Affiliations 

  • 1 Department of Medical Biochemistry, Nobel College, Pokhara University, Gandaki, Nepal
  • 2 Department of Community Medicine, International Medical School, Management and Science University, Shah Alam, Malaysia
  • 3 Manmohan Cardiothoracic Vascular and Transplant Center, Institute of Medicine, Tribhuvan University Teaching Hospital, Kathmandu, Nepal
J Midlife Health, 2024;15(2):81-90.
PMID: 39145261 DOI: 10.4103/jmh.jmh_179_23

Abstract

BACKGROUND: The use of nontraditional lipid parameters for assessing clinical conditions is emerging; however, no study has identified thresholds for those parameters for the identification of cardiovascular disease (CVD) risk. The present study aimed to establish the thresholds of nontraditional lipid parameters and test its ability to identify CVD risk factors.

METHODOLOGY: A cross-sectional study in women (n = 369, age: 46 ± 13 years, body mass index (BMI): 26.31 ± 2.54 kg/m2) was conducted. Blood samples were collected and high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, total cholesterol (TC), and triglycerides (TGs) were estimated. Subsequently, nontraditional lipid parameters were calculated, namely non-HDL-C, Castelli's Risk Index II (CRI-II), CRI-I, lipoprotein combined index (LCI), atherogenic index (AI), and AI of plasma (AIP).

RESULTS: Based on TC (≥200 mg/dL), the derived thresholds for non-HDL-C, CRI-II, CRI-I, LCI, AI, and AIP were 139 mg/dL, 2.29, 3.689, 58,066, 2.687, and 0.487, respectively. Similarly, based on the threshold of TG (≥150 mg/dL), the derived thresholds for non-HDL-C, CRI-II, CRI-I, LCI, AI, and AIP were 127 mg/dL, 2.3, 3.959, 58,251, 2.959, and 0.467, respectively. Out of considered five risk factors, non-HDL-C, CRI-II, CRI-I, LCI, and AI thresholds were capable in identifying four risk factors (physical activity, blood pressure, BMI, and age) and AIP was able to associate with two risk factors at most (blood pressure and BMI).

CONCLUSION: The derived thresholds of nontraditional lipid parameters were capable of differentiating between CVD risk and nonrisk groups suggesting the possible use of these thresholds for studying CVD risk.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.