Bayesian random effects modelling with application to childhood anaemia in Malawi

BMC Public Health

Research Article

Alfred Ngwira¹  Lawrence N Kazembe² 

[1] Department of Mathematical Sciences, University of Malawi, Chancellor College, Zomba, Malawi;Department of Statistics and Population Studies, University of Namibia, Windhoek, Namibia;

关键词: Binary logistic model;    Structured additive;    Geo-additive;    P-splines;   

DOI  :  10.1186/s12889-015-1494-y

 received in 2013-12-03, accepted in 2015-01-07,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundEpidemiological studies in Malawi on child anaemia have neglected the community spatial effect to childhood anaemia. Neglecting the community spatial effect in the model ignores the influence of unobserved or unmeasured contextual variables, and at the same time the resultant model may under estimate model parameter standard errors which can result in erroneous significance of covariates. We aimed at investigating risk factors of childhood anaemia in Malawi with focus on geographical spatial effect.MethodsWe adopted a Bayesian random effect model for child anaemia with district as spatial effect using the 2010 Malawi demographic healthy survey data. We fitted the binary logistic model for the two categories outcome (anaemia (Hb < 11), and no anaemia (Hb ≥ 11)). Continuous covariates were modelled by the penalized splines and spatial effects were smoothed by the two dimensional spline.ResultsResidual spatial patterns reveal Nsanje, Chikhwawa, Salima, Nkhota-kota, Mangochi and Machinga increasing the risk of childhood anaemia. Karonga, Chitipa, Rumphi, Mzimba, Ntchisi, and Chiradzulu reduce the risk of childhood anaemia. Known determinants such as maternal anaemia, child stunting, and child fever, have a positive effect on child anaemia. Furthermore childhood anaemia decreases with child age. It also decreases with wealth index. There is a U relationship between child anaemia and mother age.ConclusionStrategies in childhood anaemia control should be tailored to local conditions, taking into account the specific etiology and prevalence of anaemia.

【 授权许可】

CC BY   
© Ngwira and Kazembe; licensee BioMed Central. 2015

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