中华劳动卫生职业病杂志最新文献

Objective: To explore the effects of clinical ergonomics theoretical training combined with clinical chairside operation guidance strategy on the incidence of pain symptoms of work-related musculoskeletal disorders (WMSDs) among dentists. Methods: A total of 80 dentists working in the Stomatology Department of the First Medical Center of the Chinese PLA General Hospital from June 2023 to December 2023 were selected as the study objects by random simply sampling method. And the objects were separated into the control group (40 persons) and the experimental group (40 persons). The control group didn't get any special intervention, and the experimental group had half a year of training in clinical ergonomics and guidance on clinical chairside operation. The WMSDs cognitive level and symptom incidence of dentists in two groups were measured by questionnaire, and the intensity of pain symptom of WMSDs was compared by visual analogue scale (VAS). The count date was compared using χ(2) test. For measurement data that followed a normal distribution and met the homogeneity of variance requirement, independent samples t-test was used for intergroup comparison. For measurement data that followed a normal distribution but exhibited unequal variances, the corrected t-test was conducted for intergroup comparison. Results: The cognitve rates of dentists in the experimental group regarding WMSDs symptoms, affected areas, influencing factors, and preventive measures reached 90.0% (36 dentists), 87.5% (35 dentists), 80.0% (32 dentists), and 82.5% (33 dentists), respectively. The incidences of WMSDs in the neck and shoulder of the experimental group were lower than those of the control group (P<0.05). Furthermore, the VAS scores indicated that the intensity of WMSDs pain symptoms in the neck, shoulder, hands/wrists and lower bock/waist of dentists in the experimental group were significantly lower than those of the control group (P<0.05) . Conclusion: Strengthening the clinical ergonomics education and training for dentists is conducive to lowering the incidence of WMSDs, mitigating the severity of symptoms, and preserving the physical health of dentists.

Objective: To explore the influencing factors of pulmonary tuberculosis in occupational pneumoconiosis patients in China. Methods: In February 2025, through the CNKI, Wanfang, VIP databases, and PubMed, MedLine, Web of Science, and Embase databases (established up to February 25, 2025), we screened literature on the influencing factors of occupational pneumoconiosis patients with pulmonary tuberculosis in China. Fixed effect or random effect models were selected to analyze the impact of 10 factors (gender, body mass index, smoking, onset age, occupation, pneumoconiosis stage, dust exposure duration, dust exposure years, dust exposure age, and contact history with tuberculosis patients) on occupational pneumoconiosis patients with pulmonary tuberculosis in China. I(2) and Cochran's Q tests were used to assess heterogeneity, and random effect models (P<0.10, I(2)>50%, indicating heterogeneity) or fixed effect models (P≥0.10, I(2)≤50%, indicating no heterogeneity) were chosen based on the degree of heterogeneity. Results: A total of 13 high-quality Chinese and English literatures meeting the requirements were included, and a total of 1792 Chinese occupational pneumoconiosis patients with pulmonary tuberculosis were included. Gender (OR=1.06, 95%CI: 1.02-1.10), smoking (OR=1.40, 95%CI: 1.01-1.94), stage of pneumoconiosis (OR=1.99, 95%CI: 1.43-2.78), age of exposure to dust (OR=0.45, 95%CI: 0.26-0.78), age of exposure to dust (OR=1.40, 95%CI: 1.01-1.94) were influencing factors in occupational pneumoconiosis complicated with pulmonary tuberculosis (P<0.05). There was no significant heterogeneity in literatures that analysis of gender, smoking. There was significant heterogenity in literatures that analysis of stage of pneumoconiosis, age of exposure to dust, age of exposure to dust. Gender, stage of pneumoconiosis and age of exposure to dust were included in the research literatures with good robustness. The results of smoking, age of exposure to dust, and included literatures were not robust. Egger test suggest that there was no significant publication bias. Conclusion: High stage of pneumoconiosis, long age of exposure to dust, history of smoking, and long age of exposure to dust are all risk factors for pulmonary tuberculosis in occupational pneumoconiosis patients in China.

Objective: To investigate the factors influencing work-related musculoskeletal disorders (WMSDs) among fire rescue personnel and evaluate the effectiveness of a multidimensional intervention approach, in order to provide scientific evidence for the prevention of WMSDs among fire rescue personnel. Methods: A random sampling method was adopted. From March to November 2022, 5119 fire rescue personnel from 10 administrative districts of a certain city were investigated as the baseline research subjects. From March to November 2023, a "comprehensive multidimensional intervention combining prevention and treatment" was implemented on 2353 of these fire rescue personnel. The revised "Musculoskeletal Disorders Questionnaire" was used to investigate the occurrence of WMSDs symptoms before and after the intervention. Multivariable logistic regression model was used to analyze the association between occupational factors, psychosocial factors, and the risk of WMSDs. McNemar's test was employed to compare the incidence of WMSDs and absenteeism rate caused by WMSDs among fire rescue personnel before and after the interventions. Results: Being married was a risk factor for both single-site and overall WMSDs (P<0.05). Smoking emerged as a risk factor for overall WMSDs, while ceasing smoking was deemed a protective factor against single-site and multi-site WMSDs (P<0.05). Work tenure≥5 years was identified as a risk factor for multi-site WMSDs (P<0.05). Additionally, weekly working hours ≥49 hours, frequency of outdoor duties ≥once a week, occupational stress, and negative emotions during working outside were recognized as risk factors for both multi-site WMSDs and overall WMSDs (P<0.05). Prior to the intervention, the incidence rates for single-site, multi-site, and overall WMSDs were 12.28% (289/2353), 32.51% (765/2353), and 44.79% (1054/2353), respectively. The absenteeism rates caused by single-site, multiple-site, and overall WMSDs were 2.93% (69/2353), 8.84% (208/2353), and 11.77% (277/2353), respectively. After the multidimensional intervention, the incidence rates of WMSDs in the neck, shoulders, back, elbows, waist, wrists, hips, knees, ankles, multiple-site, and overall WMSDs among the fire rescue personnel, as well as the absenteeism rates caused by WMSDs in the aforementioned body regions, all decreased significantly (P<0.05) . Conclusion: Marital status, smoking status, weekly working hours, seniority, outdoor duty frequency, occupational stress, and negative emotions of fire rescue personnel may be important factors influencing the occurrence of WMSDs. A multidimensional intervention approach, incorporating initiatives such as awareness campaigns, health education, psychological well-being interventions, and exercise rehabilitation interventions, can effectively reduce the incidence of WMSDs and the resulting absenteeism rates among fire rescue personnel.

Objective: To analyze the risk factors of occupational stress among female coal miners and construct a risk prediction model. Methods: In July 2023, a cluster sampling method was conducted to select all female workers on duty at a large coal mine in Gansu Province during a specific period (totaling 1437 individuals) as research subjects. Occupational stress levels were assessed through questionnaire surveys. A total of 1435 valid questionnaires were collected, with an effective recovery rate of 99.86%. Single-factor analysis was conducted using the rank sum test, while multiple linear regression models was used for multivariate analysis. Deep learning models, including XGBoost and LightGBM, were constructed to analyze factors influencing occupational stress among female coal miners. The performance of the optimal XGBoost model was further explained using the Shapley additive explanatory (SHAP) algorithm. Results: Among the 1435 female coal miners, 89 cases (6.2%) had no occupational stress (score ≤20 points); 930 cases (64.8%) had mild occupational stress (scores 21-30 points); 405 cases (28.2%) had moderate occupational stress (scores 31-40 points); and 11 cases (0.8%) had severe occupational stress (scores 41-50 points). Educational level, marital status, annual personal income, physical exercise, job type, average weekly working time, work form, work position, exposure to noise and noise intensity, heavy labor, coal dust exposure, exposure to occupational hazards and exposure time, injury or infringement during work, and whether to wear protective equipment were influencing factors affecting the occupational stress of female coal miners (P<0.05). For the XGBoost model on the test set, the coefficient of determination (R(2)), mean squared error (MSE), and root mean squared error (RMSE) were 0.994, 0.152, and 0.390, respectively, which were better than LightGBM's 0.933, 1.692, 1.301 and the multiple linear regression model's 0.268, 18.408, and 4.290. The SHAP results showed that work position and daily household chores were the main factors affecting the occupational stress of female coal miners. In addition, physical exercise, work-related injuries or violations, and coal dust exposure also had a certain impact on occupational stress. Conclusion: The occupational stress of coal miners is the result of the combined effects of occupational and lifestyle factors. The XGBoost model demonstrates superior predictive ability and proves the feasibility of the SHAP algorithm in analyzing the occupational stress of female coal miners using machine learning models.

Objective: To understand the noise hazard levels at mining industry workplaces to provide a scientific basis for occupational disease prevention policies. Methods: The monitoring result data on occupational hazard factors in the workplace for 2023 were obtained from the National Surveillance System for Occupational Hazards during September to October 2024. Descriptive analysis was then conducted on the noise exposure results at workplace positions in mining industry enterprises, categorized by industry type, geographical distribution, enterprise size, economic type, and key positions. Noise levels at workplace positions were expressed as M (Q(1), Q(3)). The Kruskal-Wallis and Mann-Whitney U tests were used to compare noise levels between groups, while noise exposure exceedance rates were compared using the χ(2) test or Fisher's exact test. Results: A total of 8417 enterprises in the mining industry were monitored, with the non-metallic mining and beneficiation industry constituting the majority at 41.6% (3503/8417). Regionally, enterprises in North China and Southwest China dominated, accounting for 24.0% (2019/8417) and 21.9% (1843/8417) respectively. Small-sized enterprises were the primary type, accounting for 51.4% (4322/8417). In terms of economic types, limited liability companies dominated, accounting for 60.2% (5072/8417). The metal mining and beneficiation industry exhibited the highest noise exposure exceedance rate, at 39.5% (2698/6833), with the drilling position showing an exceptionally high rate of 81.7% (508/622). Northwest China and East China showed higher noise exceedance rates, at 34.8% (1331/3823) and 31.7%(1550/4893) respectively. The small-sized enterprises exhibited the highest exceedance rate of noise exposure, at 28.0% (4328/15476). In metal mining and beneficiation industry, the exceedance rate and the median of noise levels among large and medium-sized enterprises were 41.8% (665/1592) and 84.2 dB (A), respectively, both higher than those among small and micro-sized enterprises[38.8% (2033/5241) and 83.7 dB (A) ] (P<0.05). State-owned enterprises exhibited the lowest workplace noise exceedance rate at 20.1%. Statistically significant differences were found in workplace noise exceedance rates and median noise levels among different industries, regions, enterprise sizes, economic types, and key positions (P<0.05) . Conclusion: The situation of noise hazards in China's mining industry remain severe. Effective workplace noise control in the mining industry should be strengthened to reduce noise exposure at workplace positions and truely safeguard the occupational health of workers.

Objective: Meta-analysis was performed to determine the influencing factors on the progression of pneumoconiosis, providing a basis for optimizing prevention and treatment strategies for pneumoconiosis. Methods: The research date was from April 10(th), 2025 to May 5(th), 2025, PubMed, Embase, Web of Science, CNKI, VIP Chinese Science and Technology Journal Database, Wanfang and other Chinese and English databases were searched, and the search time was from the establishment of the database to April 19(th), 2025. A combined search method of subject terms and free terms was adopted to collect research on the influencing factors of the progression of pneumoconiosis. Based on the results of the heterogeneity test, a fixed-effect model or a random-effect model was selected for analysis, and the sources of heterogeneity were explored through subgroup analysis. Results: Sixteen articles were included, encompassing 20 related risk factors. Meta-analysis results showed that the stage of pneumoconiosis (OR=2.85, 95%CI=2.15-3.77), duration of dust exposure (OR=1.77, 95%CI=1.34-2.33), smoking (OR=2.47, 95%CI=1.40-4.35), comorbidities (OR=1.73, 95%CI=1.35-2.21), age at onset (OR=1.78, 95%CI=1.21-2.61), and protective measures (OR=0.74, 95%CI=0.63-0.86) were all influencing factors for the progression of pneumoconiosis (P<0.05). Body mass index and age were not significantly associated with the progression of pneumoconiosis (P>0.05) . Conclusion: The influencing factors of pneumoconiosis progression include smoking history, stage of pneumoconiosis, duration of dust exposure, comorbidities, age at onset, protective measures. Among them, stage of pneumoconiosis showing the strongest association with the progression of pneumoconiosis.

Potassium methylsilanetriolate is an organic silicon waterproofing agent widely used in the construction industry. It can be obtained by the reaction of methyltrichlorosilane with water and potassium hydroxide, and the solution is a colorless or light yellow transparent liquid with a pH of 12-13. This article shares the diagnosis and treatment process of one case of accidental ingestion of potassium methylsilanetriolate, in order to supplement and improve treatment experience. This case suggests that gastric lavage and blood perfusion are both treatment options for patients with digestive tract chemical injuries who have mistakenly taken strong alkalis. The provision of medical history and reasonable dietary adjustments are particularly important for treatment.

Objective: To tracked and analyze the follow-up diagnosis of suspected occupational noise-induced deafness (ONID) patients in an occupational disease diagnosis institution in Guangzhou City from 2020 to 2024. Methods: In December 2024, a retrospective survey method was used to track the reporting, medical consultation, and diagnosis status of suspected ONID patients, as well as to analyze the influencing factors for the confirmation of suspected ONID as ONID. Rate comparisons were conducted using Pearson's χ(2) test or Fisher's exact test for univariate analysis, while related influencing factors were analyzed using multivariate logistic regression analysis. Results: Occupational health examination was the most important reporting channel of ONID, and the tracking results showed that the number of confirmed cases, exclusion, incomplete diagnosis and non-treatment accounted for 29.58% (21/71), 32.39% (23/71), 5.63% (4/71) and 32.39% (23/71), respectively. Among the 71 suspected cases, 44 entered the diagnostic procedure and completed the diagnosis, and 21 were finally diagnosed, the diagnosis rate was 47.73% (21/44). There was a statistically significant difference in the confirmed diagnosis rate among patients with different noise exposure working years, better weighted values of auditory threshold, and whether the re-examination interval was standardized or not (P<0.05). Multivariate logistic regression analysis revealed that the length of noise-exposed working years and the standardized time interval for re-examination were the influencing factors for the final diagnosis of ONID in patients with suspected ONID (OR=0.28, 95%CI: 0.08-0.93; OR=14.92, 95%CI: 2.64-84.39; P<0.05) . Conclusion: Micro-sized enterprises are key monitoring targets for suspected ONID. Diagnosing physicians should strengthen management of non-standard re-examination intervals, emphasizing the scientific rigor and accuracy in diagnosing patients with suspected ONID.

Objective: To grasp the concentration levels of coal dust, silica dust and other dusts in the workplaces of employers in the national mining industry in 2023, and to identify the key points for occupational disease prevention and control. Methods: In December 2024, the concentrations of coal dust, silica dust and other dusts in the workplaces of 7903 mining enterprises across the country in 2023 were analyzed. Methods such as Kruskal-Wallis H rank sum test and Chi-square test were used to compare the differences in dust concentrations and over-limit ratios in the workplaces of enterprises of different scales, industries and regions. Results: The over-limit ratios of coal dust, silica dust and other dusts positions were 18.80% (1945/10343), 30.10% (4525/15033) and 5.75% (241/4194), respectively. Among them, the over-limit ratios of silica dust positions with free silica content >80% was as high as 73.46% (238/324). The time-weighted average exposure concentrations of coal dust, silica dust and other dusts were 1.50 (0.78, 2.23), 0.45 (0.28, 0.60) and 1.15 (0.56, 2.20) mg/m(3), respectively. There were statistically significant differences in the dust concentrations and over-limit ratios of free silica content ≤50% and 50% P<0.05), with higher ratios in large enterprises. There were statistically significant differences in the content of free silica ≤50%, other dusts concentrations and over-limit ratios in the workplaces of employers in different industries (P<0.05), with higher levels in the coal mining and washing industry and the non-metallic mineral mining and selection industry, respectively. There were statistically significant differences in the over-limit ratios of coal dust and silica dust in different regions (P<0.05), with higher ratios in the Northwest, Southwest and North China regions. Conclusion: The over-limit ratios of dust concentration in the workplace of the mining industry remains at a relatively high level. In the future, the supervision of enterprises in key areas and industries with serious over-limit should be strengthened to protect the health of workers.