Object: To explore the prevalence and risk factors of work-related musculoskeletal disorders (WMSDs) among footwear industry workers in China, thereby providing a scientific basis for implementing health interventions. Methods Following a cross-sectional epidemiological survey method, modified Chinese version of the WMSDs Questionnaire was adopted to investigate the prevalence of WMSDs and related risk factors such as ergonomic load and psychosocial factors, among all workers in 26 footwear factories across China from 2018 to 2020. The data were statistically analyzed with chi-square tests and multivariate logistic regression analysis. Results A total of 7106 valid questionnaires were collected. The prevalence of WMSDs among footwear workers was 36.8%, and the symptoms mostly occurred in the neck (23.9%), shoulders (19.3%), and hands (14.9%). The Chi-square test revealed 26 factors that significantly differed from the prevalence of WMSDs (P < 0.05). Multivariate logistic regression analysis revealed that gender (OR = 1.348, 95%CI:1.122–1.621, P < 0.01), marital status (OR = 1.822, 95%CI:1.320–2.515, P < 0.01), physical conditions (OR = 1.423, 95%CI:1.302–1.555, P < 0.01), working in an uncomfortable position (OR = 1.371, 95%CI:1.261–1.491, P < 0.01), cold or temperature variations at work (OR = 1.350, 95%CI:1.184–1.540, P < 0.01), working outdoors (OR = 1.324, 95%CI: 1.017–1.724, P < 0.05), and multiple repetitive operations per minute (OR = 1.207, 95%CI:1.150–1.268, P < 0.01) were key risk factors in the prevalence of WMSDs. By contrast, monthly income (OR = 0.728, 95% CI:0.667–0.794, p < 0.01) was a protective factor for WMSDs. Conclusion WMSDs show high prevalence among footwear industry worker and are associated with gender, marital status, uncomfortable position, variable temperatures, working outdoors, and multiple repetitive operations. Preventive measures on the basis of these risk factors should be implemented to reduce the adverse effects on the health of footwear industry workers.
BACKGROUND: The automotive industry is labor-intensive, and workers are involved in highly repetitive tasks, long hours, and medium to low workloads, resulting in work-related musculoskeletal disorders (WMSDs), which have become a major health concern for workers in this industry. China is a major automotive country with tens of thousands of auto repair workers, but their conditions of WMSDs have been poorly reported. OBJECTIVE: This work aimed to analyze the current prevalence of WMSDs and their associated risk factors among automobile maintenance workers. METHODS: A total of 539 respondents from 50 automotive repair and maintenance companies in China were selected to investigate the prevalence of WMSDs via the modified Nordic Musculoskeletal Disorders Questionnaire. Chi-square test and logistic regression models were applied to analyze their associated risk factors. RESULTS: The total prevalence of WMSDs among 539 workers was 32.8%. The top three body parts for prevalence were the lower back (17.1%), neck (16.3%), and shoulders (14.5%). The highest prevalence of WMSDs was found in the neck (23.6%) and lower back (14.3%) for sheet metal workers and mechanics, respectively, whereas painters had the highest prevalence of WMSDs in the lower back and feet (both at 15.4%). Logistic regression analysis showed that females were at higher risk of WMSDs than males (OR 5.027, [95% CI] [1.278–19.772], p < 0.05). Workers subjected to uncomfortable positions were at increased risk of WMSDs (OR 1.79, [95% CI] [1.333–2.410], p < 0.01). CONCLUSION: The prevalence of WMSDs is high among automotive maintenance workers, with the highest prevalence in the lower back (17.1%). Uncomfortable working postures and frequent repetitive movements with lower limbs and ankles at work may be important risk factors.
To identify the influencing factors and develop a predictive model for the risk of abnormal liver function in the automotive manufacturing industry works in Chongqing. Automotive manufacturing workers in Chongqing city surveyed during 2019–2021 were used as the study subjects. Logistic regression analysis was used to identify the influencing factors of abnormal liver function. A restricted cubic spline model was used to further explore the influence of the length of service. Finally, a deep neural network-based model for predicting the risk of abnormal liver function among workers was developed. Of all 6087 study subjects, a total of 1018 (16.7%) cases were detected with abnormal liver function. Increased BMI, length of service, DBP, SBP, and being male were independent risk factors for abnormal liver function. The risk of abnormal liver function rises sharply with increasing length of service below 10 years. AUC values of the model were 0.764 (95% CI: 0.746–0.783) and 0.756 (95% CI: 0.727–0.786) in the training and test sets, respectively. The other four evaluation indices of the DNN model also achieved good values.
BACKGROUND China remains the world’s largest automotive manufacturing country. The work-related musculoskeletal disorders (WMSDs) are a common occupational hazard associated with heavy industries. 76.2%-91.4% of vehicle maintenance workersuffers from WMSDs, among them, automotive maintenance workers have a higher risk of WMSDs due to some uncomfortable working postures and unreasonable work schedules.Furthermore, the prevalence of multi-site WMSDs is higher than that of single-site WMSDs in automotive workers. The available data (descriptive, etiological and prognostic data) largely focuses on the WMSDs defined by anatomical sites, and the research on multi-site WMSDs is particularlysparse. OBJECTIVES To explore the regularity and influencing factors of WMSDs in automotive maintenance workers. METHODS Through cluster sampling, 539 workers from 50 automotive repair and maintenance companies in China were recruited. The prevalence of WMSDs in the main anatomical sites was investigated using the modified Nordic MusculoskeletalDisorders Questionnaire (NMQ). The chi-square test and logistic regression models were used to analyze the associated risk factors. CONCLUSIONS Multisite WMSDs are more prevalent than single-site WMSDs among automotive maintenance workers, and two sites are most commonly affected. The influencing factors include demographic characteristics,such as gender, working age, certain types of movements and postures (working in uncomfortable positions, repetitive movements of the lower limbs and ankles), regular overtime, back to work after a break, and number of breaks per shift.
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