Socio-Demographic Determinants of Anaemia in Children in Uganda: A Multilevel Analysis

Kandala (Shadrack) Ngianga ()
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Kandala (Shadrack) Ngianga: University of Southampton, Division of Social Statistics

Chapter Chapter 9 in Advanced Techniques for Modelling Maternal and Child Health in Africa, 2014, pp 169-182 from Springer

Abstract: Abstract Background: Anaemia is a worldwide public health problem. Recently it affected two billion people (WHO. (2008). Worldwide prevalence of anaemia 1993–2005, WHO Global database. Geneva: World Health Organisation) which accounts for about 25 % of the world population. It appears to be not only a major cause of pre- and post-partum morbidities and mortalities in developing countries but also it affects the physical and cognition development of children and its impact in increasing children’s risk of getting other infections is of major concern. Although the immediate biological causes of anaemia are well documented, socioeconomic factors associated with anaemia and the fact that anaemia differs markedly between individuals, within households and communities have rarely been explored. Aims: To investigate background characteristics of anaemia (socioeconomic and demographic related factors) in a selected sample of children in Uganda in 2006 after accounting for some proximate determinants and use multilevel logistic regression models to account and quantify variability due to individual (child), household and community (cluster) levels. Methods: this is a retrospective cross-sectional study of 2,110 children aged between 5 and 54 months from Uganda. The 2006 Uganda Demographic Health survey (UDHS 2007) was utilised for this analysis–more detail on data and sampling design and methodology can be found in ( www.measuredhs.com ). Potential risk factors of anaemia which were previously reported were studied and contextual variables were also included. Bivariate and multivariate (multilevel logistic regression) analysis were carried out. In the bivariate analysis, Chi-square test was used to test the significance of the selected potential risk factors and the Wald test was used in the multivariate analysis to test the joint significance of categorical factors. For both tests a p-value of

Keywords: Wealth Quintile; Green Leafy Vegetable; Simple Logistic Regression; Anaemia Intervention; Multilevel Logistic Regression Model (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-94-007-6778-2_9

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