SSM - Population Health

Introduction: Economic opportunity is a core pillar of the American Dream but is not distributed equally across communities. Substantial evidence has identified economic opportunity as an independent social determinant of health, but relatively little is known about opportunity's relationship with other socioeconomic characteristics such as income. Here we address this gap in the literature to examine how area-level economic opportunity modifies the income-health gradient. Methods: We used multivariable ordinary least squares models to estimate the association between self-reported health and economic opportunity across household income levels for working age adults (ages 25-64). Our measures of income and health come from the 2010-2019 Current Population Survey Annual Social and Economic Supplements. Our measure of economic opportunity was drawn from Opportunity Insights and represents the county-averaged national income percentile rank attained in adulthood for individuals born to parents at the 25th percentile of the income distribution. We adjusted for a wide range of individual- and county-level demographic and socioeconomic characteristics. Results: We find that county-level economic opportunity modified the gradient in self-reported health and household income among working-age adults. Effects were particularly pronounced in the lowest income deciles -- an interdecile increase in economic opportunity was associated with closing almost 33% of the gap in health between the lowest and highest income deciles. The results were robust to sensitivity analyses. Conclusion: We show that local area economic opportunity flattens the relationship between household income and health, with lower-income individuals benefitting the most from living in high opportunity areas.

Abrupt changes in mortality rates and life expectancy allow us to understand how shocks like COVID-19 can exacerbate health inequalities across groups. We look at Washington, D.C., a major city with a diverse population and long-standing socio-economic divisions, to describe the all-cause mortality trends from 2015 to 2021 by age, sex, race, and ward of residence. We report differences in cause-specific mortality pre- and post-COVID-19 outbreak and estimate the Years of Life Lost (YLL) attributable to COVID-19. We compute death rates using information from death certificates and the Census, and we calculate YLL using the life table approach, comparing the life expectancy of people with and without COVID-19. We find that in 2020 and 2021, there were respectively 1,128 and 629 excess deaths (158 per 100K and 94 per 100K) compared to the annual average over the previous five years, and 689 and 363 deaths in 2020 and 2021, respectively (97 per 100K and 54 per 100K) listing COVID-19 as a cause of death. Death rates in 2020 and 2021, compared to the five previous years, were higher for men than women by about 12pp and 5pp and occurred almost entirely among residents 45 and older. Excess deaths between 2020 and 2021 were higher for Black and Hispanic residents by about 286 and 97 per 100K, respectively--with the highest proportional increase (almost twofold) for Hispanics in 2020. YLL was highest for Hispanic males and lowest for White females. Significance StatementThe leading causes of death in DC were historically heart disease and cancer. In 2020, the leading cause of death was COVID. Accidental and violent deaths increased dramatically and disproportionately by race. Racial disparities in COVID and non-COVID deaths indicate that these correlate with socioeconomic conditions. Life expectancy in the United States decreased for the first time in 2020 due to COVID-19. In the nations capital, the decline in life expectancy was more significant for Hispanic and non-Hispanic Black than White people, widening the already large difference in life expectancy among these groups.

IntroductionPeople in low-income households face a disproportionate burden of health and economic consequences brought on by the COVID-19 pandemic, including COVID-19 and food insufficiency. State minimum wage and paid sick leave policies may affect whether people are vulnerable to employment and health shocks to income and affect food insufficiency. MethodsWe evaluated the relationship between state minimum wage policies and the outcome of household food insufficiency among participants younger than 65 during the COVID-19 pandemic. We used data from biweekly, state representative Census Pulse surveys conducted between August 19 and December 21, 2020. We conducted analyses in the full population under age 65 years, who are most likely to work, and in households with children. The primary exposure was state minimum wage policies in four categories: less than $8.00, $8.00 to $9.99, $10.00 to $11.99, and $12.00 or more. A secondary exposure was missing work due to COVID-19, interacted with whether participants reported not having paid sick leave. Food insufficiency was defined as sometimes or often not having enough to eat in the past seven days. Very low child food sufficiency was defined as children sometimes or often not eating enough in the past seven days because of inability to afford food. We conducted a multivariable modified Poisson regression analysis to estimate adjusted prevalence ratios and marginal effects. We clustered standard errors by state. To adjust for state health and social programs, we adjusted for health insurance and receipt of supplemental nutrition assistance program benefits, unemployment insurance, and stimulus payments as well as for population demographic characteristics associated with food insufficiency. We conducted subgroup analyses among populations most likely to be affected by minimum wage policies: Participants who reported any work in the past seven days, who reported <$75,000 in 2019 household income, or who had a high school education or less. We conducted falsification tests among participants less likely to be directly affected by policies, [&ge;]65 years or with >$75,000 in 2019 household income. ResultsIn states with a minimum wage of less than $8.00, 14.3% of participants under age 65 and 16.6% of participants in households with children reported household food insufficiency, while 10.3% of participants reported very low child food sufficiency. A state minimum wage of $12 or more per hour was associated with a 1.83 percentage point reduction in the proportion of households reporting food insufficiency relative to a minimum wage of less than $8.00 per hour (95% CI: -2.67 to -0.99 percentage points). In households with children, a state minimum wage of $12 or more per hour was associated with a 2.13 percentage point reduction in household food insufficiency (95% CI: -3.25 to -1.00 percentage points) and in very low child food sufficiency (-1.16 percentage points, 95% CI: -1.69 to -0.63 percentage points) relative to a state minimum wage of less than $8.00 per hour. Minimum wages of $8.00 to $9.99 and $10.00 to $11.99 were not associated with changes in child food insufficiency or very low child food sufficiency relative to less than $8.00 per hour. Subgroup analyses and sensitivity analyses were consistent with the main results. Estimates were of a lesser magnitude (<0.6 percentage points) in populations that should be less directly affected by state minimum wage policies. Missing work due to COVID-19 without paid sick leave was associated with a 5.72 percentage point increase in the proportion of households reporting food insufficiency (95% CI: 3.59 to 7.85 percentage points). DiscussionFood insufficiency is high in all households and even more so in households with children during the COVID-19 pandemic. Living in a state with at least a $12 minimum wage was associated with a decrease in the proportion of people reporting food insufficiency during the COVID-19 pandemic. Not having paid leave was associated with increases in food insufficiency among people who reported missing work due to COVID-19 illness. Policymakers may wish to consider raising the minimum wage and paid sick leave as approaches to reducing food insufficiency during and after the COVID-19 pandemic.

Several analyses have highlighted racial and ethnic disparities related to COVID-19 health outcomes across the United States. Less focus has been placed on more localized contexts, such as carceral settings, where racial and ethnic inequities in COVID-19 health outcomes also exist, but the proximal drivers of inequality are different. In this study, we analyzed mortality rates among incarcerated people in the Texas Department of Criminal Justice (TDCJ) to assess racial and ethnic differences in COVID-19 mortality. We obtained monthly demographic and mortality information of the TDCJ population from April 1, 2019 to March 31, 2021 from TDCJ monthly reports and open record requests filed by the Texas Justice Initiative. We estimated the risk of COVID-19 mortality for the Hispanic and Black population relative to the White population using a Bayesian regression framework, adjusting for sex and age. In the first 12 months of the pandemic, Hispanic and Black all-cause mortality rates were higher than that of the White population, reversing the pattern observed the 12 months prior. Adjusted risk of COVID-19 mortality relative to the White population was 1.96 (CI 1.32-2.93) for the Hispanic population and 1.66 (CI 1.10-2.52) for the Black population. We find that COVID-19 mortality has disproportionately impacted Hispanic and Black individuals within the TDCJ population. As the proximal mechanisms which drive these inequalities are likely different than those which lead to racial inequalities in the non-incarcerated populations, future studies should look to assess and address the specific drivers of COVID-19 related disparities in carceral settings.

IntroductionLow educational attainment is associated with increased risk of COVID-19 mortality, but it remains unclear whether the link between education and COVID-19 mortality is causal or due to confounding factors, such as childhood socio-economic status or cognitive skills. To address this question, we evaluated whether older adults risk of COVID-19 mortality was associated with historical state-level compulsory schooling laws (CSLs) applicable when they were school-aged. We also evaluated whether that impact was unique to COVID-19 mortality or also applied to all-cause mortality, both before and during the pandemic. MethodsWe defined mortality outcomes using US death certificate data from Mar 2019-Dec 2021 for people born in the US before 1964 in three time periods: the year prior to the pandemic (Mar 2019-Feb 2020), pandemic year 1 (Mar 2020-Feb 2021), and pandemic year 2 (Mar-Dec 2021). We determined the population at risk using 2019 American Community Survey PUMS data with population weights, representing 78.7 million individuals born in the US before 1964. We linked individuals to the number of mandatory years of education defined by CSLs specific to their state of birth and years when school age. We estimated intention-to-treat effects of CSLs on mortality using logistic regressions controlling for state-of-birth fixed effects, birth year (linear and quadratic), sex, race, ethnicity, and state-level factors including percent urban, Black, and foreign-born (at age 6) and manufacturing jobs per capita and average manufacturing wages (at age 14). ResultsWe identified a dose-response relationship between CSLs and mortality. In the first year of the pandemic, people mandated to receive 8 vs 9 (reference) years of education had higher odds of COVID-19 mortality (Odds Ratio [OR]: 1.15; 95% Confidence Interval [CI]: 1.10, 1.19), while those mandated to receive 10 vs 9 (reference) years of education had lower odds of COVID-19 mortality (OR: 0.96; 95% CI: 0.94, 0.98). The association of CSLs with COVID-19 mortality was similar in pandemic years 1 and 2; for all-cause mortality in pandemic years 1 and 2; and for all-cause mortality in the year prior to the pandemic. Results were robust to alternative model specifications. ConclusionsThese findings support a causal benefit of education for reduced mortality during the COVID-19 pandemic. State investments in childrens education may have reduced pandemic-era mortality decades later. Our research has implications beyond the pandemic context, as our results suggest the observed relationship mirrors a pre-existing relationship between CSLs and all-cause mortality.

BackgroundExcess death for Black people compared with White people is a measure of health equity. We sought to determine the excess deaths under the age of 65 (<65) for Black people in the United States (US) over the most recent 20-year period. We also compared the excess deaths for Black people with a cause of death that is traditionally reported. MethodsWe used the Center of Disease Control (CDC) WONDERs Multiple Cause of Death 1999-2019 dataset to report age-adjusted mortality rates among non-Hispanic Black (Black) and non-Hispanic White (White) people and to calculate annual age-adjusted <65 excess deaths for Black people from 1999-2019. We measured the difference in mortality rates between Black and White people and the 20-year and 5-year trends using linear regression. We compared age-adjusted <65 excess deaths for Black people to the primary causes of death among <65 Black people in the US. ResultsFrom 1999 to 2019, the age-adjusted mortality rate for Black men was 1,186 per 100,000 and for White men was 921 per 100,000, for a difference of 265 per 100,000. The age-adjusted mortality rate for Black women was 802 per 100,000 and for White women was 664 per 100,000, for a difference of 138 per 100,000. While the gap for men and women is less than it was in 1999, it has been increasing among men since 2014. These differences have led to many Black people dying before age 65. In 1999, there were 22,945 age-adjusted excess deaths among Black women <65 and in 2019 there were 14,444--deaths that would not have occurred had their risks been the same as those of White women. Among Black men, 38,882 age-adjusted excess <65 deaths occurred in 1999 and 25,850 in 2019. When compared to the top 5 causes of deaths among <65 Black people, death related to disparities would be the highest mortality rate among both <65 Black men and women. CommentIn the US, over the recent 20-year period, disparities in mortality rates resulted in between 61,827 excess deaths in 1999 and 40,294 excess deaths in 2019 among <65 Black people. The race-based disparity in the US was the leading cause of death among <65 Black people. Societal commitment and investment in eliminating disparities should be on par with those focused on other leading causes of death such as heart disease and cancer.

American mortality rates have diverged in recent years between those with and without a four-year college degree, and there are many reasons to expect the education-mortality gradient to have steepened during the pandemic. Those without a BA are more likely to work in frontline occupations, to rely on public transportation, and to live in crowded quarters, all of which are associated with an increase in infection risk, a risk that was zero prior to the pandemic. We use publicly available data from the National Center for Health Statistics on deaths by age, sex, education and race/ethnicity to assess the protective effect of a BA in 2020 compared to 2019. While the BA was strongly protective during 2020, the ratio of mortality rates between those with and without a degree was little changed relative to pre-pandemic years. Among 60 groups (gender by race/ethnicity by age) that are available in the data, the relative risk reduction associated with a BA fell for more than half the groups between 2019 and 2020, and increased by more than 5 percentage points for only five groups. Our main finding is not that the BA was protective against death in 2020, which has long been the case, but that the protective effect was little different than in 2019 and earlier years, in spite of the change in the pattern of risk by occupation and income. The virus maintained the mortality-education gradient that existed pre-pandemic, at least through the end of 2020. Our results suggest that changes in the risk of infection were less important in structuring mortality than changes in the risk of death conditional on infection.

Objectives: To assess whether higher state-level community-based U.S. Immigration and Customs Enforcement (ICE) arrest rates are associated with adverse mental health outcomes among Hispanic and non-Hispanic adults in the United States. Design: Retrospective analysis using individual-level data from the 2023 and 2024 Behavioral Risk Factor Surveillance System (BRFSS) linked to monthly state-level ICE arrest records from the Deportation Data Project. Two-way fixed effects models assessed associations between mental health outcomes and ICE arrests, net of secular trends, state-specific time invariant factors, and individual covariates. Setting/participants: The sample included 534,099 US adults aged 18 years or older residing in all 50 states and the District of Columbia surveyed between September 2023 and December 2024. Analyses exploited within-state month-to-month variation in enforcement intensity with state and year-month fixed effects. Outcome measures: Number of poor mental health days in the past 30 days; any poor mental health days (binary); mental health status (3-level categorical); frequent mental distress ([&ge;]14 poor mental health days); and a composite indicator combining depressive disorder diagnosis with frequent mental distress. Results: Among 534,099 respondents (approximately 10% Hispanic), higher ICE arrest rates were significantly associated with worse mental health among Hispanic adults, including 0.19 additional poor mental health days per month (p < 0.05), a 2.2% higher likelihood of reporting any poor mental health days (p < 0.01), and a 2.4% increase in composite mental health problems (p < 0.01). Associations were concentrated among Hispanic women and those with a high school diploma or less. Among non-Hispanic adults, estimates were small and precisely centered around zero across outcomes. Similar findings obtained in difference-in-differences event study models, models including lagged exposures, and models with leave-one-out state exclusions. Conclusion: Higher community-based immigration enforcement was associated with worse mental health outcomes among Hispanic adults but not among non-Hispanic adults. Contemporary enforcement strategies may have broader psychological spillover effects within Hispanic communities, and mental health may be an underrecognized social cost of interior immigration enforcement.

BackgroundViolence across the life course is a persistent global problem with well-documented health and social consequences. Less is known about its relationship with labour market outcomes in high-income countries with strong social protections, such as Canada. This study examines whether lifetime exposure to physical or sexual violence is associated with labour force participation (LFP), reasons for economic inactivity, sectoral and occupational sorting, and income. MethodsWe analyzed data from the 2018 Canadian Survey on Safety in Public and Private Spaces (SSPPS), a nationally representative cross-sectional survey linked to 2018 administrative tax records. The analytic sample included working-age adults (18-64) with complete data on violence exposure and labour market outcomes. Lifetime violence exposure captured childhood abuse, adulthood non-partner violence, and intimate partner violence. Outcomes included past-year LFP, part- versus full-time work, employment sector and occupation, and annual personal income. We described labour market patterns by gender and exposure and used inverse probability weighted regression adjustment (IPWRA) to estimate average treatment effects (ATEs) on economic inactivity, using unexposed men as the reference group. ResultsNearly 62 percent of respondents reported lifetime violence exposure (64.5 percent of women, 59.1 percent of men). Past-year labour force participation was high (85.9 percent overall) and showed minimal differences by exposure status: 82.0 percent of exposed women versus 80.3 percent of unexposed women, and 90.7 percent of exposed men versus 90.1 percent of unexposed men. IPWRA models indicated that, relative to unexposed men, exposed women had small but statistically significant increases in the probability of health-related inactivity (ATE: 0.009; 95%CI: 0.000-0.017) and early retirement (ATE: 0.015; 95%CI: 0.000 to 0.031), whereas ATEs for exposed men were small and non-significant across all outcomes. Sectoral and occupational distributions differed chiefly by gender; within-gender differences by exposure were limited. Income patterns were inconsistent by exposure status. For example, among women with secondary education or less, exposed women earned markedly less than unexposed women ($34,604 vs. $39,913), while differences among men were smaller and uniformly negative (exposed $74,981 vs. unexposed $75,208). ConclusionsIn Canadas welfare-state context, lifetime violence exposure shows limited association with labour force participation but may influence specific pathways into inactivity and sectoral sorting. Longitudinal analyses are needed to clarify longer-term economic impacts.

ImportanceAmid efforts in the United States to promote health equity, there is a need to assess progress in reducing excess deaths and years of potential life lost (YPLL) among Black people compared with White people. ObjectiveTo evaluate trends in excess mortality and YPLL among Black people compared with White people. DesignSerial cross-sectional. SettingNational data from the Centers for Disease Control and Prevention, 1999-2020 ParticipantsNon-Hispanic White and non-Hispanic Black people ExposuresRace as documented in the death certificates. Main outcomes and measuresExcess age-adjusted all-cause and disease-specific mortality rate (per 100,000 individuals) and YPLL among Black people compared with White people. ResultsFrom 1999 to 2020, the total number of excess deaths was 658,356 and 1,154,108 among Black females and males, representing 34,938,070 and 47,005,048 excess YPLL among Black females and males. The excess deaths and YPLL were largest among infants and non-elderly adults. Heart disease had the most excess deaths. From 1999, the age-adjusted excess mortality rate declined at an annual average of -9.0 (95% CI: -10.0, -8.0; P<0.001) until 2015 among Black women and at an annual average of -16.3 (95% CI: -20.9, -11.6; P<0.001) until 2012 among Black men, followed by no significant change until 2019 in either group. From 2019 to 2020, excess deaths increased from 90.4 to 192 per 100,000 Black women and from 209.8 to 395 per 100,000 Black men, reaching rates approximating those of 1999. The trends in rates of excess YPLL followed a similar pattern. Conclusions and relevanceOver a recent 22-year period, Black people in the US lost more than 80 million years of life when compared with White people. After a period of progress, improvements stalled, and most gains were eliminated in 2020. KEY POINTSO_ST_ABSQuestionC_ST_ABSHow many excess deaths and years of potential life lost (YPLL) for Black people, compared with White people, occurred in the United States from 1999 through 2020? FindingsBased on Centers for Disease Control and Prevention data, excess deaths and YPLL persisted throughout the period, with initial progress followed by little improvement, and then worsening in 2020 to about 1999 levels. Black people had 1.8 million excess deaths and over 80 million YPLL over the study period. MeaningAfter initial progress, excess mortality and YPLL among Black people stagnated and then worsened, indicating a need for new approaches.

A better understanding of whether and how economic factors impact mental health can inform policy and program decisions to improve mental health. This study looked at the association between county-level economic factors and the prevalence of self-reported poor mental health among adults in US counties in 2019, overall and separately for urban and rural counties. General dominance analyses were completed to rank-order the relative importance of the selected variables in explaining county prevalence of adults reporting > 14 poor mental health days in the last 30 days ("poor mental health"). The highest weighted variables were assessed for the statistical significance of their relationships with county-level poor mental health through multiple linear regression. Across all models, the four highest-ranked economic factors were household income, receipt of Supplemental Security Income (SSI), population with a college degree, and receipt of Supplemental Nutrition Assistance Program (SNAP) benefits. The overall, rural, and urban models explained over 69% of the variation in poor mental health prevalence between counties. Urban and rural models also showed notable differences in the relationship between poor mental health and median home value and population with public insurance. The findings from this study indicate a significant association between several economic factors and poor mental health, which may inform decision makers in addressing mental health in the US.

Place-based disorder and social cohesion may influence LGBTQIA+ adults physical and mental health in meaningful ways given their heightened exposure to minority stress and discrimination. However, few studies have examined these associations. Using a sample of 3790 LGBTQIA+ adults in 786 counties from The Population Research in Identity and Disparities for Equality Study, we assessed associations of place-based disorder and social cohesion with depressive symptoms, perceived stress, and physical health using linear mixed models. We tested effect modification by gender modality and ethnoracial group. Residing in counties with higher social cohesion by 1-unit was associated with 1.06 lower points (95% CI -1.56, -0.56) for depressive symptoms, 1.60 lower points (95% CI -2.26, -0.94) for perceived stress, and 1.17 higher points (95% CI 0.43, 1.90) for physical health. Residence in counties with higher place-based disorder by 1-unit was only associated with 1.17 higher points (95% CI 0.32, 2.01) for perceived stress; no association was observed for depressive symptoms or physical health. Findings indicate that physical and social environments are important to the health of LGBTQIA+ individuals.

IntroductionExperiences of discrimination and bias in health care contribute to health disparities for LGBTQ+ and other minority populations. To avoid discrimination, many LGBTQ+ people go to great lengths to find healthcare providers who they trust and are knowledgeable about their health needs. This study examines whether access to an LGBTQ+ affirming provider may improve health outcomes for LGBTQ+ populations across a range of preventive health and chronic disease management outcomes. MethodsThis cross-sectional study uses Poisson regression models to examine original survey data (n=1,120) from Wave 1 of the Vanderbilt University Social Networks, Aging, and Policy Study (VUSNAPS), a panel study examining older (50{square}76 years) LGBTQ+ adults health and aging, collected between April 2020 and September 2021. ResultsOverall, access to an LGBTQ+ affirming provider is associated with greater uptake of preventive health screenings and improved management of mental health conditions among older LGBTQ+ adults. Compared to participants reporting a usual source of care that is not affirming, participants with an LGBTQ+ affirming provider are more likely to have ever and recently received several types of preventive care, including past year provider visit, flu shot, colorectal cancer screening, and HIV test. Access to an LGBTQ+ affirming provider is also associated with better management of mental health conditions. ConclusionsInclusive care is essential for reducing health disparities among LGBTQ+ populations. Health systems can reduce disparities by expanding education opportunities for providers regarding LGBTQ+ medicine, adopting nondiscrimination policies for LGBTQ+ patients and employees, and ensuring LGBTQ+ care is included in health insurance coverage.

Objective: To examine if food insecurity moderates the relationship between rurality and mental health outcomes (suicide mortality, poor mental health days, frequent mental distress) and to assess if these effects vary across U.S. Census divisions. Methods: This county-level (n=2,397) cross-sectional study used OLS and spatial error regression to analyze public data from sources including the County Health Rankings and USDA. We modeled suicide mortality, poor mental health days, and frequent mental distress as functions of the Index of Relative Rurality (IRR) and food insecurity, controlling for median income and provider rates. The suicide model was also tested across nine U.S. Census divisions. Results: Baseline models revealed a paradox: rurality was a direct risk factor for suicide (B=0.400) but protective for poor mental health days (B=-0.224). The national multivariable model revealed a significant, positive rurality-food insecurity interaction for suicide mortality (B=0.861), indicating a synergistic risk. This interaction was not significant for general mental distress, which was more strongly predicted by income and food insecurity. Regional analysis confirmed the suicide interaction was potent in five divisions, including the Pacific (B=3.048) and Mountain (B=1.712) , but absent in others (e.g., South Atlantic). Conclusions: The drivers of suicide are distinct from those of general mental distress and are geographically heterogeneous. The interaction of rurality and food insecurity creates a compounded risk for suicide. Suicide prevention must be regionally-tailored and address structural inequalities, such as food insecurity, alongside clinical care.

BackgroundLife expectancy is a critical measure of population health. In the U.S., Black Americans have historically experienced lower life expectancy than White Americans due to factors such as health insurance inequities, socioeconomic disparities, and systemic barriers. Though the Black-White life expectancy gap narrowed after 1990, it has fluctuated in recent years, influenced by socioeconomic changes and the COVID-19 pandemic. ObjectiveThis study examines how national-level differences in education and income contributed to the Black-White life expectancy gap in the United States from 2007 to 2018. MethodsData were analyzed from the National Health and Nutrition Examination Survey (2007-2018) and its Linked Mortality File. Using 3 survival models, this study assessed life expectancy at age 20 for Non-Hispanic Black (NHB) and Non-Hispanic White (NHW) populations. Covariates included education and income. ResultsThe unadjusted life expectancy gap at age 20 between NHB and NHW individuals averaged 3 years. Adjusting for education using a flexible parametric survival model reduced the gap by 50%, while adjusting for income reduced the gap by 75%. When both factors were adjusted simultaneously, two survival models indicated that NHB life expectancy slightly exceeded NHW life expectancy. Income disparities persisted across educational levels, signifying unequal economic returns to education. ConclusionsAddressing income disparities is essential for reducing racial inequities in life expectancy. Policies promoting both equitable education access and income equivalence are critical for achieving health equity and improving population health.

We examine the mortality effects of a 1947 school reform in Japan, which extended compulsory schooling from primary to secondary school by as much as 3 years. The abolition of secondary school fees also indicates that those affected by the reform likely came from disadvantaged families who could have benefited the most from schooling. Even in this relatively favorable setting, we fail to find that the reform improved later-life mortality up to the age of 87 years, although it significantly increased years of schooling. This finding suggests limited health returns to schooling at the lower level of educational attainment.

Extroverts may enjoy lower mortality than introverts under normal circumstances, but the relationship may be different during an airborne pandemic when social contact can be deadly. We used data for midlife Americans surveyed in 1995-96 with mortality follow-up through December 31, 2020 to investigate whether the association between extroversion and mortality changed during the COVID-19 pandemic. We hypothesized that excess mortality during the pandemic will be greater for extroverts than for introverts. Results were based on a Cox model estimating age-specific mortality controlling for sex, race/ethnicity, the period trend in mortality, and an additional indicator for the pandemic period (Mar-Dec 2020). We interacted extroversion with the pandemic indicator to test whether the relationship differed between prepandemic and pandemic periods. Prior to the pandemic, extroversion was associated with somewhat lower mortality (HR=0.93 per SD, 95% CI 0.88-0.97), but the relationship reversed during the pandemic: extroverted individuals appeared to suffer higher mortality than their introverted counterparts, although the effect was not significant (HR=1.20 per SD, 95% CI 0.93-1.54). Extroversion was associated with greater pandemic-related excess mortality (HR=1.20/0.93=1.29 per SD, 95% CI 1.00-1.67). Compared with someone who scored at the mean level of extroversion, mortality rates prior to the pandemic were 10% lower for a person who was very extroverted (i.e., top 12% of the sample at Wave 1), while they were 12% higher for someone who was very introverted (i.e., 11th percentile). In contrast, mortality rates during the pandemic appeared to be higher for very extroverted individuals (HR=1.15, 95% CI 0.77-1.71) and lower for those who were very introverted (HR=0.70, 95% CI 0.43-1.14) although the difference was not significant because of limited statistical power. In sum, the slight mortality advantage enjoyed by extroverts prior to the pandemic disappeared during the first 10 months of the COVID-19 pandemic. It remains to be seen whether that pattern continued into 2021-22. We suspect that the mortality benefit of introversion during the pandemic is largely a result of reduced exposure to the risk of infection, but it may also derive in part from the ability of introverts to adapt more easily to reduced social interaction without engaging in self-destructive behavior (e.g., drug and alcohol abuse). Introverts have been training for a pandemic their whole lives.

Individuals with one or more socially stigmatized identities experience extensive health disparities. However, most studies consider the effects of only individual stigmatized identities. Further, the effects of individual identities and their intersections on overall health have not been quantified. We used participant-reported survey data collected in the All of Us Research Program and released to the controlled tier in April 2023 to statistically estimate the first and second order effects of 47 stigmatized identities on self-reported overall health. After using false discovery rate to adjust for testing multiple hypotheses, 29 individual stigmas had statistically significant effects on self-reported overall health and 116 pairs of stigmas did. All significant individual effects were negative or neutral except for skin cancer. Those with the largest negative effect on self-rated overall health are difficulty walking or climbing stairs, unemployed or unable to work, difficulty with errands, and low educational attainment. Pairs of intersecting stigmas had a mix of negative and positive incremental effects, indicating that some stigmatized identities are negative modifiers, such as depression, and other combinations are less negative that the sum of their individual negative effects, such as having difficulty with multiple types of activities of daily living. Taken together, there are numerous pairs of stigmatized identities that significantly affect self-reported overall health and therefore should be considered in research and clinical care.

To assess the excess mortality burden of Covid-19 in the United States, we estimated sex, age and race stratified all-cause excess deaths in each county of the US during 2020 and 2021. Using spatial Bayesian models trained on all recorded deaths between 2003-2019, we estimated 463,187 (95% uncertainty interval (UI): 426,139 - 497,526) excess deaths during 2020, and 544,105 (95% UI: 492,202 - 592,959) excess deaths during 2021 nationally, with considerable geographical heterogeneity. Excess mortality rate (EMR) nearly doubled for each 10-year increase in age and was consistently higher among men than women. EMR in the Black population was 1.5 times that of the White population nationally and as high as 3.8 times in some states. Among the 25-54 year population excess mortality was highest in the American Indian/Alaskan Native (AI/AN) population among the four racial groups studied, and in a few states was as high as 6 times that of the White population. Strong association of EMR with county-level social vulnerability was estimated, including positive associations with prevalence of disability (standardized effect: 40.6 excess deaths per 100,000), older population (37.6), poverty (23.6), and unemployment (18.5), whereas population density (-50), higher education (-38.6), and income (-35.4) were protective. Together, these estimates provide a more reliable and comprehensive understanding of the mortality burden of the pandemic in the US thus far. They suggest that Covid-19 amplified social and racial disparities. Short-term measures to protect more vulnerable groups in future Covid-19 waves and systemic corrective steps to address long-term societal inequities are necessary. Significance StatementAll-cause excess mortality estimates, the difference between observed all-cause deaths and deaths expected in the absence of a pandemic, can help more fully assess the pandemics burden than direct Covid-19 mortality. Our estimates, based on a 17-year record of all deaths in the US and a Bayesian spatial model, quantify the differences in excess mortality across counties and by population age, race and sex, as well as between the first and second years of the pandemic. Furthermore, our results indicate that population-level socioeconomic indicators such as poverty, unemployment and educational attainment had considerable effect on excess mortality during the pandemic. Sustained efforts to protect vulnerable populations during future waves of Covid-19 (and other public health emergencies) remain vital.

ObjectivesTo disarticulate the associations of race (whiteness), class (socioeconomic status), and place (county) with risk of cause-specific death in the US. MethodsWe studied mortality in US counties for 11 causes of death (1999-2019) and COVID-19 (2020-2021). We adjusted for race and age using the American Community Survey and socioeconomic status using the Area Deprivation Index. Bayesian regressions with spatial county effects were estimated for inference. ResultsCounty whiteness and socioeconomic status modified death rates; geospatial effects differed by cause of death. Other factors equal, a 20% increase in county whiteness was associated with 5-8% increase in death from three causes and 4-15% reduction in death from others, including COVID-19. Other factors equal, advantaged counties had significantly lower death rates, even when juxtaposed with disadvantaged ones. Geospatial patterns of residual risk varied by cause of death. For example, cancer and heart disease death rates were better explained by age, socioeconomic status, and county whiteness than were COVID-19 and suicide deaths. ConclusionsThere are important independent contributions from race, class, and geography to risk of death in the US.