@article{WANG2025, 
author = {Yimeng WANG and Qing CHEN and Siwen LUO and Fuquan SHI and Mengchao HE and Shengfeng WANG and Qiaorui WEN and Yingzhong DAI and Hao QU and Jia CAO},
title = {Sleep modes based on objective measurement and diseases of the body systems: a cohort study of 87 617 participants from the UK Biobank dataset},
year = {2025},
journal = {Journal of Army Medical University},
volume = {47},
number = {4},
pages = {318-325},
keywords = {accelerometer, latent profile analysis, UK Biobank, disease risk},
url = {https://www.sciopen.com/article/10.16016/j.2097-0927.202410006},
doi = {10.16016/j.2097-0927.202410006},
abstract = {ObjectiveTo investigate the impact of sleep modes on the risk for diseases of the body systems.MethodsBased on a subset of UK Biobank dataset comprising 87 617 participants, 3 sleep dimensions including 6 sleep indicators were obtained through a wrist-worn accelerometer, that is sleep duration and onset, sleep rhythm（relative amplitude and stability）, and sleep quality（sleep efficiency and number of awakenings）. Latent profile analysis（LPA） was applied to identify and classify distinct sleep modes. Then their longitudinal medical records were the association between different sleep modes and the risk for 467 diseases.ResultsLPA identified 5 subgroups of unique sleep modes in the participants.Among the 5 subgroups, the subgroup 4 had relatively optimal levels in above sleep indicators. Compared to the subgroup 4, the other 4 subgroups exhibited variations in different sleep dimensions, with at least one indicator demonstrating an unfavorable trend. These subgroups also revealed differences in racial composition, shift work and social deprivation index. Moreover, there were notable differences in the risk of various system diseases among the subgroups（P＜0. 05）. When compared to the subgroup 4, the other 4subgroups exhibited an elevated risk for certain diseases（comprising a total of 126 diseases）, with the diseases of the circulatory system, digestive system and musculoskeletal system most common. Among the 5 subgroups,the subgroup 2（shorter sleep duration and later sleep onset） and the subgroup 5（rhythm disorder） had the highest counts of associated risks, amounting to 85 and 91 types, respectively, but there was certain difference in their systematic composition.ConclusionThere are different sleep modes within the participants, and the modes are potentially associated with an increased risk for diseases of body systems. Comprehensive interventions targeting overall sleep modes rather than single sleep indicator may yield obvious health benefits.}
}