Mining Project: Clinical and Field Data Analysis of Miner Health

Research Summary

In 2012, 64.7% of the mining workforce (169,312 workers) were employed in noncoal mining sectors—i.e., metal, industrial minerals, and stone, sand, and gravel. While coal mining has some dedicated health surveillance programs (e.g., the Coal Workers’ Health Surveillance Program, CWHSP), less is known about the current health status of metal, industrial minerals, and stone, sand, and gravel miners in the United States. Part of the reason for this knowledge gap is because no comprehensive or narrowly focused health surveillance systems exist for these populations. With a wider spectrum of potential exposures (as compared to coal), the disease distributions between and within noncoal mining sectors are likely to be different with their own priority areas. In addition, this spectrum poses a unique challenge for assessing exposure pathways and the risk of adverse health effects. Collectively, there is a dearth of empirical understanding on the health effects of acute and chronic exposures to hazards common in metal and industrial minerals mining, such as airborne contaminants (e.g., dust, particulate matter), noise, heat, and repetitive stresses. Alternative data sources and analytical approaches may help to begin to reveal these differences, while also clarifying areas of health that remain unclear and require more focused efforts to understand.

To address this need, NIOSH has initiated a Miner Health Program, which is anticipated to include both primary and secondary data collection. Several data sources have been identified that contain de-identified miner and mine-level observations related to health-related exposures, events, conditions, and compensation. Individual clinical and claims data sources were reviewed, in addition to national level surveys such as the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) and Accident, Injury and Illness reports maintained by the Mine Safety and Health Administration (MSHA). However, each of these data sources is maintained exclusive of the other and often without a specific intent to conduct epidemiologic studies. Establishing a methodology for the systematic review of these data sources is the necessary starting point for establishing a more robust miner health surveillance program.

This pilot project had three research aims, as follows:

1. To establish data management procedures that identify, review, and assess the quality (i.e., representativeness, sensitivity, and timeliness) of each aforementioned dataset.
2. To evaluate and summarize the strengths and weaknesses of each data source, including a description of potential research questions and study designs that could be researched using these data.
3. To provide information on miner health conditions, specifically metal/nonmetal mining, and to identify gaps in understanding heath outcome details that should be targeted for future surveillance efforts under the Miner Health Program.

This pilot project research has helped to direct and establish a foundation for a data surveillance effort that routinely assesses miner health. A template structure and procedure for securing and analyzing data was developed, enabling a systematic assessment of what is currently known about miner health and the potential hazards that may contribute to adverse health effects.

This pilot project research has helped direct and establish a foundation for a data surveillance effort that routinely assesses miner health. A template structure and procedure for securing and analyzing data was developed, enabling a systematic assessment of what is currently known about miner health and the potential hazards that may contribute to adverse health effects. Observations from these methods and pilot project were incorporated into a multi-year research project that will aid in identifying specific knowledge gaps in miner health, and prioritize health issues and hazards that are (1) ready for intervention or (2) require new primary and secondary data collection to improve risk estimates, and (3) identify employers and workers to collaborate within the development of pilot health improvement programs.