Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance.

Kakoli Rani Bhowmik,Sumonkanti Das,Md Atiqul Islam,Russell Kabir

doi:10.1371/journal.pone.0228215

Abstract

The existence of excess zeros in the distribution of antenatal care (ANC) visits in Bangladesh raises the research question of whether there are two separate generating processes in taking ANC and the frequency of ANC. Thus the main objective of this study is to identify a proper count regression model for the number of ANC visits by pregnant women in Bangladesh covering the issues of overdispersion, zero-inflation, and intra-cluster correlation with an additional objective of determining risk factors for ANC use and its frequency. The data have been extracted from the nationally representative 2014 Bangladesh Demographic and Health Survey, where 22% of the total 4493 women did not take any ANC during pregnancy. Since these zero ANC visits can be either structural or sampling zeros, two-part zero-inflated and hurdle regression models are investigated along with the standard one-part count regression models. Correlation among response values has been accounted for by incorporating cluster-specific random effects in the models. The hurdle negative binomial regression model with cluster-specific random intercepts in both the zero and the count part is found to be the best model according to various diagnostic tools including likelihood ratio and uniformity tests. The results show that women who have poor education, live in poor households, have less access to mass media, or belong to the Sylhet and Chittagong regions are less likely to use ANC and also have fewer ANC visits. Additionally, women who live in rural areas, depend on family members' decisions to take health care, and have unintended pregnancies had fewer ANC visits. The findings recommend taking both cluster-specific random effects and overdispersion and zero-inflation into account in modelling the ANC data of Bangladesh. Moreover, safe motherhood programmes still need to pay particular attention to disadvantaged and vulnerable subgroups of women.

Highlights

Following the third Sustainable Development Goal of reducing the global maternal mortality ratio (MMR) to 70 per 100,000 live births by 2030 [1, 2], the Bangladesh government set targets to reduce the MMR to 143 and 105 per 100,000 live births, in 2015 and 2022 respectively
The estimated odds ratio (OR) and incidence rate ratio (IRR) in this study indicate that the probability to take no antenatal care visits (ANC) and the frequency of ANC visits both increased with increasing household wealth status
The selected hurdle regression model confirms that two processes generate the number of ANC visits in Bangladesh: one process generates zero ANC visits and the other generates the frequency of ANC visits

Summary

Introduction

Following the third Sustainable Development Goal of reducing the global maternal mortality ratio (MMR) to 70 per 100,000 live births by 2030 [1, 2], the Bangladesh government set targets to reduce the MMR to 143 and 105 per 100,000 live births, in 2015 and 2022 respectively. It has been shown that there may be two separate processes that generate decisions regarding the use and frequency of prenatal care use [14, 15] Without distinguishing these generating processes, Poisson regression (PR) and negative binomial regression (NBR) models have been widely used to model the number of ANC visits in Bangladesh [12, 13, 16]. These models may provide inconsistent regression coefficient, as overdispersion and excess zeros remain unaccounted for [17]. Sepehri and Serieux [22] employed a two-part HR model incorporating such cluster effects in the model and explored the determinants of ANC use and the frequency of ANC visits utilizing ANC data from 32 developing countries

Objectives

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Discussion

Conclusion