12. Multilevel Residual Mapping
Consider NEIGHBORHOOD-2 in REGION-A, and NEIGHBORHOOD-2 in REGION-B in Figure 9. Both neighborhoods are seen to be performing well with low rates of poor health (negative neighborhood residuals). The similarity in neighborhood effects is, however, occurring in entirely different contexts and as such may be telling quite a different story. While low rates in NEIGHBORHOOD-2 in REGION-A are being achieved within a favorable context (a low-rate region), in NEIGHBORHOOD-2 in REGION-B they are occurring within an unfavorable context (a high-rate region).
As this example illustrates, we have a nuanced way of evaluating and monitoring the performance of particular places.
One possibility, as shown in Figure 10, is to have a simple four-fold typology of neighborhood health performance:
- TYPE-I: Unhealthy neighborhoods in unhealthy regions;
- TYPE-II: Unhealthy neighborhoods in healthy regions;
- TYPE-III: Healthy neighborhoods in unhealthy regions; and
- TYPE-IV: Healthy neighborhoods in healthy regions.
The purpose of such typologies is not simply methodological, but substantive and practical. For instance, TYPE-I neighborhoods are doubly disadvantaged as ‘unhealthy’ neighborhoods in ‘unhealthy’ regions, while TYPE-IV neighborhoods suggest a ‘virtuous’ reinforcement of contextual advantage (‘healthy’ neighborhoods in ‘healthy’ regions). For TYPE-II and TYPE-III neighborhoods, meanwhile, contextual advantage at one level offsets disadvantage at the other. Determining the ‘cut-off’ points’ for what can be considered ‘healthy’ and ‘unhealthy’ is critical and care must be taken while identifying specific places, an issue to which we shall return later in this chapter. Nonetheless, our aim here is to illustrate the potential of a multilevel approach for evaluative and monitoring exercises that are usually of interest for public health departments.