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Table 6 Major influencing factors on medical debt of MFA cardholders in project Areas

From: The impact of different benefit packages of Medical Financial Assistance Scheme on health service utilization of poor population in Rural China

Factors Borrowing large amount money(≥500RMB) ※
  OR (CI, 95%) P
Type (H8SP/H8) 0.8 (0.6, 1.3) 0.281
Gender (male/female) 19.8 (11.5, 34.0) 0.000
Age (15-39.9/60+) 1.4 (0.9, 2.1) 0.387
Age (40-59.9/60+) 2.5 (1.8, 3.7) 0.000
Marital status (unmarried/married) 1.6 (0.9, 2.9) 0.317
Marital status (Widowed+ divorced/married) 0.3 (0.1, 0.5) 0.000
Education (Illiterate/junior high school+) 0.8 (0.5, 1.5) 0.819
Education (Primary school/junior high school+) 1.1 (0.7, 1.8) 0.639
Economic status (Extremely poor/relatively poor) 1.4 (1.0, 2.1) 0.082
Disability status (Presence/absence) 1.0 (0.6, 1.4) 0.874
Distance from home to the nearest designated medical centre (≤3 km/>3 km) 0.8 (0.6, 1.1) 0.321
Awareness of MFA detailed package (Yes/no) 1.5 (1.0, 2.1) 0.045
Presence of Illness in last 2 weeks (Presence/absence) 1.0 (0.4, 2.3) 0.893
Presence of Chronic disease (Presence/absence) 1.5 (1.1, 2.2) 0.036
Physician visit (yes/no) 1.3 (0.6, 3.2) 0.647
High-frequency MFA use (≥2) (yes/no) 1.1 (0.7, 1.7) 0.589
Hospitalization (yes/no) 4.2 (2.4, 6.8) 0.000
  1. ※ Binominal regression with log-link model was fitted using SAS PROC GENMOD;
  2. Odds ratio was adjusted for the other remaining independent variables listed in the table.