Mood disorders in childhood and adolescence

The identification and treatment of mood disorders in children and adolescents has grown over the last decades. Major depression is one of the most common and debilitating disorders worldwide, imposing a massive burden to the youth population. Bipolar disorder is being increasingly recognized as having its roots early in life, and its presentation during childhood and adolescence has been submitted to extensive research. This review aims to highlight clinical aspects of the current knowledge on mood disorders in the pediatric population, presenting updated information on epidemiology, diagnostic procedures, and management strategies. Limitations of available evidence and future directions of research in the field are also discussed.Universidade Federal do Rio Grande do Sul Hospital de Clinicas de Porto Alegre Department of PsychiatryUniversidade Federal de São Paulo (UNIFESP) Department of Psychiatry Child and Adolescent Psychiatry UnitUNIFESP, Department of Psychiatry Child and Adolescent Psychiatry UnitSciEL

Predicting the risk of future depression among school-attending adolescents in Nigeria using a model developed in Brazil

Depression commonly emerges in adolescence and is a major public health issue in low- and middle-income countries where 90% of the world's adolescents live. Thus efforts to prevent depression onset are crucial in countries like Nigeria, where two-thirds of the population are aged under 24. Therefore, we tested the ability of a prediction model developed in Brazil to predict future depression in a Nigerian adolescent sample. Data were obtained from school students aged 14–16 years in Lagos, who were assessed in 2016 and 2019 for depression using a self-completed version of the Mini International Neuropsychiatric Interview for Children and Adolescents. Only the 1,928 students free of depression at baseline were included. Penalized logistic regression was used to predict individualized risk of developing depression at follow-up for each adolescent based on the 7 matching baseline sociodemographic predictors from the Brazilian model. Discrimination between adolescents who did and did not develop depression was better than chance (area under the curve = 0.62 (bootstrap-corrected 95% CI: 0.58–0.66). However, the model was not well-calibrated even after adjustment of the intercept, indicating poorer overall performance compared to the original Brazilian cohort. Updating the model with context-specific factors may improve prediction of depression in this setting

Predicting the risk of depression among adolescents in Nepal using a model developed in Brazil : the IDEA Project

The burden of adolescent depression is high in low- and middle-income countries (LMICs), yet research into prevention is lacking. Development and validation of models to predict individualized risk of depression among adolescents in LMICs is rare but crucial to ensure appropriate targeting of preventive interventions. We assessed the ability of a model developed in Brazil, a middle-income country, to predict depression in an existing culturally different adolescent cohort from Nepal, a low-income country with a large youth population with high rates of depression. Data were utilized from the longitudinal study of 258 former child soldiers matched with 258 war-affected civilian adolescents in Nepal. Prediction modelling techniques were employed to predict individualized risk of depression at age 18 or older in the Nepali cohort using a penalized logistic regression model. Following a priori exclusions for prior depression and age, 55 child soldiers and 71 war-affected civilians were included in the final analysis. The model was well calibrated, had good overall performance, and achieved good discrimination between depressed and non-depressed individuals with an area under the curve (AUC) of 0.73 (bootstrap-corrected 95% confidence interval 0.62-0.83). The Brazilian model comprising seven matching sociodemographic predictors, was able to stratify individualized risk of depression in a Nepali adolescent cohort. Further testing of the model's performance in larger socio-culturally diverse samples in other geographical regions should be attempted to test the model's wider generalizability

Age of Sexual Initiation, Psychiatric Symptoms, and Sexual Risk Behavior among Ecstasy and LSD Users in Porto Alegre, Brazil: A Preliminary Analysis

Ecstasy and LSD use is widespread in large Brazilian cities, but there is limited information on their use among young, middle-class, club goers in Brazil. We conducted standardized face-to-face interviews with 200 male and female ecstasy and/or LSD users, focusing on drug use and sexual history, current risk behaviors, and psychiatric symptomatology. Participants with early sexual debut (before 14) were more likely to report lifetime use of marijuana and powder and crack cocaine than those with later sexual initiation. Early sexual debut was associated with past year sexual risk behaviors, including having sex while high (Prevalence Ratio (PR)=1.3), having two or more sex partners (PR=1.3), as well as history of sexual abuse (PR=13.6). Depression and anxiety scores were similar by age of sexual initiation. The implications of these findings are discussed

Childhood exposure to ambient air pollution and predicting individual risk of depression onset in UK adolescents

Knowledge about early risk factors for major depressive disorder (MDD) is critical to identify those who are at high risk. A multivariable model to predict adolescents’ individual risk of future MDD has recently been developed however its performance in a UK sample was far from perfect. Given the potential role of air pollution in the aetiology of depression, we investigate whether including childhood exposure to air pollution as an additional predictor in the risk prediction model improves the identification of UK adolescents who are at greatest risk for developing MDD. We used data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally representative UK birth cohort of 2,232 children followed to age 18 with 93% retention. Annual exposure to four pollutants – nitrogen dioxide (NO(2)), nitrogen oxides (NO(X)), particulate matter <2.5μm (PM(2.5)) and <10μm (PM(10)) – were estimated at address-level when children were aged 10. MDD was assessed via interviews at age 18. The risk of developing MDD was elevated most for participants with the highest (top quartile) level of annual exposure to NO(X) (adjusted OR=1.43, 95% CI=0.96-2.13) and PM(2.5) (adjusted OR=1.35, 95% CI=0.95-1.92). The separate inclusion of these ambient pollution estimates into the risk prediction model improved model specificity but reduced model sensitivity – resulting in minimal net improvement in model performance. Findings indicate a potential role for childhood ambient air pollution exposure in the development of adolescent MDD but suggest that inclusion of risk factors other than this may be important for improving the performance of the risk prediction model

Schedule for affective disorders and schizophrenia for school-age children - present and lifetime version (K-SADS-PL), DSM-5 update : translation into Brazilian Portuguese

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Identifying adolescents at risk for depression: a prediction score performance in cohorts based in three different continents:A Prediction Score Performance in Cohorts Based in 3 Different Continents

OBJECTIVE: Prediction models have become frequent in the medical literature, but most published studies are conducted in a single setting. Heterogeneity between development and validation samples has been posited as a major obstacle for the generalization of models. We aimed to develop a multivariable prognostic model using sociodemographic variables easily obtainable from adolescents at age 15 to predict a depressive disorder diagnosis at age 18 and to evaluate its generalizability in 2 samples from diverse socioeconomic and cultural settings. METHOD: Data from the 1993 Pelotas Birth Cohort were used to develop the prediction model, and its generalizability was evaluated in 2 representative cohort studies: the Environmental Risk (E-Risk) Longitudinal Twin Study and the Dunedin Multidisciplinary Health and Development Study. RESULTS: At age 15, 2,192 adolescents with no evidence of current or previous depression were included (44.6% male). The apparent C-statistic of the models derived in Pelotas ranged from 0.76 to 0.79, and the model obtained from a penalized logistic regression was selected for subsequent external evaluation. Major discrepancies between the samples were identified, impacting the external prognostic performance of the model (Dunedin and E-Risk C-statistics of 0.63 and 0.59, respectively). The implementation of recommended strategies to account for this heterogeneity among samples improved the model’s calibration in both samples. CONCLUSION: An adolescent depression risk score comprising easily obtainable predictors was developed with good prognostic performance in a Brazilian sample. Heterogeneity among settings was not trivial, but strategies to deal with sample diversity were identified as pivotal for providing better risk stratification across samples. Future efforts should focus on developing better methodological approaches for incorporating heterogeneity in prognostic research