Human Nutrition & Metabolism (Mar 2024)
Body indices based receiver operating characteristics curve models are important risk assessing tools for metabolic diseases among Asian women
Abstract
Purpose: The right way to measure obesity is still a matter of debate. This study will look at the prevalence of obesity, anthropometrics, and body composition as screening tools for obesity and adiposity among adult women in urban Prayagraj (Allahabad), Uttar Pradesh, India. It will also try to figure out exactly what level of obesity is linked to a metabolic risk. Methods: A Cross-sectional study comprising 570 urban women of Prayagraj (Allahabad), Uttar Pradesh, India aged 20–49 years were examined for anthropometry, body composition analysis, blood pressure, random blood sugar, and haemoglobin. Results: Except for total body water (TBW), all measures of obesity and health markers increased with age (p < 0.000, 95% CI-confidence interval). Appropriate cutoffs calculated with model for adult women for body fat (%), muscle mass (kg), total body water (%), and visceral fat (kg) were 33.5, 34.5, 46.5, and 4.5 respectively. Using stepwise logistic regression, two models eliminating waist circumference (WC) and wait to hip ratio (WHR), respectively, were created. Age, WHR, and visceral fat (VF) for systolic blood pressure; age and TBW for diastolic blood pressure; age and VF for random blood sugar; WHR, body fat% (BF %), Muscle mass (MM), and age for haemoglobin, were all significantly associated with the presence of metabolic risk variables in Model 1. In model 2, only age was significant for predicting systolic blood pressure; age, TBW, and WC for diastolic blood pressure; age and VF for random blood sugar; BF%, WC, and age for haemoglobin were shown to be significantly associated with metabolic risk variables. Conclusions: Two basic models for predicting metabolic risk in Asian Indians were studied. Both models can be used to assess metabolic risk in them.
