Exploring protective factors in a high-risk subsample: the pivotal role of paternal support in preventing depression in a cohort of young adults.

BACKGROUND: Major depressive disorder (MDD) is a global concern due to its widespread prevalence and morbidity. Identifying protective factors in high-risk individuals, including those with a familial predisposition, maltreatment history, and socio-economic vulnerabilities, is crucial. METHODS: We assessed a high-risk subsample within a young adult population cohort (n = 791; mean age = 31.94 [SD = 2.18]) across three waves. Using multiple regression models to analyse higher education, feeling supported, spirituality, psychotherapy access, higher socioeconomic status, involvement in activities, cohabitation, and family unity in Waves 1 and 2, and their association with MDD resilience at Wave 3. RESULTS: In the high-risk group, MDD incidence was 13.7% (n=24). Paternal support had a protective effect on MDD incidence (OR = 0.366; 95% CI [0.137 to 0.955], p = 0.040) and suicidal attempt risk (OR = 0.380; 95% CI [0.150 to 0.956], p = 0.038). Higher resilience scores were also protective (OR = 0.975; 95% CI [0.953 to 0.997], p = 0.030), correlating with reduced BDI (r = 0.0484; B = -0.2202; 95% CI [-0.3572 to -0.0738]; p = 0.003) and MADRS scores (r = 0.0485; B = -0.2204; 95% CI [-0.3574 to -0.0741]; p = 0.003). CONCLUSIONS: Our paper emphasizes reorienting the MDD approach, focusing on positive prevention strategies. It highlights fathers' crucial role in family-based interventions and promoting resilience in high-risk populations.

Early exposure to cannabis and bipolar disorder incidence: Findings from a 22-year birth cohort study in Brazil.

BACKGROUND AND OBJECTIVES: Bipolar disorder is a chronic condition affecting millions of people worldwide. Currently, there is some evidence to suggest that cannabis use during adolescence may be an environmental risk factor for its onset, however inconsistencies have been observed across the literature. Considering this, we aimed to assess whether early lifetime cannabis is associated with subsequent bipolar disorder in young adults between 18 and 22 years of age. METHODS: Using data from the 1993 Pelotas (Brazil) birth cohort (n = 5249), cannabis exposure was examined at age 18 by self-report, and bipolar disorder diagnosis was measured at age 22 using the Mini International Neuropsychiatric Interview (MINI). In order to control the analysis, we considered socioeconomic status index, sex, skin color, physical abuse by parents and lifetime cocaine use. RESULTS: A total of 3781 individuals were evaluated in 2015 aged 22 years, of whom 87 were diagnosed with the bipolar disorder onset after the age of 18. Lifetime cannabis use predicted bipolar disorder onset at 22 years old (OR 1.82, 95% CI [1.10, 2.93]), and the effect remained after adjusting for socioeconomic status, sex, skin color, and physical abuse by parents (OR 2.00, 95% CI [1.20, 3.25]). However, this association was attenuated to statistically non-significant after further adjustment for all available covariates, including lifetime cocaine use (OR 1.79, 95% CI [0.95, 3.19]). We also found similar results for early cocaine use, where the association with bipolar disorder onset did not maintain significance in the multivariate model (OR 1.35, 95% CI [0.62, 2.86]). Otherwise, when we considered cannabis or cocaine lifetime use as a unique feature, our findings showed that the adolescent exposure to cannabis or cocaine increased the odds by 1.95 times of developing bipolar disorder at 22 years age, even when controlling for all other study variables (OR 2.14, 95% CI [1.30, 3.47]). Finally, our models suggest that cocaine use may potentially exert a major influence on the effect of lifetime cannabis use on bipolar disorder onset, and that physical abuse by parents and sex may modify the effect of cannabis use for later bipolar disorder onset. CONCLUSION: Based on our findings, early cannabis exposure predicted bipolar disorder onset in young adults, but this association was confounded by cocaine use. Contrary to schizophrenia, cannabis as a sole exposure was not associated with bipolar disorder onset after adjusting for control variables.

Perinatal factors as risk factors of bipolar disorder onset in young adulthood: a 22-year birth cohort.

BACKGROUND: Bipolar disorder (BD) is a leading cause of disability-adjusted life years in young adults. Complications during prenatal periods have been associated with BD previously. The study aims to examine the association between perinatal factors and BD in order to prevent the risk of developing BD. METHODS: 3,794 subjects from the 1993 Pelotas population-based birth cohort study were included. We assessed 27 initial variables at birth and modelled BD onset at 18 and 22 years. We performed bivariate analysis, using binomial logistic regression models. The variables with p-value smaller than 0.05 were included into a multiple regression with confounding variables. RESULTS: Maternal smoking was associated with a 1.42-fold increased risk of BD at 18 or 22 years old (95% CI: 1.091-1.841), and maternal passive exposure to tobacco with a 1.43-fold increased risk (95% CI: 1.086-1.875). No association was found between other perinatal factors and BD after controlling for confounding factors. CONCLUSION: The results of this cohort corroborate with previous findings in the literature that already indicate the negative outcomes of maternal smoking during pregnancy. They may now be linked to other studies to target these factors for preventing the development of BD.

Validity and reliability of the Brazilian version of the Cognitive Reserve Assessment Scale in Health

Objective: As the older population increases, it is important to identify factors that may reduce the risks of dementia in the general population. One such factor is the concept of cognitive reserve (CR). The present study analyzed the psychometric properties of the Cognitive Reserve Assessment Scale in Health (CRASH) in the Brazilian population. This scale was originally developed to measure CR in individuals with severe mental illness. We also investigated the relationship between the CRASH and clinical or sociodemographic variables. Methods: This study was conducted with 398 individuals. We assessed sociodemographic variables and depression, anxiety, and stress symptoms (Depression, Anxiety and Stress Scale [DASS-21]) using a web-based survey. We constructed a confirmatory factor analysis (CFA) model in order to test the goodness of fit of the factor structure proposed in the original CRASH study. Results: The McDonald's hierarchical ω for CRASH using CFA parameters was 0.61, and the Cronbach's alpha coefficient indicated good internal consistency when considering all items (alpha = 0.7). Conclusions: Our results suggest that CRASH can be used to assess CR in the general population in Brazil.

Validity and Reliability of the Brazilian Version of the Cognitive Reserve Assessment Scale in Health (CRASH).

OBJECTIVE: As the elderly population increases, it is important to identify factors that may reduce risks of dementia in the general population. One such factor is the concept of cognitive reserve (CR). The present study analyzed the psychometric properties of the Cognitive Reserve Assessment Scale in Health (CRASH) in the Brazilian population, which was originally developed to measure CR in individuals with severe mental illness. We also investigated the relationship between the CRASH and clinical or sociodemographic variables. METHODS: This study was conducted with 398 individuals. We assessed sociodemographic variables and depression, anxiety and stress symptoms (DASS-21), using a web-based survey. We constructed a confirmatory factor analysis (CFA) model in order to test the goodness of fit of the factor structure proposed in the original CRASH study. RESULTS: The McDonald's hierarchical ω for CRASH using CFA parameters was 0.61 and Cronbach's alpha coefficient indicated good internal consistency when considering all items (∝ = 0.7). CONCLUSIONS: Our results suggest that CRASH can be used to assess CR in the general population in Brazil.

Predictors of illicit substance abuse/dependence during young adulthood: A machine learning approach.

Prior studies have found an especially high prevalence of illicit substance use among adolescents and young adults in Brazil. The current study aimed to employ machine learning techniques to identify predictors of illicit substance abuse/dependence among a large community sample of young adults followed for 5 years. This prospective, population-based cohort study included a sample of young adults between the ages of 18-24 years from Pelotas, Brazil at baseline (T1). The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) was used to assess illicit substance abuse/dependence. A clinical interview was conducted to collect data on sociodemographic characteristics and psychopathology. Elastic net was used to generate a regularized linear model for the machine learning component of this study, which followed standard machine learning protocols. A total of 1560 young adults were assessed at T1, while 1244 were reassessed at the 5-year follow-up period (T2). The strongest predictors of illicit substance abuse/dependence at baseline (AUC of 0.83) were alcohol abuse/dependence, tobacco abuse/dependence, being in a current major depressive episode, history of a lifetime manic episode, current suicide risk, and male sex. The strongest predictors for illicit substance abuse/dependence at the 5-year follow-up (AUC: 0.79) were tobacco abuse/dependence at T1, history of a lifetime manic episode at T1, male sex, alcohol abuse/dependence at T1, and current suicide risk at T1. Our findings indicate that machine learning techniques hold the potential to predict illicit substance abuse/dependence among young adults using sociodemographic/clinical characteristics, with relatively high accuracy.

Sleep alterations as a predictor of bipolar disorder among offspring of parents with bipolar disorder: a systematic review and meta-analysis

Abstract Introduction Bipolar disorder (BD) has a high heritability rate. Current studies have been dedicated to identifying prodromes of BD in the offspring of parents with BD (BO) and the sleep patterns of these individuals have been considered important factors. Objective To describe changes in sleep parameters among offspring of parents with BD when compared to offspring of controls and to identify if changes in parameters and quality of sleep predict the onset of BD among these individuals. Methods PubMed, PsycINFO, and Embase were systematically searched with no year or language restrictions, up to August 18, 2020. We searched for a combination of the following search items ("sleep*") AND ("bipolar disorder*" OR "mania" OR "hypomania" OR "bipolar depression") AND ("ultra-high risk" OR "high risk" OR "offspring" OR "first degree relatives"). Results A total of 10 studies were included in the systematic review and 4 studies were included in the meta-analysis. Our meta-analysis showed that the BO had greater daytime sleepiness as compared to the offspring of control parents. The systematic review indicated that shorter sleep duration, sleep disorders, and other related features can differentiate the two groups. Finally, some sleep patterns such as decreased sleep, difficulty falling asleep, and overall sleep problems might be predictors for the development of BD. Conclusion Results from the meta-analysis indicated that BO had greater daytime sleepiness. Qualitative results showed that the offspring of parents with BD have an increased likelihood of experiencing an adverse sleep pattern.

Sleep alterations as a predictor of bipolar disorder among offspring of parents with bipolar disorder: a systematic review and meta-analysis.

INTRODUCTION: Bipolar disorder (BD) has a high heritability rate. Current studies have been dedicated to identifying prodromes of BD in the offspring of parents with BD (BO) and the sleep patterns of these individuals have been considered important factors. OBJECTIVE: To describe changes in sleep parameters among offspring of parents with BD when compared to offspring of controls and to identify if changes in parameters and quality of sleep predict the onset of BD among these individuals. METHODS: PubMed, PsycINFO, and Embase were systematically searched with no year or language restrictions, up to August 18, 2020. We searched for a combination of the following search items ("sleep*") AND ("bipolar disorder*" OR "mania" OR "hypomania" OR "bipolar depression") AND ("ultra-high risk" OR "high risk" OR "offspring" OR "first degree relatives"). RESULTS: A total of 10 studies were included in the systematic review and 4 studies were included in the meta-analysis. Our meta-analysis showed that the BO had greater daytime sleepiness as compared to the offspring of control parents. The systematic review indicated that shorter sleep duration, sleep disorders, and other related features can differentiate the two groups. Finally, some sleep patterns such as decreased sleep, difficulty falling asleep, and overall sleep problems might be predictors for the development of BD. CONCLUSION: Results from the meta-analysis indicated that BO had greater daytime sleepiness. Qualitative results showed that the offspring of parents with BD have an increased likelihood of experiencing an adverse sleep pattern.