Department of Agricultural & Applied Economics, Virginia Tech, 250 Drillfield Drive, Blacksburg, VA, 24061, USA.
Edward Via College of Osteopathic Medicine, Biomedical Sciences, 2265 Kraft Drive, Blacksburg, VA, 24061, USA.
BMC Public Health. 2019 Nov 8;19(1):1484. doi: 10.1186/s12889-019-7858-y.
Previous studies have associated elevated mortality risk in central Appalachia with coal-mining activities, but few have explored how different non-coal factors influence the association within each county. Consequently, there is a knowledge gap in identifying effective ways to address health disparities in coal-mining counties. To specifically address this knowledge gap, this study estimated the effect of living in a coal-mining county on non-malignant respiratory diseases (NMRD) mortality, and defined this as "coal-county effect." We also investigated what factors may accentuate or attenuate the coal-county effect.
An ecological epidemiology protocol was designed to observe the characteristics of three populations and to identify the effects of coal-mining on community health. Records for seven coal-mining counties (n = 19,692) were obtained with approvals from the Virginia Department of Health Office of Vital Statistics for the years 2005 to 2012. Also requested were records from three adjacent coal counties (n = 10,425) to provide a geographic comparison. For a baseline comparison, records were requested for eleven tobacco-producing counties (n = 27,800). We analyzed the association of 57,917 individual mortality records in Virginia with coal-mining county residency, county-level socioeconomic status, health access, behavioral risk factors, and coal production. The development of a two-level hierarchical model allowed the coal-county effect to vary by county-level characteristics. Wald tests detected sets of significant factors explaining the variation of impacts across counties. Furthermore, to illustrate how the model estimations help explain health disparities, two coal-mining county case studies were presented.
The main result revealed that coal-mining county residency increased the probability of dying from NMRD. The coal-county effect was accentuated by surface coal mining, high smoking rates, decreasing health insurance coverage, and a shortage of doctors. In Virginia coal-mining regions, the average coal-county effect increased by 147% (p-value< 0.01) when one doctor per 1000 left, and the effect increased by 68% (p-value< 0.01) with a 1% reduction of health insurance rates, holding other factors fixed.
This study showed a high mortality risk of NMRD associated with residents living in Virginia coal-mining counties. Our results also revealed the critical role of health access in reducing health disparities related to coal exposure.
先前的研究表明，阿巴拉契亚中部地区的死亡率升高与采煤活动有关，但很少有研究探讨在每个县内，不同的非采煤因素如何影响这种关联。因此，在确定解决采煤县卫生差异的有效方法方面存在知识差距。为了专门解决这一知识差距，本研究估计了居住在采煤县对非恶性呼吸道疾病（NMRD）死亡率的影响，并将其定义为“采煤县效应”。我们还研究了哪些因素可能会加剧或减弱这种采煤县效应。
设计了一项生态流行病学方案，以观察三个群体的特征，并确定采煤对社区健康的影响。在弗吉尼亚州卫生署生命统计办公室的批准下，获得了 2005 年至 2012 年七个采煤县（n=19692）的记录。还请求了三个相邻采煤县（n=10425）的记录，以提供地理比较。作为基线比较，请求了 11 个产烟县（n=27800）的记录。我们分析了弗吉尼亚州 57917 份个人死亡记录与居住在采煤县、县一级社会经济地位、获得医疗保健、行为风险因素和煤炭生产之间的关联。建立了一个两级分层模型，允许根据县一级的特征来改变采煤县效应。沃尔德检验检测到一组显著因素，这些因素解释了县一级之间影响的变化。此外，为了说明模型估计如何有助于解释卫生差异，我们展示了两个采煤县的案例研究。
主要结果表明，居住在采煤县会增加死于 NMRD 的概率。采煤县效应因露天采煤、高吸烟率、医疗保险覆盖率下降和医生短缺而加剧。在弗吉尼亚州的采煤区，当每 1000 人减少一名医生时，平均采煤县效应增加了 147%（p 值<0.01），当医疗保险率降低 1%时，效应增加了 68%（p 值<0.01），其他因素保持不变。
本研究表明，与居住在弗吉尼亚州采煤县的居民相关的 NMRD 死亡率较高。我们的结果还揭示了医疗保健机会在减少与煤炭接触相关的健康差异方面的关键作用。
