ArticlePloS one2010
Quantifying spatial disparities in neonatal mortality using a structured additive regression model.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- How applicable is geospatial analysis in maternal and neonatal health in sub-Saharan Africa? A systematic review.Journal of global health · 2022Pooled it
- Determinants of Neonatal, Infant and Child Mortalities in Iran: A Systematic Review.Iranian journal of public health · 2024Review
- Impact of ignoring sampling design in the prediction of binary health outcomes through logistic regression: evidence from Malawi demographic and health survey under-five mortality data; 2000-2016.BMC public health · 2023Article
- A novel outlier statistic in multivariate survival models and its application to identify unusual under-five mortality sub-districts in Malawi.Journal of applied statistics · 2023Article
- Spatiotemporal trends in neonatal, infant, and child mortality (1990-2019) based on Bayesian spatiotemporal modeling.Frontiers in public health · 2023Article
- Under-5 Mortality and Its Associated Factors in Northern Nigeria: Evidence from 22,455 Singleton Live Births (2013-2018).International journal of environmental research and public health · 2021Article
- Factors associated with under-5 mortality in three disadvantaged East African districts.International health · 2020Article
- A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa.International journal of environmental research and public health · 2020Article
- Transnational wealth-related health inequality measurement.SSM - population health · 2018Article
- Fine resolution mapping of population age-structures for health and development applications.Journal of the Royal Society, Interface · 2015Article
- Article
- Structured additive regression models with spatial correlation to estimate under-five mortality risk factors in Ethiopia.BMC public health · 2015Article
- Child mortality in the Democratic Republic of Congo: cross-sectional evidence of the effect of geographic location and prolonged conflict from a national household survey.BMC public health · 2014Article
- Using structured additive regression models to estimate risk factors of malaria: analysis of 2010 Malawi malaria indicator survey data.PloS one · 2014Article
- Error and bias in under-5 mortality estimates derived from birth histories with small sample sizes.Population health metrics · 2013Article
- Efficient mapping and geographic disparities in breast cancer mortality at the county-level by race and age in the U.S.Spatial and spatio-temporal epidemiology · 2013Article
- Ecological analysis of social risk factors for Rotavirus infections in Berlin, Germany, 2007-2009.International journal of health geographics · 2012Article
- Estimated effects of Asian dust storms on spatiotemporal distributions of clinic visits for respiratory diseases in Taipei children (Taiwan).Environmental health perspectives · 2012Article
- High neonatal mortality rates in rural India: what options to explore?ISRN pediatrics · 2012Article
- Childhood mortality in sub-Saharan Africa: cross-sectional insight into small-scale geographical inequalities from Census data.BMJ open · 2012Article
Corrections and comments
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2 authors.
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Abstract
backgroundNeonatal mortality contributes a large proportion towards early childhood mortality in developing countries, with considerable geographical variation at small areas within countries.
methodsA geo-additive logistic regression model is proposed for quantifying small-scale geographical variation in neonatal mortality, and to estimate risk factors of neonatal mortality. Random effects are introduced to capture spatial correlation and heterogeneity. The spatial correlation can be modelled using the Markov random fields (MRF) when data is aggregated, while the two dimensional P-splines apply when exact locations are available, whereas the unstructured spatial effects are assigned an independent Gaussian prior. Socio-economic and bio-demographic factors which may affect the risk of neonatal mortality are simultaneously estimated as fixed effects and as nonlinear effects for continuous covariates. The smooth effects of continuous covariates are modelled by second-order random walk priors. Modelling and inference use the empirical Bayesian approach via penalized likelihood technique. The methodology is applied to analyse the likelihood of neonatal deaths, using data from the 2000 Malawi demographic and health survey. The spatial effects are quantified through MRF and two dimensional P-splines priors.
resultsFindings indicate that both fixed and spatial effects are associated with neonatal mortality.
conclusionsOur study, therefore, suggests that the challenge to reduce neonatal mortality goes beyond addressing individual factors, but also require to understanding unmeasured covariates for potential effective interventions.
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