Racial inequities in homicide rates and homicide methods among Black and White women aged 25-44 years in the USA, 1999-2020: a cross-sectional time series study.

BACKGROUND: In the USA, Black women aged 25-44 years are disproportionately murdered compared with their White counterparts. Despite ongoing efforts to reduce racial and structural inequities, the result of these efforts remains unclear, particularly in light of the COVID-19 pandemic. METHODS: This study examined a cross-sectional time series of homicide death rates, by race, from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research system. We included data for women aged 25-44 years between 1999 and 2020 among 30 states in the USA. Homicide death was classified using underlying cause and multiple cause of death codes; mortality rates were calculated per 100 000 based on US Census Bureau population sizes. Homicide methods were classified as firearm, cutting or piercing, and other. Firearm homicides were compared with other homicides with logistic regression including covariates of race, time, and their interaction. We report odds ratios and 95% CIs. FINDINGS: In 2020, the homicide rate among Black women was 11·6 per 100 000, compared with 3 per 100 000 among White women. This inequity has persisted over time and is virtually unchanged since 1999. Homicide inequities vary across US states; in 11 states, racial inequities have increased since 1999. The racial inequity was greatest in Wisconsin, where in 2019-20, Black women aged 25-44 years were 20 times more likely to die by homicide than White women. Homicide by firearm is increasing in frequency; women in the USA had 2·44 (95% CI 2·14-2·78) times the odds of homicide involving firearms in 2019-20 compared with 1999-2003. Firearm homicide deaths are disproportionately concentrated among Black women in every region in the USA. INTERPRETATION: Our findings suggest that there is an urgent need to address homicide inequities among Black and White women in the USA. Enacting federal legislation that reduces gun access is a crucial step. Policy makers must address long-standing structural factors that underpin elevated gun violence by implementing sustainable wealth-building opportunities; developing desegregated, mixed income and affordable housing; and increasing green spaces in communities where Black women largely reside. FUNDING: National Institute of Mental Health of the National Institutes of Health.

Bringing home the benefits: Do pro-family employee benefits mitigate the risk of depression from competing workplace and domestic labor roles?

Despite significant historical progress toward gender parity in employment status in the US, women remain more likely to provide domestic labor, creating role competition which may increase depression symptoms. Pro-family employee benefits may minimize the stress of competing roles. We tested whether depressive symptoms were higher among women with vs. without competing roles and whether this effect was greater among women without (vs. with) pro-family benefits. Data included employed women surveyed across 4 waves of the National Longitudinal Survey (2010-2019) (N=9884). Depression symptoms were measured with the Mental Health Inventory (MHI-5). The interaction between competing roles and pro-family employee benefits on depressive symptoms was also compared with non-family-related benefits, using marginal structural models to estimate longitudinal effects in the presence of time-varying confounding. MHI-5 scores were 0.56 points higher (95% CI=0.15, 0.97) among women in competing roles (vs. not). Among women without pro-family benefits, competing roles increased MHI-5 scores by 6.1-points (95% CI=1.14, 11.1). In contrast, there was no association between competing roles and MHI-5 scores among women with access to these benefits (MHI-5 difference=0.44; 95% CI=-0.2, 1.0). Results were similar for non-family-related benefits. Dual workplace and domestic labor role competition increases women's depression symptoms, though broad availability of workplace benefits may attenuate that risk.

Is nicotine vaping associated with subsequent initiation of cannabis or other substances from adolescence into young adulthood?

Prior studies estimating longitudinal associations between nicotine vaping and subsequent initiation of cannabis and other substances (e.g., cocaine, heroin) have been limited by short follow-up periods, convenience sampling, and possibly inadequate confounding control. We sought to address some of these gaps using the nationally representative Population Assessment of Tobacco and Health Study (PATH) to estimate longitudinal associations between nicotine vaping and the initiation of cannabis or other substances among adolescents transitioning to adulthood from2013 to 2019, adjusting for treatment-confounder feedback. Estimands like the longitudinal average treatment effect were not identified because of extensive practical positivity violations. Therefore, we estimated longitudinal incremental propensity score effects, which were identified. We found that reduced odds of nicotine vaping were associated with decreased risks of cannabis or other substance initiation; these associations strengthened over time. For example, by the final wave (2018-19), cannabis and other substance initiation risks were 6.2 (95%CI:4.6-7.7) and 1.8 (95%CI:0.4-3.2) percentage points lower when odds of nicotine vaping were reduced to be 90% lower in all preceding waves (2013-14 to 2016-18), as compared with observed risks. Strategies to lower nicotine vaping prevalence during this period may have resulted in fewer young people initiating cannabis and other substances.

Assessing Trends in Internalizing Symptoms among Racialized and Minoritized Adolescents: Results from the Monitoring the Future Survey 2005-2020.

Depressive symptoms have rapidly accelerated among recent US adolescent birth cohorts, yet there remains little understanding of trends among racialized and minoritized groups. These groups may experience depressive symptoms due to the deleterious effects of structural racism. Using 2005-2020 Monitoring the Future survey data, we examine all racialized groups using within-group analyses to observe trends in high depressive symptoms across cohorts. Generally, across racialized groups and ages, the odds of high depressive symptoms increased in recent birth cohorts. For example, among 15-16-year-old students racialized as American Indian or Alaska Native and Black-Hispanic/Latine, the 2003-2006 birth cohort had 3.08 (95% CI: 2.00, 4.76) and 6.95 (95% CI: 2.70, 17.88) times higher odds, respectively, of high depressive symptoms compared to the 1987-1990 birth cohorts. Moreover, in a given year 15-16-year-olds generally experienced the highest depressive symptoms compared to 13-14 and 17-18-year-olds, suggesting that age-effects peaked during mid-adolescence. Depressive symptoms increased among US adolescents by birth cohort, within all racialized and minoritized groups assessed. Public health efforts to reduce disparities may consider barriers such as structural racism that may impact the mental health of racialized/minoritized adolescents while increasing access to culturally competent mental health providers and school-based services.

Geographic Variation, Economic Activity, and Labor Market Characteristics in Trajectories of Suicide in the United States, 2008-2020.

Suicide rates in the United States have increased over the past 15 years, with substantial geographic variation in these increases; yet there have been few attempts to cluster counties by the magnitude of suicide rate changes according to intercept and slope or to identify the economic precursors of increases. We used vital statistics data and growth mixture models to identify clusters of counties by their magnitude of suicide growth from 2008 to 2020 and examined associations with county economic and labor indices. Our models identified 5 clusters, each differentiated by intercept and slope magnitude, with the highest-rate cluster (4% of counties) being observed mainly in sparsely populated areas in the West and Alaska, starting the time series at 25.4 suicides per 100,000 population, and exhibiting the steepest increase in slope (0.69/100,000/year). There was no cluster for which the suicide rate was stable or declining. Counties in the highest-rate cluster were more likely to have agricultural and service economies and less likely to have urban professional economies. Given the increased burden of suicide, with no clusters of counties improving over time, additional policy and prevention efforts are needed, particularly targeted at rural areas in the West.

Simulating the Simultaneous Impact of Medication for Opioid Use Disorder and Naloxone on Opioid Overdose Death in Eight New York Counties.

BACKGROUND: The United States is in the midst of an opioid overdose epidemic; 28.3 per 100,000 people died of opioid overdose in 2020. Simulation models can help understand and address this complex, dynamic, and nonlinear social phenomenon. Using the HEALing Communities Study, aimed at reducing opioid overdoses, and an agent-based model, Simulation of Community-Level Overdose Prevention Strategy, we simulated increases in buprenorphine initiation and retention and naloxone distribution aimed at reducing overdose deaths by 40% in New York Counties. METHODS: Our simulations covered 2020-2022. The eight counties contrasted urban or rural and high and low baseline rates of opioid use disorder treatment. The model calibrated agent characteristics for opioid use and use disorder, treatments and treatment access, and fatal and nonfatal overdose. Modeled interventions included increased buprenorphine initiation and retention, and naloxone distribution. We predicted a decrease in the rate of fatal opioid overdose 1 year after intervention, given various modeled intervention scenarios. RESULTS: Counties required unique combinations of modeled interventions to achieve a 40% reduction in overdose deaths. Assuming a 200% increase in naloxone from current levels, high baseline treatment counties achieved a 40% reduction in overdose deaths with a simultaneous 150% increase in buprenorphine initiation. In comparison, low baseline treatment counties required 250-300% increases in buprenorphine initiation coupled with 200-1000% increases in naloxone, depending on the county. CONCLUSIONS: Results demonstrate the need for tailored county-level interventions to increase service utilization and reduce overdose deaths, as the modeled impact of interventions depended on the county's experience with past and current interventions.

Changing adolescent activity patterns and the correlation of self-esteem and externalizing mental health symptoms across time: results from the USA from 1991 through 2020.

BACKGROUND: Common adolescent psychiatric symptoms cluster into two dominant domains: internalizing and externalizing. Both domains are linked to self-esteem, which serves as a protective factor against a wide range of internalizing and externalizing problems. This study examined trends in US adolescents' self-esteem and externalizing symptoms, and their correlation, by sex and patterns of time use. METHODS: Using Monitoring the Future data (N = 338 896 adolescents, grades:8/10/12, years:1991-2020), we generated six patterns of time use using latent profile analysis with 17 behavior items (e.g. sports participation, parties, paid work). Groups were differentiated by high/low engagement in sports and either paid work or high/low peer socialization. Within each group, we mapped annual, sex-stratified means of (and correlation between) self-esteem and externalizing factors. We also examined past-decade rates of change for factor means using linear regression and mapped proportions with top-quartile levels of poor self-esteem, externalizing symptoms, or both. RESULTS: We found consistent increases in poor self-esteem, decreases in externalizing symptoms, and a positive correlation between the two across nearly all activity groups. We also identified a relatively constant proportion of those with high levels of both in every group. Increases in poor self-esteem were most pronounced for female adolescents with low levels of socializing, among whom externalizing symptoms also increased. CONCLUSIONS: Rising trends in poor self-esteem are consistent across time use groups, as is the existence of a group facing poor self-esteem and externalizing symptoms. Effective interventions for adolescents' poor self-esteem/co-occurring symptoms are needed broadly, but especially among female adolescents with low peer socialization.

Annual Research Review: Sex, gender, and internalizing conditions among adolescents in the 21st century - trends, causes, consequences.

Internalizing conditions of psychopathology include depressive and anxiety disorders; they most often onset in adolescence, are relatively common, and contribute to significant population morbidity and mortality. In this research review, we present the evidence that internalizing conditions, including depression and anxiety, as well as psychological distress, suicidal thoughts and self-harm, and fatal suicide, are considerably increasing in adolescent populations across many countries. Evidence indicates that increases are currently greatest in female adolescents. We present an epidemiological framework for evaluating the causes of these increases, and synthesize research on whether several established risk factors (e.g., age of pubertal transition and stressful life events) and novel risk factors (e.g., digital technology and social media) meet conditions necessary to be plausible causes of increases in adolescent internalizing conditions. We conclude that there are a multitude of potential causes of increases in adolescent internalizing conditions, outline evidence gaps including the lack of research on nonbinary and gender nonconforming populations, and recommend necessary prevention and intervention foci from a clinical and public health perspective.

Hindcasts and forecasts of suicide mortality in US: A modeling study.

Deaths by suicide, as well as suicidal ideations, plans and attempts, have been increasing in the US for the past two decades. Deployment of effective interventions would require timely, geographically well-resolved estimates of suicide activity. In this study, we evaluated the feasibility of a two-step process for predicting suicide mortality: a) generation of hindcasts, mortality estimates for past months for which observational data would not have been available if forecasts were generated in real-time; and b) generation of forecasts with observational data augmented with hindcasts. Calls to crisis hotline services and online queries to the Google search engine for suicide-related terms were used as proxy data sources to generate hindcasts. The primary hindcast model (auto) is an Autoregressive Integrated Moving average model (ARIMA), trained on suicide mortality rates alone. Three regression models augment hindcast estimates from auto with call rates (calls), GHT search rates (ght) and both datasets together (calls_ght). The 4 forecast models used are ARIMA models trained with corresponding hindcast estimates. All models were evaluated against a baseline random walk with drift model. Rolling monthly 6-month ahead forecasts for all 50 states between 2012 and 2020 were generated. Quantile score (QS) was used to assess the quality of the forecast distributions. Median QS for auto was better than baseline (0.114 vs. 0.21. Median QS of augmented models were lower than auto, but not significantly different from each other (Wilcoxon signed-rank test, p > .05). Forecasts from augmented models were also better calibrated. Together, these results provide evidence that proxy data can address delays in release of suicide mortality data and improve forecast quality. An operational forecast system of state-level suicide risk may be feasible with sustained engagement between modelers and public health departments to appraise data sources and methods as well as to continuously evaluate forecast accuracy.

Adverse childhood experiences among black sexually minoritized men and Black transgender women in Chicago.

BACKGROUND: Adverse childhood experiences (ACE) are important predictors of mental health outcomes in adulthood. However, commonly used ACE measures such as the Behavioural Risk Factor Surveillance System (BRFSS) have not been validated among Black sexually minoritized men (SMM) nor transgender women (TW), whom are known to have higher rates of ACE and poorer mental health outcomes. Assessing the psychometric properties of the measure is important for health equity research, as measurements that are not valid for some populations will render uninterpretable results. METHODS: Data are drawn from the Neighborhoods and Networks (N2) study, a longitudinal cohort of Black SMM and TW living in Southern Chicago. We conducted confirmatory factor analysis, correlation analysis and a two-parameter Item Response Theory (IRT) on the BRFSS ACE measure, an 11-item measure with 8 domains of ACE. RESULTS: One hundred forty seven participants (85% cisgender male) completed the BRFSS ACE measurement in the N2 study with age ranges from 16-34. The cohort were from a low socioeconomic background: about 40% of the cohort were housing insecure and made than $10,000 or less annually. They also have a high number of ACEs; 34% had endorsed 4 or more ACE domains. The three-factor structure fit the BRFSS ACE measure best; the measurement consisted of three subscales: of "Household Dysfunction", "Emotional / Physical", and "Sexual Abuse" (CFI = 0.975, TLI = 0.967, and RMSEA = 0.051). When the 8 domains of ACE were summed to one score, the total score was is correlated with depressive symptoms and anxiety scores, establishing concurrent validity. Item Response Theory model indicated that the "parental separation" domain had a low discrimination (slope) parameter, suggesting that this domain does not distinguish well between those with and without high ACE. CONCLUSIONS: The BRFFS ACE measure had adequate reliability, a well-replicated structure and some moderate evidence of concurrent validity among Black SMM and TW. The parental separation domain does not discriminate between those with high and low ACE experiences in this population. With changing population demographics and trends in marriage, further examination of this item beyond the current study is warranted to improve health equity research for all.

Examining racial and ethnic heat exposure disparities in New York City (NYC) across different spatial and political scales through geographic effect measure modification.

Structural racism in the United States has resulted in neighborhoods with higher proportions of non-Hispanic Black (Black) or Hispanic/Latine residents having more features that intensify, and less that cool, the local-heat environment. This study identifies areas of New York City (NYC) where racial/ethnic heat exposure disparities are concentrated. We analyzed data from the 2013-2017 American Community Survey, U.S Landsat-8 Analysis Ready Data on summer surface temperatures, and NYC Land Cover Dataset at the census tract-level (n = 2098). Four cross-sectional regression modeling strategies were used to estimate the overall City-wide association, and associations across smaller intra-city areas, between tract-level percent of Black and percent Hispanic/Latine residents and summer day surface temperature, adjusting for altitude, shoreline, and nature-cover: overall NYC linear, borough-specific linear, Community District-specific linear, and geographically weighted regression models. All three linear regressions identified associations between neighborhood racial and ethnic composition and summer day surface temperatures. The geographically weighted regression models, which address the issue of spatial autocorrelation, identified specific locations (such as northwest Bronx, central Brooklyn, and uptown Manhattan) within which racial and ethnic disparities for heat exposures are concentrated. Through examining the overall effects and geographic effect measure modification across spatial scales, the results of this study identify specific geographic areas for intervention to mitigate heat exposure disparities experienced by Black and Hispanic/Latine NYC residents.

Social and economic determinants of drug overdose deaths: a systematic review of spatial relationships.

PURPOSE: To synthesize the available evidence on the extent to which area-level socioeconomic conditions are associated with drug overdose deaths in the United States. METHODS: We performed a systematic review (in MEDLINE, EMBASE, PsychINFO, Web of Science, EconLit) for papers published prior to July 2022. Eligible studies quantitatively estimated the association between an area-level measure of socioeconomic conditions and drug overdose deaths in the US, and were published in English. We assessed study quality using the Effective Public Health Practice Project Quality Assessment Tool. The protocol was preregistered at Prospero (CRD42019121317). RESULTS: We identified 28 studies that estimated area-level effects of socioeconomic conditions on drug overdose deaths in the US. Studies were scored as having moderate to serious risk of bias attributed to both confounding and in analysis. Socioeconomic conditions and drug overdose death rates were moderately associated, and this was a consistent finding across a large number of measures and differences in study designs (e.g., cross-sectional versus longitudinal), years of data analyzed, and primary unit of analysis (e.g., ZIP code, county, state). CONCLUSIONS: This review highlights the evidence for area-level socioeconomic conditions are an important factor underlying the geospatial distribution of drug overdose deaths in the US and the need to understand the mechanisms underlying these associations to inform future policy recommendations. The current evidence base suggests that, at least in the United States, employment, income, and poverty interventions may be effective targets for preventing drug overdose mortality rates.

Poverty and birth cohort effects of experiencing the 2007-2009 Great Recession during adolescence on major depressive episodes and mental health treatment of young adults in the United States.

PURPOSE: Household economic adversity during adolescence is hypothesized to be a risk factor for poor mental health later in life. To test this hypothesis, we conducted a quasi-experimental analysis of an economic shock, the Great Recession of 2007-2009. We tested if going through adolescence during the Great Recession was associated with increased risk of major depressive episodes (MDE) and mental health treatment in young adulthood with potential moderation by household poverty to explore differences by economic adversity. METHODS: We analyzed data on young adults age 18-29 years from the 2005-2019 National Survey on Drug Use and Health (N = 145,394). We compared participants who were adolescents during the recession to those followed-up prior to the recession. Regression analysis tested effect modification by household poverty status. RESULTS: Adolescent exposure to the Great Recession was associated with higher likelihood of MDE during young adulthood (aOR = 1.30, 95% CI = 1.23, 1.37); there was no relationship with mental health treatment. Effects on MDE were stronger among those in households with higher incomes compared to those living in poverty. CONCLUSION: Findings support the hypothesis that exposure to the Great Recession during adolescence may have increased risk for MDE, but raise questions about whether the mechanism of this association is economic distress.

Generalized and racialized consequences of the police response to intimate partner violence in the U.S.: A systematic scoping review.

Intimate partner violence (IPV) impacts more than 40% of people in the U.S. Since the 1980s, the U.S. has maintained a police-centric response to IPV, which relies on arrest-via policies like mandatory arrest laws-as its primary intervention. There is mixed evidence on whether IPV policing decreases subsequent IPV at the individual level, but less is known about IPV policing's broader collateral consequences. This systematic scoping review is the first to synthesize existing evidence for the generalized consequences of IPV policing in the U.S. We searched Web of Science, ProQuest, and EBSCO Host, and identified 36 relevant articles. Survivor criminalization was the most studied generalized consequence of IPV policing and existing studies have documented positive associations between mandatory arrest laws and risk of survivor arrest. We also found numerous methodologically rigorous studies on the effects of mandatory arrest laws on population-level IPV victimization. The review also identifies gaps in the evidence base: there is a need for research on additional potential consequences of IPV policing such as police violence against survivors, involvement of child protective services, and psychosocial and physical health outcomes of survivors.

Causal Knowledge as a Prerequisite for Interrogating Bias: Reflections on Hernán et al. 20 Years Later.

In their seminal 2002 paper, "Causal Knowledge as a Prerequisite for Confounding Evaluation: An Application to Birth Defects Epidemiology," Hernán et al. (Am J Epidemiol. 2002;155(2):176-184) emphasized the importance of using theory rather than data to guide confounding control, focusing on colliders as variables that share characteristics with confounders but whose control may actually introduce bias into analyses. In this commentary, we propose that the importance of this paper stems from the connection the authors made between nonexchangeability as the ultimate source of bias and structural representations of bias using directed acyclic graphs. This provided both a unified approach to conceptualizing bias and a means of distinguishing between different sources of bias, particularly confounding and selection bias. Drawing on examples from the paper, we also highlight unresolved questions about the relationship between collider bias, selection bias, and generalizability and argue that causal knowledge is a prerequisite not only for identifying confounders but also for developing any hypothesis about potential sources of bias.

Relative Age Within School Grade, Including Delayed and Accelerated School Start: Associations With Midlife Psychiatric Disorders, Suicide, and Alcohol- and Drug-Related Mortality.

Within a school grade, children who are young for grade are at increased risk of psychiatric diagnoses, but the long-term implications remain understudied, and associations with students who delay or accelerate entry underexplored. We used Norwegian birth cohort records (birth years: 1967-1976, n = 626,928) linked to records in midlife. On-time school entry was socially patterned; among those born in December, 23.0% of children in the lowest socioeconomic position (SEP) delayed school entry, compared with 12.2% among the highest SEP. Among those who started school on time, there was no evidence for long-term associations between birth month and psychiatric/behavioral disorders or mortality. Controlling for SEP and other confounders, delayed school entry was associated with increased risk of psychiatric disorders and mortality. Children with delayed school entry were 1.31 times more likely to die by suicide (95% confidence interval: 1.07, 1.61) by midlife, and 1.96 times more likely to die from drug-related death (95% confidence interval: 1.59, 2.40) by midlife than those born late in the year who started school on time. Associations with delayed school entry are likely due to selection, and results thus underscore that long-term health risks can be tracked early in life, including through school entry timing, and are highly socially patterned.

Investigating a Paradox: Toward a Better Understanding of the Relationships Between Racial Group Membership, Stress, and Major Depressive Disorder.

Epidemiologic studies in the United States routinely report a lower or equal prevalence of major depressive disorder (MDD) for Black people relative to White people. Within racial groups, individuals with greater life stressor exposure experience greater prevalence of MDD; however, between racial groups this pattern does not hold. Informed by theoretical and empirical literature seeking to explain this "Black-White depression paradox," we outline 2 proposed models for the relationships between racial group membership, life stressor exposure, and MDD: an effect modification model and an inconsistent mediator model. Either model could explain the paradoxical within- and between-racial group patterns of life stressor exposure and MDD. We empirically estimated associations under each of the proposed models using data from 26,960 self-identified Black and White participants in the National Epidemiologic Survey on Alcohol and Related Conditions III (United States, 2012-2013). Under the effect modification model, we estimated relative risk effect modification using parametric regression with a cross-product term, and under the inconsistent mediation model, we estimated interventional direct and indirect effects using targeted minimum loss-based estimation. We found evidence of inconsistent mediation (i.e., direct and indirect effects operating in opposite directions), suggesting a need for greater consideration of explanations for racial patterns in MDD that operate independent of life stressor exposure. This article is part of a Special Collection on Mental Health.

Prediction of Suicide Attempts Among Persons with Depression: A Population-Based Case Cohort Study.

Studies have highlighted the potential importance of modeling interactions for suicide attempt prediction. This case-cohort study identified risk factors for suicide attempts among persons with depression in Denmark using statistical approaches that do (random forests) or do not model interactions (least absolute shrinkage and selection operator regression [LASSO]). Cases made a non-fatal suicide attempt (n = 6,032) between 1995 and 2015. The comparison subcohort was a 5% random sample of all persons in Denmark on January 1, 1995 (n = 11,963). We used random forests and LASSO for sex-stratified prediction of suicide attempts from demographic variables, psychiatric and somatic diagnoses, and treatments. Poisonings, psychiatric disorders, and medications were important predictors for both sexes. Area under the receiver operating characteristic curve (AUC) values were higher in LASSO models (0.85 [95% CI = 0.84, 0.86] in men; 0.89 [95% CI = 0.88, 0.90] in women) than random forests (0.76 [95% CI = 0.74, 0.78] in men; 0.79 [95% CI = 0.78, 0.81] in women). Automatic detection of interactions via random forests did not result in better model performance than LASSO models that did not model interactions. Due to the complex nature of psychiatric comorbidity and suicide, modeling interactions may not always be the optimal statistical approach to enhancing suicide attempt prediction in high-risk samples.

Epidemiologic trends and risk factors associated with the decline in mortality from coronary heart disease in the United States, 1990-2019.

BACKGROUND: Despite the decline in the rate of coronary heart disease (CHD) mortality, it is unknown how the 3 strong and modifiable risk factors - alcohol, smoking, and obesity -have impacted these trends. We examine changes in CHD mortality rates in the United States and estimate the preventable fraction of CHD deaths by eliminating CHD risk factors. METHODS: We performed a sequential time-series analysis to examine mortality trends among females and males aged 25 to 84 years in the United States, 1990-2019, with CHD recorded as the underlying cause of death. We also examined mortality rates from chronic ischemic heart disease (IHD), acute myocardial infarction (AMI), and atherosclerotic heart disease (AHD). All underlying causes of CHD deaths were classified based on the International Classification of Disease 9th and 10th revisions. We estimated the preventable fraction of CHD deaths attributable to alcohol, smoking, and high body-mass index (BMI) through the Global Burden of Disease. RESULTS: Among females (3,452,043 CHD deaths; mean [standard deviation, SD] age 49.3 [15.7] years), the age-standardized CHD mortality rate declined from 210.5 in 1990 to 66.8 per 100,000 in 2019 (annual change -4.04%, 95% CI -4.05, -4.03; incidence rate ratio [IRR] 0.32, 95% CI, 0.41, 0.43). Among males (5,572,629 CHD deaths; mean [SD] age 47.9 [15.1] years), the age-standardized CHD mortality rate declined from 442.4 to 156.7 per 100,000 (annual change -3.74%, 95% CI, -3.75, -3.74; IRR 0.36, 95% CI, 0.35, 0.37). A slowing of the decline in CHD mortality rates among younger cohorts was evident. Correction for unmeasured confounders through a quantitative bias analysis slightly attenuated the decline. Half of all CHD deaths could have been prevented with the elimination of smoking, alcohol, and obesity, including 1,726,022 female and 2,897,767 male CHD deaths between 1990 and 2019. CONCLUSIONS: The decline in CHD mortality is slowing among younger cohorts. The complex dynamics of risk factors appear to shape mortality rates, underscoring the importance of targeted strategies to reduce modifiable risk factors that contribute to CHD mortality.

Changes in Opioid and Benzodiazepine Poisoning Deaths After Cannabis Legalization in the US: A County-level Analysis, 2002-2020.

BACKGROUND: Cannabis legalization for medical and recreational purposes has been suggested as an effective strategy to reduce opioid and benzodiazepine use and deaths. We examined the county-level association between medical and recreational cannabis laws and poisoning deaths involving opioids and benzodiazepines in the US from 2002 to 2020. METHODS: Our ecologic county-level, spatiotemporal study comprised 49 states. Exposures were state-level implementation of medical and recreational cannabis laws and state-level initiation of cannabis dispensary sales. Our main outcomes were poisoning deaths involving any opioid, any benzodiazepine, and opioids with benzodiazepines. Secondary analyses included overdoses involving natural and semi-synthetic opioids, synthetic opioids, and heroin. RESULTS: Implementation of medical cannabis laws was associated with increased deaths involving opioids (rate ratio [RR] = 1.14; 95% credible interval [CrI] = 1.11, 1.18), benzodiazepines (RR = 1.19; 95% CrI = 1.12, 1.26), and opioids+benzodiazepines (RR = 1.22; 95% CrI = 1.15, 1.30). Medical cannabis legalizations allowing dispensaries was associated with fewer deaths involving opioids (RR = 0.88; 95% CrI = 0.85, 0.91) but not benzodiazepine deaths; results for recreational cannabis implementation and opioid deaths were similar (RR = 0.81; 95% CrI = 0.75, 0.88). Recreational cannabis laws allowing dispensary sales was associated with consistent reductions in opioid- (RR = 0.83; 95% CrI = 0.76, 0.91), benzodiazepine- (RR = 0.79; 95% CrI = 0.68, 0.92), and opioid+benzodiazepine-related poisonings (RR = 0.83; 95% CrI = 0.70, 0.98). CONCLUSIONS: Implementation of medical cannabis laws was associated with higher rates of opioid- and benzodiazepine-related deaths, whereas laws permitting broader cannabis access, including implementation of recreational cannabis laws and medical and recreational dispensaries, were associated with lower rates. The estimated effects of the expanded availability of cannabis seem dependent on the type of law implemented and its provisions.