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. 2021 Oct 5;21:1053. doi: 10.1186/s12913-021-07069-w

Table 5.

Comparison of Health Care Utilization of Migrant Parents between IMISs and. URBMIs after the Adjustment of Insurance Type

(1) (2) (3) (4) (5) (6) (7) (8) (9)
IMISs vs. non-IMISs IMISs vs. NCMSs IMISs vs. URBMIs
hospitalized in the past year(inpa) hospitalized locally in the past year(local_inpa) see a doctor locally with less serious diseases(less_serious_doctor) hospitalized in the past year(inpa) hospitalized locally in the past year(local_inpa) see a doctor locally with less serious diseases(less_serious_doctor) hospitalized in the past year(inpa) hospitalized locally in the past year(local_inpa) see a doctor locally with less serious diseases(less_serious_doctor)
imis 0.0147** 0.0244*** 0.0431* 0.0109* 0.0195*** 0.0436 0.0321*** 0.0228 0.0125
(0.00596) (0.00696) (0.0227) (0.00646) (0.00728) (0.0310) (0.00968) (0.0525) (0.0561)
the need of hospitalization(need_inpa)
Other control variables
SES
Fixed effects of origin provinces
Fixed effects of flow-in cities
N 7912 7912 7912 6885 6885 6885 1691 1691 1691

Note: Robust standard errors are reported in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Other control variables include individual demographic characteristic, self-reported health status, having hypertension or diabetes, fitness time, having health examination or not in the past year. SES includes education, income, expenditure and immigration information. Same structure of dependent variable as in Table 2. The columns (1) – (3) and (4)– (6) have same structure as column (3), (6), and (8) in Table 2. The columns (7)– (9) have same structure as column (3), (6), and (8) in Table 4. In this regression, we redefine the potentially misreported insurance type, considering samples who are rural residents with agriculture hukou as IMISs