title: Social Exclusion Index-for Health Surveys (SEI-HS): a prospective nationwide study to extend and validate a multidimensional social exclusion questionnaire.
abstract: Social exclusion (SE) refers to the inability of certain groups or individuals to fully participate in society. SE is associated with socioeconomic inequalities in health, and its measurement in routine public health monitoring is considered key to designing effective health policies. In an earlier retrospective analysis we demonstrated that in all four major Dutch cities, SE could largely be measured with existing local public health monitoring data. The current prospective study is aimed at constructing and validating an extended national measure for SE that optimally employs available items.
  
  
  
  In 2012, a stratified general population sample of 258,928 Dutch adults completed a version of the Netherlands Public Health Monitor (PHM) questionnaire in which 9 items were added covering aspects of SE that were found to be missing in our previous research. Items were derived from the SCP social exclusion index, a well-constructed 15-item instrument developed by the Netherlands Institute for Social Research (SCP). The dataset was randomly divided into a development sample (N =129,464) and a validation sample (N = 129,464). Canonical correlation analysis was conducted in the development sample. The psychometric properties were studied and compared with those of the original SCP index. All analyses were then replicated in the validation sample.
  
  
  
  The analysis yielded a four dimensional index, the Social Exclusion Index for Health Surveys (SEI-HS), containing 8 SCP items and 9 PHM items. The four dimensions: "lack of social participation", "material deprivation", "lack of normative integration" and "inadequate access to basic social rights", were each measured with 3 to 6 items. The SEI-HS showed adequate internal consistency for both the general index and for two of four dimension scales. The internal structure and construct validity of the SEI-HS were satisfactory and similar to the original SCP index. Replication of the SEI-HS in the validation sample confirmed its generalisability.
  
  
  
  This study demonstrates that the SEI-HS offers epidemiologists and public health researchers a uniform, reliable, valid and efficient means of assessing social exclusion and its underlying dimensions. The study also provides valuable insights in how to develop embedded measures for public health surveillance.
authors.affiliation: Department of Public Health, Municipality of Utrecht, Utrecht, Netherlands. A.van.Bergen@utrecht.nl.|Department of Psychiatry, Leiden University Medical Centre, Leiden, Netherlands. A.van.Bergen@utrecht.nl.
authors.forename: Addi P L
authors.initials: AP
authors.lastname: van Bergen
authors.affiliation: Department of Labour and Public Services, The Netherlands Institute of Social Research|SCP, The Hague, Netherlands.
authors.forename: Stella J M
authors.initials: SJ
authors.lastname: Hoff
authors.affiliation: Department of Public Health, Municipality of Utrecht, Utrecht, Netherlands.
authors.forename: Hanneke
authors.initials: H
authors.lastname: Schreurs
authors.affiliation: Department of Epidemiology and Health Promotion, Public Health Service of Amsterdam, Amsterdam, Netherlands.
authors.forename: Annelies
authors.initials: A
authors.lastname: van Loon
authors.affiliation: Department of Psychiatry, Leiden University Medical Centre, Leiden, Netherlands.
authors.forename: Albert M
authors.initials: AM
authors.lastname: van Hemert
mesh_terms: D000328:Adult; D000368:Aged; D005260:Female; D000069576:Health Equity; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D009426:Netherlands; D011446:Prospective Studies; D012929:Psychological Distance; D011594:Psychometrics; D011634:Public Health / Q000379:methods*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012934:Social Isolation; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires / Q000592:standards*
keywords: Embedded measure; Health inequalities; Non-linear canonical correlation analysis; OVERALS; Public health monitoring; Social exclusion