Tehran University of Medical Sciences Iranian Journal of Public Health 2251-6085 48 12 2019 12 02 2224 2231 Muhammad SAQLAIN Department of Biochemistry, PMAS–Arid Agriculture University, Rawalpindi, Pakistan Zainab AKHTAR Department of Biochemistry, PMAS–Arid Agriculture University, Rawalpindi, Pakistan Raheela KARAMAT Department of Biochemistry, PMAS–Arid Agriculture University, Rawalpindi, Pakistan Samra MUNAWAR Department of Biochemistry, PMAS–Arid Agriculture University, Rawalpindi, Pakistan Maria IQBAL Department of Biochemistry, PMAS–Arid Agriculture University, Rawalpindi, Pakistan Muhammad FIAZ Department of Pathology, Shaheed Zulfiqar Ali Bhutto Medical University, Islamabad, Pakistan Muhammad Mubeen ZAFAR Department of Biochemistry, PMAS–Arid Agriculture University, Rawalpindi, Pakistan Sadia SAEED Department of Biochemistry, PMAS–Arid Agriculture University, Rawalpindi, Pakistan Muhammad Farooq NASIR Department of Entomology, PMAS–Arid Agriculture University, Rawalpindi, Pakistan S.M. Saqlan NAQVI Department of Biochemistry, PMAS–Arid Agriculture University, Rawalpindi, Pakistan Ghazala Kaukab RAJA Department of Biochemistry, PMAS–Arid Agriculture University, Rawalpindi, Pakistan 2019 12 02 Background: A number of anthropometric indices have been used in different world populations as markers to estimate obesity and its related health risks. The present study is large population based study dealing with five anthropometric obesity scales; Body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR), basal adiposity index (BAI), and Visceral adiposity index (VAI) to identify common adiposity trait(s) that best predict obesity and associated health complication(s). Methods: A total of 4000 subjects including 1000 in each category of BMI from four provinces (Punjab, Sindh, Kahyber pakhtoonkha and Balochistan) of Pakistan from 2012-2017 were collected. Complete anthropometric measurementswere obtained and blood samples were collected and Biochemical profiling was performed. Descriptive statistics, linear regression, binary and multiple regression analysis was done. Results: Our data analysis explored the relationships of obesity five indices; BMI, WC, WHR, BAI, and VAI with common metabolic health complications. Effect size analysis clearly indicates that a unit increase in BMI significant raised all anthropometric and clinical parameters. General and sex specific association analysis of adiposity traits with risk phenotypes (hypertension, hyperglycemia and dyslipidemia) indicated significant associations of WC with all three metabolic risks. Varying degrees of correlations of other adiposity traits with metabolic risks were observed. Frequency of different obesity classes among obese population group were as follows; 55.7% class I, 28.50% Class II and 15.80% Class III. Conclusion: WC is the strong predictor of obesity associated metabolic health issues in Pakistani populations. While BMI has significant increasing effect on other obesity indices like WHR, VAI and BAI. https://ijph.tums.ac.ir/index.php/ijph/article/view/19074 https://ijph.tums.ac.ir/index.php/ijph/article/download/19074/6604