Guidelines for Using Rural-Urban Classification Systems
for Public Health Assessment
<<<
Previous <<<
>>>
Next >>>
Choosing the right classification system
Analysts should consider three main factors when
choosing a rural-urban classification scheme.
1) At what unit of geography are the health event and
population data available? The decision of which
rural-urban classification scheme to use may be driven
by the level of geo-coding in the health dataset, as
well as the availability of population denominators, if
the analyst needs to generate rates, Although many
health datasets include ZIP or county codes, the
complete street address required for geo-coding to
census tract is less commonly available and when
available, may have more missing values. Population
estimates, especially estimates by age, sex and year,
are commonly available at the county level. Estimates at
smaller levels of geography are less consistently
available. (See
Guidelines for Population Denominators
and Rates)
2) Is there special interest in a particular level of
rural or urban geography? Some county classifications
(e.g., Urban Influence Codes) distinguish between
counties with large and small urban areas. However,
these classification schemes generally do not account
for residential sub-urban areas often found on the
fringes of urban counties located across the county
border. Sub-county classification schemes, (e.g., RUCA
codes), are more effective at identifying the bedroom
communities adjacent to, but in different counties than
the urban core.
The analyst might be interested in differentiating more
remote from less remote rural areas. Classification
systems with larger spectrums of rurality, such as
Rural-Urban Continuum Codes, Urban Influence Codes or
RUCA codes, differentiate remote rural areas from less
remote rural areas. Thus, they are appropriate for rural
to rural comparisons.
3) Is comparability and reproducibility of the findings
or methods for other states or the nation important? In
some cases, the value of adopting a more widely used
classification scheme outweighs the value of choosing a
scheme that might yield higher precision or otherwise be
more suited to answering a specific question.
Nationally, the OMB’s Micropolitan, Metropolitan, and
Outside Core-Based Statistical Area system for county
classification and the RUCA sub-county classification
are the two most widely used rural classification
systems.
The Rural-Urban Commuting Area (RUCA) system: a good
choice
For most analyses, the
DOH Community Health Systems
Office recommends the RUCA system. The US Departments of
Agriculture and Health and Human Services and the WWAMI
Rural Health Research Center, originally developed this
system in the late 1990s. It is the only system
available at the census tract or ZIP code levels. The
RUCA system is currently considered the state of the
art, and is used widely. The RUCA system is more precise
than county-based alternatives, since it uses smaller
geographic units.
The RUCA system is a ten-tiered classification system
that uses US Census Bureau definitions of
Urbanized
Areas and Urban Clusters and commuting relationships at
the census tract level as the basic building blocks. The
primary (largest) and secondary (second largest)
commuting flows to core areas are identified using the
most recently available commuting data, the 2000 US
Census for the latest version of RUCA. Strongly linked
tracts are those where the primary commuting flow to a
core area is greater than 30% of commuting trips. Weakly
linked tracts are those where the largest flow to a core
area is 10-30%. Isolated rural areas are those with no
town greater than 2,500 where the primary commuting flow
is local. This yields the following scheme:
Table 2: Rural Urban Commuting Area (RUCA)
Classification System: Ten Primary Tiers
|
General
Classification |
Core Area
Codes |
High
Commuting Flow
(more than 30%) Codes |
Low Commuting
Flow
(Between 10-29%) Codes |
|
Metropolitan
(Urban)
(50,000 or more) |
1 |
2 |
3 |
|
Micropolitan
(Large Rural Town)
(10,000 - 49,999) |
4 |
5 |
6 |
|
Small Rural
Town
(2,500 – 9,999) |
7 |
8 |
9 |
|
Isolated
Rural
(under 2,500) |
10 |
|
|
The ten codes are sub-divided into 33 secondary codes
which can be consolidated or combined in several
different ways. See
Appendix 2 for a listing of the
secondary codes.
Washington State RUCA codes using census tract geography
are mapped in Figure 3.
 (Click
map for larger image)
A 2004 ZIP code approximation of the 2000 RUCA codes
developed by the WWAMI Rural Health Research Center is
mapped in Figure 4. The ZIP code approximation is less
accurate than the census tract version. ZIP codes do not
uniformly correspond with census blocks as do the census
tracts. A listing of 2006 ZIP code approximations of the RUCA codes is available at
DOH Health Care Access Page.
(Click map for larger image)
More information on the RUCA system is available at the
WWAMI Rural Health Research Center.
A four-tier consolidation of the RUCA system at the
sub-county level
Many datasets do not have sufficient sample size to
support analysis using a ten-tiered classification
system. For general descriptive analyses where
sub-county data are available, we suggest a four-tiered
consolidation based on secondary codes that identify the
general character of an area.
-
Urban Core: contiguous built-up areas of 50,000
persons or more. These areas correspond to US Census
Bureau’s Urbanized Areas.
-
Sub-Urban: areas, often in Metropolitan Counties, with
high commuting flows to Urban Cores (for example
Eatonville in Pierce County). These areas also include
all other areas where 30%-49% of the population commutes
to Urban Cores for work.
-
Large Rural Town: towns with populations between
10,000 and 49,999 and surrounding rural areas with 10%
or more primary commuting flows to these towns, as well
as secondary commuting flows of 10% or more to Urban
Cores.
-
Small Town and Isolated Rural Areas: towns with
populations below 10,000 and their surrounding commuter
areas and other isolated rural areas with more than one
hour driving distance to a nearest city.
Table 3 provides the four-level consolidation
recommended by the
DOH Community Health Systems Office.
This consolidation is based on the WWAMI Rural Health
Research Center’s seven-tiered classification system.
WWAMI’s own four-tiered classification collapses all of
urban into one urban category, and splits rural among
three additional categories. (See
http://depts.washington.edu/uwruca/ruca-maps.php.)
We recommend the consolidation in
Table 3, because large
proportions of Washington residents live in urban and
sub-urban areas, making analyses with these designations
informative. This Guideline defines the ‘urban core’ and
‘other urban’ found in the seven-tiered consolidation as
Urban Core and Sub-Urban, respectively. Large Rural Town
combines ‘large rural core’ and ‘other large rural’ from
the seven-tiered classification. Small Town and Isolated
Rural Areas comprise the remaining three rural
categories from WWAMI’s seven-tiered classification:
small rural core, other small rural, and isolated rural.
Table 3: Four-Tier Consolidation of Secondary RUCA Codes
|
Class |
Tier |
Secondary RUCA
Codes |
|
Urban Core |
1 |
1.0, 1.1 |
|
Sub-Urban |
2 |
2.0, 2.1, 3.0, 4.1, 5.1, 7.1, 8.1, 10.1 |
|
Large Rural Town |
3 |
4.0, 4.2, 5.0, 5.2, 6.0, 6.1 |
|
Small
Town/Isolated Rural |
4 |
7.0, 7.2, 7.3, 7.4, 8.0, 8.2, 8.3, 8.4, 9.0, 9.1, 9.2,
10.0, 10.2, 10.3, 10.4, 10.5, 10.6 |
As with the full set of RUCA codes, the census tract
version of the four-tiered consolidation (Figure 5)
allows more precise classification than a similar
consolidation done with the ZIP code RUCA approximations
(Figure 6), since the ZIP code boundaries do not always
coincide with census tract or county boundaries. But the
ZIP code approximation of RUCA codes can be used with
several public health datasets that use ZIP code as the
smallest geographic level. Data analysts need to be
aware that ZIP codes change over time. These changes can
result in misclassification.
(Click map for larger image)
(Click map for larger image)
<<<
Previous <<<
>>>
Next >>>
|
