TY - JOUR
T1 - Sleep duration and metabolic body size phenotypes among Chinese young workers
AU - Wang, Jiangshui
AU - Xue, Dan
AU - Shi, Bin
AU - Xia, Lu
AU - Chen, Weiyi
AU - Liu, Li
AU - Liu, Junling
AU - Wang, Huaiji
AU - Ye, Fang
N1 - Publisher Copyright:
Copyright © 2022 Wang, Xue, Shi, Xia, Chen, Liu, Liu, Wang and Ye.
PY - 2022/10/5
Y1 - 2022/10/5
N2 - 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.
AB - 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.
KW - body size phenotypes
KW - metabolically healthy obesity
KW - shift work
KW - sleep duration
KW - young adults
UR - http://www.scopus.com/inward/record.url?scp=85140238249&partnerID=8YFLogxK
U2 - 10.3389/fpubh.2022.1017056
DO - 10.3389/fpubh.2022.1017056
M3 - 文章
C2 - 36276399
AN - SCOPUS:85140238249
SN - 2296-2565
VL - 10
JO - Frontiers in Public Health
JF - Frontiers in Public Health
M1 - 1017056
ER -