Cardiovascular disease risk score prediction models for women and its applicability to Asians

Louise Gh Goh1, Satvinder S Dhaliwal1, Timothy A Welborn2

  • 1School of Public Health, Curtin Health Innovation Research Institute, Curtin University, Perth, WA, Australia.

Insights

Cardiovascular disease (CVD) risk varies by ethnicity. This study found Asian women generally had lower CVD risk than Caucasian women, though some risk predictions were similar between Asian and Australian women.

Area of Science:

  • Cardiology
  • Public Health
  • Epidemiology

Background:

  • Cardiovascular disease (CVD) risk factors show ethnic variations in distribution and association.
  • Understanding these differences is crucial for accurate risk assessment and targeted prevention strategies.

Purpose of the Study:

  • To assess and compare the 10-year predicted cardiovascular disease (CVD) risk between Asian and Caucasian women in a multiethnic cohort.
  • To evaluate ethnic variations in CVD risk factor prevalence and their impact on risk prediction models.

Main Methods:

  • Utilized data from 4,354 women (aged 20-69) with no prior heart disease, diabetes, or stroke.
  • Calculated 10-year CVD risk using Framingham, SCORE, and general CVD risk score models, with ethnicity determined by country of birth.
  • Employed nonparametric statistics to compare risk levels between ethnic groups.

Main Results:

  • Asian women generally exhibited a lower risk of CVD compared to Caucasian women.
  • However, the 10-year predicted CVD risk was similar between Asian and Australian women across certain risk models.
  • These findings align with established Australian CVD prevalence data.

Conclusions:

  • Ethnicity is a significant factor that must be integrated into cardiovascular disease (CVD) risk assessment protocols.
  • Current Australian risk quantification and treatment standards may be applicable to Asian populations as an interim measure.
  • Recommended risk models include the SCORE risk chart (low-risk regions) and Framingham risk score, with a call for incorporating variables like obesity, diet, and physical activity to enhance risk estimation.
Abstract

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