Association between calf girth and peripheral artery disease in the Atherosclerosis Risk in Communities Study

J Cardiol. 2020 Sep;76(3):273-279. doi: 10.1016/j.jjcc.2020.04.002. Epub 2020 May 19.

Abstract

Background: The pathogenesis of peripheral artery disease (PAD) is associated with impaired calf muscle. We sought to investigate the association between gender-specific calf girth and the prevalence of PAD among participants from a community-based cohort study.

Methods: A total 13,808 participants in the Atherosclerosis Risk in Communities (ARIC) study without prior PAD were included in the final analysis. Calf girth was measured at baseline (1985-1987). A hospital diagnosis with an ICD-9 code defined incident PAD during follow up. Cox regression analysis adjusted for demographic variables and other covariates was used to estimate hazard ratios (HR) and 95% confidence interval (CI) for the association between calf girth and PAD.

Results: After a medium follow-up of 25.2 years, the overall prevalence of PAD in our study was 5.2% (721/13,808), 335 patients were women and 386 were men. The adjusted HR for PAD with calf girth as continuous variables was 0.99 (95% CI 0.95-1.04) in females and 0.93 (95% CI 0.88-0.99) in males, respectively. Moreover, interaction for gender was statistically significant between calf girth and PAD in overall population (p=0.001).

Conclusions: Our findings revealed a linear association of calf girth with the prevalence of PAD among male participants in ARIC.

Keywords: Atherosclerosis Risk in Communities; Calf girth; Peripheral artery disease.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Anthropometry / methods*
  • Body Size*
  • Cohort Studies
  • Female
  • Heart Disease Risk Factors
  • Humans
  • Incidence
  • Leg / physiopathology*
  • Male
  • Middle Aged
  • Peripheral Arterial Disease / diagnosis*
  • Peripheral Arterial Disease / epidemiology
  • Peripheral Arterial Disease / etiology
  • Prevalence
  • Proportional Hazards Models
  • Regression Analysis
  • Risk Assessment / methods*
  • Risk Factors
  • Sex Factors