Geographic variations in the environment and population of interest mean that assessments are greatly affected by the spatial scale (or more strictly ‘spatial resolution’) at which the analysis is done.  They also need to be considered in selecting the way in which the results are displayed and communicated.

Results of most assessments are given in a relatively aggregated form (e.g. as total impacts for the whole study population).  Analysis, however, is generally done at a more detailed level, in order to reflect the highly localised (and often individual-level) interactions that really occur between environment and human health. 

Decisions about the spatial resolution for the analysis can have profound effects on the estimated impacts.  In general, the coarser the resolution (i.e. the more aggregated the analysis), the more attenuated the estimates will become: extremes will be lost and the distribution of impacts will appear much narrower than it really is.  As a consequence, local hot-spots or severely at-risk populations may be missed, while abrupt (and artificial) differences in impact may appear to exist between adjacent areas.  How much this affects the overall estimate of impact (across the study population as a whole) will vary.  If relationships between exposure and health are linear, the effect is likely to be small.  Where the relationships are non-linear, however, carrying out the analysis at a coarse resolution can strongly bias the estimates.  As the attached worked example illustrates, however, changing the resolution of the analysis can alter both the estimated levels of impact and their apparent spatial distribution.

Choosing an appropriate resolution needs care.  We do not necessarily get better results simply by using a finer resolution (i.e. smaller study units), for two reasons.  First, this may add to the uncertainty in our estimates of exposures, because we do not have reliable data at a local level.  Secondly, it exacerbates the 'small number problem' in terms of estimates of risk, because each study unit contains only a few people.  For rare effects, especially, the estimated impacts then become vanishingly small (e.g. with excess risks of only a fraction of a person in each area).  This can make the results difficult to interpret, especially for non-specialist users.

The watchwords for choosing the spatial resolution should thus be:

1. Select a resolution for analysis that reflects the scale of the phenomena being studied (e.g. the spatial variations in the hazards and the populations that might be affected);
2. Select a resolution for display and communication of the results that:

• is no smaller (and preferably coarser) than that of the analysis;
• provides stable estimates of impact in each study unit;
• enables users to identify relevant variations in the impacts (e.g. local hotspots) that might merit attention.