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https://www.arca.fiocruz.br/handle/icict/57767
CORRELATES OF SCREEN-BASED BEHAVIORS AMONG ADULTS FROM THE 2019 BRAZILIAN NATIONAL HEALTH SURVEY
Author
Affilliation
Federal University of Sergipe. Department of Physical Education. Sergipe, SE, Brasil.
Bradford Teaching Hospitals NHS Foundation Trust. Bradford Institute for Health Research, Bradford, UK.
Londrina State University. Graduation Program in Health Sciences. Londrina, PR, Brasil
University of Brasília. Graduation Program in Physical Education. Brasília, DF, Brasil.
Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.
University of São Paulo. Center for Epidemiological Research in Nutrition and Health. Department of Nutrition. School of Public Health. São Paulo, SP, Brasil.
Bradford Teaching Hospitals NHS Foundation Trust. Bradford Institute for Health Research, Bradford, UK.
Londrina State University. Graduation Program in Health Sciences. Londrina, PR, Brasil
University of Brasília. Graduation Program in Physical Education. Brasília, DF, Brasil.
Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.
University of São Paulo. Center for Epidemiological Research in Nutrition and Health. Department of Nutrition. School of Public Health. São Paulo, SP, Brasil.
Abstract
We aimed to investigate correlates of TV viewing and other types of screen-based behaviors in a nationally representative sample of Brazilian adults. In the 2019 Brazilian National Health Survey (including 88,509 adults), TV viewing time
and other types of screen behaviors (computer, tablet, and cellphone use) were self-reported and diferent geographical, sociodemographic, behavioral, and health status factors were investigated as potential correlates. Multinomial
logistic regression models were used for the main analyses. Living in capital cities, urban areas, being unemployed,
high consumption of soft drinks, obesity, and elevated depressive symptoms were each associated with more TV
viewing and more time using other types of screens. There were diferential associations between TV viewing and
the use of other types of screen across age and socioeconomic variables. For instance, younger adults have a more
diverse portfolio of screen time than older adults. To conclude, levels of screen-based behaviors vary by geographical,
sociodemographic, behavioral, and health status characteristics. Interventions should focus on high-risk population
groups and may beneft from targeting specifc sedentary behaviors of interest.
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