Table 6.

Type 2 diabetes (T2D) and adiposity

Type 2 diabetes		OR	SE	z	p value	95% CI		Model
						Lower	Upper	pseudo- R 2
A
	VAT	2.17	0.18	9.5	<2 × 10-16	1.85	2.54	0.07
	DXA abdominal fat	1.86	0.13	8.6	<2 × 10-16	1.61	2.14	0.05
	BMI	1.66	0.12	7.2	2 × 10-13	1.45	1.91	0.04
	Age	1.05	0.01	4.3	8 × 10-6	1.03	1.07	0.02
B
	VAT	2.08	0.18	8.5	<2 × 10-16	1.76	2.47	0.08
	Age	1.02	0.01	2.0	0.05	1.00	1.05

The study sample prevalence (females > = 40 years) estimate for T2D = 0.05. Logistic regressions (n = 2964) presenting unadjusted odds ratios (OR) (A) and best-fit multiple regression model with adjusted OR for visceral adipose fat (VAT) area and age (B). For evidence of the presented best-fit model and an analysis of residuals to account for co-linearity between adiposity variables, see Additional file 1: Tables S2 and S3, respectively. Explanatory variables VAT, DXA and BMI are all standardised, implying a change in odds ratio per unit SD change. For logistic regression, the pseudo-R² model-fit statistic is analogous (but not directly comparable) to the ordinary least squares regression R² statistic, known as the coefficient of determination. While R² can be interpreted as the proportion of variance explained by the model, pseudo-R² is loosely interpreted as the proportion of variation in risk liability explained by the model (StatCorp, Texas). Abbreviation: CI - confidence interval.