MCDC News and Updates

Map of the Month

Food Insecurity for Missouri’s Children

One of the most significant changes to daily life that we’ve seen from Missouri’s response to the Coronavirus is the closure of many public school systems. While no state-level order has been put into action, cities and counties from across Missouri have closed their doors and moved to online education. This, in turn, has brought the topic of childhood food insecurity to the forefront of many discussions across Missouri.

This web map, designed by the Missouri Spatial Data Information Service (MSDIS), illustrates the percentage of children, by county, who are faced with such a challenge. With schools now closed for an unknown amount of time, it is more important than ever to keep the reality of childhood hunger in mind.

Missouri childhood food insecurity

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.

Map of the Month

Missourians Over 60 and Local Healthcare Resources

As the Coronavirus becomes a global threat, older Missourians are increasingly at risk of contracting this potent disease. This web map, designed by the Missouri Spatial Data Information Service (MSDIS), features county-level demographic data from the Missouri Census Data Center that highlights Missouri’s over-60 population, as well as several datasets from the Missouri Department of Health and Senior Services that highlight some of the healthcare resources that are available to them.

Missourians over 60
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.

Data Updates (February 2020)

Many relatively minor updates this winter:

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

Story Map

Missouri and the 2020 Census

2020 will be more than just another new year in the United States. In addition to marking the beginning of a new decade and heralding another presidential election, 2020 will bring with it another decennial census.

What is the census, though? And why is it so important?

Our colleagues at the Missouri Spatial Data Information Service built a story map exploring the 2020 Census and its consequences for Missouri.

The 2020 Census in Missouri

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.

Data Updates (June 2019)

This month sees the updates of many of our population-related applications and datasets.

  • New data for 2018 added to State/county annual population change, Population trends with demographics, and Population estimates by age applications.
  • NCHS (National Center for Health Statistics) “bridged race” estimates added for 2018, including state- and county-level numbers with detail by single years of age, race, sex, and hispanic origin. These datasets are located in the nchsbri directory of our data archive.
  • Population and components of change estimates: 2018 data added for Missouri and USA. These datasets are located in the popests directory of our data archive. The uscom18 dataset includes estimates of the total population of counties, states, and the US for July 1 of each year from 2010 to 2018, along with annual birth, death, international and domestic migration estimates (the components of change). The ushuest2018 dataset includes estimates of total housing units by county for each year from 2010 through 2018. The ussc18 dataset includes estimates of the total population of places (cities) and other subcounty geographic areas for each year starting with 2010 and ending with 2018. All of these datasets have corresponding Missouri-only versions, e.g. mohuest2018 for MO housing unit estimates.
  • Curmoests (current MO estimates): This Excel spreadsheet includes the latest available (2018) population estimates for Missouri counties and places (incorporated cities).

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

Application and Data Updates (April 2019)

Story Map

Missouri Voter Turnout in General Elections Since 2000

How many people in Missouri actually exercise their right to vote?

As Missourians get ready to head back to the polls for the 2018 midterm election, our colleagues at the Missouri Spatial Data Information Service built a story map showing voter turnout for previous Missouri general elections from 2000 through 2016.

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.

Map of the Month

Missouri Educational Attainment and Income

Educational attainment is an established, validated predictor of income. This map-of-the-month series looks at the distribution of both characteristics in Missouri’s counties. Derived from the U.S. Census Bureau, American Community Survey (ACS) 2012-2016 5-year data, Missouri households are mapped here by level of educational attainment and median household income, while a bivariate choropleth map displays the variable impact of earning less than a high school diploma on household income.

Education vs. Income in Missouri, 2012-2016

The bar chart, based on the 2016 ACS 1-year release, establishes the relative distribution of median household income by level of education. While the overall median household in Missouri realizes approximately $36,000 in income, the median household in Missouri headed by someone without a high school diploma or GED is closer to $20,000.  Completing high school results in a bump of roughly  $10,000, with the median household income of high school graduates a little more than $30,000. Completing some college or an associate’s (2-year degree) results in an incremental increase in household median income to the mid-$30,000 range, but it is completion of a bachelor’s degree or greater that accelerates median household income into the mid-$40,000 to mid-$50,000 range annually.

Educational attainment, however, is not the only driver of income. Access to workforce opportunities and proximity to infrastructure impacts potential income too. Review of the Median household income map reveals the influence of infrastructure investment and population density in driving up wages and income, as seen in the counties shaded in the darkest green.  It’s also interesting to visually note the geographically layered gradation of quantiles of the state with the I-70 highway corridor connecting Missouri’s relatively high income metropolitan areas, and the agricultural northern tier of counties falling into the mid-quantiles, while lower income households concentrate in the southern tier of counties (with exception of income concentrating in the Springfield metro area).

Not surprisingly, a close look at the concentrations of level of educational attainment (the blue-scale maps), correlate at the county level to the median household income map fairly predictably: Populations with higher concentrations of higher levels of education also have higher median household incomes.

The bivariate choropleth map, Median household income by percent of adults with less than high school diploma or GED, lets us see the outliers as well as validating the correlations we anticipated. For example, the truer the shade of blue a county is coded, the higher the percent of the adult population without a high school diploma/GED and the higher median household income indicating some combination of higher wage job and income opportunities relative to educational qualifications. We see these on the periphery of the other end of the spectrum, counties with higher median household incomes and the lowest rates of households with low educational attainment, suggesting “bedroom” communities. Further study to confirm this pattern might include looking at patterns of in-migration over time and commuting patterns.