title: A brief conceptual tutorial on multilevel analysis in social epidemiology: interpreting neighbourhood differences and the effect of neighbourhood characteristics on individual health.
abstract: 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.
  
  
  METHODS
  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.
authors.affiliation: Department of Community Medicine (Section of Preventive Medicine), Malmö University Hospital, Faculty of Medicine (Campus Malmö), Lund University, S-205 02 Malmö, Sweden. juan.merlo@med.lu.se
authors.forename: Juan
authors.initials: J
authors.lastname: Merlo
authors.forename: Basile
authors.initials: B
authors.lastname: Chaix
authors.forename: Min
authors.initials: M
authors.lastname: Yang
authors.forename: John
authors.initials: J
authors.lastname: Lynch
authors.forename: Lennart
authors.initials: L
authors.lastname: Råstam
mesh_terms: D000959:Antihypertensive Agents / Q000627:therapeutic use; D001794:Blood Pressure; D015992:Body Mass Index; D004812:Epidemiologic Methods; D006297:Health Services Accessibility; D006304:Health Status; D006801:Humans; D007182:Income; D015233:Models, Statistical; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors
chemical_list: D000959:Antihypertensive Agents