A brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon

Simple item page
dc.contributor.authorMerlo, J.
dc.contributor.authorChaix, B.
dc.contributor.authorYang, M.
dc.contributor.authorLynch, J.
dc.contributor.authorRastam, L.
dc.date.issued2005
dc.description.abstractStudy objective: This didactical essay is directed to readers disposed to approach multilevel regression analysis (MLRA) in a more conceptual than mathematical way. However, it specifically develops an epidemiological vision on multilevel analysis with particular emphasis on measures of health variation (for example, intraclass correlation). Such measures have been underused in the literature as compared with more traditional measures of association (for example, regression coefficients) in the investigation of contextual determinants of health. A link is provided, which will be comprehensible to epidemiologists, between MLRA and social epidemiological concepts, particularly between the statistical idea of clustering and the concept of contextual phenomenon. Design and participants: The study uses an example based on hypothetical data on systolic blood pressure (SBP) from 25 000 people living in 39 neighbourhoods. As the focus is on the empty MLRA model, the study does not use any independent variable but focuses mainly on SBP variance between people and between neighbourhoods. Results: The intraclass correlation (ICC = 0.08) informed of an appreciable clustering of individual SBP within the neighbourhoods, showing that 8% of the total individual differences in SBP occurred at the neighbourhood level and might be attributable to contextual neighbourhood factors or to the different composition of neighbourhoods. Conclusions: The statistical idea of clustering emerges as appropriate for quantifying "contextual phenomena" that is of central relevance in social epidemiology. Both concepts convey that people from the same neighbourhood are more similar to each other than to people from different neighbourhoods with respect to the health outcome variable.
dc.description.statementofresponsibilityJuan Merlo, Basile Chaix, Min Yang, John Lynch, Lennart Råstam
dc.identifier.citationJournal of Epidemiology and Community Health, 2005; 59(6):443-449
dc.identifier.doi10.1136/jech.2004.023473
dc.identifier.issn0143-005X
dc.identifier.issn1470-2738
dc.identifier.orcidLynch, J. [0000-0003-2781-7902]
dc.identifier.urihttp://hdl.handle.net/2440/65845
dc.language.isoen
dc.publisherBritish Med Journal Publ Group
dc.rightsCopyright status unknown
dc.source.urihttps://doi.org/10.1136/jech.2004.023473
dc.subjectHumans
dc.subjectEpidemiologic Methods
dc.subjectCluster Analysis
dc.subjectModels, Statistical
dc.subjectRegression Analysis
dc.subjectSociology, Medical
dc.subjectHealth Status
dc.subjectResidence Characteristics
dc.subjectAdult
dc.subjectMiddle Aged
dc.titleA brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon
dc.typeJournal article
pubs.publication-statusPublished

Files

Collections

Public Health publications