Socio-economic status and malaria-related outcomes in Mvomero District, Tanzania

• Published in: Global public health Vol. 7; no. 4; pp. 384 - 399
• Main Authors: Dickinson, Katherine L., Randell, Heather F., Kramer, Randall A., Shayo, Elizabeth H.
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis Group 01.04.2012; Taylor & Francis Ltd
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Antimalarials - economics; Antimalarials - therapeutic use; Associations; Demographics; Disease prevention; Diseases; Female; fundamental causes; Health inequalities; Health inequality; Health policy; Health Services Accessibility; Healthcare Disparities; Households; Humans; Illness; insecticide-treated nets; Level of education; Malaria; Malaria - diagnosis; Malaria - drug therapy; Malaria - epidemiology; Malaria - prevention & control; Male; Medical diagnosis; Middle Aged; Mosquito Nets - economics; Poverty; Prevention; Risk; Risk Factors; Rural areas; Rural Health - statistics & numerical data; Rural Population; Social Class; socio-economic status; Socioeconomic Factors; Socioeconomic status; Tanzania; Wealth; Young Adult; Tanzania
• ISSN: 1744-1692; 1744-1706
• DOI: 10.1080/17441692.2010.539573

While policies often target malaria prevention and treatment - proximal causes of malaria and related health outcomes - too little attention has been given to the role of household- and individual-level socio-economic status (SES) as a fundamental cause of disease risk in developing countries. This paper presents a conceptual model outlining ways in which SES may influence malaria-related outcomes. Building on this conceptual model, we use household data from rural Mvomero, Tanzania, to examine empirical relationships among multiple measures of household and individual SES and demographics, on the one hand, and malaria prevention, illness, and diagnosis and treatment behaviours, on the other. We find that access to prevention and treatment is significantly associated with indicators of households' wealth; education-based disparities do not emerge in this context. Meanwhile, reported malaria illness shows a stronger association with demographic variables than with SES (controlling for prevention). Greater understanding of the mechanisms through which SES and malaria policies interact to influence disease risk can help to reduce health disparities and reduce the malaria burden in an equitable manner.