Health researchers commonly use existing rural–urban continua based on population size and adjacency to metro areas to categorize counties. When these continua are collapsed into simple rural-versus-urban aggregations, significant differences within the categories are masked. We show that when the entire range of the 10-category Rural–Urban Continuum Codes (RUCC) is used, the direction of the coefficients may differ and the fit of the model varies substantially across contiguous categories. However, collapsing contiguous categories masks variations within the continuum. To the extent that health policy decisions are made based on such aggregations, inappropriate policy choices may result (e.g., low payments to counties with relatively high needs). Given Congressional calls to address rural health, and the new Office of Management and Budget (OMB) statistical area classification system, debate over appropriate categorizations schemes is timely. We regress age-adjusted all-causes of death on various socioeconomic factors to assess the appropriate use of variants of the rural–urban continuum for health research. Our findings support two main conclusions. First, researchers collapsing urban–rural categorization schemes may be masking important categorical differences, inadvertently influencing policymaking predicated on their work. Second, finer classification of settlements yields uneven results. That is, coefficients shift signs across the continuum, indicating that collapsed models may be inappropriate. Results derived using collapsed variants of the RUCC may be too unstable to use as health research and funding categorization schemes. We suggest that a health status or outcomes categorization scheme is likely to be a more appropriate metric for rural health research.
Population Research and Policy Review – Springer Journals
Published: Feb 2, 2008
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