Table 3.
Hierarchical multiple regression predicting MCS and PCS.
| Standardized beta coefficients | ||||||
|---|---|---|---|---|---|---|
| MCS | PCS | |||||
| Model 1 | Model 2 | Model 3 | Model 1 | Model 2 | Model 3 | |
| Block 1 demographic characteristics | ||||||
| Gender (female vs. male) | −0.077 | −0.105 ∗ | −0.088 | −0.132 ∗∗ | −0.14 ∗∗ | −0.129 ∗∗ |
| Medical insurance (others vs. basic medical insurance for urban residents) | −0.035 | −0.025 | −0.020 | −0.171 ∗∗ | −0.168 ∗∗ | −0.165 ∗∗ |
| Marital status (widowed vs. married) | 0.006 | 0.018 | −0.103∗ | 0.076 | 0.079 | −0.132 ∗∗ |
| Age | −0.239 ∗∗ | −0.225 ∗∗ | −0.203 ∗∗ | −0.339 ∗∗ | −0.335 ∗∗ | −0.321 ∗∗ |
| Monthly medical expenses for hypertension | −0.231 ∗∗ | −0.232 ∗∗ | −0.151 ∗∗ | −0.245 ∗∗ | −0.245 ∗∗ | −0.195 ∗∗ |
| Block 2 APGAR | 0.224 ∗∗ | 0.14 ∗∗ | 0.062 | 0.009 | ||
| Block 3 SAS | −0.464 ∗∗ | −0.29 ∗∗ | ||||
| Adjusted R2 | 0.140 | 0.183 | 0.362 | 0.244 | 0.245 | 0.314 |
| ΔR2 | 0.192 | 0.043 | 0.170 | 0.29 | 0.003 | 0.067 |
∗P < 0.05 (two-tailed). ∗∗P < 0.01 (two-tailed).