Background: The distribution of body fat and its variation is of great importance in determining the pathogenesis of insulin resistance. Central obesity has been recognized as an independent risk factor for diabetes. The objective of the study was to evaluate the predictive accuracy of various anthropometric measures of body fat in determining impaired glucose tolerance (IGT) or prediabetes among South Indian population.
Methodology: This was a community-based comparative cross-sectional study where the anthropometric measures of a representative sample of 171 individuals with glycosylated hemoglobin (HbA1c) in the range for IGT were compared with age- and gender-matched controls with HbA1c in the normal range. The predictive accuracy of the various anthropometric measures of obesity to identify individuals with IGT was estimated using the area under the receiver operating characteristic (ROC) curve.
Results: Patients with IGT in both genders had significantly higher BMI, waist circumference (WC), neck circumference (NC), and waist-to-height ratio (WHtR). ROC analysis revealed WHtR in females and NC among males to have the largest area under the curve for predicting IGT. In both genders, WC, WHtR, and NC had better predictive accuracy for prediabetes as compared to BMI and waist-to-hip ratio (WHR).
Conclusion: It is suggested that the WHtR and WC are better screening tools for prediabetes in comparison to BMI and WHR among the South Indian population.
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http://dx.doi.org/10.4103/jfmpc.jfmpc_269_20 | DOI Listing |
Nutrients
December 2024
Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI 96822, USA.
Compared to the general population of Hawai'i, Native Hawaiians and Other Pacific Islanders (NHPI) shoulder a disproportionately high risk for obesity-related cardiometabolic disorders, such as type 2 diabetes and cardiovascular disease. The gut microbiome is an area of rapid research interest for its role in regulating adjacent metabolic pathways, offering novel opportunities to better understand the etiology of these health disparities. Obesity and the gut microbiome are influenced by regional, racial-ethnic, and community-specific factors, limiting the generalizability of current literature for understudied populations.
View Article and Find Full Text PDFBiomedicines
December 2024
World-Class Research Center «Digital Biodesign and Personalized Healthcare», I.M. Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya Street, 119991 Moscow, Russia.
Ischemic heart disease (IHD) impacts the quality of life and is the most frequently reported cause of morbidity and mortality globally. To assess the changes in the exhaled volatile organic compounds (VOCs) in patients with vs. without ischemic heart disease (IHD) confirmed by stress computed tomography myocardial perfusion (CTP) imaging.
View Article and Find Full Text PDFNutrition
November 2024
Department of Gastroenterology (LIM-35), School of Medicine, University of São Paulo, São Paulo, Brazil.
Background: Sarcopenia is associated with clinical complications that increase mortality in older adults. Current screening tools, such as Sarc-F and Sarc-CalF, focus primarily on muscular performance but have limited sensitivity in identifying elderly individuals at risk of sarcopenia. The present study aims to develop a more comprehensive sarcopenia risk screening tool, Sarc-Global, which integrates additional anthropometric and clinical variables to enhance the sensitivity and accuracy of sarcopenia risk assessment in older adults.
View Article and Find Full Text PDFBackground: The mid-upper arm circumference (MUAC) is an anthropometric screening tool used to assess the nutritional status of individuals, offering a practical and feasible option in low-resource settings. However, the potential of MUAC as a screening tool for identifying thinness among adolescents remains underexplored.
Objective: This study aimed to evaluate the accuracy of MUAC in identifying all forms of thinness among adolescent girls enrolled in selected schools in Addis Ababa, Ethiopia.
Front Public Health
January 2025
Reproductive Medicine Center, Obstetrics and Gynecology, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Introduction: Frailty is an emerging global health burden, and there is no consensus on the precise prediction of frailty. We aimed to explore the association between grip strength and frailty and interpret the optimal machine learning (ML) model using the SHapley Additive exPlanation (SHAP) to predict the risk of frailty.
Methods: Data for the study were extracted from the China Health and Retirement Longitudinal Study (CHARLS) database.
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