Table 2.
Logistic regression analyses, showing adjusteda odds ratios (ORs), with the corresponding 95 % confidence intervals (CIs) in brackets
| Predictor | OR (95 % CI) | |
|---|---|---|
| Ageb | Younger vs. medium | 1.36 (1.11, 1.66) |
| Older vs. medium | 1.24 (1.07, 1.43) | |
| Older vs. younger | 0.91 (0.70, 1.18) | |
| BMIc | Low vs. medium | 0.99 (0.83, 1.17) |
| High vs. medium | 1.26 (1.09, 1.46) | |
| High vs. low | 1.28 (0.95, 1.72) | |
| Oral contraceptive use | Yes vs. no | 0.43 (0.32, 0.58) |
| No. of pregnancies | Per-pregnancy increase | 0.93 (0.84, 1.02) |
| Self-reported endometriosis | yes vs. no | 2.63 (1.28, 5.41) |
BMI body mass index
aORs were estimated using a multiple logistic regression model, with the predictors listed in the first column of the table
bAge was used as a nonlinear continuous predictor. It was evaluated at the first sextile (“young” — i.e., 51 years), median (“medium” — i.e., 62 years), and fifth sextile (“older” — i.e., 70 years)
cBMI was used as a nonlinear continuous predictor. It was evaluated at the first sextile (“low” — i.e., 21.7 kg/m2), median (“medium” — i.e., 25.0 kg/m2), and fifth sextile (“high” — i.e., 30.1 kg/m2)