Table 4.
Results of the logistic regression analysis model.
|
N
=
24,562 Prob > chi2 = 0.0000 Pseudo R2 = 0.2345 Pearson Chi2 (1,541) = 1,461.89 | |||||
|---|---|---|---|---|---|
| Health insurance ownership | Odds ratio | Std. Err. | z | P >| z | [95% Conf. Interval] |
| Age | 1.00839 | 0.0073803 | 1.14 | 0.254 | 0.9940287 – 1.02296 |
| Residence | 0.7936482 | 0.104363 | −1.76 | 0.079 | 0.6133339 – 1.026973 |
| Education | 5.606138 | 0.7868402 | 12.28 | 0.000* | 4.257894 – 7.381299 |
| HH Head | 0.9270029 | 0.1365027 | −0.51 | 0.607 | 0.6946088 – 1.237149 |
| Wealth | |||||
| Middle | 3.03394 | 1.033773 | 3.26 | 0.001* | 1.555865 – 5.916192 |
| Richest | 15.97973 | 5.190536 | 8.53 | 0.000* | 8.454384 – 30.20346 |
| Marital status | 15.97973 | 0.1900378 | 1.70 | 0.089 | 0.9624323 – 1.717829 |
| Occupation | 2.398547 | 0.3202295 | 6.55 | 0.000* | 1.846309 – 3.115961 |
| _cons | | 0.0010086 | 0.0003848 | −18.09 | 0.000 | 0.0004776 – 0.0021304 |
*
represents significance of the variables.