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Ergonomic exposure is one of the important causes of work-related musculoskeletal disorders (WMSDs). Accurate measurement and evaluation of ergonomic exposure level and implementation of ergonomic intervention are of great significance to the prevention and control of WMSDs. Ergonomic exposure can be divided into external exposure and internal exposure, and its evaluation methods include subjective judgment method, systematic observation method, and direct measurement method. This paper summarized the internal exposure assessment methods based on musculoskeletal dynamics and biomarkers, introduced the overall design concept of ergonomic exposure assessment system, used the Ergonomic Assessment Worksheet (EAWS) as an example, and discussed the development trend of automation, intelligence, and compounding of ergonomic exposure assessment methods and the factors considered in the selection of ergonomic exposure assessment methods.

BackgroundChina's manufacturing industry is still labor-intensive, and assembly employees in manufacturing industry are facing a great risk of work-related musculoskeletal disorders (WMSDs). ObjectiveTo investigate and analyze the prevalence and distribution of WMSDs among assembly workers in manufacturing enterprises and explore the relationship between WMSDs and ergonomic exposure factors such as posture load and mental load. MethodsFrom July to September 2017, by convenient sampling, a cross-sectional survey was conducted to select 670 workers engaged in electronic accessories assembly and railway vehicle manufacturing in three manufacturing enterprises in two cities in northern China as the research participants. The posture load assessment was based on the Chinese Musculoskeletal Questionnaire independently developed by our research group. The mental load assessment was based on a revised Chinese version of the Subjective Workload Assessment Technique. An unconditional logistic regression model was used to explore the relationship between ergonomic exposure and WMSDs. ResultsThe overall prevalence rate of WMSDs was 39.6% (265/670) with 43.8% in males and 25.2% in females; the highest prevalence rate was 47.7% in the group aged 40 years and over. The prevalence rate of WMSDs in the electronic accessories assembly workers was 16.9%, that in the railway vehicle manufacturing workers was 57.3%, and the difference was statistically significant (\begin{document}$ {\chi ^2} $\end{document}=112.63, P

BackgroundThe prevalence rate of work-related musculoskeletal disorders (WMSDs) among manufacturing workers is relatively high and has been widely concerned. However, research on the prevalence and risk factors of multi-site WMSDs is still insufficient. ObjectiveTo explore the prevalence and risk factors of multi-site WMSDs of assembly workers in four manufacturing enterprises. MethodsThe "Chinese Musculoskeletal Questionnaire" was used to conduct a cross-sectional survey among 1401 assembly workers selected by convenient sampling in four manufacturing enterprises, and their demographic characteristics, the prevalence of WMSDs in various body parts, and the information about biomechanical factors, work organizations, work environment, and psychosocial factor exposure were collected. The prevalence of WMSDs and multi-site WMSDs were estimated, Pearson χ2 test was used for univariate analysis of multi-site WMSDs risk factors, and logistic regression was used for multi-factor analysis. ResultsThe total prevalence rate of WMSDs was 54.9% (769/1 401). The top three affected sites were neck (41.4%), shoulders (30.7%), and wrist/hand (25.1%). The prevalence rate of multi-site WMSDs was 41.9% (587/1 401). The prevalence rates of multi-site WMSDs in railway vehicle assembly and riveting workers were higher than those in electronic parts processing and glass manufacturing workers (P

BackgroundMusculoskeletal disorders (MSDs) are critical occupational and social problems. With the improvement of production mechanization and automation, and the widespread application of computers, more occupations are exposed to static postures and load. This study explored the role of inflammation in the association between static postures exposure and MSDs.MethodsThis study adopted a prospective nested case-control design in which 66 lower back MSDs cases and 66 healthy controls were selected from a cohort study of university employees. The personal information, postural load, musculoskeletal symptoms, pressure pain thresholds (PPTs), and inflammatory cytokines were collected. Logistic and linear regressions were used to investigate the association among postural load, inflammatory cytokines, and lower back MSDs. Mediation analysis was used to calculate the mediation effect.ResultsThe results of logistic and linear regressions showed that postural load and inflammatory cytokines were positively associated with lower back MSDs (P < 0.05), and postural load was positively associated with inflammatory cytokines (P < 0.05). Further, mediation analysis showed that the mediation effect of postural load on the lower back MSDs through TNF-α was 0.073 (95%CI: 0.025–0.128), and the mediation effect of posture load on the lower back MSDs through IL-6 was 0.098 (95%CI: 0.041–0.179), respectively.ConclusionStatic postures were associated with the occurrence of MSDs through inflammatory cytokines, and low-level inflammation may be a critical early event in the generation of MSDs. This study may help bridge the gap of potential mechanisms linking static postures to increased risks of MSDs, and provide new evidence for targeted protection against the global increasing MSDs.

Previous studies have shown the correlation between p-STAT3 overexpression and prognosis in a variety of human tumors. However, their correlation in lung cancer remains controversial. We performed a systematic review and meta-analysis to explore the correlation between p-STAT3 overexpression and prognosis in lung cancer patients.We searched PubMed, Embase, Web of Science, CNKI, VIP, and WanFang Data to identify relevant studies. Two reviewers independently screened the literature search results, extracted data, and assessed the methodological quality of the included studies. Then, meta-analysis was performed by using Review Manager 5.3 and STATA 14 software. A random-effect model was employed to evaluate all related pooled results. Statistical heterogeneity of each study was assessed by I2. Publication bias was determined by funnel plot and the Begg's or Egger's tests.Eventually, 13 studies were included in present meta-analysis. Among these 13 studies, 8 studies were associated with the overall survival of lung cancer and 10 studies with other clinicopathological characteristics. The results of this meta-analysis suggested that p-STAT3 overexpression may be a poor prognosis biomarker in lung cancer (HR: 1.23; 95% CI: 1.04-1.46; P = 0.02). In terms of other clinicopathological characteristics, p-STAT3 overexpression was more frequent to advanced TNM stages ranging from III to IV (OR: 1.92; 95% CI: 1.13-3.27; P = 0.02) and lymphatic node metastasis (OR: 1.81; 95% CI: 1.20-2.72; P = 0.004). But, it was not associated with tumor differentiation (OR: 0.82; 95% CI: 0.44-1.53; P = 0.54).p-STAT3 overexpression has significant correlation with poorer overall survival of lung cancer patients, as well as with more advanced TNM stages and lymph node metastasis. Thus, it may serve a biomarker for poor prognosis in lung cancer. Nevertheless, our findings should be confirmed by large prospective studies.