Youngwon Kim1,2, Ryan D Burns3, Duck-Chul Lee4, Gregory J Welk4. 1. School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Pokfulam, Hong Kong. youngwon.kim@hku.hk. 2. MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, Cambridgeshire, UK. youngwon.kim@hku.hk. 3. Department of Health, Kinesiology, and Recreation, University of Utah, Salt Lake City, UT, 84112, USA. 4. Department of Kinesiology, Iowa State University, Ames, IA, 50011-4008, USA.
Abstract
BACKGROUND/ OBJECTIVES: Evidence on the associations between lifestyle movement behaviors and obesity has been established without taking into account the time-constrained nature of categorized, time-based lifestyle behaviors. We examined the associations of sleep, sedentary behavior (SED), light-intensity physical activity (LPA), and moderate-to-vigorous PA (MVPA) with body mass index (BMI) using Compositional Data Analysis (CoDA), and compared the associations between a report-based method (24-h Physical Activity Recall; 24PAR) and a monitor-based method (SenseWear Armband; SWA). SUBJECTS/ METHODS: Replicate data from a representative sample of 1247 adults from the Physical Activity Measurement Survey (PAMS) were used in the study. Participants completed activity monitoring on two randomly selected days, each of which required wearing a SWA for a full day, and then completing a telephone-administered 24PAR the following day. Relationships among behavioral compositional parts and BMI were analyzed using CoDA via multiple linear regression models with both 24PAR and SWA data. RESULTS: Using 24PAR, time spent in sleep (γ = -3.58, p = 0.011), SED (γ = 3.70, p = 0.002), and MVPA (γ = -0.53, p = 0.018) was associated with BMI. Using SWA, time spent in sleep (γ = -5.10, p < 0.001), SED (γ = 8.93, p < 0.001), LPA (γ = -3.12, p < 0.001), and MVPA (γ = -1.43, p < 0.001) was associated with BMI. The SWA models explained more variance in BMI (R2 = 0.28) compared with the 24PAR models (R2 = 0.07). The compositional isotemporal substitution models revealed reductions in BMI when replacing SED by MVPA, LPA (not with 24PAR) or sleep for both 24PAR and SWA, but the effect estimates were larger with SWA. CONCLUSIONS: Favorable levels of relative time spent in lifestyle movement behaviors were, in general, associated with decreased BMI. The observed associations were stronger using the monitor-based SWA method compared with the report-based 24PAR method.
BACKGROUND/ OBJECTIVES: Evidence on the associations between lifestyle movement behaviors and obesity has been established without taking into account the time-constrained nature of categorized, time-based lifestyle behaviors. We examined the associations of sleep, sedentary behavior (SED), light-intensity physical activity (LPA), and moderate-to-vigorous PA (MVPA) with body mass index (BMI) using Compositional Data Analysis (CoDA), and compared the associations between a report-based method (24-h Physical Activity Recall; 24PAR) and a monitor-based method (SenseWear Armband; SWA). SUBJECTS/ METHODS: Replicate data from a representative sample of 1247 adults from the Physical Activity Measurement Survey (PAMS) were used in the study. Participants completed activity monitoring on two randomly selected days, each of which required wearing a SWA for a full day, and then completing a telephone-administered 24PAR the following day. Relationships among behavioral compositional parts and BMI were analyzed using CoDA via multiple linear regression models with both 24PAR and SWA data. RESULTS: Using 24PAR, time spent in sleep (γ = -3.58, p = 0.011), SED (γ = 3.70, p = 0.002), and MVPA (γ = -0.53, p = 0.018) was associated with BMI. Using SWA, time spent in sleep (γ = -5.10, p < 0.001), SED (γ = 8.93, p < 0.001), LPA (γ = -3.12, p < 0.001), and MVPA (γ = -1.43, p < 0.001) was associated with BMI. The SWA models explained more variance in BMI (R2 = 0.28) compared with the 24PAR models (R2 = 0.07). The compositional isotemporal substitution models revealed reductions in BMI when replacing SED by MVPA, LPA (not with 24PAR) or sleep for both 24PAR and SWA, but the effect estimates were larger with SWA. CONCLUSIONS: Favorable levels of relative time spent in lifestyle movement behaviors were, in general, associated with decreased BMI. The observed associations were stronger using the monitor-based SWA method compared with the report-based 24PAR method.
Authors: Charles E Matthews; Kong Y Chen; Patty S Freedson; Maciej S Buchowski; Bettina M Beech; Russell R Pate; Richard P Troiano Journal: Am J Epidemiol Date: 2008-02-25 Impact factor: 4.897
Authors: Aviroop Biswas; Paul I Oh; Guy E Faulkner; Ravi R Bajaj; Michael A Silver; Marc S Mitchell; David A Alter Journal: Ann Intern Med Date: 2015-01-20 Impact factor: 25.391
Authors: Catrine Tudor-Locke; Meghan M Brashear; William D Johnson; Peter T Katzmarzyk Journal: Int J Behav Nutr Phys Act Date: 2010-08-03 Impact factor: 6.457
Authors: Youfa Wang; May A Beydoun; Lan Liang; Benjamin Caballero; Shiriki K Kumanyika Journal: Obesity (Silver Spring) Date: 2008-07-24 Impact factor: 5.002
Authors: Bethany Barone Gibbs; Andrea L Hergenroeder; Peter T Katzmarzyk; I-Min Lee; John M Jakicic Journal: Med Sci Sports Exerc Date: 2015-06 Impact factor: 5.411
Authors: Michael Pratt; Olga L Sarmiento; Felipe Montes; David Ogilvie; Bess H Marcus; Lilian G Perez; Ross C Brownson Journal: Lancet Date: 2012-07-21 Impact factor: 79.321
Authors: Michael A Grandner; Elizabeth A Schopfer; Megan Sands-Lincoln; Nicholas Jackson; Atul Malhotra Journal: Obesity (Silver Spring) Date: 2015-11-02 Impact factor: 5.002
Authors: Ryan D Burns; Yang Bai; Christopher D Pfledderer; Timothy A Brusseau; Wonwoo Byun Journal: Int J Environ Res Public Health Date: 2020-09-20 Impact factor: 3.390
Authors: Laura Gallardo-Alfaro; Maria Del Mar Bibiloni; Emma Argelich; Escarlata Angullo-Martinez; Cristina Bouzas; Josep A Tur Journal: J Clin Med Date: 2021-12-13 Impact factor: 4.241