<p>Adiposity Indicators as Cardio-Metabolic Risk Predictors in Adults from Country with High Burden of Obesity</p>

Abstract

Background: In Qatar more than 70% 0f the adults are overweight and obese. Different adiposity assessment methods have been proposed to identify individuals at cardio-metabolic risk. Purpose: This study aimed to compare anthropometric indicators with Dual-energy X-ray absorptiometry (DXA)-derived adiposity indicators in predicting cardio-metabolic risk among Qatari adults. Patients and Methods: A random sample of five hundred and fifty-eight (558) healthy Qatari adults (men and women) aged 20 to 50 years was obtained from Qatar Biobank survey data. Anthropometric data (weight, height, and waist circumference), the DXAderived data, and cardio-metabolic (CM) risk parameters were analyzed. A Spearman partial correlation coefficient, Receiver Operating Characteristics (ROC) curve and an area under curve (AUC) were used to assess the predicting ability of adiposity indicators for CM risk factors. Results: Adiposity indices (anthropometric and DXA) were significantly correlated with most of the CM indicators (r= −0.292 to 0.486, p< 0.001). The AUC of waist to height ratio (WHtR) was significantly higher than that of body mass index (BMI) and waist circumference (WC) in the prediction of low high density lipoprotein (HDL) (AUC=0.65, AUC=0.59; AUC=0.64), high low density lipoprotein (LDL) (AUC=0.67; AUC=0.62; AUC=0.66), high cholesterol (AUC=0.66; AUC=0.63; AUC=0.63), and high Homeostatic Model Assessment-(HOMA) (AUC= 0.81; AUC= 0.78; AUC=0.78). Among DXA-parameters, trunk fat had the highest AUCs for total cholesterol (AUC= 0.64, CI=0.56, 0.73), triglycerides and glucose index (TyG) (AUC=0.69, CI=0.64, 0.74), and HOMA (AUC=0.78, CI= 0.73, 0.84). Conclusion: Results of the present study show that adiposity indicators (WC and WHtR) are clinically valuable tools to identify individuals at risk of CVD compared to DXA-derived parameters, while DXA can provide more accurate estimates.

The Role of Different Indexes of Adiposity and Body Composition for the Identification of Metabolic Syndrome in Women with Obesity

“…These results were consistent with previous studies, demonstrating that WtHR was a valuable screening tool for adult cardiometabolic risk factors [ 27 ] and the most sensitive marker for predicting MetS [ 28 , 29 ].…”

The triglyceride‐glucose index as an adiposity marker and a predictor of fat loss induced by a low‐calorie diet

“…37,38 Interestingly, the predictive performance of the TyG index as an adiposity indicator has been reported in an Indian population, 39 as well as cardiometabolic risk predictor in an Arabian population. 40 The anthropometric amelioration and metabolic amelioration found in this study after energy restriction are similar to those reported in other comparable trials such as NUGENOB, 41 PREVIEW, 42 POUNDS LOST, 43 Look AHEAD 44 and DiRECT. 45 Accordingly, changes in weight, BMI and fat content after the 8 weeks of nutritional intervention were controlled by age, smoking status, cholesterol, blood pressure and daily physical activity.…”

<p>Optimal Body Fat Percentage Cut-Off Values in Predicting the Obesity-Related Cardiovascular Risk Factors: A Cross-Sectional Cohort Study</p>

“…47 Frequently, indicators of WC and WHR adipose tissue distribution within the body are recommended with regard to detecting obesity and determining overall health hazard, in view of the strong links between abdominal obesity and CVDs. 42,[47][48][49] The results of our study were based on adipose tissue measurement using the BIA method. To date, no clear cut-offs for BF% have been established for both obesity diagnosis, and CRFs risk prediction.…”