Association of rurality and decreased continuity of care prior to a diagnosis of prediabetes

J Rural Health. 2025 Jan;41(1):e12907. doi: 10.1111/jrh.12907.

Abstract

Purpose: To assess trends in continuity of care (COC) by geographic context (i.e., rural vs urban) among a cohort of persons with prediabetes prior to and after diagnosis of prediabetes.

Methods: We use cross-sectional data from Geisinger's electronic health record between 1997 and 2017. Our dependent variable is the Modified Modified Continuity Index (MMCI), a measure of dispersion among primary care providers seen. Our primary independent variable is a binary indicator variable for rurality constructed from the 2010 Census Bureau's Urban and Rural Classification. We control for age, sex, race/ethnicity, and baseline clinical characteristics. We use fractional logistic regression with bootstrapped standard errors.

Findings: Urban residing patients had greater odds of increased COC in the 3-year period prior to a diagnosis of prediabetes (aOR = 1.10, 95% CI = 1.03, 1.18; P = .007). However, there were no significant differences in COC among rural and urban residing patients upon diagnosis of prediabetes in unadjusted and fully adjusted regression models. Other factors significantly associated with COC across the observed time periods (pre- and post-diagnosis of prediabetes) include age, male, and hypertension in the patients' problem list at baseline.

Conclusions: Among persons diagnosed with prediabetes, rurality was associated with decreased COC in the 3-year period prior to being diagnosed. However, in the 3-year period after diagnosis of prediabetes, geographic disparities in COC were not observed. Rural residing patients need enhanced continuity of primary care to potentially improve opportunistic screening for prediabetes.

Keywords: continuity; diabetes; health disparities; prevention; primary care; rural; screening.

MeSH terms

  • Adult
  • Aged
  • Cohort Studies
  • Continuity of Patient Care* / standards
  • Continuity of Patient Care* / statistics & numerical data
  • Cross-Sectional Studies
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Prediabetic State* / diagnosis
  • Prediabetic State* / epidemiology
  • Rural Population* / statistics & numerical data