Dataset Information

Equations for predicting DXA-measured visceral adipose tissue mass based on BMI or weight in adults.

ABSTRACT:

Background

Obesity, especially presenting with excessive amounts of visceral adipose tissue (VAT), is strongly associated with insulin resistance (IR), atherosclerosis, metabolic syndrome, and cardiovascular diseases (CVDs).

Aims

To construct a predication equation for estimating VAT mass using anthropometric parameters and validate the models with a validation group.

Methods

Five hundred fifteen subjects (366 for the derivation group and 149 for the validation group) were enrolled in the study. The anthropometric parameters, blood lipid profile, and VAT mass were accessed from medical records. Stepwise regression was applied to develop prediction models based on the dual X-ray absorptiometry (DXA)-measured VAT mass in the derivation group. Bland-Altman plots and correlation analysis were performed to validate the agreements in the validation group. The performance of the prediction equations was evaluated with the Hosmer-Lemeshow test and area under the curve (AUC).

Results

Model 1, which included age, sex, body mass index (BMI), triglyceride (TG), high-density lipoprotein (HDL), and the grade of hepatic steatosis, had a variance of 70%, and model 2, which included age, sex, weight, height, TG, HDL, and the grade of hepatic steatosis, had a variance of 74%. The VAT mass measured by DXA was correlated with age, sex, height, weight, BMI, TG, HDL, and grade of hepatic steatosis. In the validation group, the VAT mass calculated by the prediction equations was strongly correlated with the DXA-VAT mass (r = 0.870, r = 0.875, respectively). The AUC, sensitivity, and specificity of the two prediction equations were not significantly different (both P = 0.933).

Conclusion

The study suggests that prediction equations including age, sex, height, BMI, weight, TG, HDL, and the grade of hepatic steatosis could be useful tools for predicting VAT mass when DXA is not available.

SUBMITTER: Song X

PROVIDER: S-EPMC9109344 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Publications

Equations for predicting DXA-measured visceral adipose tissue mass based on BMI or weight in adults.

Song Xuan X Wu Hongxia H Zhang Wenhua W Wang Bei B Sun Hongjun H

Lipids in health and disease 20220516 1

<h4>Background</h4>Obesity, especially presenting with excessive amounts of visceral adipose tissue (VAT), is strongly associated with insulin resistance (IR), atherosclerosis, metabolic syndrome, and cardiovascular diseases (CVDs).<h4>Aims</h4>To construct a predication equation for estimating VAT mass using anthropometric parameters and validate the models with a validation group.<h4>Methods</h4>Five hundred fifteen subjects (366 for the derivation group and 149 for the validation group) were ...[more]

PMID: 35578238

Similar Datasets

Project description:BackgroundIn terms of assessing obesity-associated risk, quantification of visceral adipose tissue (VAT) has become increasingly important in risk assessment for cardiovascular and metabolic diseases. However, differences exist in the accuracy of various modalities, with a lack of up-to-date comparison with three-dimensional whole volume assessment.AimsUsing CT or MRI three-dimensional whole volume VAT as a reference, we evaluated the correlation of various commonly used modalities and techniques namely body impedance analysis (BIA), dual-energy x-ray absorptiometry (DXA) as well as single slice CT to establish how these methods compare.MethodsWe designed the study in two parts. First, we performed an intra-individual comparison of the 4558 participants from the UK Biobank cohorts with matching data of MRI abdominal body composition, DXA with VAT estimation, and BIA. Second, we evaluated 174 CT scans from the publicly available dataset to assess the correlation of the commonly used single-slice technique compared to three-dimensional VAT volume.ResultsAcross the UK Biobank cohort, the DXA-derived VAT measurement correlated better (R2 0.94, p<0.0001) than BIA (R2 0.49, p<0.0001) with reference three-dimensional volume on MRI. However, DXA-derived VAT correlation was worse for participants with a BMI of < 20 (R2 = 0.62, p=0.0013). A commonly used single slice method on CT demonstrated a modest correlation (R2 between 0.51 - 0.64), with best values at L3- and L4 (R2 L3 = 0.63, p<0.0001; L4 = 0.64, p<0.0001) compared to reference three-dimensional volume. Combining multiple slices yielded a better correlation, with a strong correlation when L2-L3 levels were combined (R2 = 0.92, p<0.0001).ConclusionWhen deployed at scale, DXA-derived VAT volume measurement shows excellent correlation with three-dimensional volume on MRI based on the UK Biobank cohort. Whereas a single slice CT technique demonstrated moderate correlation with three-dimensional volume on CT, with a stronger correlation achieved when multiple levels were combined.

Dataset Information

Equations for predicting DXA-measured visceral adipose tissue mass based on BMI or weight in adults.

Background

Aims

Methods

Results

Conclusion

Publications

Equations for predicting DXA-measured visceral adipose tissue mass based on BMI or weight in adults.

Similar Datasets

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