title: Estimating areas of common risk in low birth weight and infant mortality in Namibia: a joint spatial analysis at sub-regional level.
abstract: There is lots of literature documenting a positive association between low birth weight (LBW) and infant mortality (IM), however, little is known how the risk of LBW and IM are geographically co-distributed. We fitted joint spatial models of LBW and IM, and used data from Namibia, to examine their geographical variability. We used a Bayesian approach to measure and rank areas according to specific and shared risk of LBW and IM. Our findings show some degree of similarities in the spatial pattern of LBW and IM, with high risk in the central and north-eastern parts of the country. Results suggest a need for comprehensive programming of maternal and newborn interventions that reach areas of spatially concentrated risk of LBW and IM. It further presents an opportunity for generating hypotheses for further research aimed at improving child health, especially in higher risk constituencies thus identified.
authors.affiliation: Department of Statistics and Population Studies, University of Namibia, Private Bag 13301 Windhoek, 340 Mandume Ndemufayo Avenue, Pionerspark, Namibia. Electronic address: lkazembe@yahoo.com.
authors.forename: Lawrence N
authors.initials: LN
authors.lastname: Kazembe
authors.affiliation: Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK.
authors.forename: N-B
authors.initials: NB
authors.lastname: Kandala
mesh_terms: D001499:Bayes Theorem; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D007230:Infant, Low Birth Weight; D007231:Infant, Newborn; D008297:Male; D008423:Maternal Age; D009276:Namibia / Q000453:epidemiology; D010298:Parity; D011247:Pregnancy; D012307:Risk Factors; D012680:Sensitivity and Specificity; D062206:Spatial Analysis
keywords: Bayesian inference; Infant mortality; Joint spatial analysis; Low birth weight; Namibia; Shared latent component model