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Objective: Increase knowledge of US coal miners' respiratory health by linking data from the black lung benefits program (BLBP) and the coal workers' health surveillance program (CWHSP)., Methods: BLBP claims data from 2000 through 2013 was linked to CWHSP data from 1970 through 2016., Results: Overall, 273,644 miners participated in CWHSP, 37,548 in BLBP, and 22,903 in both programs. Median age of miners at their time of first/only participation in CWHSP was 28 and 32 years, respectively. BLBP claimants were older (median age 59). Thirty-nine percent of BLBP claimants had not participated in CWHSP. The relative contributions of states to participation differed between CWHSP and BLBP. For example, Kentucky miners accounted for 18% of CWHSP participants, but 36% of BLPB participants., Conclusions: Many BLBP claimants never appeared in CWHSP, indicating missed opportunities for secondary prevention.

Objective: This study examines differences in chronic health outcomes between coal, uranium, metal, and nonmetal miners., Methods: In a cross-sectional study using data from a health screening program for current and former New Mexico miners, log-binomial logistic regression models were used to estimate relative risks of respiratory and heart disease, cancer, osteoarthritis, and back pain associated with mining in each sector as compared with coal, adjusting for other relevant risk factors., Results: Differential risks in angina, pulmonary symptoms, asthma, cancer, osteoarthritis, and back pain between mining sectors were found., Conclusions: New Mexico miners experience different chronic health challenges across sectors. These results demonstrate the importance of using comparable data to understand how health risks differ across mining sectors. Further investigation among a broader geographic population of miners will help identify the health priorities and needs in each sector.

Objective: Determine whether select cause of death mortality disparities in four Appalachian regions is associated with coal mining or other factors., Methods: We calculated direct age-adjusted mortality rates and associated 95% confidence intervals by sex and study group for each cause of death over 5-year time periods from 1960 to 2009 and compared mean demographic and socioeconomic values between study groups via two-sample t tests., Results: Compared with non-coal-mining areas, we found higher rates of poverty in West Virginia and Virginia (VA) coal counties. All-cause mortality rates for males and females were higher in coal counties across all time periods. Virginia coal counties had statistically significant excesses for many causes of death., Conclusions: We found elevated mortality and poverty rates in coal-mining compared with non-coal-mining areas of West Virginia and VA. Future research should examine these findings in more detail at the individual level.

Background: Exposures associated with coal mining have long been linked to occupational disease. More recently, investigators have suggested that this industry may affect community health., Methods: We explored associations between age-adjusted, county-level respiratory disease hospitalization rates (RHRs) in West Virginia and total, surface, and underground coal production, taking into account relevant sociodemographic and behavioral covariates. RHRs were calculated for 2005 to 2009, and analyses were performed to assess the effect of coal production after adjusting for sociodemographic factors., Results: After controlling for percent below poverty, percent urban, and smoking, neither total nor underground tonnage was associated with RHR. Surface coal production, however, was significantly related with RHR (P < 0.05)., Conclusions: Surface coal production makes a small but significant contribution to RHR in West Virginia after accounting for other important sociodemographic and behavioral determinants of health.

Objective: To determine whether mortality disparities in Appalachia are due to coal mining or other factors., Methods: Unadjusted and covariate adjusted rate ratio models calculated total, all external, and all cancer mortality rates from 1960 to 2009 for cumulative total, surface, and underground coal production in coal-mining counties compared with non-coal-mining counties., Results: No coal-related statistically significant elevations in total or all external mortality were found. Control for covariates attenuated rate ratios for all levels of coal mining. All forms of coal were statistically significant in the adjusted rate ratio models for all cancer mortality, with 4% to 6% excesses in the highest quartiles of production., Conclusions: Total and all external mortalities do not seem to be related to coal production in Appalachia, but all cancer mortality should be further examined. Additional causes of death should also be considered.

Objective: To explore factors associated with fatal accidents among contractors and operators by using the Mine Safety and Health Administration database., Methods: Cross-sectional data on 157,410 miners employed by operators or contractors during 1998-2007 were analyzed using logistic regression and multiple imputation., Results: Univariate odds of fatal versus nonfatal accident were 2.8 (95% confidence interval, 2.3 to 3.4) times higher for contractors than operators. In a multivariable model, fatality was associated with contractor, less experience at the current mine, and occurrence at more than 8 hours into the workday (P < 0.05 for each). Differences in odds of fatality by employment type were more pronounced in surface mines., Conclusions: Contractors had a higher proportion of fatal injuries. Fatality also varied by mine experience, the number of hours worked before injury, work location, and mine type.

Objective: To determine the predictive value of coal mining and other risk factors for explaining disproportionately high mortality rates across Appalachia., Method: Mortality and covariate data were obtained from publicly available databases for 2000 to 2004. Analysis employed ordinary least square multiple linear regression with age-adjusted mortality as the dependent variable., Results: Age-adjusted all-cause mortality was independently related to Poverty Rate, Median Household Income, Percent High School Graduates, Rural-Urban Location, Obesity, Sex, and Race/Ethnicity, but not Unemployment Rate, Percent Uninsured, Percent College Graduates, Physician Supply, Smoking, Diabetes, or Coal Mining., Conclusions: Coal mining is not per se an independent risk factor for increased mortality in Appalachia. Nevertheless, our results underscore the substantial economic and cultural disadvantages that adversely impact health in Appalachia, especially in the coal-mining areas of Central Appalachia.

Objective: To estimate the prevalence and costs of respiratory illness for workers in coal mining, compared with other US industries., Methods: Using 5 years of insurance claims data for an annual average of 96,240 adult males, we model the probability and costs of respiratory illness as a function of workers' industry and other factors., Results: Controlling for nonindustry factors, workers in coal mining had significantly higher rates of respiratory illness claims (by 2.1% to 3.3% points) compared with other mining, agriculture, construction, and manufacturing. For coal mining workers with respiratory illness, annual medical care costs for these claims were also significantly higher (by $111 to $289). Surprisingly, drug costs were mostly lower (by $17 to $268)., Conclusions: Our findings underscore the continued importance and potential cost effectiveness of measures to protect miners from harmful occupational exposures, particularly to coal dust.

Objectives: We describe inconsistencies in disease and illness reporting in U.S. mining, identify under-reporting of disease and illness in U.S. mining, and summarize selected disease and illness in U.S. mining from 1983 through 2001., Methods: We summarized information on mining-related disease and illness data for the years 1983-2001 from the Mining Safety and Health Administration database (MSHA)., Results: Discrepancies exist in types of information collected by the Centers for Disease and Control, the National Institute for Occupational Safety and Health, and the Mining Safety and Health Administration database. Several factors, including a worker's fear of losing his or her job, health insurance, or other job-related benefits contribute to under-reporting of disease and illness information in the US mining industry., Conclusions: Since 1997, both number of workers employed in mining and disease and illness rates have decreased; however, the highest disease and illness rates in mining continue to be coal worker's pneumoconiosis and hearing loss.