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Sleep duration and metabolic body size phenotypes among Chinese young workers

The evidence linking sleep duration and metabolic body size phenotypes is limited, especially in young adulthood. In this study, we aimed to examine the association between sleep duration and metabolic body size phenotypes among Chinese young workers and investigate whether discrepancies exist among...

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Autores principales: Wang, Jiangshui, Xue, Dan, Shi, Bin, Xia, Lu, Chen, Weiyi, Liu, Li, Liu, Junling, Wang, Huaiji, Ye, Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580563/
https://www.ncbi.nlm.nih.gov/pubmed/36276399
http://dx.doi.org/10.3389/fpubh.2022.1017056
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author Wang, Jiangshui
Xue, Dan
Shi, Bin
Xia, Lu
Chen, Weiyi
Liu, Li
Liu, Junling
Wang, Huaiji
Ye, Fang
author_facet Wang, Jiangshui
Xue, Dan
Shi, Bin
Xia, Lu
Chen, Weiyi
Liu, Li
Liu, Junling
Wang, Huaiji
Ye, Fang
author_sort Wang, Jiangshui
collection PubMed
description The evidence linking sleep duration and metabolic body size phenotypes is limited, especially in young adulthood. In this study, we aimed to examine the association between sleep duration and metabolic body size phenotypes among Chinese young workers and investigate whether discrepancies exist among shift and non-shift workers. A cross-sectional study was performed between 2018 and 2019 in Wuhan, China and 7,376 young adults aged 20–35 years were included. Self-reported sleep duration was coded into four groups: <7, 7–8, 8–9, and ≥9 h per day. Participants were classified into four metabolic body size phenotypes according to their body mass index and metabolic health status: metabolically healthy normal weight, metabolically unhealthy normal weight, metabolically healthy overweight/obesity (MHO), and metabolically unhealthy overweight/obesity (MUO). Multinomial logistic regression models were used to explore the associations between sleep duration and metabolic body phenotypes. Compared with those who slept 7–8 h each night, those with sleep duration <7 h per day had higher odds of MHO (OR 1.27, 95% CI: 1.02–1.56) and MUO (OR 1.22, 95% CI: 1.03–1.43), irrespective of multiple confounders. Stratification analyses by shift work showed that the association between short nighttime sleep and increased odds of MUO was only observed in shift workers (OR 1.26, 95% CI 1.03–1.54). Sleep duration is independently associated with metabolic body size phenotypes among Chinese young adults, while shift work could possibly modulate the association. These results may provide evidence for advocating adequate sleep toward favorable metabolic body size phenotypes in young workers.
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spelling pubmed-95805632022-10-20 Sleep duration and metabolic body size phenotypes among Chinese young workers Wang, Jiangshui Xue, Dan Shi, Bin Xia, Lu Chen, Weiyi Liu, Li Liu, Junling Wang, Huaiji Ye, Fang Front Public Health Public Health The evidence linking sleep duration and metabolic body size phenotypes is limited, especially in young adulthood. In this study, we aimed to examine the association between sleep duration and metabolic body size phenotypes among Chinese young workers and investigate whether discrepancies exist among shift and non-shift workers. A cross-sectional study was performed between 2018 and 2019 in Wuhan, China and 7,376 young adults aged 20–35 years were included. Self-reported sleep duration was coded into four groups: <7, 7–8, 8–9, and ≥9 h per day. Participants were classified into four metabolic body size phenotypes according to their body mass index and metabolic health status: metabolically healthy normal weight, metabolically unhealthy normal weight, metabolically healthy overweight/obesity (MHO), and metabolically unhealthy overweight/obesity (MUO). Multinomial logistic regression models were used to explore the associations between sleep duration and metabolic body phenotypes. Compared with those who slept 7–8 h each night, those with sleep duration <7 h per day had higher odds of MHO (OR 1.27, 95% CI: 1.02–1.56) and MUO (OR 1.22, 95% CI: 1.03–1.43), irrespective of multiple confounders. Stratification analyses by shift work showed that the association between short nighttime sleep and increased odds of MUO was only observed in shift workers (OR 1.26, 95% CI 1.03–1.54). Sleep duration is independently associated with metabolic body size phenotypes among Chinese young adults, while shift work could possibly modulate the association. These results may provide evidence for advocating adequate sleep toward favorable metabolic body size phenotypes in young workers. Frontiers Media S.A. 2022-10-05 /pmc/articles/PMC9580563/ /pubmed/36276399 http://dx.doi.org/10.3389/fpubh.2022.1017056 Text en Copyright © 2022 Wang, Xue, Shi, Xia, Chen, Liu, Liu, Wang and Ye. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Wang, Jiangshui
Xue, Dan
Shi, Bin
Xia, Lu
Chen, Weiyi
Liu, Li
Liu, Junling
Wang, Huaiji
Ye, Fang
Sleep duration and metabolic body size phenotypes among Chinese young workers
title Sleep duration and metabolic body size phenotypes among Chinese young workers
title_full Sleep duration and metabolic body size phenotypes among Chinese young workers
title_fullStr Sleep duration and metabolic body size phenotypes among Chinese young workers
title_full_unstemmed Sleep duration and metabolic body size phenotypes among Chinese young workers
title_short Sleep duration and metabolic body size phenotypes among Chinese young workers
title_sort sleep duration and metabolic body size phenotypes among chinese young workers
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580563/
https://www.ncbi.nlm.nih.gov/pubmed/36276399
http://dx.doi.org/10.3389/fpubh.2022.1017056
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