The contribution of spatial analysis to understanding HIV/TB mortality in children

A structural equation modelling approach

Dados Bibliográficos

ID19529691
AutoresEustasius Musenge (0000-0002-3382-2372, University of the Witwatersrand, autor correspondente), Penelope Vounatsou (0000-0002-4904-5352, Swiss Tropical and Public Health Institute), Mark Collinson (0000-0002-8205-7099, University of the Witwatersrand), Stephen Tollman (0000-0003-0744-7588, Indepth Network), Kathleen Kahn (0000-0003-3339-3931, Umeå University)
Ano2013
Volume6
Fascículo1
Páginas19266
Data de publicação2013-12-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoGlobal Health Action (JOURNAL)
Identificadores do periódicoISSN: 1654-9716 • E-ISSN: 1654-9880
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.3402/gha.v6i0.19266
PMID23364095
OpenAlexW2103185881
IdiomaEN
Citações recebidas7
Referências citadas20

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. OBJECTIVES: 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. 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. 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. CONCLUSION: 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

Cause of death · Child mortality · Confidence interval · Cross-sectional study · Disease · Environmental health · Logistic regression · Odds · Odds ratio · Pathology · Population · Rural area · Statistics · Structural equation modeling · Verbal autopsy · Demography · Global Maternal and Child Health · HIV/AIDS Impact and Responses · HIV/AIDS Research and Interventions · Medicine · Pediatrics