How to Estimate Fat Mass in Overweight and Obese Subjects

Table 4

Fat mass prediction (FM from DXA)—multivariate regression analysis.

		Variables in the model	𝐵	Sig. 𝑡 changes	𝑅^2	𝑅^2 adj
		Constant	−10.55	0.032
		BMI	0.285	0.042
		AFA	0.628	0.034
		H	0.117	0.028
	Block model	FM-BIA	0.739	0.000	0.879	0.868
		FMI	0.288	0.345
		CRP	0.0036	0.995
Model 1		Leptin	0.00714	0.01
		LAR	0.0594	0.599
		Constant	−11.021	0.02
		FM-BIA	0.645	0.000
	Forward stepwise selection	Leptin	0.00545	0.004	0.877	0.871
		BMI	0.245	0.058
		H	0.131	0.11
		AFA	0.627	0.32
		Constant	6.818	0.000
	Block model	FM-BIA	0.868	0.000	0.852	0.847
		Leptin	0.00629	0.002
Model 2		CRP	0.477	0.41
		Constant	6.642	0.000
	Forward stepwise selection	FM-BIA	0.876	0.000	0.851	0.848
		Leptin	0.00681	0.001
		Constant	−10.21	0.011
	Block model	BMI	1.338	0.000	0.68	0.67
		Leptin	0.0153	0.000
Model 3		CRP	0.842	0.321
		Constant	−11.025	0.005
	Forward stepwise selection	BMI	1.369	0.000	0.677	0.67
		Leptin	0.01638	0.000

Legend: BMI: body mass index; AFA: arm fat area; H: hips circumference; FM-BIA: fat mass estimate through bioimpedance analysis; CRP: C-reactive protein; LAR: leptin-adiponectin ratio.