Loading
Life sciences · Journal article
International Journal of Medical Science in Clinical Research and Review · November 5, 2026
No summary has been generated for this record yet. What follows is drawn from its source metadata only.
Journal article.
No findings were extractable from the material analysed.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
The source did not state who this applies to in practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
This record has not been graded across any dimension yet. Treat the label above as provisional and read the source.
What is missing. This record has no bottom line, key findings, reported figures, evidence dimensions. That is a gap in the analysis, not a judgement about the study.
ABSTRACT Background: India faces a dual burden of communicable and non-communicable diseases, with rising rates of obesity, particularly abdominal obesity, which is linked to increased cardiovascular disease (CVD) risk. Anthropometric measures like Body Mass Index (BMI) have limitations in assessing fat distribution. The Conicity Index (CI) incorporates waist circumference (WC), height, and weight, potentially offering a better measure of central obesity. This study aimed to evaluate the utility of CI as a screening tool for CVD risk factors in an Indian population in Kota, Rajasthan. Methods: A hospital-based cross-sectional study was conducted at a Govt Medical College involving 230 patients (>18 years) recruited via simple random sampling from the outpatient clinic in the medicine department. Data collected included medical history, anthropometric measurements (WC, height, weight), blood pressure, fasting blood glucose (FBG), and lipid profile. Associations between CI (using a cutoff of ≥1.23 for high CI) and various risk factors were analyzed using the Chi-Square test (p<0.05 significant). ROC curve analysis was performed to assess discriminatory power. Results: The study included 120 males (52.2%) and 110 females (47.8%), with the largest age group being 40-<60 years (39.1%). MetS (Metabolic Syndrome) prevalence was 34.8%. High CI (≥1.23) was found in 70.4% of participants. CI showed statistically significant associations with MetS (p<0.001), WC ≥80 cm (p<0.001), Blood Pressure ≥130/85 mmHg (p<0.05), VLDL (Very Low Density Lipoprotein)-Cholesterol ≥20 mg/dl (p<0.05), BMI ≥23 kg/m² (p<0.05), and high WtHR (Waist to Hip CIrcumference Ratio) (p<0.001). ROC analysis for predicting cardiovascular risk (PROCAM) showed CI had the highest AUC (0.8840, p<0.05) with 77.8% sensitivity and 81.0% specificity. Conclusion: CI is significantly associated with MetS, central obesity measures (WC, WtHR), BMI, elevated blood pressure, and VLDL-cholesterol in this population, hence its utility as a simple screening tool for identifying individuals with increased central obesity-related cardiovascular risk. Keywords: Conicity index, cardiovascular diseases, metabolic syndrome