ArticleNature and science of sleep2023
Impact of Sleep Profiles on Multimorbidity Among US Active-Duty Service Members in the 2018 Health-Related Behaviors Survey.
Article in Nature and science of sleep, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Body roundness index modified the association between sleep changes and multimorbidity in middle-aged and older adults: a nationwide cohort study.Journal of health, population, and nutrition · 2026Article
- Association between mental health and insomnia in young soldiers: a mediation analysis of mental health literacy.BMC public health · 2025Article
- Health is beyond genetics: on the integration of lifestyle and environment in real-time for hyper-personalized medicine.Frontiers in public health · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Sleep is a modifiable factor affecting chronic diseases and conditions in the Active-Duty (AD) United States (US) military population. This study assesses the impact of reported sleep health behaviors and sleep profiles on reported multimorbidity in active-duty service members (ADSMs). Participants and methods: The study used a military representative sample of 17,166 active duty SMs from the 2018 Department of Defense Results: Sleep-related health behaviors were associated with increased odds of obesity, hypertension, and hyperlipidemia. We found higher odds of reported multimorbidity in SMs who reported lack of energy due to poor sleep (adjusted odds ratio [aOR] = 2.35, 95% CI:1.88-2.93), sleep 6 hours or less per night (aOR = 1.95, 95% CI:1.53-2.50), trouble sleeping (aOR = 2.19, 95% CI:1.76-2.72), and use of sleep medications (aOR = 2.10, 95% CI:1.64-2.68). Latent class analysis (LCA) identified three unobservable sleep profiles in SMs: minimal or low-risk sleep patterns (37.43%), moderate-risk sleep patterns (31.11%), and high-risk sleep patterns (31.46%). SMs with high-risk sleep patterns were significantly associated with reported multimorbidity (adjusted odds ratio [aOR] = 3.54, 95% CI:2.75-4.56). Conclusion: We found a strong association between sleep-related health behaviors and their unobservable sleep profiles with multimorbidity in this AD population. Future studies should investigate whether other chronic diseases may be influenced by sleep impairment in the US military population.
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