TY - JOUR
T1 - Investigating Health Inequality Using Trend, Decomposition and Spatial Analyses
T2 - A Study of Maternal Health Service Use in Nepal
AU - Ali, Shehzad
AU - Thind, Amardeep
AU - Stranges, Saverio
AU - Campbell, M Karen
AU - Sharma, Ishor
N1 - Copyright © 2023 Ali, Thind, Stranges, Campbell and Sharma.
PY - 2023/6/2
Y1 - 2023/6/2
N2 - Objectives: (a) To quantify the level and changes in socioeconomic inequality in the utilization of antenatal care (ANC), institutional delivery (ID) and postnatal care (PNC) in Nepal over a 20-year period; (b) identify key drivers of inequality using decomposition analysis; and (c) identify geographical clusters with low service utilization to inform policy. Methods: Data from the most recent five waves of the Demographic Health Survey were used. All outcomes were defined as binary variables: ANC (=1 if ≥4 visits), ID (=1 if place of delivery was a public or private healthcare facility), and PNC (=1 if ≥1 visits). Indices of inequality were computed at national and provincial-level. Inequality was decomposed into explanatory components using Fairile decomposition. Spatial maps identified clusters of low service utilization. Results: During 1996-2016, socioeconomic inequality in ANC and ID reduced by 10 and 23 percentage points, respectively. For PND, the gap remained unchanged at 40 percentage points. Parity, maternal education, and travel time to health facility were the key drivers of inequality. Clusters of low utilization were displayed on spatial maps, alongside deprivation and travel time to health facility. Conclusion: Inequalities in the utilization of ANC, ID and PNC are significant and persistent. Interventions targeting maternal education and distance to health facilities can significantly reduce the gap.
AB - Objectives: (a) To quantify the level and changes in socioeconomic inequality in the utilization of antenatal care (ANC), institutional delivery (ID) and postnatal care (PNC) in Nepal over a 20-year period; (b) identify key drivers of inequality using decomposition analysis; and (c) identify geographical clusters with low service utilization to inform policy. Methods: Data from the most recent five waves of the Demographic Health Survey were used. All outcomes were defined as binary variables: ANC (=1 if ≥4 visits), ID (=1 if place of delivery was a public or private healthcare facility), and PNC (=1 if ≥1 visits). Indices of inequality were computed at national and provincial-level. Inequality was decomposed into explanatory components using Fairile decomposition. Spatial maps identified clusters of low service utilization. Results: During 1996-2016, socioeconomic inequality in ANC and ID reduced by 10 and 23 percentage points, respectively. For PND, the gap remained unchanged at 40 percentage points. Parity, maternal education, and travel time to health facility were the key drivers of inequality. Clusters of low utilization were displayed on spatial maps, alongside deprivation and travel time to health facility. Conclusion: Inequalities in the utilization of ANC, ID and PNC are significant and persistent. Interventions targeting maternal education and distance to health facilities can significantly reduce the gap.
KW - Female
KW - Pregnancy
KW - Humans
KW - Maternal Health Services
KW - Nepal
KW - Health Status Disparities
KW - Socioeconomic Factors
KW - Prenatal Care
UR - https://pubmed.ncbi.nl.nih.gov/37332772/
U2 - 10.3389/ijph.2023.1605457
DO - 10.3389/ijph.2023.1605457
M3 - Article
C2 - 37332772
SN - 1661-8556
VL - 68
JO - International Journal of Public Health
JF - International Journal of Public Health
M1 - 1605457
ER -