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Table 3 Factors influencing catastrophic health expenditure in multivariate logistic regression model

From: A comparative study of catastrophic health expenditure in Zhejiang and Qinghai province, China

Variables Zhejiang Qinghai
b S.E. OR P-value b S.E. OR P-value
Household income per year −0.0001 0.00002 1.000 < 0.000 −0.0002 0.00002 1.000 < 0.000
Poor/low-insured household 1.797 .507 6.029 < 0.000     
Minority household head      0.724 0.233 2.063 0.002
Employment status of household head (reference: unemployed)
 Employed −0.710 0.313 0.492 0.023 −0.652 0.257 0.521 0.011
 Retired −0.149 0.394 0.861 0.704 −0.180 0.325 0.835 0.580
Number of members with chronic diseases in household in the last six months 0.528 0.182 1.695 0.004 0.452 0.161 1.572 0.005
Number of outpatients in household in the last two weeks of the survey      0.505 0.231 1.657 0.029
Number of inpatients in household in the last one year of the survey 1.752 0.232 5.764 < 0.000 0.859 0.186 2.361 < 0.000
 (Constant) −1.007 0.282 0.365 < 0.000 −0.133 0.276 0.876 0.631
Model < 0.000     < 0.000    
−2 log likelihood 409.504     550.674    
Nagelkerke R2 0.415     0.384    
Cox & Snell R2 0.200     0.272    
  1. SE standard error; OR odds ratio
  2. Household size: number of permanent residents in household; Poor/low-insured household: poor or low-insured household identified by the local government; Married: married status in the marriage law