Submitted: 08 Jan 2018
Revised: 16 Mar 2019
Accepted: 10 May 2019
First published online: 23 May 2019
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J Cardiovasc Thorac Res. 2019;11(2):100-108.
doi: 10.15171/jcvtr.2019.18
  Abstract View: 18
  PDF Download: 16

Original Article

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

Ali Soroush 1, Nasim Shams-Alizadeh 2, Afsoon Vahdat 3, Zeinab Mohebi 4, Mozhgan Saeidi 4, Saeid Komasi 3 *

1 Heart Research Center, Imam Ali Hospital, Kermanshah University of Medical Sciences. Kermanshah, Iran
2 Lifestyle Modification Research Center, Imam Reza Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran
3 Clinical Research Development Center, Imam Reza Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran
4 Cardiac Rehabilitation Center, Imam Ali Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran

Abstract

Introduction: Regarding the expanding population in developing countries who are at risk for cardiovascular diseases (CVDs), identification and management of effective factors are important in reducing the risk of CVDs. So, the present study aimed to assess the role of perceived heart risk factors (PHRFs) in the prediction of cardiovascular risk among outpatient patients.
Methods: The samples of this cross-sectional study included 150 outpatient patients who attend the clinic of Imam Reza hospital during October-December 2016. The participants were completed the Perceived Heart Risk Factors Scale (PHRFS) and Cardiovascular Risk Assessment Questionnaire (CRAQ). Data analyzed through Pearson correlation and multiple regression analyses.
Results: Based on the findings, 28%, 40%, 22.7%, and 9.3% of patients were low, medium, high, and severely high-risk, respectively. The strongest predictors of the cardiovascular risk were physiological (β = -0.273; P = 0.004), psychological (β=0.236; P = 0.020), and biological risk factors (β=0.209; P = 0.016), respectively. In addition, the strongest predictor of the lifestyle risk was physiological risk factors (β = -0.264; P = 0.007). Other variables do not play a significant role in predict the lifestyle risk (P > 0.05). Our model was able to explain 9.2% of cardiovascular risk variance and 5.7% of cardiovascular risk caused by lifestyle variance.
Conclusion: The higher patients’ perception about biological and psychological risk factors is concerned as an alarm for increased cardiovascular risk while higher perception about physiological risk factors is associated with reduced cardiovascular risk caused by lifestyle and total cardiovascular risk. The programs reducing cardiovascular risk should target the high-risk groups to save cost and time.
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