A hypothetical intervention to reduce inequities in anxiety for Multiracial people: simulating an intervention on childhood adversity.

Multiracial people report higher mean Adverse Childhood Experiences (ACEs) scores and prevalence of anxiety than other racial groups. Studies using statistical interactions to estimate racial differences in ACEs-anxiety associations do not show stronger associations for Multiracial people. Using data from Waves 1 (1995-97) through 4 (2008-09) of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we simulated a stochastic intervention over 1,000 resampled datasets to estimate the race-specific cases averted per 1,000 of anxiety if all racial groups had the same exposure distribution of ACEs as Whites. Simulated cases averted were greatest for the Multiracial group, (median = -4.17 cases per 1,000, 95% CI: -7.42, -1.86). The model also predicted smaller risk reductions for Black participants (-0.76, 95% CI: -1.53, -0.19). CIs around estimates for other racial groups included the null. An intervention to reduce racial disparities in exposure to ACEs could help reduce the inequitable burden of anxiety on the Multiracial population. Stochastic methods support consequentialist approaches to racial health equity, and can encourage greater dialogue between public health researchers, policymakers, and practitioners.

Risk of adverse perinatal outcomes among African-born Black women in California, 2011-2020.

BACKGROUND: African-born women have a lower risk of preterm birth and small for gestational age (SGA) birth compared to United States (US)-born Black women, however variation by country of origin is overlooked. Additionally, the extent that nativity disparities in adverse perinatal outcomes to Black women are explained by individual-level factors remains unclear. METHODS: We conducted a population-based study of non-anomalous singleton live births to US- and African-born Black women in California from 2011-2020 (n=194,320). We used age-adjusted Poisson regression models to estimate risk of preterm birth and SGA, and reported risk ratios (RR) and 95% confidence intervals (CI). Decomposition using Monte Carlo integration of the g-formula computed the percentage of disparities in adverse outcomes between US- and African-born women explained by individual-level factors. RESULTS: Eritrean women (RR 0.4; 95%CI: 0.3, 0.5) had the largest differences in risk of preterm birth and Cameroonian women (RR 0.5; 95% CI: 0.3, 0.6) in SGA birth, compared to US-born Black women. Ghanaian women had smaller differences in risk of preterm birth (RR 0.8; 95%CI: 0.7, 1.0) and SGA (RR 0.9; 95% CI 0.8, 1.1) compared to US-born women. Overall, we estimate that absolute differences in socio-demographic and clinical factors contributed to 32% of nativity-based disparities in the risk of preterm birth and 26% of disparities in SGA. CONCLUSIONS: We observed heterogeneity in risk of adverse perinatal outcomes for African- compared to US-born Black women, suggesting that nativity disparities in adverse perinatal outcomes were not fully explained by differences in individual-level factors.

Structural Racism, Mass Incarceration, and Racial and Ethnic Disparities in Severe Maternal Morbidity.

Importance: Racial and ethnic inequities in the criminal-legal system are an important manifestation of structural racism. However, how these inequities may influence the risk of severe maternal morbidity (SMM) and its persistent racial and ethnic disparities remains underinvestigated. Objective: To examine the association between county-level inequity in jail incarceration rates comparing Black and White individuals and SMM risk in California. Design, Setting, and Participants: This population-based cross-sectional study used state-wide data from California on all live hospital births at 20 weeks of gestation or later from January 1, 1997, to December 31, 2018. Data were obtained from hospital discharge and vital statistics records, which were linked with publicly available county-level data. Data analysis was performed from January 2022 to February 2023. Exposure: Jail incarceration inequity was determined from the ratio of jail incarceration rates of Black individuals to those of White individuals and was categorized as tertile 1 (low), tertile 2 (moderate), tertile 3 (high), with mean cutoffs across all years of 0 to 2.99, 3.00 to 5.22, and greater than 5.22, respectively. Main Outcome and Measures: This study used race- and ethnicity-stratified mixed-effects logistic regression models with birthing people nested within counties and adjusted for individual- and county-level characteristics to estimate the odds of non-blood transfusion SMM (NT SMM) and SMM including blood transfusion-only cases (SMM; as defined by the Centers for Disease Control and Prevention SMM index) associated with tertiles of incarceration inequity. Results: This study included 10 200 692 births (0.4% American Indian or Alaska Native, 13.4% Asian or Pacific Islander, 5.8% Black, 50.8% Hispanic or Latinx, 29.6% White, and 0.1% multiracial or other [individuals who self-identified with ≥2 racial groups and those who self-identified as "other" race or ethnicity]). In fully adjusted models, residing in counties with high jail incarceration inequity (tertile 3) was associated with higher odds of SMM for Black (odds ratio [OR], 1.14; 95% CI, 1.01-1.29 for NT SMM; OR, 1.20, 95% CI, 1.01-1.42 for SMM), Hispanic or Latinx (OR, 1.24; 95% CI, 1.14-1.34 for NT SMM; OR, 1.20; 95% CI, 1.14-1.27 for SMM), and White (OR, 1.02; 95% CI, 0.93-1.12 for NT SMM; OR, 1.09; 95% CI, 1.02-1.17 for SMM) birthing people, compared with residing in counties with low inequity (tertile 1). Conclusions and Relevance: The findings of this study highlight the adverse maternal health consequences of structural racism manifesting via the criminal-legal system and underscore the need for community-based alternatives to inequitable punitive practices.

Structural racism, nativity and risk of adverse perinatal outcomes among Black women.

BACKGROUND: Black women in the United States (US) have the highest risk of preterm birth (PTB) and small for gestational age (SGA) births, compared to women of other racial groups. Among Black women, there are disparities by nativity whereby foreign-born women have a lower risk of PTB and SGA compared to US-born women. Differential exposure to racism may confer nativity-based differences in adverse perinatal outcomes between US- and foreign-born Black women. This remains unexplored among US- and African-born women in California. OBJECTIVES: Evaluate the relationship between structural racism, nativity, PTB and SGA among US- and African-born Black women in California. METHODS: We conducted a population-based study of singleton births to US- and African-born Black women in California from 2011 to 2017 (n = 131,424). We examined the risk of PTB and SGA by nativity and neighbourhoods with differing levels of structural racism, as measured by the Index of Concentration at the Extremes. We fit crude and age-adjusted Poisson regression models, estimated using generalized estimating equations, with risk ratios (RR) and 95% confidence intervals (CI) as the effect measure. RESULTS: The proportions of PTB and SGA were 9.7% and 14.5%, respectively, for US-born women, while 5.6% and 8.3% for African-born women. US-born women (n = 24,782; 20.8%) were more likely to live in neighbourhoods with high structural racism compared to African-born women (n = 1474; 11.6%). Structural racism was associated with an elevated risk of PTB (RR 1.19, 95% CI 1.12, 1.26) and SGA (RR 1.19, 95% CI 1.13, 1.25) for all Black women, however, there was heterogeneity by nativity, with US-born women experiencing a higher magnitude of effect than African-born women. CONCLUSIONS: Among Black women in California, exposure to structural racism and the impacts of structural racism on the risk of PTB and SGA varied by nativity.

Racial differences in associations between adverse childhood experiences and physical, mental, and behavioral health.

Purpose: Adverse childhood experiences (ACEs) are associated with poor adulthood health. Multiracial people have elevated mean ACEs scores and risk of several outcomes. We aimed to determine whether this group should be targeted for prevention efforts. Methods: We analyzed three waves (1994-2009) of the National Longitudinal Study of Adolescent to Adult Health (n = 12,372) in 2023, estimating associations between four or more ACEs and physical (metabolic syndrome, hypertension, asthma), mental (anxiety, depression), and behavioral (suicidal ideation, drug use) outcomes. We estimated adjusted risk ratios for each outcome in modified Poisson models interacting race and ACEs. We used the interaction contrast to estimate race-specific excess cases per 1000 relative to Multiracial participants. Results: Excess case estimates of asthma were smaller for White (-123 cases, 95% CI: -251, -4), Black (-141, 95% CI: -285, -6), and Asian (-169, 95% CI: -334, -7) participants compared to Multiracial participants. Black (-100, 95% CI: -189, -10), Asian (-163, 95% CI: -247, -79) and Indigenous (-144, 95% CI: -252, -42) participants had fewer excess cases of and weaker relative scale association with anxiety compared to Multiracial participants. Conclusions: Adjusted associations with asthma and anxiety appear stronger for Multiracial people. Existing ACEs prevention strategies should be tailored to support Multiracial youth and families.

Racial Differences in Associations Between Adverse Childhood Experiences and Physical, Mental, and Behavioral Health.

Introduction: Adverse childhood experiences (ACEs) are associated with poor adulthood health, with individuals experiencing multiple ACEs at greatest risk. Multiracial people have high mean ACEs scores and elevated risk of several outcomes, but are infrequently the focus of health equity research. This study aimed to determine whether this group should be targeted for prevention efforts. Methods: We analyzed Waves 1 (1994-95), 3 (2001-02), and 4 (2008-09) of the National Longitudinal Study of Adolescent to Adult Health (n = 12,372) in 2023, estimating associations between four or more ACEs and physical (metabolic syndrome, hypertension, asthma), mental (anxiety, depression), and behavioral (suicidal ideation, drug use) outcomes. We estimated risk ratios for each outcome in modified Poisson models with a race × ACEs interaction, adjusted for hypothesized confounders of the ACE-outcome relationships. We used the interaction contrast to estimate excess cases per 1,000 individuals for each group relative to Multiracial participants. Results: Excess case estimates of asthma were significantly smaller for White (-123 cases, 95% CI: -251, -4), Black (-141, 95% CI: -285, -6), and Asian (-169, 95% CI: -334, -7) participants compared to Multiracial participants. Black (-100, 95% CI: -189, -10), Asian (-163, 95% CI: -247, -79) and Indigenous (-144, 95% CI: -252, -42) participants had significantly fewer excess cases of and weaker (p < 0.001) relative scale association with anxiety compared to Multiracial participants. Conclusions: Adjusted associations between ACEs and asthma or anxiety appear stronger for Multiracial people than other groups. ACEs are universally harmful but may contribute disproportionately to morbidity in this population.

A hypothetical intervention to reduce inequities in anxiety for Multiracial people: simulating an intervention on childhood adversity.

Multiracial people report higher mean Adverse Childhood Experiences (ACEs) scores and prevalence of anxiety than other racial groups. Studies using statistical interactions to estimate racial differences in ACEs-anxiety associations do not show stronger associations for Multiracial people. Using data from Waves 1 (1995-97) through 4 (2008-09) of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we simulated a stochastic intervention over 1,000 resampled datasets to estimate the race-specific cases averted per 1,000 of anxiety if all racial groups had the same exposure distribution of ACEs as Whites. Simulated cases averted were greatest for the Multiracial group, (median = -4.17 cases per 1,000, 95% CI: -7.42, -1.86). The model also predicted smaller risk reductions for Black participants (-0.76, 95% CI: -1.53, -0.19). CIs around estimates for other racial groups included the null. An intervention to reduce racial disparities in exposure to ACEs could help reduce the inequitable burden of anxiety on the Multiracial population. Stochastic methods support consequentialist approaches to racial health equity, and can encourage greater dialogue between public health researchers, policymakers, and practitioners.

Comparing Two-way Fixed Effects and New Estimators for Difference-in-Differences: A Simulation Study and Empirical Example.

BACKGROUND: Two-way fixed effects methods have been used to estimate effects of policies adopted in different places over time, but they can provide misleading results when effects are heterogeneous or dynamic, and alternate methods have been proposed. METHODS: We compared methods for estimating the average treatment effect on the treated (ATT) under staggered adoption of policies, including two-way fixed effects, group-time ATT, cohort ATT, and target-trial approaches. We applied each method to assess the impact of Medicaid expansion on preterm birth using the National Center for Health Statistics' birth records. We compared each estimator's performance in a simulation parameterized to mimic the empirical example. We generated constant, heterogeneous, and dynamic effects and calculated bias, mean squared error, and confidence interval coverage of each estimator across 1000 iterations. RESULTS: Two-way fixed effects estimated that Medicaid expansion increased the risk of preterm birth (risk difference [RD], 0.12; 95% CI = 0.02, 0.22), while the group-time ATT, cohort ATT, and target-trial approaches estimated protective or null effects (group-time RD, -0.16; 95% CI = -0.58, 0.26; cohort RD, -0.02; 95% CI = -0.46, 0.41; target trial RD, -0.16; 95% CI = -0.59, 0.26). In simulations, two-way fixed effects performed well when treatment effects were constant and less well under heterogeneous and dynamic effects. CONCLUSIONS: We demonstrated why new approaches perform better than two-way fixed effects when treatment effects are heterogeneous or dynamic under a staggered policy adoption design, and created simulation and analysis code to promote understanding and wider use of these methods in the epidemiologic literature.

Incidence, Timing, and Factors Associated With Suicide Among Patients Undergoing Surgery for Cancer in the US.

Importance: The risk and timing of suicide among patients who undergo surgery for cancer remain largely unknown, and, to our knowledge, there are currently no organized programs in place to implement regular suicide screening among this patient population. Objective: To evaluate the incidence, timing, and factors associated with suicide among patients undergoing cancer operations. Design, Setting, and Participants: This retrospective population-based cohort study used data from the Surveillance, Epidemiology, and End Results Program database to examine the incidence of suicide, compared with the general US population, and timing of suicide among patients undergoing surgery for the 15 deadliest cancers in the US from 2000 to 2016. A Fine-Gray competing risks regression model was used to identify factors associated with an increased risk of suicide among patients in the cohort. Data were analyzed from September 2021 to January 2022. Exposures: Surgery for cancer. Main Outcomes and Measures: Incidence, compared with the general US population, timing, and factors associated with suicide after surgery for cancer. Results: From 2000 to 2016, 1 811 397 patients (74.4% female; median [IQR] age, 62.0 [52.0-72.0] years) met study inclusion criteria. Of these patients, 1494 (0.08%) committed suicide after undergoing surgery for cancer. The incidence of suicide, compared with the general US population, was statistically significantly higher among patients undergoing surgery for cancers of the larynx (standardized mortality ratio [SMR], 4.02; 95% CI, 2.67-5.81), oral cavity and pharynx (SMR, 2.43; 95% CI, 1.93-3.03), esophagus (SMR, 2.25; 95% CI, 1.43-3.38), bladder (SMR, 2.09; 95% CI, 1.53-2.78), pancreas (SMR, 2.08; 95% CI, 1.29-3.19), lung (SMR, 1.73; 95% CI, 1.47-2.02), stomach (SMR, 1.70; 95% CI, 1.22-2.31), ovary (SMR, 1.64; 95% CI, 1.13-2.31), brain (SMR, 1.61; 95% CI, 1.12-2.26), and colon and rectum (SMR, 1.28; 95% CI, 1.16-1.40). Approximately 3%, 21%, and 50% of suicides were committed within the first month, first year, and first 3 years after surgery, respectively. Patients who were male, White, and divorced or single were at greatest risk of suicide. Conclusions and Relevance: In this cohort study, the incidence of suicide among patients undergoing cancer operations was statistically significantly elevated compared with the general population, highlighting the need for programs to actively implement regular suicide screening among such patients, especially those whose demographic and tumor characteristics are associated with the highest suicide risk.

Harnessing Google Health Trends Data for Epidemiologic Research.

Interest in using internet search data, such as that from the Google Health Trends Application Programming Interface (GHT-API), to measure epidemiologically relevant exposures or health outcomes is growing due to their accessibility and timeliness. Researchers enter search term(s), geography, and time period, and the GHT-API returns a scaled probability of that search term, given all searches within the specified geographic-time period. In this study, we detailed a method for using these data to measure a construct of interest in 5 iterative steps: first, identify phrases the target population may use to search for the construct of interest; second, refine candidate search phrases with incognito Google searches to improve sensitivity and specificity; third, craft the GHT-API search term(s) by combining the refined phrases; fourth, test search volume and choose geographic and temporal scales; and fifth, retrieve and average multiple samples to stabilize estimates and address missingness. An optional sixth step involves accounting for changes in total search volume by normalizing. We present a case study examining weekly state-level child abuse searches in the United States during the coronavirus disease 2019 pandemic (January 2018 to August 2020) as an application of this method and describe limitations.

US shelter in place policies and child abuse Google search volume during the COVID-19 pandemic.

The COVID-19 pandemic has led to unemployment, school closures, movement restrictions, and social isolation, all of which are child abuse risk factors. Our objective was to estimate the effect of COVID-19 shelter in place (SIP) policies on child abuse as captured by Google searches. We applied a differences-in-differences design to estimate the effect of SIP on child abuse search volume. We linked state-level SIP policies to outcome data from the Google Health Trends Application Programming Interface. The outcome was searches for child abuse-related phrases as a scaled proportion of total searches for each state-week between December 31, 2017 and June 14, 2020. Between 914 and 1512 phrases were included for each abuse subdomain (physical, sexual, and emotional). Eight states and DC were excluded because of suppressed outcome data. Of the remaining states, 38 introduced a SIP policy between March 19, 2020 and April 7, 2020 and 4 states did not. The introduction of SIP generally led to no change, except for a slight reduction in child abuse search volume in weeks 8-10 post-SIP introduction, net of changes experienced by states that did not introduce SIP at the same time. We did not find strong evidence for an effect of SIP on child abuse searches. However, an increase in total search volume during the pandemic that may be differential between states with and without SIP policies could have biased these findings. Future work should examine the effect of SIP at the individual and population level using other data sources.

Excess Google Searches for Child Abuse and Intimate Partner Violence During the COVID-19 Pandemic: Infoveillance Approach.

BACKGROUND: The COVID-19 pandemic has created environments with increased risk factors for household violence, such as unemployment and financial uncertainty. At the same time, it led to the introduction of policies to mitigate financial uncertainty. Further, it hindered traditional measurements of household violence. OBJECTIVE: Using an infoveillance approach, our goal was to determine if there were excess Google searches related to exposure to child abuse, intimate partner violence (IPV), and child-witnessed IPV during the COVID-19 pandemic and if any excesses are temporally related to shelter-in-place and economic policies. METHODS: Data on relative search volume for each violence measure was extracted using the Google Health Trends application programming interface for each week from 2017 to 2020 for the United States. Using linear regression with restricted cubic splines, we analyzed data from 2017 to 2019 to characterize the seasonal variation shared across prepandemic years. Parameters from prepandemic years were used to predict the expected number of Google searches and 95% prediction intervals (PI) for each week in 2020. Weeks with searches above the upper bound of the PI are in excess of the model's prediction. RESULTS: Relative search volume for exposure to child abuse was greater than expected in 2020, with 19% (10/52) of the weeks falling above the upper bound of the PI. These excesses in searches began a month after the Pandemic Unemployment Compensation program ended. Relative search volume was also heightened in 2020 for child-witnessed IPV, with 33% (17/52) of the weeks falling above the upper bound of the PI. This increase occurred after the introduction of shelter-in-place policies. CONCLUSIONS: Social and financial disruptions, which are common consequences of major disasters such as the COVID-19 pandemic, may increase risks for child abuse and child-witnessed IPV.

Area-level racial prejudice and health: A systematic review.

BACKGROUND: In recent years, there has been growing interest in "moving beyond the individual" to measure area-level racism as a social determinant of health. Much of this work has aggregated racial prejudice data collected at the individual-level to the area-level. OBJECTIVE: As this is a rapidly emerging area of research, we conducted a systematic literature review to describe evidence of the relationship between area-level racial prejudice and health, whether results differed by race/ethnicity, and to characterize key conceptual and methodological considerations to guide future research. METHOD: We searched four interdisciplinary databases for US-based, peer-reviewed articles measuring area level racial prejudice by aggregating individual-level indicators of racial prejudice and examining associations with mental or physical health outcome(s). Data extraction followed PRISMA guidelines and also included theory and conceptualization, pathways to health, and strengths and limitations. RESULTS: Fourteen of 14,632 identified articles met inclusion criteria and were included in the review. Health outcomes spanned all-cause (n = 4) and cause-specific (n = 4) mortality, birth outcomes (n = 4), cardiovascular outcomes (n = 2), mental health (n = 1), and self-rated health (n = 1). All studies found a positive association between area-level racial prejudice and adverse health outcomes among racial/ethnic minoritized groups, with four studies also showing a similar association among Whites. Engagement with formal theory was limited and exposure conceptualization was mixed. Methodological considerations included unmeasured confounding and trade-offs between generalizability, self-censorship, and specificity of measurement. CONCLUSIONS: Future research should continue to develop the conceptual and methodological rigor of this work and test hypotheses to inform evidence-based interventions to advance population health and reduce racial health inequities. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Hyper-localized measures of air pollution and risk of preterm birth in Oakland and San Jose, California.

BACKGROUND: US preterm-birth rates are 1.6 times higher for Black mothers than for White mothers. Although traffic-related air pollution (TRAP) may increase the risk of preterm birth, evaluating its effect on preterm birth and disparities has been challenging because TRAP is often measured inaccurately. This study sought to estimate the effect of TRAP exposure, measured at the street level, on the prevalence of preterm birth by race/ethnicity. METHODS: We linked birth-registry data with TRAP measured at the street level for singleton births in sampled communities during 2013-2015 in Oakland and San Jose, California. Using logistic regression and marginal standardization, we estimated the effects of exposure to black carbon, nitrogen dioxide and ultrafine particles on preterm birth after confounder adjustment and stratification by race/ethnicity. RESULTS: There were 8823 singleton births, of which 760 (8.6%) were preterm. Shifting black-carbon exposure from the 10th to the 90th percentile was associated with: 6.8%age point higher risk of preterm birth (95% confidence interval = 0.1 to 13.5) among Black women; 2.1%age point higher risk (95% confidence interval = -1.1 to 5.2) among Latinas; and inconclusive null findings among Asian and White women. For Latinas, there was evidence of a positive association between the other pollutants and risk of preterm birth, although effect sizes were attenuated in models that co-adjusted for other TRAP. CONCLUSIONS: Exposure to TRAP, especially black carbon, may increase the risk of preterm birth for Latina and Black women but not for Asian and White women.

A New Approach for Classifying Fetal Growth Restriction.

BACKGROUND: Fetal growth restriction is commonly defined using small for gestational age (SGA) birth (birthweight < 10th percentile) as a proxy, but this approach is problematic because most SGA infants are small but healthy. In this proof-of-concept study, we sought to develop a new approach for identifying fetal growth restriction at birth that combines information on multiple, imperfect measures of fetal growth restriction in a probabilistic manner. METHODS: We combined information on birthweight, placental weight, placental malperfusion lesions, maternal disease, and fetal acidemia using latent profile analysis to classify fetal growth in births at the Royal Victoria Hospital in Montreal, Canada, 2001-2009. We examined the clinical characteristics and health outcomes of infants classified as growth-restricted and nongrowth-restricted by our model, and among the subgroup of growth-restricted infants who had a birthweight ≥10th percentile (i.e., would have been missed by the conventional SGA proxy). RESULTS: Among 26,077 births, 345 (1.3%) were classified as growth-restricted by our latent profile model. Growth-restricted infants were more likely than nongrowth-restricted infants to have an Apgar score <7 (10% vs. 2%), have hypoglycemia at birth (17% vs. 3%), require neonatal intensive care unit admission (59% vs. 6%), die in the perinatal period (3.8% vs. 0.2%), and require an emergency cesarean delivery (42% vs. 15%). Risks remained elevated in growth-restricted infants who were not SGA, suggesting our model identified at-risk infants not detected using the SGA proxy. CONCLUSIONS: Latent profile analysis is a promising strategy for classifying growth restriction at birth in fetal growth restriction research.

Declining Life Expectancy in the United States: Missing the Trees for the Forest.

In recent years, life expectancy in the United States has stagnated, followed by three consecutive years of decline. The decline is small in absolute terms but is unprecedented and has generated considerable research interest and theorizing about potential causes. Recent trends show that the decline has affected nearly all race/ethnic and gender groups, and the proximate causes of the decline are increases in opioid overdose deaths, suicide, homicide, and Alzheimer's disease. A slowdown in the long-term decline in mortality from cardiovascular diseases has also prevented life expectancy from improving further. Although a popular explanation for the decline is the cumulative decline in living standards across generations, recent trends suggest that distinct mechanisms for specific causes of death are more plausible explanations. Interventions to stem the increase in overdose deaths, reduce access to mechanisms that contribute to violent deaths, and decrease cardiovascular risk over the life course are urgently needed to improve mortality in the United States.

Suicide, overdose and worker exit in a cohort of Michigan autoworkers.

BACKGROUND: In recent decades, suicide and fatal overdose rates have increased in the US, particularly for working-age adults with no college education. The coincident decline in manufacturing has limited stable employment options for this population. Erosion of the Michigan automobile industry provides a striking case study. METHODS: We used individual-level data from a retrospective cohort study of 26 804 autoworkers in the United Autoworkers-General Motors cohort, using employment records from 1970 to 1994 and mortality follow-up from 1970 to 2015. We estimated HRs for suicide or fatal overdose in relation to leaving work, measured as active or inactive employment status and age at worker exit. RESULTS: There were 257 deaths due to either suicide (n=202) or overdose (n=55); all but 21 events occurred after leaving work. The hazard rate for suicide was 16.1 times higher for inactive versus active workers (95% CI 9.8 to 26.5). HRs for suicide were elevated for all younger age groups relative to those leaving work after age 55. Those 30-39 years old at exit had the highest HR for suicide, 1.9 (95% CI 1.2 to 3.0). When overdose was included, the rate increased by twofold for both 19- to 29-year-olds and 30- to 39-year-olds at exit. Risks remained elevated when follow-up was restricted to 5 years after exit. CONCLUSIONS: Autoworkers who left work had a higher risk of suicide or overdose than active employees. Those who left before retirement age had higher rates than those who left after, suggesting that leaving work early may increase the risk.

Using change in a seat belt law to study racially-biased policing in South Carolina.

Seat belt laws have increased seat belt use in the US and contributed to reduced fatalities and injuries. However, these policies provide the potential for increased discrimination. The objective of this study is to determine whether a change in seat belt use enforcement led to a differential change in the number of stops, arrests, and searches to White, Black and Hispanic drivers in one US state. We used data on 1,091,424 traffic stops conducted by state troopers in South Carolina in 2005 and 2006 to examine how the change from secondary to primary enforcement of seat belt use in December 2005 affected the number of stops, arrests, and searches to White, Black, and Hispanic drivers using quasi-Poisson and logistic regressions. We found that the policy led to a 50% increase in the number of non-speeding stops for White drivers, and that this increase was 5% larger among Black drivers [RR (95% CI) = 1.05 (1.00, 1.10)], but not larger among Hispanic drivers [1.00 (0.93, 1.08)]. The policy decreased arrests and searches among non-speeding stops, with larger decreases for Black vs. White drivers [RR searches = 0.86 (0.81, 0.91) and RR arrests = 0.90 (0.85, 0.96)]. For Hispanic drivers, effects of the policy change were also found among stops for speeding, which failed the falsification test and suggested that other changes likely affected this group. These findings may support the hypothesis of differential enforcement of seat belt policy in South Carolina for Black and White drivers.