Body adiposity index assess body fat with high accuracy in nondialyzed chronic kidney disease patients

Silva, Maria Inês B.; Vale, Barbara S.; Lemos, Carla; Torres, Márcia Regina Simas Gonçalves; Bregman, Rachel

doi:10.1002/oby.20261

Cited by 42 publications

(25 citation statements)

References 37 publications

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“…A validade do IAC está bem documentada na literatura 13, [16][17][18][19][20][21][22][23][24][25][26][27]37 , porém estudos da prevalência do excesso de adiposidade corporal utilizando o IAC e fatores associados não foram identificados, até o presente momento. Este é o primeiro estudo, de que se tem conhecimento, que se concentrou em identificar a prevalência de adiposidade corporal em adultos pelo IAC e associá-lo a fatores sociodemográficos, comportamentais, de morbidades autorreferidas e de percepção.…”

Section: Discussionunclassified

“…Além disso, Carpio Rivera et al 24 verificaram a capacidade do IAC em predizer o percentual de gordura corporal em estudantes da Costa Rica. Com a população brasileira, foram conduzidos estudos para estimar o risco para o diabetes mellitus tipo 2 20 , avaliar a gordura corporal em adultos de ambos os sexos com doença renal crônica 25 e em adultos com obesidade severa 26 ; para verificar a sua validade em mulheres brasileiras na meia-idade 27 e com mulheres com lipodistrofia 17 . No entanto, não foram encontrados estudos que identificaram a prevalência de excesso de adiposidade corporal em adultos e seus fatores associados utilizando o IAC.…”

Section: Introductionunclassified

See 1 more Smart Citation

Fatores associados e índice de adiposidade corporal (IAC) em adultos: estudo de base populacional

Segheto

Hallal

Marins

et al. 2018

Ciênc. saúde coletiva

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Section: Discussionunclassified

Section: Introductionunclassified

Fatores associados e índice de adiposidade corporal (IAC) em adultos: estudo de base populacional

Segheto

Hallal

Marins

et al. 2018

Ciênc. saúde coletiva

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“…7 Fat measurement by single frequency bioimpedance is not superior to simple anthropometric measurements. 8 Because gold standard measurements of body fat content are problematic to perform in clinical practice, both WHR and skin fold thickness are recommended for routine use. 6 The conicity index is an easy anthropometric estimate using WC, height, and weight to model the relative accumulation of abdominal fat without requiring the hip circumference to assess fat distribution.…”

Section: Definition and Assessment Of Obesitymentioning

confidence: 99%

Obesity in CKD—What Should Nephrologists Know?

Stenvinkel

Zoccali

İkizler

2013

Journal of the American Society of Nephrology

195

172

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Obesity, the epidemic of the 21st century, carries a markedly increased risk for comorbid complications, such as type 2 diabetes, cancer, hypertension, dyslipidemia, cardiovascular disease, and sleep apnea. In addition, obesity increases the risk for CKD and its progression to ESRD. Paradoxically, even morbid obesity associates with better outcomes in studies of ESRD patients on maintenance dialysis. Because the number of obese CKD and maintenance dialysis patients is projected to increase markedly in developed as well as low-and middle-income countries, obesity is a rapidly emerging problem for the international renal community. Targeting the obesity epidemic represents an unprecedented opportunity for health officials to ameliorate the current worldwide increase in CKD prevalence. Nephrologists need more information about assessing and managing obesity in the setting of CKD. Specifically, more precise estimation of regional fat distribution and the amount of muscle mass should be introduced into regular clinical practice to complement more commonly used practical markers, such as body mass index. Studies examining the effects of obesity on kidney disease progression and other clinical outcomes along with weight management strategies are much needed in this orphan area of research. 24: 172724: -173624: , 201324: . doi: 10.1681 Obesity has emerged as the largest pandemic in near history, with important implications of not only cardiovascular disease (CVD) but also CKD. Recent data from the United States indicate that the incidence and prevalence rates of obesity in maintenance dialysis patients largely exceed the corresponding figures in the general population. 1 A large European population survey documented that a high body mass index (BMI) ranks as one of the strongest risk factors for new-onset CKD. 2 The dimension of the obesity epidemic and the impact of the same epidemic on the kidney demand efforts for understanding the epidemiology and the mechanisms of CKD associated with excess adiposity. It also sets as an absolute public health priority for the development of treatment policies integrated across specialties and general practice to halt this much concerning problem. In this scenario, it is fundamental that nephrologists are updated on current knowledge about obesity in the setting of CKD. However, little attention is still paid to this issue in major nephrology journals. The suboptimal attention to the problem by major sources of dissemination of specialty information suggests that nephrologists may have scarce knowledge of how obesity should be assessed, its epidemiology, mechanisms whereby excess fat mass is conducive to CKD, and management of obesity in the catabolic uremic milieu. 3 J Am Soc Nephrol DEFINITION AND ASSESSMENT OF OBESITYThe most common method for defining obesity is based on BMI (i.e., a person's weight as obese. It should be emphasized that population norms of BMI could be different based on ethnic and racial background (i.e., the proportion of Asian people with a high ...

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“…The results confirmed BAI as a valid predictor of BF% when compared to data obtained with DEXA. In addition, it has been widely used in hospitals (i.e., patients with non-dialysed chronic kidney disease) [10] and research areas (i.e., patients with severe obesity from Brazil) [11]. Correlation coefficients between parameters of body composition assessed by BAI were highly related to those determined by DEXA or magnetic resonance imaging (r values between 0.62 and 0.96) [1,9,12,13], but several publications have criticized the accuracy of BAI [14,15].…”

Section: Introductionmentioning

confidence: 99%

Predictive Validity of the Body Adiposity Index in Overweight and Obese Adults Using Dual-Energy X-ray Absorptiometry

et al. 2016

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The body adiposity index (BAI) is a recent anthropometric measure proven to be valid in predicting body fat percentage (BF%) in some populations. However, the results have been inconsistent across populations. This study was designed to verify the validity of BAI in predicting BF% in a sample of overweight/obese adults, using dual-energy X-ray absorptiometry (DEXA) as the reference method. A cross-sectional study was conducted in 48 participants (54% women, mean age 41.0 ± 7.3 years old). DEXA was used as the “gold standard” to determine BF%. Pearson’s correlation coefficient was used to evaluate the association between BAI and BF%, as assessed by DEXA. A paired sample t-test was used to test differences in mean BF% obtained with BAI and DEXA methods. To evaluate the concordance between BF% as measured by DEXA and as estimated by BAI, we used Lin’s concordance correlation coefficient and Bland–Altman agreement analysis. The correlation between BF% obtained by DEXA and that estimated by BAI was r = 0.844, p < 0.001. Paired t-test showed a significant mean difference in BF% between methods (BAI = 33.3 ± 6.2 vs. DEXA 39.0 ± 6.1; p < 0.001). The bias of the BAI was −6.0 ± 3.0 BF% (95% CI = −12.0 to 1.0), indicating that the BAI method significantly underestimated the BF% compared to the reference method. Lin’s concordance correlation coefficient was considered stronger (ρc = 0.923, 95% CI = 0.862 to 0.957). In obese adults, BAI presented low agreement with BF% measured by DEXA; therefore, BAI is not recommended for BF% prediction in this overweight/obese sample studied.

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Body adiposity index assess body fat with high accuracy in nondialyzed chronic kidney disease patients

Abstract: These findings suggest that BAI estimates BF with high accuracy in nondialyzed CKD patients and may be helpful in the treatment of this population with increased BF.

Cited by 42 publications

References 37 publications

Fatores associados e índice de adiposidade corporal (IAC) em adultos: estudo de base populacional

Fatores associados e índice de adiposidade corporal (IAC) em adultos: estudo de base populacional

Obesity in CKD—What Should Nephrologists Know?

Predictive Validity of the Body Adiposity Index in Overweight and Obese Adults Using Dual-Energy X-ray Absorptiometry

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