How can we analyze environmental health resilience and vulnerability? A joint analysis with composite indices applied to the north of France

Abstract

In environmental health, vulnerability reflecting the cumulative harmful constraints and nuisances to which populations are subjected and resilience defined as the capacity of a territory to cope with health inequalities have been little extensively investigated together with the same importance. Besides the diversity of factors involved, there is no consensual framework to develop composite indices, one recognized methodology to deal with a multifaceted issue. Therefore, this research aims to establish a new transferable approach to assess the spatial heterogeneity of territorial inequalities. This new strategy relies on the simultaneous evaluation of resilience and vulnerability and the joint analysis based on the cross-interpretation of the spatialized composite indices of resilience and vulnerability. A case study was conducted to demonstrate the feasibility of this methodology, using the municipality as a spatial unit of analysis within a region in the north of France. To provide the most holistic description possible of the 3817 studied municipalities, 50 variables related to the economic, environment, policy, health, services and social dimensions were used to develop the composite indices. The vulnerability Index has a median value of 0.151 with an IQR of [0.126-0.180] and the Resilience Index has a median value of 0.341 with an IQR of [0.273-0.401]. The joint analysis was conducted to classify each municipality among four defined typologies: 1687 municipalities (44.2%) belong to the "To monitor" category, 1646 (43.1%) to the "Resilient" category, 329 (8.6%) to the "Have resources" category and 155 (4.1%) to the "Territorial blackspot" category. The methodology herein may be a diagnostic tool to identify and prioritize municipalities that could benefit from the implementation of specifically tailored public health policies.

Keywords: Diagnostic tool; Environmental health determinants; Multidimensional indices; Territorial blackspot; Territorial inequalities.