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Table 2 Results of multiple linear regression analysis (n = 7772)

From: Reduction but not elimination: health inequalities among urban, migrant, and rural children in China—the moderating effect of the fathers’ education level

Dependent variable:
HAZ
Model 1 Model 2 Model 3 Model 4
Coefficient (SE) Coefficient (SE) Coefficient (SE) Coefficient (SE)
Intercept: 0.031 (0.037) 4.879*** (0.189) 4.789*** (0.195) 4.694*** (0.197)
Gender: (ref. = male)   −0.612*** (0.021) −0.612*** (0.021) −0.399*** (0.073)
Age:   − 0.329*** (0.013) − 0.328*** (0.013) − 0.328*** (0.013)
Race: (ref. = Han race)   0.173*** (0.038) 0.167*** (0.039) 0.166*** (0.039)
Number of siblings:   −0.172*** (0.017) −0.174*** (0.017) − 0.181*** (0.017)
Family economic conditions: (ref. = Poverty)
 Middle income   0.176*** (0.026) 0.175*** (0.026) 0.174*** (0.026)
 Affluent   0.372*** (0.048) 0.371*** (0.048) 0.376*** (0.048)
Child types: (ref. = Rural children)
 Migrant children 0.096** (0.033) 0.153*** (0.029) 0.287** (0.097) 0.289** (0.097)
 Urban children 0.233*** (0.028) 0.165*** (0.026) 0.301*** (0.083) 0.294*** (0.083)
Fathers’ education level: 0.072*** (0.004) 0.042*** (0.004) 0.053*** (0.007) 0.059*** (0.008)
Interaction terms between child type and fathers’ years of education: (ref. = Rural children × father’s education level)
 Migrant children × fathers’ education level    −0.018* (0.008) −0.011 (0.011)
 Urban children × fathers’ education level    −0.016† (0.009) −0.008 (0.009)
Interaction terms between gender, child type and fathers’ education level: (ref. = Male × Rural children × Fathers’ education level)
 Female × Rural children × Fathers’ education level     −0.016† (0.009)
 Female × Migrant children × Fathers’ education level     −0.025** (0.008)
 Female × Urban children × Fathers’ education level     −0.028*** (0.007)
F-statistic 212.15*** 304.72*** 249.68*** 198.97***
DF 3 9 11 14
R2 0.076 0.261 0.261 0.264
  1. Note: *** p < 0.001, ** p < 0.01, * p < 0.05, † p < 0.1