Joint associations of physical activity and sedentary behaviors with body mass index: results from a time use survey of US adults

Obesity risk is negatively associated with physical activity and positively associated with time spent in sedentary behaviors. Yet, it is not known how different combinations of sedentary and active behavior are associated with body mass index (BMI). This study examined the interaction between time...

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Bibliographic Details
Published in:International Journal of Obesity 2009-12, Vol.33 (12), p.1427-1436
Main Authors: DUNTON, G. F, BERRIGAN, D, BALLARD-BARBASH, R, GRAUBARD, B, ATIENZA, A. A
Format: Article
Language:English
Subjects:
Adult
Adults
Behavior
Biological and medical sciences
Body Mass Index
Cancer
Care and treatment
Cross-Sectional Studies
Demographic aspects
Epidemiology
Exercise
Female
Health aspects
Health Behavior
Health care
Health Surveys
Humans
Interviews
Interviews as Topic
Leisure
Leisure Activities
Male
Measurement
Medical sciences
Metabolic diseases
Motor Activity - physiology
Obesity
Obesity - epidemiology
Obesity - physiopathology
Physiological aspects
Prevention
Risk factors
Sedentary Lifestyle
Surveys
Surveys and Questionnaires
Time use
United States - epidemiology
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Summary:Obesity risk is negatively associated with physical activity and positively associated with time spent in sedentary behaviors. Yet, it is not known how different combinations of sedentary and active behavior are associated with body mass index (BMI). This study examined the interaction between time spent in physical activity and sedentary behavior on BMI in US adults. Cross-sectional, data from the 2006 American Time Use Survey. 10 984 non-underweight adults (aged 21 + years). A phone interview assessed all activities performed in the past 24 h, height, weight, health status, and other sociodemographic characteristics. Time spent in (1) moderate-to-vigorous leisure-time physical activity (MVPA), (2) active transportation (walking, biking), (3) sedentary leisure activities (TV/movie watching, computer use, playing games, reading), and (4) sedentary transportation (motorized vehicles) was determined from activity coding. BMI was calculated. After adjusting for age, gender, education level, race/ethnicity, and health status, sample-weighted linear regressions found significant interactions for leisure MVPA x TV/movies, leisure MVPA x playing games, active transportation x sedentary transportation, and active transportation x reading (Ps
ISSN:0307-0565
1476-5497
DOI:10.1038/ijo.2009.174