Identification of Predictors for Late or No Registration of Pregnancy by Selecting an Appropriate Logistic Model after Comparing ANC Visits and Skilled Birth Attendant

Abstract

Introduction: India is a major contributor to both maternal and neonatal death worldwide. Majority of these fatalities can be averted by adequate utilization of Antenatal care (ANC) services. Large scale surveys like National Family Health Survey follow hieratical characters in which subjects within the clusters are often correlated. The ordinary logistic model ignores this correlation and provide compromised estimate of effect size of predictors. Multilevel model that incorporates correlation is the appropriate method. Aim: To demonstrate the adequacy of multilevel logistic model over ordinary logistic model in hieratical data sets with ANC visits >4 and delivery assisted by Skilled Birth Attendant (SBA). Materials and Methods: This retrospective, cross-sectional study was conducted at the Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India, from October 2021 to March 2022. The data of 174607 women, who delivered the children within five years, obtained using cluster sampling, from country wide survey during 20th January 2015 to 4th December 2016 (India’s National Family Health Survey-IV) was used. Firstly, the model adequacy of ordinary and multilevel logistic models was evaluated for ANC >4 visits and delivery assisted by SBA, the same data set of fourth round National Family Health Survey by considering the outcomes;. Thereafter, predictors of late or no registration of pregnancy were identified using three level logistic model. Results: Because of high Variance Partition Coefficients (VPC) at state and district levels, the multilevel model applied on components ANC >4 visits and delivery assisted by SBA suggested better accuracy of the multilevel logistic model (-2Log L=189334 for ANC >4 visits and 141148 for delivery assisted by SBA) than the ordinary logistic model (-2Log L=220268 for ANC >4 visits and 151978 for delivery assisted by SBA). For the late (registration in third trimester of pregnancy) or no registration of pregnancy, each predictor was found significantly associated in which the most important were women’s education, child birth order, caste and wealth quintile. Conclusion: The present study concluded that multilevel logistic model in clustered design data was useful instead of individual level for more precise estimate of effect size of the predictors.