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

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Laurie Wideman, Safrit-Ennis Distinguished Professor (Creator)
Institution
The University of North Carolina at Greensboro (UNCG )
Web Site: http://library.uncg.edu/

Abstract: 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.

Additional Information

Publication
Occupational Medicine
Language: English
Date: 2017
Keywords
Diabetes, driving, work environment, work-related cardiovascular diseases

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