ADDRESSING HEALTH DISPARITIES IN COAL MINING REGIONS OF VIRGINIA USING THE PRECEDE-PROCEED MODEL

Health disparities are defined as health condition that are unique to, more serious, or more prevalent in subpopulations in socioeconomically disadvantaged and medically underserved, rural, and urban communities. The purpose of this work was to determine prevalence rates of the most common chronic diseases in counties located in southwest Virginia. Once the most prevalent chronic diseases were identified the information was used in the Precede-Proceed model (PPM) (acronyms for an “educational diagnosis” - PRECEDE” - Predisposing, Reinforcing and Enabling Constructs in Educational Diagnosis and Evaluation and an “ecological diagnosis” - PROCEED, for Policy, Regulatory, and Organizational Constructs in Educational and Environmental Development).

Virginia Department of Health death records (n= 755,414) from 1960 through 2012 were analyzed utilizing IBM SPSS Version 21.0. Data for each county in two Virginia Department of Health Districts in southwest Virginia were filtered from the state-level data. Chronic disease deaths rates from each county were aggregated over short year ranges. Data on social determinants of health were obtained from County Health Rankings and Road Maps (2013) and the US Census Bureau. The data was used to identify predisposing, reinforcing, and enabling factors that fit the PPM.

By utilizing the multidimensional PPM the dimensions of social/behavioral sciences, epidemiology, administration and education were integrated in the model that defined the problems, established goals and developed solutions to improve rates of chronic disease prevalence in coal communities in southwest Virginia.

Funding source: This study was sponsored by the Appalachian Research Initiative for Environmental Science (ARIES). ARIES is an industrial affiliates program at Virginia Tech, supported by members that include companies in the energy sector. The research under ARIES is conducted by independent researchers in accordance with the policies on scientific integrity of their institutions. The views, opinions and recommendations expressed herein are solely those of the authors and do not imply any endorsement by ARIES employees, other ARIES-affiliated researchers or industrial members. Information about ARIES can be found at http://www.energy.vt.edu/ARIES.”