Amina Nadeem1, Abdul Khaliq Naveed2, Muhammad Mazhar Hussain3, Syed Irfan Raza4. 1. Department of Physiology, Army Medical College, National University of Sciences and Technology, Islamabad, Pakistan. nadeemamina@yahoo.com 2. Department of Biochemistry and Dean, Army Medical College, National University of Sciences and Technology, Islamabad, Pakistan. 3. Department of Physiology, Army Medical College, National University of Sciences and Technology, Islamabad, Pakistan. 4. Department of Biochemistry and Molecular Biology, Army Medical College, National University of Sciences and Technology, Islamabad, Pakistan.
Abstract
OBJECTIVE: To determine the cut-off values of anthropometric indices to indicate insulin resistance and correlation of these indices with insulin resistance in Pakistani adults. METHODS: The cross-sectional study was conducted at the Military Hospital and Army Medical College, Rawalpindi, Pakistan, from June 2010 to November 2011. The study measured 209 adults for body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio and conicity index. Receiver operating characteristics curve analyses were done to determine the predictive values of these anthropometric measures and their cut-off values for insulin resistance by triglyceride/high density lipoprotein ratio. RESULTS: Overall mean age was 51.5 +/- 1.16 years (range: 28-73) and there were 136 (65%) males and 73 (35%) females. Body mass index had the maximum predictive value for insulin resistance followed by waist circumference and waist-to-height ratio in males (p < 0.0001), sensitivity and specificity being 68% and 62% respectively with cut-off value of 25.04 kg/m2. ROC curve analyses showed the maximum predictive value of conicity index for insulin resistance followed by waist circumference and waist-to-height ratio in females (p < 0.08), sensitivity and specificity being 65% and 50% respectively with cut-off value of 1.39. CONCLUSION: In Pakistani male adults, BMI is the best indicator of insulin resistance, while in female adults, conicity index is the best indicator.This is the first study in Pakistan reporting predictive values of anthropometric indices as a non-invasive method in determining insulin resistance.
OBJECTIVE: To determine the cut-off values of anthropometric indices to indicate insulin resistance and correlation of these indices with insulin resistance in Pakistani adults. METHODS: The cross-sectional study was conducted at the Military Hospital and Army Medical College, Rawalpindi, Pakistan, from June 2010 to November 2011. The study measured 209 adults for body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio and conicity index. Receiver operating characteristics curve analyses were done to determine the predictive values of these anthropometric measures and their cut-off values for insulin resistance by triglyceride/high density lipoprotein ratio. RESULTS: Overall mean age was 51.5 +/- 1.16 years (range: 28-73) and there were 136 (65%) males and 73 (35%) females. Body mass index had the maximum predictive value for insulin resistance followed by waist circumference and waist-to-height ratio in males (p < 0.0001), sensitivity and specificity being 68% and 62% respectively with cut-off value of 25.04 kg/m2. ROC curve analyses showed the maximum predictive value of conicity index for insulin resistance followed by waist circumference and waist-to-height ratio in females (p < 0.08), sensitivity and specificity being 65% and 50% respectively with cut-off value of 1.39. CONCLUSION: In Pakistani male adults, BMI is the best indicator of insulin resistance, while in female adults, conicity index is the best indicator.This is the first study in Pakistan reporting predictive values of anthropometric indices as a non-invasive method in determining insulin resistance.
Authors: Nayla Cristina do Vale Moreira; Renan M Montenegro; Haakon E Meyer; Bishwajit Bhowmik; Ibrahimu Mdala; Tasnima Siddiquee; Virgínia Oliveira Fernandes; Akhtar Hussain Journal: Int J Environ Res Public Health Date: 2019-09-26 Impact factor: 3.390