Occurrence pattern of musculoskeletal disorders and its influencing factors among manufacturing workers.
10.19723/j.issn.1671-167X.2020.03.021
- Author:
Fu Jiang WANG
1
;
Xu JIN
1
;
Mamat NAZAKAT
1
;
Yi Dan DONG
1
;
Shi Juan WANG
1
;
Zhong Bin ZHANG
2
;
Shan Fa YU
3
;
Li Yun YANG
4
;
Li Hua HE
1
Author Information
1. Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing 100191, China.
2. National Center of Occupational Safety and Health, National Health Commission, Beijing 102308, China.
3. Henan Medical College, Zhengzhou 451191, China.
4. Institute of Environmental Medicine, Karolinska Institutet, Stockholm 171 77, Sweden.
- Publication Type:Journal Article
- Keywords:
Manufacturing industry;
Musculoskeletal disorders;
Risk factors
- MeSH:
China;
Female;
Humans;
Musculoskeletal Diseases;
Occupational Diseases;
Prevalence;
Risk Factors;
Shoulder;
Surveys and Questionnaires
- From:
Journal of Peking University(Health Sciences)
2020;52(3):535-540
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To explore the occurrence pattern and its influencing factors of multi-site work-related musculoskeletal disorders (WMSDs) of the main affected body sites among manufacturing workers.
METHODS:Musculoskeletal disorders questionnaire was adopted to investigate the prevalence of WMSDs and the influencing factors among workers from four manufacturing factories in China. The case of WMSDs was defined as the one who had symptoms such as pain, numbness, discomfort, or limitation of activities in one or more of the nine body sites, including neck, shoulder, elbow, wrist/hand, upper back, lower back, hip/thigh, knee and ankle/foot during the last year, which lasted for more than 24 hours and did not completely relieve after rest. Besides, trauma, disability, other acute injuries or sequelae were excluded. The correlation of WMSDs between different body sites was estimated by the prevalence ratio (PR) calculated by log-binominal model. The influencing factors of multi-site WMSDs of the main affected body sites were analyzed by multinomial logistic regression model.
RESULTS:The overall prevalence rate of WMSDs was 79.7% among the manufacturing workers. The main affected body sites were lower back, neck, shoulder and upper back, of which the prevalence rates were 62.3%, 55.7%, 45.6%, and 38.7%, respectively. The PR values of WMSDs among these sites were relatively high. The prevalence of multi-site WMSDs involving these four sites at the same time was 25.2%, and that of three to four sites was 41.4%. Multinomial Logistic regression analysis suggested that influencing factors of multi-site WMSDs in 3-4 sites of neck, shoulder, upper back and lower back involved several aspects. Among these factors, females (OR=2.86, 95%CI 2.38-3.33) and individuals with job tenure of 15-19 years (OR=1.87, 95%CI 1.49-2.34) might have higher risk of disease. Biomechanical factors, such as often bending neck forward or holding neck in a forward position for long periods (OR=2.15, 95%CI 1.86-2.48), often twisting neck or holding neck in a twisted position for long periods (OR=1.64, 95%CI 1.40-1.92) and often twisting trunk heavily (OR=1.40, 95%CI 1.20-1.64) might be risk factors. In the aspect of work organization, doing the same work every day (OR=1.73, 95%CI 1.44-2.08), shortage of workers (OR=1.50, 95%CI 1.31-1.71) and often working overtime (OR=1.38, 95%CI 1.20-1.60) might increase the risk of disease. Factors, such as often standing for long periods at work (OR=0.77, 95%CI 0.65-0.91) and feeling breaks sufficient (OR=0.51, 95%CI 0.44-0.59) were suggested to be protective factors with OR<1.
CONCLUSION:The pre-valence rates of WMSDs in neck, shoulder, upper back, and lower back were high among manufacturing workers in this study. The correlation of WMSDs of these four sites was close in this study, and the comorbidity rate of 3-4 sites of these sites was relatively high, suggesting that there might be a multi-site occurrence pattern of WMSDs in "neck-shoulder-upper back-lower back" among manufacturing workers. The main influencing factors of this pattern included individual factors, biomechanical factors and work organization factors.
