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Table 4 Linear regression models for CT visceral adipose fat (VAT) area using the validation sample (n = 54)

From: The relationship between DXA-based and anthropometric measures of visceral fat and morbidity in women

 

VAT model

Measure

β

SE

t

pvalue

95% CI

Model

       

Lower

Upper

R 2

A

Model 0:

       

0.91

Combination of DXA & anthropometric measures

DXA abdominal fat

20.1

3.4

5.9

2 × 10-9

13.2

27.0

 

BC CSA

32.4

4.5

7.2

4 × 10-13

23.2

41.6

 

WC

11.1

5.6

2.0

2 × 10-2

-0.3

22.4

 

B

Model 1:

       

0.83

Combination of DXA & anthropometric measures

DXA abdominal fat

10.1

4.8

2.1

0.04

0.31

19.9

 

WC

40.8

5.7

7.2

3 × 10-13

29.2

52.3

 

Age

1.4

0.5

2.6

0.01

0.3

2.4

 

C

Model 2:

       

0.86

Anthropometric measures only

BC CSA

25.5

5.6

4.6

2 × 10-6

14.1

36.8

 
  

WC

30.5

5.5

5.6

1 × 10-8

19.4

41.6

 
  1. Model 0: combination of DXA and anthropometric measures guided by previously published models presented in Tables 3A (A); Model 1: combination of DXA and anthropometric measures restricted to DXA total abdominal fat, WC and age that were also available for the study sample (B); Model 2: using anthropometric measures only (C). BC CSA was estimated using BC = (π × (SD–2SFW) × TID) from the CT images at intervertebral disc L4:L5 as described in Methods. Note that for Model 2, using these explanatory variables instead of BC CSA, yields equally good or better prediction of VAT area (R 2 = 0.89), but the model is less interpretable with a negative beta coefficient for SFW. Abbreviations: BC, body cavity, CSA, cross sectional area, SD, sagittal depth, SFW, subcutaneous fat width, TED, transverse external diameter, TID, transverse internal diameter.