Table 2. Multivariable logistic regression analysis on the treatment success rates for migrant smear-positive cases by confounding factors, Shanghai, China, 2006 and 2010.
| Variables | β | Wald | P-value | OR | 95% CI |
|---|---|---|---|---|---|
| Patient site (non-project = 0) | –0.725 | –2.63 | 0.009 | 0.484 | (0.282–0.831) |
| Patient site * year (year, 2006 = 0) | 1.156 | 2.55 | 0.011 | 3.178 | (1.305–7.736) |
| Sex (female = 0) | –0.403 | –2.13 | 0.033 | 0.668 | (0.461–0.969) |
| Patient type(new cases = 0) | –0.588 | –2.59 | 0.010 | 0.555 | (0.356–0.867) |
| Occupationretired * (skilled or partly skilled = 0) | –1.040 | –2.63 | 0.009 | 0.354 | (0.163–0.768) |
| Constant | 2.026 |
a Occupation is used as dummy variables in regression analysis. All other occupation fields are not included in the regression model.