Abstract
Most ecological indices of deprivation are constructed from census data at the national level, which raises questions about the relevance of their use, and their comparability across a country. We aimed to determine whether a national index can account for deprivation regardless of location characteristics. In Metropolitan France, 43,853 residential census block groups (IRIS) were divided into eight area types based on quality of life. We calculated score deprivation for each IRIS using the French version of the European Deprivation Index (F-EDI). We decomposed the score by calculating the contribution of each of its components by area type, and we assessed the impact of removing each component and recalculating the weights on the identification of deprived IRIS. The set of components most contributing to the score changed according to the area type, but the identification of deprived IRIS remained stable regardless of the component removed for recalculating the score. Not all components of the F-EDI are markers of deprivation according to location characteristics, but the multidimensional nature of the index ensures its robustness. Further research is needed to examine the limitations of using these indices depending on the purpose of the study, particularly in relation to the geographical grid used to calculate deprivation scores.
Highlights
A large variety of ecological indices of deprivation have been developed around the world to study socio-economic and territorial inequalities [1–14]
Using the French version of the European Deprivation Index (EDI) (F-EDI), we explored how the index fits the characteristics of various areas, categorised according to quality of life, in Metropolitan France
We investigated which set of components contributed most to the French version of the European Deprivation Index (F-EDI) score deprivation points contributed by each component to the F-EDI score
Summary
A large variety of ecological indices of deprivation have been developed around the world to study socio-economic and territorial inequalities [1–14]. Used to compensate for the lack of socio-economic data at the individual level, they include a contextual dimension related to the geographical level of measurement. They allow the assessment of the socio-economic situation of a geographical area by aggregating the socio-economic characteristics of its residents. This contextual dimension has been described in the literature [30–32], and corresponds to a part of the “place effect”, which aims to explain the role of location in the construction of health inequalities.
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