. Author manuscript; available in PMC: 2010 Mar 1.

Published in final edited form as: Obstet Gynecol. 2009 Mar;113(3):601–608. doi: 10.1097/AOG.0b013e3181998998

Table 7. Multivariable model of risk factors for PFR after hysterectomy in Olmsted County, Minnesota women who had a substantial increase in overall pelvic organ prolapse severity between the two procedures (Group B)^*.

Risk Factor Assessment at Hysterectomy	Cases (n = 46)	Controls (n = 46)	OR (95% CI) ^†	p-value
Age, Mean ± SD	44.8 ± 9.3	44.1 ± 9.3	1.0 (0.9, 1.1)	0.73
BMI, Mean ± SD	24.2 ± 4.4	26.4 ± 6.5	1.0 (0.9, 1.0)	0.26
Uterine fibroids	14 (30.4%)	16 (34.9%)	1.1 (0.3, 4.2)	0.85
Endometriosis or adenomyosis	6 (13.0%)	10 (21.7%)	0.7 (0.2, 2.0)	0.44
Inflammatory disease or pelvic pain disorder or adnexal mass	21 (45.6%)	13 (28.3%)	2.5 (0.6, 9.6)	0.20
Other diagnosis	6 (13.0%)	7 (15.2%)	0.9 (0.2, 3.0)	0.80

This model based on 46 pairs (n=92) with complete data out of 72 pairs in Group B.

^†

Odds ratio (OR) adjusted for age at time of hysterectomy.

Table 7. Multivariable model of risk factors for PFR after hysterectomy in Olmsted County, Minnesota women who had a substantial increase in overall pelvic organ prolapse severity between the two procedures (Group B)*.