Daniel M. Cook

Objectives: Previous research has indicated that area-level income inequality is associated with increased risk in alcohol consumption. However, few studies have been conducted among adolescents living within smaller area units, such as neighborhoods. We investigated whether neighborhood income inequality is associated with alcohol consumption among adolescents. Methods: We analyzed cross-sectional data from a sample of 1878 adolescents living in 38 neighborhoods participating in the 2008 Boston Youth Survey. Multilevel logistic regression modeling was used to determine the role of neighborhood income inequality and the odds for alcohol consumption and to determine if social cohesion and depressive symptoms were mediators. Results: In comparison to the first tertile of income inequality, or the most equal neighborhood, adolescent participants living in the second tertile (AOR = 1.20, 95% CI: 0.89, 1.61) and third tertile (AOR = 1.44, 95% CI: 1.06, 1.96) were more likely to have consumed alcohol in the last 30 days. Social cohesion and depressive symptoms were not observed to mediate this relationship. Conclusions: Findings indicate that the distribution of incomes within urban areas may be related to alcohol consumption among adolescents. To prevent alcohol consumption, public health practitioners should prioritize prevention efforts for adolescents living in neighborhoods with large gaps between rich and poor.

Objectives: Since the US Supreme Court′s 1973 Roe v. Wade decision legalizing abortion, states have enacted laws restricting access to abortion services. Previous studies suggest that restricting access to abortion is a risk factor for adverse maternal and infant health. The objective of this investigation is to study the relationship between the type and the number of state-level restrictive abortion laws and infant mortality risk. Methods: We used data on 11,972,629 infants and mothers from the US Cohort Linked Birth/Infant Death Data Files 2008–2010. State-level abortion laws included Medicaid funding restrictions, mandatory parental involvement, mandatory counseling, mandatory waiting period, and two-visit laws. Multilevel logistic regression was used to determine whether type or number of state-level restrictive abortion laws during year of birth were associated with odds of infant mortality. Results: Compared to infants living in states with no restrictive laws, infants living in states with one or two restrictive laws (adjusted odds ratio (AOR) = 1.08; 95% confidence interval [CI] = 0.99–1.18) and those living in states with 3 to 5 restrictive laws (AOR = 1.10; 95% CI = 1.01–1.20) were more likely to die. Separate analyses examining the relationship between parental involvement laws and infant mortality risk, stratified by maternal age, indicated that significant associations were observed among mothers aged ≤19 years (AOR = 1.09, 95% CI = 1.00–1.19), and 20 to 25 years (AOR = 1.10, 95% CI = 1.03–1.17). No significant association was observed among infants born to older mothers. Conclusion: Restricting access to abortion services may increase the risk for infant mortality.

Objectives We examined the relationship between income inequality and the risk for infant/neonatal mortality at the state and county level and tested possible mediators of this relationship. Methods We first linked state and county Gini coefficients to US Vital Statistics 2010 Cohort Linked Birth and Infant Death records (n = 3,954,325). We then fit multilevel models to test whether income inequality was associated with infant/neonatal mortality. County-level factors were tested as potential mediators. Results Adjusted analyses indicated that income inequality at the county level—but not at the state level—was associated with increased odds of infant mortality (OR 1.14, 95% CI 1.10, 1.18) and neonatal death (OR 1.17, 95% CI 1.12, 1.23). Our mediators explained most of this variation. Bivariate analyses revealed associations between 3 county-level measures—patient-to-physician ratio, the violent crime rate, and sexually transmitted infection rate—and infant and neonatal mortality. Proportion of college-educated adults was associated with decreased odds for neonatal mortality. Conclusions Local variations in access to care, the rate of sexually transmitted disease, and crime are associated with infant mortality, while variations in college education in addition to these mediators explain neonatal mortality. To reduce infant and neonatal mortality, experiments are needed to examine the effectiveness of policies targeted at reducing income inequality and improving healthcare access, policing, and educational opportunities.

Background: United States state-level income inequality is positively associated with infant mortality in ecological studies. We exploit spatiotemporal variations in a large dataset containing individual-level data to conduct a cohort study and to investigate whether current income inequality and increases in income inequality are associated with infant and neonatal mortality risk over the period of the 2007–2010 Great Recession in the United States. Methods: We used data on 16,145,716 infants and their mothers from the 2007–2010 United States Statistics Linked Infant Birth and Death Records. Multilevel logistic regression was used to determine whether 1) US state-level income inequality, as measured by Z-transformed Gini coefficients in the year of birth and 2) change in Gini coefficient between 1990 and year of birth (2007–2010), predicted infant or neonatal mortality. Our analyses adjusted for both individual and state-level covariates. Results: From 2007 to 2010 there were 98,002 infant deaths: an infant mortality rate of 6.07 infant deaths per 1000 live births. When controlling for state and individual level characteristics, there was no significant relationship between Gini Z-score and infant mortality risk. However, the observed increase in the Gini Z-score was associated with a small but significant increase likelihood of infant mortality (AOR = 1.03 to 1.06 from 2007 to 2010). Similar findings were observed when the neonatal mortality was the outcome (AOR = 1.05 to 1.13 from 2007 to 2010). Conclusions: Infants born in states with greater changes in income inequality between 1990 and 2007 to 2010 experienced a greater likelihood of infant and neonatal mortality.

Background Compared to other Organisation for Economic Co-operation and Development (OECD) nations, US infant mortality rates (IMRs) are particularly high. These differences are partially driven by racial disparities, with non-Hispanic black having IMRs that are twice those of non-Hispanic white. Income inequality (the gap between rich and poor) is associated with infant mortality. One proposed way to decrease income inequality (and possibly to improve birth outcomes) is to increase the minimum wage. We aimed to elucidate the relationship between state-level minimum wage and infant mortality risk using individual-level and state-level data. We also determined whether observed associations were heterogeneous across racial groups. Methods Data were from US Vital Statistics 2010 Cohort Linked Birth and Infant Death records and the 2010 US Bureau of Labor Statistics. We fit multilevel logistic models to test whether state minimum wage was associated with infant mortality. Minimum wage was standardised using the z-transformation and was dichotomised (high vs low) at the 75th percentile. Analyses were stratified by mother's race (non-Hispanic black vs non-Hispanic white). Results High minimum wage (adjusted OR (AOR)=0.93, 95% CI 0.83 to 1.03) was associated with decreased odds of infant mortality but was not statistically significant. High minimum wage was significantly associated with reduced infant mortality among non-Hispanic black infants (AOR=0.80, 95% CI 0.68 to 0.94) but not among non-Hispanic white infants (AOR=1.04, 95% CI 0.92 to 1.17). Conclusions Increasing the minimum wage might be beneficial to infant health, especially among non-Hispanic black infants, and thus might decrease the racial disparity in infant mortality.

Objectives While ecological studies indicate that high levels of structural racism within US states are associated with elevated infant mortality rates, studies using individual-level data are needed. To determine whether indicators of structural racism are associated with the individual odds for infant mortality among white and black infants in the US. Methods We used data on 2,163,096 white and 590,081 black infants from the 2010 US Cohort Linked Birth/Infant Death Data Files. Structural racism indicators were ratios of relative proportions of blacks to whites for these domains: electoral (registered to vote and voted; state legislature representation), employment (civilian labor force; employed; in management; with a bachelor’s degree), and justice system (sentenced to death; incarcerated). Multilevel logistic regression was used to determine whether structural racism indicators were risk factors of infant mortality. Results Compared to the lowest tertile ratio of relative proportions of blacks to whites with a bachelor’s degree or higher—indicative of low structural racism—black infants, but not whites, in states with moderate (OR = 1.12, 95% CI = 0.94, 1.32) and high tertiles (OR = 1.25, 95% CI = 1.03, 1.51) had higher odds of infant mortality. Conclusions Educational and judicial indicators of structural racism were associated with infant mortality among blacks. Decreasing structural racism could prevent black infant deaths.

Racial and ethnic discrimination in health care have been associated with suboptimal use of health care. However, limited research has examined how facets of health care utilization influence, and are influenced by, discrimination.

Studies assessing the impacts of China’s New-type Rural Cooperative Medical Scheme (NCMS) reform of 2003 among rural elderly have been limited. Multistage stratified cluster sampling household surveys of 1838, 1924, 1879, 1888, 1890 and 1896 households from 27 villages in Jiangxi province were conducted in 2003/2004, 2006, 2008, 2010, 2012 and 2014. Data from older adults age 65 and above were analyzed. Weighted logistic regression was applied to find factors of elderly hospitalization services. Since 2003, hospitalization rates for elderly increased, while rates of patients leaving against medical advice and patients avoiding the hospital decreased (P < 0.05). Factors associated with a higher likelihood of reporting hospitalization in the past year for elderly were the per-capita financial level V in 2012 for NCMS (Adjusted Odds Ratios [aOR]: 2.295), the level VI in 2014 (aOR: 3.045) versus the level I in 2003 and chronic disease (aOR: 2.089) versus not having a chronic disease. Lower rate of elderly left against medical advice was associated with the financial level V in 2012 (aOR: 0.099) versus the level I. The higher rate of hospital avoidance was associated with chronic disease status (aOR: 5.759) versus not having a chronic disease, while the lower rate was associated with the financial level VI in 2014 (aOR: 0.143) versus the level I. Among reporting reasons for elderly hospital avoidance, the cost-related reasons just dropped slightly over the years. NCMS improved access to health services for older adults. The utilization of hospitalization services for rural elderly increased gradually, but cost-related barriers remained the primary reporting barrier to accessing hospitalization services.