Jonathan A Mitchell1, Matteo Bottai, Yikyung Park, Simon J Marshall, Steven C Moore, Charles E Matthews. 1. 1Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; 2Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, SWEDEN; 3Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD; and 4Department of Family and Preventive Medicine, Division of Behavioral Medicine, University of California, San Diego, San Diego, CA.
Abstract
PURPOSE: We aimed to determine whether baseline sedentary behavior was associated with changes in body mass index (BMI) over 9 yr. METHODS: Participants were enrolled into the National Institutes of Health American Association of Retired Persons (NIH-AARP) Diet and Health study in 1995-1996 (median age, 63 yr), and BMI was reported at baseline and 9 yr later (n = 158,436). Sitting time (<3 (referent), 3-4, 5-6, 7-8, or ≥9 h·d), television viewing (none, <1, 1-2, 3-4, 5-6, 7-8, or ≥9 h·d), and the covariates (age, sex, race, education, smoking, moderate-to-vigorous physical activity, caloric intake, and sleep duration) were reported at baseline. We used longitudinal quantile regression to model changes at the 10th, 25th, 50th, 75th, and 90th BMI percentiles. RESULTS: More sitting at baseline was associated with additional increases in BMI over time, and the association was stronger at the upper BMI percentiles (e.g., <3 (referent) vs 5-6 h·d of sitting additional increases: 50th percentile = 0.41 kg·m and 95% confidence interval (CI) = 0.34-0.48; 90th percentile = 0.85 kg·m and 95% CI = 0.72-0.98). Similar associations were observed between more television viewing at baseline and additional increases in BMI over time (e.g., no television (referent) vs 3-4 h·d of television: 50th percentile = 1.96 kg·m and 95% CI = 1.77-2.15; 90th percentile = 2.11 kg·m and 95% CI = 1.49-2.73). CONCLUSIONS: Reducing sedentary behavior could help prevent an increase in BMI in adulthood especially at the upper percentiles of the BMI distribution and thereby reduce the prevalence of obesity.
PURPOSE: We aimed to determine whether baseline sedentary behavior was associated with changes in body mass index (BMI) over 9 yr. METHODS:Participants were enrolled into the National Institutes of Health American Association of Retired Persons (NIH-AARP) Diet and Health study in 1995-1996 (median age, 63 yr), and BMI was reported at baseline and 9 yr later (n = 158,436). Sitting time (<3 (referent), 3-4, 5-6, 7-8, or ≥9 h·d), television viewing (none, <1, 1-2, 3-4, 5-6, 7-8, or ≥9 h·d), and the covariates (age, sex, race, education, smoking, moderate-to-vigorous physical activity, caloric intake, and sleep duration) were reported at baseline. We used longitudinal quantile regression to model changes at the 10th, 25th, 50th, 75th, and 90th BMI percentiles. RESULTS: More sitting at baseline was associated with additional increases in BMI over time, and the association was stronger at the upper BMI percentiles (e.g., <3 (referent) vs 5-6 h·d of sitting additional increases: 50th percentile = 0.41 kg·m and 95% confidence interval (CI) = 0.34-0.48; 90th percentile = 0.85 kg·m and 95% CI = 0.72-0.98). Similar associations were observed between more television viewing at baseline and additional increases in BMI over time (e.g., no television (referent) vs 3-4 h·d of television: 50th percentile = 1.96 kg·m and 95% CI = 1.77-2.15; 90th percentile = 2.11 kg·m and 95% CI = 1.49-2.73). CONCLUSIONS: Reducing sedentary behavior could help prevent an increase in BMI in adulthood especially at the upper percentiles of the BMI distribution and thereby reduce the prevalence of obesity.
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