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U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011–2014)

BACKGROUND: Suboptimal rest-activity patterns in adolescence are associated with worse health outcomes in adulthood. Understanding sociodemographic factors associated with rest-activity rhythms may help identify subgroups who may benefit from interventions. This study aimed to investigate the associ...

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Autores principales: Yeung, Chris Ho Ching, Lu, Jiachen, Soltero, Erica G., Bauer, Cici, Xiao, Qian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571346/
https://www.ncbi.nlm.nih.gov/pubmed/37833691
http://dx.doi.org/10.1186/s12966-023-01520-3
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author Yeung, Chris Ho Ching
Lu, Jiachen
Soltero, Erica G.
Bauer, Cici
Xiao, Qian
author_facet Yeung, Chris Ho Ching
Lu, Jiachen
Soltero, Erica G.
Bauer, Cici
Xiao, Qian
author_sort Yeung, Chris Ho Ching
collection PubMed
description BACKGROUND: Suboptimal rest-activity patterns in adolescence are associated with worse health outcomes in adulthood. Understanding sociodemographic factors associated with rest-activity rhythms may help identify subgroups who may benefit from interventions. This study aimed to investigate the association of rest-activity rhythm with demographic and socioeconomic characteristics in adolescents. METHODS: Using cross-sectional data from the nationally representative National Health and Nutrition Examination Survey (NHANES) 2011–2014 adolescents (N = 1814), this study derived rest-activity profiles from 7-day 24-hour accelerometer data using functional principal component analysis. Multiple linear regression was used to assess the association between participant characteristics and rest-activity profiles. Weekday and weekend specific analyses were performed in addition to the overall analysis. RESULTS: Four rest-activity rhythm profiles were identified, which explained a total of 82.7% of variance in the study sample, including (1) High amplitude profile; (2) Early activity window profile; (3) Early activity peak profile; and (4) Prolonged activity/reduced rest window profile. The rest-activity profiles were associated with subgroups of age, sex, race/ethnicity, and household income. On average, older age was associated with a lower value for the high amplitude and early activity window profiles, but a higher value for the early activity peak and prolonged activity/reduced rest window profiles. Compared to boys, girls had a higher value for the prolonged activity/reduced rest window profiles. When compared to Non-Hispanic White adolescents, Asian showed a lower value for the high amplitude profile, Mexican American group showed a higher value for the early activity window profile, and the Non-Hispanic Black group showed a higher value for the prolonged activity/reduced rest window profiles. Adolescents reported the lowest household income had the lowest average value for the early activity window profile. CONCLUSIONS: This study characterized main rest-activity profiles among the US adolescents, and demonstrated that demographic and socioeconomic status factors may shape rest-activity behaviors in this population. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12966-023-01520-3.
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spelling pubmed-105713462023-10-14 U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011–2014) Yeung, Chris Ho Ching Lu, Jiachen Soltero, Erica G. Bauer, Cici Xiao, Qian Int J Behav Nutr Phys Act Research BACKGROUND: Suboptimal rest-activity patterns in adolescence are associated with worse health outcomes in adulthood. Understanding sociodemographic factors associated with rest-activity rhythms may help identify subgroups who may benefit from interventions. This study aimed to investigate the association of rest-activity rhythm with demographic and socioeconomic characteristics in adolescents. METHODS: Using cross-sectional data from the nationally representative National Health and Nutrition Examination Survey (NHANES) 2011–2014 adolescents (N = 1814), this study derived rest-activity profiles from 7-day 24-hour accelerometer data using functional principal component analysis. Multiple linear regression was used to assess the association between participant characteristics and rest-activity profiles. Weekday and weekend specific analyses were performed in addition to the overall analysis. RESULTS: Four rest-activity rhythm profiles were identified, which explained a total of 82.7% of variance in the study sample, including (1) High amplitude profile; (2) Early activity window profile; (3) Early activity peak profile; and (4) Prolonged activity/reduced rest window profile. The rest-activity profiles were associated with subgroups of age, sex, race/ethnicity, and household income. On average, older age was associated with a lower value for the high amplitude and early activity window profiles, but a higher value for the early activity peak and prolonged activity/reduced rest window profiles. Compared to boys, girls had a higher value for the prolonged activity/reduced rest window profiles. When compared to Non-Hispanic White adolescents, Asian showed a lower value for the high amplitude profile, Mexican American group showed a higher value for the early activity window profile, and the Non-Hispanic Black group showed a higher value for the prolonged activity/reduced rest window profiles. Adolescents reported the lowest household income had the lowest average value for the early activity window profile. CONCLUSIONS: This study characterized main rest-activity profiles among the US adolescents, and demonstrated that demographic and socioeconomic status factors may shape rest-activity behaviors in this population. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12966-023-01520-3. BioMed Central 2023-10-13 /pmc/articles/PMC10571346/ /pubmed/37833691 http://dx.doi.org/10.1186/s12966-023-01520-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 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
Yeung, Chris Ho Ching
Lu, Jiachen
Soltero, Erica G.
Bauer, Cici
Xiao, Qian
U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011–2014)
title U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011–2014)
title_full U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011–2014)
title_fullStr U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011–2014)
title_full_unstemmed U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011–2014)
title_short U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011–2014)
title_sort u.s. adolescent rest-activity patterns: insights from functional principal component analysis (nhanes 2011–2014)
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571346/
https://www.ncbi.nlm.nih.gov/pubmed/37833691
http://dx.doi.org/10.1186/s12966-023-01520-3
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