logitππππ‘ = π½ 0 +
ππ‘ + π½1πΊ+ π½2π‘ +
π½3πΊ.π‘ + ππππ‘ +
ππππ‘β¦β¦ (1)
Where Y represents the pregnancy outcome indicator.π½ 0 is
the intercept. ππ‘ captures the period of
time-invariant fixed effects. πΊ is an area indicator for
treatment (πΊ =1) or comparison (πΊ = 0) districts.t is an indicator variable for baseline (=0) or endline (=1), theπ½ s are the regression coefficients to be estimated,π½3 captures the average treatment effect of
GEHIP intervention on pregnancy outcome; Uigt captures
individual-level factors that predict adverse pregnancy outcome.
Predictor variables include motherβs age, marital status, educational
status, household wealth index, religion, ethnicity and parity.ππππ‘ is the error term.
To assess if GEHIPβs intervention had an impact in the reduction of
inequalities in adverse pregnancy outcomes, two variables; hosuehold
wealth index and maternal eductaional attainment were used as equity
stratifiers in line with the literature .
logistic regression models with interaction terms are used to examine
the equity effect of GEHIPβs community-based health program on adverse
pregnancy outcomes stratified by household wealth index and maternal
education. Equation (2) shows the specification of the logistic model
for estimating the effect of wealth status: