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  • Use of multilevel modeling allows us to account for natural and sampling induced nesting within L.A.FANS, as well as model contextual heterogeneity; directing inquiry away from average effects, to inquire about differences and examine potential neighborhood variation in asthma. [29] Multilevel models are also appropriate when causal processes are thought to operate at more than one level; as asthma is a multi-factorial disease which is influenced not only by compositional factors (such as genetics) but also by contextual factors (such as neighborhood violence), single level regression models would be inappropriate. [30] We first examined the effects of neighborhood safety characteristics on the odds ratio of reporting an asthma diagnosis (Model 1) and subsequently adjusted for the effects of individual characteristics (Model 2), followed by primary caregiver’s characteristics (Model 3), and lastly physical characteristics of the indoor home environment and neighborhood poverty (Model 4).
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