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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Using remotely sensed night-time light as a proxy for poverty in Africa
Population Health Metrics, Volume 6, Article 5, Year 2008
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Description
Background: Population health is linked closely to poverty. To assess the effectiveness of health interventions it is critical to monitor the spatial and temporal changes in the health indicators of populations and outcomes across varying levels of poverty. Existing measures of poverty based on income, consumption or assets are difficult to compare across geographic settings and are expensive to construct. Remotely sensed data on artificial night time lights (NTL) have been shown to correlate with gross domestic product in developed countries. Methods: Using national household survey data, principal component analysis was used to compute asset-based poverty indices from aggregated household asset variables at the Administrative 1 level (n = 338) in 37 countries in Africa. Using geographical information systems, mean brightness of and distance to NTL pixels and proportion of area covered by NTL were computed for each Administrative1 polygon. Correlations and agreement of asset-based indices and the three NTL metrics were then examined in both continuous and ordinal forms. Results: At the Administrative 1 level all the NTL metrics distinguished between the most poor and least poor quintiles with greater precision compared to intermediate quintiles. The mean brightness of NTL, however, had the highest correlation coefficient with the asset-based wealth index in continuous (Pearson correlation = 0.64, p < 0.01) and ordinal (Spearman correlation = 0.79, p < 0.01; Kappa = 0.64) forms. Conclusion: Metrics of the brightness of NTL data offer a robust and inexpensive alternative to asset-based poverty indices derived from survey data at the Administrative 1 level in Africa. These could be used to explore economic inequity in health outcomes and access to health interventions at sub-national levels where household assets data are not available at the required resolution. © 2008 Noor et al; licensee BioMed Central Ltd.
Authors & Co-Authors
Noor, Abdisalan Mohamed
United Kingdom, Oxford
University of Oxford
United Kingdom, Oxford
John Radcliffe Hospital
Alegana, Victor Adagi
United Kingdom, Oxford
University of Oxford
Gething, Peter W.
United Kingdom, Southampton
University of Southampton
United Kingdom, Oxford
University of Oxford
Tatem, Andrew J.
United Kingdom, Oxford
University of Oxford
Snow, Robert William
United Kingdom, Oxford
University of Oxford
United Kingdom, Oxford
John Radcliffe Hospital
Statistics
Citations: 148
Authors: 5
Affiliations: 3
Identifiers
Doi:
10.1186/1478-7954-6-5
ISSN:
14787954
Research Areas
Health System And Policy
Study Design
Cross Sectional Study
Study Approach
Quantitative