Comparative assessment of anthropometric and bioimpedence methods for determining adiposity. Issue 12 (December 2020)

• Record Type: Journal Article
• Authors: Adedia, David; Boakye, Adjoa A.; Mensah, Daniel; Lokpo, Sylvester Y.; Afeke, Innocent; Duedu, Kwabena O.
• Is Part Of: Heliyon. Volume 6:Issue 12(2020)
• Publication Date: 2020-12
• Subjects: Body fat percentage -- Body mass index -- Waist-to-hip ratio -- Conicity index -- Obesity status -- Body adiposity index -- Visceral fat; Research -- Periodicals; Medical sciences -- Periodicals; Natural history -- Periodicals; Social sciences -- Periodicals; Earth sciences -- Periodicals; Physical sciences -- Periodicals; 507.2
• DOI: 10.1016/j.heliyon.2020.e05740
• Languages: English
• ISSNs: 2405-8440

Abstract

Abstract: Background: Obesity is a risk factor for different chronic conditions. Over the years, obesity has become a pandemic and it is therefore important that effective diagnostic tools are developed. Obesity is a measure of adiposity and it has become increasingly evident that anthropometric measures such as body mass index (BMI) used to estimate adiposity are inadequate. This study therefore examined the ability of different anthropometric measurements to diagnose obesity within a cross-section of Ghanaian women. Methods: We obtained anthropometric measurements and used that to generate derived measures of adiposity such as body adiposity index (BAI) and conicity index. Furthermore we also measured adiposity using a bioimpedance analyser. Associations between these measurements and percentage body fat (%BF) were drawn in order to determine the suitability of the various measures to predict obesity. The prevalence of obesity was determined using both %BF and BMI. Results: BMI, Waist and hip circumference and visceral fat (VF) were positively correlated with % BF whereas skeletal muscle mass was negatively correlated. Prevalence of obesity was 16% and 31.6% using BMI and %BF respectively. Receiver operating characteristic (ROC) analysis showed that these differences in prevalence was due to BMI based misclassification of persons who have obesity as overweight. Similar, shortfalls were observed for the other anthropometric measurements using ROC. Conclusions: No single measure investigated could adequately predict obesity as an accumulation of fat using current established cut-off points within our study population. Large scale epidemiological studies are therefore needed to define appropriate population based cut-off points if anthropometric measurements are to be employed in diagnosing obesity within a particular population. Abstract : Body fat percentage; Body mass index; Waist-to-hip ratio; Conicity index; Obesity status; Body adiposity index; Visceral fat.