Trends in inequality in the coverage of vitamin A supplementation among children 6–59 months of age over two decades in Ethiopia: Evidence from demographic and health surveys

• Published in: SAGE open medicine 2022, Vol.10, p.20503121221094688-20503121221094688
• Main Authors: Zegeye, Betregiorgis, Olorunsaiye, Comfort Z, Ahinkorah, Bright Opoku, Ameyaw, Edward Kwabena, Seidu, Abdul-Aziz, Budu, Eugene, Yaya, Sanni
• Format: Article
• Language: English
• Subjects: Health surveys; Original; Population; Vitamin A
• ISSN: 2050-3121; 2050-3121
• DOI: 10.1177/20503121221094688

Objectives: There is a dearth of evidence on inequalities in vitamin A supplementation in Ethiopia. The goal of this study was to assess the magnitude and overtime changes of inequalities in vitamin A supplementation among children aged 6–59 months in Ethiopia. Methods: We extracted data from four waves of the Ethiopia Demographic and Health Surveys (2000, 2005, 2011, and 2016). The analysis was carried out using the 2019 updated World Health Organization’s Health Equity Assessment Toolkit software that facilitates the use of stored data from World Health Organization’s Health Equity Monitor Database. We conducted analysis of inequality in vitamin A supplementation by five equity stratifiers: household economic status, educational status, place of residence, child’s sex, and subnational region. Four summary measures—population attributable fraction, ratio, difference, and population attributable risk—were assessed. We computed 95% uncertainty intervals for each point estimate to ascertain statistical significance of the observed vitamin A supplementation inequalities and overtime disparities. Results: The findings suggest marked absolute and relative pro-rich (population attributable fraction = 29.51, 95% uncertainty interval; 25.49–33.53, population attributable risk = 13.18, 95% uncertainty intervals; 11.38–14.98) and pro-urban (difference = 16.55, 95% uncertainty intervals; 11.23–21.87, population attributable fraction = 32.95, 95% uncertainty intervals; 32.12–33.78) inequalities. In addition, we found education-related (population attributable risk = 18.95, 95% uncertainty intervals; 18.22–19.67, ratio = 1.54, 95% uncertainty intervals; 1.37–1.71), and subnational regional (difference = 38.56, 95% uncertainty intervals; 29.57–47.54, ratio = 2.10, 95% uncertainty intervals; 1.66–2.54) inequalities that favored children from educated subgroups and those living in some regions such as Tigray. However, no sex-based inequalities were observed. While constant pattern was observed in subnational regional disparities, mixed but increasing patterns of socioeconomic and urban–rural inequalities were observed in the most recent surveys (2011–2016). Conclusion: In this study, we found extensive socioeconomic and geographic-based disparities that favored children from advantaged subgroups such as those whose mothers were educated, lived in the richest/richer households, resided in urban areas, and from regions like Tigray. Government policies and programs should pr