{"title":"Neighbourhood Health Inequalities between Ethnic Groups in England: An Application of Ecological Inference","authors":"Peter Congdon","doi":"10.1007/s12061-024-09570-1","DOIUrl":null,"url":null,"abstract":"<div><p>Ecological inference has had primarily political science applications, but this study considers an application to assess variations in neighbourhood mental health between population sub-groups. The methodology used has particular utility when neighbourhood health data are available only in aggregate form, without disaggregation (e.g. by ethnic or socioeconomic group). The ecological inference approach is shown to provide insights into contextual effects, where neighbourhood features influence disease variations between sub-groups (e.g. the ethnic density effect on psychosis among non-white groups). The present study also highlights important issues raised by the data’s geographic framework, namely strong spatial clustering in the outcome, and compares spatial error and spatial lag methods to represent this spatial patterning appropriately. The study considers neighbourhood variations in psychosis between four ethnic groups, with a spatial framework provided by 32,844 small areas (Lower Super Output Areas, LSOAs) in England.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 2","pages":"847 - 866"},"PeriodicalIF":2.0000,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12061-024-09570-1.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Spatial Analysis and Policy","FirstCategoryId":"90","ListUrlMain":"https://link.springer.com/article/10.1007/s12061-024-09570-1","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
Ecological inference has had primarily political science applications, but this study considers an application to assess variations in neighbourhood mental health between population sub-groups. The methodology used has particular utility when neighbourhood health data are available only in aggregate form, without disaggregation (e.g. by ethnic or socioeconomic group). The ecological inference approach is shown to provide insights into contextual effects, where neighbourhood features influence disease variations between sub-groups (e.g. the ethnic density effect on psychosis among non-white groups). The present study also highlights important issues raised by the data’s geographic framework, namely strong spatial clustering in the outcome, and compares spatial error and spatial lag methods to represent this spatial patterning appropriately. The study considers neighbourhood variations in psychosis between four ethnic groups, with a spatial framework provided by 32,844 small areas (Lower Super Output Areas, LSOAs) in England.
期刊介绍：
Description
The journal has an applied focus: it actively promotes the importance of geographical research in real world settings
It is policy-relevant: it seeks both a readership and contributions from practitioners as well as academics
The substantive foundation is spatial analysis: the use of quantitative techniques to identify patterns and processes within geographic environments
The combination of these points, which are fully reflected in the naming of the journal, establishes a unique position in the marketplace.
RationaleA geographical perspective has always been crucial to the understanding of the social and physical organisation of the world around us. The techniques of spatial analysis provide a powerful means for the assembly and interpretation of evidence, and thus to address critical questions about issues such as crime and deprivation, immigration and demographic restructuring, retailing activity and employment change, resource management and environmental improvement. Many of these issues are equally important to academic research as they are to policy makers and Applied Spatial Analysis and Policy aims to close the gap between these two perspectives by providing a forum for discussion of applied research in a range of different contexts
Topical and interdisciplinaryIncreasingly government organisations, administrative agencies and private businesses are requiring research to support their ‘evidence-based’ strategies or policies. Geographical location is critical in much of this work which extends across a wide range of disciplines including demography, actuarial sciences, statistics, public sector planning, business planning, economics, epidemiology, sociology, social policy, health research, environmental management.
FocusApplied Spatial Analysis and Policy will draw on applied research from diverse problem domains, such as transport, policing, education, health, environment and leisure, in different international contexts. The journal will therefore provide insights into the variations in phenomena that exist across space, it will provide evidence for comparative policy analysis between domains and between locations, and stimulate ideas about the translation of spatial analysis methods and techniques across varied policy contexts. It is essential to know how to measure, monitor and understand spatial distributions, many of which have implications for those with responsibility to plan and enhance the society and the environment in which we all exist.
Readership and Editorial BoardAs a journal focused on applications of methods of spatial analysis, Applied Spatial Analysis and Policy will be of interest to scholars and students in a wide range of academic fields, to practitioners in government and administrative agencies and to consultants in private sector organisations. The Editorial Board reflects the international and multidisciplinary nature of the journal.
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