Is Body Adiposity Index a Better and Easily Applicable Measure for Determination of Body Fat?

Yeşil, Esen; Köse, Beril; Özdemir, Merve

doi:10.1080/07315724.2020.1727378

Cited by 9 publications

(7 citation statements)

References 24 publications

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“…Increased AIP might be concordantly associated with the incidence of NAFLD [ 19 , 20 ]. BAI is a better and more easily applicable measure for the determination of body fat than BMI, WHR, WHtR and WC in Turkish adults [ 39 ]. BRI was used to predict body fat and the percentage of visceral adipose tissue by Thomas et al [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

Comparison of obesity-related indices for identifying nonalcoholic fatty liver disease: a population-based cross-sectional study in China

et al. 2021

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Background The relationship between nonalcoholic fatty liver disease (NAFLD) and obesity-related indices has been analyzed separately thus far, and evidence comparing these indices together is still lacking, especially in China. This study aimed to comprehensively evaluate the predictive performance of anthropometric and metabolic indices to identify NAFLD in Chinese adults. Methods This study recruited a total of 1748 participants who were 18 years or older in southeastern China. The systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG), total cholesterol (TC), triglycerides (TGs), low-density lipoprotein (LDL), waist circumference (WC), a body shape index (ABSI), atherogenic index of plasma (AIP), abdominal volume index (AVI), body adiposity index (BAI), body mass index (BMI), body roundness index (BRI), conicity index (CI), triglyceride glucose (TyG), waist hip ratio (WHR), and waist height ratio (WHtR) were measured. The association between these indices and NAFLD was analyzed via logistic analyses with odds ratios (ORs). Receiver operating characteristic (ROC) curves and areas under the curve (AUCs) were used to compare the predictive performance of these indices to identify NAFLD. Results BMI had the greatest total AUC (AUC = 0.841) in the ROC curve analysis. However, BRI and BMI both had the best diagnostic ability in males (AUC = 0.812), and BRI had the best diagnostic ability in females (AUC = 0.849). Furthermore, AVI had the greatest AUC for patients who were ~ 20 (AUC = 0.892) and ~ 40 years old (AUC = 0.831), while TyG showed a higher predictive ability than AVI in those who were ~ 60 years old (AUC = 0.766). Conclusion This study identified sex- and age-specific indices for predicting NAFLD in Chinese subjects. Compared with indices for all age groups, sex- and age-specific indices can provide more accurate assistance for clinical diagnosis and treatment.

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Section: Discussionmentioning

confidence: 99%

Comparison of obesity-related indices for identifying nonalcoholic fatty liver disease: a population-based cross-sectional study in China

et al. 2021

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“…To determine the nutritional status of a patient, it is essential to examine the fat content in the body. Calculating body fat using skinfold measurement is still a clinically established method [1], and is applicable for both normal-weight patients at risk of malnutrition and patients suffering from obesity [2,3]. Obesity plays an increasingly important role in daily clinical work because its prevalence has reached almost epidemic proportions [4,5].…”

Section: Introductionmentioning

confidence: 99%

Measuring subcutaneous fat thickness using skinfold calipers vs. high-resolution B-scan ultrasonography in healthy volunteers: A pilot study

Nösslinger

Mair

Toplak

et al. 2022

Clinical Nutrition Open Science

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The best agreement for women was obtained with the measurements of the chest fold (47.2%), followed by the measurements of the back fold (38.9%). For men, it was the measurements of the thigh fold (63.6%), followed by the measurements of the triceps (51.5%) and back fold (51.5%). Conclusion:The agreement between skinfold measurements made using calipers and ultrasonography depends on the skinfold thickness and the localization of the measurement, with genderbased differences.

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“…It is calculated from hip circumference and height. The final formula was shown to predict the percentage of body adiposity measured by DXA [ 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Visceral Adiposity in Relation to Body Adiposity and Nutritional Status in Elderly Patients with Stable Coronary Artery Disease

et al. 2021

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Introduction: The accumulation of visceral abdominal tissue (VAT) seems to be a hallmark feature of abdominal obesity and substantially contributes to metabolic abnormalities. There are numerous factors that make the body-mass index (BMI) a suboptimal measure of adiposity. The visceral adiposity index (VAI) may be considered a simple surrogate marker of visceral adipose tissue dysfunction. However, the evidence comparing general to visceral adiposity in CAD is scarce. Therefore, we have set out to investigate visceral adiposity in relation to general adiposity in patients with stable CAD. Material and methods: A total of 204 patients with stable CAD hospitalized in the Department of Medicine and the Department of Geriatrics entered the study. Based on the VAI-defined adipose tissue dysfunction (ATD) types, the study population (N = 204) was divided into four groups: (1) no ATD (N = 66), (2) mild ATD (N = 50), (3) moderate ATD (N = 48), and (4) severe ATD (N = 40). Nutritional status was assessed using the Controlling Nutritional Status (CONUT) score. Results: Patients with moderate and severe ATD were the youngest (median 67 years), yet their metabolic age was the oldest (median 80 and 84 years, respectively). CONUT scores were similar across all four study groups. The VAI had only a modest positive correlation with BMI (r = 0.59 p < 0.01) and body adiposity index (BAI) (r = 0.40 p < 0.01). There was no correlation between VAI and CONUT scores. There was high variability in the distribution of BMI-defined weight categories across all four types of ATD. A total of 75% of patients with normal nutritional status had some form of ATD, and one-third of patients with moderate or severe malnutrition did not have any ATD (p = 0.008). In contrast, 55–60% of patients with mild, moderate, or severe ATD had normal nutritional status (p = 0.008). ROC analysis demonstrated that BMI and BAI have poor predictive value in determining no ATD. Both BMI (AUC 0.78 p < 0.0001) and BAI (AUC 0.66 p = 0.003) had strong predictive value for determining severe ATD (the difference between AUC 0.12 being p = 0.0002). However, BMI predicted mild ATD and severe ATD better than BAI. Conclusions: ATD and malnutrition were common in patients with CAD. Notably, this study has shown a high rate of misclassification of visceral ATD via BMI and BAI. In addition, we demonstrated that the majority of patients with normal nutritional status had some form of ATD and as much as one-third of patients with moderate or severe malnutrition did not have any ATD. These findings have important clinical ramifications for everyday practice regarding the line between health and disease in the context of malnutrition in terms of body composition and visceral ATD, which are significant for developing an accurate definition of the standards for the intensity of clinical interventions.

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Is Body Adiposity Index a Better and Easily Applicable Measure for Determination of Body Fat?

Cited by 9 publications

References 24 publications

Comparison of obesity-related indices for identifying nonalcoholic fatty liver disease: a population-based cross-sectional study in China

Comparison of obesity-related indices for identifying nonalcoholic fatty liver disease: a population-based cross-sectional study in China

Measuring subcutaneous fat thickness using skinfold calipers vs. high-resolution B-scan ultrasonography in healthy volunteers: A pilot study

Visceral Adiposity in Relation to Body Adiposity and Nutritional Status in Elderly Patients with Stable Coronary Artery Disease

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