MULTIVARIATE ASSOCIATION OF MENTAL HEALTH WITH HABITUAL, MOVEMENT, AND SEDENTARY BEHAVIORS IN AN ACADEMIC COMMUNITY

Abstract

This study aimed to assess mental health (MS) by investigating feelings of isolation, sadness-depression, and anxiety-nervousness, and associating them with sociodemographic and behavioral factors, health status, and body mass index in a university community. This is an observational and cross-sectional study, with a sample composed of 1,655 volunteers, of both sexes, aged between 17 and 72 years, belonging to different segments of the academic community of a public institution in the interior of Brazil. An adapted version of the "ConVid: Behavior Survey" questionnaires and the short version of the "International Physical Activity Questionnaire (IPAQ)" were used, adopting a significance level of α = 5% for statistical analyses. The grouping of feelings was performed using the Two Step Cluster method, and the resulting classification was analyzed by multinomial regression and Multiple Correspondence Analysis. The cluster  model generated seven adjusted classes and, based on this, three mental health categories were defined: "worst MS", "moderate MS" and "best MS". The regression showed that age up to 39 years, female gender, reduction or maintenance of income during the pandemic, receipt of Emergency Aid, diagnosis of chronic non-communicable diseases, experience of severe cases or deaths of family members/friends, moderate or intense difficulties in the work or study routine, poor sleep quality, not reaching the recommendations for moderate and vigorous physical activity,  daily screen use for ≥ 4 hours and body mass index classified as eutrophic were associated with higher odds of worse MS classification. It is concluded, based on the clusters and multivariate analyses, that changes in behaviors, lifestyle, and socioeconomic context caused by social isolation resulting from COVID-19 significantly increased the chances of classifying the university population evaluated as the worst MS.