Table 4.
Associations between migration city type and health services use based on a logistic regression analysis
| Variables | Health records | Health education | Medical treatment |
|---|---|---|---|
| Independent variables | |||
| Migration city type (third-tier cities and smaller cities) | |||
| Second-tier cities | -0.28(0.04)*** | -0.29(0.04)*** | -0.24(0.06)*** |
| First-tier cities | -1.12(0.09)*** | -0.58(0.06)*** | -0.39(0.09)*** |
| Control variables | |||
| Predisposing | |||
| Age | 0.01(0.00)** | -0.02(0.00)*** | -0.00(0.00) |
| Gender (male) | |||
| Female | 0.07(0.04) | -0.12(0.04)** | 0.01(0.05) |
| Education (illiterate or primary school) | |||
| Middle school | 0.11(0.04)* | 0.25(0.04)*** | -0.07(0.05) |
| High school and above | 0.03(0.06) | 0.31(0.06)*** | -0.04(0.08) |
| Marital status (no spouse) | |||
| Married | 0.22(0.07)** | 0.05(0.06) | 0.03(0.09) |
| Enabling | |||
| Migration range (across counties within a city) | |||
| Across cities, within a province | 0.00(0.05) | -0.00(0.05) | -0.19(0.07)** |
| Across province | -0.20(0.05)*** | -0.10(0.05) | -0.10(0.07) |
| Medical insurance (no) | |||
| Yes | 0.24(0.08)** | 0.20(0.07)** | 0.13(0.10) |
| Social security card (no) | |||
| Yes | 0.48(0.04)*** | 0.34(0.04)*** | 0.20(0.05)*** |
| Needs | |||
| Self-health assessment (unwell) | |||
| Fair | 0.12(0.07) | 0.24(0.06)*** | -0.35(0.07)*** |
| Health | 0.18(0.07)** | 0.31(0.06)*** | -0.62(0.07)*** |
| Hypertension or diabetes (no) | |||
| Yes | 0.25(0.05)*** | 0.09(0.05)* | 0.25(0.06)*** |
| Constants | -2.31(0.24)*** | 1.15(0.22)*** | 0.47(0.30) |
| Log likelihood | -8189.45*** | -9214.57*** | -4692.86** |
| Sample | 14372 | 14372 | 6938 |
Note: * p < 0.05; ** p < 0.01; *** p < 0.001. The reference items are in parentheses.