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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 (least absolute shrinkage and selection operator regression [LASSO]) model interactions. Cases made a nonfatal suicide attempt (n  = 6032) 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 (in men, 0.85, 95% CI, 0.84-0.86; in women, 0.89, 95% C, 0.88-0.90) than random forests (in men, 0.76, 95% CI, 0.74-0.78; in women, 0.79, 95% CI = 0.78-0.81). 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. This article is part of a Special Collection on Mental Health. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Cannabis use disorder diagnoses are increasing among U.S. adults and are more prevalent among people with comorbid psychiatric disorders. Recent changes in cannabis laws, increasing cannabis availability, and higher-potency cannabis may have placed people with cannabis use and psychiatric disorders at disproportionately increasing risk for cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine whether trends in cannabis use disorder prevalence among VHA patients differ by whether they have psychiatric disorders. VHA electronic health records from 2005 to 2019 (N range, 4,332,165–5,657,277) were used to identify overall and age-group-specific (<35, 35–64, and ≥65 years) trends in prevalence of cannabis use disorder diagnoses among patients with depressive, anxiety, posttraumatic stress, bipolar, or psychotic spectrum disorders and to compare these to corresponding trends among patients without any of these disorders. Given transitions in ICD coding, differences in trends were tested within two periods: 2005–2014 (ICD-9-CM) and 2016–2019 (ICD-10-CM). Greater increases in prevalence of cannabis use disorder diagnoses were observed among patients with psychiatric disorders compared to those without (difference in prevalence change, 2005–2014: 1.91%, 95% CI=1.87–1.96; 2016–2019: 0.34%, 95% CI=0.29–0.38). Disproportionate increases in cannabis use disorder prevalence among patients with psychiatric disorders were greatest among those under age 35 between 2005 and 2014, and among those age 65 or older between 2016 and 2019. Among patients with psychiatric disorders, the greatest increases in cannabis use disorder prevalences were observed among those with bipolar and psychotic spectrum disorders. The findings highlight disproportionately increasing disparities in risk of cannabis use disorder among VHA patients with common psychiatric disorders. Greater public health and clinical efforts are needed to monitor, prevent, and treat cannabis use disorder in this population. [ABSTRACT FROM AUTHOR]

Background and Aims: Benzodiazepines (BZDs) carry a risk for drug overdose and are prescribed alone or simultaneously with selective‐serotonin reuptake inhibitors (SSRIs) for the treatment of anxiety and depression in young adults. We aimed to measure risks of drug overdose following BZD treatment initiation, and simultaneous BZD and SSRI initiation, compared with SSRI treatment alone in young adults with depression or anxiety. Design, Setting, Participants: The cohort study used administrative databases covering privately (MarketScan, 1/1/2009–12/31/2018) and publicly (Medicaid, 1/1/2015–12/31/2016) insured young adults (18–29 years) in the United States. Those with depression or anxiety diagnoses newly initiating BZD or SSRI treatment (without BZD or SSRI prescriptions in prior year) were included. Simultaneous "BZD + SSRI" initiation was defined as starting BZD and SSRI treatment on the same day. The cohorts included 604 664 privately insured young adults (BZD = 22%, BZD + SSRI = 10%, SSRI = 68%) and 110 493 publicly insured young adults (BZD = 23%, BZD + SSRI = 5%, SSRI = 72%). Measurements: Incident medically treated drug overdose events were identified from emergency department and inpatient encounters (ICD poisoning codes) within 6 months of treatment initiation. Crude and propensity‐score adjusted cumulative incidence and hazard ratios (HR) were estimated. Sub‐analyses evaluated drug overdose intent. Findings Adjusted HRs of drug overdose for BZD vs. SSRI treatment was 1.36 (95% confidence interval [CI]:1.23–1.51) in privately and 1.59 (95%CI:1.37–1.83) in publicly insured young adults. The adjusted HRs of drug overdose for BZD + SSRI treatment vs. SSRI treatment were 1.99 (95%CI:1.77–2.25) in privately and 1.98 (95%CI:1.47–2.68) in publicly insured young adults. Conclusions: Among young adults in the United States, initiating benzodiazepine treatment for anxiety and depression, alone or simultaneously with selective‐serotonin reuptake inhibitors (SSRI), appears to have an increased risk of medically treated drug overdose compared with SSRI treatment alone. These associations were observed in publicly and privately insured individuals. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Mandatory prescription drug monitoring programs and cannabis legalization have been hypothesized to reduce overdose deaths. We examined associations between prescription monitoring programs with access mandates ("must-query PDMPs"), legalization of medical and recreational cannabis supply, and opioid overdose deaths in United States counties in 2013-2020. Using data on overdose deaths from the National Vital Statistics System, we fit Bayesian spatiotemporal models to estimate risk differences and 95% credible intervals (CrI) in county-level opioid overdose deaths associated with enactment of these state policies. Must-query PDMPs were independently associated with on average 0.8 (95% CrI: 0.5, 1.0) additional opioid-involved overdose deaths per 100,000 person-years. Legal cannabis supply was not independently associated with opioid overdose deaths in this time period. Must-query PDMPs enacted in the presence of legal (medical or recreational) cannabis supply were associated with 0.7 (95% CrI: 0.4, 0.9) more opioid-involved deaths, relative to must-query PDMPs without any legal cannabis supply. In a time when overdoses are driven mostly by non-prescribed opioids, stricter opioid prescribing policies and more expansive cannabis legalization were not associated with reduced overdose death rates., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Importance: The proportion of mental disorders and burden causally attributable to childhood maltreatment is unknown., Objective: To determine the contribution of child maltreatment to mental health conditions in Australia, accounting for genetic and environmental confounding., Design, Setting, and Participants: This meta-analysis involved an epidemiological assessment accounting for genetic and environmental confounding between maltreatment and mental health and 3 cross-sectional national surveys: the Australian Child Maltreatment Study (ACMS) 2023, National Study of Mental Health and Well-being 2020-2022, and Australian Burden of Disease Study 2023. Causal estimates were derived on the association between childhood maltreatment and mental health conditions from a meta-analysis of quasi-experimental studies. This was combined with the prevalence of maltreatment from the ACMS to calculate the population attributable fraction (PAF). The PAF was applied to the number and burden of mental health conditions in Australia, sourced from 2 population-based, nationally representative surveys of Australians aged 16 to 85 years, to generate the number and associated burden of mental disorders attributable to child maltreatment., Exposure: Physical abuse, sexual abuse, emotional abuse, or neglect prior to age 18 years., Main Outcomes and Measures: Proportion and number of cases, years of life lost, years lived with disability, and disability-adjusted life-years of mental health conditions (anxiety, depression, harmful alcohol and drug use, self-harm, and suicide attempt) attributable to childhood maltreatment., Results: Meta-analytic estimates were generated from 34 studies and 54 646 participants and applied to prevalence estimates of childhood maltreatment generated from 8503 Australians. Childhood maltreatment accounted for a substantial proportion of mental health conditions, ranging from 21% (95% CI, 13%-28%) for depression to 41% (95% CI, 27%-54%) of suicide attempts. More than 1.8 million cases of depressive, anxiety, and substance use disorders could be prevented if childhood maltreatment was eradicated. Maltreatment accounted for 66 143 years of life lost (95% CI, 43 313-87 314), primarily through suicide, and 184 636 disability-adjusted life-years (95% CI, 109 321-252 887)., Conclusions and Relevance: This study provides the first estimates of the causal contribution of child maltreatment to mental health in Australia. Results highlight the urgency of preventing child maltreatment to reduce the population prevalence and burden of mental disorders.

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., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)

In population neuroscience, samples are not often selected with equal or known probability from an underlying population of interest; in other words, samples are not often formally representative of a specified underlying population. This chapter provides an overview of an epidemiological approach to considering the implications of selective participation on the value of our results for population health. We discuss definitions of generalizability and transportability, given the growing recognition that generalizability and transportability are central for interpreting data that are aiming to be population-based. We provide evidence that differences in the prevalence of effect measure modifiers between a study sample and a target population will lead to a lack of generalizability and transportability. We provide an example of an association between a poly-genetic risk score and depression, showing how an internally valid association can differ based on the prevalence of effect measure modifiers. We show that when estimating associations, inferences from a study sample to a population can depend on clearly defining a target population. Given that representative sampling from explicitly defined target populations may not be feasible or realistic in many situations, especially given the sample sizes needed for statistical power for many exposures of interest (and especially when interactions are being tested), researchers should be well versed in tools available to enhance the interpretability of samples regarding target populations., (© 2024. The Author(s), under exclusive license to Springer Nature Switzerland AG.)

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., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)