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Citation |
Mantua J, Bessey AF, Mickelson C, Choynowski JJ, Noble J, Burke TM, McKeon AB, Sowden WJ. Sleep 2020; ePub(ePub): ePub. |
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Copyright |
(Copyright © 2020, American Academy of Sleep Medicine, Publisher Associated Professional Sleep Societies) |
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DOI |
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PMID |
33125489 |
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Abstract |
Experimental sleep restriction and deprivation lead to risky decision-making. Further, in naturalistic settings, short sleep duration and poor sleep quality have been linked to real-world high-risk behaviors (HRB), such as reckless driving or substance use. Military populations, in general, tend to sleep less and have poorer sleep quality than non-military populations due to a number of occupational, cultural, and psychosocial factors (e.g., continuous operations, stress, trauma). Consequently, it is possible that insufficient sleep in this population is linked to HRB. To investigate this question, we combined data from four diverse United States Army samples and conducted a mega-analysis by aggregating raw, individual-level data (n = 2296, age 24.7 ± 5.3). A negative binomial regression and a logistic regression were used to determine whether subjective sleep quality (Pittsburgh Sleep Quality Index [PSQI], Insomnia Severity Index [ISI] and duration [hours]) predicted instances of military-specific HRB and the commission of any HRB (yes/no), respectively. Poor sleep quality slightly elevated the risk for committing HRBs (PSQI Exp(B): 1.12 and ISI Exp(B): 1.07), and longer duration reduced the risk for HRBs to a greater extent (Exp(B): 0.78), even when controlling for a number of relevant demographic factors. Longer sleep duration also predicted a decreased risk for commission of any HRB behaviors (Exp(B): 0.71). These findings demonstrate that sleep quality and duration (the latter factor, in particular) could be targets for reducing excessive HRB in military populations. These findings could therefore lead to unit-wide or even military-wide policy changes regarding sleep and HRB. Language: en |
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Keywords |
military; sleep; high-risk behavior; pooled data analysis |