MCDC News and Updates

DHC 2020 Profiles Applications

MCDC has added two new web applications for browsing the 2020 Census Demographic and Housing Characteristics (DHC) data.

In August 2023, we posted our “standard extracts” (also called profiles) of the DHC data — a set of just over 100 key variables from the ~9,000 table cells in the complete 2020 DHC file. This collection is located in the /data/dhc2020x directory and is also accessible from our data portal page.

The two new web apps facilitate browsing and extracting data from the profiles. The Census 2020 DHC Extract Assistant is a portal for accessing the collection of SAS datasets linked above. Essentially, it’s a easy-to-use, menu-driven front end for the Dexter data extractor, customized for the DHC Profiles collection. Users may use basic presets, or select the “advanced” option to pass through to the standard Dexter form for additional filters. The application can output web tables, CSV files, PDFs, SAS, and DBF data files.

The Census 2020 Profile Report application offers a simple interface for selecting up to four areas and generating a report listing all of the DHC profile values for each selected area. This is the easiest option for quick results.

Geographic coverage for both apps includes:

  • Census regions
  • Census divisions
  • States
  • Counties
  • Minor civil divisions (county subdivisions)
  • Places (cities, towns)
  • Metropolitan/micropolitan statistical areas
  • Census tracts
  • Census block groups
  • Census blocks
  • Urban areas (complete and state portions)
  • Congressional districts (118th Congress)
  • State senate districts
  • State house districts
  • Public use microdata areas (PUMAs)
  • ZIP Codes (ZCTAs) within state
  • Elementary school districts
  • Secondary school districts
  • Unified school districts

Geocorr and Other Application Updates (December 2023)

MCDC has a number of significant application updates to announce this month.

We added several new geography types to the Geocorr 2022 application, including the new core-based statistical areas (CBSAs, which include metropolitan and micropolitan statistical areas), metropolitan divisions, and combined statistical areas (CSAs), all of which were released by the Office of Management and Budget in July 2023. We also added the “new” Connecticut planning regions, and updated the urban areas to match those currently used by the Census Bureau.

The Connecticut planning regions pose a special problem for those using Geocorr to do county-level correlations. Earlier this year, the State of Connecticut finalized adoption of the State’s nine Councils of Governments (COGs), also called planning regions, as the county-equivalent geographic unit. Unfortunately for longitudinal county-level data users, the new regions don’t match the boundaries of the state’s eight counties that were previously used for census data tabulation.

In Geocorr, we’ve designated the planning regions as a new geography type that exists only in Connecticut. The unwanted consequence is that if you try to run a correlation using the new planning regions with any state besides CT, you’ll get an error. Thus, if you want to run a county-to-target correlation for many states or the whole nation, you’ll need to run it twice: once with all the states except CT, and then a second run to do the region-to-target correlation just for CT.

For more information about the CT changes, see Final Change to County Equivalents in Connecticut and the Final Federal Register Notice, Change to County Equivalents in the State of Connecticut.

Two other MCDC data applications have also been extensively updated: Population Estimates by Age and Population Trends with Demographics. The earlier versions of these apps relied on the so-called “bridged-race” single-year-of-age data from the National Center for Health Statistics (NCHS). Unfortunately, this very valuable data source was discontinued in 2020. These applications now use the annual population estimates published by the Census Bureau’s Population Estimates Program. Rather than single-year-of-age data, these estimates are aggregated into 18 five-year age “buckets” or cohorts. Therefore, it’s no longer possible to extract single years of age or make custom cohorts with the MCDC apps. Moreover, the census race classifications changed in 2000. Before then, there was not a separate race category for “Hawaiian and other Pacific Islander”. These populations were included in the “Asian” category prior to 2000. In addition, there was no category for “Two or more races” before 2000. Please exercise due caution when using pre-2000 population estimates from our applications and from the Census Bureau sources.

Please contact the MCDC web manager with any questions or comments.

Data Updates (September 2023)

We have a few routine data and application updates to announce this month.

  • On August 24, we posted new a zcta_master set to our geographic reference data collection. Zcta_master is a comprehensive ZCTA (ZIP Code Tabulation Area) resource with geographic correspondences and vintage 2021 ACS-based demographics. This new version uses ZCTAs as defined for the 2020 census. We have our usual SAS dataset, accessible via the Dexter data extraction tool, as well as a CSV file.
  • We found some minor errors in the new DHC data collection. Tract codes were missing final digits. These have been corrected.
  • Two of our workhorse data applications, uex2dex and Dexter, underwent substantial code updates and revisions.
  • Just this week, we published the 2022-vintage round of intercensal population estimates, released earlier this year. These include the CASRH (characteristics of age, sex, race, and Hispanic origin) data for all states, population ranks, housing unit estimates, and the new “curmoests” Excel file (Missouri current population estimates for the state, counties, subcounty units, and cities and towns).

Please contact the MCDC web manager with any questions or comments.

CAPS 2020 Is Finally Here!

MCDC is pleased to announce the launch of the newest version of our popular CAPS (Circular Area Profiles) applications.

CAPS 2020 is based on our new standard profiles (/data/dhc2020x), created earlier this month from the Demographic and Housing Characteristics (DHC) data from the 2020 decennial census, released in May 2023.

Much like the versions of CAPS based on previous decennial censuses, the new application reports just over 100 key variables (with corresponding percents) from the 2020 DHC file.

Functionally, CAPS 2020 is very similar to the older CAPS applications, although we did a lot of code updates under the hood.

Keen-eyed users may notice that 2010 populations reported by the CAPS 2020 app differ (sometimes significantly) from those reported for the same circles in CAPS 2010. In addition to normal population growth or decline, this is primarily due to the many changes in census geographies (blocks, block groups, and tracts) between 2010 and 2020. There is really no good way around this issue. The 2010 population, and the 2010-to-2020 change/percent change figures should be taken with a grain of salt.

DHC 2020 Standard Extracts Added to MCDC’s Collection

The Missouri Census Data Center has added our “standard extract” data based on the 2020 Demographic and Housing Characteristics (DHC) data. The collection is located in the /data/dhc2020x directory and is also accessible from our data portal page.

This is the collection of standard extracts, where we create a set of just over 100 key variables (with corresponding percents) from the ~9,000 table cells in the complete 2020 DHC file. For each state in the US (plus DC and PR), we have three data sets: one for census blocks, one for complete block groups (summary level 150), and one for “selected inventory” levels: state, county, county subdivision, place (complete and within-county), census tract, and ZIP code (ZCTA). For most geographies, we have added the 2010 population count and used it to calculate change over the decade.

This collection will be the basis for our forthcoming update to the CAPS (Circular Area Profiles) application using 2020 Census data. Users may expect to see the updated CAPS 2020 application in late August 2023.

Demographic and Housing Characteristics Data Added to MCDC’s Collection

The Missouri Census Data Center is pleased to announce that we’ve added the new Demographic and Housing Characteristics (DHC) data to our census data archives. The collection is located in the /data/dhc2020 directory and is also accessible from our data portal page.

The Demographic and Housing Characteristics data was released by the U.S. Census Bureau in May 2023. This is one of the main data products based on the 2020 decennial census.

As in 2010, there was only a short form questionnaire in 2020, so the DHC tables contain just basic demographics (age, sex, race / ethnicity, household types, etc.). The DHC is more or less equivalent to Summary File 1 from the 2010 and earlier censuses, and contains many of the same tables and variables as SF1, although there are some differences.

This data will become the source for MCDC’s DHC standard extract (or “profiles”) — our custom set of key variables for useful geographic area types — which should be ready within a month or so.

Story Map

Missouri Racial Demographics in Census 2010

race map illustration

About a year ago, the Missouri Census Data Center and MSDIS jointly published a story map detailing just a few of the many ways that Missouri benefits from a complete and accurate census. While the official counting period for Census 2020 has only just recently come to a close, we thought it would be interesting to take a look back at what Missouri looked like ten years ago, starting with racial demographics.

The maps in this application show the percentage of each Missouri census tract that identified as White, Black, Hispanic, Asian, American Indian, or Native Hawaiian. Unsurprisingly, the overwhelming majority of our census tracts are primarily occupied with Missourians who identified themselves as White. If you take a moment to compare the different categories, though, some very interesting patterns start to make themselves known.

Missouri Census Data Center frequently works with MSDIS on mapping and data projects. MSDIS is a spatial data retrieval and archival system offering many mapping resources, primarily focused on the state of Missouri.

Data Updates (Spring 2021)

We’ve updated many of our population-related applications and datasets over the past couple of months.

As always, please contact the MCDC website manager with any questions or comments.

Story Map

Women’s Role in the Missouri Workforce

Illustration by Ankita Ackroyd-Isales

Although Women’s History Month has come and gone, it is important to continue thinking about the various trends facing women at work. Here, we examine workforce participation. Women’s participation greatly increased throughout the second half of the twentieth century, but beginning in 2000, it began to stagnate and decrease.

This story map, designed by Abby Hunt of the Missouri Spatial Data Information Service (MSDIS), offers a county-level look at female participation in Missouri’s economy.

The Missouri Census Data Center frequently works with MSDIS on mapping and data projects. MSDIS is a spatial data retrieval and archival system offering many mapping resources, primarily focused on the state of Missouri.

ACS Report

Nearly a Quarter of Veterans Live in Rural Areas

About five million (24.1%) U.S. veterans 18 years and older lived in areas designated as rural between 2011 and 2015, according to a new report (Veterans in Rural America: 2011–2015) from the U.S. Census Bureau’s American Community Survey (ACS). The report found that when considering demographic and economic characteristics, rural veterans were similar to urban veterans except for their median household income and employment rates.

Rural veterans had median household incomes more similar to those of rural nonveterans than urban veterans ($53,554 compared with $52,161 and $59,674, respectively). The poverty rate for all rural veterans was 6.9%. This rate increased by level of rurality, to a high of 8.6% for veterans in completely rural counties. Level of rurality is based on the percentage of the county population living in rural areas.

Working-age rural veterans (18-64 years old) had an employment rate of 66.0%, lower than rural nonveterans and urban veterans (67.7% and 70.7%, respectively). The employment rate of rural veterans decreased as the level of rurality increased. Employed rural veterans, however, were more likely to work full time and year-round than rural nonveterans (81.6% compared with 71.5%).

These findings use the ACS 5-year statistics released on December 8. Other highlights include:


Just under half of all rural veterans lived in the South (45.9%), followed by 26.4% in the Midwest, 14.1% in the West, and 13.7% in the Northeast.


The median age of rural veterans was about 15 years higher than rural nonveterans and two years higher than urban veterans, and their age increased as the level of rurality increased. Rural veterans living in counties that were completely rural were the oldest, with a median age of 66.

Health Insurance

During the 2011-2015 period, 5.2% of all rural veterans and 15.4% of all rural nonveterans were not covered by any type of health insurance plan. Of the rural veterans who had health insurance during this period, 30.3% had private insurance only, 24.6% had public insurance only, and the remainder (45.1%) had a combination of private and public insurance.