Key result
Waist circumference strongly predicts metabolic complications including hypertension, hyperglycemia, and dyslipidemia.
Why the study?
Multiple anthropometric indices estimate obesity risks across populations, but the best adiposity trait to predict obesity and associated health complications required identification.
Which adiposity trait best predicts obesity-associated metabolic health complications in a Pakistani population?
Observational (n=4,000)
Yes
Which adiposity trait best predicts obesity-associated metabolic health complications in a Pakistani population?
Waist circumference is a strong predictor of obesity-associated metabolic health issues in the Pakistani population.
May support multiple indices for obesity screening in Iranians; leaves open which best predicts complications.
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.
No takes yet. Share an insight, caveat, or question.
Saqlain et al. (2020) conducted an observational in Obesity and cardiometabolic risk (n=4,000). Anthropometric obesity scales (BMI, WC, WHR, BAI, VAI) was evaluated on Metabolic health complications (hypertension, hyperglycemia, and dyslipidemia). Waist circumference strongly predicted metabolic risks, while among the obese population, 55.7% were class I, 28.5% class II, and 15.8% class III.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: