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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Survived infancy but still vulnerable: spatial-temporal trends and risk factors for child mortality in rural South Africa (Agincourt), 1992-2007</title><author><name sortKey="Sartorius, Benn" sort="Sartorius, Benn" uniqKey="Sartorius B" first="Benn" last="Sartorius">Benn Sartorius</name><affiliation><nlm:aff id="A1">MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa</nlm:aff></affiliation></author><author><name sortKey="Kahn, Kathleen" sort="Kahn, Kathleen" uniqKey="Kahn K" first="Kathleen" last="Kahn">Kathleen Kahn</name><affiliation><nlm:aff id="A1">MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre for Global Health Research, Epidemiology and Global Health, University of Umeå, Umeå, Sweden</nlm:aff></affiliation><affiliation><nlm:aff id="A3">INDEPTH Network, Accra, Ghana</nlm:aff></affiliation></author><author><name sortKey="Collinson, Mark A" sort="Collinson, Mark A" uniqKey="Collinson M" first="Mark A." last="Collinson">Mark A. Collinson</name><affiliation><nlm:aff id="A1">MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre for Global Health Research, Epidemiology and Global Health, University of Umeå, Umeå, Sweden</nlm:aff></affiliation><affiliation><nlm:aff id="A3">INDEPTH Network, Accra, Ghana</nlm:aff></affiliation></author><author><name sortKey="Vounatsou, Penelope" sort="Vounatsou, Penelope" uniqKey="Vounatsou P" first="Penelope" last="Vounatsou">Penelope Vounatsou</name><affiliation><nlm:aff id="A4">Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, CH-4002 Basel, Switzerland</nlm:aff></affiliation><affiliation><nlm:aff id="A5">University of Basel, CH-4003 Basel, Switzerland</nlm:aff></affiliation></author><author><name sortKey="Tollman, Stephen M" sort="Tollman, Stephen M" uniqKey="Tollman S" first="Stephen M." last="Tollman">Stephen M. Tollman</name><affiliation><nlm:aff id="A1">MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre for Global Health Research, Epidemiology and Global Health, University of Umeå, Umeå, Sweden</nlm:aff></affiliation><affiliation><nlm:aff id="A3">INDEPTH Network, Accra, Ghana</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">21590679</idno><idno type="pmc">3523210</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3523210</idno><idno type="RBID">PMC:3523210</idno><date when="2011">2011</date><idno type="wicri:Area/Pmc/Corpus">001A51</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">001A51</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Survived infancy but still vulnerable: spatial-temporal trends and risk factors for child mortality in rural South Africa (Agincourt), 1992-2007</title><author><name sortKey="Sartorius, Benn" sort="Sartorius, Benn" uniqKey="Sartorius B" first="Benn" last="Sartorius">Benn Sartorius</name><affiliation><nlm:aff id="A1">MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa</nlm:aff></affiliation></author><author><name sortKey="Kahn, Kathleen" sort="Kahn, Kathleen" uniqKey="Kahn K" first="Kathleen" last="Kahn">Kathleen Kahn</name><affiliation><nlm:aff id="A1">MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre for Global Health Research, Epidemiology and Global Health, University of Umeå, Umeå, Sweden</nlm:aff></affiliation><affiliation><nlm:aff id="A3">INDEPTH Network, Accra, Ghana</nlm:aff></affiliation></author><author><name sortKey="Collinson, Mark A" sort="Collinson, Mark A" uniqKey="Collinson M" first="Mark A." last="Collinson">Mark A. Collinson</name><affiliation><nlm:aff id="A1">MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre for Global Health Research, Epidemiology and Global Health, University of Umeå, Umeå, Sweden</nlm:aff></affiliation><affiliation><nlm:aff id="A3">INDEPTH Network, Accra, Ghana</nlm:aff></affiliation></author><author><name sortKey="Vounatsou, Penelope" sort="Vounatsou, Penelope" uniqKey="Vounatsou P" first="Penelope" last="Vounatsou">Penelope Vounatsou</name><affiliation><nlm:aff id="A4">Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, CH-4002 Basel, Switzerland</nlm:aff></affiliation><affiliation><nlm:aff id="A5">University of Basel, CH-4003 Basel, Switzerland</nlm:aff></affiliation></author><author><name sortKey="Tollman, Stephen M" sort="Tollman, Stephen M" uniqKey="Tollman S" first="Stephen M." last="Tollman">Stephen M. Tollman</name><affiliation><nlm:aff id="A1">MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre for Global Health Research, Epidemiology and Global Health, University of Umeå, Umeå, Sweden</nlm:aff></affiliation><affiliation><nlm:aff id="A3">INDEPTH Network, Accra, Ghana</nlm:aff></affiliation></author></analytic><series><title level="j">Geospatial health</title><idno type="ISSN">1827-1987</idno><idno type="eISSN">1970-7096</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p id="P1">Targeting of health interventions to poor children at highest risk of mortality are promising approaches for promoting equity. Methods have emerged to accurately quantify excess risk and identify space-time disparities. This provides useful and detailed information for guiding policy. A spatial-temporal analysis was performed to identify risk factors associated with child (1-4 years) mortality in rural South Africa (the Agincourt sub-district), to assess temporal changes in child mortality patterns within the study site between 1992 and 2007, and to produce all-cause and cause-specific mortality maps to identify high risk areas. Demographic, maternal, paternal and fertility-related factors, household mortality experience, distance to health care facility and socio-economic status were among the examined risk factors. The analysis was carried out by fitting a Bayesian discrete time Bernoulli survival geostatistical model using Markov chain Monte Carlo simulation. Bayesian kriging was used to produce maps of all-cause and cause-specific mortality risk. Significant temporal increase in child mortality was observed due to the HIV epidemic. A distinct spatial risk pattern was observed with higher risk areas being concentrated in poorer settlements on the eastern part of the study area, largely inhabited by former Mozambican refugees. The major risk factors for childhood mortality, following multivariate adjustment, were mother’s death (especially when due to HIV and tuberculosis), greater number of children under 5 years living in the same household and winter season. This study demonstrates the use of Bayesian geostatistical models for accurately quantifying risk factors and producing maps of child mortality risk in a health and demographic surveillance system. According to the space-time analysis, the southeast and upper central regions of the site appear to have the highest mortality risk. The results inform policies to address health inequalities in the Agincourt sub-district and to improve access to health services. Targeted efforts to prevent vertical transmission of HIV in specific settings need to be undertaken as well as ensuring the survival of the mother and father in childhood.</p></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<pmc-dir>properties manuscript</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-journal-id">101302943</journal-id><journal-id journal-id-type="pubmed-jr-id">33356</journal-id><journal-id journal-id-type="nlm-ta">Geospat Health</journal-id><journal-id journal-id-type="iso-abbrev">Geospat Health</journal-id><journal-title-group><journal-title>Geospatial health</journal-title></journal-title-group><issn pub-type="ppub">1827-1987</issn><issn pub-type="epub">1970-7096</issn></journal-meta><article-meta><article-id pub-id-type="pmid">21590679</article-id><article-id pub-id-type="pmc">3523210</article-id><article-id pub-id-type="manuscript">EMS36790</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Survived infancy but still vulnerable: spatial-temporal trends and risk factors for child mortality in rural South Africa (Agincourt), 1992-2007</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Sartorius</surname><given-names>Benn</given-names></name><xref ref-type="aff" rid="A1">1</xref></contrib><contrib contrib-type="author"><name><surname>Kahn</surname><given-names>Kathleen</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref><xref ref-type="aff" rid="A3">3</xref></contrib><contrib contrib-type="author"><name><surname>Collinson</surname><given-names>Mark A.</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref><xref ref-type="aff" rid="A3">3</xref></contrib><contrib contrib-type="author"><name><surname>Vounatsou</surname><given-names>Penelope</given-names></name><xref ref-type="aff" rid="A4">4</xref><xref ref-type="aff" rid="A5">5</xref></contrib><contrib contrib-type="author"><name><surname>Tollman</surname><given-names>Stephen M.</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref><xref ref-type="aff" rid="A3">3</xref></contrib></contrib-group><aff id="A1"><label>1</label>MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa</aff><aff id="A2"><label>2</label>Centre for Global Health Research, Epidemiology and Global Health, University of Umeå, Umeå, Sweden</aff><aff id="A3"><label>3</label>INDEPTH Network, Accra, Ghana</aff><aff id="A4"><label>4</label>Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, CH-4002 Basel, Switzerland</aff><aff id="A5"><label>5</label>University of Basel, CH-4003 Basel, Switzerland</aff><author-notes><corresp id="CR1">Corresponding author: Benn Sartorius MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt) School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa Tel: +27 11 717-2627; Fax: +27 11 717-2084 <email>benn.sartorius@wits.ac.za</email></corresp></author-notes><pub-date pub-type="nihms-submitted"><day>13</day><month>10</month><year>2011</year></pub-date><pub-date pub-type="ppub"><month>5</month><year>2011</year></pub-date><pub-date pub-type="pmc-release"><day>16</day><month>12</month><year>2012</year></pub-date><volume>5</volume><issue>2</issue><fpage>285</fpage><lpage>295</lpage><abstract><p id="P1">Targeting of health interventions to poor children at highest risk of mortality are promising approaches for promoting equity. Methods have emerged to accurately quantify excess risk and identify space-time disparities. This provides useful and detailed information for guiding policy. A spatial-temporal analysis was performed to identify risk factors associated with child (1-4 years) mortality in rural South Africa (the Agincourt sub-district), to assess temporal changes in child mortality patterns within the study site between 1992 and 2007, and to produce all-cause and cause-specific mortality maps to identify high risk areas. Demographic, maternal, paternal and fertility-related factors, household mortality experience, distance to health care facility and socio-economic status were among the examined risk factors. The analysis was carried out by fitting a Bayesian discrete time Bernoulli survival geostatistical model using Markov chain Monte Carlo simulation. Bayesian kriging was used to produce maps of all-cause and cause-specific mortality risk. Significant temporal increase in child mortality was observed due to the HIV epidemic. A distinct spatial risk pattern was observed with higher risk areas being concentrated in poorer settlements on the eastern part of the study area, largely inhabited by former Mozambican refugees. The major risk factors for childhood mortality, following multivariate adjustment, were mother’s death (especially when due to HIV and tuberculosis), greater number of children under 5 years living in the same household and winter season. This study demonstrates the use of Bayesian geostatistical models for accurately quantifying risk factors and producing maps of child mortality risk in a health and demographic surveillance system. According to the space-time analysis, the southeast and upper central regions of the site appear to have the highest mortality risk. The results inform policies to address health inequalities in the Agincourt sub-district and to improve access to health services. Targeted efforts to prevent vertical transmission of HIV in specific settings need to be undertaken as well as ensuring the survival of the mother and father in childhood.</p></abstract><kwd-group><kwd>Bayesian inference</kwd><kwd>autoregressive</kwd><kwd>geostatistical data</kwd><kwd>child mortality</kwd><kwd>kriging</kwd><kwd>survival</kwd><kwd>Bernoulli or logistic</kwd><kwd>spatio-temporal model</kwd><kwd>health and demographic surveillance</kwd><kwd>mortality</kwd><kwd>South Africa</kwd></kwd-group><funding-group><award-group><funding-source country="United Kingdom">Wellcome Trust : </funding-source><award-id>085477 || WT</award-id></award-group><award-group><funding-source country="United Kingdom">Wellcome Trust : </funding-source><award-id>069683 || WT</award-id></award-group><award-group><funding-source country="United Kingdom">Wellcome Trust : </funding-source><award-id>058893/Z/99/A || WT</award-id></award-group></funding-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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