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.
Int J Health Geogr. 2020 Nov 9;19(1):46. doi: 10.1186/s12942-020-00242-0.
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.
健康的空间不平等是由于地理环境特征不同而导致的健康风险因素暴露不同，这些特征包括物理环境、社会剥夺和医疗保健可及性。使用一个共同的地理参照系，结合衡量这些背景特征的指数，可以提高研究的可比性，并更好地理解健康不平等的空间维度。
我们开发了地理分类健康研究（GeoClasH），以根据其影响健康结果的能力来区分法国的市镇。计算了十个衡量物理和社会环境以及医疗保健空间可达性的环境分数，并通过 K 均值聚类对法国的市镇进行分类。根据该分类的聚类计算了年龄标准化死亡率，以评估其有效性。
与法国大陆人口相比，发现富裕的大都市区（SMR=0.868，95%置信区间 0.863-0.873）和住宅郊区（SMR=0.971，95%置信区间 0.964-0.978）的死亡率显著较低，而脆弱人口地区（SMR=1.037，95%置信区间 1.035-1.039）、农业和工业平原（SMR=1.066，95%置信区间 1.063-1.070）和农村边缘地区（SMR=1.042，95%置信区间 1.037-1.047）的死亡率则显著偏高。
我们的结果表明，地理环境在构成健康不平等方面具有全面的贡献。据我们所知，GeoClasH 是第一个在市镇规模上结合社会、环境和医疗保健可达性分数的全国性分类。因此，它可以用作公共卫生研究中评估个体地理环境的替代指标。
