Table 5 Logit regression models assessing the relationship between self-employment and social health insurance
From: Effect of self-employment on the sub-health status and chronic disease of rural migrants in China
| Â | Social health insurance | |
|---|---|---|
β | 95% CI | |
Employment status | ||
 Self-employed | −2.6891*** | (−2.7559, − 2.6223) |
 Wage-employed | Reference |  |
Gender | ||
 Male | −0.0505** | (−0.0906, − 0.0104) |
 Female | Reference |  |
Age | 0.1847*** | (0.1682, 0.2012) |
Age^2 | −0.0024*** | (−0.0026, − 0.0021) |
Education attainment | ||
 Primary school or below | Reference |  |
 Junior high school | 0.7024*** | (0.6303, 0.7744) |
 Senior high school | 1.3755*** | (1.2976, 1.4534) |
 College or above | 2.3361*** | (2.2518, 2.4204) |
Marital status | ||
 Married | 0.4233*** | (0.3482, 0.4984) |
 Unmarried | Reference |  |
Income (monthly) | 0.0001*** | (0.00008, 0.00009) |
Industry | ||
 Other | Reference |  |
 Construction industry | 0.8963*** | (0.8241, 0.9685) |
 Service industry | 0.1161*** | (0.0436, 0.1886) |
Migrated with children | ||
 Yes | −0.0228 | (−0.0807, 0.0350) |
 No | Reference |  |
Migrated with couple | ||
 Yes | −0.3237*** | (−0.3881, − 0.2593) |
 No | Reference |  |
Constant | −5.9795*** | (−6.2675, −5.6916) |