Application Of Statistical Modeling In Analyzing Health And Safety Data For Mineral Industry

Health and safety of workers in mineral industry in the U.S. is still a vey important issue as Mining along with Agriculture, Forestry and Fishing and Construction industries have contributed most of the fatal occupational injuries ill between 1980 - 1995 (Worker Health Chartbook, 2000). Health and safety issues, especially for the mining or related excavation industries, arise either from exposures of the human workers to the contaminants liberated or generated by mining operations that have adverse effects on human health (for example coal dust etc.) or from the exposures of the human workers to hazardous working environment that constitutes mining operations (for example blasting etc.). One of the biggest challenges is to understand the combinatorial effect of numerous work-condition (e.g. exposure to dust) and human-factor (e.g. smoking habit) variables on a health or safety-condition variable (e.g. incidence rate of a disease). This paper uses an example dataset on Coal miners' cough problem to illustrate the applicability of Generalized Linear Modeling (GLM) in understanding the relation between cough and other response variables, such as, age, height, smoking habits, time of underground exposure etc.