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. 2016 Oct;45(10):1247–1260.

Table 4:

Cox regression to evaluate the effect of health insurance on survival

Independent variables Dependent variable: survival time
Model III Model IV Model V
Type of insurance 0.5889 (0.3058) 0.6253 (0.3247) 0.3417 (0.4973)
Gender 0.9933 (0.2356) 1.0771 (0.2835) 0.7100 (0.1171)
Age (yr) 1.0258** (0.0122) 1.0279** (0.0126) 1.0542* (0.0425)
Place of residence 1.3983 (0.4484) 1.6895 (0.5647) 1.8050 (0.4748)
Marital status 1.2328 (0.4454) 1.2029 (0.4404) 1.1251 (1.6336)
Travel time 1.0022 (0.0031) 1.0018 (0.0032) 1.0027 (0.0084)
Work status 0.9943 (0.2353) 1.1471 (0.2818) 1.3037 (0.3011)
Household expenditures 0.9461* (0.0277) 0.9388* (0.0269) 0.9323* (0.0295)
Disability 1.1403** (0.2821) 1.1614** (0.1792)
Chronic disease 1.2843*** (0.2505) 1.2798*** (0.3332)
Health status 1.2344* (0.2135) 1.1727* (0.2656)
Physical examination 0.8201*** (0.2024)
Smoking habits 1.0790* (3.8756)
Drinking habits 1.1585 (0.3587)
Exercise habits 0.7766** (0.1198)
LR (Chi square) 17.33** 22.79*** 32.02***
Number of observations 587 584 533

Note: 1) Data in the table represent hazard ratio, and the numbers in the parentheses represent standard deviations. 2) *, **, and *** denote the level of significance test by 10%, 5%, and 1%, respectively