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Table 2 Comparison of Health Care Utilization of Migrant Parents in Residency between IMISs and non-IMISs

From: Does integrated medical insurance system alleviate the difficulty of using cross-region health care for the Migrant Parents in China-- evidence from the China migrants dynamic survey

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

hospitalized in the past year(inpa)

hospitalized in the past year(inpa)

hospitalized in the past year(inpa)

hospitalized locally in the past year(local_inpa)

hospitalized locally in the past year(local_inpa)

hospitalized locally in the past year(local_inpa)

see a doctor locally with less serious diseases(less_serious_doctor)

see a doctor locally with less serious diseases(less_serious_doctor)

imis

0.0315**

0.0315**

0.0163**

0.0330***

0.0337***

0.0226***

0.0446*

0.0401

 

(0.0128)

(0.0127)

(0.00749)

(0.0121)

(0.0119)

(0.00809)

(0.0269)

(0.0250)

the need of hospitalization (need_inpa)

  

0.818***

  

0.594***

  
   

(0.0173)

  

(0.0242)

  

self-reported health status

−0.0811***

−0.0735***

− 0.00194

− 0.0632***

− 0.0575***

− 0.00558

0.00617

0.00873

 

(0.00713)

(0.00748)

(0.00307)

(0.00655)

(0.00681)

(0.00430)

(0.0110)

(0.0109)

Having hypertension or diabetes

0.100***

0.0958***

0.00470

0.0854***

0.0823***

0.0162**

0.0347**

0.0335**

 

(0.0115)

(0.0112)

(0.00410)

(0.0110)

(0.0108)

(0.00645)

(0.0151)

(0.0148)

Fitness time per day (min)

0.000134

0.0000815

0.0000116

0.0000971

0.0000489

−0.00000183

0.000351**

0.000181

 

(0.0000876)

(0.0000852)

(0.0000343)

(0.0000786)

(0.0000769)

(0.0000434)

(0.000156)

(0.000153)

Health examination in the past one year

−0.00183

− 0.00293

− 0.00360

0.00305

0.00182

0.00134

0.0755***

0.0715***

 

(0.00821)

(0.00811)

(0.00357)

(0.00803)

(0.00788)

(0.00461)

(0.0204)

(0.0205)

age

0.00153**

0.000946

0.000113

0.00113*

0.000631

0.0000274

0.00488***

0.00321**

 

(0.000691)

(0.000761)

(0.000271)

(0.000630)

(0.000689)

(0.000392)

(0.00122)

(0.00127)

male

0.00793

0.0126**

0.00258

0.00547

0.00823*

0.000999

−0.0365***

−0.0236**

(reference group: female)

(0.00562)

(0.00587)

(0.00280)

(0.00491)

(0.00497)

(0.00345)

(0.00845)

(0.00950)

Married

0.00237

0.000302

0.000569

−0.00316

−0.00437

−0.00418

− 0.0171

−0.0107

(reference group: Unmarried)

(0.00887)

(0.00873)

(0.00415)

(0.00767)

(0.00758)

(0.00516)

(0.0161)

(0.0167)

Han ethnic

−0.000451

0.00125

0.00373

−0.00464

−0.00464

− 0.00285

−0.0280

− 0.0322

(reference group: minority)

(0.0127)

(0.0127)

(0.00752)

(0.0115)

(0.0116)

(0.0100)

(0.0281)

(0.0273)

Elementary school

 

0.00266

−0.00218

 

−0.00233

−0.00584

 

−0.0170

(reference group: no formal education)

 

(0.00986)

(0.00443)

 

(0.00790)

(0.00499)

 

(0.0178)

Middle school

 

−0.0157

−0.0102**

 

−0.0127

−0.00867

 

0.000487

(reference group: no formal education)

 

(0.0118)

(0.00515)

 

(0.00988)

(0.00574)

 

(0.0213)

High school/vocational school

 

0.000738

−0.00193

 

0.00700

0.00507

 

−0.0170

(reference group: no formal education)

 

(0.0162)

(0.00682)

 

(0.0145)

(0.00799)

 

(0.0384)

college and above

 

−0.0709***

−0.0225*

 

−0.0621***

−0.0270*

 

−0.0617

(reference group: no formal education)

 

(0.0187)

(0.0136)

 

(0.0171)

(0.0145)

 

(0.0604)

rural

 

0.0101

0.000679

 

0.00742

0.000608

 

−0.0321

(reference group: urban)

 

(0.00892)

(0.00527)

 

(0.00799)

(0.00585)

 

(0.0206)

income

 

−0.00474

−0.000639

 

0.00472

0.00770**

 

0.0275**

  

(0.00521)

(0.00211)

 

(0.00319)

(0.00327)

 

(0.0120)

expenditure

 

0.0166

−0.000869

 

0.00600

− 0.00663

 

− 0.0205

  

(0.0108)

(0.00423)

 

(0.00788)

(0.00527)

 

(0.0215)

Food expenditure

 

−0.00831

0.00225

 

−0.00677

0.000888

 

−0.000658

  

(0.00773)

(0.00361)

 

(0.00669)

(0.00443)

 

(0.0155)

House expenditure

 

−0.000830

−0.000593

 

−0.000495

−0.000323

 

−0.00820**

  

(0.00154)

(0.000736)

 

(0.00136)

(0.000929)

 

(0.00377)

Main source of income

        

Pension and Savings

 

0.0279**

−0.0151**

 

0.0252**

−0.00598

 

0.0417

(reference group: self-employment)

 

(0.0137)

(0.00688)

 

(0.0120)

(0.00799)

 

(0.0298)

Support from other family numbers

 

0.0110

−0.0143**

 

0.0152

−0.00315

 

0.0585**

(reference group: self-employment)

 

(0.0131)

(0.00638)

 

(0.0123)

(0.00756)

 

(0.0280)

Others

 

0.0109

−0.0145*

 

0.00732

−0.0111

 

−0.0179

(reference group: self-employment)

 

(0.0183)

(0.00755)

 

(0.0163)

(0.00996)

 

(0.0336)

Number of friends in residence

 

0.000474

0.0000575

 

0.000582

0.000280

 

0.00251***

  

(0.000450)

(0.000152)

 

(0.000388)

(0.000250)

 

(0.000959)

years since migration

 

0.000649

0.000408

 

0.00140***

0.00122***

 

−0.00107

  

(0.000557)

(0.000302)

 

(0.000519)

(0.000366)

 

(0.00122)

Main source of income

 

0.0141

0.0242***

 

0.00457

0.0119

 

0.0198

  

(0.0123)

(0.00773)

 

(0.0115)

(0.00791)

 

(0.0293)

Fixed effects of origin provinces

Fixed effects of flow-in cities

_cons

0.121*

0.0781

0.0588*

0.163***

0.114

0.0996**

0.591***

0.702***

 

(0.0616)

(0.0835)

(0.0319)

(0.0589)

(0.0776)

(0.0486)

(0.122)

(0.175)

N

7919

7912

7912

7919

7912

7912

7919

7912

  1. Note: Robust standard errors are reported in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. The dependent variable of Columns (1)– (3) is inpa; the dependent variable of Columns (4)– (6) is local_inpa; the dependent variable of Columns (7)– (8) is less_serious_doctor. The Column (1) (4), and (7) only control health status, health behaviors, individual demographic characteristics and city fixed effect. The Column (2) (5), and (8) also controls SES, including education, income, expenditure and immigration information, on the basis of Column (1) (4), and (7). The Column (3) and (6) also controls need_inpa on the basis of Column (2) and (5). Since the dependent variable of Column (7) and (8) is less_serious_doctor (the circumstance that the Migrant Parents do not need inpatient services), we do not control need_inpa in these two columns