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Associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model

BACKGROUND: Physical activity was believed to be associated with reduced aging among adults, while the competing nature of the physical activity and sedentary behavior has mainly been neglected in studies. We aimed to estimate the association of sleeping, sedentary behavior, and physical activity wi...

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Autores principales: Han, Mengying, Fang, Jiaxin, Zhang, Yixin, Song, Xingxu, Jin, Lina, Ma, Yanan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035275/
https://www.ncbi.nlm.nih.gov/pubmed/36959562
http://dx.doi.org/10.1186/s12877-023-03874-6
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author Han, Mengying
Fang, Jiaxin
Zhang, Yixin
Song, Xingxu
Jin, Lina
Ma, Yanan
author_facet Han, Mengying
Fang, Jiaxin
Zhang, Yixin
Song, Xingxu
Jin, Lina
Ma, Yanan
author_sort Han, Mengying
collection PubMed
description BACKGROUND: Physical activity was believed to be associated with reduced aging among adults, while the competing nature of the physical activity and sedentary behavior has mainly been neglected in studies. We aimed to estimate the association of sleeping, sedentary behavior, and physical activity with aging among adults, considering the competing nature between variables of activity status. METHODS: A total of 5288 participants who were 20 years or older from the National Health and Nutrition Examination Survey were involved. The questionnaire was used to collect data regarding sociodemographics (age, sex, ethnicity/race, and education), and lifestyle behaviors (smoking, drinking). The Global Physical Activity Questionnaire was used to measure self-reported time for sedentary behavior, walking/bicycling, and moderate-to-vigorous physical activity (MVPA). The sleeping duration was obtained via interview. Phenotypic age acceleration (PhenoAgeAccel) was calculated as an aging index using nine chemistry biomarkers. Isotemporal substitution models using multivariable linear regression to examine the associations of sleeping, sedentary behavior, and physical activity with PhenoAgeAccel, stratified by MVPA (< 150 min/week, ≥ 150 min/week). RESULTS: Thirty minutes per day spent on sedentary behavior was positively associated with PhenoAgeAccel (β = 0.07, 95% CI: 0.04, 0.11), and 30 min/day spent on leisure-time MVPA was adversely associated with PhenoAgeAccel (β =  − 0.55, 95% CI: − 0.73, − 0.38). Replacing 30 min/day sedentary behaviors with 30 min/day of MVPA (β = -3.98, 95% CI: -6.22, -1.74) or 30 min/day of walking/bicycling (β = -0.89, 95% CI: -1.10, -0.68) was adversely associated with PhenoAgeAccel. Substituting 30 min/day of walking/bicycling for 30 min/day of leisure-time MVPA was positively associated with PhenoAgeAccel (β = 3.09, 95% CI: 0.93, 5.25). CONCLUSION: Sedentary behavior was positively associated with aging. Replacing sedentary behaviors with walking/bicycling or MVPA was adversely associated with aging among adults. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-023-03874-6.
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spelling pubmed-100352752023-03-24 Associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model Han, Mengying Fang, Jiaxin Zhang, Yixin Song, Xingxu Jin, Lina Ma, Yanan BMC Geriatr Research BACKGROUND: Physical activity was believed to be associated with reduced aging among adults, while the competing nature of the physical activity and sedentary behavior has mainly been neglected in studies. We aimed to estimate the association of sleeping, sedentary behavior, and physical activity with aging among adults, considering the competing nature between variables of activity status. METHODS: A total of 5288 participants who were 20 years or older from the National Health and Nutrition Examination Survey were involved. The questionnaire was used to collect data regarding sociodemographics (age, sex, ethnicity/race, and education), and lifestyle behaviors (smoking, drinking). The Global Physical Activity Questionnaire was used to measure self-reported time for sedentary behavior, walking/bicycling, and moderate-to-vigorous physical activity (MVPA). The sleeping duration was obtained via interview. Phenotypic age acceleration (PhenoAgeAccel) was calculated as an aging index using nine chemistry biomarkers. Isotemporal substitution models using multivariable linear regression to examine the associations of sleeping, sedentary behavior, and physical activity with PhenoAgeAccel, stratified by MVPA (< 150 min/week, ≥ 150 min/week). RESULTS: Thirty minutes per day spent on sedentary behavior was positively associated with PhenoAgeAccel (β = 0.07, 95% CI: 0.04, 0.11), and 30 min/day spent on leisure-time MVPA was adversely associated with PhenoAgeAccel (β =  − 0.55, 95% CI: − 0.73, − 0.38). Replacing 30 min/day sedentary behaviors with 30 min/day of MVPA (β = -3.98, 95% CI: -6.22, -1.74) or 30 min/day of walking/bicycling (β = -0.89, 95% CI: -1.10, -0.68) was adversely associated with PhenoAgeAccel. Substituting 30 min/day of walking/bicycling for 30 min/day of leisure-time MVPA was positively associated with PhenoAgeAccel (β = 3.09, 95% CI: 0.93, 5.25). CONCLUSION: Sedentary behavior was positively associated with aging. Replacing sedentary behaviors with walking/bicycling or MVPA was adversely associated with aging among adults. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-023-03874-6. BioMed Central 2023-03-23 /pmc/articles/PMC10035275/ /pubmed/36959562 http://dx.doi.org/10.1186/s12877-023-03874-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Han, Mengying
Fang, Jiaxin
Zhang, Yixin
Song, Xingxu
Jin, Lina
Ma, Yanan
Associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model
title Associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model
title_full Associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model
title_fullStr Associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model
title_full_unstemmed Associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model
title_short Associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model
title_sort associations of sleeping, sedentary and physical activity with phenotypic age acceleration: a cross-sectional isotemporal substitution model
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035275/
https://www.ncbi.nlm.nih.gov/pubmed/36959562
http://dx.doi.org/10.1186/s12877-023-03874-6
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