Table 3 Association between migration region and health services use, based on a logistic regression analysis
From: The health service use of aged rural-to-urban migrant workers in different types of cities in China
Variables | Health records | Health education | Medical treatment |
|---|---|---|---|
Independent variables | |||
Migration region (western) | |||
Central | 0.39(0.05)*** | -0.35(0.05)*** | -0.13(0.06)* |
Eastern | -0.64 (0.05)*** | -0.90(0.04)*** | -0.19(0.06)** |
Control variables | |||
Predisposing | |||
Age | 0.01(0.00)* | -0.02(0.00)*** | -0.00(0.00) |
Gender (male) | |||
Female | 0.06(0.04) | -0.12(0.04)*** | -0.00(0.05) |
Education (illiterate or primary school) | |||
Middle school | 0.06(0.04) | 0.25(0.04)*** | -0.08(0.05) |
High school and above | -0.03(0.06) | 0.32(0.07)*** | -0.05(0.08) |
Marital status (no spouse) | |||
Married | 0.20(0.07)** | 0.08(0.06) | 0.039(0.09) |
Enabling | |||
Migration range (across counties, within a city) | |||
Across cities, within a province | 0.00(0.05) | -0.06(0.05) | -0.26(0.07)*** |
Across province | -0.03(0.06) | -0.02(0.05) | -0.17(0.07)* |
Medical insurance (no) | |||
Yes | 0.23(0.08)** | 0.19(0.07)** | 0.12(0.10) |
Social security card (no) | |||
Yes | 0.52(0.04)*** | 0.33(0.04)*** | 0.18(0.05)*** |
Needs | |||
Self-health assessment (unwell) | |||
Fair | 0.14(0.07)* | 0.25(0.06)*** | -0.37(0.07)*** |
Healthy | 0.22(0.07)*** | 0.33(0.06)*** | -0.65(0.07)*** |
Hypertension or diabetes (no) | |||
Yes | 0.24(0.05)*** | 0.10(0.05)* | 0.24(0.06)*** |
Constants | -2.37(0.28)*** | 1.44(0.22)*** | 0.61(0.30)* |
Log likelihood | -8110.00*** | -9060.88*** | -4703.12*** |
Sample | 14372 | 14372 | 6938 |