Sleep as a Component of the Performance Triad: The Importance of Sleep in a Military Population

Objective: Sleep habits among military populations are problematic. Poor sleep hygiene occurs in parallel with the global increase in obesity and metabolic syndrome and contributes to a decrease in performance. The extent of sleep issues needs to be quantified to provide feedback for optimizing warfighter performance and readiness. This study assessed various health behaviors and habits of US Army Soldiers and their relationship with poor sleep quality by introducing a set of new questions into the Comprehensive Soldier and Family Fitness (CSF2) Global Assessment Tool (GAT). Methods: Subjects included 14,148 US Army Active, Reserve, and National Guard members (83.4% male) who completed the GAT, a self-report questionnaire that measures 4 fitness dimensions: social, family, emotional, and spiritual. Approximately 60 new questions, including ones on sleep quality, within the fifth CSF2 dimension (physical) were also answered. A sleep score was calculated from 2 questions validated in the Pittsburgh Insomnia Rating Scale (0 to 6). Results: Poor sleepers (5-6) were significantly (P<.001) more likely than good sleepers (0-1) to consider themselves in fair or poor health, be overweight or obese, and score in the lowest quartile of the emotional, social, family, and spiritual fi tness dimensions. Additionally, poor sleepers were significantly (P<.001) less likely to have a healthy body mass index and waist circumference, eat breakfast 6 or more times a week, meet aerobic exercise and resistance training recommendations, and pass their Army Physical Fitness Test in the top quartile. Conclusion: This study examined sleep quality in a group of military personnel and indicated significant associations between quality of sleep and physical performance, nutritional habits, measures of obesity, lifestyle behaviors and measures of psychosocial status. Targeted educational interventions and resources are needed to improve sleep patterns based on behaviors that can be most easily modified.