Restrictive abortion legislation and adverse mental health during pregnancy and postpartum.

PURPOSE: To determine the impact of abortion legislation on mental health during pregnancy and postpartum and assess whether pregnancy intention mediates associations. METHODS: We quantified associations between restrictive abortion laws and stress, depression symptoms during and after pregnancy, and depression diagnoses after pregnancy using longitudinal data from Nurses' Health Study 3 in 2010-2017 (4091 participants, 4988 pregnancies) using structural equation models with repeated measures, controlling for sociodemographics, prior depression, state economic and sociopolitical measures (unemployment rate, gender wage gap, Gini index, percentage of state legislatures who are women, Democratic governor). RESULTS: Restrictive abortion legislation was associated with unintended pregnancies (ß = 0.127, p = 0.02). These were, in turn, associated with increased risks of stress and depression symptoms during pregnancy (total indirect effects ß = 0.035, p = 0.03; ß = 0.029, p = 0.03, respectively, corresponding <1% increase in probability), but not after pregnancy. CONCLUSIONS: Abortion restrictions are associated with higher proportions of unintended pregnancies, which are associated with increased risks of stress and depression during pregnancy.

Sex-Specific Depressive Symptom Trajectories Among Adolescents in Los Angeles County, 2013 to 2017.

Objective: After remaining stable for many years, the prevalence of depression among adolescents increased over the past decade, particularly among girls. In this study, we used longitudinal data from a cohort of high school students to characterize sex-specific trajectories of depressive symptoms during this period of increasing prevalence and widening gender gap in adolescent depression. Method: Using data from the Health and Happiness Cohort, a longitudinal 8-wave study of high school students residing in Los Angeles County from 2013 to 2017 (N = 3,393), we conducted a multiple-group, latent class growth analysis by sex to differentiate developmental trajectories in depressive symptoms scores measured by the Center for Epidemiological Studies- Depression (CES-D) scale (range, 0-60). Results: A 4-class solution provided the best model fit for both girls and boys. Trajectories among girls included low stable (35.1%), mild stable (42.8%), moderate decreasing (16.2%), and high arching (5.9%). Trajectories among boys included low stable (49.2%), mild increasing (34.7%), moderate decreasing (12.2%), and high increasing (3.9%). Average scores consistently exceeded or crossed the threshold for probable depression (≥16). Across comparable sex-specific trajectory groups, the average CES-D scores of girls were higher than those of boys, whose average scores increased over time. Conclusion: In a diverse cohort of students in Los Angeles County, depressive symptom trajectories were comparable to prior time periods but with a higher proportion of students in trajectories characterized by probable depression. Trajectories differed by sex, suggesting that future research should consider differential severity and onset of depression between boys and girls.

"Breaking the silence" suicide Prevention media campaign in Oregon: Evaluation of impact on help-seeking and suicide mortality.

INTRODUCTION: Research has established that suicide-related media can impact suicide rates both positively and negatively, supporting efforts to engage the media in the service of suicide prevention. The goal of the current study is to evaluate the impact of a suicide prevention media campaign implemented April 7-14, 2019 in Oregon. METHODS: Several indices of help-seeking behavior and suicide risk were employed: suicide-related Google Health API searches, National Suicide Prevention Lifeline (Lifeline) (currently known as the 988 Suicide and Crisis Lifeline) call volume, and state suicide mortality data from April 7, 2016-May 6, 2019. Eight states with similar 2016-2018 average suicide rates were compared with Oregon. Bayesian structural time-series modeling in R was used to test intervention effects. RESULTS: During the 30 days following the start of the campaign, there was a significant increase in Lifeline calls from Oregon area codes (2488 observed vs. 2283 expected calls, p = 0.03). There were no significant changes in suicide mortality or suicide-related Google searches in Oregon. CONCLUSIONS: The campaign appeared to increase help-seeking behavior in the form of Lifeline calls, without any indication of an iatrogenic suicide contagion effect. However, the campaign's potential to reduce suicide mortality was unmet.

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.

County-level estimates of suicide mortality in the USA: a modelling study.

BACKGROUND: Suicide is one of the leading causes of death in the USA and population risk prediction models can inform decisions on the type, location, and timing of public health interventions. We aimed to develop a prediction model to estimate county-level suicide risk in the USA using population characteristics. METHODS: We obtained data on all deaths by suicide reported to the National Vital Statistics System between Jan 1, 2005, and Dec 31, 2019, and age, sex, race, and county of residence of the decedents were extracted to calculate baseline risk. We also obtained county-level annual measures of socioeconomic predictors of suicide risk (unemployment, weekly wage, poverty prevalence, median household income, and population density) and state-level prevalence of major depressive disorder and firearm ownership from US public sources. We applied conditional autoregressive models, which account for spatiotemporal autocorrelation in response and predictors, to estimate county-level suicide risk. FINDINGS: Estimates derived from conditional autoregressive models were more accurate than from models not adjusted for spatiotemporal autocorrelation. Inclusion of suicide risk and protective covariates further reduced errors. Suicide risk was estimated to increase with each SD increase in firearm ownership (2·8% [95% credible interval (CrI) 1·8 to 3·9]), prevalence of major depressive episode (1·0% [0·4 to 1·5]), and unemployment rate (2·8% [1·9 to 3·8]). Conversely, risk was estimated to decrease by 4·3% (-5·1 to -3·2) for each SD increase in median household income and by 4·3% (-5·8 to -2·5) for each SD increase in population density. An increase in the heterogeneity in county-specific suicide risk was also observed during the study period. INTERPRETATION: Area-level characteristics and the conditional autoregressive models can estimate population-level suicide risk. Availability of near real-time situational data are necessary for the translation of these models into a surveillance setting. Monitoring changes in population-level risk of suicide could help public health agencies select and deploy targeted interventions quickly. FUNDING: US National Institute of Mental Health.

Trends in psychiatric diagnoses by COVID-19 infection and hospitalization among patients with and without recent clinical psychiatric diagnoses in New York city from March 2020 to August 2021.

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.

When Effects Cannot be Estimated: Redefining Estimands to Understand the Effects of Naloxone Access Laws.

Violations of the positivity assumption (also called the common support condition) challenge health policy research and can result in significant bias, large variance, and invalid inference. We define positivity in the single- and multiple-timepoint (i.e., longitudinal) health policy evaluation setting, and discuss real-world threats to positivity. We show empirical evidence of the practical positivity violations that can result when attempting to estimate the effects of health policies (in this case, Naloxone Access Laws). In such scenarios, an alternative is to estimate the effect of a shift in law enactment (e.g., the effect if enactment had been delayed by some number of years). Such an effect corresponds to what is called a modified treatment policy, and dramatically weakens the required positivity assumption, thereby offering a means to estimate policy effects even in scenarios with serious positivity problems. We apply the approach to define and estimate the longitudinal effects of Naloxone Access Laws on opioid overdose rates.

Role of Foreign-Born Status on Suicide Mortality in Spain Between 2000 and 2019: An Age-Period-Cohort Analysis.

Objectives: To examine recent age-period-cohort effects on suicide among foreign-born individuals, a particularly vulnerable sociodemographic group in Spain. Methods: Using 2000-2019 mortality data from Spain's National Institute of Statistics, we estimated age-period-cohort effects on suicide mortality, stratified by foreign-born status (native- vs. foreign-born) and, among the foreign-born, by Spanish citizenship status, a proxy for greater socioeconomic stability. Results: Annual suicide mortality rates were lower among foreign- than native-born individuals. There was heterogeneity in age-period-cohort effects between study groups. After 2010, suicide mortality increased markedly among the foreign-born-especially for female cohorts born around 1950, and slightly among native-born women-especially among female cohorts born after the 1960s. Among native-born men, suicide increased linearly with age and remained stable over time. Increases in suicide among the foreign-born were driven by increases among individuals without Spanish citizenship-especially among cohorts born after 1975. Conclusion: After 2010, suicide in Spain increased markedly among foreign-born individuals and slightly among native-born women, suggesting an association between the downstream effects of the 2008 economic recession and increases in suicide mortality among socioeconomically vulnerable populations.

Racial Disparities in Spatial and Temporal Youth Suicide Clusters.

OBJECTIVE: Deaths by suicide correlate both spatially and temporally, leading to suicide clusters. This study aimed to estimate racial patterns in suicide clusters since 2000. METHOD: Data from the US National Vital Statistics System included all International Classification of Diseases, Tenth Revision (ICD-10)-coded suicide cases from 2000-2019 among American Indian/Alaska Native (AI/AN), Asian/Pacific Islander (A/PI), Black, or White youth and young adults, aged 5-34 years. We estimated age, period, and cohort (APC) trends and identified spatiotemporal clusters using the SaTScan space-time statistic, which identified lower- and higher-than-expected suicide rates (cold and hot clusters) in a prespecified area (150 km) and time interval (15 months). We also calculated the average proportion of deaths by suicide contained in clusters, to quantify the relative importance of spatiotemporal patterning as a driver of overall suicide rates. RESULTS: From 2010-2019, suicide rates increased from between 37% among AI/AN (95% CI = 1.22, 1.55) to 81% among A/PI (95% CI = 1.65, 2.01) groups. Suicide clusters accounted for 0.8%-10.3% of all suicide deaths, across racial groups. Since 2000, the likelihood of detecting cluster increased over time, with considerable differences in the number of clusters in each racial group (4 among AI/AN to 72 among White youth). Among Black youth and young adults, 27 total clusters were identified. Hot clusters were concentrated in southeastern and mid-Atlantic counties. CONCLUSION: Suicide rates and clusters in youth and young adults have increased in the past 2 decades, requiring attention from policy makers, clinicians, and caretakers. Racially distinct patterns highlight opportunities to tailor individual- and population-level prevention efforts to prevent suicide deaths in emerging high-risk groups.

The politics of depression: Diverging trends in internalizing symptoms among US adolescents by political beliefs.

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.

Associations between COVID-19 mobility restrictions and economic, mental health, and suicide-related concerns in the US using cellular phone GPS and Google search volume data.

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 <0.001)). Nationally, we also found strong associations between declining mobility and increasing mental health and suicide-related searches (time at home: mood/anxiety CC = 0.53 (<0.001), social stressor CC = 0.51 (<0.001), suicide seeking CC = 0.37 (0.006)). Our findings suggest that pandemic-related isolation coincided with acute economic distress and may be a risk factor for poor mental health and suicidal behavior. These emergent relationships warrant ongoing attention and causal assessment given the potential for long-term psychological impact and suicide death. As US populations continue to face stress, Google search data can be used to identify possible warning signs from real-time changes in distributions of population thought patterns.

Role of Firearm Ownership on 2001-2016 Trends in U.S. Firearm Suicide Rates.

INTRODUCTION: In the U.S., state-level household firearm ownership is strongly associated with firearm suicide mortality rates. Whether the recent increases in firearm suicide are explained by state-level household firearm ownership rates and trends remains unknown. METHODS: Mortality data from the U.S. National Vital Statistics System and an estimate of state-level household firearm ownership rate were used to conduct hierarchical age-period-cohort (random-effects) modeling of firearm suicide mortality between 2001 and 2016. Models were adjusted for individual-level race and sex and for state-level poverty rate, unemployment rate, median household income in U.S. dollars, population density, and elevation. RESULTS: Between 2001 and 2016, the crude national firearm suicide mortality rate increased from 6.8 to 8.0 per 100,000, and household firearm ownership rate remained relatively stable, at around 40%. Both variables were markedly heterogeneous and correlated at the state level. Age-period-cohort models revealed period effects (affecting people across ages) and cohort effects (affecting specific birth cohorts) underlying the recent increases in firearm suicide. Individuals born after 2000 had higher firearm suicide rates than most cohorts born before. A 2001-2006 decreasing period effect was followed, after 2009, by an increasing period effect that peaked in 2015. State-level household firearm ownership rates and trends did not explain cohort effects and only minimally explained period effects. CONCLUSIONS: State-level firearm ownership rates largely explain the state-level differences in firearm suicide but only marginally explain recent increases in firearm suicide. Although firearms in the home increase firearm suicide risk, the recent national rise in firearm suicide might be the result of broader, more distal causes of suicide risk.

Age, period, and cohort effects on suicide death in the United States from 1999 to 2018: moderation by sex, race, and firearm involvement.

The role of sex, race, and suicide method on recent increases in suicide mortality in the United States remains unclear. Estimating the age, period, and cohort effects underlying suicide mortality trends can provide important insights for the causal hypothesis generating process. We generated updated age-period-cohort effect estimates of recent suicide mortality rates in the US, examining the putative roles of sex, race, and method for suicide, using data from all death certificates in the US between 1999 and 2018. After designating deaths as attributable to suicide according to ICD-10 underlying cause of death codes X60-X84, Y87.0, and U03, we (i) used hexagonal grids to describe rates of suicide by age, period, and cohort visually and (ii) modeled sex-, race-, and suicide method-specific age, period, and cohort effects. We found that, while suicide mortality increased in the US between 1999 and 2018 across age, sex, race, and suicide method, there was substantial heterogeneity in age and cohort effects by method, sex, and race, with a first peak of suicide risk in youth, a second peak in older ages-specific to male firearm suicide, and increased rates among younger cohorts of non-White individuals. Our findings should prompt discussion regarding age-specific clinical firearm safety interventions, drivers of minoritized populations' adverse early-life experiences, and racial differences in access to and quality of mental healthcare.

Helped into Harm: Mediation of a Housing Voucher Intervention on Mental Health and Substance Use in Boys.

BACKGROUND: Interventions can have harmful effects among subgroups they intend to help. The Moving To Opportunity experiment, in which families were randomized to receive a Section 8 housing voucher, was one example. Voucher receipt generally resulted in better long-term mental health and lower substance use and risk behavior outcomes among adolescent girls, but resulted in worse outcomes among adolescent boys. Reasons for this discrepancy and the unintended harmful health effects for boys are unclear. We used mediation analysis to estimate processes through which voucher receipt was hypothesized to affect adolescent mental health and substance use. METHODS: We used longitudinal data (10-15 years) on boys enrolled in Moving To Opportunity. We estimated interventional (also known as stochastic) indirect effects of voucher receipt on mental health and substance use outcomes through mediators capturing aspects of the school environment, neighborhood poverty, and instability of the social environment. We also estimated interventional direct effects not operating through these mediators. We used a robust, efficient, nonparametric substitution estimator in the targeted minimum loss-based framework. RESULTS: Housing voucher receipt increased long-term risk of any diagnostic statistical manual disorder, any mood disorder, any externalizing disorder, and cigarette smoking among boys. The majority (between 69% and 90%) of the total negative long-term effects could be explained by indirect effects through the mediators considered. CONCLUSIONS: This evidence suggests that, even though the intervention had the desired effects on neighborhood poverty and the school environment, these "positives" ultimately negatively impacted the long-term mental health and behaviors of boys.