Beyond the map: evidencing the spatial dimension of health inequalities

International Journal of Health Geographics

Elodie Faure¹  Béatrice Fervers²  Delphine Praud²  Jean-Yves Blay³  Guy Fagherazzi⁴  Françoise Ducimetiere⁵  Yohan Fayet⁶  Isabelle Ray-Coquard⁶ 

[1] Center of Epidemiology and Population Health, UMR 1018, Inserm, Paris South, Paris Saclay University, Villejuif, France;Gustave Roussy Institute, Villejuif, France;Department Prevention Cancer Environment, Centre Léon Bérard, Lyon, France;Inserm UA 08: Radiations, Défense, Santé, Environnement, Centre Léon Bérard, Lyon, France;Department of Medical Oncology, Centre Léon Bérard, Université Claude Bernard, Lyon, France;Digital Epidemiology and e-Health Research Hub, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg;Center of Epidemiology and Population Health, UMR 1018, Inserm, Paris South, Paris Saclay University, Villejuif, France;Equipe EMS – Département de Sciences Humaines et Sociales, Centre Léon Bérard, 28 rue Laennec, 69008, Lyon, France;Equipe EMS – Département de Sciences Humaines et Sociales, Centre Léon Bérard, 28 rue Laennec, 69008, Lyon, France;EA 7425 Health Services and Performance Research, Université de Lyon, Lyon, France;

关键词: Health inequalities;    Environment;    Social deprivation;    Health care access;    Geography;    Public health;    France;    GIS;   

DOI  :  10.1186/s12942-020-00242-0

来源: Springer

【 摘 要 】

BackgroundSpatial 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.MethodsWe 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.ResultsSignificant 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).ConclusionsOur 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.

【 授权许可】

CC BY