Work organization, sleep and metabolic syndrome among long-haul truck drivers.

BACKGROUND: The work organization of long-haul truck drivers in the USA contains factors that have been shown to degrade sleep. In combination, these factors generate elevated cardiometabolic risk by inducing components of the metabolic syndrome (MetS). However, the prevalence and severity of MetS and the degree to which such factors differentially influence MetS among these drivers are unknown. AIMS: To determine the prevalence and severity of MetS among US long-haul truck drivers and to determine the predictive value of demographic, work organization and sleep variables in MetS diagnosis and severity. METHODS: A non-experimental, descriptive, cross-sectional study, designed to collect survey, anthropometric and biometric data from US long-haul truck drivers. Descriptive analyses were performed for demographic, work organization, sleep and MetS measures. Logistic and linear regression analyses examined potential predictive relationships between demographic, work organization and sleep variables and MetS diagnosis and severity. RESULTS: The study population was 262. Nearly 60% of drivers met MetS diagnosis criteria. Over 80% had a waist circumference >102 cm, 50% had triglyceride levels of ≥150 mg/dl, 66% had an high-density lipoprotein of <40 mg/dl, 28% had a blood pressure of ≥135/80 mm Hg and 17% had a fasting glucose of ≥110 mg/dl. Driving experience and work day sleep quality were associated with MetS prevalence and severity. CONCLUSIONS: The prevalence and severity of MetS among this sample of US long-haul truck drivers were high. Preventive efforts should focus on experienced drivers and work day sleep quality.

Work patterns, sleeping hours and excess weight in commercial drivers.

BACKGROUND: Work and sleep patterns for commercial motor vehicle (CMV) drivers often include long working hours, shift work and diminished sleep duration and quality, which have been linked to overweight, obesity and other problems. AIMS: To explore possible connections between work, sleep and obesity among CMV drivers. METHODS: Survey and anthropometric data were collected from male long-haul CMV drivers in central North Carolina, USA, over a period of 6 months. Drivers' body mass index (BMI) was used as a measure of total body obesity and sagittal abdominal diameter (SAD) as a measure of central adiposity. RESULTS: Among the 260 study subjects, mean BMI was 33.1 (64% were obese or morbidly obese) and mean SAD was 32.3cm, classifying 89% of drivers as being at high or very high cardiometabolic risk. About 83% of drivers worked an irregular daily schedule, 64% worked irregular total daily hours, 32% worked irregular days of the week and 46% reported getting <7h of sleep during work nights. Significant predictors of BMI included the number of hours worked daily (P < 0.05) and the age (P < 0.01) of the driver, while age was also a significant predictor for SAD (P < 0.05). Significant predictors of sleep quality included the extent of shift work (P < 0.05) and sleep duration (P < 0.001). CONCLUSIONS: Work and sleep configurations appear to affect the weight status of CMV drivers. Shift work and sleep duration are both associated with the weight status of CMV drivers, and both appear to function as indicators of their sleep quality.