title: Spatial modelling of perinatal mortality in Mchinji, Malawi.
abstract: BACKGROUND
  Annual global estimates of perinatal mortality show Malawi among sub-Saharan Africa with the highest rates. Targeted interventions are required to reduce this mortality. This study aimed to quantify small-scale geographical variations in perinatal mortality, and estimate risk factors associated with perinatal mortality in Mchinji district.
  
  
  METHODS
  As part of the 2005-2010 randomised controlled trial conducted in Mchinji district, prospective data from the control arm of the trial was collected on perinatal mortality. A Structured Additive Regression model was applied to account for influence of both individual and contextual factors, and jointly accounting for nonlinear effects of continuous covariates, spatially structured variation, unstructured heterogeneity and fixed effects. Modelling and inference used a fully Bayesian approach.
  
  
  RESULTS
  Factors associated with reduced perinatal mortality were: previous pregnancy; early and consistent use of antenatal care; syphilis test; abdominal examination; pregnancy danger signs advice; skilled birth attendant; normal labour duration; gestation period of at least 9 months; and normal delivery. Perinatals whose mothers had blood test were associated with high probability of dying. Perinatals from mothers between 16 and 40 years had reduced prevalence of dying while those aged less than 16 years and greater than 40 years were associated with higher prevalence of dying. After accounting for all significant covariates, high perinatal mortality was observed in eastern part of the district whereas low perinatal mortality was observed in the western part.
  
  
  CONCLUSIONS
  Targeting health interventions to higher risk areas and ensuring universal coverage are promising approaches for promoting equity and reducing perinatal mortality.
authors.affiliation: Mathematical Sciences Department, Chancellor College, University of Malawi, P.O. Box 280, Zomba, Malawi; Save the Children, P.O. Box 30374, Lilongwe, Malawi. Electronic address: masfordbanda@gmail.com.
authors.forename: Masford
authors.initials: M
authors.lastname: Banda
authors.affiliation: Department of Statistics and Population Studies, University of Namibia, Windhoek, Namibia.
authors.forename: Lawrence
authors.initials: L
authors.lastname: Kazembe
authors.affiliation: Institute of Global Health, University College London, UK.
authors.forename: Sonia
authors.initials: S
authors.lastname: Lewycka
authors.affiliation: Institute of Global Health, University College London, UK.
authors.forename: Carina
authors.initials: C
authors.lastname: King
authors.affiliation: MaiMwana Project, Mchinji, Malawi.
authors.forename: Tambosi
authors.initials: T
authors.lastname: Phiri
authors.affiliation: Parent and Child Health Initiative, Lilongwe, Malawi.
authors.forename: Gibson
authors.initials: G
authors.lastname: Masache
authors.affiliation: Baylor College of Medicine, Children's Foundation, Lilongwe, Malawi.
authors.forename: Peter
authors.initials: P
authors.lastname: Kazembe
authors.affiliation: Ministry of Health, Lilongwe, Malawi.
authors.forename: Charles
authors.initials: C
authors.lastname: Mwasambo
mesh_terms: D000293:Adolescent; D000328:Adult; D001499:Bayes Theorem; D002648:Child; D005260:Female; D006801:Humans; D008295:Malawi / Q000453:epidemiology; D008875:Middle Aged; D015233:Models, Statistical; D054238:Perinatal Mortality; D011247:Pregnancy; D011446:Prospective Studies; D012307:Risk Factors; D062206:Spatial Analysis; D055815:Young Adult
keywords: Full bayesian; MCMC; Perinatal mortality and sub-Saharan Africa; STAR models