Body Roundness Index Trajectories and the Incidence of Cardiovascular Disease: Evidence From the China Health and Retirement Longitudinal Study

J Am Heart Assoc. 2024 Oct;13(19):e034768. doi: 10.1161/JAHA.124.034768. Epub 2024 Sep 25.

Abstract

Background: Several previous cross-sectional studies suggested that body roundness index (BRI) may be associated with cardiovascular disease (CVD). However, the association should be further validated. Our study aimed to assess the association of the BRI trajectories with CVD among middle-aged and older Chinese people in a longitudinal cohort.

Methods and results: A total of 9935 participants from the CHARLS (China Health and Retirement Longitudinal Study) with repeated BRI measurements from 2011 to 2016 were included. The BRI trajectories were identified by group-based trajectory modeling. The primary outcome was incident CVD (stroke or cardiac events), which occurred in 2017 to 2020. Cox proportional hazards regression models were used to examine the association of BRI trajectories with CVD risk. Participants were divided into 3 BRI trajectories, named the low-stable BRI trajectory, moderate-stable BRI trajectory and high-stable BRI trajectory, accounting for 49.81%, 42.35%, and 7.84% of the study population, respectively. Compared with participants in the low-stable BRI trajectory group, those in the moderate-stable and high-stable BRI trajectory groups had an increased risk of CVD, with multivariable adjusted hazard ratios of 1.22 (95% CI, 1.09-1.37) and 1.55 (95% CI, 1.26-1.90), respectively. Furthermore, simultaneously adding the BRI trajectory to the conventional risk model improved CVD risk reclassification (all P<0.05).

Conclusions: A higher BRI trajectory was associated with an increased risk of CVD. The BRI can be included as a predictive factor for CVD incidence.

Keywords: CHARLS; body roundness index; cardiovascular disease; group‐based trajectory modeling.

MeSH terms

  • Aged
  • Cardiovascular Diseases* / epidemiology
  • China / epidemiology
  • Female
  • Humans
  • Incidence
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Retirement / statistics & numerical data
  • Risk Assessment
  • Risk Factors