The study was conducted on workers in Na Duong coal mine, Lang Son province to investigate the working environment, health status and diseases. The results showed that working environment was contaminated by toxics that were above allowed limits, such as high silic dust level. Some common diseases were ear-nose-throat diseases, accounting for 77.2%, eye diseases 39.9%, digestion 17.8%, heart diseases 15.1%, and respiratory diseases 14.1%. Among respiratory diseases, silic dust-related one was significant. The rate in the mine neighborhood area was 10% and at the working site was 11%. Coal mine workers’ health was a little below the average compared with other domestic manufacturing sectors, nobody had health status at level I.
Environment ; Health ; Coal Mining

The underground environment is dark and humid, and it is easy to breed pathogenic microorganisms. A lump in the right lung of a coal mine underground transport worker was found druing occupational health examination. CT examination showed that the lump was located in the posterior segment of the upper lobe of the right lung, with point strip calcification, liquefaction necrosis, and proximal bronchial stenosis and occlusion. MRI examination FS-T(2)WI and DWI showed "target sign", annular low signal around the central high signal, and low mixed signal around the periphery, and annular high signal in the isosignal lesions on T(1)WI. Then the pulmonary aspergillus infection was confirmed by pathology.
Humans ; Coal ; Miners ; Pneumonia ; Lung ; Aspergillosis ; Coal Mining

Coal ; Coal Mining ; Dust/analysis* ; Humans ; Occupational Exposure ; Pneumoconiosis

Objective: To understand the harm degree of underground noise and provide basis for noise control. Methods: In November 2019, 13 typical coal mines in Sichuan Province were selected as the research objects, and a total of 1203 sites and 609 jobs of noise exposure were investigated. Results: The noise intensity P75 >80 dB (A) was measured. The noise intensity of the inspection place of the air compressor is >86 dB (A) , the noise intensity of the inspection place of the gas drainage and the operation place of the main fan is between 80-85 dB (A) . Conclusion: Besides the harm of dust, noise exposure should also be paid attention to, and the measures of sound absorption and sound insulation should be taken or personal protection should be strengthened.
Coal ; Coal Mining ; Dust/analysis* ; Noise ; Occupational Exposure

BACKGROUND: Collisions involving workers and mobile machines continue to be a major concern in underground coal mines. Over the last 30 years, these collisions have resulted in numerous injuries and fatalities. Recently, the Mine Safety and Health Administration (MSHA) proposed a rule that would require mines to equip mobile machines with proximity detection systems (PDSs) (systems designed for automated collision avoidance). Even though this regulation has not been enacted, some mines have installed PDSs on their scoops and hauling machines. However, early implementation of PDSs has introduced a variety of safety concerns. Past findings show that workers' trust can affect technology integration and influence unsafe use of automated technologies.METHODS: Using a mixed-methods approach, the present study explores the effect that factors such as mine of employment, age, experience, and system type have on workers' trust in PDSs for mobile machines. The study also explores how workers are trained on PDSs and how this training influences trust.RESULTS: The study resulted in three major findings. First, the mine of employment had a significant influence on workers' trust in mobile PDSs. Second, hands-on and classroom training was the most common types of training. Finally, over 70% of workers are trained on the system by the mine compared with 36% trained by the system manufacturer.CONCLUSION: The influence of workers' mine of employment on trust in PDSs may indicate that practitioners and researchers may need to give the organizational and physical characteristics of each mine careful consideration to ensure safe integration of automated systems.
Automation ; Coal ; Employment ; Mining ; Occupational Health

OBJECTIVES: This study was planned to compare the epidemiological features such as radiological and clinical features between coal worker's pneumoconiosis and manufacturing pneumoconiosis in connection with their age and dust exposure duration. METHODS: For the study, detailed examination records of those workers who had been confirmed to have pneumoconiosis in coal mining and manufacturing industries by the Ministry of Labour during two year period of 1991 and 1992. Total number of study subjects was 895 pneumoconiosis cases; 504 from coal mining and 391 from manufacturing industries. Information variables for the data analysis were sex, age, dust exposure duration, work position as the independent variables and radiological pneumoconiosis category, pulmonary function test results and pulmonary tuberculosis complication status as the dependent study variables. RESULTS: There was a significant difference in distribution of radiological categories of both pneumoconiosis groups. The proportion of suspicious and category 1 pneumoconiosis was higher in manufacturing pneumoconiosis group than in coal mine pneumoconiosis group whereas category 2 and large opacity pneumoconiosis was higher in coal mine pneumoconiosis group than in manufacturing pneumoconiosis group. Major ventilatory indices such as FVC and FEV1 were significantly lower in coal mine pneumoconiosis group than in manufacturing pneumoconiosis group even after other variables such as age and smoking history were statistically adjusted for. CONCLUSIONS: It is suggested that some selected outcome variables such as radiological category of pneumoconiosis, ventilatory impairment, and pulmonary tuberculosis complication rate were significantly different between coal mine pneumoconiosis and manufacturing pneumoconiosis.
Anthracosis ; Coal ; Coal Mining ; Dust ; Korea* ; Mining* ; Pneumoconiosis* ; Respiratory Function Tests ; Smoke ; Smoking ; Statistics as Topic ; Tuberculosis, Pulmonary

BACKGROUND: Coal mining is of significant economic importance to the Australian economy. Despite this fact, the related workforce is subjected to a number of psychosocial risks and musculoskeletal injury, and various psychological disorders are common among this population group. Because only limited research has been conducted in this population group, we sought to examine the relationship between physical (pain) and psychological (distress) factors, as well as the effects of various demographic, lifestyle, and fatigue indicators on this relationship. METHODS: Coal miners (N = 231) participated in a survey of musculoskeletal pain and distress on-site during their work shifts. Participants also provided demographic information (job type, age, experience in the industry, and body mass index) and responded to questions about exercise and sleep quality (on- and off-shift) as well as physical and mental tiredness after work. RESULTS: A total of 177 workers (80.5%) reported experiencing pain in at least one region of their body. The majority of the sample population (61.9%) was classified as having low-level distress, 28.4% had scores indicating mild to moderate distress, and 9.6% had scores indicating high levels of distress. Both number of pain regions and job type (being an operator) significantly predicted distress. Higher distress score was also associated with greater absenteeism in workers who reported lower back pain. In addition, perceived sleep quality during work periods partially mediated the relationship between pain and distress. CONCLUSION: The study findings support the existence of widespread musculoskeletal pain among the coal-mining workforce, and this pain is associated with increased psychological distress. Operators (truck drivers) and workers reporting poor sleep quality during work periods are most likely to report increased distress, which highlights the importance of supporting the mining workforce for sustained productivity.
Absenteeism ; Coal Mining ; Coal* ; Efficiency ; Fatigue ; Humans ; Life Style ; Low Back Pain ; Mining ; Musculoskeletal Pain ; Occupational Health ; Population Groups

Pneumoconiosis, especially Coal-workers' Pneumoconi6sis(GWP), is the principal occupation-related disease in Korea because of the large number of affected workers. Coal mines and miners have been reduced abruptly during recent 8 years, but coal mining should be kept in Korea. Recently, pneumoconiotic workers are increasing in manufacturing industry. It is necessary to know the characteristics of CWP to prevent the development of CWP and manage employed or retired pneumoconiotic workers. Furthermore, it is also necessary to study CWP to protect workers from pneumoconiosis in manufacturing industry. Of the total of 6,452 workers who were diagnosed as CWP initially during the 20 years from 1973 to 1992, X-ray category was as follows: category 1(35.2%), category 2(23.1%), suspicious (0/1 category, 13.4%), category 3(5.7%), large opacity (3.5%), unknown by. complete classification (19.1%). The patients' cardiopulmonary disability was as follows: no disability 79.3%, slight 14.2%, mild 4.1%, moderate 1.9%, severe 0.5%. The patients' X-ray category and disability were not related with the initially exposed age or job position, but their severity was positively related with the exposed duration that was adjusted by the initially exposed age. Also, the patients' X-ray category and disability had positive relationship each other. The cumulative exposure dose of silica/was more important than that'of respirable dust in the. development of large opacity CWP. The annual incidence density of CWP was 73.2 persons in 1982 and 75.8 persons in 1986per 10,000 person years. Afterthen it has been gradually decreasing and was in the range of 20-30 persons in the period of 1989-1992.
Classification ; Coal ; Coal Mining ; Dust ; Humans ; Incidence* ; Korea* ; Pneumoconiosis* ; Risk Factors*

Objective: Differential flora and differential metabolites shared by the intestinal and respiratory tracts of rats were screened to analyze the possible role of changes in intestinal flora and metabolites in the progression of pneumoconiosis in rats. Methods: In April 2020, 18 SD rats were randomly divided into three groups (control group, coal mine dust group and silica group, 6 in each group) , rats in the coal mine dust group and silica group were perfused with 1 ml of 50 mg/ml coal mine well dust suspension and silica suspension by nontracheal exposure, respectively. While rats in the control group were perfused with an equal dose of sterilized normal saline. Twenty four weeks after dust staining, rat feces, throat swabs, and lung lavages were collected. 16SrDNA gene sequencing and UHPLC-QTOF-MS untargeted metabolomics were used to analyze the flora and metabolites in feces, throat swabs and lung lavage fluid of rats in each group, to screen for shared differential flora and shared differential metabolites in intestinal and respiratory tract, and the correlation analysis between the differential flora and metabolites was performed using Spearman's statistics. Results: Compared with the control group, a total of 9 species shared differential flora between intestinal and respiratory tract were screened at phylum level, and a total of 9 species shared differential genus between intestinal and respiratory tract were screened at genus level in the coal mine dust group, mainly Firmicutes, Actinobacteria, Streptococcus, Lactobacillus, etc. Compared with the control group, a total of 9 shared differential flora were screened at the phylum level, and a total of 5 shared differential genus were screened at the genus level in the silica group, mainly Proteobacteria, Actinobacteria, Allobactera, Mucilaginibacter, etc. Compared with the control group, a total of 7 shared differential metabolites were screened for up-regulation of Stigmatellin, Linalool oxide and Isoleucine-leucine in both intestinal and respiratory tract in the coal mine dust group. Compared with the control group , a total of 19 shared differential metabolites werescreened in the silica group, of which Diethanolamine, 1-Aminocyclopropanecarboxylic acid, Isoleucine-leucine, Sphingosine, Palmitic acid, D-sphinganine, 1, 2-dioleoyl-sn-glycero-3-phosphatidylcholine, and 1-Stearoyl-2-oleoyl-sn-glycerol 3-phosphocholine were up-regulated in both the intestinal and respiratory tract. Conclusion: There is a translocation of intestinal and respiratory flora in pneumoconiosis rats, and rats have an imbalance of lipid metabolism during the progression of pneumoconiosis.
Rats ; Animals ; Isoleucine ; Leucine ; Coal Mining ; Rats, Sprague-Dawley ; Pneumoconiosis ; Dust/analysis* ; Silicon Dioxide ; Coal

Objective: To construct and verify a light-weighted convolutional neural network (CNN), and explore its application value for screening the early stage (subcategory 0/1 and stage Ⅰ of pneumoconiosis) of coal workers' pneumoconiosis (CWP) from digital chest radiography (DR) . Methods: A total of 1225 DR images of coal workers who were examined at an Occupational Disease Prevention and Control Institute in Anhui Province from October 2018 to March 2021 were retrospectively collected. All DR images were collectively diagnosed by 3 radiologists with diagnostic qualifications and gave diagnostic results. There were 692 DR images with small opacity profusion 0/- or 0/0 and 533 DR images with small opacity profusion 0/1 to stage Ⅲ of pneumoconiosis. The original chest radiographs were preprocessed differently to generate four datasets, namely 16-bit grayscale original image set (Origin16), 8-bit grayscale original image set (Origin 8), 16-bit grayscale histogram equalized image set (HE16) and 8-bit grayscale histogram equalized image set (HE8). The light-weighted CNN, ShuffleNet, was applied to train the generated prediction model on the four datasets separately. The performance of the four models for pneumoconiosis prediction was evaluated on a test set containing 130 DR images using measures such as the receiver operating characteristic (ROC) curve, accuracy, sensitivity, specificity, and Youden index. The Kappa consistency test was used to compare the agreement between the model predictions and the physician diagnosed pneumoconiosis results. Results: Origin16 model achieved the highest ROC area under the curve (AUC=0.958), accuracy (92.3%), specificity (92.9%), and Youden index (0.8452) for predicting pneumoconiosis, with a sensitivity of 91.7%. And the highest consistency between identification and physician diagnosis was observed for Origin16 model (Kappa value was 0.845, 95%CI: 0.753-0.937, P<0.001). HE16 model had the highest sensitivity (98.3%) . Conclusion: The light-weighted CNN ShuffleNet model can efficiently identify the early stages of CWP, and its application in the early screening of CWP can effectively improve physicians' work efficiency.
Humans ; Retrospective Studies ; Anthracosis/diagnostic imaging* ; Pneumoconiosis/diagnostic imaging* ; Coal Mining ; Neural Networks, Computer ; Coal