M K Lemke1,2, Y Apostolopoulos1,2, A Hege3, L Wideman4, S Sönmez5. 1. Complexity & Computational Population Health Group, Texas A&M University, 4243 TAMU, College Station, TX 77843-4243, USA. 2. Department of Health & Kinesiology, Texas A&M University, 4243 TAMU, College Station, TX 77843-4243, USA. 3. Department of Health & Exercise Science, Appalachian State University, 111 Rivers Street, PO Box 32071, Boone, NC 28608, USA. 4. Department of Kinesiology, University of North Carolina Greensboro, PO Box 26107, Greensboro, NC 27402-6170, USA. 5. Rosen College of Hospitality Management, University of Central Florida, 9907 Universal Boulevard, Orlando, FL 32819, USA.
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.
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.
Authors: Adam Hege; Michael K Lemke; Yorghos Apostolopoulos; Brian Whitaker; Sevil Sönmez Journal: Int J Environ Res Public Health Date: 2019-03-19 Impact factor: 3.390
Authors: Antonia L Wadley; Stella Iacovides; Johanna Roche; Karine Scheuermaier; W D Francois Venter; Alinda G Vos; Samanta T Lalla-Edward Journal: PLoS One Date: 2020-12-03 Impact factor: 3.240
Authors: Beatriz Bastos Braga; Fabrícia Geralda Ferreira; Hamilton Henrique Teixeira Reis; João Carlos Bouzas Marins Journal: Rev Bras Med Trab Date: 2022-06-30