NIOSHTIC-2 Publications Search
Respiratory impairment and symptoms as predictors of early retirement with disability in US underground coal miners.
Ames RG; Trent RB
Am J Public Health 1984 Aug; 74(8):837-838
Objective measures of respiratory function and respiratory symptoms, correlating the concept of early retirement with disability and utilizing a 5 year prospective study design were investigated. The investigation was conducted with data from 1394 miners in four diesel and three non diesel coal mines in Colorado, Utah, and Kentucky. Analysis was based on a logic regression model of early retirement with disability. The prediction model included terms for obstruction, restriction, forced expiratory flow rate at 50 percent, cough, phlegm, and dyspnea. Smoking status was defined in terms of current smokers versus exsmokers and non smokers in 1977. Age, education, and years of mining were included as possible confounding variables. A test of the statistical significance of the adjusted regression coefficients was based on Z-values. Of the measures of respiratory function and respiratory symptoms, only chronic phlegm provided a statistically significant prediction of early retirement with disability. There was a controversy involving smoking, whether it was to be considered an explanation for disability previously attributed to occupation or does occupation mask smoking related disability. Data suggested that cigarette smoking was not an independent predictor of early retirement with disability. The traditional measures of respiratory impairment, obstruction, and restriction were not significant predictors of early retirement with disability. It was also noted that these traditional measures did not reflect pulmonary changes in small airways. For this group of coal miners, expiratory volume (a measure of small airways disease) did not appear to show a strong relation between spirometric measures of pulmonary function and subjective reports of disability.
NIOSH-Author; Analytical-methods; Quantitative-analysis; Research; Analytical-models; Mathematical-models; Epidemiology; Occupational-respiratory-disease; Disease-incidence; Morbidity-rates; Risk-analysis; Occupational-health
Richard G. Ames, PhD, MPH, Appalachian Laboratories for Occupational Safety and Health (ALOSH), 944 Chestnut Ridge Road, Morgantown, WV 26505
Issue of Publication
American Journal of Public Health
WV; CO; KY; UT
Page last reviewed: June 15, 2021
Content source: National Institute for Occupational Safety and Health Education and Information Division