Whole-body vibration exposure and chronic low back pain among heavy machine operators and long-haul truck drivers in Tanzania: a cross-sectional study

Abstract

Background: The Workers Compensation Fund (WCF) in Tanzania has noted an increased rate of injury claims for work-related musculoskeletal disorders (WRMSDs), particularly chronic low back pain among truck drivers and heavy machine operators. These trends indicate a likelihood of occupational exposure to whole-body vibration (WBV), nevertheless local and contextual evidence is needed to guide policy and decision-making. This study aimed to quantity and characterize the WBV exposure and examined its association with self-reported 12-month chronic low back pain among heavy machine operators and long-haul truck drivers in Tanzania. Methods: We conducted an analytical cross-sectional study of 632 participants in 2023 with a total of 141 WBV measurements. The WBV was measured at the seat-operator interface and analyzed using the International Organization for Standardization - ISO 2631-1:1997 to derive 8-h equivalent daily exposure, A(8). A standardized and pretested questionnaire was used to collect information on WRMSDs related factors. Data were analyzed using regression models and Chronic low back pain was defined as self-reported low back pain during the preceding 12 months. Results: was associated with higher prevalence of chronic low back pain (adjusted RR 1.22; 95% CI 1.01-1.47), as were working in the mining sector (adjusted RR 1.36; 95% CI 1.05-1.75), increase in body mass index (BMI) (adjusted RR 1.02; 95% CI 1.00-1.04) and reporting leg pain symptoms (adjusted RR 2.36; 95% CI 2.04-2.73). Conclusion: A significant number of measurements exceeded the Directive 2002/44/EC EAV, and a substantial proportion of workers reported chronic low back pain, suggesting a potential relationship. Preventive interventions to reduce WBV exposure could benefit heavy machine operators and truck drivers. Longitudinal studies with repeated measurements are warranted to better characterize exposure variability and WRMSDs.