BMC Public Health (May 2024)

Regional and rural-urban patterns in the prevalence of diagnosed hypertension among older U.S. adults with diabetes, 2005–2017

  • Jalal Uddin,
  • Sha Zhu,
  • Gargya Malla,
  • Emily B. Levitan,
  • Deborah B. Rolka,
  • April P. Carson,
  • D. Leann Long

DOI
https://doi.org/10.1186/s12889-024-18802-5
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 11

Abstract

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Abstract Background Hypertension prevalence among the overall US adult population has been relatively stable during the last two decades. However, whether this stabilization has occurred across rural-urban communities and across different geographic regions is unknown, particularly among older adults with diabetes who are likely to have concomitant cardiovascular risk factors. Methods This serial cross-sectional analysis used the 5% national sample of Medicare administrative claims data (n = 3,516,541) to examine temporal trends (2005–2017) in diagnosed hypertension among older adults with diabetes, across urban-rural communities and US census regions (Northeast, Midwest, South, and West). Joinpoint regression was used to obtain annual percent change (APC) in hypertension prevalence across rural-urban communities and geographic regions, and multivariable adjusted regression was used to assess associations between rural-urban communities and hypertension prevalence. Results The APC in the prevalence of hypertension was higher during 2005–2010, and there was a slowdown in the increase during 2011–2017 across all regions, with significant variations across rural-urban communities within each of the regions. In the regression analysis, in the adjusted model, older adults living in non-core (most rural) areas in the Midwest (PR = 0.988, 95% CI: 0.981–0.995) and West (PR = 0.935, 95% CI: 0.923–0.946) had lower hypertension prevalence than their regional counterparts living in large central metro areas. Conclusions Although the magnitudes of these associations are small, differences in hypertension prevalence across rural-urban areas and geographic regions may have implications for targeted interventions to improve chronic disease prevention and management.

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