Occupational
Military occupation and sleep trends over time: longitudinal results from the Annual Periodic Health Assessment of active duty US Navy and Marine Corps personnel, 2017-2021 James K. Romine* James Romine Romine Romine NHRC/Leidos, Inc.
Introduction: US military personnel are less likely than civilians to obtain the recommended 7-9 hours of sleep per night, increasing risk of impaired performance and safety issues. There is little understanding of occupation-specific sleep trajectories. Estimates of expected changes in sleep quality have yet to be quantified.
Materials and Methods: The Periodic Health Assessment (PHA) was used to examine the relationship of military occupation with trends of sufficient sleep among active duty US Navy and Marine Corps personnel from 2017 to 2021. Sufficient sleep was defined as ≥7 hours “on most days” during the previous 2 weeks (self-reported). Occupational titles were derived from Defense Manpower Data Center codes. Population-averaged generalized estimating equations were used to estimate the prevalence of sufficient sleep at baseline and the percent change over time, accounting for repeated measures. Covariates were age, sex, and number of deployments.
Results: The total sample (n=496,079) was 59% Navy and 41% Marine Corps. Across 48 Navy occupations, the baseline prevalence of sufficient sleep ranged from 21.4% to 52.0%. The Navy’s average prevalence of sufficient sleep decreased by 2.9 -%/yr (95% CI, 2.6-3.2 -%/yr). Law Enforcement (21.4%), Food Service Personnel (21.7%), and Material Receipt, Storage and Issue (22.7%) showed the lowest baseline sleep prevalence. The fastest decreases were observed among Aircraft Launch Equipment (21.19 -%/yr); Metalworking (17.70 -%/yr); Religious, Morale and Welfare (8.69 -%/yr); and Food Service (8.32 -%/yr). Across 55 Marine Corps occupations, the baseline prevalence ranged from 22.7% to 49.2%. Average prevalence decreased by 4.1 -%/yr (95% CI, 3.5-4.6 -%/yr). Cyberspace Maintenance (22.7%), Administration (23.0%), and Food Service (23.5%) showed the lowest baseline sleep prevalence. The fastest decreases were observed among Other Mechanical and Electrical Equipment (15.7 -%/yr), Metalworking (12.7 -%/yr), Motor Transport (11.1 -%/yr), and Unmanned Vehicle System (UVS) Operation (10.7 -%/yr).
Conclusion: This study demonstrates a method to identify at-risk occupations that could be targeted for interventions to prevent sleep deterioration over time. Future studies are needed to understand how occupations contribute to sleep quality over time.