Incidence of Suicidal Ideation in a Civil Servants Cohort During the COVID-19 Pandemic in Brazil: Insights from the ELSA-Brasil Study.

OBJECTIVE: This study investigated the incidence of suicidal ideation and its associated risk factors in the São Paulo state of ELSA-Brasil cohort during the COVID-19 pandemic. METHODS: During a pre-pandemic ELSA-Brasil onsite assessment in 2016-2018 (wave 3) and a pandemic online assessment in May-July 2020 (wave COVID), we assessed suicidal ideation using the Clinical Interview Scheduled-Revised (CIS-R). Single and multi predictor logistic regressions were performed using sociodemographic characteristics, household finance impact during pandemic, presence of previous chronic diseases, alcohol abuse, adverse childhood experiences (ACE), living alone, and previous CMD as predictors. Suicidal ideation incidence was used as outcome. RESULTS: Out of 4191 participants of wave 3, 2117 (50.5%) answered wave COVID. There was a threefold increase in suicide ideation, from 34 (1.8%) to 104 (5.6%).In multiple predictor models, we found that previous CMD (OR 7.17; 95% CI 4.43 - 11.58) and ACE (OR 1.72; 95% CI 1.09 - 2.72) increased the odds of incident suicidal ideation. The sociodemographic predictors female sex, younger age and low income were significant risk factors only in the single predictor model. Conclusions These findings underscore the importance of monitoring and supporting individuals who suffered ACE and have a history of mental health disorders. This is especially critical in times of heightened societal stress, such as the COVID-19 pandemic. CONCLUSIONS: These findings underscore the importance of monitoring and supporting individuals who suffered ACE and have a history of mental health disorders. This is especially critical in times of heightened societal stress, such as the COVID-19 pandemic.

A pandemic toll in frail older adults: Higher odds of incident and persistent common mental disorders in the ELSA-Brasil COVID-19 mental health cohort.

INTRODUCTION: We aimed to investigate the association of frailty with persistent and incident common mental disorders (CMD) in older adults during the pandemic. METHODS: We included 706 older adults who participated in the onsite wave of the ELSA-Brasil study (2017-2019) and the online COVID-19 assessment (May-July 2020). CMD were assessed in both waves by the Clinical Interview Schedule-Revised. Frailty was defined according to the physical phenotype and Frailty Index in the 2017-2019 wave. Logistic regression was used to investigate the association of frailty with persistent and incident CMD, adjusted for sociodemographics. RESULTS: Frailty according to both definitions were associated with persistent CMD (Frailty Index: OR = 8.61, 95 % CI = 4.08-18.18; physical phenotype: OR = OR = 23.67, 95 % CI = 7.08-79.15), and incident CMD (Frailty Index: OR = 2.79, 95 % CI = 1.15-6.78; physical phenotype OR = 4.37, 95 % CI = 1.31-14.58). The exclusion of exhaustion (that overlaps with psychiatric symptoms) from the frailty constructs did not change the association between frailty and persistent CMD, although the associations with indent CMD were no longer significant. LIMITATIONS: Fluctuations in CMD status were not captured between both assessments. CONCLUSION: Frailty status before the COVID-19 outbreak was associated with higher odds of persistent and incident CMD in older adults during the pandemic first wave. Identifying individuals at higher risk of mental burden can help prioritize resources allocation and management.

Prevalence and risk factors of psychiatric symptoms and diagnoses before and during the COVID-19 pandemic: findings from the ELSA-Brasil COVID-19 mental health cohort.

BACKGROUND: There is mixed evidence on increasing rates of psychiatric disorders and symptoms during the coronavirus disease 2019 (COVID-19) pandemic in 2020. We evaluated pandemic-related psychopathology and psychiatry diagnoses and their determinants in the Brazilian Longitudinal Study of Health (ELSA-Brasil) São Paulo Research Center. METHODS: Between pre-pandemic ELSA-Brasil assessments in 2008-2010 (wave-1), 2012-2014 (wave-2), 2016-2018 (wave-3) and three pandemic assessments in 2020 (COVID-19 waves in May-July, July-September, and October-December), rates of common psychiatric symptoms, and depressive, anxiety, and common mental disorders (CMDs) were compared using the Clinical Interview Scheduled-Revised (CIS-R) and the Depression Anxiety Stress Scale-21 (DASS-21). Multivariable generalized linear models, adjusted by age, gender, educational level, and ethnicity identified variables associated with an elevated risk for mental disorders. RESULTS: In 2117 participants (mean age 62.3 years, 58.2% females), rates of CMDs and depressive disorders did not significantly change over time, oscillating from 23.5% to 21.1%, and 3.3% to 2.8%, respectively; whereas rate of anxiety disorders significantly decreased (2008-2010: 13.8%; 2016-2018: 9.8%; 2020: 8%). There was a decrease along three wave-COVID assessments for depression [ß = -0.37, 99.5% confidence interval (CI) -0.50 to -0.23], anxiety (ß = -0.37, 99.5% CI -0.48 to -0.26), and stress (ß = -0.48, 99.5% CI -0.64 to -0.33) symptoms (all ps < 0.001). Younger age, female sex, lower educational level, non-white ethnicity, and previous psychiatric disorders were associated with increased odds for psychiatric disorders, whereas self-evaluated good health and good quality of relationships with decreased risk. CONCLUSION: No consistent evidence of pandemic-related worsening psychopathology in our cohort was found. Indeed, psychiatric symptoms slightly decreased along 2020. Risk factors representing socioeconomic disadvantages were associated with increased odds of psychiatric disorders.

Trajectories of common mental disorders symptoms before and during the COVID-19 pandemic: findings from the ELSA-Brasil COVID-19 Mental Health Cohort.

AIM: Evidence indicates most people were resilient to the impact of the COVID-19 pandemic on mental health. However, evidence also suggests the pandemic effect on mental health may be heterogeneous. Therefore, we aimed to identify groups of trajectories of common mental disorders' (CMD) symptoms assessed before (2017-19) and during the COVID-19 pandemic (2020-2021), and to investigate predictors of trajectories. METHODS: We assessed 2,705 participants of the ELSA-Brasil COVID-19 Mental Health Cohort study who reported Clinical Interview Scheduled-Revised (CIS-R) data in 2017-19 and Depression Anxiety Stress Scale-21 (DASS-21) data in May-July 2020, July-September 2020, October-December 2020, and April-June 2021. We used an equi-percentile approach to link the CIS-R total score in 2017-19 with the DASS-21 total score. Group-based trajectory modeling was used to identify CMD trajectories and adjusted multinomial logistic regression was used to investigate predictors of trajectories. RESULTS: Six groups of CMD symptoms trajectories were identified: low symptoms (17.6%), low-decreasing symptoms (13.7%), low-increasing symptoms (23.9%), moderate-decreasing symptoms (16.8%), low-increasing symptoms (23.3%), severe-decreasing symptoms (4.7%). The severe-decreasing trajectory was characterized by age < 60 years, female sex, low family income, sedentary behavior, previous mental disorders, and the experience of adverse events in life. LIMITATIONS: Pre-pandemic characteristics were associated with lack of response to assessments. Our occupational cohort sample is not representative. CONCLUSION: More than half of the sample presented low levels of CMD symptoms. Predictors of trajectories could be used to detect individuals at-risk for presenting CMD symptoms in the context of global adverse events.

Post-COVID-19 psychiatric and cognitive morbidity: Preliminary findings from a Brazilian cohort study.

OBJECTIVE: The present study aims to investigate the occurrence of psychiatric and cognitive impairments in a cohort of survivors of moderate or severe forms of COVID-19. METHOD: 425 adults were assessed 6 to 9 months after hospital discharge with a structured psychiatric interview, psychometric tests and a cognitive battery. A large, multidisciplinary, set of clinical data depicting the acute phase of the disease, along with relevant psychosocial variables, were used to predict psychiatric and cognitive outcomes using the 'Least Absolute Shrinkage and Selection Operator' (LASSO) method. RESULTS: Diagnoses of 'depression', 'generalized anxiety disorder' and 'post-traumatic stress disorder' were established respectively in 8%, 15.5% and 13.6% of the sample. After pandemic onset (i.e., within the previous year), the prevalence of 'depression' and 'generalized anxiety disorder' were 2.56% and 8.14%, respectively. Memory decline was subjectively reported by 51.1% of the patients. Psychiatric or cognitive outcomes were not associated with any clinical variables related to the severity of acute-phase disease, nor by disease-related psychosocial stressors. CONCLUSIONS: This is the first study to access rates of psychiatric and cognitive morbidity in the long-term outcome after moderate or severe forms of COVID-19 using standardized measures. As a key finding, there was no significant association between clinical severity in the acute-phase of SARS-CoV-2 infection and the neuropsychiatric impairment 6 to 9 months thereafter.

Examining the impact of the COVID-19 pandemic through the lens of the network approach to psychopathology: Analysis of the Brazilian Longitudinal Study of Health (ELSA-Brasil) cohort over a 12-year timespan.

Cohort studies have displayed mixed findings on changes in mental symptoms severity in 2020, when the COVID-19 pandemic outbreak started. Network approaches can provide additional insights by analyzing the connectivity of such symptoms. We assessed the network structure of mental symptoms in the Brazilian Longitudinal Study of Health (ELSA-Brasil) in 3 waves: 2008-2010, 2017-2019, and 2020, and hypothesized that the 2020 network would present connectivity changes. We used the Clinical Interview Scheduled-Revised (CIS-R) questionnaire to evaluates the severity of 14 common mental symptoms. Networks were graphed using unregularized Gaussian models and compared using centrality and connectivity measures. The predictive power of centrality measures and individual symptoms were also estimated. Among 2011 participants (mean age: 62.1 years, 58% females), the pandemic symptom 2020 network displayed higher overall connectivity, especially among symptoms that were related to general worries, with increased local connectivity between general worries and worries about health, as well as between anxiety and phobia symptoms. There was no difference between 2008 and 2010 and 2017-2019 networks. According to the network theory of mental disorders, external factors could explain why the network structure became more densely connected in 2020 compared to previous observations. We speculate that the COVID-19 pandemic and its innumerous social, economical, and political consequences were prominent external factors driving such changes; although further assessments are warranted.

Disinfection of 3D-printed protective face shield during COVID-19 pandemic.

This study assessed the disinfection using 70% ethanol; H2O2-quaternary ammonium salt mixture; 0.1% sodium hypochlorite and autoclaving of four 3D-printed face shields with different designs, visor materials; and visor thickness (0.5-0.75 mm). We also investigated their clinical suitability by applying a questionnaire to health workers (HW) who used them. Each type of disinfection was done 40 times on each type of mask without physical damage. In contrast, autoclaving led to appreciable damage.

Metabolism under hypoxia in Tm1 murine melanoma cells is affected by the presence of galectin-3, a metabolomics approach.

Metabolomics has proven an useful tool for systems biology. Here we have used a metabolomics approach to identify conditions in which de novo expression of an established tumor marker, galectin-3, would confer a potential selective advantage for melanoma growth and survival. A murine melanoma cell line (Tm1) that lacks galectin-3 was modified to express it or not (Tm1.G2 and Tm1.N3, respectively). These variant cell line were then exposed to conditions of controlled oxygen tensions and glucose levels. Metabolic profiling of intracellular metabolites of cells exposed to these conditions was obtained in steady state using high resolution (1)H Magnetic Resonance Spectroscopy ((1)H-MRS) and multivariate statistical analysis. The Nuclear Magnetic Resonance (NMR) spectra contained a large number of absorption lines from which we were able to distinguish 20 metabolites, 3 fatty acids and some absorption lines and clusters were not identified. Principal Components Analysis (PCA) allowed for the discrimination of 2 experimental conditions in which expression of the tumor marker galectin-3 may play a significant role, namely exposure of cells to hypoxia under high glucose. Interestingly, under all other experimental conditions tested, the cellular system was quite robust. Our results suggest that the Metabolomics approach can be used to access information about changes in many metabolic pathways induced in tumorigenic cells and to allow the evaluation of their behavior in controlled environmental conditions or selective pressures.