Challier B, Viel J F
Département de Santé Publique, Faculté de Médecine et de Pharmacie de Besançon, 2 place St Jacques, 25030 Besançon Cedex.
Rev Epidemiol Sante Publique. 2001 Feb;49(1):41-50.
A number of disease conditions are influenced by deprivation. Geographical measurement of deprivation can provide an independent contribution to individual measures by accounting for the social context. Such a geographical approach, based on deprivation indices, is classical in Great Britain but scarcely used in France. The objective of this work was to build and validate an index readily usable in French municipalities and cantons.
Socioeconomic data (unemployment, occupations, housing specifications, income, etc.) were derived from the 1990 census of municipalities and cantons in the Doubs departement. A new index was built by principal components analysis on the municipality data. The validity of the new index was checked and tested for correlations with British deprivation indices.
Principal components analysis on municipality data identified four components (explaining 76% of the variance). Only the first component (CP1 explaining 42% of the variance) was retained. Content validity (wide choice of potential deprivation items, correlation between items and CP1: 0.52 to 0.96) and construct validity (CP1 socially relevant; Cronbach's alpha=0.91; correlation between CP1 and three out of four British indices ranging from 0.73 to 0.88) were sufficient. Analysis on canton data supported that on municipality data.
The validation of the new index being satisfactory, the user will have to make a choice. The new index, CP1, is closer to the local background and was derived from data from a French departement. It is therefore better adapted to more descriptive approaches such as health care planning. To examine the relationship between deprivation and health with a more etiological approach, the British indices (anteriority, international comparisons) would be more appropriate, but CP1, once validated in various health problem situations, should be most useful for French studies.
许多疾病状况受贫困影响。通过考虑社会背景,贫困的地理测量可为个体测量提供独立贡献。这种基于贫困指数的地理方法在英国很经典,但在法国很少使用。本研究的目的是构建并验证一个可在法国市镇和行政区轻松使用的指数。
社会经济数据(失业、职业、住房规格、收入等)来自杜省1990年的市镇和行政区人口普查。通过对市镇数据进行主成分分析构建了一个新指数。检查并测试了新指数与英国贫困指数的相关性以验证其有效性。
对市镇数据进行主成分分析确定了四个成分(解释了76%的方差)。仅保留了第一个成分(CP1解释了42%的方差)。内容效度(潜在贫困项目选择广泛,项目与CP1的相关性:0.52至0.96)和结构效度(CP1具有社会相关性;Cronbach's alpha = 0.91;CP1与四个英国指数中的三个的相关性在0.73至0.88之间)是足够的。对行政区数据的分析支持了对市镇数据的分析结果。
新指数的验证令人满意,使用者将必须做出选择。新指数CP1更接近当地背景,且源自法国一个省份的数据。因此,它更适合用于如医疗保健规划等更具描述性的方法。要用更具病因学的方法研究贫困与健康之间的关系,英国指数(优先性、国际比较)会更合适,但CP1一旦在各种健康问题情境中得到验证,对法国的研究应该会非常有用。