Effects of occupational exposure to dust on chest radiograph, pulmonary function, blood pressure and electrocardiogram among coal miners in an eastern province, China

Black Lung Disease Among Coal Miners in Asia: A Systematic Review

Background

Coal miners are highly prone to occupational health risks, such as black lung disease. This study aims to assess the prevalence of black lung disease and the factors associated with black lung disease among coal miners in Asia.

Method

This systematic review, conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, searched through the scientific literature of the following databases: EBSCO, ScienceDirect, PubMed, and Scopus. We selected articles that studied black lung disease among coal miners from 48 countries in Asia and were published between 2014 and 2023. Article quality was evaluated using the Critical Appraisal Skills Program.

Result

The seven articles that we review studied a total of 653,635 coal miners from various types of coal mines from three countries in Asia. Of these miners, 59,998 experienced black lung disease. Black lung disease is prevalent among 9.18% of coal miners in Asia, which is approximately four times higher than the worldwide prevalence. Common factors that influence black lung disease in Asia include age, years of dust exposure, smoking, drinking, working types, and sizes of mines, type of mines, respiratory functions, spirometry parameters, tenure, lack of attention to occupational health, inefficient surveillance, and weak occupational health service.

Conclusion

Although the prevalence of black lung disease among coal miners in Asia is considerably high, it can be addressed through effective prevention measures, monitoring, control, and case reporting.

Associations of coal mine dust exposure with arterial stiffness and atherosclerotic cardiovascular disease risk in chinese coal miners

OBJECTIVE

Whether coal mine dust exposure increases cardiovascular diseases (CVDs) risk was rarely explored. Our objective was to examine the association between coal mine dust exposure and cardiovascular risk.

METHODS

We estimated cumulative coal mine dust exposure (CDE) for 1327 coal miners by combining data on workplace dust concentrations and work history. We used brachial-ankle pulse wave velocity (baPWV, a representative indicator of arterial stiffness) and ten-year atherosclerotic cardiovascular disease (ASCVD) risk to assess potential CVD risk, exploring their associations with CDE.

RESULTS

Positive dose-response relationships of CDE with baPWV and ten-year ASCVD risk were observed after adjusting for covariates. Specifically, each 1 standard deviation (SD) increase in CDE was related to a 0.27 m/s (95% CI: 0.21, 0.34) increase in baPWV and a 1.29 (95% CI: 1.14, 1.46) elevation in OR (odds ratio) of risk of abnormal baPWV. Moreover, each 1 SD increase in CDE was associated with a 0.74% (95% CI: 0.63%, 0.85%) increase in scores of ten-year ASCVD and a 1.91 (95% CI: 1.62, 2.26) increase in OR of risk of ten-year ASCVD. When compared with groups unexposed to coal mine dust, significant increase in the risk of arterial stiffness and ten-year ASCVD in the highest CDE groups were detected.

CONCLUSION

The study suggested that cumulative exposure to coal mine dust was associated with elevated arterial stiffness and ten-year ASCVD risk in a dose-response manner. These findings contribute valuable insights for cardiovascular risk associated with coal mine dust.

Application of urease-producing microbial community in seawater to dust suppression in desert

In order to solve the dust problem caused by sandstorms, this paper aims to propose a new method of enriching urease-producing microbial communities in seawater in a non-sterile environment. Besides, the difference of dust suppression performance of enriched microorganisms under different pH conditions was also explored to adapt the dust. The Fourier-transform infrared spectrometry (FTIR) and Scanning electron microscopy (SEM) confirmed the formation of CaCO₃. The X-ray diffraction (XRD) further showed that the crystal forms of CaCO₃ were calcite and vaterite. When urease activity was equivalent, the alkaline environment was conducive to the transformation of CaCO₃ to more stable calcite. The mineralization rate at pH = 10 reached the maximum value on the 7^th day, which was 97.49 ± 1.73%. Moreover, microbial community analysis results showed that the relative abundance of microbial community structure was different under different pH enrichment. Besides, the relative abundance of Sporosarcina, a representative genus of urease-producing microbial community, increased with the increase of pH under culture conditions, which consistent with the mineralization performance results. In addition, the genus level species network diagram also showed that in the microbial community, Sporosarcina was negatively correlated with another urease-producing genus Bacillus, and had a reciprocal relationship with Atopostipes, which means that the urease-producing microbial community was structurally stable. The enrichment of urease-producing microbial communities in seawater will provide empirical support for the large-scale engineering application of MICP technology in preventing and controlling sandstorms in deserts.

The Potential Diagnostic Biomarkers for the IgG Subclass in Coal Workers' Pneumoconiosis

Evidence suggests that exposure to coal dust increases immunoglobulin concentration. However, there is a paucity of data reporting immunoglobulin G (IgG) subclass in coal workers' pneumoconiosis (CWP). Therefore, this study intended to evaluate potential diagnostic biomarkers for the disease. CWP patients, dust-exposed workers without pneumoconiosis (DEW), and matched healthy controls (HCs) presented to the General Hospital of Datong Coal Mining Group and Occupational Disease Prevention and Treatment Hospital of Datong Coal Mining Group between May 2019 and September 2019 were recruited. The serum immunoglobulin concentration was determined by the multiplex immunoassay technique. Totally, 104 CWP patients, 109 DEWs, and 74 HCs were enrolled. Serum levels of IgG1, IgG2, IgM, and IgA were elevated in CWPs compared with those in DEWs and HCs (P < 0.05). The order of diagnostic accuracy between CWPs and DEWs depicted by the receiver operating characteristic (ROC) curve was IgG2, IgM, IgG1, IgG3, and IgA. Significantly higher IgG1/IgG3 and IgG2/IgG3 ratios were observed in the CWP group than in DEW and HC groups. Based on the IgG2/IgG3 ratio, the area under the ROC curve between CWP and DEW was 0.785 (95% CI 0.723-0.838), with a sensitivity of 73.1% and a specificity of 73.4%. Our findings suggest that IgG1, IgG2, IgM, and IgA are higher in the CWPs than DEWs and HCs. The IgG2/IgG3 ratio provides a viable alternative for the diagnosis of CWP.

Prevalence of coal worker's pneumoconiosis: a systematic review and meta-analysis

Global prevalence trend and regional differences of coal worker's pneumoconiosis (CWP) remain unclear. This study aimed to provide systematic and comprehensive evidence for the global prevalence of CWP. Literature research for studies that reported prevalence of CWP was conducted in PubMed, CNKI, and Web of Science. The identified studies were strictly screened according to predetermined inclusion and exclusion criteria. The pooled prevalence of CWP in different periods and regions was calculated. A total of 37 studies were included after screening, and data from the Coal Workers' Health Surveillance Program was additionally included in the meta-analysis. The global pooled prevalence of CWP decreased from 23.33% (95% confidence interval [CI]: 18.03%, 28.62%) before 1970 to 6.00% (95% CI: 4.11%, 7.90%) in 1981-1990, but indicated a rebound (10.35%, 95% CI: 8.08%, 12.62%) in 1991-2000 and finally dropped to 2.29% (95% CI: 2.06%, 2.51%) in 2011-2020. In the recent 30 years, the top three pooled prevalence of CWP was found in Europe, China, and the USA, respectively. Few articles have reported the prevalence in developing regions, but available evidence indicated that the prevalence in developing regions was much higher than that in developed regions. Higher pooled prevalence was observed in studies which reported larger number of miners in collieries, older average age of miners, underground collieries, and longer dust exposure time. The global prevalence of CWP indicates a rebound in 1990s, but the overall trend is downward in the recent 60 years. The prevention and treatment of CWP should be currently emphasized in developing countries.

Association of coal mine dust lung disease with Nodular thyroid disease in coal miners: A retrospective observational study in China

Background

Coal dust is a major risk factor for the occupational health of coal miners, and underground workers with coal mine dust lung disease (Coal miners with coal mine dust lung disease (CMDLD) may have a higher risk of developing Nodular thyroid disease (NTD). The aim of this study was to investigate the relationship between coal mine dust lung disease and the development of Nodular thyroid disease in coal miners.

Methods

This was a clinical retrospective observational study that included 955 male coal miners from 31 different coal mining companies in Huainan, Anhui Province, China, who were examined in April 2021 at the Huainan Occupational Disease Prevention and Control Hospital to collect all their clinical physical examination data, including general conditions, laboratory test indices and imaging indices. Based on the presence or absence of Nodular thyroid disease, 429 cases with Nodular thyroid disease were classified as the diseased group and 526 cases without Nodular thyroid disease were classified as the control group. Logistic regression was used to analyse the correlation between the occurrence of Nodular thyroid disease in coal miners, and further single- and multi-factor logistic regression was used to screen the risk exposure factors for Nodular thyroid disease in coal miners.

Results

Age, coal mine dust lung disease (CMDLD), red blood cells (RBC), mean red blood cell volume (MCV), albumin (ALB), albumin/globulin (A/G), indirect bilirubin (IBIL), globulin (GLOB), total bilirubin (TBil) and myeloperoxidase (MPO) were associated with the development of Nodular thyroid disease in coal miners (p < 0.05) The results of univariate and multifactorial logistic regression analysis showed that CMDLD (OR:4.5,95%CI:2.79-7.51) had the highest OR and CMDLD was the strongest independent risk exposure factor for the development of Nodular thyroid disease in coal miners.

Conclusions

There is a strong correlation between coal mine dust lung disease and Nodular thyroid disease in underground coal miners, and clinicians need to be highly aware of the high risk of NTD in coal miners with CMDLD and adopt individualized clinical prevention strategies.

Differences in the characteristics and pulmonary toxicity of nano- and micron-sized respirable coal dust

BACKGROUND

The characteristics of coal dust (CD) particles affect the inhalation of CD, which causes coal worker's pneumoconiosis (CWP). CD nanoparticles (CD-NPs, < 500 nm) and micron particles (CD-MPs, < 5 μm) are components of the respirable CD. However, the differences in physicochemical properties and pulmonary toxicity between CD-NPs and CD-MPs remain unclear.

METHODS

CD was analyzed by scanning electron microscopy, Malvern nanoparticle size potentiometer, energy dispersive spectroscopy, infrared spectroscopy, and electron paramagnetic resonance spectroscopy. CCK-8 assay, ELISA, transmission electron microscope, JC-1 staining, reactive oxygen species activity probe, calcium ion fluorescent probe, AO/EB staining, flow cytometry, and western blot were used to determine the differences between CD-NPs and CD-MPs on acute pulmonary toxicity. CCK-8, scratch healing and Transwell assay, hematoxylin-eosin and Masson staining, immunohistochemistry, immunofluorescence, and western blot were applied to examine the effects of CD-NPs and CD-MPs on pneumoconiosis.

RESULTS

Analysis of the size distribution of CD revealed that the samples had been size segregated. The carbon content of CD-NPs was greater than that of CD-MPs, and the oxygen, aluminum, and silicon contents were less. In in vitro experiments with A549 and BEAS-2B cells, CD-NPs, compared with CD-MPs, had more inflammatory vacuoles, release of pro-inflammatory cytokines (IL-6, IL-1β, TNFα) and profibrotic cytokines (CXCL2, TGFβ1), mitochondrial damage (reactive oxygen species and Ca2+ levels and decreased mitochondrial membrane potential), and cell death (apoptosis, pyroptosis, and necrosis). CD-NPs-induced fibrosis model cells had stronger proliferation, migration, and invasion than did CD-MPs. In in vivo experiments, lung coefficient, alveolar inflammation score, and lung tissue fibrosis score (mean: 1.1%, 1.33, 1.33) of CD-NPs were higher than those of CD-MPs (mean: 1.3%, 2.67, 2.67). CD-NPs accelerated the progression of pulmonary fibrosis by upregulating the expression of pro-fibrotic proteins and promoting epithelial-mesenchymal transition. The regulatory molecules involved were E-cadherin, N-cadherin, COL-1, COL-3, ZO-1, ZEB1, Slug, α-SMA, TGFβ1, and Vimentin.

CONCLUSIONS

Stimulation with CD-NPs resulted in more pronounced acute and chronic lung toxicity than did stimulation with CD-MPs. These effects included acute inflammatory response, mitochondrial damage, pyroptosis, and necrosis, and more pulmonary fibrosis induced by epithelial-mesenchymal transition.

A New Strategy for Identification of Coal Miners With Abnormal Physical Signs Based on EN-mRMR

Coal miners’ occupational health is a key part of production safety in the coal mine. Accurate identification of abnormal physical signs is the key to preventing occupational diseases and improving miners’ working environment. There are many problems when evaluating the physical health status of miners manually, such as too many sign parameters, low diagnostic efficiency, missed diagnosis, and misdiagnosis. To solve these problems, the machine learning algorithm is used to identify miners with abnormal signs. We proposed a feature screening strategy of integrating elastic net (EN) and Max-Relevance and Min-Redundancy (mRMR) to establish the model to identify abnormal signs and obtain the key physical signs. First, the raw 21 physical signs were expanded to 25 by feature construction technology. Then, the EN was used to delete redundant physical signs. Finally, the mRMR combined with the support vector classification of intelligent optimization algorithm by Gravitational Search Algorithm (GSA-SVC) is applied to further simplify the rest of 12 relatively important physical signs and obtain the optimal model with data of six physical signs. At this time, the accuracy, precision, recall, specificity, G-mean, and MCC of the test set were 97.50%, 97.78%, 97.78%, 97.14%, 0.98, and 0.95. The experimental results show that the proposed strategy improves the model performance with the smallest features and realizes the accurate identification of abnormal coal miners. The conclusion could provide reference evidence for intelligent classification and assessment of occupational health in the early stage.

Study on the nonfatigue and fatigue states of orchard workers based on electrocardiogram signal analysis

In recent years, fatigue has become an important issue in modern life that cannot be ignored, especially in some special occupations. Agricultural workers are high-risk occupations that, under fatigue conditions over a long period, will cause health problems. In China, since very few studies have focused on the fatigue state of agricultural workers, we were interested in using electrocardiogram (ECG) signals to analyze the fatigue state of agricultural workers. Healthy agricultural workers were randomly recruited from hilly orchards in South China. Through the field experiment, 130 groups of 5-min interval ECG signals were collected, and we analyzed the ECG signal by HRV. The time domain (meanHR, meanRR, SDNN, RMSSD, SDSD, PNN20, PNN50 and CV), frequency domain (VLF percent, LF percent, HF percent, LF norm, HF norm and LF/HF) and nonlinear parameters (SD1, SD2, SD1/SD2 and sample entropy) were calculated and Spearman correlation coefficient analysis and Mann-Whitney U tests were performed on each parameter for further analysis. For all subjects, nine parameters were slightly correlated in nonfatigue and fatigue state. Six parameters were significantly increased and ten HRV parameters were significantly decreased compared the nonfatigue state. As for males, fifteen parameters were significantly different, and for females, eighteen parameters were significantly different. In addition, the probability density functions of SDNN, SDSD, VLF%, HFnorm and LF/HF were significantly different in nonfatigue and fatigue state for different genders, and the nonlinear parameters become more discrete compared the nonfatigue state. Finally, we obtained the most suitable parameters, which reflect the fatigue characteristics of orchard workers under different genders. The results have instructional significance for identifying fatigue in orchard workers and provide a convincing and valid reference for clinical diagnosis.