Excess US Deaths Attributable to High All-Cause Mortality Rates Among Youths Aged 0 to 19 Years.

This cross-sectional study compares US mortality rates among youths aged 0 to 19 years with rates in 16 high-income countries, calculates excess deaths from 1999 to 2019, and examines temporal trends through 2021.

Racial and Ethnic Disparities in All-Cause and Cause-Specific Mortality Among US Youth.

Importance: Mortality rates in US youth have increased in recent years. An understanding of the role of racial and ethnic disparities in these increases is lacking. Objective: To compare all-cause and cause-specific mortality trends and rates among youth with Hispanic ethnicity and non-Hispanic American Indian or Alaska Native, Asian or Pacific Islander, Black, and White race. Design, Setting, and Participants: This cross-sectional study conducted temporal analysis (1999-2020) and comparison of aggregate mortality rates (2016-2020) for youth aged 1 to 19 years using US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database. Data were analyzed from June 30, 2023, to January 17, 2024. Main Outcomes and Measures: Pooled, all-cause, and cause-specific mortality rates per 100 000 youth (hereinafter, per 100 000) for leading underlying causes of death were compared. Injuries were classified by mechanism and intent. Results: Between 1999 and 2020, there were 491 680 deaths among US youth, including 8894 (1.8%) American Indian or Alaska Native, 14 507 (3.0%) Asian or Pacific Islander, 110 154 (22.4%) Black, 89 251 (18.2%) Hispanic, and 267 452 (54.4%) White youth. Between 2016 and 2020, pooled all-cause mortality rates were 48.79 per 100 000 (95% CI, 46.58-51.00) in American Indian or Alaska Native youth, 15.25 per 100 000 (95% CI, 14.75-15.76) in Asian or Pacific Islander youth, 42.33 per 100 000 (95% CI, 41.81-42.86) in Black youth, 21.48 per 100 000 (95% CI, 21.19-21.77) in Hispanic youth, and 24.07 per 100 000 (95% CI, 23.86-24.28) in White youth. All-cause mortality ratios compared with White youth were 2.03 (95% CI, 1.93-2.12) among American Indian or Alaska Native youth, 0.63 (95% CI, 0.61-0.66) among Asian or Pacific Islander youth, 1.76 (95% CI, 1.73-1.79) among Black youth, and 0.89 (95% CI, 0.88-0.91) among Hispanic youth. From 2016 to 2020, the homicide rate in Black youth was 12.81 (95% CI, 12.52-13.10) per 100 000, which was 10.20 (95% CI, 9.75-10.66) times that of White youth. The suicide rate for American Indian or Alaska Native youth was 11.37 (95% CI, 10.30-12.43) per 100 000, which was 2.60 (95% CI, 2.35-2.86) times that of White youth. The firearm mortality rate for Black youth was 12.88 (95% CI, 12.59-13.17) per 100 000, which was 4.14 (95% CI, 4.00-4.28) times that of White youth. American Indian or Alaska Native youth had a firearm mortality rate of 6.67 (95% CI, 5.85-7.49) per 100 000, which was 2.14 (95% CI, 1.88- 2.43) times that of White youth. Black youth had an asthma mortality rate of 1.10 (95% CI, 1.01-1.18) per 100 000, which was 7.80 (95% CI, 6.78-8.99) times that of White youth. Conclusions and Relevance: In this study, racial and ethnic disparities were observed for almost all leading causes of injury and disease that were associated with recent increases in youth mortality rates. Addressing the increasing disparities affecting American Indian or Alaska Native and Black youth will require efforts to prevent homicide and suicide, especially those events involving firearms.

Association Between Partisan Affiliation of State Governments and State Mortality Rates Before and During the COVID-19 Pandemic.

Policy Points The increasing political polarization of states reached new heights during the COVID-19 pandemic, when response plans differed sharply across party lines. This study found that states with Republican governors and larger Republican majorities in legislatures experienced higher death rates during the COVID-19 pandemic-and in preceding years-but these associations often lost statistical significance after adjusting for the average income and health status of state populations and for the policy orientations of the states. Future research may help clarify whether the higher death rates in these states result from policy choices or have other explanations, such as the tendency of voters with lower incomes or poorer health to elect Republican candidates. CONTEXT: Increasing polarization of states reached a high point during the COVID-19 pandemic, when the party affiliation of elected officials often predicted their policy response. The health consequences of these divisions are unclear. Prior studies compared mortality rates based on presidential voting patterns, but few considered the partisan orientation of state officials. This study examined whether the partisan orientation of governors or legislatures was associated with mortality outcomes during the COVID-19 pandemic. METHODS: Data on deaths and the partisan orientation of governors and legislators were obtained from the Centers for Disease Control and Prevention and the National Conference of State Legislatures, respectively. Linear regression was used to measure the association between Republican representation (percentage of seats held) in legislatures and (1) age-adjusted, all-cause mortality rates (AAMRs) in 2015-2021 and (2) excess death rates during three phases of the COVID-19 pandemic, controlling for median household income, the prevalence of four risk factors (obesity, chronic obstructive pulmonary disease, heart attack, stroke), and state policy orientation. Associations between excess death rates and the governor's party were also examined. FINDINGS: States with Republican governors or greater Republican representation in legislatures experienced higher AAMRs during 2015-2021, lower excess death rates during Phase 1 of the COVID-19 pandemic (weeks ending March 28, 2020, through June 13, 2020), and higher excess death rates in Phases 2 and 3 (weeks ending June 20, 2020, through April 30, 2022; p < 0.05). Most associations lost statistical significance after adjustment for control variables. CONCLUSIONS: Mortality was higher in states with Republican governors and greater Republican legislative representation before and during much of the pandemic. Observed associations could be explained by the adverse effects of policy choices, reverse causality (e.g., popularity of Republican candidates in states with lower socioeconomic and health status), or unmeasured factors that predominate in states with Republican leaders.

The Lives Lost to Inequities: Avertable Deaths From Neurologic Diseases in the Past Decade.

BACKGROUND AND OBJECTIVES: Mortality rates for neurologic diseases are increasing in the United States, with large disparities across geographical areas and populations. Racial and ethnic populations, notably the non-Hispanic (NH) Black population, experience higher mortality rates for many causes of death, but the magnitude of the disparities for neurologic diseases is unclear. The objectives of this study were to calculate mortality rates for neurologic diseases by race and ethnicity and-to place this disparity in perspective-to estimate how many US deaths would have been averted in the past decade if the NH Black population experienced the same mortality rates as other groups. METHODS: Mortality rates for deaths attributed to neurologic diseases, as defined by the International Classification of Diseases, were calculated for 2010 to 2019 using death and population data obtained from the Centers for Disease Control and Prevention and the US Census Bureau. Avertable deaths were calculated by indirect standardization: For each calendar year of the decade, age-specific death rates of NH White persons in 10 age groups were multiplied by the NH Black population in each age group. A secondary analysis used Hispanic and NH Asian populations as the reference groups. RESULTS: In 2013, overall age-adjusted mortality rates for neurologic diseases began increasing, with the NH Black population experiencing higher rates than NH White, NH American Indian and Alaska Native, Hispanic, and NH Asian populations (in decreasing order). Other populations with higher mortality rates for neurologic diseases included older adults, the male population, and adults older than 25 years without a high school diploma. The gap in mortality rates for neurologic diseases between the NH Black and NH White populations widened from 4.2 individuals per 100,000 in 2011 to 7.0 per 100,000 in 2019. Over 2010 to 2019, had the NH Black population experienced the neurologic mortality rates of NH White, Hispanic, or NH Asian populations, 29,986, 88,407, or 117,519 deaths, respectively, would have been averted. DISCUSSION: Death rates for neurologic diseases are increasing. Disproportionately higher neurologic mortality rates in the NH Black population are responsible for a large number of excess deaths, making research and policy efforts to address the systemic causes increasingly urgent.

The Mediating Effect of Sleep Duration on the Association between Food Insecurity and Childhood Obesity.

Background: Childhood obesity has increased globally during the past four decades. Food insecurity could heighten the risk of obesity. However, little is known about the underlying mechanism. This study aims to investigate the mediating role of sleep duration in the association between food insecurity and childhood obesity and whether there are differences by age, sex, and race/ethnicity. Method: Data from the National Survey of Children's Health for the years 2016-2020 were used, including children 10-17 years of age. We employed causal mediation analysis within a counterfactual framework to decompose the total effect of food insecurity into natural direct and indirect effects and estimate the proportion mediated. Result: The prevalence of obesity was 15.8% in our study sample. Children with food insecurity had 78% higher odds [odds ratio (OR) = 1.78, 95% confidence interval (CI): 1.70-1.86] of having obesity compared with children who were food secure. Overall, only 6.13% of this association was mediated by sleep duration. The association between food insecurity and obesity was stronger in females (OR = 1.96, 95% CI: 1.84-2.10) than males (OR = 1.66, 95% CI: 1.56-1.75), but the proportion mediated by sleep duration was larger in males (7.13%) than females (5.22%). Evidence of mediation was more pronounced in children 10-11 years of age and non-Hispanic Asian children (proportion mediated = 14.85% and 11.21%, respectively). Conclusion: Food insecurity is associated with an increased prevalence of obesity among children. Although a small proportion of this association is mediated by sleep duration, these results suggest that sleep should be considered when assessing the link between food insecurity and childhood obesity.

Urban-Rural Disparities in Deaths of Despair: A County-Level Analysis 2004-2016 in the U.S.

Introduction: The purpose of this study is to examine nationwide disparities in drug, alcohol, and suicide mortality; evaluate the association between county-level characteristics and these mortality rates; and illustrate spatial patterns of mortality risk to identify areas with elevated risk. Methods: The authors applied a Bayesian spatial regression technique to investigate the association between U.S. county-level characteristics and drug, alcohol, and suicide mortality rates for 2004-2016, accounting for spatial correlation that occurs among counties. Results: Mortality risks from drug, alcohol, and suicide were positively associated with the degree of rurality, the proportion of vacant housing units, the population with a disability, the unemployed population, the population with low access to grocery stores, and the population with no health insurance. Conversely, risks were negatively associated with Hispanic population, non-Hispanic Black population, and population with a bachelor's degree or higher. Conclusions: Spatial disparities in drug, alcohol, and suicide mortality exist at the county level across the U.S. social determinants of health; educational attainment, degree of rurality, ethnicity, disability, unemployment, and health insurance status are important factors associated with these mortality rates. A comprehensive strategy that includes downstream interventions providing equitable access to healthcare services and upstream efforts in addressing socioeconomic conditions is warranted to effectively reduce these mortality burdens.

U.S. state policy contexts and mortality of working-age adults.

The rise in working-age mortality rates in the United States in recent decades largely reflects stalled declines in cardiovascular disease (CVD) mortality alongside rising mortality from alcohol-induced causes, suicide, and drug poisoning; and it has been especially severe in some U.S. states. Building on recent work, this study examined whether U.S. state policy contexts may be a central explanation. We modeled the associations between working-age mortality rates and state policies during 1999 to 2019. We used annual data from the 1999-2019 National Vital Statistics System to calculate state-level age-adjusted mortality rates for deaths from all causes and from CVD, alcohol-induced causes, suicide, and drug poisoning among adults ages 25-64 years. We merged that data with annual state-level data on eight policy domains, such as labor and taxes, where each domain was scored on a 0-1 conservative-to-liberal continuum. Results show that the policy domains were associated with working-age mortality. More conservative marijuana policies and more liberal policies on the environment, gun safety, labor, economic taxes, and tobacco taxes in a state were associated with lower mortality in that state. Especially strong associations were observed between certain domains and specific causes of death: between the gun safety domain and suicide mortality among men, between the labor domain and alcohol-induced mortality, and between both the economic tax and tobacco tax domains and CVD mortality. Simulations indicate that changing all policy domains in all states to a fully liberal orientation might have saved 171,030 lives in 2019, while changing them to a fully conservative orientation might have cost 217,635 lives.

Comparing forms of neighborhood instability as predictors of violence in Richmond, VA.

Violence events tend to cluster together geospatially. Various features of communities and their residents have been highlighted as explanations for such clustering in the literature. One reliable correlate of violence is neighborhood instability. Research on neighborhood instability indicates that such instability can be measured as property tax delinquency, yet no known work has contrasted external and internal sources of instability in predicting neighborhood violence. To this end we collected data on violence events, company and personal property tax delinquency, population density, race, income, food stamps, and alcohol outlets for each of Richmond, Virginia's 148 neighborhoods. We constructed and compared ordinary least-squares (OLS) to geographically weighted regression (GWR) models before constructing a final algorithm-selected GWR model. Our results indicated that the tax delinquency of company-owned properties (e.g., rental homes, apartments) was the only variable in our model (R2 = 0.62) that was associated with violence in all but four Richmond neighborhoods. We replicated this analysis using violence data from a later point in time which yielded largely identical results. These findings indicate that external sources of neighborhood instability may be more important to predicting violence than internal sources. Our results further provide support for social disorganization theory and point to opportunities to expand this framework.

Identifying bright spot communities: Socioecological, workforce, and healthcare delivery factors influencing opioid mortality.

Context: There were 50,000 U.S. opioid overdose deaths in 2019. Millions suffer from opioid addiction. Identifying protective factors for low community opioid mortality may have important implications for addressing the opioid epidemic. This study was funded through the Virginia (VA) Department of Medical Assistance Services (DMAS) through a SUPPORT Act Grant. Objective: To identify "Bright Spot" communities in Virginia with protective factors associated with reduced opioid mortality and morbidity. Study Design: Ecologic study. Dataset: Virginia All Payer Claims Database (APCD), Virginia Department of Health (VDH) statewide medical examiner registry, and American Community Survey (ACS). Time Period: 2016-2019; 2019 data cited here. Population Studied: APCD includes VA residents with medical claims through commercial, Medicaid, and Medicare coverage. VDH data includes fatal drug overdoses. ACS surveys all VA residents. Outcome Measures: Primary outcome: fatal opioid overdoses. Secondary outcomes: emergency room visits for overdoses and opioid-related diagnoses, outpatient diagnoses for opioid-related disorder, prescription rate for opioids, and prescription rate for buprenorphine. Results: Opioid mortality was associated with higher rates of community poverty (r=.38, p<.0001) and disability (r=.52, r<.0001). Opioid mortality was associated with inequality, with higher Gini index associated with higher opioid mortality (r=.23, p<.0001). A higher percentage of black residents was associated with increased fatal opioid overdoses (r=.37, p<.0001) and ED visits for overdoses (r=.30, p<.0001). A higher percentage of white residents correlated with increased outpatient visits for opioid use disorder (r=.24, p<.0001) and higher rates of buprenorphine (r=.34, p<.0001) and opioid prescriptions (r=.31, p <.0001). Conclusions: These findings suggest significant racial disparities in opioid outcomes. Communities with a higher percentage of black residents are more likely to have higher opioid mortality and a lower rate of outpatient treatment. This association may be affected by the time period used in the analysis (2015-2019), as nationally there has been an increasing rate of synthetic opioid deaths in Black communities. These measures have been incorporated into a multivariate analysis to identify Bright Spot communities, which will be discussed during the presentation.

Changes in the Relationship Between Income and Life Expectancy Before and During the COVID-19 Pandemic, California, 2015-2021.

Importance: The COVID-19 pandemic caused a large decrease in US life expectancy in 2020, but whether a similar decrease occurred in 2021 and whether the relationship between income and life expectancy intensified during the pandemic are unclear. Objective: To measure changes in life expectancy in 2020 and 2021 and the relationship between income and life expectancy by race and ethnicity. Design, Setting, and Participants: Retrospective ecological analysis of deaths in California in 2015 to 2021 to calculate state- and census tract-level life expectancy. Tracts were grouped by median household income (MHI), obtained from the American Community Survey, and the slope of the life expectancy-income gradient was compared by year and by racial and ethnic composition. Exposures: California in 2015 to 2019 (before the COVID-19 pandemic) and 2020 to 2021 (during the COVID-19 pandemic). Main Outcomes and Measures: Life expectancy at birth. Results: California experienced 1 988 606 deaths during 2015 to 2021, including 654 887 in 2020 to 2021. State life expectancy declined from 81.40 years in 2019 to 79.20 years in 2020 and 78.37 years in 2021. MHI data were available for 7962 of 8057 census tracts (98.8%; n = 1 899 065 deaths). Mean MHI ranged from $21 279 to $232 261 between the lowest and highest percentiles. The slope of the relationship between life expectancy and MHI increased significantly, from 0.075 (95% CI, 0.07-0.08) years per percentile in 2019 to 0.103 (95% CI, 0.098-0.108; P < .001) years per percentile in 2020 and 0.107 (95% CI, 0.102-0.112; P < .001) years per percentile in 2021. The gap in life expectancy between the richest and poorest percentiles increased from 11.52 years in 2019 to 14.67 years in 2020 and 15.51 years in 2021. Among Hispanic and non-Hispanic Asian, Black, and White populations, life expectancy declined 5.74 years among the Hispanic population, 3.04 years among the non-Hispanic Asian population, 3.84 years among the non-Hispanic Black population, and 1.90 years among the non-Hispanic White population between 2019 and 2021. The income-life expectancy gradient in these groups increased significantly between 2019 and 2020 (0.038 [95% CI, 0.030-0.045; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI: 0.005-0.044; P = .02] years per percentile among Asian individuals; 0.015 [95% CI, 0.010-0.020; P < .001] years per percentile among Black individuals; and 0.011 [95% CI, 0.007-0.015; P < .001] years per percentile among White individuals) and between 2019 and 2021 (0.033 [95% CI, 0.026-0.040; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI, 0.010-0.038; P = .002] years among Asian individuals; 0.024 [95% CI, 0.011-0.037; P = .003] years per percentile among Black individuals; and 0.013 [95% CI, 0.008-0.018; P < .001] years per percentile among White individuals). The increase in the gradient was significantly greater among Hispanic vs White populations in 2020 and 2021 (P < .001 in both years) and among Black vs White populations in 2021 (P = .04). Conclusions and Relevance: This retrospective analysis of census tract-level income and mortality data in California from 2015 to 2021 demonstrated a decrease in life expectancy in both 2020 and 2021 and an increase in the life expectancy gap by income level relative to the prepandemic period that disproportionately affected some racial and ethnic minority populations. Inferences at the individual level are limited by the ecological nature of the study, and the generalizability of the findings outside of California are unknown.

Disparities by Sex in COVID-19 Risk and Related Harms Among People with Opioid Use Disorder.

Objectives: (1) Report sex-specific prevalence of coronavirus disease 2019 (COVID-19) test positivity among an opioid use disorder (OUD) cohort (2) Assess sex-specific rates of opioid overdose and mortality. Methods: A retrospective cohort study was performed on all adult patients with OUD who received a COVID-19 test in calendar year 2020 at a large academic medical center in Richmond, Virginia. Our study outcomes were positive COVID-19 test, opioid overdose, and all-cause in-hospital mortality. Sex-stratified multivariable logistic regression assessed sociodemographic factors associated with COVID-19 test positivity. Results: A total of 2,600 patients (males = 1,294, females = 1,306) with OUD received a COVID-19 test. Approximately 5% across both sexes tested positive for COVID-19 (p = 0.420), whereas 7% presented with an opioid overdose (males 10%; females 4%; p < 0.0001). However, mortality rates were similar across sex. Among males, individuals in the other racial group had increased odds of COVID-19 test positivity (adjusted odds ratio or AOR: 5.03, 95% confidence interval [CI]: 1.70-14.88), whereas black females had higher odds of COVID-19 test positivity (AOR: 1.92, 95% CI: 1.01-3.62) compared to their white counterparts. Conclusions: Opioid overdose, more often than COVID-19, impacted the health of patients with OUD presenting to a public safety net health system. Despite a female advantage documented in the general population for COVID-19 susceptibility, COVID-19 test positivity rates were similar across sex in an OUD cohort; yet, racial disparities emerged with notable sex-related variation. Sex and gender are important variables that modify health outcomes, including OUD and COVID-19, and should be further investigated using an intersectionality framework.

Measuring psychosocial stress during pregnancy: a multiple-group confirmatory factor analysis across race/ethnicity among Medicaid-covered pregnant women in the United States.

BACKGROUND: Differential experiences of psychosocial stress during pregnancy may contribute to racial inequities in adverse pregnancy outcomes in the US. Valid and unbiased measurement scales are needed to assess the effect of psychosocial stress on pregnancy outcomes, however, the numerous modified scales implemented to measure stress are not always validated. METHODS: The construct validity and measurement invariance of maternal stress among Medicaid-covered pregnant women (N = 1,632) were examined. Model fit estimates of three confirmatory factor analysis (CFA) models were compared to determine the appropriate measurement structure. Multiple-group CFA assessed measurement invariance across Black or African American women (51.7%) and women of all other races. RESULTS: Robust estimates of model fit supported a hierarchical CFA model composed of four latent domains of stress. Standardized factor loadings of three of these latent domains-external stress, perceived stress, and enhancers of stress- indicated positive correlations with a second-order latent factor for overall maternal stress, whereas the fourth domain, buffers of stress, had a negative association. Multiple-group CFA demonstrated strong measurement invariance. CONCLUSIONS: Among Medicaid-covered pregnant women, measures for psychosocial stress were unbiased across two subgroups of maternal race/ethnicity. These findings support the construct validity of overall maternal stress underlying the common variability among four latent domains of stress.

California Healthy Places Index: Frames Matter.

INTRODUCTION: We describe the California Healthy Places Index (HPI) and its performance relative to other indexes for measuring community well-being at the census-tract level. The HPI arose from a need identified by health departments and community organizations for an index rooted in the social determinants of health for place-based policy making and program targeting. The index was geographically granular, validated against life expectancy at birth, and linked to policy actions. MATERIALS AND METHODS: Guided by literature, public health experts, and a positive asset frame, we developed a composite index of community well-being for California from publicly available census-tract data on place-based factors linked to health. The 25 HPI indicators spanned 8 domains; weights were derived from their empirical association with tract-level life expectancy using weighted quantile sums methods. RESULTS: The HPI's domains were aligned with the social determinants of health and policy action areas of economic resources, education, housing, transportation, clean environment, neighborhood conditions, social resources, and health care access. The overall HPI score was the sum of weighted domain scores, of which economy and education were highly influential (50% of total weights). The HPI was strongly associated with life expectancy at birth (r = 0.58). Compared with the HPI, a pollution-oriented index did not capture one-third of the most disadvantaged quartile of census tracts (representing 3 million Californians). Overlap of the HPI's most disadvantaged quartile of census tracts was greater for indexes of economic deprivation. We visualized the HPI percentile ranking as a web-based mapping tool that presented the HPI at multiple geographies and that linked indicators to an action-oriented policy guide. PRACTICE IMPLICATIONS: The framing of indexes and specifications such as domain weighting have substantial consequences for prioritizing disadvantaged populations. The HPI provides a model for tools and new methods that help prioritize investments and identify multisectoral opportunities for policy action.