A comparison between perceived rurality and established geographic rural status among Indiana residents

Medicine (Baltimore). 2023 Oct 13;102(41):e34692. doi: 10.1097/MD.0000000000034692.

Abstract

The study assessed the association and concordance of the traditional geography-based Rural-Urban Commuting Area (RUCA) codes to individuals' self-reported rural status per a survey scale. The study included residents from rural and urban Indiana, seen at least once in a statewide health system in the past 12 months. Surveyed self-reported rural status of individuals obtained was measured using 6 items with a 7-point Likert scale. Cronbach's alpha was used to measure the internal consistency between the 6 survey response items, along with exploratory factor analysis to evaluate their construct validity. Perceived rurality was compared with RUCA categorization, which was mapped to residential zip codes. Association and concordance between the 2 measures were calculated using Spearman's rank correlation coefficient and Gwet's Agreement Coefficient (Gwet's AC), respectively. Primary self-reported data were obtained through a cross-sectional, statewide, mail-based survey, administered from January 2018 through February 2018, among a random sample of 7979 individuals aged 18 to 75, stratified by rural status and race. All 970 patients who completed the survey answered questions regarding their perceived rurality. Cronbach's alpha value of 0.907 was obtained indicating high internal consistency among the 6 self-perceived rurality items. Association of RUCA categorization and self-reported geographic status was moderate, ranging from 0.28 to 0.41. Gwet's AC ranged from -0.11 to 0.26, indicating poor to fair agreement between the 2 measures based on the benchmark scale of reliability. Geography-based and self-report methods are complementary in assessing rurality. Individuals living in areas of relatively high population density may still self-identify as rural, or individuals with long commutes may self-identify as urban.

MeSH terms

  • Cross-Sectional Studies
  • Humans
  • Indiana / epidemiology
  • Reproducibility of Results
  • Rural Population*
  • Surveys and Questionnaires
  • Urban Population