The Investigation And Study On Occupational Disease Hazard In State-owned Mining Enterprises Of Henan Province

Mineral resourse is the basis and leading industry of the economic development in our country. There is plenty of mineral reserve in Henan province, so there are lots of mining enterprises, especially collieries. The total production value of the mine industry is more than 30 billion Yuan. However, the situation of the occupational diseases has become worse because of the exploitation of the mine. The main occupational diseases that happened in mining enterprises include pneumoconiosis, occupational hearing loss, occupational poisoning, bursitis and so on. Some of them have seriously harmed the workers'health, and created the life-long pain to many patients.This paper launches the sample investigation on the occupational disease hazard which faces in view of the state-owned mining enterprises of Henan province. The main content of the investigation is the situation of the pneumoconiosis(including coal worker's pneumoconiosis and silicosis), the occupational hearing loss as well as the bursitis. The investigation objects are the workers who contact the dusts, noise and any other dangerous factors when they are working. The investigation projects include the type of work, the occupational medical history, the age, the working year, the occupational diseases degree and so on. The result of the investigation can reflect the general regularity of different local occupational disease hazard.In the foundation of investigation, analyzing the composition trends of the occupational disease, and studying the relationship between the occupational diseases and the environmental factors. For studying the dose-response relationship between cumulative exposure to dusts and incidence of pneumoconiosis, as well as cumulative noise exposure and incidence of hearing loss, we used the Logistic Regression Model which can describe the regularity quantitatively. Using the Grey Dynamics Model GM(1,1) to forecast the number of the pneumoconiosis patient in the future 5 years. Applying the existing Logistic Regression equation to forecast the working years and the morbidity of the noise exposure workers in hearing loss forecasting.