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Intensifying storms and inter-annual El Niño events may increase psychological stress and worsen mental health. This study examines the relationship between flood exposure and long-term mental health symptoms among adolescents and young people in Peru, the world’s most affected country by El Niño. We analyzed community and self-reported survey data from the Young Lives Study to contrast mental health in 2016 among youth who lived in communities that experienced or did not experience flooding between 2013 and 2016. We pre-processed data on 1344 individuals in 93 communities, using optimal full matching on Mahalanobis distance with a propensity score caliper, and estimated relative risks to mental health scores in the general population of young people and among gender-stratified groups via quasi-Poisson regression. Exposure to floods did not yield conclusive differences in mental health scores in this sample. Further evidence is needed on mental health patterns over time, the influence of exposure severity, and the impact of disaster relief on symptomology in mounting an effective global health response.

Objective: To estimate the prevalence of clinically meaningful youth mood, anxiety, behavioral, and attention symptoms across US states. Method: Data are drawn from the Adolescent Brain Cognitive Development (ABCD) study baseline wave, which included 11,876 children ages 9–10. Statistical weighting strategies generated projected state-specific prevalence estimates for the 17 states where ABCD collected data based on state socio-demographics. Twenty dimensions of mental health were assessed with the Child Behavior Checklist using recommended cut-scores to assess clinical and sub-threshold symptoms. Results: Psychopathology symptom prevalence varied by state and outcome. Projected prevalence of internalizing problems ranged from 11.0% [95% CI: 9.8%, 12.2%; Oklahoma] to 7.9% [95% CI: 6.9%, 9.0%; Maryland] across states. Projected prevalence of externalizing problems ranged from 6.9% [95% CI: 6.1%, 7.8%; South Carolina] to 4.5% [95% CI: 3.7%, 5.4%; California]. Regions with high symptoms included sections of the South (e.g., Oklahoma, South Carolina) and Vermont. Conduct problems had the most variability across states (i.e., greatest state-level prevalence 91% higher than the lowest). Attention problems had the least variability across states (greatest state-level prevalence 26% higher than the lowest). Conclusions: Clinically meaningful psychopathology symptoms are common in children across the US, with substantial state-level variability in prevalence. Understanding variability in the prevalence of psychopathology symptoms across the US can help to inform resource allocation to increase the availability of youth mental health services.

Abstract 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.

Abstract Objectives To assess (1) the prevalence of suicide ideation/behavior among adolescents with short sleep by race/ethnicity and (2) the association between sleep duration and suicidal ideation and behavior among American youth by race/ethnicity from 2007 to 2019. Methods Data were drawn from the Youth Risk Behavior Surveillance System (YRBSS). Logistic regression analyses were used to assess the relationship between sleep duration and suicidal ideation/behavior. Results Overall, suicide ideation/behavior increased among U.S. adolescents of all racial groups from 2007 to 2019. Adjusting for race/ethnicity, sexual identity, age, sex, substance use, trauma, and bullying, those with short sleep had approximately twice the odds [OR: 1.92 (95% CI: 1.65, 2.23)] of suicide ideation/consideration compared to those with long sleep. Stratified analyses indicated that Black students with short sleep had higher odds of making a suicide plan (OR = 1.51, 95% C.I.: 1.27, 1.79) compared with Black students with long sleep. A similar pattern was observed across other racial/ethnic groups (e.g., Hispanic: (OR = 1.74, 95% C.I.: 1.53, 1.97). Conclusion Emphasis on suicide interventions is of the essence, especially with increasing rates. Sleep duration significantly predicts suicide risk among all adolescents. Additional research is needed to assess factors that predict suicide among minoritized adolescents, specifically Black and Hispanic adolescents.

Abstract Objective The Department of Veterans Affairs’ (VA) electronic health records (EHR) offer a rich source of big data to study medical and health care questions, but patient eligibility and preferences may limit generalizability of findings. We therefore examined the representativeness of VA veterans by comparing veterans using VA healthcare services to those who do not. Methods We analyzed data on 3051 veteran participants age ≥ 18 years in the 2019 National Health Interview Survey. Weighted logistic regression was used to model participant characteristics, health conditions, pain, and self-reported health by past year VA healthcare use and generate predicted marginal prevalences, which were used to calculate Cohen’s d of group differences in absolute risk by past-year VA healthcare use. Results Among veterans, 30.4% had past-year VA healthcare use. Veterans with lower income and members of racial/ethnic minority groups were more likely to report past-year VA healthcare use. Health conditions overrepresented in past-year VA healthcare users included chronic medical conditions (80.6% vs. 69.4%, d = 0.36), pain (78.9% vs. 65.9%; d = 0.35), mental distress (11.6% vs. 5.9%; d = 0.47), anxiety (10.8% vs. 4.1%; d = 0.67), and fair/poor self-reported health (27.9% vs. 18.0%; d = 0.40). Conclusions Heterogeneity in veteran sociodemographic and health characteristics was observed by past-year VA healthcare use. Researchers working with VA EHR data should consider how the patient selection process may relate to the exposures and outcomes under study. Statistical reweighting may be needed to generalize risk estimates from the VA EHR data to the overall veteran population.

Abstract Determining emerging trends of clinical psychiatric diagnoses among patients infected with the SARS-CoV-2 virus is important to understand post-acute sequelae of SARS-CoV-2 infection or long COVID. However, published reports accounting for pre-COVID psychiatric diagnoses have usually relied on self-report rather than clinical diagnoses. Using electronic health records (EHRs) among 2,358,318 patients from the New York City (NYC) metropolitan region, this time series study examined changes in clinical psychiatric diagnoses between March 2020 and August 2021 with month as the unit of analysis. We compared trends in patients with and without recent pre-COVID clinical psychiatric diagnoses noted in the EHRs up to 3 years before the first COVID-19 test. Patients with recent clinical psychiatric diagnoses, as compared to those without, had more subsequent anxiety disorders, mood disorders, and psychosis throughout the study period. Substance use disorders were greater between March and August 2020 among patients without any recent clinical psychiatric diagnoses than those with. COVID-19 positive patients (both hospitalized and non-hospitalized) had greater post-COVID psychiatric diagnoses than COVID-19 negative patients. Among patients with recent clinical psychiatric diagnoses, psychiatric diagnoses have decreased since January 2021, regardless of COVID-19 infection/hospitalization. However, among patients without recent clinical psychiatric diagnoses, new anxiety disorders, mood disorders, and psychosis diagnoses increased between February and August 2021 among all patients (COVID-19 positive and negative). The greatest increases were anxiety disorders (378.7%) and mood disorders (269.0%) among COVID-19 positive non-hospitalized patients. New clinical psychosis diagnoses increased by 242.5% among COVID-19 negative patients. This study is the first to delineate the impact of COVID-19 on different clinical psychiatric diagnoses by pre-COVID psychiatric diagnoses and COVID-19 infections and hospitalizations across NYC, one of the hardest-hit US cities in the early pandemic. Our findings suggest the need for tailoring treatment and policies to meet the needs of individuals with pre-COVID psychiatric diagnoses.

Abstract Background The role of traumatic event exposure and psychiatric disorders as central risk factors for suicidal behavior has been established, but there are limited data in high conflict regions with significant trauma exposures such as Afghanistan. Methods A nationally representative, cross-sectional survey was conducted through systematic stratified random sampling in 8 regions of Afghanistan in 2017 (N = 4474). Well-validated instruments were used to establish trauma exposure, psychiatric disorders. Death preference, suicidal ideation, plan, and attempts were assessed. Results In the total sample, 2.2% reported suicidal ideation in the past 12 months, and 7.1% of respondents reported that they had suicidal ideation at some point in their lives; 3.4% reported a suicide attempt. Women were at higher risk than men. All traumatic event exposures were strongly associated with suicidal behavior. Respondents who reported experiencing sexual violence were 4.4 times more likely to report lifetime suicide attempts (95% CI 2.3–8.4) and 5.8 times more likely to report past 12-month suicidal ideation (95% CI 2.7–12.4). Associations were strong and significant for all psychiatric disorders related to suicidal behavior. Respondents who met criteria for major depressive episodes (OR = 7.48; 95% CI 4.40–12.72), generalized anxiety disorder (OR = 6.61; 95% CI 3.54–12.33), and PTSD (OR = 7.26; 95% CI 4.21–12.51) had the highest risk of past 12-month suicidal ideation. Conclusion Traumatic event exposures and psychiatric disorders increase risk of suicidal behavior in the Afghan general population; women are at high risk. Interventions to reduce trauma exposure, including expansion of a mental health workforce in the region, are critically important.

Abstract Background Substance-related interactions with the criminal justice system are a potential touchpoint to identify people at risk for firearm violence. We used an agent-based model to simulate the change in firearm violence after disqualifying people from owning a firearm given prior alcohol- and drug-related misdemeanors. Methods We created a population of 800,000 agents reflecting a 15% sample of the adult New York City population. Results Disqualification from purchasing firearms for 5 years after an alcohol-related misdemeanor conviction reduced population-level rates of firearm homicide by 1.0% [95% CI 0.4–1.6%] and suicide by 3.0% [95% CI 1.9–4.0%]. Disqualification based on a drug-related misdemeanor conviction reduced homicide by 1.6% [95% CI 1.1–2.2%] and suicide by 4.6% [95% CI 3.4–5.8%]. Reductions were generally 2 to 8 times larger for agents meeting the disqualification criteria. Conclusions Denying firearm access based on a history of drug and alcohol misdemeanors may reduce firearm violence among the high-risk group. Enactment of substance use-related firearms denial criteria needs to be balanced against concerns about introducing new sources of disenfranchisement among already vulnerable populations.

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.

Summary: Background: Given slowing secular declines and persistent racial disparities, stillbirth remains a major health burden in the US. We investigate changes in stillbirth rates overall and for Black and White women, and determine how maternal age, delivery year (period), and birth year (cohort) have shaped trends. Methods: We designed a sequential time-series analysis utilising the 1980 to 2020 US vital records data of live births and stillbirths at ≥24 weeks gestation. Stillbirth rates overall and among Black and White women were examined. We undertook an age-period-cohort analysis to evaluate temporal changes in stillbirth trends. Findings: Of 157,192,032 live births and 710,832 stillbirths between 1980 and 2020, stillbirth rates per 1000 births declined from 10.6 (95% confidence interval [CI] 10.5, 10.7) in 1980 to 5.8 (95% CI 5.7, 5.8) in 2020. Stillbirth rates declined from 9.2 to 5.0 per 1000 births among White women (rate ratio [RR] 0.54, 95% CI 0.53, 0.55), and from 17.4 to 10.1 per 1000 births among Black women (RR 0.57, 95% CI 0.55, 0.59). Black women experienced persistent two-fold higher rates compared to White women (2.01, 95% CI 1.97, 2.05 in 2020). Stillbirth rates declined until 2005, increased from 2005 to the mid-2010s and plateaued thereafter. Strong cohort effects contributed to declining rates in earlier cohorts (1930–1955) and increasing rates among women born after 1980. Interpretation: Age, period, and birth cohorts greatly influenced US stillbirth rates over the last forty years. The decline in stillbirth rate was evident between 1980 and 2005, however subsequent declines have been minimal, reflecting no further gains for cohorts of women born in 1955–1980 and stagnation of period effects starting in 2005. A significant racial disparity persisted with a two-fold excess in stillbirth rates for Black compared to White women, underscoring the need for targeted health and social policies to address disparities. Funding: None.

Background: Nicotine vaping among U.S. adolescents has risen rapidly over the past decade, particularly for youth in grade 12. While previous studies examined the relationship between nicotine vaping and combustible cigarette use, less is known about the co-occurrence between vaping and other tobacco products. Methods: Using Monitoring the Future grade 12 data (2017-2019), we investigated associations between past 30-day nicotine vaping and non-vaping, non-cigarette tobacco use (smokeless tobacco, large cigars, cigarillos, hookah). Population prevalences of four categories were assessed: neither, vaping only, non-vaping of non-cigarette tobacco only, or both. We further investigated these relationships with logistic regressions accounting for the complex survey design (unadjusted, demographic-adjusted, and further adjusted for other substance use). Finally, analyses were stratified by combustible cigarette use. Results: Depending on the non-cigarette tobacco product, 2.5% to 5.4% of grade 12 students vaped nicotine and used a non-cigarette tobacco product. Controlling for demographics, cigarillo use was associated with nicotine vaping (adjusted RR = 3.44, 95% CI: 3.08, 3.84), as was hookah use (aRR = 3.51, 95% CI: 2.92, 4.23), smokeless tobacco (aRR = 2.97, 95% CI: 2.51, 3.52), and cigar use (aRR = 2.90, 95% CI: 2.49, 3.37). Controlling for cannabis and all non-cigarette tobacco products simultaneously attenuated associations. Associations were stronger among students who did not use cigarettes. Discussion: Nicotine vaping is associated with use of many non-cigarette tobacco products, including smokeless tobacco, cigarillos, cigars, and hookah. As prevalence of nicotine vaping remains high among adolescents, we should monitor co-use of vaping and other tobacco products.

Adolescent internalizing symptoms (e.g. depressive affect) have increased over the past decade in the US, particularly among girls. The reasons for these increases are unclear. We hypothesize that increasing exposure to politicized events has contributed to these trends in adolescent internalizing symptoms, and that effects may be differential by political beliefs and sociodemographic characteristics. We analyzed nationally-representative data from 2005 to 2018 Monitoring the Future annual cross-sectional samples of 12th-grade students (N ​= ​86,138). We examined self-reported political beliefs, sex, and parental education as predictors of four internalizing symptom scales over time, including depressive affect. From 2005 to 2018, 19.8% of students identified as liberal and 18.1% identified as conservative, with little change over time. Depressive affect (DA) scores increased for all adolescents after 2010, but increases were most pronounced for female liberal adolescents (b for interaction ​= ​0.17, 95% CI: 0.01, 0.32), and scores were highest overall for female liberal adolescents with low parental education (Mean DA 2010: 2.02, SD 0.81/2018: 2.75, SD 0.92). Findings were consistent across multiple internalizing symptoms outcomes. Trends in adolescent internalizing symptoms diverged by political beliefs, sex, and parental education over time, with female liberal adolescents experiencing the largest increases in depressive symptoms, especially in the context of demographic risk factors including parental education. These findings indicate a growing mental health disparity between adolescents who identify with certain political beliefs. It is therefore possible that the ideological lenses through which adolescents view the political climate differentially affect their mental wellbeing.

Introduction: Adolescent time use in recent cohorts is distinguished by large-scale changes, including shifts in parental monitoring, supervision, and adolescent activity patterns, that together may provide a more complete perspective on changing patterns of mental health than can be captured by single risk factors. Methods: To determine whether patterns of adolescent time use explain recent increases in depressive and other internalizing symptoms, we first conducted latent profile analyses of 465,839 adolescents, grades 8/10, from annual, cross-sectional Monitoring the Future surveys, years:1991–2019, using twenty-one variables (e.g., frequency of attending parties) to identify groups based on patterns of time use. Most of the sample was female (51.0%), non-Hispanic white (58.8%), and in grade 8 (52.2%); mean age: 14.60 years (95% CI: 14.57, 14.64). We subsequently examined differences in depressive and other internalizing symptoms between these time use groups over time with survey-weighted logistic regressions producing odds ratios. Results: Analyses derived six groups: part time workers, full time workers, and four groups based on levels of social activities (Low, medium, and high levels, with “High Social” split between those engaged in sports, academics, and community service and those who were not). Internalizing symptoms were predicted by lower socialization, low engagement in activities like sports, academics, and community service, and time spent at a paid job. Adolescents decreasingly engaged in social activities over time, though shifts in time use patterns did not account for much of the overall increase in depressive symptoms. Conclusion: Shifts in adolescent time use do not explain increases in depressive and other internalizing symptoms, which increased across different patterns of time use. Levels of internalizing symptoms were highest among those with low socialization, low recreational engagement, and those working substantial hours. Encouraging socialization, engagement in recreational activities, and providing mental health resources for isolated adolescents may reduce internalizing symptom trends.

Opioid-related overdose deaths have increased since 2010 in the U.S., but information on trends in opioid use disorder (OUD) prevalence is limited due to unreliable data. Multiplier methods are a classical epidemiological technique to estimate prevalence when direct estimation is infeasible or unreliable. We used two different multiplier approaches to estimate OUD prevalence from 2010 to 2019. First, we estimated OUD in National Survey on Drug Use and Health (NSDUH), and based on existing capture-recapture studies, multiplied prevalence by 4.5x. Second, we estimated the probability of drug poisoning death among people with OUD (Meta-analysis indicates 0.52/100,000), and divided the number of drug poisoning deaths in the US by this probability. Estimates were weighted to account for increase in drug-related mortality in recent years due to fentanyl. Estimated OUD prevalence was lowest when estimated in NSDUH with no multiplier, and highest when estimated from vital statistics data without adjustment. Consistent findings emerged with two methods: NSDUH data with multiplier correction, and vital statistics data with multiplier and adjustment. From these two methods, OUD prevalence increased from 2010 to 2014; then stabilized and slightly declined annually (survey data with multiplier, highest prevalence of 4.0% in 2015; death data with a multiplier and correction, highest prevalence of 2.35% in 2016). The number of US adolescent and adult individuals with OUD in 2019 was estimated between 6.7–7.6 million. When multipliers and corrections are used, OUD may have stabilized or slightly declined after 2015. Nevertheless, it remains highly prevalent, affecting 6–7 million US adolescents and adults.

Background Firearm violence remains a persistent public health threat. Comparing the impact of targeted high-risk versus population-based approaches to prevention may point to efficient and efficacious interventions. We used agent-based modeling to conduct a hypothetical experiment contrasting the impact of high-risk (disqualification) and population-based (price increase) approaches on firearm homicide in New York City (NYC). Methods We simulated 800,000 agents reflecting a 15% sample of the adult population of NYC. Three groups were considered and disqualified from all firearm ownership for five years, grouped based on prevalence: low prevalence (psychiatric hospitalization, alcohol-related misdemeanor and felony convictions, 0.23%); moderate prevalence (drug misdemeanor convictions, domestic violence restraining orders, 1.03%); and high prevalence (all other felony/misdemeanor convictions, 2.30%). Population-level firearm ownership was impacted by increasing the price of firearms, assuming 1% price elasticity. Results In this hypothetical scenario, to reduce firearm homicide by 5% in NYC, 25% of the moderate prevalence group, or 12% of the high prevalence group needed to be effectively disqualified; even when all of the low prevalence group was disqualified, homicide did not decrease by 5%. An 18% increase in price similarly reduced firearm homicide by 5.37% (95% CI 4.43–6.31%). Firearm homicide declined monotonically as the proportion of disqualified individuals increased and/or price increased. A combined intervention that both increased price and effectively disqualified “high-risk” groups achieved approximately double the reduction in homicide as any one intervention alone. Increasing illegal firearm ownership by 20%, a hypothetical response to price increases, did not meaningfully change results. Conclusion A key takeaway of our study is that adopting high-risk versus population-based approaches should not be an “either-or” question. When individual risk is variable and diffuse in the population, “high-risk approaches” to firearm violence need to focus on relatively prevalent groups and be highly efficacious in disarming people at elevated risk to achieve meaningful reductions in firearm homicide, though countering issues of social justice and stigma should be carefully considered. Similar reductions can be achieved with population-based approaches, such as price increases, albeit with fewer such countering issues.

U.S. adolescent suicidal behavior and digital media use prevalence have contemporaneously increased this decade in population-level ecological analyses. The purpose of this study was to determine whether these two trends are directly associated by using multi-year person-level data to test whether the association of year with suicidal behavior was mediated by digital media use. Data were from the Youth Risk Behavior Surveillance System (2009–2017), a nationally-representative biennial cross-sectional self-report survey of U.S. students (N = 72,942). Mediation analysis was used to estimate the proportion of cross-year changes in suicidal behavior that were mediated by concurrent changes in leisure-time digital media use. Past-year suicidal behavior in 2011 (19.6%), 2013 (20.4%), 2015 (21.7%), and 2017 (20.5%) increased relative to 2009 (17.1%). Hours of daily digital media use in 2011 (mean[SD] = 2.65[1.86]), 2013 (mean[SD] = 3.02[2.08]), 2015 (mean[SD] = 2.97[2.12]), and 2017 (mean[SD] = 3.01[2.18) increased vs. 2009 (mean[SD] = 2.31[1.81]). The association of survey year with suicidal behavior was mediated by digital media use—20.5%(95%CI = 16.2, 24.8), 34.3%(95%CI = 24.5, 44.1), 22.8%(95%CI = 17.3, 28.0), and 41.4%(95%CI = 33.9, 49.5) of cross-year suicidal behavior prevalence increases (vs. 2009) for 2011, 2013, 2015, and 2017, respectively, were mediated by concurrent digital media use increases. Therefore, small proportions of the 2009–2017 increases in U.S. adolescent suicidal behavior are associated with concurrent increasing digital media use trends. Further exploration of these trends is warranted.

Gender differences in binge drinking have converged in recent cohorts, due in part to faster decreases in consumption among boys in adolescence, and faster increases in consumption among women in young to middle adulthood. Changes in education and occupation explain a portion, but not all, of these differences; the present study examines how attitudes about gender, religion and family additionally explain cohort effects in binge drinking by sex. Data were drawn from the Monitoring the Future panel studies, including >54,000 participants who were high school seniors from 1976 through 2006, followed to age 29/30 from 1988 through 2016. The main effect relationship between cohort and binge drinking was assessed, and 28 items on gender, religion and family were evaluated to determine if mediation criteria were met; mediation models assessed direct and indirect effects. Results indicated that gender, religion and family attitudes and beliefs among US adults across the 20 th and 21 st centuries have shifted dramatically but not monotonically. US adolescents and adults have largely become less religious; some attitudes on women and family have become less conservative and some more. Among men, views on marriage showed the largest mediation effects; agreeing with the statement ‘one partner is too restrictive’ mediated 3.35% of the cohort effect (95% C.I. 2.42, 4.31) and ‘couples should live together before they are married’ mediated 1.6% of the cohort effect (95% C.I. −2.37, −0.8). Among women, declines in religious service attendance mediated 2.0% of cohort effects in binge drinking (95% C.I. −3.03, −1.09), as well as similar family attitudes as men. In conclusion, changes in social roles, as well as some gender, and religious views, partially mediate cohort effects on binge drinking for men and women. The dynamic changes in how adolescents and adults view family and gender are important components of alcohol epidemiology.

Summary: Background: Mass incarceration has collateral consequences for community health, which are reflected in county-level health indicators, including county mortality rates. County jail incarceration rates are associated with all-cause mortality rates in the USA. We assessed the causes of death that drive the relationship between county-level jail incarceration and mortality. Methods: In this retrospective, longitudinal study, we assessed the association between county-level jail incarceration rates and county-level cause-specific mortality using county jail incarceration data (1987–2017) for 1094 counties in the USA obtained from the Vera Institute of Justice and cause-specific mortality data for individuals younger than 75 years in the total county population (1988–2018) obtained from the US National Vital Statistics System. We fitted quasi-Poisson models for nine common causes of death (cerebrovascular disease, chronic lower respiratory disease, diabetes, heart disease, infectious disease, malignant neoplasm, substance use, suicide, and unintentional injury) with county fixed effects, controlling for all unmeasured stable county characteristics and measured time-varying confounders (county median age, county poverty rate, county percentage of Black residents, county crime rate, county unemployment rate, and state incarceration rate). We lagged county jail incarceration rates by 1 year to assess the short-term, by 5 years to assess the medium-term, and by 10 years to assess the long-term associations of jail incarceration with premature mortality. Findings: A 1 per 1000 within-county increase in jail incarceration rate was associated with a 6·5% increase in mortality from infectious diseases (risk ratio 1·065, 95% CI 1·061–1·070), a 4·9% increase in mortality from chronic lower respiratory disease (1·049, 1·045–1·052), a 2·6% increase in mortality induced from substance use (1·026, 1·020–1·032), a 2·5% increase in suicide mortality (1·025, 1·020–1·029), and smaller increases in mortality from heart disease (1·021, 1·019–1·023), unintentional injury (1·015, 1·011–1·018), malignant neoplasm (1·014, 1·013–1·016), diabetes (1·013, 1·009–1·018), and cerebrovascular disease (1·010, 1·007–1·013) after 1 year. Associations between jail incarceration and cause-specific mortality rates weakened as time lags increased, but to a greater extent for causes of death with generally shorter latency periods (infectious disease and suicide) than for those with generally longer latency periods (heart disease, malignant neoplasm, and cerebrovascular disease). Interpretation: Jail incarceration rates are potential drivers of many causes of death in US counties. Jail incarceration can be harmful not only to the health of individuals who are incarcerated, but also to public health more broadly. Our findings suggest important points of intervention, including disinvestment from carceral systems and investment in social and public health services, such as community-based treatment of substance-use disorders. Funding: US National Institute on Drug Abuse (National Institutes of Health).

During the COVID-19 pandemic, US populations have experienced elevated rates of financial and psychological distress that could lead to increases in suicide rates. Rapid ongoing mental health monitoring is critical for early intervention, especially in regions most affected by the pandemic, yet traditional surveillance data are available only after long lags. Novel information on real-time population isolation and concerns stemming from the pandemic's social and economic impacts, via cellular mobility tracking and online search data, are potentially important interim surveillance resources. Using these measures, we employed transfer function model time-series analyses to estimate associations between daily mobility indicators (proportion of cellular devices completely at home and time spent at home) and Google Health Trends search volumes for terms pertaining to economic stress, mental health, and suicide during 2020 and 2021 both nationally and in New York City. During the first pandemic wave in early-spring 2020, over 50% of devices remained completely at home and searches for economic stressors exceeded 60,000 per 10 million. We found large concurrent associations across analyses between declining mobility and increasing searches for economic stressor terms (national proportion of devices at home: cross-correlation coefficient (CC) = 0.6 (p-value

BackgroundThe World Health Organization recommends that treatment of depression in low and middle-income countries with a scarcity of psychiatrists could be done in primary care and should include prescription of antidepressant medications for moderate and severe depression. Little is known, however, about the actual practices of antidepressant prescription by primary care physicians in low and middle-income countries, nor about adherence by people receiving such prescriptions. In a large study of primary care clinics in Goa, India, we examined the relationship of actual to recommended prescribing practices for depression, among all patients who screened positive for common mental disorder. We also examined other patient and clinic characteristics associated with antidepressant prescription, and self-reported adherence over a one-month period.MethodsPatients attending 24 primary care clinics were screened for common mental disorders. Those who screened positive were eligible to enroll in a trial to assess the effectiveness of a collaborative stepped care (CSC) intervention for mental disorders. Physicians in the 12 intervention and 12 control clinics (usual care) were free to prescribe antidepressants and follow-up interviews were conducted at 2, 6 and 12 months. Screening results were shared with the physician, but they were blinded to the diagnosis generated later using a standardized diagnostic interview administered by a health counsellor. We categorized these later diagnoses as "moderate/severe depression", "mild depression or non-depression diagnosis", and "no diagnosis". We used a two-level hierarchical logistic regression model to examine diagnostic and other factors associated with antidepressant prescription and one-month adherence.ResultsOverall, about 47% of screened positive patients (n = 1320) received an antidepressant prescription: 60% of those with moderate/severe depression, 48% of those with mild depression or non-depression diagnosis, and 31% with no diagnosis. Women (OR 1.29; 95%CI 1.04-1.60) and older adults (OR 1.80; 95%CI 1.32-2.47) were more likely to receive an antidepressant prescription. While the overall rate of antidepressant prescription was similar in clinics with and without CSC, patients without any diagnosis were more likely to receive a prescription (OR 2.20 95% CI 1.03-4.70) in the usual care clinics. About 47% of patients adhered to antidepressant treatment for one month or more and adherence was significantly better among older adults (OR 3.92; 95% CI 1.70-8.93) and those who received antidepressant as part of the CSC treatment model (OR 6.10 95% CI 3.67-10.14) compared with those attending the usual care clinic.ConclusionAntidepressants were widely prescribed following screening in primary care, but prescription patterns were in poor accord with WHO recommendations. The data suggest under-prescription for people with moderate/severe depression; over-prescription for people with mild depression or non-depression diagnoses; and over-prescription for people with no disorders. For all diagnoses adherence was low, especially in usual care clinics. To address these concerns, there is an urgent need to study and develop strategies in primary care practices to limit unnecessary antidepressant prescriptions, target prescription for those patients who clearly benefit, and to improve adherence to antidepressant treatment. ClinicalTrials.gov Identifier: NCT00446407.

ObjectiveTo determine whether emotional and physical intimate partner violence (IPV) and financial adversity increase risk of incident homelessness in pregnancy and the post-partum period.Study designData were drawn from the Avon Longitudinal Study of Parents and Children, which starting in 1990 mailed questionnaires to 14,735 mothers in the UK, over 7 years from pregnancy onwards. Marginal structural models and multiple imputation were used to address time-varying confounding of the primary variables, testing for interaction between concurrent emotional/physical IPV and financial adversity, and adjusted for baseline age, ethnicity, education, partner's alcohol use, parity, depression, and social class.ResultsEmotional IPV (HR 1.44 (1.13,1.84)), physical IPV (HR 2.05 (1.21,3.49)), and financial adversity (HR 1.59 (1.44,1.77)) each predicted a multiplicative increase in the discrete-time hazard of incident homelessness. We identified joint effects for concurrent emotional IPV and financial adversity (HR 2.09 (1.35,3.22)) and concurrent physical IPV and financial adversity (HR 2.79 (1.21,6.44)). We further identified a temporary decline in self-reported physical IPV among mothers during pregnancy and up to 8 months post-partum.ConclusionsEmotional and physical IPV and financial adversity independently and jointly increase the risk of incident homelessness. The effects of emotional and physical IPV are comparable to or greater than the risk of financial adversity. Homelessness prevention policies should consider IPV victims as high-risk, regardless of financial status. Furthermore, self-reported physical IPV declines temporarily during pregnancy and up to 8 months post-partum. Screening for IPV in this period may miss high-risk individuals.

Abstract Background Although the flipped classroom model has been widely adopted in medical education, reports on its use in graduate-level public health programs are limited. This study describes the design, implementation, and evaluation of a flipped classroom redesign of an introductory epidemiology course and compares it to a traditional model. Methods One hundred fifty Masters-level students enrolled in an introductory epidemiology course with a traditional format (in-person lecture and discussion section, at-home assignment; 2015, N = 72) and a flipped classroom format (at-home lecture, in-person discussion section and assignment; 2016, N = 78). Using mixed methods, we compared student characteristics, examination scores, and end-of-course evaluations of the 2016 flipped classroom format and the 2015 traditional format. Data on the flipped classroom format, including pre- and post-course surveys, open-ended questions, self-reports of section leader teaching practices, and classroom observations, were evaluated. Results There were no statistically significant differences in examination scores or students’ assessment of the course between 2015 (traditional) and 2016 (flipped). In 2016, 57.1% (36) of respondents to the end-of-course evaluation found watching video lectures at home to have a positive impact on their time management. Open-ended survey responses indicated a number of strengths of the flipped classroom approach, including the freedom to watch pre-recorded lectures at any time and the ability of section leaders to clarify targeted concepts. Suggestions for improvement focused on ways to increase regular interaction with lecturers. Conclusions There was no significant difference in students’ performance on quantitative assessments comparing the traditional format to the flipped classroom format. The flipped format did allow for greater flexibility and applied learning opportunities at home and during discussion sections.

Maximizing both efficiency and equity are core considerations for population health. These considerations can result in tension in population health science as we seek to improve overall population health while achieving equitable health distributions within populations. Limited work has explored empirically the consequences of different population health intervention strategies on the burden of disease and on within- and between-group differences in disease. To address this gap, we compared the impact of four simulated interventions using data from the National Health and Nutrition Examination Survey. In particular, we focus on assessing how population and high-risk primary prevention and population and high-risk secondary interventions efforts to reduce smoking behavior influence systolic blood pressure (SBP) and hypertension, and how such strategies influence inequalities in SBP by income. The greatest reductions in SBP mean and standard deviation resulted from the population secondary prevention. High-risk primary and secondary prevention and population secondary prevention programs all yielded substantial reductions in hypertension prevalence. The effect of population primary prevention did little to decrease population SBP mean and standard deviation, as well as hypertension prevalence. Both high-risk strategies had a larger impact in the low-income population, leading to the greatest narrowing the income-related gap in disease. The population prevention strategies had a larger impact in the high-income population. Population health approaches must consider the potential impact on both the whole population and also on those with different levels of risk for disease within a population, including those in under-represented or under-served groups.

The influence of sample composition on human neuroimaging results is unknown. Here, the authors weight a large, community-based sample to better reflect the US population and describe how applying these sample weights changes conclusions about age-related variation in brain structure.

Abstract Background Drug overdose is a public health crisis in the United States, due in part to the unintended consequences of increases in prescribing of opioid analgesics. Many clinicians evaluate risk markers for opioid-related harms when prescribing opioids for chronic pain; however, more data on predictive risk markers are needed. Risk markers are attributes (modifiable and non-modifiable) that are associated with increased probability of an outcome. This review aims to identify risk markers associated with fatal and non-fatal prescription drug overdose by synthesizing findings in the existing peer-reviewed and grey literature. Eligible cohort, case-control, cross-sectional, and case-cohort studies were reviewed and data were extracted for qualitative and quantitative synthesis. Findings Summary odds ratios (SOR) were estimated from 29 studies for six risk markers: sex, age, race, psychiatric disorders, substance use disorder (SUD), and urban/rural residence. Heterogeneity was assessed and effect estimates were stratified by study characteristics. Of the six risk markers identified, SUD had the strongest association with drug overdose death (SOR = 5.24, 95% confidence interval (CI) = 3.53 - 7.76), followed by psychiatric disorders (SOR = 3.94, 95% CI = 3.09 - 5.01), white race (SOR = 2.28, 95% CI = 1.93 - 2.70), the 35-44 year age group relative to the 25-34 year reference group (SOR = 1.52, 95% CI = 1.31 - 1.76), and male sex (SOR = 1.33, 95% CI = 1.17 - 1.51). Conclusions This review highlights fatal and non-fatal prescription drug risk markers most frequently assessed in peer-reviewed and grey literature. There is a need to better understand modifiable risk markers and underlying reasons for drug misuse in order to inform interventions that may prevent future drug overdoses.

Objectives Material well-being, beliefs, and emotional states are believed to influence one’s health and longevity. In this paper, we explore racial differences in self-rated health, happiness, trust in others, feeling that society is fair, believing in God, frequency of sexual intercourse, educational attainment, and percent in poverty and their association with mortality. Study designs Age-period-cohort (APC) study. Methods Using data from the 1978–2014 General Social Survey-National Death Index (GSS-NDI), we conducted APC analyses using generalized linear models to quantify the temporal trends of racial differences in our selected measures of well-being, beliefs, and emotional states. We then conducted APC survival analysis using mixed-effects Cox proportional hazard models to quantify the temporal trends of racial differences in survival after removing the effects of racial differences in our selected measures. Results For whites, the decline in happiness was steeper than for blacks despite an increase in high school graduation rates among whites relative to blacks over the entire period, 1978–2010. Self-rated health increased in whites relative to blacks from 1978 through 1989 but underwent a relative decline thereafter. After adjusting for age, sex, period effects, and birth cohort effects, whites, overall, had higher rates of self-rated health (odds ratio [OR] = 1.88; 95% confidence interval [CI] = 1.63, 2.16), happiness (OR = 2.05; 1.77, 2.36), and high school graduation (OR = 2.88; 2.34, 3.53) compared with blacks. Self-rated health, happiness, and high school graduation also mediated racial differences in survival over time. Conclusions We showed that some racial differences in survival could be partly mitigated by eliminating racial differences in health, happiness, and educational attainment. Future research is needed to analyze longitudinal clusters and identify causal mechanisms by which social, behavioral, and economic interventions can reduce survival differences.

BACKGROUND:Binge and heavy drinking are preventable causes of mortality and morbidity. Alcohol consumption by women who parent is damaging to child health, and it is concerning that women in the United States in their reproductive years have experienced increased drinking over the past decade. Although media attention has focused on the drinking status of women who are child-rearing, it remains unclear whether binge and heavy drinking vary by parenting status and sex. METHODS AND FINDINGS:We examined national trends in binge drinking, defined as 5 or more drinks in a single day for men and 4 or more drinks for women, and heavy drinking, defined as 60 or more days with binge episodes in a year. We used survey-weighted logistic regression from the 2006-2018 waves of the cross-sectional National Health Interview Survey (NHIS, N = 239,944 eligible respondents) to study time trends in drinking outcomes by sex, age, and parenting status. Binge drinking increased for both sexes in nearly all age groups, with the largest increase among women ages 30-44 without children (from 21% reporting binge drinking in 2006 to 42% in 2018); the exception was young men (ages 18-29) with children, among whom binge drinking declined. By 2012, the prevalence of binge drinking among young men with children (38.5%) declined to below that of young women without children (39.2%) and stayed lower thereafter. Despite widespread increases in binge drinking, heavy drinking declined or remained stable for all groups except older women (ages 45-55) without children (odds ratio [OR] for heavy drinking each year = 1.06, 95% CI 1.02-1.10) and women ages 30-44, regardless of parenting status. For binge drinking outcomes only, we saw evidence of interaction in drinking trends by parenting status, but this was shown to be confounded by sex and age. Men and women with children reported consistently lower levels of drinking than those without children. Rates of abstention mirrored trends in binge outcomes for both sexes, limiting concerns about invariance. Study limitations include self-reported data and measurement invariance in binge drinking cutoffs across study years. CONCLUSIONS:This study demonstrated that trends in binge and heavy drinking over time were not differential by parenting status for women; rather, declines and increases over time were mainly attributable to sex and age. Women both with and without children are increasing binge and heavy drinking; men, regardless of parenting status, and women without children consumed more alcohol than women with children. Regardless of impact on child health, increased drinking rates in the past decade are concerning for adult morbidity and mortality: binge drinking has increased among both sexes, and heavy drinking has increased among older women. Men and women of all ages and parenting status should be screened for heavy alcohol use and referred to specialty care as appropriate.

Alexander Tsai and co-authors discuss the role of stigma in responses to the US opioid crisis.