NIOSHTIC-2 Publications Search
Associations with shift work with leptin, insulin, and adiponectin.
Charles-LE; Burchfiel-CM; Gu-JK; Fekedulegn-D; Violanti-JM; Ma-CC; Adjeroh-LC; Andrew-ME
Am J Epidemiol 2012 Jun; 175(Suppl 11):S118
Shift work disrupts circadian rhythms and may affect metabolic function. Our objective was to investigate cross-sectional associations between shift work and three biomarkers of metabolic function: leptin, insulin, and adiponectin. Participants were 394 police officers from Buffalo, NY. Objective data on shift work were obtained from daily city payroll records over 12 years. Officers were categorized as working day, afternoon, or night shift based on the shift for which they had the highest percentage of hours. Metabolic markers were measured after fasting using standardized techniques. Mean levels of the biomarkers were compared across shifts using ANOVA and ANCOVA. Shift work was significantly associated with insulin among officers with BMI <25 kg/m2 (P = 0.015) and BMI significantly modified this association (interaction P = 0.018). Among officers with BMI <25 kg/m2, those who worked the afternoon shift had higher mean levels of insulin (7.7 uU/mL, 95% confidence interval (CI): 4.9- 12.2) than those on day shift (3.5 uU/mL, 95% CI: 2.5-4.8); P = 0.004, after adjustment for age, gender, race, sleep duration, workload, smoking, HDL and total cholesterol, triglycerides, and glucose. Mean insulin levels were higher overall across shifts among officers with a BMI .25 kg/m2, though not significantly different. Shift work was not significantly associated with leptin or adiponectin after accounting for gender. Several factors that could affect metabolic function (e.g., irregular or poor eating patterns) have been shown, in previous studies, to be associated with shift work. Our results show that working on the afternoon shift was associated with the higher insulin levels in officers with a BMI <25 kg/m2.
Shift-work; Shift-workers; Circadian-rhythms; Metabolism; Metabolic-equilibrium; Biomarkers; Emergency-responders; Police-officers; Epidemiology; Statistical-analysis; Demographic-characteristics
American Journal of Epidemiology