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The main objective of this paper is to employ some multifactorial data mining techniques for studying the direct and indirect effects of the physical activity intensity on persons' health-related well-being. The availability of such a data-driven modeling and simulation interface enables analysts and decision makers to boost their decision by better understanding the types and levels of relationships between the main factors promoting the well-being of individuals. The data mining investigation is conducted at the CHU Gabriel Montpied (Clermont-Ferrand, France) on a population of employees, composed of medical and nonmedical staff. An observation-like study is conducted with the main aim of assessing direct and indirect effects of the physical activity intensity on the population's health. This is especially performed by examining the significance of associations between physical activity indices and a set of their medical records. One of the main models resulting from data mining in this paper links cardiovascular risks to a set of exogenous variables including work and sport activity indices. The empirical results are consistent with many recent findings emphasizing the role of increasing high and intermediate levels of physical activity among health public-sector employees to effectively fight some diabetic and cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Background: Despite the potential detrimental consequences for individuals' health and discrimination from covid-19 symptoms, the outcomes have received little attention. This study examines the relationships between having personally experienced discrimination based on the symptoms of covid-19 (during the first wave of the pandemic), mental health, and emotional responses (anger and sadness). It was predicted that covid-19 discrimination would be positively related to poor mental health and that this relationship would be mediated by the emotions of anger and sadness., Methods: The study was conducted using an online questionnaire from January to June 2020 (the Covistress network; including 44 countries). Participants were extracted from the COVISTRESS database (Ntotal = 280) with about a half declaring having been discriminated due to covid-19 symptoms (N = 135). Discriminated participants were compared to non-discriminated participants using ANOVA. A mediation analysis was conducted to examine the indirect effect of emotional responses and the relationships between perceived discrimination and self-reported mental health., Results: The results indicated that individuals who experienced discrimination based on the symptoms of covid-19 had poorer mental health and experienced more anger and sadness. The relationship between covid-19 personal discrimination and mental health disappeared when the emotions of anger and sadness were statistically controlled for. The indirect effects for both anger and sadness were statistically significant., Discussion: This study suggests that the covid-19 pandemic may have generated discriminatory behaviors toward those suspected of having symptoms and that this is related to poorer mental health via anger and sadness., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Dambrun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)