Using remotely sensed night-time light as a proxy for poverty in Africa
Using remotely sensed night-time light as a proxy for poverty in Africa
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.
1-15
Noor, A.M.
241236c3-43df-47b0-bcab-ff7c25318cc6
Alegana, V.A.
6fdaa47e-c08c-48bc-b881-1dc7b89085e4
Gething, P.W.
82a5722c-21cc-462c-bdaf-7af4d50a6219
Tatem, A.J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Snow, R.W.
1df934dd-70f4-4bf1-8a98-7feb0207d796
21 October 2008
Noor, A.M.
241236c3-43df-47b0-bcab-ff7c25318cc6
Alegana, V.A.
6fdaa47e-c08c-48bc-b881-1dc7b89085e4
Gething, P.W.
82a5722c-21cc-462c-bdaf-7af4d50a6219
Tatem, A.J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Snow, R.W.
1df934dd-70f4-4bf1-8a98-7feb0207d796
Noor, A.M., Alegana, V.A., Gething, P.W., Tatem, A.J. and Snow, R.W.
(2008)
Using remotely sensed night-time light as a proxy for poverty in Africa.
Population Health Metrics, 6 (5), .
(doi:10.1186/1478-7954-6-5).
(PMID:18939972)
Abstract
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.
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Published date: 21 October 2008
Organisations:
Geography & Environment, PHEW – S (Spatial analysis and modelling), Population, Health & Wellbeing (PHeW)
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Local EPrints ID: 344437
URI: http://eprints.soton.ac.uk/id/eprint/344437
PURE UUID: 4e54a5a3-b02f-4425-9e00-ff834af2dc9e
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Date deposited: 05 Nov 2012 11:40
Last modified: 15 Mar 2024 03:43
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Author:
A.M. Noor
Author:
V.A. Alegana
Author:
P.W. Gething
Author:
R.W. Snow
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