Cureus
Cardiometabolic Risk Factors, Obesity Phenotypes, and Novel Anthropometric Indices in Patients With Acute Coronary Syndrome: A Hospital-Based Case-Control Study in Central India
By Sanskruti Boob, Tanuja Manohar, Fahad Idrees Shaikh and 6 others.
Abstract
Background: Acute coronary syndrome (ACS) is the most severe manifestation of cardiovascular disease and disproportionately affects South Asians at a younger age than Western populations.Body mass index (BMI) inadequately reflects visceral adiposity, particularly in Indian populations.Obesity phenotypes, which combine BMI with metabolic status, and novel anthropometric indices may improve cardiovascular risk assessment, but data from Indian ACS patients remain limited.Objectives: To evaluate the association between cardiometabolic risk factors, obesity phenotypes, and novel anthropometric indices with ACS, and to quantify these associations using odds ratios (ORs).Methods: This case-control study enrolled 50 patients with confirmed ACS (unstable angina, Non-STelevation myocardial infarction (NSTEMI), or ST-elevation myocardial infarction (STEMI)) and 50 age-, sex-, and weight-matched healthy controls at a tertiary care hospital.Sociodemographic, clinical, anthropometric, and biochemical data were recorded.Participants were classified into four obesity phenotypes -metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obese (MHO), and metabolically unhealthy overweight/obese (MUO) -based on BMI and presence of hypertension, diabetes, and/or dyslipidemia.Five novel indices were calculated: A body shape index (ABSI), body roundness index (BRI), waist-to-height ratio (WHtR), weightadjusted waist index (WWI), and abdominal volume index (AVI).Continuous variables were compared using t-tests and categorical variables using chi-square/Fisher's exact test; unadjusted ORs with 95% CIs were calculated.p<0.05 was significant.ST-elevation myocardial infarction Results: Cases and controls were comparable for age and sex (p>0.05).Hypertension (60% vs 36%), diabetes (52% vs 28%), dyslipidemia (56% vs 32%), and smoking (44% vs 24%) were more common among cases (all p<0.05).Per 1-SD increase, BMI was not significantly associated with ACS (Exp(B) 1.208, 95% CI 0.816-1.790,Wald 0.89, p=0.345), whereas waist circumference, waist-to-hip ratio, and neck circumference were each significantly associated with ACS.Each of the five novel indices was significantly associated with ACS per 1-SD increase (all p<0.001; e.g., WHtR Exp(B) 2.473, 95% CI 1.638-3.732,Wald 18.59); because each index reflects a different geometric construct even when expressed per 1-SD, indices are not ranked by strength of association.Using MHNW as reference, MUO showed significantly increased odds of ACS (OR 3.33, 95% CI 1.10-10.12);MUNW showed a similar point estimate (OR 3.33, 95% CI 0.89-12.49)that did not reach significance (p=0.074), and MHO was not significantly associated with ACS (OR 1.50, 95% CI 0.48-4.65).All ORs are unadjusted.Conclusion: In this unadjusted, cross-sectional comparison, metabolic health and central fat distribution were associated with ACS, whereas BMI was not.Obesity phenotyping and novel anthropometric indices warrant further evaluation in larger, multivariable-adjusted, prospective studies as potential adjuncts to cardiovascular risk stratification in South Asian populations.







