Background and Purpose: The prevalence of premature coronary artery disease (PCAD) has increased in recent years, particularly among younger populations. The differences in the risk factor profiles of PCAD and late coronary artery disease (LCAD) remain insufficiently understood. Therefore, this study aimed to compare the demographic, clinical, anthropometric, and laboratory risk factors associated with PCAD and LCAD.
Materials and Methods: This case-control study was conducted among ۲۰۶ patients with angiography-confirmed CAD who were referred to Fatemeh-Zahra Heart Center during ۲۰۲۱-۲۰۲۲. Participants were divided into two groups: ۱۰۳ patients with PCAD and ۱۰۳ patients with LCAD. Demographic, clinical, anthropometric, and laboratory data were collected using a researcher-designed checklist based on patients’ medical records and clinical evaluations. Data were analyzed using IBM SPSS Statistics (version ۲۶). Independent-samples t-test, Mann-Whitney U test, chi-square test, and logistic regression analysis were used for statistical analysis.
Results: Patients with PCAD had significantly higher body mass index, waist circumference (WC), hip circumference, triglyceride levels, low-density lipoprotein (LDL) levels, and waist-to-hip ratio. In contrast, creatinine, blood urea nitrogen, aspartate aminotransferase, and vitamin D levels were significantly higher in patients with LCAD. Multivariable logistic regression analysis demonstrated that higher educational level, housewife status, alcohol consumption, family history of PCAD, and elevated WC were independently associated with increased odds of PCAD (P<۰.۰۵). In contrast, cigarette smoking was more strongly associated with LCAD (P=۰.۰۰۲).
Conclusion: The findings of this study suggest that the risk factor profiles of PCAD and LCAD differ considerably. Anthropometric indices and familial predisposition appear to play a more prominent role in PCAD, whereas smoking and renal dysfunction were more common among patients with LCAD. The identification of these distinct risk factor patterns may contribute to improved prevention, early detection, and management strategies for CAD, particularly among younger populations.