BACKGROUND: Body mass index (BMI) is the most common parameter for classifying nutritional status. However, body composition (BC) may vary considerably among individuals with identical BMIs; consequently, we need to assess BC efficiently. Bariatric surgery is the most effective method for treating obesity. To improve quality assessment of postoperative weight loss, it is essential to assess BC. Multi-frequency bioelectrical impedance analysis (BIA) is a practical assessment instrument, though limited when applied among the obese population. Despite dual-energy X-ray absorptiometry (DXA) being the current reference standard, it has physical limitations which restrict its practical application. This study, therefore, sought to correlate the results of BC assessments of same patient population using BIA and DXA. METHODS: This was a cross-sectional validation study with patients invited to undergo a multi-frequency BIA (Inbody 720®) and afterwards a DXA examination Statistical analyses were done using the intraclass correlation coefficient (ICC), paired t-test and the Bland-Altman plot analysis. RESULTS: A total of 108 patients were randomly selected, with 73 meeting the criteria for study inclusion. Most were female (89%) and had an average BMI of 40.17 ± 4.08 kg/m(2). An almost perfect correlation of fat (kg) and fat-free mass (kg) was found in results from the BIA and DXA examination (ICC = 0.832 and ICC = 0.899, respectively). A substantial correlation was also found between the percentage of body fat (%BF) and the percentage of fat-free mass (%FFM). The comparison made between the BIA and DXA using the t-test showed significant differences between all parameters. The Bland-Altman plot showed that the BIA method tends to underestimate the FM and overestimate the LM measurements when compared with DXA. CONCLUSION: BIA proved to be a safe alternative for assessing BC in clinically severely obese patients and thus provides a more accessible evaluation tool for this population. But, consideration should be given to the formula added to the BIA measurement, adjusting the values to differences observed in order to reduce errors when compared with the DXA measurements.
BACKGROUND: Body mass index (BMI) is the most common parameter for classifying nutritional status. However, body composition (BC) may vary considerably among individuals with identical BMIs; consequently, we need to assess BC efficiently. Bariatric surgery is the most effective method for treating obesity. To improve quality assessment of postoperative weight loss, it is essential to assess BC. Multi-frequency bioelectrical impedance analysis (BIA) is a practical assessment instrument, though limited when applied among the obese population. Despite dual-energy X-ray absorptiometry (DXA) being the current reference standard, it has physical limitations which restrict its practical application. This study, therefore, sought to correlate the results of BC assessments of same patient population using BIA and DXA. METHODS: This was a cross-sectional validation study with patients invited to undergo a multi-frequency BIA (Inbody 720®) and afterwards a DXA examination Statistical analyses were done using the intraclass correlation coefficient (ICC), paired t-test and the Bland-Altman plot analysis. RESULTS: A total of 108 patients were randomly selected, with 73 meeting the criteria for study inclusion. Most were female (89%) and had an average BMI of 40.17 ± 4.08 kg/m(2). An almost perfect correlation of fat (kg) and fat-free mass (kg) was found in results from the BIA and DXA examination (ICC = 0.832 and ICC = 0.899, respectively). A substantial correlation was also found between the percentage of body fat (%BF) and the percentage of fat-free mass (%FFM). The comparison made between the BIA and DXA using the t-test showed significant differences between all parameters. The Bland-Altman plot showed that the BIA method tends to underestimate the FM and overestimate the LM measurements when compared with DXA. CONCLUSION: BIA proved to be a safe alternative for assessing BC in clinically severely obesepatients and thus provides a more accessible evaluation tool for this population. But, consideration should be given to the formula added to the BIA measurement, adjusting the values to differences observed in order to reduce errors when compared with the DXA measurements.
Authors: Ursula G Kyle; Ingvar Bosaeus; Antonio D De Lorenzo; Paul Deurenberg; Marinos Elia; José Manuel Gómez; Berit Lilienthal Heitmann; Luisa Kent-Smith; Jean-Claude Melchior; Matthias Pirlich; Hermann Scharfetter; Annemie M W J Schols; Claude Pichard Journal: Clin Nutr Date: 2004-12 Impact factor: 7.324
Authors: Antonio Carlos Valezi; Jorge Mali Junior; Mariano Almeida de Menezes; Edivaldo Macedo de Brito; Shirley A F de Souza Journal: Obes Surg Date: 2010-11 Impact factor: 4.129
Authors: Gladys W Strain; Jack Wang; Michel Gagner; Alfons Pomp; William B Inabnet; Steven B Heymsfield Journal: Obesity (Silver Spring) Date: 2008-06-12 Impact factor: 5.002
Authors: Gabriel Cunha Beato; Michele Novais Ravelli; Alex Harley Crisp; Maria Rita Marques de Oliveira Journal: Obes Surg Date: 2019-01 Impact factor: 4.129
Authors: S Salekzamani; H Mehralizadeh; A Ghezel; Y Salekzamani; M A Jafarabadi; A S Bavil; B P Gargari Journal: J Endocrinol Invest Date: 2016-07-11 Impact factor: 4.256