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Fig. 1 | Infectious Diseases of Poverty

Fig. 1

From: Why is malaria associated with poverty? Findings from a cohort study in rural Uganda

Fig. 1

Conceptual framework for the relationship between relative agricultural success, socioeconomic position (SEP) and malaria in Nagongera, Uganda. In sub-Saharan Africa, the odds of malaria infection are on average halved in children with the highest socioeconomic position (SEP) within a community, compared to children with the lowest SEP [3]. Household SEP may be approximated using a wealth index. Wealthier children are hypothesised to have a lower risk of malaria due, among other factors, to: (1) greater disposable income, that makes prophylaxis, treatment and transport to clinics more affordable and therefore improves access to health care [9], (2) greater ownership and use of LLINs [9], (3) improved treatment-seeking behaviour among caregivers [9], (4) better housing, which lowers the risk of exposure to malaria vectors indoors [11, 16] and (5) greater food security, which reduces undernutrition and protein-energy malnutrition and possibly susceptibility to malaria infection and progression to severe disease [10] (though the evidence is inconsistent [20]). Modern houses were defined as those with cement, wood or metal walls; a tiled or metal roof and closed eaves. All other houses were classified as traditional. Access to healthcare and LLIN use were not hypothesised to be associated with SEP in this study population, since LLINs and all healthcare were provided by the study free of charge, but wealthier households were hypothesised to seek treatment more promptly than poorer households. Other household-level risk factors for malaria include distance to larval habitats, distance to village periphery, urbanicity and the density of livestock nearby, which were outside the scope of this study. In turn, malaria imposes costs that can cause poverty [7, 8], but this feedback loop was not analysed in this study. Heterogeneity in SEP is hypothesised to be driven largely by relative success in smallholder agriculture, since agriculture is the primary livelihood source in Nagongera (Box 1). There are many other determinants of SEP that are well studied outside the health sphere [18, 24], but we include here only non-agricultural income and access to remittances. Land area cultivated* is included as an indicator of relative agricultural success, but may also be a determinant of relative agricultural success among other factors which are outside the scope of this study. This conceptual framework is not an exhaustive representation of all malaria risk factors, confounders, mediators and causal associations, but includes only those analysed in this study. The conceptual framework adds greater complexity to those by de Castro [8] and Somi [7], which primarily demonstrate bi-directionality, while the present study is chiefly interested in dissecting the strands of the poverty-to-malaria direction

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