Date of Award
Open Access Dissertation
Epidemiology and Biostatistics
The Norman J. Arnold School of Public Health
Background: Sleep is considered a physiological necessity and its disruption is associated with a wide variety of adverse mental and physical health outcomes including increased incidence of obesity, cancer, hypertension, cardiovascular disease, type 2 diabetes mellitus, stroke, depression, post-traumatic stress disorder (PTSD), work-related and vehicle accidents, and aberration of the autonomic nervous system.
Methods: Three studies were conducted from three separate populations. The first study examined the latent trajectories of self-reported sleep quality in active duty Army soldiers over a 3-year period using data from the Global Assessment 2.0 survey and Repeated Measures Latent Class Analysis (RMCLA) procedures. Generalized Estimating Equations (GEE) were then used to compare demographic, military characteristics, and health-behaviors between the resultant latent classes. In the second study, a sample of police officers from Buffalo, New York were used to identify the predominant subgroups of evening and night workers using latent class analysis procedures that characterize adaptation to shiftwork. Generalized Linear Models (GLM) and chi-square tests were utilized to compare demographic, law-enforcement characteristics, and health behaviors between subgroups. In addition, logistic regression was used to develop a risk prediction model for shiftwork adaptation and GLMs were used to compare inflammatory, heart rate variability, and cardiometabolic factors between the subgroups. In the last study, a sample of participants from the Midlife in the United States Study (MIDUS II) Biomarker projects were utilized to examine the relationship between sleep quality,HRV, and metabolic syndrome.
Results: In the first study, soldiers with poorer sleep quality trajectories tended to be female, non-white, enlisted, and have non-combat military occupations. Soldiers with persistently better sleep quality had better body composition metrics, physical fitness scores, and were more likely to meet weapon qualification standards. Soldiers in the poorer sleep trajectory groups had lower levels of resiliency across all psychosocial dimensions measured by the GAT 2.0. In the second study, the shiftwork adapted group reported lower probabilities of having a poor response to sleep, stress, and chronic fatigue measures. Additionally, officers in the adapted group were slightly older, had better diets, higher levels of extraversion, agreeableness, hardiness, and lower levels of neuroticism. The adapted group also tended to have more family independence and organization, and less family conflict. There were no differences in inflammatory, HRV, or cardiometabolic risk factors between the latent classes of police officers except for diastolic blood pressure and leptin. In the third paper, there was a negative relationship between poor subjective sleep quality and HRV; an association between poor sleep quality and metabolic syndrome; and an association between low HRV and metabolic syndrome were observed after controlling for relevant covariates.
Discussion: Sleep has profound effects on physical and mental health. Although there were no significant differences in terms inflammatory, HRV, and cardiometabolic biomarkers between shiftwork adapted and maladapted police officers in our study, our results suggest that the physiological consequences of shiftwork are worse among police officers who are not adapted to shiftwork. Our findings highlight the protentional for interventions such as heart rate variability biofeedback for increasing HRV and sleep quality.
Torrance, T.(2018). Sleep, Shiftwork Adaptation, Autonomic Dysfunction, And Metabolic Syndrome. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/4852