Table 4:
Predictors of catastrophic costs
| Variable | Univariate Logistic Regression | Multiple Logistic Regression | ||
|---|---|---|---|---|
| OR (95% CI) | p-value | AOR (95% CI) | p-value | |
| Coping costs >0 | 5.87 (2.95, 12.26) | 0.000 | 3.84 (1.81, 8.40) | 0.001 |
| Poora | 2.68 (1.26, 5.85) | 0.011 | 2.91 (1.29, 6.72) | 0.011 |
| Hospitalized | 11.94 (3.90, 52.10) | 0.000 | 8.66 (2.60, 39.54) | 0.001 |
| Quit job | 4.81 (1.77, 15.38) | 0.004 | -- | -- |
| Female | 1.03 (0.58, 1.84) | 0.914 | -- | -- |
| HIV+ | 1.15 (0.63, 2.11) | 0.648 | -- | -- |
| Age | 0.87 (0.58, 1.28) | 0.470 | -- | -- |
| Education | 0.95 (0.67, 1.32) | 0.744 | -- | -- |
NOTES: Univariate logistic regressions were used to identify contributory variables (p<0.2), which were then subjected to AIC forward selection to produce an optimized multiple logistic regression model. The adjusted odds ratio, 95% confidence interval, and p-value are shown for the three selected variables.
a
Earning less than $47.53 per month