Multilevel Modeling

11. Multiple Spatial Contexts

Much of the existing accounts of multilevel methods have been largely restricted to two-level structures, which typically put individuals at level-1 and places at level-2. In this section, we extend the model to consider the multiplicity of spatial levels in public health. For instance, in the US, geographical units such as block groups (BGs), census tracts (CTs), counties, or states may each exert a differential influence on health in the population.

Despite this, most research examining the effects of context on health has conceptualized contextual effects at only one level of geography.

Multiple hierarchical geographic levels may be needed to explain the mechanisms by which context at different levels affects health. The multiplicity of geographic levels raises a fundamental issue in design: determining the number of levels necessary to analyze a particular health outcome and the relative importance of different levels. Consider, for example, a hierarchy of different geographic levels, in which BGs are nested within CTs that in turn are nested within counties within states. A fallacy would occur if poor health has a strong dependence at the BG level, but the analysis only considers the CT level, thereby resulting in incorrect inference at the individual level and the CT level.