Structural equation analysis on the inter-relationships between optimal antenatal care, health facility delivery and early postnatal care among women in Ethiopia: EDHS 2016.

OBJECTIVE

This study employs structural equation modelling to explore the inter-relationships among optimal antenatal care (ANC), health facility delivery and early postnatal care (EPNC) in Ethiopia. By identifying both direct and indirect influencing factors, the study offers valuable insights to support integrated maternal health strategies and guide informed decision-making by policymakers and women alike.

DESIGN

The secondary analysis of the Ethiopian Demographic and Health Survey 2016 was performed to investigate inter-relationships between optimal ANC, health facility delivery and postnatal care (PNC) among women in Ethiopia. Data were analysed with R software V.4.3.2. The study used binary logistic regression to examine differences in optimal ANC, health facility delivery and EPNC, focusing on variables with a p value of 0.1 or less. Selected variables were incorporated into a generalised structural equation model (GSEM) using the LAVAAN package to explore both direct and indirect effects. The GSEM method assessed the impact of exogenous variables on endogenous variables, all binary, using a logistic link and binomial family. Missing data were handled with the multiple imputation by chained equations package, and sampling weights were applied to ensure national and regional representativeness.

SETTING AND PARTICIPANT

The source population comprised all women of reproductive age (15-49 years) who gave birth in the 5 years preceding the survey. From 16 650 interviewed households (98% response rate), we identified 7590 eligible women with recent births. Finally, we included 2415 women who had attended four or more ANC visits.

RESULT

Media exposure significantly boosts the likelihood of using ANC (OR=1.8, 95% CI (1.04 to 3.23), p=0.04), health facility delivery (OR=1.7, 95% CI (1.23 to 2.45), p=0.05) and PNC (OR=2.0, 95% CI (1.6 to 4.01), p=0.01). Urban residence and secondary education also enhance ANC (OR=1.2, 95% CI (1.01 to 2.88), p=0.022; OR=1.3, 95% CI (1.20 to 3.01), p=0.018), health facility delivery (OR=1.1, 95% CI (1.01 to 3.24), p=0.035; OR=1.5, 95% CI (1.22 to 3.45), p=0.03) and PNC (OR=1.6, 95% CI (1.01 to 4.32), p=0.03). ANC directly affects health facility delivery (OR=1.4, 95% CI (1.28 to 3.09), p=0.01) and PNC (OR=1.6, 95% CI (1.01 to 3.80), p=0.03). Additionally, women aged 20-34 years and those from male-headed households positively impact health facility delivery (OR=1.5, 95% CI (1.20 to 4.80), p=0.01; OR=1.3, 95% CI (1.07 to 3.45), p=0.014) and PNC (OR=1.4, 95% CI (1.10 to 2.90), p=0.01; OR=1.2, 95% CI (1.07 to 3.08), p=0.025).

CONCLUSIONS

Optimal ANC is vital for encouraging health facility delivery and EPNC. To enhance maternal and neonatal health, policies should integrate these services. Key predictors include being aged 20-34, having secondary and higher education, media exposure, male-headed households and living in urban areas. Improving education and media exposure can boost maternal healthcare service use.