Saqlain Muhammad, Akhtar Zainab, Karamat Raheela, Munawar Samra, Iqbal Maria, Fiaz Muhammad, Zafar Muhammad Mubeen, Saeed Sadia, Nasir Muhammad Farooq, Naqvi S M Saqlan, Raja Ghazala Kaukab
Department of Biochemistry, PMAS-Arid Agriculture University, Rawalpindi, Pakistan.
Department of Pathology, Shaheed Zulfiqar Ali Bhutto Medical University, Islamabad, Pakistan.
Iran J Public Health. 2019 Dec;48(12):2224-2231.
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).
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.
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.
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.
多种人体测量指标已在不同世界人群中用作估计肥胖及其相关健康风险的标志物。本研究是一项基于大量人群的研究,涉及五种人体测量肥胖量表;体重指数(BMI)、腰围(WC)、腰臀比(WHR)、基础肥胖指数(BAI)和内脏脂肪指数(VAI),以确定最能预测肥胖及相关健康并发症的常见肥胖特征。
2012年至2017年期间,从巴基斯坦四个省份(旁遮普省、信德省、开伯尔-普赫图赫瓦省和俾路支省)收集了总共4000名受试者,包括BMI各分类中的1000名。获得了完整的人体测量数据,采集了血样并进行了生化分析。进行了描述性统计、线性回归、二元和多元回归分析。
我们的数据分析探讨了肥胖的五个指标;BMI、WC、WHR、BAI和VAI与常见代谢健康并发症之间的关系。效应量分析清楚地表明,BMI每增加一个单位,所有人体测量和临床参数均显著升高。肥胖特征与风险表型(高血压、高血糖和血脂异常)的总体及性别特异性关联分析表明,WC与所有三种代谢风险均存在显著关联。观察到其他肥胖特征与代谢风险存在不同程度的相关性。肥胖人群组中不同肥胖等级的频率如下:I级55.7%,II级28.50%,III级15.80%。
在巴基斯坦人群中,WC是肥胖相关代谢健康问题的有力预测指标。而BMI对WHR、VAI和BAI等其他肥胖指标有显著的增加作用。