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Table 3 Estimated two-part models of rural patients’ medical debt

From: What contributes to medical debt? Evidence from patients in rural China

Independent variables Prevalence(n = 826) Log (debt load)(n = 568)
Coefficient (SE) z-Stat. Coefficient (SE) z-Stat.
Age (years) ≤17 Ref   Ref  
18–44 0.518 (0.388) 1.34 −0.046 (0.157) −0.29
45–64 0.657 (0.402) 1.63 −0.045 (0.167) −0.27
65+ −0.236 (0.413) − 0.57 − 0.329 (0.181) −1.81
Gender Male Ref   Ref  
Female 0.060 (0.172) 0.35 −0.104 (0.067) −1.55
Marriage Married Ref   Ref  
Others −0.263 (0.247) −1.07 −0.074 (0.105) − 0.71
Household size ≤3 Ref   Ref  
≥4 0.422 (0.187)a 2.25 0.062 (0.072) 0.86
PCHI (least to highest) Quartile 1 Ref   Ref  
Quartile 2 0.230 (0.247) 0.93 −0.144 (0.094) −1.53
Quartile 3 −0.019 (0.257) − 0.07 −0.306 (0.097)b −3.16
Quartile 4 −0.404 (0.255) −1.59 −0.236 (0.099)a −2.40
Hospital level County or less Ref   Ref  
Municipal or higher 0.054 (0.232) 0.23 0.187 (0.096)a 1.96
Inpatient days −0.001 (0.002) −0.39 − 0.002 (0.001)b − 3.43
Inpatient expenses (least to highest) Quartile 1 Ref   Ref  
Quartile 2 −0.178 (0.241) −0.74 0.001 (0.097) 0.10
Quartile 3 −0.010 (0.262) −0.04 0.340 (0.100)b 3.40
Quartile 4 −0.404 (0.308) −0.69 0.569 (0.117)c 4.88
NCMS reimbursement ratio 1.633 (0.819)a 1.99 −0.120 (0.346) −0.35
CII reimbursement ratio 2.574 (2.103) 1.22 1.995 (0.785)a 2.54
NDMC 0.225 (0.067)b 3.36 0.121 (0.029)c 4.12
Indirect cost 0.035 (0.020) 1.75 −0.006 (0.008) − 0.77
Financial assistance from kin No Ref   Ref  
Yes −1.468 (0.206)c −7.14 −0.189 (0.095)a −1.98
Medical assistance No Ref   Ref  
Yes 0.420 (0. 231) 1.81 0.078 (0.084) 0.93
Constant −2.384 (1.074)a −2.22 9.411 (0.479)c 19.67
Likelihood-ratio test vs. logistic/linear regression
Chiba2 0.00 6.83b
  1. aIndicates significance at the 0.05 level
  2. bIndicates significance at the 0.01 level
  3. cIndicates significance at the 0.001 level