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Background: Physical inactivity in each domain (leisure, work, commuting, and household) is not completely independent. This study aimed to describe the clustering of physical inactivity in different domains and its association with sociodemographic factors among Brazilian industrial workers., Methods: This was a cross-sectional, population-based study using data from 23 Brazilian states and the Federal District collected via questionnaires between 2006 and 2008. Physical inactivity in each domain was defined as nonparticipation in specific physical activities. Clustering of physical inactivity was identified using the ratio of the observed (O) and expected (E) percentages of each combination. Multinomial logistic regression was used to identify sociodemographic factors with the outcome., Results: Among the 44,477 interviewees, most combinations exceeded expectations, particularly the clustering of physical inactivity in all domains among men (O/E = 1.37; 95% CI: 1.30; 1.44) and women (O/E = 1.47; 95% CI: 1.36; 1.60). Physical inactivity in 2 or more domains was observed more frequently in women, older age groups, individuals living without a partner, and those with higher education and income levels., Conclusions: Physical inactivity tends to be observed in clusters regardless of gender. Women and workers with higher income levels were the main factors associated with to be physically inactive in 2 or more domains.

Background Economic and technological improvements can help increase screen time use among adolescents, but evidence in developing countries is scarce. The aim of this study was to examine changes in TV watching and computer/video game use patterns on week and weekend days after a decade (2001 and 2011), among students in Santa Catarina, southern Brazil. Methods A comparative analysis of two cross-sectional surveys that included 5 028 and 6 529 students in 2001 and 2011, respectively, aged 15–19 years. The screen time use indicators were self-reported. 95% Confidence intervals were used to compare the prevalence rates. All analyses were separated by gender. Results After a decade, there was a significant increase in computer/video game use. Inversely, a significant reduction in TV watching was observed, with a similar magnitude to the change in computer/video game use. The worst trends were identified on weekend days. Conclusions The decrease in TV watching after a decade appears to be compensated by the increase in computer/video game use, both in boys and girls. Interventions are needed to reduce the negative impact of technological improvements in the lifestyles of young people, especially on weekend days. [ABSTRACT FROM AUTHOR]