Spatial variability of the relationship between fuel use and respiratory illness in sub-Saharan Africa

Authors: Katerina Brandt*, University of North Carolina at Chapel Hill
Topics: Medical and Health Geography, Energy, Development
Keywords: energy poverty, clean cooking, respiratory illness, sub-Saharan Africa
Session Type: Paper
Day: 4/6/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Cleveland 1, Marriott, Mezzanine Level
Presentation File: No File Uploaded


Energy poverty, which is defined as a lack of access to electricity and clean cooking technologies, affects more than three billion people globally. Persistent use of traditional cooking fuels exposes people in sub-Saharan Africa to adverse effects of household air pollution which is related to respiratory health problems. This study investigates the relationship between fuel use and respiratory health and compares relationships across six sub-Saharan African countries. Nationally-representative Demographic and Health Survey data from Malawi, Zambia, Zimbabwe, Democratic Republic of the Congo, Ghana, and Gabon from 1999 to 2016 are used to understand spatial variability of household demographics, respiratory infections, and fuel use. MODIS data are used to develop an understanding of land use and land cover change, and how this may affect fuel use. Rainfall and temperature data are to account for environmental seasonality in fuel choice and performance. A series of regression methods are used to measure the relationship between household fuel use and respiratory infections. Categorical and geographically weighted regressions are built to analyze the influence of fuel type, within-household cooking practices, access to electricity, urbanicity, and seasonality on the prevalence of infections. Susceptible groups, such as young children and primary cooks in each household, are identified. This comprehensive overview establishes a foundation on which further analysis may be conducted to understand the implications of differential political and social contexts. Understanding of these variable patterns across space is imperative to designing effective, targeted interventions for clean fuel use over the course of the global energy transition.

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