Benn Sartorius|Kurt Sartorius|Tobias Chirwa|Sharon Fonn
Infant mortality in South Africa - distribution, associations and policy implications, 2007: an ecological spatial analysis
Faculty of Public Health|University of the Witwatersrand|Institute of Commerce and Law|University of the Witwatersrand|Faculty of Public Health|University of the Witwatersrand|Faculty of Public Health|University of the Witwatersrand
many subsaharan countries confronted persistently high levels infant mortality impact range biological social determinants particular infant mortality increased subsaharan africa recent decades due hivaids epidemic geographic distribution health problems relationship potential risk factors invaluable cost effective intervention planning objective paper determine map spatial nature infant mortality south africa sub district level order inform policy intervention particular paper identifies maps high risk clusters infant mortality well examines impact range determinants infant mortality bayesian approach used quantify spatial risk infant mortality well significant associations given spatial correlation neighbouring areas infant mortality range determinants attributable determinants subdistrict calculated based combination prevalence model risk factor coefficient estimates integrated small area approach adapted applied high burden settings assist intervention planning targeting infant mortality remains high south africa seemingly little reduction since previous estimates early 2000s results showed marked geographical differences infant mortality risk provinces well within provinces well significantly higher risk specific subdistricts provinces number determinants found significant adverse influence infant mortality subdistrict level following multivariable adjustment increasing maternal mortality antenatal hiv prevalence previous sibling mortality male infant gender remained significantly associated increased infant mortality risk antenatal hiv seroprevalence previous sibling mortality maternal mortality found attributable respectively study demonstrates usefulness advanced spatial analysis quantify excess infant mortality risk lowest administrative unit well use bayesian modelling quantify determinant significance given spatial correlation novel integration determinant prevalence subdistrict coefficient estimates estimate attributable fractions elucidates high impact factors particular areas considerable potential applied locations usefulness paper therefore suggests intervene geographically also specific interventions policy makers prioritize order reduce infant mortality burden specific administration areas