Gadiaga Assane N, De Longueville Florence, Georganos Stephanos, Grippa Tais, Dujardin Sébastien, Diène Aminata Niang, Masquelier Bruno, Diallo Mouhamadou, Linard Catherine
Institute of Life, Earth and Environment, Université de Namur, Namur, Belgium; Department of Geography, Université de Namur, Namur.
Department of Geoscience, Environment and Society, Université Libre De Bruxelles, Bruxelles.
Geospat Health. 2021 May 5;16(1). doi: 10.4081/gh.2021.910.
In sub-Saharan African cities, the dearth of accurate and detailed data is a major problem in the study of health and socioeconomic changes driven by rapid urbanization. Data on both health determinants and health outcomes are often lacking or are of poor quality. Proxies associated with socioeconomic differences are needed to compensate the lack of data. One of the most straightforward proxies is housing quality, which is a multidimensional concept including characteristics of both the built and natural environments. In this work, we combined the 2013 census data with remotely sensed land cover and land use data at a very high resolution in order to develop an integrated housing quality-based typology of the neighbourhoods in Dakar, Senegal. Principal component analysis and hierarchical classification were used to derive neighbourhood housing quality indices and four neighbourhood profiles. Paired tests revealed significant variations in the censusderived mortality rates between profile 1, associated with the lowest housing quality, and the three other profiles. These findings demonstrate the importance of housing quality as an important health risk factor. From a public health perspective, it should be a useful contribution for geographically targeted planning health policies, at the neighbourhood spatial level, which is the most appropriate administrative level for interventions.
在撒哈拉以南非洲城市，准确而详细的数据匮乏是研究快速城市化驱动的健康与社会经济变化的一个主要问题。关于健康决定因素和健康结果的数据往往缺失或质量不佳。需要与社会经济差异相关的替代指标来弥补数据的不足。最直接的替代指标之一是住房质量，它是一个多维概念，包括建筑环境和自然环境的特征。在这项工作中，我们将2013年人口普查数据与高分辨率的遥感土地覆盖和土地利用数据相结合，以便开发出一种基于住房质量的塞内加尔达喀尔社区综合类型学。主成分分析和层次分类被用于得出社区住房质量指数和四种社区概况。配对测试显示，与住房质量最低相关的概况1与其他三种概况之间，普查得出的死亡率存在显著差异。这些发现证明了住房质量作为一个重要健康风险因素的重要性。从公共卫生角度来看，这对于在社区空间层面进行地理定位的健康政策规划应是一项有益贡献，而社区空间层面是进行干预最合适的行政级别。
