Introduction: The excessive sitting time involved in activities of low energy expenditure (sedentary behavior) can contribute to the development of chronic diseases. Assessing factors related to this behavior in a population is important to identify its most vulnerable segments.
Objective: To describe sitting time distribution in the adult population of São Paulo City according to sociodemographic and environmental characteristics and health conditions.
Methods: This is a cross-sectional study involving 2,512 individuals, aged 20 to 65 years, who participated in the Health Survey in the City of São Paulo (Inquérito de Saúde no Município de São Paulo - ISA-Capital) 2015. Data relating to sitting time were collected using the International Physical Activity Questionnaire (IPAQ), initially analyzed continuously, and, afterward, dichotomized by the median to analyze categorical variables.
Results: The total sitting time median in the sample was 180 min/day. The variables that, after adjustments, remained related to sedentary behavior were: schooling (prevalence ratio - PR = 1.41; 95% confidence interval - 95%CI 1.35 - 1.48); marital status (PR = 1.05; 95%CI 1.02 - 1.08); neighborhood safety (PR = 0.96; 95%CI 0.93 - 0.99); age (PR = 0.91; 95%CI 0.87 - 0.95); income (PR = 1.07; 95%CI 1.00 - 1.15); self-rated health (PR = 1.03; 95%CI 1.01 - 1.07), and gender (PR = 0.96; 95%CI 0.94 - 0.99).
Conclusion: The most vulnerable groups to sedentary behavior in this population are: younger males, with higher schooling and income, who live in neighborhoods considered safe, unmarried, and with negative self-rated health.
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http://dx.doi.org/10.1590/1980-549720190050 | DOI Listing |
Physical activity (PA), including sedentary behavior, is associated with many diseases, including Alzheimer's disease and all-cause dementia. However, the specific biological mechanisms through which PA protects against disease are not entirely understood. To address this knowledge gap, we first assessed the conventional observational associations of three self-reported and three device-based PA measures with circulating levels of 2,911 plasma proteins measured in the UK Biobank (n =39,160) and assessed functional enrichment of identified proteins.
View Article and Find Full Text PDFBMC Public Health
January 2025
Amsterdam UMC location Vrije Universiteit Amsterdam, Public and Occupational Health, De Boelelaan 1117, Amsterdam, the Netherlands.
Background: Developing interventions along with the population of interest using systems thinking is a promising method to address the underlying system dynamics of overweight. The purpose of this study is twofold: to gain insight into the perspectives of adolescents regarding: (1) the system dynamics of energy balance-related behaviours (EBRBs) (physical activity, screen use, sleep behaviour and dietary behaviour); and (2) underlying mechanisms and overarching drivers of unhealthy EBRBs.
Methods: We conducted Participatory Action Research (PAR) to map the system dynamics of EBRBs together with adolescents aged 10-14 years old living in a lower socioeconomic, ethnically diverse neighbourhood in Amsterdam East, the Netherlands.
Objectives: This study aims to estimate the impact of the co-occurrence of behavioural risk factors on mortality in the Spanish adult population.
Design: Population-based cohort study based on data from the 2011-2012 Spanish National Health Survey and the 2014 European Health Survey (n=35 053 participants ≥15 years of age) both linked to mortality data as of December 2022. Risk factors included tobacco use, high-risk alcohol consumption, low adherence to the Mediterranean diet, leisure time sedentary lifestyle and body mass index outside the 18.
Nutrients
January 2025
Department of Community Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania.
Background/objectives: This study aimed to investigate the lifestyle and the behavioral factors that influence the nutritional status of adolescents from Transylvania, Romania.
Methods: The Global School-Based Student Health Survey (GSHS) was used to collect data from 900 adolescents between 11 and 18 years old from the Transylvania region, Romania. This study assessed nutritional status by calculating BMI indicators adjusted to Z-Score, cut-off points according to the World Health Organization (WHO), using self-reported weight and height; perceived health status; food vulnerability; physical activity; addictive behaviors (cigarette, alcohol and drug consumption); number of hours spent in front of the computer/phone; hand and oral hygiene; sitting time/day; and sleep.
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