National Neighborhood Data Archive (NaNDA): Urbanicity by Census Tract, United States, 2010 (ICPSR 38606)
Version Date: Dec 12, 2022 View help for published
Principal Investigator(s): View help for Principal Investigator(s)
Stephanie Miller, University of Michigan;
Robert Melendez, University of Michigan. Institute for Social Research;
Megan Chenoweth, University of Michigan. Institute for Social Research
Series:
https://doi.org/10.3886/ICPSR38606.v1
Version V1
Summary View help for Summary
This dataset contains measures of the urban/rural characteristics of each census tract in the United States. These include proportions of urban and rural population, population density, rural/urban commuting area (RUCA) codes, and RUCA-based four- and seven-category urbanicity scales.
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Funding View help for Funding
Subject Terms View help for Subject Terms
Geographic Coverage View help for Geographic Coverage
Smallest Geographic Unit View help for Smallest Geographic Unit
census tract
Distributor(s) View help for Distributor(s)
Time Period(s) View help for Time Period(s)
Date of Collection View help for Date of Collection
Data Collection Notes View help for Data Collection Notes
- The data and documentation for National Neighborhood Data Archive (NaNDA): Urbanicity by Census Tract, United States, 2010 was originally deposited in openICPSR.
- For additional information, see the National Neighborhood Data Archive (NaNDA).
Study Purpose View help for Study Purpose
The purpose of the study is to measure the urbanicity of each census tract in the United States.
Study Design View help for Study Design
The research team obtained data from the 2010 decennial census and the U.S. Department of Agriculture (USDA) Economic Research Service (2019) to create measures of urbanicity. The team used population data for urbanized areas (population of 50,000 or more), urban clusters (population between 2,500 and 50,000), and rural areas (population less than 2,500) for each census tract from the Census Bureau. The team also obtained rural/urban commuting area (RUCA) primary and secondary codes and population density figures from USDA. Urban and rural population figures are missing for Alaska, Hawaii, and Puerto Rico.
Time Method View help for Time Method
Universe View help for Universe
All census tracts in the United States, including Puerto Rico.
Unit(s) of Observation View help for Unit(s) of Observation
Data Source View help for Data Source
United States Census Bureau. "2010 Census of Population and Housing Summary File 1," 2010. https://www2.census.gov/census_2010/04-Summary_File_1
United States Department of Agriculture Economic Research Service. "2010 Rural-Urban Commuting Area Codes (Revised 7/3/2019)," 2019. https://www.ers.usda.gov/webdocs/DataFiles/53241/ruca2010revised.xlsx?v=9541.3
Data and documentation were originally deposited in openICPSR project 130452.
Data Type(s) View help for Data Type(s)
Description of Variables View help for Description of Variables
Multiple measures of urbanicity were used:
- Urbanized areas (UAs), urban clusters (UCs), and rural area populations for each census tract, and percentage of population residing within UAs/UCs and rural areas
- Rural/urban commuting area (RUCA) codes, which classify census tracts based on population density and commuting patterns
- Population density, as a four-category item and a seven-category item
Original Release Date View help for Original Release Date
2022-12-12
Version History View help for Version History
2022-12-12 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:
- Checked for undocumented or out-of-range codes.
Notes
The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.