The Impact of Severe Obesity on Post-Acute Rehabilitation Efficiency, Length of Stay, and Hospital Costs

Table 4

Linear regression analysis examining the effect of severe obesity on log LOS and log FIM efficiency.

Model	Variable	Beta-coefficient (SE)	𝑃 value
Overall LOS; model 𝑅^2=0.1798	Intercept	4.44 (0.46)	<0.0001
	Severe obesity	0.51 (0.23)	0.03
	Retired (versus employed)	0.67 (0.26)	0.01
	Age (per one year increase)	−0.02 (0.009)	0.04
	smoking former	−0.26 (0.19)	0.17
	Diabetes	−0.26 (0.22)	0.25
Rehab LOS; model 𝑅^2=0.1693	Intercept	4.14 (0.37)	<0.0001
	Severe obesity	0.46 (0.18)	0.02
	Retired (versus employed)	0.47 (0.21)	0.03
	Diabetes	−0.32 (0.18)	0.08
	Age (per one year increase)	−0.01 (0.01)	0.09
	Mental illness	−0.21 (0.15)	0.16
FIM efficiency model; 𝑅^2=0.3133	Intercept	−2.12 (0.59)	0.0006
	Severe obesity	−0.63 (0.33)	0.06
	Unemployed (versus employed)	−0.84 (0.27)	0.003
	Heart Disease	−0.60 (0.34)	0.08
	Mental illness	0.65 (0.25)	0.01
	Asthma	1.01 (0.63)	0.11
	Current smoker (versus never)	0.60 (0.30)	0.05
	Age	0.02 (0.01)	0.07
	HTN	0.52 (0.32)	0.10
	Venous thromboembolic disease	0.68 (0.42)	0.13
	Dementia	−0.66 (0.42)	0.13
	PVD	−0.55 (0.40)	0.18
	DM	0.37 (0.30)	0.23

LOS: length of stay; FIM: functional independence measure.