A Formal Analysis of Anthropometric Parameters for Effective Forecasting of Dyslipidemia in Healthy Young Adults

Background: Obesity in the younger age groups predisposes an individual for a high risk for developing dyslipidemia and cardiovascular disease. Distribution of the abdominal adipose tissue cannot be accurately described by the traditional anthropometric indices.Newer anthropometric indices are better predictors of obesity.

Objective: To compare the ability of different anthropometric indices in predicting dyslipidemia in healthy young adults.

Materials and Methods: The cross-sectional study was performed on 100 subjects (48 males and 52 females) at K S Hegde Medical Academy from 2017 to 2018 (power of study: 80%). Apparently healthy individuals attending the executive health checkup plan and individuals from hospital staff aged 18-35 years were selected for the study. The Kolmogorov Smirnov test was used to determine the data's normality. Pearson's correlation test was used to measure the relationship between lipid parameters and various anthropometric indices. The predictive capacity of various anthropometric indices for distinguishing between dyslipidemic and healthy individuals was investigated using ROC curve analysis.

Results: Newer anthropometric measurement approaches such as ABSI, BRI, CI, AVI, VAI, and LAP have been suggested as better instruments for predicting dyslipidemia. The present study found that VAI had the highest predictive efficiency in identifying dyslipidemia among apparently healthy adults using ROC analysis. This discovery may lead to the use of a simple anthropometric index as a screening tool for cardiovascular disease prediction.

Conclusion: The current study has shown that the VAI has emerged as a valuable instrument for dyslipidemia assessment in healthy young adults. Using regular laboratory tests and basic anthropometric measurements, VAI can be easily measured and can therefore be used as relevant dyslipidemia evaluation methods in clinical practice.