Role of perceived heart risk factors by outpatient population in predicting cardiovascular risk

Ali Soroush1, Nasim Shams-Alizadeh2, Afsoon Vahdat3

  • 1Heart Research Center, Imam Ali Hospital, Kermanshah University of Medical Sciences. Kermanshah, Iran.

Insights

Perceptions of biological and psychological heart risks predict increased cardiovascular disease (CVD) risk. However, perceiving physiological risks is linked to lower CVD and lifestyle risks. Targeted interventions are crucial for high-risk individuals.

Area of Science:

  • Cardiology and Public Health

Background:

  • Cardiovascular diseases (CVDs) pose a growing threat, especially in developing nations.
  • Effective identification and management of risk factors are crucial for CVD prevention.
  • Understanding perceived heart risk factors (PHRFs) can aid in predicting and mitigating CVD risk.

Purpose of the Study:

  • To assess the predictive role of perceived heart risk factors (PHRFs) on cardiovascular risk in outpatient patients.
  • To identify key factors influencing cardiovascular risk and lifestyle risk.

Main Methods:

  • A cross-sectional study involving 150 outpatient patients.
  • Utilized the Perceived Heart Risk Factors Scale (PHRFS) and Cardiovascular Risk Assessment Questionnaire (CRAQ).
  • Data analyzed using Pearson correlation and multiple regression analyses.

Main Results:

  • 28% low, 40% medium, 22.7% high, and 9.3% severely high cardiovascular risk.
  • Physiological (β=-0.273), psychological (β=0.236), and biological (β=0.209) risk factors were significant predictors of cardiovascular risk.
  • Physiological risk factors were the strongest predictor of lifestyle risk (β=-0.264).
  • The model explained 9.2% of cardiovascular risk variance and 5.7% of lifestyle risk variance.

Conclusions:

  • Higher perception of biological and psychological risks correlates with increased cardiovascular risk.
  • Higher perception of physiological risks is associated with reduced lifestyle and total cardiovascular risk.
  • Targeting high-risk groups in CVD prevention programs can optimize resource allocation.

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