Logit(𝑌ij) = 𝛽 0 + 𝜃𝑡 + 𝛽1𝐺+ 𝛽2𝑡 + 𝛽3𝐺.𝑡 + γ 1W + γ2W.𝑡 + γ3𝐺.W + γ4W.𝐺.𝑡 + 𝑈𝑖𝑔𝑡 + 𝜀𝑖𝑔𝑡 ….(2)
As equation (1) above, 𝑌 is the binary outcome indicator for adverse pregnancy outcome 𝛽0 is the intercept. 𝜃𝑡 captures the period of time-invariant fixed effects. 𝐺 is an area indicator for treatment (𝐺 =1) or comparison (𝐺 = 0) districts. t is an indicator variable for baseline (=0) or endline (=1), 𝛽s are the regression coefficients to be estimated by maximum likelihood. W indicates the household wealth index. The parameters γ1, γ2, and γ3 represent adjusted effects of wealth in comparison districts at baseline, the change in the effect of wealth in comparison districts between baseline and end-line, and the difference in the effect of wealth between intervention and comparison districts at baseline respectively. Thus,γ4 estimates the effect of GEHIP on health equity relative to comparison districts, that is the difference in change in equity between intervention and comparison districts. The vector Uigt refers to control variables in the model while 𝜀𝑖𝑔𝑡 is the error term. STATA software was used in all the analyses.