Quantifying Spatial Disparities in Neonatal Mortality Using a Structured Additive Regression Model
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Mendeley | Further Information

{"title"=>"Quantifying spatial disparities in neonatal mortality using a structured additive regression model", "type"=>"journal", "authors"=>[{"first_name"=>"Lawrence N.", "last_name"=>"Kazembe", "scopus_author_id"=>"14830318700"}, {"first_name"=>"Placid M G", "last_name"=>"Mpeketula", "scopus_author_id"=>"36239044500"}], "year"=>2010, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"20567519", "doi"=>"10.1371/journal.pone.0011180", "sgr"=>"77955299203", "scopus"=>"2-s2.0-77955299203", "issn"=>"19326203", "pui"=>"359301708"}, "id"=>"995565ea-b50d-36d4-b1a8-099efcf82f9b", "abstract"=>"BACKGROUND: Neonatal mortality contributes a large proportion towards early childhood mortality in developing countries, with considerable geographical variation at small areas within countries.\\n\\nMETHODS: A 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.\\n\\nRESULTS: Findings indicate that both fixed and spatial effects are associated with neonatal mortality.\\n\\nCONCLUSIONS: Our 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.", "link"=>"http://www.mendeley.com/research/quantifying-spatial-disparities-neonatal-mortality-using-structured-additive-regression-model-1", "reader_count"=>27, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>8, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>5, "Student > Master"=>4, "Other"=>1, "Student > Bachelor"=>1, "Professor"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>8, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>5, "Student > Master"=>4, "Other"=>1, "Student > Bachelor"=>1, "Professor"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Environmental Science"=>1, "Nursing and Health Professions"=>1, "Medicine and Dentistry"=>8, "Business, Management and Accounting"=>1, "Veterinary Science and Veterinary Medicine"=>1, "Psychology"=>2, "Social Sciences"=>6, "Computer Science"=>2, "Earth and Planetary Sciences"=>2, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>8}, "Social Sciences"=>{"Social Sciences"=>6}, "Psychology"=>{"Psychology"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>2}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Computer Science"=>{"Computer Science"=>2}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Belgium"=>1, "Kenya"=>2}, "group_count"=>7}

Scopus | Further Information

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  • {"files"=>["https://ndownloader.figshare.com/files/845301"], "description"=>"<p>Neonatal mortality data: Locations where survey data was collected based on 2000 Malawi Demographic and Health Survey.</p>", "links"=>[], "tags"=>["pediatrics and child health", "mathematics/statistics", "public health and epidemiology/epidemiology", "public health and epidemiology/global health"], "article_id"=>515758, "categories"=>["Mathematics", "Cancer", "Neuroscience", "Medicine"], "users"=>["Lawrence N. Kazembe", "Placid M. G. Mpeketula"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0011180.g001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Survey_data_location_/515758", "title"=>"Survey data location.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 01:00:45"}
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Relative Metric

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