INTRODUCTION:Prior efforts to estimate the lives lost to racial-ethnic mortality disparities have focused on the Black-White mortality gap. This study expanded the approach by estimating avertable deaths for multiple racial-ethnic populations and drawing on multiple reference populations for comparisons. Trends over time, by sex, and by state were also examined. METHODS:Mortality data and population counts for 2001-2023 were obtained in 2025 from the Centers for Disease Control and Prevention for non-Hispanic Black, non-Hispanic White, Hispanic, and non-Hispanic Asian/Pacific Islander populations. Avertable deaths were calculated by direct standardization, drawing comparisons with multiple racial-ethnic populations with lower mortality rates. Temporal, sex-, and state-specific trends in age-adjusted avertable death rates were also examined. RESULTS:During 2001-2023, the non-Hispanic Black, non-Hispanic White, and Hispanic populations experienced 1.7-4.5 million, 12.3-21.5 million, and 1.2 million avertable deaths, depending on the reference population used for comparison. Avertable death rates decreased in the first decade of the century but then increased after 2010 in the non-Hispanic White population and after 2013 in the non-Hispanic Black and Hispanic populations, primarily in men, and surged in all populations during the COVID-19 pandemic. States with the highest avertable death rates among non-Hispanic Black, non-Hispanic White, and Hispanic populations were concentrated in the Midwest, South, and Southwest, respectively. CONCLUSIONS:Racial-ethnic disparities in mortality rates affect multiple U.S. populations and account for an enormous death toll. Using reference populations other than the non-Hispanic White population provides new insights about avertable deaths. Efforts to reduce racial-ethnic disparities will require attention to root causes and socioecologic context.

INTRODUCTION:This study utilizes the Virginia all-payer claims database (APCD) to examine the relationship between primary care utilization and emergency department (ER) use and to explore geographic variation in primary care utilization and ER use. We hypothesize that higher rates of primary care utilization will be associated with lower ER use rates, with maps showing clear geographic patterns. METHODS:This retrospective observational analysis utilized Bayesian smoothing techniques, regression analysis, and geographic information system (GIS) mapping to explore the association of ER use with primary care utilization. Our analysis included 866 ZIP Code Tabulation Areas (ZCTAs) in Virginia. RESULTS:Primary care utilization was significantly associated with ER usage rates. The results show that for every increase of 10 primary care visit rates per 1,000 population, ER use rates decline by 7 per 1,000. The maps show clusters of higher rates of PC utilization throughout central and eastern Virginia, with lower rates in many parts of southern Virginia. Higher rates of ER use are observed in western Virginia, particularly along the border with West Virginia, with clusters of lower rates in northern Virginia near Washington, DC. CONCLUSIONS:Utilizing the Virginia APCD and GIS mapping, this study finds that primary care utilization is associated with lower rates of ER use. The maps show clear geographic patterns for both ER use and primary care utilization. Important next steps include identifying priority areas, exploring their characteristics, and conducting qualitative research to better understand local factors contributing to their high or low rates of ER use.

Drug use disorders (DUDs) represent a major global health challenge, leading to substantial morbidity and mortality, while also being compounded by social and structural barriers. In this study, we examined global epidemiological trends in DUDs over the past three decades to inform clinical and public health responses. We extracted data on the incidence, deaths, and disability-adjusted life years (DALYs) attributable to DUDs from the 2021 Global Burden of Diseases, Injuries, and Risk Factors Study between 1990 and 2021. Age-standardized incidence (ASIR), mortality (ASMR), and DALY rates per 100,000 population were calculated. The analysis focused on four DUDs-opioid, amphetamine, cocaine, and cannabis use disorders-and further stratified rates by sex, Socio-demographic Index (SDI), countries, and world regions. In 2021, there were 13.6 (95% UI, 11.6-15.7) million new cases, 137,278 (95% UI, 129,269-146,181) deaths, and 15.6 (95% UI, 12.8-18.1) million DALYs attributed to DUDs. Between 1990 and 2021, the ASIR decreased by 8.1%, while the ASMR and DALY rates rose by 30.8% and 14.8%, respectively. Opioid use disorder accounted for the highest ASIR (169.4 [95% UI, 145.1-195.0] per 100,000), ASMR (1.7 [95% UI, 1.6-1.8] per 100,000), and age-standardized DALY rate (191.0 [95% UI, 156.1-222.8] per 100,000) in 2021. Sex and geographical variations were notable, with males and world regions like high-income North America, Australasia, and Eastern/Western Europe showing disproportionately higher rates. Overall, these findings highlight rising mortality and morbidity rates despite a modest decline in incidence, underscoring the need for tailored public health interventions, advancing harm reduction programs, and expanding access to treatment.

Objectives/Goals: The goals of this research are to 1) determine the prevalence of perinatal doula services use in Virginia, with a focus on individuals with substance use disorders (SUD), 2) evaluate awareness of doulas among pregnant and postpartum people with SUD, and 3) assess provider knowledge and interaction with doulas for the care of this population. Methods/Study Population: Both quantitative and qualitative methods will be used to evaluate patient and healthcare provider knowledge regarding doula services and the patient–doula–healthcare provider relationship. Surveys and semi-structured interviews will be administered to doulas, pregnant and postpartum women, and healthcare providers in this mixed-methods approach. Information from the Centers for Medicare and Medicaid Services National Provider Identifier (NPI) Registry, and doula training programs will be utilized to recruit doulas for participation. Paper and online recruitment materials will be posted to engage pregnant and postpartum individuals. Healthcare provider recruitment will occur via the NPI Registry along with contacting physicians’ practices. SAS 9.4 and NVivo will be utilized for analysis. Results/Anticipated Results: This proposed research will be an initial assessment of the current state of doula services utilization, mothers’ knowledge of doulas and their purpose, and healthcare providers’ awareness of and partnership with doulas to provide optimal birthing and postpartum experiences to the pregnant and parenting population with and without SUD. Results from this study will be disseminated to community doulas, pregnant people and mothers with substance use disorders, and relevant healthcare providers to decrease barriers to doula care and advocate for consistent, systematic documentation of doula services in the medical record and in public health surveillance systems. Discussion/Significance of Impact: This study will be the first study to assess doula services utilization in Virginia, with a specific focus on pregnant and postpartum women with substance use disorders. This work will support advocacy for improved data capture and utilization regarding doula services in order to reduce barriers to care and improve perinatal outcomes.

Violent injuries tend to cluster together geospatially. The discriminatory housing practice of redlining undertaken by the United States federal government in the 1930s has been repeatedly linked with various contemporary community-level disparities. However, no known work has explored the association between historical redlining and the risk of violent injuries among adolescents. To this end, we utilized surveillance data of adolescent patients (N = 401) who presented to a Level I trauma center in Richmond, VA, for violence-based injuries across 2 years (2022-2023). Our analyses revealed significant spatial clustering of violence events using Moran's I after controlling for population density. High violence clusters (N22 = 9, N23 = 12), and low violence clusters (N22 = 9, N23 = 10) were identified across both years. Historically redlined neighborhoods comprised most of the high-violence regions identified (i.e., 85.71% of hot spots were in redlined areas). Our findings suggest that the legacy of historic redlining practices in Richmond, VA is observable in the current-day risks of violent injury for adolescents. Interventions aimed at reducing community violence should consider how such efforts may address the extant effects of past policies (e.g., redlining) as one means of reducing violence.

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.

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.

Youth violence is a national public health concern in USA, especially in resource-constrained urban communities. Between 2018 and 2021, the Healthy Communities for Youth (HCFY) program addressed youth violence prevention in select economically marginalized urban communities, with the HCFY program reducing the likelihood of youth-involved violent crime. Leveraging costs from program expense reports, this study analyzes the costs of the HCFY program in order to inform policymaking and the program's future ongoing implementation. Total HCFY program costs were $821,000 ($290,100 annually including program start-up costs) over the 34-month project period. Operationalization costs contributed the largest share (64.8%), with 45% attributable to intervention coordinators. In the intervention community, the program costs $100 per capita, $1100 per youth-involved crime case, and $8100 per youth-involved violent crime case. Findings were sensitive to the number of youth-involved crime or violent crime cases and costs of high-level program leadership and self-evaluation analysts, with the per youth-involved violent crime case cost ranging between $700 and $1600 over the program period. Analysis of HCFY program costs is an important step in determining the affordability of a community-level program to prevent youth violence in resource-limited urban communities.

Objectives. To estimate state-level excess death rates during 2020 to 2023 and examine differences by region and partisan orientation. Methods. We modeled death and population counts from the Centers for Disease Control and Prevention to estimate excess death rates for the United States, 9 census divisions, and 50 states. We compared excess death rates for states with different partisan orientations, measured by the party of the seated governor and the level of partisan representation in state legislatures. Results. The United States experienced 1 277 697 excess deaths between March 2020 and July 2023. Almost 90% of these deaths were attributed to COVID-19, and 51.5% occurred after vaccines were available. The highest excess death rates first occurred in the Northeast and then shifted to the South and Mountain states. Between weeks ending June 20, 2020, through March 19, 2022, excess death rates were higher in states with Republican governors and greater Republican representation in state legislatures. Conclusions. Excess death rates during the COVID-19 pandemic varied considerably across the US states and were associated with partisan representation in state government, although the influence of confounding variables cannot be excluded. (Am J Public Health. 2024;114(9):882-891. https://doi.org/10.2105/AJPH.2024.307731).

Background:An extensive literature documents substantial variations in life expectancy (LE) between countries and at various levels of subnational geography. These variations in LE are significantly correlated with socioeconomic covariates, though no analyses have been produced at the finest feasible census tract (CT) level of geographic disaggregation in Canada or designed to compare Canada with the United States. Data and methods:Abridged life tables for each CT where robust estimates were feasible were estimated comparably with U.S. data. Cross-tabulations and graphical visualizations are used to explore patterns of LE across Canada, for Canada's 15 largest cities, and for the 6 largest U.S. cities. Results:LE varies by as much as two decades across CTs in both countries' largest cities. There are notable differences in the strength of associations with socioeconomic status (SES) factors across Canada's largest cities, though these associations with income-poverty rates are noticeably weaker for Canada's largest cities than for the United States' largest cities. Interpretation:Small area geographic variations in LE signal major health inequalities. The association of CT-level LE with SES factors supports and extends similar findings across many studies. The variability in these associations within Canada and compared with those in the United States reinforces the importance for population health of better understanding differences in social structures and public policies not only at the national and provincial or state levels, but also within municipalities to better inform interventions to ameliorate health inequalities.

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.

Violence is a major public health concern that particularly impacts Black young adults living in under-resourced, urban communities. There is limited research on promotive and protective factors that mitigate the impact of violence exposure on aggressive behavior. This study aims to address this gap by exploring positive factors across the ecological model in a sample of 141 predominantly Black young adults ages 18 to 22 years living in low-income communities. Regression analyses indicated that generally factors at the individual/peer and family level were more likely to be promotive. Additionally, nine significant interactions found in the moderation analyses highlighted a complex relation between ecological protective factors and aggressive behaviors for these young adults. Implications for future empirical work are discussed.

Context: There were 50,000 U.S. opioid overdose deaths in 2019. Research on opioids often focuses on communities with poor opioid-related outcomes, while studies on community-level protective factors are limited. Objective: To identify “Bright spot” communities in Virginia with lower opioid mortality than predicted based on risk factors. Dataset: Virginia All Payer Claims Database (APCD), Virginia Department of Health (VDH) statewide medical examiner registry, and American Community Survey (ACS). Time period: 2019. Population: APCD includes VA residents with medical claims through commercial, Medicaid, and Medicare coverage. VDH data includes fatal drug overdoses. ACS surveys all VA residents. Study Design and Analysis: Ecologic study. We created a multivariate model to predict opioid mortality at the community level based on socioecological, workforce, and healthcare delivery data. A generalized linear mixed model was used to calculate the magnitude of difference between actual and predicted opioid mortality per 100,000 across all census tracks in VA and to identify communities with lower mortality than predicted. A qualitative analysis was performed, using thematic coding, to review key factors associated with Bright Spots. Outcome Measures: Primary outcome: fatal opioid overdoses. Secondary outcomes: emergency room visits for opioid-related diagnoses, outpatient diagnoses for opioid use disorder, opioid prescription rate, and buprenorphine prescription rate. Results: Opioid mortality is associated with higher community percent poverty (r=.38, p<.0001), disability (r=.52, r<.0001), inequality using Gini Index as proxy (r=.23, p<.001), and rate of mental health diagnosis (r=.53, p<.001). 30 Bright Spot communities were identified. A qualitative analysis indicated 18 of the 30 Bright Spots have higher rates of buprenorphine prescriptions than the 2019 statewide median, and 28 of the 30 Bright Spots have higher rates of primary care visits than the 2019 statewide median. There were Bright Spots that fell into clusters geographically and in terms of population size. Conclusions: Our findings indicate there may be several typologies of Bright Spot communities, including various types of community-level protective factors associated with low opioid mortality. This analysis could help to inform future community-level interventions to address opioid mortality, and to potentially enable additional communities to become a Bright Spot.

Context: Over the last two years the U.S. has experienced its largest number of drug overdose deaths, with Virginia having an increase of almost 50% from 2019 to 2020. These deaths are largely a result of opioid overdoses, particularly related to the use of fentanyl. Medication-assisted treatment (MAT) improves outcomes for people with opioid use disorder, though access to treatment is still uneven across the U.S. Objective: To identify priority areas for withdrawal management (detox) and medication-assisted treatment (MAT) in the state of Virginia. Study Design and Analysis: Cross sectional approach includes geographic information systems (GIS) and co-location mapping. First, we identify opioid treatment deserts (OTDs) as areas with no DATA-waived providers, opioid treatment programs (OTPs), or Substance Abuse and Mental Health Services Administration (SAMHSA) substance abuse facilities. Next, we use co-location mapping to identify priority areas that are both high opioid overdose mortality areas and OTDs. Setting/Dataset: Virginia All-Payer Claims Database, HealthLandscape Virginia; ZIP Code Tabulation Areas (ZCTAs); OTPs and SAMHSA substance abuse facilities, SAMHSA behavioral health services locator. Outcome Measures: Opioid overdose mortality; OTDs. Results: We identified 616 ZCTAs (69.7% of all ZCTAs in Virginia) as OTDs; almost 6 in 10 of OTDs were located in metropolitan areas, while about 1 in 5 were located in the most rural areas. We also identified 183 priority areas – ZCTAs that were OTDs and in the highest quartile for opioid overdose mortality. Priority areas were scattered throughout the state and follow similar patterns for urban and rural areas as OTDs in general. Conclusions: Increasing access to evidence-based withdrawal management and medication-assisted treatment has the potential to reduce the rising number of opioid overdose deaths across the state of Virginia. Increasing access to innovative data sources such as the All-Payer Claims Database allows for combining multiple data sources to address important public health issues such as the opioid epidemic.

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.

Context: Emergency department visits are costly and often preventable. Increasing access to primary care can help reduce unnecessary emergency department visits and associated costs. Objective: To explore the relationship between primary care utilization and emergency department (ED) visits and identify areas with better-than-expected ED visit rates in the state of Virginia. Study Design and Analysis: Cross sectional approach includes regression analysis, residual analysis, and hot spot mapping (using the Local Moran's I). We first utilize an Empirical Bayes approach for smoothing various rates from the Virginia All-Payer Claims Database (APCD) and model ED visit rates on primary visit rates controlling for mental health and type 2 diabetes prevalence, health insurance status, and race. We then use Local Moran's I on the residuals to identify geographic clusters of better-than-expected bright spots ED visit rates and compare them with areas with worse-than-expected cold spots rates. Setting/Dataset: Data from the Virginia All-Payer Claims Database, HealthLandscape Virginia, and CDC PLACES are aggregated to the Zip Code Tabulation Area (ZCTAs, n=866). Outcome Measures: ED visits per 1,000 population. Results: Primary care visit rates have a significant, negative relationship with ED visit rates. Geographic clusters of bright spots (n=98) are concentrated throughout central and southwestern Virginia, while clusters of cold spots (n=70) are concentrated in northern Virginia and along the West Virginia border. Compared to cold spots, bright spots have significantly higher rates of social deprivation, lower percentages of racial and ethnic minorities, and higher rates of primary care utilization for several chronic conditions, including diabetes, and mental health. Further, bright spots have significantly higher percentages of social needs addressed by primary care. Conclusions: Consistent with previous literature, the results suggest that primary care utilization, including primary care visits for various chronic conditions and social needs, is associated with lower ED visit rates. Future research could explore qualitative approaches for better understanding the socio-environmental factors contributing to better- than-expected ED visit rates in bright spot areas. Increasing access to innovative data sources such as the All-Payer Claims Database allows for combining multiple data sources to explore primary care utilization.

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.

Context: Climate change is causing prolonged periods of extreme heat and the incidence of heat-related illness is rising. Heat-related illness is not equitably distributed. Some people and communities are at greater health risk. Nationally, this increase in healthcare utilization has significant costs. Objective: To calculate the excess number of emergency department (ED) visits and hospital admissions caused by heat event days in Virginia, identify communities with higher adverse health events, and extrapolate Virginia's findings nationally to estimate the annual cost of care. Study Design: Retrospective observational analysis. Dataset: We used data from 15 Virginia (or near) and 298 national weather stations to identify heat event days, Virginia All-Payer Claims Data to identify healthcare utilization, American Community Survey to compare community characteristics, and the Healthcare Cost & Utilization Project to estimate cost of care. Population studied: Census tract level evaluation of Virginia with national extrapolation. Analysis: Between 2016 and 2020, we calculated the per capita rate of ED visits and hospitalizations for heat-related and heat-adjacent illness. From daily climate data, we determined the number of heat event days experienced by each ZCTA and the size of the exposed population. We compared health care utilization by ZCTA on heat event days to non-heat event days. We applied Virginia's health event rates to national measures of heat events to calculate a national cost. Results: There were 80 heat-event days per year in Virginia between 2016 and 2020. During heat event days, ED visits for heat related and adjacent illness increased 179% and hospital admissions increased 217% for an additional 6967 ED visits and 1667 hospital admissions each year. Rates appeared to be higher in more vulnerable communities. Extrapolating Virginia's findings nationally and assuming average ED visits and hospital admission costs of $800 and $15,000, respectively, heat event days resulted nationwide in 234,188 ED visits, 56,037 hospital admissions, and $1.03 billion in costs every summer. Conclusions: These findings highlight the stark impact of climate change on health and demonstrate the value of integrating health, community, and environmental data. Action is needed to slow rising temperatures, raise public awareness about the risks of extreme heat, increase community resilience, and strengthen health care services.

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.

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.