This project provides resources for the classification of areas and places in Alabama based on the concepts of rural and urban. As pointed out in a number of articles referenced in the Resources page, there is no one-size-fits-all definition of the terms. Rather, rural and urban are best thought of in the context of a particular application (healthcare or education, for example). Moreover, the binary dichotomy is misleading. Many areas and places will have varying degrees of rural and urban characteristics. For healthcare, a particularly good recent article is Considerations For Defining Rural Places in Health Policies and Programs, published by the Rural Policy Research Institute.
The terms and abbreviations defined below are used frequently in the maps and tables in this project.
The US Census Bureau defines rural and urban in terms of census blocks. A core of census blocks containing at least 1000 people per square mile, and adjoining blocks containing at least 500 people per square mile as an Urbanized Area (UA) if their population is 50000 or more, or an Urban Cluster (UC) if their population is between 2500 and 50000. All other census blocks are defined as rural. The Census Bureau gives each urbanized area a Urbanized Area Census Code (UACE).
The Census Bureau also classifies a community as either a city, a town, or a place. Cities and towns are incorporated, self-governing communities, while places are unincorporated communities. At the community level, a community that falls within an urbanized area maybe considered urban, while a community that is not within an urbanized area or an urban cluster may be considered rural. Communities that fall within an urban cluster typically would have both urban and rural characteristics.
A Core-Based Statistical Area (CBSA) is a US geographic area defined by the Office of Management and Budget (OMB) consisting of one or more contiguous counties (or equivalents). Specifically, CBSA consists of counties anchored by an urban center of at least 10,000 people plus adjacent counties that are socioeconomically tied to the urban center by commuting. The term CBSA
refers collectively to both metropolitan statistical areas and micropolitan statistical areas. Micropolitan areas are based on Census Bureau-defined urban clusters of at least 10,000 and fewer than 50,000 people. Metropolitan area are based on a Census Bureau-defined urbanized area of at least 50,000 people. So at the county level, a county in a metropolitan CBSA might be considered predominately urban while a county that is not in a CBSA might be considered thoroughly rural. Counties in a micropolitan CBSA from the gray area, typically with both urban and rural characteristics.
Of particular importance for healthcare is the urban-rural classification scheme developed by the National Center for Health Statistics (NCHS), part of the Centers for Disease Control and Prevention (CDC). This scheme is based on CBSAs, and so applies to counties, but is enhanced and adapted specifically for health statistics. It has four urban levels and two rural levels (ordered from most urban to most rural):
The first five are associated with CBSAs. The last level, Noncore is not associated with a CBSA, hence the name. So a Noncore county could be considered completely rural.
The Rural-Urban Continuum Codes (RUCC) are a classification scheme at the county level developed by the Economic Research Service of the US Department of Agriculture. The classification distinguishes metropolitan counties by the population size of their metro area, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area. There are nine codes, three metro and six non-metro as follows
The Rural-Urban Commuting Areas (RUCA) are a classification scheme at the census block level, also developed by the Economic Research Service of the US Department of Agriculture. The classification scheme is based on measures of population density, urbanization, and daily commuting. The primary and secondary RUCA codes are as follows:
Ultimately, each census block is classified as rural, urban, or mixed.
Primary Care Service Areas (PCSAs) have been defined by the Office of Family Health, Education, and Research at the UAB School of Medicine Huntsville Regional Medical Campus. Each PCSA is centered at a community with a cluster of medical resources (often including a general admissions hospital). PCSAs are based on the Alabama road network and each corresponds to a drive time of 30 minutes or less from the center. The PCSAs partition the state, like counties, but are more rational in terms of the delivery of healthcare services. Each PCSA is classified with the NCHS scheme discussed above, based on the classification of the county that contains the centroid.
The Geographic Names Information System (GNIS) was developed by the US Geological Survey (USGS) in cooperation with the US Board on Geographic Names (BGN). This board maintains cooperative working relationships with state authorities to standardize geographic names. GNIS contains information about the official names for places, features, and areas in the 50 states, the District of Columbia, and the territories and outlying areas of the United States, including Antarctica. GNIS is the geographic names component of The National Map.
Federal Information Processing Standards (FIPS) are publicly announced standards developed by the National Institute of Standards and Technology for use in computer systems by non-military American government agencies and government contractors. FIPS 6-4 is a code for US counties and equivalents.
For the purpose of rural health grants, the Federal Office of Rural Health Policy (FORHP) classifies ZIP code areas as eligible or not eligible, so essentially rural or urban. Because matching geographic areas with different boundaries can never be perfect, there are ZIP codes with urban population that are eligible, and there are ZIP codes with rural population that are not eligible. Any ZIP code where more than 50% of its population resides in either a non-metro county and/or a rural census tract is classified as eligible.
In Alabama, the term blackbelt refers to counties in the central part of the state that traditionally have been poor, rural, and marginalized (and hence vulnerable in terms of healthcare services). There is no universally accepted definition for the blackbelt counties of Alabama, but for purposes of healthcare, the following list is appropriate, and is the one used in this project:
By overlapping with counties, we have extended the blackbelt concept to PCSAs. The following list gives the blackbelt PCSAs:
Our data are displayed in the form of interactive maps and interactive tables. The maps generally have point or area layers that can be added or removed with the layer control on the map. The user can zoom in and out of a map and move about in the usual way. Zooming in reveals additional features such as small towns and then streets and roads. A click on the home button returns the map to its origional location and scale. The zoom-to-area button allows the user to zoom to a selected rectangular area of the map. Clicking on an object in a layer shows summary data for that object.
The interactive tables can be sorted by any field, by clicking on the header for that field. The buttons at the top allow the table data to be copied to the clipboard, in tab-separated text format, printed, or downloaded in various formats (tab-separated text, Excel, or PDF). With the search bar, the table can be filtered according to a text string.
In the interactive tables you can click on a row to select an object (community, county, PCSA) and see the object highlighted in the map. You can select as many rows as you wish. Click on a selected row again to de-select and remove the highlighting in the map.
The information and data presented in this project are provided as a service to the educational and healthcare communities. Although care was taken in gathering the data at the time of posting, no warranties are expressed or implied as to the correctness or usefulness of the material. Moreover, the project should be viewed as a snapshot in time. Inevitably, the further from the time of posting the less accurate the data will be.