Nature and Science of Sleep (Dec 2023)

Impact of Sleep Profiles on Multimorbidity Among US Active-Duty Service Members in the 2018 Health-Related Behaviors Survey

  • Weinberger M,
  • Ahmed AE,
  • Singer DE

Journal volume & issue
Vol. Volume 15
pp. 1019 – 1032

Abstract

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Marina Weinberger,1 Anwar E Ahmed,1,2 Darrell E Singer1,2 1School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA; 2Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USACorrespondence: Anwar E Ahmed, Email [email protected]: 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 Health Related Behaviors Survey (HRBS) to explore sleep patterns and profiles, and medical conditions. Multimorbidity was defined as the presence of two or more medical conditions which we limited to include obesity, hypertension, and hyperlipidemia. The adjusted odds ratios for six sleep-related health behaviors and their unobservable sleep profiles were calculated using a weighted multinomial logistic model.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.Keywords: sleep, multimorbidity, hypertension, obesity, hyperlipidemia, military

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