Determinants and spatial factors of anemia in women of reproductive age in Democratic Republic of Congo (drc): a Bayesian multilevel ordinal logistic regression model approach.

Autor: Soda MA; Section de Sciences Infirmières Institut Supérieur des Techniques Médicales de Kisangani, Kisangani, Democratic Republic of the Congo. martinsoda2000@gmail.com.; Institut Supérieur Des Techniques Médicales de Kinshasa, Kinshasa, Democratic Republic of the Congo. martinsoda2000@gmail.com.; Division of Epidemiology and Biostatistics, School of Public Health, University of Witwatersrand, Witwatersrand, South Africa. martinsoda2000@gmail.com., Hamuli EK; Institut Supérieur Des Techniques Médicales de Kinshasa, Kinshasa, Democratic Republic of the Congo., Batina SA; Département de Médecine Interne, Université de Kisangani, Kisangani, Democratic Republic of the Congo., Kandala NB; Institut Supérieur Des Techniques Médicales de Kinshasa, Kinshasa, Democratic Republic of the Congo.; Department of Epidemiology and Biostatistics, Western University, London, ON, Canada.
Jazyk: angličtina
Zdroj: BMC public health [BMC Public Health] 2024 Jan 17; Vol. 24 (1), pp. 202. Date of Electronic Publication: 2024 Jan 17.
DOI: 10.1186/s12889-023-17554-y
Abstrakt: Background: As a global public health problem, anemia affects more than 400 million women of reproductive age worldwide, mostly in Africa and India. In the DRC, the prevalence of anemia has decreased slightly from 52.9% in 2007, to 46.4% in 2012 and 42.4% in 2019. However, there is considerable regional variation in its distribution. The aim of this study is to determine the factors contributing to anemia in women of reproductive age and to explore its spatial distribution in the DRC.
Methods: Based on the Bayesian Multilevel Spatial Ordinal Logistic Regression Model, we used the 2013 Democratic Republic of Congo Demographic and Health Survey (DHS-DRC II) data to investigate individual and environmental characteristics contributing to the development of anemia in women of reproductive age and the mapping of anemia in terms of residual spatial effects.
Results: Age, pregnancy status, body mass index, education level, current breastfeeding, current marital status, contraceptive and insecticide-treated net use, source of drinking water supply and toilet/latrine use including the province of residence were the factors contributing to anemia in women of reproductive age in DRC. With Global Moran's I = -0.00279, p-value ≥ 0.05, the spatial distribution of anemia in women of reproductive age in DRC results from random spatial processes. Thus, the observed spatial pattern is completely random.
Conclusion: The Bayesian Multilevel Spatial Ordinal Logistic Regression statistical model is able to adjust for risk and spatial factors of anemia in women of reproductive age in DRC highlighting the combined role of individual and environmental factors in the development of anemia in DRC.
(© 2024. The Author(s).)
Databáze: MEDLINE
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