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Inicio Annals of Hepatology P- 52 CORRELATION AMONG DIFFERENT METHODS TO ESTIMATE BODY AND LIVER FAT IN HEAL...
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Vol. 29. Núm. S1.
Abstracts of the 2023 Annual Meeting of the ALEH
(febrero 2024)
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Vol. 29. Núm. S1.
Abstracts of the 2023 Annual Meeting of the ALEH
(febrero 2024)
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P- 52 CORRELATION AMONG DIFFERENT METHODS TO ESTIMATE BODY AND LIVER FAT IN HEALTHY ADULTS
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Sophia Eugenia Martínez1, Ashuin Kammar2, Carlos Moctezuma3, Graciela Elia Castro1, Luis Uscanga1
1 Gastroenterology Department, National Institute of Medical Sciences and Nutrition Salvador Zubirán, Ciudad de México, México
2 Research Division, National Institute of Geriatrics, Ciudad de México, México
3 Liver Unit, University of Alberta, Edmonton, Canadá
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Vol. 29. Núm S1

Abstracts of the 2023 Annual Meeting of the ALEH

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Introduction an Objectives

An increase in body fat is a risk factor to develop fatty liver disease. Until now, few studies have related different methods to estimate body fat related to liver fat. We aimed to determinate the correlation among different methods to estimate body and liver fat in healthy adults.

Materials and Methods

In a cross- sectional study registered in ethics and research committees GAS3794 evaluating healthy adults; chronic illness, uncontrolled diabetes, hypertension or thyroid, bariatric surgery or pacemaker, were not included. The estimation of body fat (BF) was by 3 methods, two with bioelectric impedance of 19 frequencies (19F), 4 frequencies (4F) and the third by the Durnin- Womersley (DW) skinfold thickness formulae; also, were measured body mass index (BMI), waist circumference (WC) and visceral fat (VF). The liver fat was estimated by controlled attenuation parameter (CAP) using transitory elastography. Correlations were calculated with Pearson coefficient among body composition methods and CAP; each anthropometric isolated parameter was associated with hepatic steatosis grades by a logistic regression analysis using SPSS v21.0.

Results

In 231 participants, mean age was 41.8 years (SD 11.3), WC 91 cm (SD 12), BMI 27.8 kg/m2 (SD 4.6). 112 had some grade of steatosis (S3 n=72, S2 n=18). The correlation among 3 methods was on average r= 0.853 (p=0.000), and between CAP and BF was 0.290 (p= 0.000). BMI, WC, VF and suprailiac skinfold thickness showed correlations of r=0.570 (p=0.000), r=0.477 (p=0.000), r=0.393 (p= 0.000) y r= 0.471 (p=0.000) respectively. Regression analysis demonstrated that BMI (OR=1.32, p=0.000), WC > 80 women and > 90 cm men (OR=14.7, p=0.010), VF (OR=1.8, p=0.008) and suprailiac skinfold thickness (OR=1.14, p=0.000) showed association with steatosis.

Conclusions

Three methods were like to estimate body fat although they were not able to represent the liver fat; waist circumference was the best indicator related with steatosis

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