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Table 4 Logit regression results of the impact of different medical insurance system on the utilization of health services by the floating elderly population

From: Institutional differences and geographical disparity: the impact of medical insurance on the equity of health services utilization by the floating elderly population - evidence from China

Variables (1) (2) (3) (4)
  the Average Marginal Effect   the Average Marginal Effect   the Average Marginal Effect   the Average Marginal Effect
  Medical insurance − 0.157* − 0.0383* − 0.147* − 0.0355* − 0.0912 − 0.0215   
  (0.0810) (0.0197) (0.0823) (0.0199) (0.0849) (0.0200)   
No medical insurance        0.0629 0.0148
        (0.0883) (0.0208)
BMISUE        −0.124 −0.0292
        (0.102) (0.0239)
Gender    −0.124* −0.0299* − 0.105 − 0.0248 − 0.103 − 0.0243
    (0.0644) (0.0156) (0.0677) 0.0160 (0.0678) (0.0160)
Age    0.00957* 0.00232* 0.00718 0.00169 0.00737 0.00174
    (0.00553) (0.00134) (0.00602) 0.00142 (0.00603) (0.00142)
Ethnicity    −0.142 −0.0343 −0.0845 −0.0199 − 0.0838 − 0.0198
    (0.106) (0.0256) (0.109) (0.0256) (0.109) (0.0257)
Household registration type (Hukou) Rural hukou    −0.0949 −0.0230 0.0479 0.0113 0.0128 0.00301
    (0.0733) (0.0177) (0.0873) (0.0206) (0.0919) (0.0217)
Rural to resident hukou    −0.0500 −0.0121 −0.0285 −0.00671 − 0.0705 −0.0166
    (0.279) (0.0676) (0.284) 0.0670 (0.288) (0.0680)
Nonrural to resident hukou    0.487 0.118 0.306 0.0721 0.334 0.0787
    (0.382) (0.0924) (0.393) (0.0926) (0.394) (0.0928)
Marital Status Single    −0.359 − 0.0869 − 0.210 − 0.0495 −0.217 − 0.0511
    (0.331) (0.0799) (0.337) (0.0794) (0.337) (0.0794)
Married    −0.202** −0.0490** −0.187** − 0.0440** −0.184** − 0.0434**
    (0.0812) (0.0196) (0.0825) (0.0194) (0.0826) (0.0194)
  Education Level    0.0674** 0.0163** 0.0679** 0.0160** 0.0730** 0.0172**
    (0.0322) (0.00779) (0.0337) (0.00792) (0.0339) (0.00798)
Range of Migration Interprovince      0.317*** 0.0748*** 0.315*** 0.0742***
      (0.0811) (0.0190) (0.0810) (0.0190)
Intercity      0.0353 0.00833 0.0366 0.00862
      (0.0827) (0.0195) (0.0827) (0.0195)
  Monthly household income      2.15e-05*** 5.08e-06*** 2.15e-05*** 5.06e-06***
      (7.06e-06) 1.66e-06 (7.00e-06) (1.64e-06)
Main Source of Income Income from employment      −0.258*** −0.0609*** −0.258*** −0.0609***
      (0.0959) (0.0226) (0.0959) (0.0225)
Pension/savings      0.0538 0.0127 0.0901 0.0212
      (0.0984) (0.0232) (0.102) (0.0241)
Others      −0.0518 − 0.0122 − 0.0537 − 0.0127
      (0.162) (0.0381) (0.162) (0.0381)
  No. of friends of residence      0.00381 0.000899 0.00390 0.000920
      (0.00285) (0.000672) (0.00285) (0.000672)
Daily exercise time      −0.000841 −0.000198 −0.000800 −0.000188
      (0.000723) (0.000170) (0.000723) (0.000170)
Physical examination      0.223*** 0.0527*** 0.225*** 0.0530***
      (0.0657) (0.0154) (0.0657) (0.0154)
Self-rated health      0.0624 0.0147 0.0626 0.0148
      (0.0496) (0.0117) (0.0496) (0.0117)
  Province of residence      0.0130*** 0.00307*** 0.0130*** 0.00307***
      (0.00185) (0.000426) (0.00185) (0.000426)
  Constant −0.185** −0.185** −0.580 −0.580 −1.567*** −1.567*** −1.651*** −1.651***
  (0.0739) (0.0739) (0.431) (0.431) (0.521) (0.521) (0.519) (0.519)
Observations 4484   4484 4484 4481   4481  
Pseudo-R2 0.0006   0.0058   0.0247   0.0249  
  1. 1) Columns (1)–(3) divides medical insurance into two categories: “with medical insurance” and “no medical insurance,” and “no medical insurance” is the baseline variable. Column (4) divides medical insurance into three categories: “BMISUE”, “BMISURR”, and “no medical insurance”, and “BMISURR” is the baseline variable. 2) The baseline variables for household registration type, marital status, distance from place of origin, and main source of income are “nonrural hukou,” “divorced or widowed,” “intercity,” and “other members of the family”, respectively. 3) The robust standard errors are reported in parentheses. 4) *** p < 0.01, ** p < 0.05, * p < 0.1