevalence of past six month depression was 12.4%. In a final adjusted model, neighbourhood level income inequality was positively associated with depression but this association was not significant (beta = 7.58, p = 0.1). However, among those with low individual income (< 20,000 US dollars) there was a strong significant association between income inequality and depression (beta = 35.02, p<0.01), while there was no association among those with higher income. CONCLUSIONS: In the post-disaster context, neighbourhood level income inequality was associated with depression among persons with lower income; this group may be more socially or economically marginalized and dependent on local resources. Future research should examine potential mechanisms through which income inequality and other features of the social context may affect mental health in the post-disaster context.     

Cross-border health and productivity effects of alcohol policies

This paper studies the cross-border health and productivity effects of alcohol taxes. We estimate the effect of a large cut in the Finnish alcohol tax on mortality, alcohol-related illnesses and work absenteeism in Sweden. This tax cut led to large differences in the prices of alcoholic beverages between these two countries and to a considerable increase in cross-border shopping. The effect is identified using differences-in-differences strategy where changes in these outcomes in regions near the Finnish border are compared to changes in other parts of northern Sweden. We use register data where micro level data on deaths, hospitalisations and absenteeism is merged to population-wide micro data on demographics and labour market outcomes. Our results show that the Finnish tax cut did not have any clear effect on mortality or alcohol-related hospitalisations in Sweden. However, we find that workplace absenteeism increased by 9% for males and by 15% for females near the Finnish border as a result of the tax cut.     

Associations between income inequality and mortality among US states: the importance of time period and source of income data

OBJECTIVES: We used census data to examine associations between income inequality and mortality among US states for each decade from 1949 to 1999 and tax return income data to estimate associations for 1989. METHODS: Cross-sectional correlation analyses were used to assess income inequality-mortality relationships. RESULTS: Census income analyses revealed little association between income inequality and mortality for 1949, 1959, or 1969. An association emerged for 1979 and strengthened for 1989 but weakened for 1999. When income inequality was based on tax return data, associations were weaker for both 1989 and 1999. CONCLUSIONS: The strong association between income inequality and mortality observed among US states for 1989 was not observed for other periods from 1949 through 1999. In addition, when tax return rather than census data were used, the association was weaker for 1989 and 1999. The potential for distal social determinants of population health (e.g., income inequality) to affect mortality is contingent on how such determinants influence levels of proximal risk factors and the time lags between exposure to those risk factors and effects on specific health outcomes.     

The effect of primary care physician supply and income inequality on mortality among blacks and whites in US metropolitan areas

OBJECTIVES: This study assessed whether income inequality and primary care physician supply have a different effect on mortality among Blacks compared with Whites. METHODS: We conducted a multivariate ecologic analysis of 1990 data from 273 US metropolitan areas. RESULTS: Both income inequality and primary care physician supply were significantly associated with White mortality (P < .01). After the inclusion of the socioeconomic status covariates, the effect of income inequality on Black mortality remained significant (P < .01), but the effect of primary care physician supply was no longer significant (P > .10), particularly in areas with high income inequality. CONCLUSIONS: Improvement in population health requires addressing socioeconomic determinants of health, including income inequality and primary care availability and access.     

The impact of income inequality on individual and societal health: absolute income, relative income and statistical artefacts

The relative income hypothesis, that relative income has a direct effect on individual health, has become an important part of the literature on health inequalities. This paper presents a four-quadrant diagram, which shows the effect of income, relative income and aggregation bias on individual and societal health. The model predicts that increased income inequality reduces average health regardless of whether relative income affects individual health. If relative income does have a direct effect then societal health will decrease further.     

The impact of race,income, drug abuse and dependence on health insurance coverage among US adults

Little is known about the impact of drug abuse/dependence on health insurance coverage, especially by race groups and income levels. In this study, we examine the disparities in health insurance predictors and investigate the impact of drug use (alcohol abuse/dependence, nicotine dependence, and illicit drug abuse/dependence) on lack of insurance across different race and income groups. To perform the analysis, we used insurance data (8057 uninsured and 28,590 insured individual adults) from the National Surveys on Drug Use and Health (NSDUH 2011). To analyze the likelihood of being uninsured we performed weighted binomial logistic regression analyses. The results show that the overall prevalence of lacking insurance was 19.6 %. However, race differences in lack of insurance exist, especially for Hispanics who observe the highest probability of being uninsured (38.5 %). Furthermore, we observe that the lowest income level bracket (annual income <$20,000) is associated with the highest likelihood of being uninsured (37.3 %). As the result of this investigation, we observed the following relationship between drug use and lack of insurance: alcohol abuse/dependence and nicotine dependence tend to increase the risk of lack of insurance for African Americans and whites, respectively; illicit drug use increases such risk for whites; alcohol abuse/dependence increases the likelihood of lack of insurance for the group with incomes $20,000–$49,999, whereas nicotine dependence is associated with higher probability of lack of insurance for most income groups. These findings provide some useful insights for policy makers in making decisions regarding unmet health insurance coverage.     

The politics of preventable deaths: local spending, income inequality, and premature mortality in US cities

OBJECTIVE: To examine the association between (1) local political party, (2) urban policies, measured by spending on local programmes, and (3) income inequality with premature mortality in large US cities. DESIGN: Cross sectional ecological study. OUTCOME MEASURES: All cause death rates and death rates attributable to preventable or immediate causes for people under age 75. PREDICTOR MEASURES: Income inequality, city spending, and social factors. SETTING: All central cities in the US with population equal to or greater than 100 000. RESULTS: Income inequality is the most significant social variable associated with preventable or immediate death rates, and the relation is very strong: a unit increase in the Gini coefficient is associated with 37% higher death rates. Spending on police is associated with 23% higher preventable death rates compared with 14% lower death rates in cities with high spending on roads. CONCLUSIONS: Cities with high income inequality and poverty are so far unable to reduce their mortality through local expenditures on public goods, regardless of the mayoral party. Longitudinal data are necessary to determine if city spending on social programmes reduces mortality over time.     

Suppression of symptoms of alcohol dependence and craving using high-dose baclofen

AIMS: To further test whether the baclofen-induced suppression of motivation to consume alcohol in animals could be transposed to humans. METHODS: A patient who had neither tolerated nor benefited from other alcohol treatment modalities was put on trial with baclofen on a dosage up to 140 mg/day. RESULTS: The patient reported dramatic reduction in cravings for and preoccupation with alcohol. CONCLUSIONS: High-dose baclofen therapy was associated with complete and prolonged suppression of symptoms and consequences of alcohol-dependence.     

Ecological analysis of the health effects of income inequality in Argentina

OBJECTIVES: Despite a large body of empirical literature, a consensus has not been reached concerning the health effects of income inequality. This study contributes to ongoing debates by examining the robustness of the income inequality-population health relationship in Argentina, using five different income inequality indexes (each sensitive to inequalities in differing parts of the income spectrum) and five measures of population health. STUDY DESIGN: Cross-sectional, ecological study. METHODS: Income and self-reported morbidity data from Argentina's 2001 Encuesta de Condiciones de Vida (Survey of living conditions) were analysed at the provincial level. Provincial rates of male/female life expectancy and infant mortality were drawn from the Instituto Nacional de Estadistica y Censos database. RESULTS: Life expectancy was correlated in the expected direction with provincial-level income inequality (operationalized as the Gini coefficient) for both males (r=-0.55, P<0.01) and females (r=-0.61, P<0.01), but this association was not robust for all five income inequality indexes. In contrast, infant mortality, self-reported poor health and self-reported activity limitation were not correlated with any of the income inequality indexes. CONCLUSIONS: This study adds further complexity to the literature on the health effects of income inequality by highlighting the important effects of operational definitions. Mortality and morbidity data cannot be used as reasonably interchangeable variables (a common practice in this literature), and the choice of income inequality indicator may influence the results.     

The relationship between primary care, income inequality, and mortality in US States, 1980-1995

OBJECTIVES: This study tests the robustness of the relationships between primary care, income inequality, and population health by (1) assessing the relationship during 4 time periods-1980, 1985, 1990 and 1995; (2) examining the independent effect of components of the primary care physician supply; (3) using 2 different measures of income inequality (Robin Hood index and Gini coefficient); and (4) testing the robustness of the association by using 5-year time-lagged independent variables. DATA SOURCES/STUDY SETTING: Data are derived from the Compressed Mortality Files, the US Department of Commerce and the Census Bureau, the National Center for Health Statistics, the Centers for Disease Control and Prevention, and the American Medical Association Physician Master File. The unit of analysis was the 50 US states over a 15-year period. STUDY DESIGN: Ecological, cross-sectional design for 4 selected years (1980, 1985, 1990, 1995), and incorporating 5-year time-lagged independent variables. The main outcome measure is age-standardized, all-cause mortality per 100,000 population in all 50 US states in all 4 time periods. DATA COLLECTION/EXTRACTION METHODS: The study used secondary data from publicly available data sets. The CDC WONDER/PC software was used to obtain mortality data and directly standardize them for age to the 1980 US population. Data used to calculate the income inequality measure came from the US census population and housing summary tapes for the years 1980 to 1995. Counts of the number of households that fell into each income interval along with the total aggregate income and the median household income were obtained for each state. The Gini coefficient for each state was calculated using software developed for this purpose. RESULTS: In weighted multivariate regressions, both contemporaneous and time-lagged income inequality measures (Gini coefficient, Robin Hood Index) were significantly associated with all-cause mortality (P <.05 for both measures for all time periods). Contemporaneous and time-lagged primary care physician-to-population ratios were significantly associated with lower all-cause mortality (P <.05 for all 4 time periods), whereas specialty care measures were associated with higher mortality (P <.05 for all time periods, except 1990, where P <.1). Among primary care subspecialties, only family medicine was consistently associated with lower mortality (P <.01 for all time periods). CONCLUSIONS: Enhancing primary care, particularly family medicine, even in states with high levels of income inequality, could lead to lower all-cause mortality in those states.     

Correlation between biological state markers of alcohol abuse and severity of alcohol dependence syndrome

Data on the correlation between the degree of severity of the alcohol dependence syndrome, as evaluated through the Short Alcohol Dependence Data (SADD) questionnaire, and alterations of four biological state markers of alcohol abuse, namely gamma-glutamyltransferase (GGT), glutamate pyruvate transaminase (SGPT), glutamate oxalacetate transaminase (SGOT) and mean corpuscular volume (MCV), in a sample of 137 alcoholics, are presented. A significant increase in the proportion of altered GGT and SGOT results was found in those patients with higher scores in the SADD. The analysis of the correlation (Spearman coefficient) between the values of each biological test and the SADD scores showed only a significant, though low, positive correlation for SGOT (r = 0.29).     

Contextual effect of income inequality on birth outcomes

BACKGROUND: Though associations between income inequality and birth outcome have been suggested, mechanisms underlying this relationship are not known. In this analysis, we examined the relationship between income inequality and preterm birth (PTB) and post-neonatal mortality (PNM) to explore two potential mechanisms-the proposed psychosocial stress and neo-material pathways. METHODS: Data on singleton births from 1998 to 2000 were obtained from the CDC's National Center for Health Statistics' Linked Birth and Infant Death files. The Gini Index was utilized to measure income inequality and was divided into tertiles representing high, medium, and low county-level inequality. To determine the association between the birth outcomes and county income inequality and to account for clustering within counties, we employed generalized estimating equation (GEE) modelling. RESULTS: PTB increased from 8.3% in counties with low income inequality to 10.0% in counties with high inequality. The Gini Index remained modestly associated with PTB after adjusting for individual level variables and mean county-level per capita income within the total population (AOR: 1.06; 95% CI 1.03-1.09) as well as within most of the racial/ethnic groups. PNM increased from 1.15 deaths per 1000 live births in low inequality counties to 1.32 in high-inequality counties. However, after adjustment, income inequality was only associated with PNM within the non-Hispanic black population (AOR: 1.20; 95% CI 1.03-1.39). CONCLUSIONS: These findings may provide some support for the association between income inequality and PTB. Further research is required to elucidate the biological mechanisms of income inequality.