2000115-Strengthening-Communities-with-Neighborhood-Data

290 Strengthening Communities with Neighborhood Data
tools to specify individualized neighborhood boundaries centered on the
location of households. Buffers of varying sizes are drawn around each
household’s location, and neighborhood indicators are calculated for
these buffers (Chaix et al. 2009; Guo and Bhat 2007). The buffer may be
specified by distance weights, population size, or other geographic features
(Chaix, Merlo, and Chauvin 2005). In this way, a neighborhood measure
is created for each household’s unique area. There is evidence that
the magnitude of contextual effects on some health outcomes is greater
when ego-centric or sliding rather than the administratively defined
neighborhoods used in statistical models (Chaix, Merlo, Subramanian,
et al. 2005).
Finally, sometimes it may be desirable to craft neighborhood units that
are demographically homogeneous, are of a designated size and shape, or
that do not cross selected barriers or landmarks. Automated zone-design
programs can be used to aggregate areas while optimizing such criteria
(Cockings and Martin 2005). This method of crafting neighborhood units
was investigated in Bristol, England, following an iterative process that
imposed various constraints with respect to population and housing characteristics,
area size, and geographic considerations (Haynes et al. 2007).
The resulting neighborhood units were similar to community areas that
were designated by local government officers.
All these alternatives to administratively defined neighborhoods face
practical challenges. The availability of data can be a problem. Data at
the point level or data for small aggregations such as blocks are fairly easy to
allocate into unique boundaries, but data that are available only for larger
geographies (e.g., census tracts) may have to be approximately apportioned
to the new units. Moreover, the burden of analytic work required
to use resident maps, street networks, spatial buffers, and so forth is not
trivial. However, when the purpose of a study is to explain how neighborhoods
change or affect behavior, such methods hold promise as a way of
assuring that the neighborhood is correctly specified for the individuals
involved.
Finally, although the above techniques are promising as alternatives
to the delineation of neighborhoods by administrative agencies, it is
important to further evaluate them based on a deeper understanding of
how people interact with and relate to their neighborhoods (Matthews
2011). The relevant neighborhood unit will differ depending on the
desired outcome and by characteristics of the individual (Spielman and
Yoo 2009). Moreover, greater attention is needed to the variation within