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Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis
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-int...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7752757/ https://www.ncbi.nlm.nih.gov/pubmed/32661291 http://dx.doi.org/10.1038/s41366-020-0638-z |
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author | Kim, Youngwon Burns, Ryan D. Lee, Duck-chul Welk, Gregory J. |
author_facet | Kim, Youngwon Burns, Ryan D. Lee, Duck-chul Welk, Gregory J. |
author_sort | Kim, Youngwon |
collection | PubMed |
description | 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 (R(2) = 0.28) compared with the 24PAR models (R(2) = 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. |
format | Online Article Text |
id | pubmed-7752757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77527572020-12-29 Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis Kim, Youngwon Burns, Ryan D. Lee, Duck-chul Welk, Gregory J. Int J Obes (Lond) Article 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 (R(2) = 0.28) compared with the 24PAR models (R(2) = 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. Nature Publishing Group UK 2020-07-13 2021 /pmc/articles/PMC7752757/ /pubmed/32661291 http://dx.doi.org/10.1038/s41366-020-0638-z Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Kim, Youngwon Burns, Ryan D. Lee, Duck-chul Welk, Gregory J. Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis |
title | Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis |
title_full | Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis |
title_fullStr | Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis |
title_full_unstemmed | Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis |
title_short | Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis |
title_sort | associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using compositional data analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7752757/ https://www.ncbi.nlm.nih.gov/pubmed/32661291 http://dx.doi.org/10.1038/s41366-020-0638-z |
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