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Small Area Estimation Method for District Level Prevalence of Maternal Health Care Indicators in Bangladesh

Corresponding Author : Mossamet Kamrun Nesa (mknesa-sta@sust.edu)

Authors : Sabina Islam

Keywords : Small Area Estimation, Fay-Herriot Model, Direct Estimate, Antenatal Care, Postnatal Care

Abstract :

Small area estimation (SAE) method is commonly used to obtain micro-level estimates of development indicators. The SAE method through Fay-Herriot model is well-known to compute small area level estimates. This study aims to apply Fay-Harriot model to estimate the district level maternal health care indicators (MHCI) viz., antenatal care (ANC), postnatal care (PNC), skilled birth attendance (SBA), and caesarean section (C-section) with their accuracy level. Both Bangladesh Demographic and Health Survey (BDHS) 2011 and Bangladesh Population and Housing Census (BPHC) 2011 datasets are used to perform this study. The results of the study demonstrate that model-based estimates provide a better representation than the direct estimates showing lower coefficient of variations. The map of the various MHCI reveals substantial inequality across the district level estimates of Bangladesh. The study findings indicated that ANC visits (at least one) varies from 28% to 98% and most vulnerable district is appeared as Rangamati. The standard visits of ANC (four or more) differs within 8-51% showing Narail district hold the lowest ranking. The SBA lies within the range 0-55% and Netrokona district is the worst position. Further, PNC deviates within 27-73% and found Netrokona as the most vulnerable condition. Finally, C-section varies within range 5-35% and Bhola district appeared as the worst position. The outcomes of the study could be helpful for policymakers to identify the most vulnerable districts regarding MHCI and taking initiative to strengthen the existing programs relating to MHCI in the vulnerable areas.

Published on December 31st, 2020 in Volume 30, Issue 2, Applied Sciences and Technology