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The contribution of spatial analysis to understanding HIV/TB mortality in children: a structural equation modelling approach.

Identifieur interne : 000378 ( PubMed/Checkpoint ); précédent : 000377; suivant : 000379

The contribution of spatial analysis to understanding HIV/TB mortality in children: a structural equation modelling approach.

Auteurs : Eustasius Musenge [Afrique du Sud] ; Penelope Vounatsou [Suisse] ; Mark Collinson [Afrique du Sud] ; Stephen Tollman [Afrique du Sud] ; Kathleen Kahn [Afrique du Sud]

Source :

RBID : pubmed:28140966

Abstract

South Africa accounts for more than a sixth of the global population of people infected with HIV and TB, ranking her highest in HIV/TB co-infection worldwide. Remote areas often bear the greatest burden of morbidity and mortality, yet there are spatial differences within rural settings.

DOI: 10.3402/gha.v6i0.19266
PubMed: 28140966


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<country xml:lang="fr">Afrique du Sud</country>
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<nlm:affiliation>c Swiss Tropical and Public Health Institute , University of Basel Basel , Switzerland.</nlm:affiliation>
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<name sortKey="Kahn, Kathleen" sort="Kahn, Kathleen" uniqKey="Kahn K" first="Kathleen" last="Kahn">Kathleen Kahn</name>
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<div type="abstract" xml:lang="en">South Africa accounts for more than a sixth of the global population of people infected with HIV and TB, ranking her highest in HIV/TB co-infection worldwide. Remote areas often bear the greatest burden of morbidity and mortality, yet there are spatial differences within rural settings.</div>
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<Title>Global health action</Title>
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<ArticleTitle>The contribution of spatial analysis to understanding HIV/TB mortality in children: a structural equation modelling approach.</ArticleTitle>
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<AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">South Africa accounts for more than a sixth of the global population of people infected with HIV and TB, ranking her highest in HIV/TB co-infection worldwide. Remote areas often bear the greatest burden of morbidity and mortality, yet there are spatial differences within rural settings.</AbstractText>
<AbstractText Label="OBJECTIVES" NlmCategory="OBJECTIVE">The primary aim was to investigate HIV/TB mortality determinants and their spatial distribution in the rural Agincourt sub-district for children aged 1-5 years in 2004. Our secondary aim was to model how the associated factors were interrelated as either underlying or proximate factors of child mortality using pathway analysis based on a Mosley-Chen conceptual framework.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">We conducted a secondary data analysis based on cross-sectional data collected in 2004 from the Agincourt sub-district in rural northeast South Africa. Child HIV/TB death was the outcome measure derived from physician assessed verbal autopsy. Modelling used multiple logit regression models with and without spatial household random effects. Structural equation models were used in modelling the complex relationships between multiple exposures and the outcome (child HIV/TB mortality) as relayed on a conceptual framework.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">Fifty-four of 6,692 children aged 1-5 years died of HIV/TB, from a total of 5,084 households. Maternal death had the greatest effect on child HIV/TB mortality (adjusted odds ratio=4.00; 95% confidence interval=1.01-15.80). A protective effect was found in households with better socio-economic status and when the child was older. Spatial models disclosed that the areas which experienced the greatest child HIV/TB mortality were those without any health facility.</AbstractText>
<AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">Low socio-economic status and maternal deaths impacted indirectly and directly on child mortality, respectively. These factors are major concerns locally and should be used in formulating interventions to reduce child mortality. Spatial prediction maps can guide policy makers to target interventions where they are most needed. Appendices available online under Reading Tools.</AbstractText>
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<Affiliation>a MRC/Wits Rural Public Health & Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences , University of the Witwatersrand , Johannesburg , South Africa.</Affiliation>
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<Affiliation>b Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences , University of the Witwatersrand , Johannesburg , South Africa.</Affiliation>
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<AffiliationInfo>
<Affiliation>d Centre for Global Health Research , Umeå University , Umeå , Sweden.</Affiliation>
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<Affiliation>e INDEPTH Network , Accra , Ghana.</Affiliation>
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<Affiliation>d Centre for Global Health Research , Umeå University , Umeå , Sweden.</Affiliation>
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<Affiliation>e INDEPTH Network , Accra , Ghana.</Affiliation>
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<AffiliationInfo>
<Affiliation>d Centre for Global Health Research , Umeå University , Umeå , Sweden.</Affiliation>
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<Affiliation>e INDEPTH Network , Accra , Ghana.</Affiliation>
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<Keyword MajorTopicYN="N">HIV/TB</Keyword>
<Keyword MajorTopicYN="N">South Africa</Keyword>
<Keyword MajorTopicYN="N">child mortality</Keyword>
<Keyword MajorTopicYN="N">conceptual framework</Keyword>
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