logo
ResearchBunny Logo
Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis

Health and Fitness

Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis

Y. Kim, R. D. Burns, et al.

This groundbreaking study by Youngwon Kim, Ryan D. Burns, Duck-chul Lee, and Gregory J. Welk explores how sleep, sedentary behavior, and physical activity are linked to body mass index (BMI). Utilizing advanced Compositional Data Analysis, the research highlights the stronger associations found using monitor-based methods. Discover how shifting your routine could lead to significant BMI reductions!

00:00
00:00
~3 min • Beginner • English
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.
Publisher
International Journal of Obesity
Published On
Jul 13, 2020
Authors
Youngwon Kim, Ryan D. Burns, Duck-chul Lee, Gregory J. Welk
Tags
sleep
sedentary behavior
physical activity
body mass index
Compositional Data Analysis
monitor-based method
Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny