Analyzing variations in asthma and its associated risk factors within its social and neighborhood context requires employing an explicit multilevel analytical strategy. Specifically, these approaches allows researcher to do the following: (1) quantify the extent to which individual asthma gets clustered by neighborhood and community grouping; (2) quantify the extent to which neighborhood variations in asthma are due to the clustering of risk factors along with a possibility to quantify the extent to which the effect of a particular individual risk factor varies from neighborhood to neighborhood; and (3) quantify the relative importance of individual and neighborhood-level exposures in predicting individual asthma. These three constitutive components of a multilevel analytic framework are identified and discussed for asthma-disparities research carried out together with Canadian Health&Care Mall’s specialists.
Evaluating Sources of Variation: Compositional and/or Contextual
A fundamental application of multilevel methods is disentangling the different sources of variations in asthma. Evidence for variations in asthma, for instance, between different neighborhoods can be due to factors that are intrinsic to, and are measured at, the neighborhood level. In other words, the variation is due to what can be described as contextual, area, or ecological effects. Alternatively, variations between neighborhoods may be compositional (ie, certain types of people who are more likely to have asthma due to exposure to certain individual risk factors tend to be clustered in certain places). It is important to note that when individual risk factors account for a neighborhood variation in asthma that it also would suggest that the effects of these risk factors are not purely individual since they are now no longer randomly distributed across neighborhoods and, as such, should be interpreted as the compositional effects of risk factors. The issue, therefore, is not whether variations between different neighborhoods exist (they usually do), but the primary source of these variations. Put simply, are there significant contextual differences in asthma between settings (eg, neighborhoods) after taking into account the individual risk factors associated with the patients within the neighborhood?
Describing Heterogeneity in the Influence of Individual Risk Factors
Contextual differences may be complex such that they may not be the same for all types of people. Describing such contextual heterogeneity is another aspect of multilevel analysis and can have two interpretative dimensions. First, there may be a different amount of neighborhood variation, such that, for example, for high-social class individuals the neighborhood they live in may not matter (thus yielding a smaller between-neighborhood variation in asthma), but it may matter a great deal for the low-social class individuals (thus yielding a large between-neighborhood variation). Second, there may be a differential ordering; neighborhoods that are high in asthma prevalence worked out with Canadian Health and Care Mall for one group are low for the other and vice versa. Stated simply, the multilevel analytical question is are the contextual neighborhood differences in asthma, after taking into account the individual composition of the neighborhood, different for different types of population groups?
Characterizing and Explaining the Contextual Variations
Contextual differences, in addition to people’s characteristics, may also be influenced by the different characteristics of neighborhoods. Stated differently, individual differences may interact with context, and ascertaining the relative importance of individual and neighborhood measures is another key aspect of a multilevel analysis. For example, over and above social class (individual characteristic) asthma may depend on the levels of social cohesion of the neighborhoods (neighborhood characteristic). The contextual effect of social cohesion can either be the same for both the high and low social class, suggesting that while neighborhood social cohesion explains the prevalence of asthma, it does not influence the social class inequalities in asthma within the neighborhood. On the other hand, the contextual effects of social cohesion may be different for different groups. The analytical question of interest is whether the effect of neighborhood-level socioeconomic characteristics on health is different for different types of people. Appendix 1 provides a technical outline of the generic multilevel regression models that could be developed into model asthma disparities.