Sociobehavioral, Biological, and Health Characteristics of Riverside People in the Xingu Region, Pará, Brazil.

This study aimed to evaluate the sociodemographic, behavioral, and biological profile and its relationship with the emergence of chronic non-communicable diseases in riverside populations in the Xingu region, Pará, Brazil. Characteristics related to health indicators and which risk factors are considered most important were analyzed. This is a cross-sectional, exploratory, and descriptive study. The sample consisted of riverside people of over 18 years of both sexes. The sample size (n = 86) was calculated with a confidence level of 95% and a sample error of 5%. The K-means clustering algorithm was adopted through an unsupervised method to divide the groups, and the values were expressed as a median. For continuous and categorical data, the Mann-Whitney and chi-square tests were used, respectively, and the significance level was set at p < 5%. The multi-layer perceptron algorithm was applied to classify the degree of importance of each variable. Based on this information, the sample was divided into two groups: the group with low or no education, with bad habits and worse health conditions, and the group with opposite characteristics. The risk factors considered for cardiovascular diseases and diabetes in the groups were low education (p < 0.001), sedentary lifestyle (p < 0.01), smoking, alcoholism, body mass index (p < 0.05), and waist-hip ratio, with values above the expected being observed in both groups. The factors considered important so as to be considered to have good health condition or not were the educational and social conditions of these communities, and one part of the riverside population was considered healthier than the other.

The impact of the social isolation in elderly Brazilian mental health (anxiety and depression) during the COVID-19 pandemic.

The impact of social isolation in the pandemic context on elderly Brazilian mental health is little known, especially about the occurrence of depressive symptoms. In this study, we evaluated elderly people undergoing social isolation in order to identify factors associated with depression and which of these are more important to characterize elderly Brazilians with depression. In a cross-sectional, exploratory, and analytical study of a quantitative nature, the mental profile of elderly individuals subjected to social isolation during the COVID-19 pandemic period was used. A total of 450 participants was divided into normal and depressive groups, and a form covering sociodemographic data, opinions/perceptions about the pandemic, and a Reduced Geriatric Depression Scale was used to assess participants' mental health. To assess the statistical significance between the variables, chi-square test was applied, considering the p-value <0.05. The effect size was analyzed to identify the magnitude of the difference between groups. To identify the most important characteristics to define the groups Multilayer Perceptron algorithm were applied. We found that elderly people with a depressive profile are (in Multilayer Perceptron rank order) (1) showing signs of anxiety during the COVID-19 pandemic, (2) of low education, (3) being divorced, (4) having more than one mental disorder, (5) reading, watching, or listening to information about COVID-19, and (6) being previously diagnosed with depression. In conclusion, elderly Brazilians in social isolation tend to develop depressive disorders during quarantine. Thus, we can consider that the pandemic requires effective and safe gerontological care and monitoring, especially with regard to mental health.