Design and validation of a novel estimator of visceral adipose tissue area and comparison to existing adiposity surrogates.
J Diabetes Complications
; 32(11): 1062-1067, 2018 Nov.
Article
in En
| MEDLINE
| ID: mdl-30236542
ABSTRACT
AIMS:
Visceral adiposity measured by computed tomography (CT) as intra-abdominal fat area (IAFA) predicts metabolic diseases. Existing adiposity surrogates have not been systematically compared to a regression-based model derived in individuals of Japanese ancestry. We developed and validated a method to estimate IAFA in individuals of Japanese ancestry and compared it to existing adiposity surrogates.METHODS:
We assessed age, BMI, waist circumference (WC), fasting lipids, glucose, smoking status, grip strength, mid-thigh circumference (MTC), humeral length, leg length, and IAFA by single-slice CT at the umbilicus for 622 Japanese Americans. We used stepwise linear regression to predict IAFA and termed the predicted value the Estimate of Visceral Adipose Tissue Area (EVA). For men, the final model included age, BMI, WC, high-density lipoprotein cholesterol (HDLc), glucose, and MTC; for women, age, BMI, WC, HDLc, low-density lipoprotein cholesterol, glucose, and MTC. We compared goodness-of-fit (R2) from linear regression models and mean-squared errors (MSE) from k-fold cross-validation to compare the ability of EVA to estimate IAFA compared to an estimate by Després et al., waist-to-height ratio, WC, deep abdominal adipose tissue index, BMI, lipid accumulation product, and visceral adiposity index (VAI). We classified low/high IAFA using area under receiver-operating characteristic curves (AUROC) for IAFA dichotomized at the 75th percentile.RESULTS:
EVA gave the least MSE and greatest R2 (men 1244, 0.61; women 581, 0.72). VAI gave the greatest MSE and smallest R2 (mean 2888, 0.08; women 1734, 0.14).CONCLUSIONS:
EVA better predicts IAFA in Japanese-American men and women compared to existing surrogates for adiposity.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Body Weights and Measures
/
Biomarkers
/
Intra-Abdominal Fat
/
Obesity, Abdominal
Type of study:
Observational_studies
/
Prevalence_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Adult
/
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Country/Region as subject:
Asia
Language:
En
Journal:
J Diabetes Complications
Journal subject:
ENDOCRINOLOGIA
Year:
2018
Document type:
Article