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Evaluation of the Predictive Value of Different Dietary Antioxidant Capacity Assessment Methods on Healthy and Unhealthy Phenotype in Overweight and Obese Women Publisher



Noori S1 ; Keshavarz SA2 ; Yekaninejad MS3 ; Naghshi S2 ; Mirzaei K1, 4
Authors
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Authors Affiliations
  1. 1. Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), 14155-6117, Tehran, Iran
  2. 2. Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
  3. 3. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Food Microbiology Research Center, Tehran University of Medical Sciences (TUMS), Tehran, Iran

Source: Journal of Diabetes and Metabolic Disorders Published:2022


Abstract

Purpose: Predictive value of different dietary antioxidant capacity assessment methods on healthy and unhealthy phenotypes in overweight and obese women is still unclear. This study aimed to evaluate the predictive value of different dietary antioxidant capacity assessment methods on healthy and unhealthy phenotypes in overweight and obese women. Methods: A total of 290 overweight and obese women were included in this cross-sectional study. Food intake was assessed using a semi-quantitative food frequency questionnaire (FFQ). Dietary antioxidant capacity was calculated using valid databases of antioxidant value. The receiver operating characteristic (ROC) curve method was used to evaluate the predictive value of antioxidant capacity indices, including dietary antioxidant quality score (DAQS), ferric reducing ability of plasma (FRAP), total reactive antioxidant potential (TRAP), and trolox equivalent antioxidant capacity (TEAC). Results: The results showed that the highest area under the ROC curve for predicting metabolically healthy obesity (MHO) belongs to the TRAP method (area under the curve (AUC) = 0.53). In addition, this method had the highest AUC for predicting inflammatory marker of C-reactive protein (hs-CRP) (AUC = 0.54) and the index of the homeostatic model assessment for insulin resistance (HOMA-IR) (AUC = 0.59). The highest AUC for triglyceride prediction was related to the DAQS method (AUC = 0.56). Moreover, a significant correlation of FRAP (r = −0.15, P = 0.02), TRAP (r = −0.19, P < 0.001), TEAC (r = −0.18, P< 0.001) with HOMA-IR was reached. Conclusion: The findings of this study show that the best way to predict the status of MHO is TRAP method. This method is also the best predictor of hs-CRP and HOMA-IR. DAQS method is the best predictor for TG. © 2022, The Author(s), under exclusive licence to Tehran University of Medical Sciences.
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