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Inequalities in anemia among Peruvian children aged 6–59 months: A decomposition analysis

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Objective: To quantify the inequalities of anemia in Peruvian children aged 6–59 months and uncover its contributing factors. Materials and methods: We conducted a cross-sectional study based on the secondary data analysis of the 2021 Peruvian Demographic and Health Survey (DHS). Our sample included...

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Detalles Bibliográficos
Autores: Al-kassab-Córdova, Ali, Mendez-Guerra, Carolina, Robles-Valcarcel, Pamela, Iberico-Bellomo, Luis, Alva, Kenedy, Herrera-Añazco, Percy, Benites-Zapata, Vicente A.
Formato: artículo
Fecha de Publicación:2023
Institución:Universidad Peruana de Ciencias Aplicadas
Repositorio:UPC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorioacademico.upc.edu.pe:10757/668379
Enlace del recurso:http://hdl.handle.net/10757/668379
Nivel de acceso:acceso abierto
Materia:anemia
children
demographic and health survey
healthcare inequalities
Peru
Peruvian children
Inequalities
Cross-sectional study
Peruvian Demographic and Health Survey (DHS)
Hemoglobin level
Erreygers Concentration Index (ECI)
Socio-economic inequality
Determinants
Public policies
Descripción
Sumario:Objective: To quantify the inequalities of anemia in Peruvian children aged 6–59 months and uncover its contributing factors. Materials and methods: We conducted a cross-sectional study based on the secondary data analysis of the 2021 Peruvian Demographic and Health Survey (DHS). Our sample included Peruvian children aged 6–59 months with complete data for the variables of interest. Anemia was defined as having a hemoglobin level of less than 11 g/dL, adjusted by altitude. Erreygers Concentration Index (ECI) and concentration curves were computed to estimate the socio-economic inequality in anemia among Peruvian children. Moreover, ECI was decomposed to figure out the contributing factors to the inequality of anemia and the residual variation. Results: Nationwide, the prevalence of anemia in Peruvian children was 29.47%. We found a pro-poor inequality regarding anemia at the national level (ECI = −0.1848). The determinants included in the model explained 81.85% of the overall socio-economic inequality in anemia. The largest contribution to inequality was from household- and community-related factors. Having a higher mother’s education level (26.26%) and being from the highlands (24.91%) were the major significant contributors to the overall health inequality. Conclusion: Almost one-third of Peruvian children have anemia. A pro-poor inequality of anemia in Peruvian children was found. Public policies ought to address the major contributing factors of anemia inequality.
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