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Cluster Analysis of Sleep Time and Adolescent Health Risk Behaviors
Adolescents are prone to multiple health risk behaviors. These might lead to insufficient sleep, which is inconducive to adolescent growth. Therefore, this study explored the impact of a cluster of adolescent health risk behaviors on sleep time, providing a reference for designing relevant intervent...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9909054/ https://www.ncbi.nlm.nih.gov/pubmed/36748745 http://dx.doi.org/10.1177/00469580231153272 |
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author | Yu, Junjie Liu, Yang Liao, Liping Yan, Jie Wang, Hong |
author_facet | Yu, Junjie Liu, Yang Liao, Liping Yan, Jie Wang, Hong |
author_sort | Yu, Junjie |
collection | PubMed |
description | Adolescents are prone to multiple health risk behaviors. These might lead to insufficient sleep, which is inconducive to adolescent growth. Therefore, this study explored the impact of a cluster of adolescent health risk behaviors on sleep time, providing a reference for designing relevant intervention measures. From November to December 2019, a stratified cluster sampling method was used to sample middle and high schools in 4 functional districts of Chongqing, China. A total of 8546 participants were selected for a questionnaire survey. Two-step clustering helped identify the health risk behavior clusters. Multivariate logistic regression models helped examine the association between the different clusters and sleep time. The rate of insufficient sleep was 65.8%. Three types of clusters were identified, namely (1) high-risk (poor) cluster (17.3%), (2) low physical activity (medium) cluster (55.1%), and (3) low-risk (good) cluster (27.6%). The high-risk and low physical activity clusters showed that the adjusted OR values of 1.471 (1.266-1.710) and 1.174 (1.052-1.310) were significantly associated with insufficient sleep (P < .001). Adolescent health risk behaviors were clustered, and different clusters had different sleep time. Schools authorities and healthcare practitioners should formulate effective intervention measures according to the characteristics of different clusters to promote healthy growth among adolescents. |
format | Online Article Text |
id | pubmed-9909054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-99090542023-02-10 Cluster Analysis of Sleep Time and Adolescent Health Risk Behaviors Yu, Junjie Liu, Yang Liao, Liping Yan, Jie Wang, Hong Inquiry Original Research Adolescents are prone to multiple health risk behaviors. These might lead to insufficient sleep, which is inconducive to adolescent growth. Therefore, this study explored the impact of a cluster of adolescent health risk behaviors on sleep time, providing a reference for designing relevant intervention measures. From November to December 2019, a stratified cluster sampling method was used to sample middle and high schools in 4 functional districts of Chongqing, China. A total of 8546 participants were selected for a questionnaire survey. Two-step clustering helped identify the health risk behavior clusters. Multivariate logistic regression models helped examine the association between the different clusters and sleep time. The rate of insufficient sleep was 65.8%. Three types of clusters were identified, namely (1) high-risk (poor) cluster (17.3%), (2) low physical activity (medium) cluster (55.1%), and (3) low-risk (good) cluster (27.6%). The high-risk and low physical activity clusters showed that the adjusted OR values of 1.471 (1.266-1.710) and 1.174 (1.052-1.310) were significantly associated with insufficient sleep (P < .001). Adolescent health risk behaviors were clustered, and different clusters had different sleep time. Schools authorities and healthcare practitioners should formulate effective intervention measures according to the characteristics of different clusters to promote healthy growth among adolescents. SAGE Publications 2023-02-07 /pmc/articles/PMC9909054/ /pubmed/36748745 http://dx.doi.org/10.1177/00469580231153272 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Yu, Junjie Liu, Yang Liao, Liping Yan, Jie Wang, Hong Cluster Analysis of Sleep Time and Adolescent Health Risk Behaviors |
title | Cluster Analysis of Sleep Time and Adolescent Health Risk Behaviors |
title_full | Cluster Analysis of Sleep Time and Adolescent Health Risk Behaviors |
title_fullStr | Cluster Analysis of Sleep Time and Adolescent Health Risk Behaviors |
title_full_unstemmed | Cluster Analysis of Sleep Time and Adolescent Health Risk Behaviors |
title_short | Cluster Analysis of Sleep Time and Adolescent Health Risk Behaviors |
title_sort | cluster analysis of sleep time and adolescent health risk behaviors |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9909054/ https://www.ncbi.nlm.nih.gov/pubmed/36748745 http://dx.doi.org/10.1177/00469580231153272 |
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