衡量比利时小区域水平的剥夺:比利时多重剥夺指数

IF 2.1 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Spatial and Spatio-Temporal Epidemiology Pub Date : 2023-06-01 DOI:10.1016/j.sste.2023.100587
Martina Otavova , Bruno Masquelier , Christel Faes , Laura Van den Borre , Catherine Bouland , Eva De Clercq , Bram Vandeninden , Andreas De Bleser , Brecht Devleesschauwer
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引用次数: 0

摘要

背景过去,在比利时的健康和社会不平等研究中,贫困大多是通过简单的单变量衡量标准来衡量的,例如低收入或教育程度低。本文介绍了从总体层面向更复杂、多维的贫困衡量标准的转变,并描述了2001年和2011年第一个比利时多重贫困指数(BIMD)的发展。方法BIMD是在比利时最小的行政单位统计部门层面构建的。它们是六个剥夺领域的结合:收入、就业、教育、住房、犯罪和健康。每个领域都建立在一套相关指标的基础上,这些指标代表了一个地区遭受某种剥夺的个人。将这些指标组合起来创建领域剥夺分数,然后对这些分数进行加权,以创建总体BIMD分数。领域和BIMD的分数可以进行排名,并分配到从1(最贫困)到10(最不贫困)的十分位数。结果我们显示了贫困程度最高和最低的统计部门在各个领域和总体BIMD方面的分布的地理差异,并确定了贫困热点。大多数贫困程度最高的统计部门位于瓦隆尼亚,而大多数贫困程度最低的统计部门则位于佛兰德斯。结论BIMD为研究人员和政策制定者提供了一种新的工具,用于分析贫困模式,并确定可以从特殊举措和计划中受益的领域。
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Measuring small-area level deprivation in Belgium: The Belgian Index of Multiple Deprivation

Background

In the past, deprivation has been mostly captured through simple and univariate measures such as low income or poor educational attainment in research on health and social inequalities in Belgium. This paper presents a shift towards a more complex, multidimensional measure of deprivation at the aggregate level and describes the development of the first Belgian Indices of Multiple Deprivation (BIMDs) for the years 2001 and 2011.

Methods

The BIMDs are constructed at the level of the smallest administrative unit in Belgium, the statistical sector. They are a combination of six domains of deprivation: income, employment, education, housing, crime and health. Each domain is built on a suite of relevant indicators representing individuals that suffer from a certain deprivation in an area. The indicators are combined to create the domain deprivation scores, and these scores are then weighted to create the overall BIMDs scores. The domain and BIMDs scores can be ranked and assigned to deciles from 1 (the most deprived) to 10 (the least deprived).

Results

We show geographical variations in the distribution of the most and least deprived statistical sectors in terms of individual domains and overall BIMDs, and we identify hotspots of deprivation. The majority of the most deprived statistical sectors are located in Wallonia, whereas most of the least deprived statistical sectors are in Flanders.

Conclusion

The BIMDs offer a new tool for researches and policy makers for analyzing patterns of deprivation and identifying areas that would benefit from special initiatives and programs.

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来源期刊
Spatial and Spatio-Temporal Epidemiology
Spatial and Spatio-Temporal Epidemiology PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
5.10
自引率
8.80%
发文量
63
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