Does the Choice of Rurality Measurement Matter? A Case Study of Rural-Urban Gradients in the Prevalence of Depression
Steven A. Cohen, Virginia Commonwealth University
Defining "rural" has been a persistent challenge in demographic and health research. The objectives of this study are to describe, compare, and contrast five common measures of rurality in US counties, overall and by region; demonstrate how the population prevalence of depression varies rurality, and how the inferences about the association between rurality and depression depends upon the rurality measurement used. We abstracted five measures of reality from the 2010 US Census and the USDA to characterize US counties, including rural-urban continuum codes, urban influence codes, and population density quartile. The highest observed rank correlation between different sources (Census vs. USDA) was between rural-urban continuum codes and percent urban population (rho = 0.447, p < 0.001). Associations were stronger in the Northeast and West states and weakest in the South and Midwest. Non-monotonic associations were observed between depression and rurality. Developing meaningful and universally accepted rurality measures for demographic research.
Presented in Poster Session 7