Prevalence of musculoskeletal symptoms among industrial employees in a modern industrial region in Beijing, China
- PMID: 30897593
- PMCID: PMC6595845
- DOI: 10.1097/CM9.0000000000000165
Prevalence of musculoskeletal symptoms among industrial employees in a modern industrial region in Beijing, China
Abstract
Background: Growing industrialization of China exposes its labor population to the risk of musculoskeletal disorders (MSDs). This study aimed to investigate the prevalence and risk factors of MSDs in a modern industrial region of Beijing.
Methods: A cross-sectional study included 1415 employees in six industrial companies was conducted between January 2018 and May 2018 in Fangshan district, Beijng, China. Nordic Musculoskeletal Questionnaire (NMQ) was used to collect the information about MSDs. Demographic factors, lifestyle factors, health and medical factors, and work-related factors were collected as independent variables. Descriptive statistics, the chi-squared (χ) test, and binary logistic regression analysis were used to analyze data.
Results: Among 1415 participants, 498 reported MSDs. The regions involved were the neck (25.16%), shoulders (17.17%), and upper back (13.29%). There was a significant statistical difference between frontline industrial workers and other staff in the prevalence of self-reported symptoms involving the shoulders (χ = 4.33, P = 0.037), wrists and hands (χ = 8.90, P = 0.003), and ankles and feet (χ = 12.88, P < 0.001). Increased age (P = 0.005, OR = 1.63; P = 0.001, OR = 2.33), a high or a low salary (P < 0.001, OR = 0.49; P < 0.001, OR = 0.30), night-shift (P = 0.027, OR = 1.46), two-week-history of illness and treatment (P = 0.004, OR = 5.60; P = 0.013, OR = 4.19), concurrent chronic diseases (P = 0.001, OR = 3.45; P = 0.092, OR = 7.81), limited access to health information (P = 0.004, OR = 0.49), and negative attitude towards seeking healthcare (P = 0.010, OR = 1.77; P = 0.009, OR = 2.75) were associated with MSDs in frontline workers. Female gender (P < 0.001, OR = 2.30), high education (P = 0.001, OR = 1.96), no exercises (P = 0.027, OR = 0.59), night-shift (P = 0.017, OR = 1.98), concurrent chronic diseases (P = 0.002, OR = 3.73; P = 0.020, OR = 13.42), limited access to health information (P = 0.013, OR = 0.53), far distance to medical institution (P = 0.009, OR = 1.83), and negative propensity (P = 0.009, OR = 1.94; P = 0.014, OR = 2.74) were associated with MSDs in other staffs.
Conclusions: The prevalence of MSDs among industrial employees has changed. Frontline workers had different prevalence and risk factors for MSDs compared with other employees. Negative propensity to healthcare, limited ways to obtain health knowledge, and concomitant chronic diseases were associated with MSDs. Surprisingly, highly educated and high-income employees had a higher risk of MSDs.
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