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Durham University

Research & business

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Publication details for Prof Steve Lindsay

Tusting, L.S., Rek, J.C., Arinaitwe, E., Staedke, S.G., Kamya, M.R., Cano, J., Bottomley, C., Johnston, D., Dorsey, G., Lindsay, S.W. & Lines, J.D. (2016). Why is malaria associated with poverty? Findings from a cohort study in rural Uganda. Infectious Diseases of Poverty 5(1): 78.

Author(s) from Durham

Abstract

Background
Malaria control and sustainable development are linked, but implementation of ‘multisectoral’ intervention is restricted by a limited understanding of the causal pathways between poverty and malaria. We investigated the relationships between socioeconomic position (SEP), potential determinants of SEP, and malaria in Nagongera, rural Uganda.

Methods
Socioeconomic information was collected for 318 children aged six months to 10 years living in 100 households, who were followed for up to 36 months. Mosquito density was recorded using monthly light trap collections. Parasite prevalence was measured routinely every three months and malaria incidence determined by passive case detection. First, we evaluated the association between success in smallholder agriculture (the primary livelihood source) and SEP. Second, we explored socioeconomic risk factors for human biting rate (HBR), parasite prevalence and incidence of clinical malaria, and spatial clustering of socioeconomic variables. Third, we investigated the role of selected factors in mediating the association between SEP and malaria.

Results
Relative agricultural success was associated with higher SEP. In turn, high SEP was associated with lower HBR (highest versus lowest wealth index tertile: Incidence Rate Ratio 0.71, 95 % confidence intervals (CI) 0.54–0.93, P = 0.01) and lower odds of malaria infection in children (highest versus lowest wealth index tertile: adjusted Odds Ratio 0.52, 95 % CI 0.35–0.78, P = 0.001), but SEP was not associated with clinical malaria incidence. Mediation analysis suggested that part of the total effect of SEP on malaria infection risk was explained by house type (24.9 %, 95 % CI 15.8–58.6 %) and food security (18.6 %, 95 % CI 11.6–48.3 %); however, the assumptions of the mediation analysis may not have been fully met.

Conclusion
Housing improvements and agricultural development interventions to reduce poverty merit further investigation as multisectoral interventions against malaria. Further interdisplinary research is needed to understand fully the complex pathways between poverty and malaria and to develop strategies for sustainable malaria control.