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      Sleep disturbances and predictors of nondeployability among active-duty Army soldiers: an odds ratio analysis of medical healthcare data from fiscal year 2018

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          Abstract

          Background

          The impact of sleep disorders on active-duty soldiers’ medical readiness is not currently quantified. Patient data generated at military treatment facilities can be accessed to create research reports and thus can be used to estimate the prevalence of sleep disturbances and the role of sleep on overall health in service members. The current study aimed to quantify sleep-related health issues and their impact on health and nondeployability through the analysis of U.S. military healthcare records from fiscal year 2018 (FY2018).

          Methods

          Medical diagnosis information and deployability profiles (e-Profiles) were queried for all active-duty U.S. Army patients with a concurrent sleep disorder diagnosis receiving medical care within FY2018. Nondeployability was predicted from medical reasons for having an e-Profile (categorized as sleep, behavioral health, musculoskeletal, cardiometabolic, injury, or accident) using binomial logistic regression. Sleep e-Profiles were investigated as a moderator between other e-Profile categories and nondeployability.

          Results

          Out of 582,031 soldiers, 48.4% ( n = 281,738) had a sleep-related diagnosis in their healthcare records, 9.7% ( n = 56,247) of soldiers had e-Profiles, and 1.9% ( n = 10,885) had a sleep e-Profile. Soldiers with sleep e-Profiles were more likely to have had a motor vehicle accident (pOR (prevalence odds ratio) =4.7, 95% CI 2.63–8.39, P ≤ 0.001) or work/duty-related injury (pOR = 1.6, 95% CI 1.32–1.94, P ≤ 0.001). The likelihood of nondeployability was greater in soldiers with a sleep e-Profile and a musculoskeletal e-Profile (pOR = 4.25, 95% CI 3.75–4.81, P ≤ 0.001) or work/duty-related injury (pOR = 2.62, 95% CI 1.63–4.21, P ≤ 0.001).

          Conclusion

          Nearly half of soldiers had a sleep disorder or sleep-related medical diagnosis in 2018, but their sleep problems are largely not profiled as limitations to medical readiness. Musculoskeletal issues and physical injury predict nondeployability, and nondeployability is more likely to occur in soldiers who have sleep e-Profiles in addition to these issues. Addressing sleep problems may prevent accidents and injuries that could render a soldier nondeployable.

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          Most cited references17

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          Sleep and mental disorders: A meta-analysis of polysomnographic research.

          Investigating sleep in mental disorders has the potential to reveal both disorder-specific and transdiagnostic psychophysiological mechanisms. This meta-analysis aimed at determining the polysomnographic (PSG) characteristics of several mental disorders. Relevant studies were searched through standard strategies. Controlled PSG studies evaluating sleep in affective, anxiety, eating, pervasive developmental, borderline and antisocial personality disorders, attention-deficit-hyperactivity disorder (ADHD), and schizophrenia were included. PSG variables of sleep continuity, depth, and architecture, as well as rapid-eye movement (REM) sleep were considered. Calculations were performed with the "Comprehensive Meta-Analysis" and "R" software. Using random effects modeling, for each disorder and each variable, a separate meta-analysis was conducted if at least 3 studies were available for calculation of effect sizes as standardized means (Hedges' g). Sources of variability, that is, sex, age, and mental disorders comorbidity, were evaluated in subgroup analyses. Sleep alterations were evidenced in all disorders, with the exception of ADHD and seasonal affective disorders. Sleep continuity problems were observed in most mental disorders. Sleep depth and REM pressure alterations were associated with affective, anxiety, autism and schizophrenia disorders. Comorbidity was associated with enhanced REM sleep pressure and more inhibition of sleep depth. No sleep parameter was exclusively altered in 1 condition; however, no 2 conditions shared the same PSG profile. Sleep continuity disturbances imply a transdiagnostic imbalance in the arousal system likely representing a basic dimension of mental health. Sleep depth and REM variables might play a key role in psychiatric comorbidity processes. Constellations of sleep alterations may define distinct disorders better than alterations in 1 single variable. (PsycINFO Database Record
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            Sleep and emotion regulation: An organizing, integrative review.

            A growing body of research suggests that disrupted sleep is a robust risk and maintenance factor for a range of psychiatric conditions. One explanatory mechanism linking sleep and psychological health is emotion regulation. However, numerous components embedded within this construct create both conceptual and empirical challenges to the study of emotion regulation. These challenges are reflected in most sleep-emotion research by way of poor delineation of constructs and insufficient distinction among emotional processes. Most notably, a majority of research has focused on emotions generated as a consequence of inadequate sleep rather than underlying regulatory processes that may alter these experiences. The current review utilizes the process model of emotion regulation as an organizing framework for examining the impact of sleep upon various aspects of emotional experiences. Evidence is provided for maladaptive changes in emotion at multiple stages of the emotion generation and regulation process. We conclude with a call for experimental research designed to clearly explicate which points in the emotion regulation process appear most vulnerable to sleep loss as well as longitudinal studies to follow these processes in relation to the development of psychopathological conditions.
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              Sleep, Health, and Society.

              Biological needs for sleep are met by engaging in behaviors that are largely influenced by the environment, social norms and demands, and societal influences and pressures. Insufficient sleep duration and sleep disorders such as insomnia and sleep apnea are highly prevalent in the US population. This article outlines some of these downstream factors, including cardiovascular and metabolic disease risk, neurocognitive dysfunction, and mortality, as well as societal factors such as age, sex, race/ethnicity, and socioeconomics. This review also discusses societal factors related to sleep, such as globalization, health disparities, public policy, public safety, and changing patterns of use of technology.
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                Author and article information

                Contributors
                jdevine@ibrinc.org
                jacob.f.collen.mil@mail.mil
                john.j.choynowski.ctr@mail.mil
                vincent.f.capaldi.mil@mail.mil
                Journal
                Mil Med Res
                Mil Med Res
                Military Medical Research
                BioMed Central (London )
                2095-7467
                2054-9369
                10 March 2020
                10 March 2020
                2020
                : 7
                : 9
                Affiliations
                [1 ]GRID grid.427080.9, Institutes for Behavior Resources, Operational Fatigue and Performance, ; 2104 Maryland Ave, Baltimore, MD 21218 USA
                [2 ]GRID grid.414467.4, ISNI 0000 0001 0560 6544, Pulmonary, Critical Care and Sleep Medicine Walter Reed National Military Medical Center, ; Bethesda, MD 20889 USA
                [3 ]GRID grid.420210.5, ISNI 0000 0001 0036 4726, Behavioral Biology Branch, Center for Military Psychiatry and Neuroscience, , Walter Reed Army Institute of Research, ; Silver Spring, MD 20910 USA
                Article
                239
                10.1186/s40779-020-00239-7
                7063745
                32151283
                45c37008-95f2-4e81-b474-593cd76ef01d
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 23 July 2019
                : 26 February 2020
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                medical readiness,behavioral sleep medicine,deployability,healthcare records,military,big data,data mining

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