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Table 2 Decomposition of inequality in the maternal health services utilization

From: Measuring and decomposing the inequality of maternal health services utilization in Western Rural China

 

More than 4 times prenatal visits

Hospital delivery

More than 2 times postnatal visits

 

Marginal effects

Contributions

Marginal effects

Contributions

Marginal effects

Contributions

Women’s age

      

 <20

-

     

 20-

0.4015*

0.0226

0.1723*

0.0036

0.2247*

−0.0032

 30-

0.5959*

0.0509

0.2657*

0.0069

0.1849*

0.0019

 40-

0.4848*

0.0078

0.3139

0.0129

0.0592

0.0000

 Ethnicity

0.3208*

0.0281

0.8199*

0.0158

0.1917*

0.0038

Parity

      

 1

-

     

 2

−0.2116*

−0.0153

−0.1746*

−0.0042

0.0147

0.0003

 > = 3

−0.4654*

0.0041

−0.4451*

−0.0062

−0.0573

0.0063

Women education

      

 Primary school

-

     

 Second school

0.1848*

0.0066

0.2208*

0.0025

−0.0679*

0.0019

 High school

0.3611*

0.0168

0.4035*

0.0058

−0.0377

0.0001

Husband education

      

 Primary school

-

     

 Second school

0.1476*

0.0077

0.0979*

0.0184

0.1115*

−0.0016

 High school

0.2303*

0.0115

0.1869*

0.0041

0.1964*

−0.0025

Wealth index

      

 Poor

-

     

 Middle

0.2506*

0.0165

0.1887*

0.0023

0.0552*

0.0002

 Good

0.2952*

0.0170

0.3590*

0.0037

−0.0479*

0.0007

  1. *The marginal effects demonstrate associations between determinants and maternal health services utilization outcomes. Those with positive signs indicate positive associations with the probability of maternal health services utilization, while those with negative signs indicate negative associations. In addition, the larger the absolute value of a marginal effect, more substantial is the association. Statistically significant estimates of marginal effects are highlighted (p<0.05).