A brief conceptual tutorial on multilevel analysis in social epidemiology: interpreting neighbourhood differences and the effect of neighbourhood characteristics on individual health

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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: Using a conceptual rather than a mathematical approach, this article proposed a link between multilevel regression analysis (MLRA) and social epidemiological concepts. It has been previously explained that the concept of clustering of individual health status within neighbourhoods is useful for operationalising contextual phenomena in social epidemiology. It has been shown that MLRA permits investigating neighbourhood disparities in health without considering any particular neighbourhood characteristic but only information on the neighbourhood to which each person belongs. This article illustrates how to analyse cross level (neighbourhood–individual) interactions, how to investigate associations between neighbourhood characteristics and individual health, and how to use the concept of clustering when interpreting those associations and geographical differences in health. Design and participants: A MLRA was performed using hypothetical data pertaining to systolic blood pressure (SBP) from 25 000 subjects living in the 39 neighbourhoods of an imaginary city. Associations between individual characteristics (age, body mass index (BMI), use of antihypertensive drug, income) or neighbourhood characteristic (neighbourhood income) and SBP were analysed. Results: About 8% of the individual differences in SBP were located at the neighbourhood level. SBP disparities and clustering of individual SBP within neighbourhoods increased along individual BMI. Neighbourhood low income was associated with increased SBP over and above the effect of individual characteristics, and explained 22% of the neighbourhood differences in SBP among people of normal BMI. This neighbourhood income effect was more intense in overweight people. Conclusions: Measures of variance are relevant to understanding geographical and individual disparities in health, and complement the information conveyed by measures of association between neighbourhood characteristics and health.
dc.description.statementofresponsibilityJuan Merlo, Basile Chaix, Min Yang, John Lynch, Lennart Råstam
dc.identifier.citationJournal of Epidemiology and Community Health, 2005; 59(12):1022-1029
dc.identifier.doi10.1136/jech.2004.028035
dc.identifier.issn0143-005X
dc.identifier.issn1470-2738
dc.identifier.orcidLynch, J. [0000-0003-2781-7902]
dc.identifier.urihttp://hdl.handle.net/2440/65844
dc.language.isoen
dc.publisherBritish Med Journal Publ Group
dc.rightsCopyright status unknown
dc.source.urihttps://doi.org/10.1136/jech.2004.028035
dc.subjectHumans
dc.subjectAntihypertensive Agents
dc.subjectBody Mass Index
dc.subjectEpidemiologic Methods
dc.subjectModels, Statistical
dc.subjectHealth Status
dc.subjectResidence Characteristics
dc.subjectBlood Pressure
dc.subjectSocioeconomic Factors
dc.subjectIncome
dc.subjectHealth Services Accessibility
dc.titleA brief conceptual tutorial on multilevel analysis in social epidemiology: interpreting neighbourhood differences and the effect of neighbourhood characteristics on individual health
dc.typeJournal article
pubs.publication-statusPublished

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