Yimin Liu

Objective: This study aims to investigate the one-year prevalence and the associated factors of work-related musculoskeletal disorders (WMSDs) among furniture manufacturing workers in Guangdong, China. Methods: A cross-sectional study of 4181 (2953 males and 1228 females) furniture manufacturing workers was conducted between September 2019 and December 2019. All information about WMSDs was collected by the electronic version of Chinese Musculoskeletal Questionnaires (CMQ). Descriptive statistics and a binary logistic regression model were used to interpret the data. Result: The overall prevalence of WMSDs was 31.57%. The WMSD symptoms most commonly occurred in the neck (16.77%), followed by the shoulders (14.90%), ankles/feet (14.64%), hands/wrists (13.30%), upper back (11.48%), and lower back (10.95%). Multiple logistic regression analysis revealed that several individual, labor organization, and ergonomics-related factors conferred significant risks to WMSDs at different body sites. Conclusions: WMSDs remain the major occupational health problem for furniture manufacturing workers. Hence, some effective and feasible protective measures for furniture manufacturing workers are required in order to alleviate the health burden caused by WMSDs.

We analyzed the lead levels in blood and urine from lead-exposed workers in Guangzhou and assessed the influencing factors. The data were analyzed by descriptive statistics, and the time-dependent changes were mapped via analytical statistics. Although the lead burden showed a clear downward trend over time, it remained high among the exposed workers. The highest lead burden was detected in workers of the electrical equipment manufacturing industry, especially among those in lead-acid battery factories where we did field studies. Hazardous as the working conditions of the original lead-acid battery factories were, there were improvements in the applications of occupational disease prevention measures after the relocation of factories, but the lead burdens were still above the average levels of lead-related industries. Improvements are needed in the management and regulations on occupational safety and health to further decrease the lead burden to acceptable levels.

In this paper, the hazard factors of an optical enterprise were analyzed, and the appropriate prevention and control measures were discussed. The field investigation and detection of occupational health was applied. The on spot monitoring results showed that the over-standard rate of acetone in the workplace was 10.0%, the over-standard rate of trichloroethylene was 25.0%, the over-standard rate of dichloromethane was 50.0%, and the over-standard rate of noise was 23.8%. Acetone, trichloroethylene, dichloromethane and noise were the key points of prevention and control in this optical enterprise. It was suggested that the ventilation system of the cleaning workshop should been improved comprehensively, and the workers’ hearing protection measures should been increased to effectively protect their health.

To evaluate the association between ambient air pollution and hyperuricemia, we prospectively followed 1748 traffic police officers without hyperuricemia at baseline (2009–2014) from 11 districts in Guangzhou, China. We calculated six-year average PM₁₀, SO₂ and NO₂ concentrations using data collected from air monitoring stations. The hazard ratios for hyperuricemia per 10 µg/m³ increase in air pollutants were 1.46 (95% CI: 1.28–1.68) for PM₁₀, 1.23 (95% CI: 1.00–1.51) for SO₂, and 1.43 (95% CI: 1.26–1.61) for NO₂. We also identified changes in the ratio of serum uric acid to serum creatinine concentrations (ua/cre) per 10 µg/m³ increase in air pollutants as 11.54% (95% CI: 8.14%-14.93%) higher for PM₁₀, 5.09% (95% CI: 2.76%-7.42%) higher for SO₂, and 5.13% (95% CI: 2.35%-7.92%) higher for NO₂, respectively. Long-term exposure to ambient air pollution was associated with a higher incidence of hyperuricemia and an increase in ua/cre among traffic police officers.

To explore the application of the gray series model GM (1, 1) in predicting trends in the incidence of pneumoconiosis and evaluate its degree of predicted precision. Analyzing the incidence of pneumoconiosis in this region from 2009 to 2013, and predicting the incidence of pneumoconiosis of the area in 2014-2016 by establishing GM (1, 1) according to the gray system theory. Using occupational pneumoconiosis population data from 2009 to 2013, to establish GM (1, 1) model: yt = 1396.89e(0.12(t-1)), α = -0.12, µ = 147.2. The pneumoconiosis in 2014, 2015, 2016 were predicted respectively 51, 47, 43 cases based on the GM (1, 1) model, and C value of model is 0.15, P value is 1, all of them meet the requirements of model predictions. It shows the cases of pneumoconiosis are rising significantly. GM (1, 1) model can be used to predict the recent trend in the incidence of pneumoconiosis.