Beyond the map: evidencing the spatial dimension of health inequalities

Springer Science and Business Media LLC - Tập 19 - Trang 1-11 - 2020
Yohan Fayet1,2, Delphine Praud3,4, Béatrice Fervers3,4, Isabelle Ray-Coquard1,2, Jean-Yves Blay5, Françoise Ducimetiere1, Guy Fagherazzi6,7, Elodie Faure7,8
1Equipe EMS – Département de Sciences Humaines et Sociales, Centre Léon Bérard, Lyon, France
2EA 7425 Health Services and Performance Research, Université de Lyon, Lyon, France
3Department Prevention Cancer Environment, Centre Léon Bérard, Lyon, France
4Inserm UA 08: Radiations, Défense, Santé, Environnement, Centre Léon Bérard, Lyon, France
5Department of Medical Oncology, Centre Léon Bérard, Université Claude Bernard, Lyon, France
6Digital Epidemiology and e-Health Research Hub, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
7Center of Epidemiology and Population Health, UMR 1018, Inserm, Paris South, Paris Saclay University, Villejuif, France
8Gustave Roussy Institute, Villejuif, France

Tóm tắt

Spatial inequalities in health result from different exposures to health risk factors according to the features of geographical contexts, in terms of physical environment, social deprivation, and health care accessibility. Using a common geographical referential, which combines indices measuring these contextual features, could improve the comparability of studies and the understanding of the spatial dimension of health inequalities. We developed the Geographical Classification for Health studies (GeoClasH) to distinguish French municipalities according to their ability to influence health outcomes. Ten contextual scores measuring physical and social environment as well as spatial accessibility of health care have been computed and combined to classify French municipalities through a K-means clustering. Age-standardized mortality rates according to the clusters of this classification have been calculated to assess its effectiveness. Significant lower mortality rates compared to the mainland France population were found in the Wealthy Metropolitan Areas (SMR = 0.868, 95% CI 0.863–0.873) and in the Residential Outskirts (SMR = 0.971, 95% CI 0.964–0.978), while significant excess mortality were found for Precarious Population Districts (SMR = 1.037, 95% CI 1.035–1.039), Agricultural and Industrial Plains (SMR = 1.066, 95% CI 1.063–1.070) and Rural Margins (SMR = 1.042, 95% CI 1.037–1.047). Our results evidence the comprehensive contribution of the geographical context in the constitution of health inequalities. To our knowledge, GeoClasH is the first nationwide classification that combines social, environmental and health care access scores at the municipality scale. It can therefore be used as a proxy to assess the geographical context of the individuals in public health studies.

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