Using GIS-based methods of multicriteria analysis to construct socio-economic deprivation indices
Using GIS-based methods of multicriteria analysis to construct socio-economic deprivation indices
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DOI：
10.1186/1476-072x-6-17
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发表时间：
2007-05-14
影响因子：
4.9
通讯作者：
Hayes, Michael V.
中科院分区：
文献类型：
--
作者：
Bell, Nathaniel;Schuurman, Nadine;Hayes, Michael V.
背景：在过去的几十年里，研究人员已经提出了大量证据表明，在各种健康结果中存在着社会梯度，这是由于人群中收入、教育、就业条件和家庭动态的系统性差异造成的。健康的社会梯度是使用剥夺指数来衡量的，剥夺指数通常是根据从全国人口普查中获得的汇总社会经济数据构建的--这一技术至少可以追溯到20世纪70年代初的S。过去十年来构建指数的主要方法是主成分分析。由于在核实答复分数的主观性方面存在固有的困难，很少从基于调查的数据来源构建指数。我们认为，这种主观性可以揭示当地健康结果的空间分布。此外，如果在没有专家意见的情况下对邻里社会经济地位进行加权，则表明邻里社会经济地位的比例可能不足。在本文中，我们提出使用地理信息科学(GIS)来构建索引。我们使用基于地理信息系统的顺序加权平均(OWA)多准则分析(MCA)作为一种技术来验证使用更定性的数据源构建的剥夺指数。OWA和传统MCA都是众所周知的空间分析方法，但在社会流行病学中应用很少。结果：对不列颠哥伦比亚省医务卫生官员(MHO)的调查被用来填充基于MCA的索引。在调查结果的基础上，选取了7个变量进行加权。OWA可变权重使用滑动标度将局部和全局权重分配给指数变量，从而产生一系列可变方案。当地的权重也为控制MHO回答分数中的不确定性水平提供了杠杆。这与传统的剥夺指数不同，因为权重同时由原始受访者得分和数据集中变量的值决定。结论：基于OWA的MCA是一种敏感的工具，允许在量化健康状况的社会经济梯度时纳入专家意见。OWA将主观和客观权重应用于指标变量，从而为将调查结果纳入空间分析提供了更合理的手段。
Background: Over the past several decades researchers have produced substantial evidence of a social gradient in a variety of health outcomes, rising from systematic differences in income, education, employment conditions, and family dynamics within the population. Social gradients in health are measured using deprivation indices, which are typically constructed from aggregated socio-economic data taken from the national census - a technique which dates back at least until the early 1970's. The primary method of index construction over the last decade has been a Principal Component Analysis. Seldom are the indices constructed from survey-based data sources due to the inherent difficulty in validating the subjectivity of the response scores. We argue that this very subjectivity can uncover spatial distributions of local health outcomes. Moreover, indication of neighbourhood socio-economic status may go underrepresented when weighted without expert opinion. In this paper we propose the use of geographic information science (GIS) for constructing the index. We employ a GIS-based Order Weighted Average (OWA) Multicriteria Analysis (MCA) as a technique to validate deprivation indices that are constructed using more qualitative data sources. Both OWA and traditional MCA are well known and used methodologies in spatial analysis but have had little application in social epidemiology.Results: A survey of British Columbia's Medical Health Officers (MHOs) was used to populate the MCA-based index. Seven variables were selected and weighted based on the survey results. OWA variable weights assign both local and global weights to the index variables using a sliding scale, producing a range of variable scenarios. The local weights also provide leverage for controlling the level of uncertainty in the MHO response scores. This is distinct from traditional deprivation indices in that the weighting is simultaneously dictated by the original respondent scores and the value of the variables in the dataset.Conclusion: OWA-based MCA is a sensitive instrument that permits incorporation of expert opinion in quantifying socio-economic gradients in health status. OWA applies both subjective and objective weights to the index variables, thus providing a more rational means of incorporating survey results into spatial analysis.