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Aims: To explore the association between a depression diagnosis in young adulthood and risk of marginalisation at age 29 years, among those who had completed upper secondary school and those who had not completed at age 21. Methods: In a longitudinal cohort study based on nationwide registers we followed 111,558 people from age 22–29 years. Outcomes were risk of marginalisation and educational achievement at age 29. Exposure was a diagnosed depression at ages 22–26 years. Comorbid mental and somatic health conditions, gender and country of origin were covariates. Relative risks were estimated with Poisson regression models, stratified by educational level at age 21. Results: For people who had not completed upper secondary school at age 21 years, a depression diagnosis at age 22–26 increased the risk of low income (relative risk = 1.33; 95% confidence interval = 1.25–1.40), prolonged unemployment benefit (1.46; 1.38–1.55) and social security benefit (1.56; 1.41–1.74) at age 29 compared with those with no depression. Among those who had completed upper secondary school at age 21 years, depression increased the risk of low income (1.71; 1.60–1.83), prolonged unemployment benefit (2.17; 2.03–2.31), social security benefit (3.62; 2.91–4.51) and disability pension (4.43; 3.26–6.01) compared with those with no depression. Mental comorbidity had a significant impact on risk of marginalisation in both groups. Conclusions: Depression in one's mid-20s significantly increases the risk of marginalisation at age 29 years, and comorbid mental health conditions reinforce this association. Functional ability should be given priority in depression care in early adulthood to counteract marginalisation. [ABSTRACT FROM AUTHOR]

Background Young adults in Neither in Employment, Education nor Training (NEET) are at risk of adverse labour market outcomes. Earlier studies often measured NEET status at one time point or compared persistent NEETs with non-NEETs, neglecting other patterns of NEET status. Evidence on early life factors associated with NEET patterns is lacking. This study aims to (i) identify patterns of NEET status over time and (ii) examine whether factors in childhood and adolescence are associated with these patterns. Methods Data were used from 1499 participants of the TRacking Adolescents' Individual Lives Survey (TRAILS), a Dutch prospective cohort study with 15-year follow-up. NEET status was assessed at ages 19, 22 and 26. Socioeconomic status of parents (SES), intelligence and negative life events were measured at age 11, educational attainment at age 26 and mental health problems at ages 11, 13.5 and 16. Data were analyzed using multinomial logistic regression analysis. Results Four NEET patterns were identified: (i) non-NEETs (85.2%), (ii) early NEETs (4.5%), (iii) late NEETs (5.7%) and (iv) persistent NEETs (4.5%). Reporting internalizing problems at age 11 was a risk factor for early and late NEETs [odds ratio (OR) 2.77, 95% confidence interval (CI) 1.16–6.62; OR 5.00, 95% CI 2.22–11.3, respectively]. Low parental SES, lower intelligence scores and negative life events (≥3) were risk factors for persistent NEETs (OR 4.45, 95% CI 2.00–9.91; OR 0.96, 95% CI 0.94–0.98; OR 4.42, 95% CI 1.62–12.08, respectively). Conclusions The results highlight the importance of timing and duration of NEET status and emphasize the need for tailored interventions to prevent specific NEET patterns. [ABSTRACT FROM AUTHOR]

Background and Objectives Suicide rates typically increase during recessions. However, few studies have explored how recessions affect risk among older adults nearing retirement. This study used a large suicide mortality registry to characterize and quantify suicide related to retirement during the Great Recession (GR). Research Design and Methods Data come from the National Violent Death Reporting System (NVDRS, 2004–2017; N  = 53,298 suicide deaths age ≥50). We analyzed the text narratives (i.e. descriptions of the most salient circumstances to each suicide) of these decedents using natural language processing (NLP) to identify cases that were "retirement-related" (RR, e.g. anticipating, being unable to, or recently retiring). We used time-series analysis to quantify variation in RR over the GR, and compared these trends to retirees (i.e. decedents whose occupation was "retired") and all decedents aged ≥50. We used content and network analysis to characterize themes represented in the narratives. Results There were 878 RR cases (1.6% of suicides aged ≥50) identified by the NLP model; only 52% of these cases were among retirees. RR cases were younger (62 vs 75 years) and more educated (41.5% vs 24.5% college degree) than retirees. The rate of RR suicide was positively associated with indicators of the GR (e.g. short-term unemployment R 2 = 0.70, p  = .024), but economic indicators were not correlated with the suicide rate among retirees or older adults in general. Economic issues were more central to the narratives of RR cases during the GR compared to other periods. Discussion and Implications Recessions shape suicide risk related to retirement transitions. [ABSTRACT FROM AUTHOR]

Introduction: Existing literature suggests that transgender women (TW) may be at high risk for adverse mental health due to stress attributed to combined experiences of stigma and complex social and structural vulnerabilities. Little research has examined how these co‐occurring experiences relate to mental health. We aimed to test a theoretically driven conceptual model of relationships between stigma, social and structural vulnerabilities, and mental health to inform future intervention tailoring. Design/Methods: Partial least square path modeling followed by response‐based unit segmentation was used to identify homogenous clusters in a diverse community sample of United States (US)‐based TW (N = 1418; 46.2% White non‐Hispanic). This approach examined associations between latent constructs of stigma (polyvictimization and discrimination), social and structural vulnerabilities (housing and food insecurity, unemployment, sex work, social support, and substance use), and mental health (post‐traumatic stress and psychological distress). Results: The final conceptual model defined the structural relationship between the variables of interest within stigma, vulnerability, and mental health. Six clusters were identified within this structural framework which suggests that racism, ethnicism, and geography may be related to mental health inequities among TW. Conclusion: Our findings around the impact of racism, ethnicism, and geography reflect the existing literature, which unfortunately shows us that little change has occurred in the last decade for TW of color in the Southern US; however, the strength of our evidence (related to sampling structure and sample size) and type of analyses (accounting for co‐occurring predictors of health, i.e., stigma and complex vulnerabilities, reflecting that of real‐world patients) is a novel and necessary addition to the literature. Findings suggest that health interventions designed to offset the negative effects of stigma must include anti‐racist approaches with components to reduce or eliminate barriers to resources that contribute to social and structural vulnerabilities among TW. Herein we provide detailed recommendations to guide primary, secondary, and tertiary prevention efforts. Clinical Relevance: This study demonstrated the importance of considering stigma and complex social and structural vulnerabilities during clinical care and design of mental health interventions for transgender women who are experiencing post‐traumatic stress disorder and psychological distress. Specifically, interventions should take an anti‐racist approach and would benefit from incorporating social support‐building activities. [ABSTRACT FROM AUTHOR]