Zhongxu Wang

Work-related musculoskeletal disorders (WMSDs) show a rapid growth trend. It has brought a huge economic burden to the society and become a serious occupational health problem that needs to be solved urgently. This study aimed to analyze the local muscle response under continuous ergonomic load, screen sensitive fatigue-related biomarkers and provide data support for the early prevention of local muscle damage and the exploration of early warning indicators. Thirteen male college student volunteers were recruited to perform simulated repetitive manual lifting tasks in the laboratory. The lifting task was designed for 4 periods which lasted for 12 min in each, and then paused for 3 min for sampling. Local muscle fatigue is assesed by the Rating of perceived exertion (RPE) and the Joint analysis of sEMG spectrum and amplitude (JASA). Elbow venous blood was collected and 14 kinds of biomarkers were analyzed, which included Metabolic markers Ammonia (AMM), Lactic acid (LAC), Creatine kinase (CK), Lactate dehydrogenase (LDH), Cartilage oligomeric matrix protein (COMP), C-telopeptide of collagen I and II (CTX-I, CTX-II) and Calcium ion (Ca2+); Oxidative stress marker Glutathione (GSH); Inflammatory markers C-reaction protein (CRP), Prostaglandin E2 (PG-E2), Interleukin-6 (IL-6) and Tumor necrosis factor α (TNF-α); Pain marker Neuropeptide Y (NPY). Repeated measures analysis of variance (Repeated ANOVA), linear regression analysis, t-test and spearman correlation analysis were used to analyze the data. Both subjective and objective fatigue appeared at the same period. Serum AMM, LAC, CK, LDH, COMP, CTX-II, Ca2+ and NPY after fatigue were significantly higher than those before fatigue (p < 0.05). There was a certain degree of correlation between the markers with statistical differences before and after fatigue. Metabolic markers (serum AMM, LAC, CK, LDH, COMP, CTX-II, Ca2+) and pain markers (serum NPY) can reflect local muscle fatigue to a certain extent in repetitive manual lifting tasks. It is necessary to further expand the research on fatigue-related biomarkers in different types of subjects and jobs in the future.

Although studies have shown that work-related musculoskeletal disorders (WMSDs) are common and continue to be a major source of disability and work time loss, there are few reports about elbow WMSDs. The aim of this study was to explore the prevalence and associated factors of elbow WMSDs. The valid questionnaires of 57501 workers from 15 different industries nationwide were collected and the c² test and logistic regression analysis were applied to reveal the prevalence and risk factors of elbow WMSDs. The findings indicated that the overall prevalence of elbow WMSDs among workers was 7.3%. However, the prevalence of elbow WMSDs in toy manufacturing was 21.3%, which was significantly higher than that in other industries (P < .05). Logistic regression analysis showed that age 40 and above, married, very poor health, left-handedness, lifting weights (more than 20 kg each time), work requiring upper limb or hand force, work in an uncomfortable position, repetitive operations within 1 minute, using vibrating tools, work involving cold, cool draughts, or temperature changes, work being completed in the same workshop, work being done outdoors, frequent dealings with customers, 2 shifts, often working overtime, staff shortage, and often working for colleagues were risk factors for elbow WMSDs. A higer education level, monthly income, and enough rest time were protective factors for elbow WMSDs. Toy manufacturing is a high-risk industry for elbow WMSDs. Promotion of education about ergonomics should be strengthened, and workers’ ergonomics awareness should be improved to reduce the impact of WMSDs.

We investigated the prevalence of work-related musculoskeletal symptoms (WMSs) among medical staff and evaluated the associations of different levels of adverse ergonomic factors with WMSs. A total of 6099 Chinese medical staff were asked to complete a self-reported questionnaire to assess the prevalence and risk factors of WMSs from June 2018 to December 2020. A prevalence rate of 57.5% was observed for WMSs among overall medical staffs, which mainly affected the neck (41.7%) and shoulder (33.5%). “Keeping sitting for long hours very frequently” (OR = 1.26, 95% CI: 1.04, 1.53) was positively associated with WMSs in doctors, while “keeping sitting for long hours occasionally” (OR = 0.91, 95% CI: 0.85, 0.97) was identified as a protective factor of WMSs in nurses. The associations of adverse ergonomic factors, organizational factors, and environmental factors with WMSs were different among medical staff in different positions. We conducted a multi-city study concerning the risk factors of WMSs by carrying out a face-to-face one-to-multiple questionnaire survey among medical staff in China. As a risk factor of WMSs in medical staff, adverse ergonomic factors should be paid more attention by the standard setting department and policy makers.

Objectives: To describe the prevalence of self-reported musculoskeletal disorders among workers in the electronics manufacturing industry and to investigate the relations between work-related musculoskeletal disorders (WMSDs) and work-related variables.Methods: An interview-based questionnaire survey was carried out in thirty electronics manufacturing factories in China in 2018. The prevalence of WMSDs was estimated using the modified Nordic Musculoskeletal Questionnaire (NMQ). A multivariate logistic regression model was applied to evaluate the effects of risk factors on WMSDs on multiple body parts.Results: The 12-month prevalence of WMSDs among participants was 40.6%, and the common body sites affected were the neck (26.8%), shoulder (22.8%), upper back (14.9%), and lower back (14.8%). The results of logistic regression showed that female adults, > 5 job tenure and work-related factors (including awkward posture, lifting or carrying weights, excessive repetition, prolonged sitting, monotonous work and working under conditions of cold or temperature variations) led to a higher risk of WMSDs on most body parts. Upper back, wrist/hand and elbow pain levels were significantly higher for workers with vibration. However, more frequently, physical exercise was a protective factor against WMSDs on most body parts except the upper back, leg and knee.Conclusions: The study indicates a high prevalence of musculoskeletal pain among the electronics manufacturing industry in China. Different personal and work factors are related to the occurrence of WMSD on different body parts. Preventive measures should be implemented based on the characteristics of WMSD in the electronic manufacturing industry. Furthermore, the training and intervention guidance of ergonomic hazards in the workplace need to be strengthened by understanding the impact of bad posture, avoiding long-term sitting posture and increasing physical activities.

Background: With the development of the electronics manufacturing industry, the demand for human resources has increased, which has also led to the frequent occurrence of multi-site work-related musculoskeletal disorders. Method: The participants (n = 7307) were recruited from 30 enterprises in China in 2018. The prevalence of musculoskeletal disorders was estimated using a modified Chinese version of the Musculoskeletal Disorders Questionnaire. The multivariate logistic regression model was applied to evaluate the effects of risk factors on multi-site musculoskeletal symptoms. Additionally, the log-binomial model was established to examine the correlation between the various sites of musculoskeletal symptoms in the body. Results: The 12-month prevalence of musculoskeletal symptoms among participants was 40.6%. The proportion of musculoskeletal symptoms involving single-site and 2/>2 body sites were 11.6% and 29.0%, respectively. The results of logistic regression showed that female adults who smoked, had >5-year job tenure, and always stood or sat for long period at work had a higher risk in 2/>2 body sites of musculoskeletal symptoms (p < 0.05). However, physical exercise during leisure time and “Squatting or kneeling for long period at work” were more frequently protective factors. Furthermore, the log-binomial model indicated that the neck and shoulder were significantly related to each other (Prevalence Ratio, PR: 5.511 and 7.017). Conclusions: Several demographic characteristics and work-related factors were associated with multi-site musculoskeletal symptoms in the electronics manufacturing industry in China. Improving the levels of physical exercise and reducing posture problems and force loads may help to promote the health of workers.

Background: With the acceleration of industrialization and population aging, low back pain (LBP) has become the leading cause of life loss years caused by disability. Thus, it places a huge economic burden on society and is a global public health problem that needs urgent solution. This study aimed to conduct an epidemiological investigation and research on a large sample of workers in key industries in different regions of China, determine the incidence and distribution characteristics of LBP, explore the epidemic law, and provide a reference basis for alleviating global public health problems caused by LBP.Methods: We adopted a modified epidemiological cross-sectional survey method and a stratified cluster sampling method. All on-duty workers who fulfill the inclusion criteria are taken as the research participants from the representative enterprises in key industries across seven regions: north, east, central, south, southwest, northwest, and northeast China. The Chinese version of the musculoskeletal disease questionnaire, modified by a standardized Nordic questionnaire, was used to collect information, and 57,501 valid questionnaires were received. Descriptive statistics were used, and multivariate logistic regression analysis (p < 0.05) was performed to explore the association between musculoskeletal disorders and potential risk factors.Results: LBP annual incidence among workers in China’s key industries is 16.4%. There was a significant difference in LBP incidence among occupational groups across different industries (p < 0.05). The multivariate regression model showed the following as risk factors for LBP: frequent repetitive movements with the trunk, working in the same positions at a high pace, trunk position, frequently turning around with your trunk, often working overtime, lifting heavy loads (i.e., more than 20 kg), education level, staff shortage, working age (years), cigarette smoking, use of vibration tools at work, body mass index, lifting heavy loads (i.e., more than 5 kg), and age (years). Physical exercise, often standing at work, and absolute resting time were protective factors.Conclusion: LBP incidence among key industries and workers in China is high. Thus, it is urgent to take relevant measures according to the individual, occupational, and psychosocial factors of LBP to reduce the adverse impact of LBP on workers’ health.

What is already known about this topic? The burden of illness and economic losses due to upper-limb work-related musculoskeletal disorders (UL-WMSDs) is high; thus, they have become a major global public health problem. At present, the epidemiological characteristics of UL-WMSDs in China's occupational population are still unknown. What is added by this report? The incidence of UL-WMSDs among key occupational groups in China is 22.5%, with distinct occupational characteristics. What are the implications for public health practice? This study has primarily determined the occurrence and potential risk factors of UL-WMSDs in key industries in China and provided data support for recommending prevention and control of the occurrence of such diseases in key industries in China, and in facilitating the addition into the China’s List of Legal Occupational Diseases.

Background: With the acceleration of industrialization and the growth of population aging, LBP has become the main disease of life loss caused by disability, which brings huge economic burden to society and is a global public health problem that needs to be solved urgently. The purpose of this study is to carry out epidemiological investigation and research on a large sample of people in key industries in different regions of China, to find out the incidence and distribution characteristics of LBP in key industries in China, to explore the epidemic law, and to provide reference basis for alleviating the global public health problems caused by LBP.Methods: This study adopts the modified epidemiological cross-sectional survey method and the stratified cluster sampling method. From the representative enterprises in key industries in seven regions of North China, East China, central China, South China, southwest, northwest and Northeast China, all workers on duty and fulfill the criteria are taken as the research objects. The Chinese version of musculoskeletal disease questionnaire modified by a standardized Nordic Questionnaire was used to collect information, and a total of 57501 valid questionnaires were received. Descriptive statistics were used and multivariate logistic regression analysis (p < 0.05) was performed to explore the associations between musculoskeletal disorders and potential risk factors.Results: The annual incidence of LBP in key industries or workers in China is 16.4%. There was significant difference in the incidence of LBP among occupational groups in different industries (P < 0.05). The results of multivariate regression model show that always make the same movements with your trunk, working in the same positions at a high pace, trunk position, always turn round with your trunk, often work overtime, lift heavy loads (more than 20 kg), education level, staff shortage, working age (years), cigarette smoking, use vibration tools at work Body mass index (BMI), lift heavy loads (more than 5 kg) and age (years) were risk factors for LBP. Physical exercise, standing often at work and absolute resting time are protective factors.Conclusion: The incidence of LBP in key industries or workers in China is high. It is urgent to take relevant measures according to individual, occupational and psychosocial factors of LBP to reduce the adverse impact of LBP on workers' health.

What is already known about this topic? In recent decades, work-related musculoskeletal disorders (WMSDs) have become increasingly prominent and have become an important issue that is of universal concern and an urgent need to be solved in all countries of the world. What is added by this report? The top three industries or occupational groups with the highest standardized prevalence rate of WMSDs were flight attendants, medical staff, and vegetable greenhouses in that order. Women workers were 1.5 times more likely to suffer from WMSDs than men workers. What are the implications for public health practice? This study has found the prevalence and distribution characteristics of WMSDs in key industries in China. It is urgent to draw up relevant measures to prevent and control occupational populations with WMSDs.

The Chinese government has taken strong prevention and control measures to fight against the spread of coronavirus disease 2019 (COVID-19), such as promoting public awareness of disease prevention, stopping large gatherings, wearing masks, etc., to reduce the risk of human infection The source of COVID-19 infection is mainly novel coronavirus infected patients. Asymptomatic infected persons can also become the sources of infection. Respiratory droplets and close contact transmissions have been regarded as the main routes of transmission. There is also a possibility of aerosol transmission in a relatively closed environment for a longer exposure time. Other routes of transmission need to be clarified. The whole population is susceptible (National Health Commission of the PRC, 2020.3.7). Among all control measures, respiratory protection plays a key role in prevention and control of COVID-19. Based on the characteristics of different population groups, the Chinese Center for Disease Control and Prevention (CCDC) has issued recommendations and guidance on respiratory protection against COVID-19.