ABSTRACT
Background Furniture manufacturing is one of the typical labor-intensive industries, and workers in this industry face a high risk of work-related musculoskeletal disorders (WMSDs), which seriously affect the physical and mental health of workers. Objective To explore the prevalence and potential risk factors of WMSDs among workers in a large-scale furniture manufacturing factory. Methods A cross-sectional study of 3431 workers in a furniture factory in Guangdong Province was conducted from September to December 2019. Information including reported WMSDs in various body parts in the past year, demographic characteristics, work organization factors, job characteristics, and work postures was collected by an electronic version of Musculoskeletal Disorders Questionnaire. Pearson χ2 test and binary logistic regression were used to analyze the risk factors leading to WMSDs. Results The overall prevalence rate of WMSDs was 32.12% (1102/3431). The most common WMSDs symptoms occurred in the neck (16.85%), followed by the feet (15.27%), shoulders (14.81%), and hands (14.25%). The prevalence rates of WMSDs in the neck, shoulders, elbows, hands, legs, and feet were significantly different among different types of work (P<0.05). The results of multiple logistic regression analysis showed that individual factors, work organization factors, job characteristics, and awkward work postures were associated with the frequency of reporting WMSDs in specific parts of workers. Comparatively poor physical health (including moderate, poor, and very poor) was positively correlated with neck, shoulder, hand, and foot WMSDs (OR=1.479-4.077); working with an uncomfortable posture (OR=1.983) and doing the same task almost every day (OR=1.783) were positively correlated with neck pain; doing the same task almost every day (OR=2.408) and neck twisting for a long time (OR=1.830) were positively correlated with shoulder pain; bending wrists up and down frequently (OR=1.948) and bending wrists for a long time (OR=2.081) were positively correlated with hand pain; prolonged standing (OR=1.953) and often working overtime (OR=1.627) were positively correlated with feet pain; sufficient rest time was negatively correlated with WMSDs in the neck, shoulders, hands, and foot (OR=0.544-0.717). Conclusion The prevalence rate of WMSDs in furniture manufacturing workers is relatively high, and neck, feet, shoulders, and hands are the most involved body parts. The frequency of reporting WMSDs is related to individual factors, work organization factors, job characteristics, and awkward work postures.
ABSTRACT
Background Occupational noise-induced hearing loss (NIHL) is one of the most prevalent occupational diseases in the world. With the development of industry, noise sources in the workplace have become increasingly complex. Objective To apply kurtosis-adjusted cumulative noise exposure (CNE) to assess the occupational hearing loss among furniture manufacturing workers, and to provide a basis for revising noise measurement methods and occupational exposure limits in China. Methods A cross-sectional survey was conducted to select 694 manufacturing workers, including 542 furniture manufacturing workers exposed to non-Gaussian noise, and 152 textile manufacturing workers and paper manufacturing workers exposed to Gaussian noise. The job titles involving non-Gaussian noise were gunning and nailing, and woodworking, while those involving Gaussian noise were weaving, spinning, and pulping. High frequency noise-induced hearing loss (HFNIHL) and noise exposure data were collected for each study subject. Noise energy metrics included eight-hour equivalent continuous A-weighted sound pressure level (LAeq,8 h) and CNE. Kurtosis was a noise temporal structure metric. Kurtosis-adjusted CNE was a combined indicator of noise energy and temporal structure. Results The age of the study subjects was (35.64±10.35) years, the exposure duration was (6.71±6.44) years, and the proportion of males was 75.50%. The LAeq,8 h was (89.43±6.01) dB(A). About 81.42% of the study subjects were exposed to noise levels above 85 dB(A), the CNE was (95.85±7.32) dB(A)·year, with a kurtosis of 99.34 ± 139.19, and the prevalence rate of HFNIHL was 35.59%. The mean kurtosis of the non-Gaussian noise group was higher than that of the Gaussian noise group (125.33±147.17 vs. 5.86±1.94, t=−21.04, P<0.05). The results of binary logistic regression analysis showed that kurtosis was an influential factor of workers' HFNIHL after correcting for age, exposure duration, and LAeq,8 h (OR=1.49, P<0.05). The results of multiple linear regression analysis showed that the effects of age, exposure duration, LAeq,8 h, and kurtosis on noise-induced permanent threshold shift at frequencies of 3, 4, and 6 kHz of the poor hearing ear were statistically significant (all P<0.05). The results of chi-square trend analysis showed that when CNE ≥ 90 dB(A)·year, the HFNIHL prevalence rate elevated with increasing kurtosis (P<0.05). The mean HFNIHL prevalence rate was higher in the non-Gaussian noise group than in the Gaussian noise group (31.7% vs. 22.0%, P<0.05). After applying kurtosis-adjusted CNE, the linear equation between CNE and HFNIHL prevalence rate for the non-Gaussian noise group almost overlapped with that for the Gaussian noise group, and the mean difference in HFNIHL prevalence rate between the two groups decreased from 9.7% to 1.4% (P<0.05). Conclusion Noise kurtosis is an effective metric for NIHL evaluation. Kurtosis-adjusted CNE can effectively evaluate occupational hearing loss due to non-Gaussian noise exposure in furniture manufacturing workers, and is expected to be a new indicator of non-Gaussian noise measurement and assessment.