Malaria Public Health and Epidemiology Group, Centre for Geographic Medicine, KEMRI - University of Oxford - Wellcome Trust Collaborative Programme, Kenyatta National Hospital Grounds (behind NASCOP), P,O, Box 43640-00100, Nairobi, Kenya.
Popul Health Metr. 2008 Oct 21;6:5. doi: 10.1186/1478-7954-6-5.
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.
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.
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.
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.
人口健康与贫困密切相关。为了评估卫生干预措施的效果，必须监测人口健康指标和不同贫困程度下的结果在时空上的变化。基于收入、消费或资产的现有贫困衡量标准在不同地理环境下难以比较，且构建成本高昂。在发达国家，基于人造夜间灯光（NTL）的遥感数据已被证明与国内生产总值相关。
利用国家住户调查数据，采用主成分分析法，从非洲 37 个国家的住户资产变量中，在行政 1 级（n=338）汇总得到基于资产的贫困指数。利用地理信息系统，计算了每个行政 1 级多边形的 NTL 像素平均亮度和与 NTL 的距离，以及 NTL 覆盖区域的比例。然后，以连续和有序形式检验了基于资产的指数和三个 NTL 指标的相关性和一致性。
在行政 1 级，所有 NTL 指标都能在最贫困和最富裕的五分位数之间进行区分，与中间五分位数相比，其区分精度更高。然而，NTL 的平均亮度与基于资产的财富指数在连续（皮尔逊相关系数=0.64，p<0.01）和有序（斯皮尔曼相关系数=0.79，p<0.01；Kappa=0.64）形式下的相关性系数最高。
NTL 数据亮度指标为在非洲的行政 1 级，从调查数据中提取基于资产的贫困指数提供了一种稳健且廉价的替代方法。在没有所需分辨率的住户资产数据的情况下，这些指标可以用于探索次国家级卫生结果和卫生干预措施获取方面的经济不平等问题。
