State- and county-level income inequality and infant mortality in the USA in 2010: a cohort study

Neighborhood income inequality, maternal relative deprivation and neonatal health in Sweden: A cross-sectional study using individually defined multi-scale contexts

•Maternal relative deprivation is linked to intrauterine growth restriction.•Neighborhood income inequality is linked to fewer low Apgar scores in high-income mothers.•Findings support relative deprivation hypothesis over income inequality hypothesis.

State-level association between income inequality and mortality in the USA, 1989-2019: ecological study

BACKGROUND

Prior studies have shown a positive relationship between income inequality and population-level mortality. This study investigates whether the relationship between US state-level income inequality and all-cause mortality persisted from 1989 to 2019 and whether changes in income inequality were correlated with changes in mortality rates.

METHODS

We perform repeated cross-sectional regressions of mortality on state-level inequality measures (Gini coefficients) at 10-year intervals. We also estimate the correlation between within-state changes in income inequality and changes in mortality rates using two time-series models, one with state- and year-fixed effects and one with a lagged dependent variable. Our primary regressions control for median income and are weighted by population.

MAIN OUTCOME MEASURES

The two primary outcomes are male and female age-adjusted mortality rates for the working-age (25-64) population in each state. The secondary outcome is all-age mortality.

RESULTS

There is a strong positive correlation between Gini and mortality in 1989. A 0.01 increase in Gini is associated with more deaths: 9.6/100 000 (95% CI 5.7, 13.5, p<0.01) for working-age females and 29.1 (21.2, 36.9, p<0.01) for working-age males. This correlation disappears or reverses by 2019 when a 0.01 increase in Gini is associated with fewer deaths: -6.7 (-12.2, -1.2, p<0.05) for working-age females and -6.2 (-15.5, 3.1, p>0.1) for working-age males. The correlation between the change in Gini and change in mortality is also negative for all outcomes using either time-series method. These results are generally robust for a range of income inequality measures.

CONCLUSION

The absence or reversal of correlation after 1989 and the presence of an inverse correlation between change in inequality and change in all-cause mortality represents a significant reversal from the findings of a number of other studies. It also raises questions about the conditions under which income inequality may be an important policy target for improving population health.

Evaluating the Prevalence of Maternal Health Indicators on Infant Mortality Rates in Florida

Background The infant mortality rate is defined as the number of infant deaths for every 1000 live births. In 2020, the infant mortality rate was 5.8% in the state of Florida, compared to 7.0% in 2000. Although infant mortality rates have declined in the state of Florida, disparities influencing these rates exist across varying Florida counties, with the widest differences being compared between the healthiest versus unhealthiest counties in Florida. Many factors can contribute to high infant mortality rates in certain counties, including income inequality, access to and quality of healthcare, race/ethnicity, obesity, and disadvantaged socioeconomic status (SES). Methods This study utilized data from Florida Health Charts on infant mortality rates in the state of Florida and the Pregnancy and Young Child Profiles in 10 counties to examine how certain risk factors impact infant mortality outcomes in the state of Florida. These 10 counties consist of five healthiest and five unhealthiest counties, as determined by the 2022 County Health Rankings data. T-tests were used to evaluate the relationship between county health status and several county health indicators. Results The average infant mortality rate from 2011 to 2020 differed significantly among healthy and unhealthy counties (p-value=0.0000). Median household income, individuals below the poverty level, and those aged zero to 17 years old were found to differ significantly by county health status (p-values 0.0000, 0.001, and 0.009, respectively). However, mothers having no high school education, births with first-trimester care, births with adequate care, and births with late or no prenatal care were not statistically significant. Conclusion Our study suggests that counties more likely to have fewer resources than other counties, such as those considered unhealthy, are more impacted by a higher infant mortality rate. The unhealthy counties in this study were found to have lower average median household income, higher rates of no high school education among mothers, and less prenatal care in comparison to healthy counties.

Abortion Restrictiveness and Infant Mortality: An Ecologic Study, 2014-2018

INTRODUCTION

The U.S. has the highest infant mortality rate among peer countries. Restrictive abortion laws may contribute to poor infant health outcomes. This ecological study investigated the association between county-level infant mortality and state-level abortion access legislation in the U.S. from 2014 to 2018.

METHODS

A multivariable regression analysis with the outcome of county-level infant mortality rates, controlling for the primary exposure of state-level abortion laws, and county-level factors, county-level distance to an abortion facility, and state Medicaid expansion status was performed. Incidence rate ratios and 95% CIs were reported. Analyses were conducted in 2022-2023.

RESULTS

There were 113,397 infant deaths among 19,559,660 live births (infant mortality rate=5.79 deaths/1,000 live births; 95% CI=5.75, 5.82). Black infant mortality rate (10.69/1,000) was more than twice the White infant mortality rate (4.87/1,000). In the multivariable model, increased infant mortality rates were seen in states with ≥8 restrictive laws, with the most restrictive (11-12 laws) having a 16% increased infant mortality level (adjusted incidence rate ratios=1.162; 95% CI=1.103, 1.224). Increased infant mortality rates were associated with increased county-level Black race individuals (adjusted incidence rate ratios=1.031; 95% CI=1.026, 1.037), high school education (adjusted incidence rate ratios=1.018; 95% CI=1.008, 1.029), maternal smoking (adjusted incidence rate ratios=1.025; 95% CI=1.018, 1.033), and inadequate prenatal care (adjusted incidence rate ratios=1.045; 95% CI=1.036, 1.055).

CONCLUSIONS

State-level abortion law restrictiveness is associated with higher county-level infant mortality rates. The Supreme Court decision on Dobbs versus Jackson and changes in state laws limiting abortion may affect future infant mortality.

Structural Racism as an Environmental Justice Issue: A Multilevel Analysis of the State Racism Index and Environmental Health Risk from Air Toxics

Communities of color and poor neighborhoods are disproportionately exposed to more air pollution-a pattern known as environmental injustices. Environmental injustices increase susceptibility to negative health outcomes among residents in affected communities. The structural mechanisms distributing environmental injustices in the USA are understudied. Bridging the literatures on the social determinants of health and environmental justice highlights the importance of the environmental conditions for health inequalities and sheds light on the institutional mechanisms driving environmental health inequalities. Employing a critical quantitative methods approach, we use data from an innovative state racism index to argue that systematic racialized inequalities in areas from housing to employment increase outdoor airborne environmental health risks in neighborhoods. Results of a multilevel analysis in over 65,000 census tracts demonstrate that tracts in states with higher levels of state-level Black-white gaps report greater environmental health risk exposure to outdoor air pollution. The state racism index explains four-to-ten percent of county- and state-level variation in carcinogenic risk and noncarcinogenic respiratory system risks from outdoor air toxics. The findings suggest that the disproportional exposure across communities is tied to systematic inequalities in environmental regulation and other structural elements such as housing and incarceration. Structural racism is an environmental justice issue.

Income inequality and child maltreatment rates in US counties, 2009-2018

BACKGROUND AND OBJECTIVE

Studies have confirmed that income inequality is associated with compromised health and well-being. However, much less is known about the effects of county-level income inequality on risk of perpetrating child maltreatment, particularly for distinct types of child maltreatment. By utilizing recent national data over 10 years (2009-2018), our study explored the associations of county-level income inequality (i.e., Gini index and income quantile ratios) with child maltreatment rates, including both overall and specific types of maltreatment rates (i.e., physical, psychological, and sexual abuse and neglect) in the US.

PARTICIPANTS AND SETTING

We utilized data from approximately 902 US counties by linking the National Child Abuse and Neglect Data System with the American Community Survey.

METHODS

Ordinary Least Squares regression models were estimated to examine the relationship between county-level income inequality and child maltreatment rates and the moderating role of poverty rates.

RESULTS

Higher scores on county-level Gini index were significantly associated with higher overall child maltreatment rates and neglect, after controlling for county-level characteristics. Income quantile ratios were significantly associated with overall child maltreatment, physical abuse, and neglect. We also found significant interaction effects between income inequality and poverty rates in the associations with physical and psychological abuse rates, suggesting that the effects of inequality were exacerbated by county-level poverty.

CONCLUSIONS

Given the tremendous increases in inequality in the US over recent decades, this research sheds light on the mechanisms through which inequality impacts parents' caregiving abilities in highly unequal counties.

Income inequality and population health: a political-economic research agenda

There is more than 30 years of research on relationships between income inequality and population health. In this article, we propose a research agenda with five recommendations for future research to refine existing knowledge and examine new questions. First, we recommend that future research prioritise analyses with broader time horizons, exploring multiple temporal aspects of the relationship. Second, we recommend expanding research on the effect of public expenditures on the inequality-health relationship. Third, we introduce a new area of inquiry focused on interactions between social mobility, income inequality and population health. Fourth, we argue the need to examine new perspectives on 21st century capitalism, specifically the population health impacts of inequality in income from capital (especially housing), in contrast to inequality in income from labour. Finally, we propose that this research broaden beyond all-cause mortality, to cause-specific mortality, avoidable mortality and subcategories thereof. We believe that such a research agenda is important for policy to respond to the changes following the COVID-19 pandemic.

State-Level Social and Economic Policies and Their Association With Perinatal and Infant Outcomes

Policy Points State-level social and economic policies that expand tax credits, increase paid parental leave, raise the minimum wage, and increase tobacco taxes have been demonstrated to reduce adverse perinatal and infant health outcomes. These findings can help prioritize evidence-based legislated policies to improve perinatal and infant outcomes in the United States.

CONTEXT

Rates of preterm birth and infant mortality are alarmingly high in the United States. Legislated efforts may directly or indirectly reduce adverse perinatal and infant outcomes through the enactment of certain economic and social policies.

METHODS

We conducted a narrative review to summarize the associations between perinatal and infant outcomes and four state-level US policies. We then used a latent profile analysis to create a social and economic policy profile for each state based on the observed policy indicators.

FINDINGS

Of 27 articles identified, nine focused on tax credits, eight on paid parental leave, four on minimum wages, and six on tobacco taxes. In all but three studies, these policies were associated with improved perinatal or infant outcomes. Thirty-three states had tax credit laws, most commonly the earned income tax credit (n = 28, 56%). Eighteen states had parental leave laws. Two states had minimum wage laws lower than the federal minimum; 14 were equal to the federal minimum; 29 were above the federal minimum; and 5 did not have a state law. The average state tobacco tax was $1.76 (standard deviation = $1.08). The latent profile analysis revealed three policy profiles, with the most expansive policies in Western and Northeastern US states, and the least expansive policies in the US South.

CONCLUSIONS

State-level social and economic policies have the potential to reduce adverse perinatal and infant health outcomes in the United States. Those states with the least expansive policies should therefore consider enacting these evidence-based policies, as they have shown a demonstratable benefit in other states.

County-Level Variation in Utilization of Surgical Resection for Early-Stage Hepatopancreatic Cancer Among Medicare Beneficiaries in the USA

INTRODUCTION

Geographic variations in access to care exist in the USA. We sought to characterize county-level disparities relative to access to surgery among patients with early-stage hepatopancreatic (HP) cancer.

METHODS

Data were extracted from the Surveillance, Epidemiology, and End Results (SEER)-Medicare Linked database from 2004 to 2015 to identify patients undergoing surgery for early-stage HP cancer . County-level information was acquired from the Area Health Resources Files (AHRF). Multivariable logistic regression analysis was performed to assess factors associated with utilization of HP surgery on the county level.

RESULTS

Among 13,639 patients who met inclusion criteria, 66.9% (n = 9125) were diagnosed with pancreatic cancer and 33.1% (n = 4514) of patients had liver cancer. Among patients diagnosed with early-stage liver and pancreas malignancy, two-thirds (n = 8878, 65%) underwent surgery. Marked county-level variation in the utilization of surgery was noted among patients with early-stage HP cancer ranging from 57.1% to more than 83.3% depending on which county a patient resided. After controlling for patient and tumor-related characteristics, counties with the highest quartile of patients living below the poverty level had 35% lower odds of receiving surgery for early stage HP cancer compared patients who lived in a county with the lowest proportion of patients below the poverty line (OR 0.65, 95% CI 0.55-0.77). In addition, patients residing in counties with the highest surgeon-to-population ratio (OR 2.01, 95% CI 1.52-2.65), as well as the highest hospital bed-to-population ratio (OR 1.29, 95% CI 1.07-1.54), were more likely to undergo surgical treatment for an early-stage HP malignancy.

CONCLUSION

Area-level variations among patients undergoing surgery for early-stage HP cancer were mainly due to differences in structural measures and county-level factors. Policies targeting high-poverty counties and improvement in structural measures may reduce variations in utilization of surgery among patients diagnosed with early-stage HP cancer.