Environmental Public Health Tracking: Community Design Data

Wisconsin Tracking provides information about community design in Wisconsin. Community design is all of the human-made elements of a community that make-up the physical characteristics of that community.

These elements include:

  • Buildings, such as schools, workplaces, and homes
  • Roads
  • Parks and recreation areas
  • Transportation systems
  • Places to buy food

Access the community design data

 

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Interested in environmental health data?

Join the environmental health listserv by sending an email to DHS Environmental Public Health Tracking with the subject line "Join envhealth listserv."


Frequently asked questions

How is community design related to public health?

The way we design and build our communities affects our physical and mental health. Healthy community design is planning and designing communities that make it easier for people to live healthy lives. Healthy community design can provide many advantages:

  • Promote physical activity
  • Improve air quality
  • Lower risk of injuries
  • Improve healthy eating habits
  • Increase social connection and sense of community
  • Reduce contributions to climate change

Public health problems in the U.S., such as motor vehicle-related injuries, obesity, physical inactivity, and breathing and heart problems related to air pollution are all influenced by the design of our communities. Designing communities that encourage healthy choices is critical to improving the health and quality of life of community members.

Why does Wisconsin Tracking track community design?

Gathering data on elements of community design, such as motor vehicle-related fatalities and types of transportation to work, can help inform community design decisions. Multiple agencies monitor these elements and related environmental and health impacts to make sure that people live in healthy environments.

By tracking these elements of community design we are better able to assess whether people have access to:

  • Public transportation, like buses or trains
  • Sidewalks and bike paths
  • Stores that sell food, especially those stocked with fresh fruits and vegetables
  • Safe and energy efficient housing
  • Parks and public spaces

What is the data source?

The community design data used on the Wisconsin Tracking Portal are developed from a combination of resources.

Access to parks and public elementary schools

Park data come from NAVTEQ, a commercial company that provides GIS data. School data come from the National Center for Educational Statistics which provides street addresses for each school record.

Motor vehicle-related fatalities

The motor vehicle-related fatality data are available from the Fatality Analysis Reporting System (FARS) collected by the National Highway Traffic Safety Administration (NHTSA). FARS contains data on all vehicle crashes in the United States that occur on a public roadway and involve a fatality.

Proximity of population to schools and highways

These data were created using data from the National Center for Education Statistics (NCES) and road network data from NAVTEQ, a commercial company that provides GIS data.

Commute time

The types of transportation to work data were developed from the U.S. Census Bureau's American Community Survey (ACS). ACS collects data on demographic characteristics, family and relationships, income, health insurance, education, veteran status, where people work and how they get there, and homeowner status. This information is similar to the Census, but it is collected every year rather than every 10 years.

Which topics does Wisconsin Tracking have for community design?​

Please note that not all topics are available at both the census tract and county geographies.

  • Access to parks and public elementary schools
    • Number of children aged 5 to 9 years living within a half mile of a public elementary school
    • Number of people living within a half mile of a park
    • Percent of population aged 5 to 9 years living within a half mile of a public elementary school
    • Percent of population living within a half mile of a park​
  • Commute time
    • Average one-way commute time (minutes) for workers 16 years and older for all travel modes
    • Number of workers 16 years and older driving 20+ minutes to work (car, truck, van)
    • Number of workers 16 years and older taking public transportation 45+ minutes to work
    • Number of workers 16 years and older walking 10+ minutes to work
    • Percent of workers 16 years and older driving 20+ minutes to work (car, truck, van)
    • Percent of workers 16 years and older taking public transportation 45+ minutes to work
    • Percent of workers 16 years and older walking 10+ minutes to work
  • Motor vehicle-related fatalities
    • Number of fatal motor vehicle crashes
    • Percent of fatal motor vehicle crashes involving cyclists or pedestrians
    • Rate of fatal motor vehicle crashes per 100,000 population
  • Proximity of population and schools to highways
    • Number of people living within 150m of a highway
    • Number of public schools located within 150m of a highway
    • Percent of people living within 150m of a highway
    • Percent of public schools located within 150m of a highway​

What are some considerations for interpreting the data?​

There are numerous considerations to keep in mind when interpreting the data. Please visit the Centers for Disease Control and Prevention (CDC) National Tracking Program Indicators and Data webpage for additional information.

Select the content area from the drop down list, e.g., Community Design. Then select the specific indicator you are interested in from the drop down list, e.g., "Access to Parks and Public Elementary Schools."

Where can I learn more about community design?

Community design data details

Data details

Access to parks and public elementary schools

Number of children ages 5 to 9 years living within a half mile of a public elementary school

A list of public schools was provided by the National Center for Educational Statistics. School Description includes regular, special education, and other/alternative; Special School Type includes charter and magnet schools; and Grade-Span includes pre-kindergarten to 4th grade. All half-mile buffers were restricted by county. If a half-mile buffer crossed county or state boundaries, only the proportion of the population residing within the same county as the school contributed to the estimate.

Number of people living within a half mile of a park

Number of people within a buffer of a half mile radius of a park was determined at the census tract level. These estimates are aggregated to county, and state levels. Park data are from NAVTEQ (2010), Esri StreetMap Premium HERE (2016), and PAD-US (2015), providers of Geographic Information Systems (GIS) data. The underlying map database is a compilation of first-hand observation of geographic features and third-party data sources. 2010 and 2015 park data are from different sources; data for these measures are, therefore, not comparable across years. There are no advanced view options for 2015 as the underlying age, race, and race/ethnicity data were unavailable at the time of calculation. If a half- or one-mile buffer crossed a county or state boundary, the population residing within this buffer is estimated and attributed to the county within which the population resides (not the county within which the park is located).

Percent of children ages 5 to 9 years living within a half mile of a public elementary school

A list of public schools was provided by the National Center for Educational Statistics. School Description includes regular, special education, and other/alternative; Special School Type includes charter and magnet schools; and Grade-Span includes pre-kindergarten to 4th grade. All half-mile buffers were restricted by county. If a half-mile buffer crossed county or state boundaries, only the proportion of the population residing within the same county as the school contributed to the estimate.

Percent of people living within a half mile of a park

Percentages of people living within a half mile of the park boundary are calculated for the census tract, county, state, and national levels. The percentage uses the estimated numbers of people as determined via the buffer analysis and then divides this numerator by the total number of people in each geographic unit. Park data are from NAVTEQ (2010), Esri StreetMap Premium HERE (2016), and PAD-US (2015), providers of (GIS data. The underlying map database is a compilation of first-hand observation of geographic features and third-party data sources. 2010 and 2015 park data are from different sources; data for these measures are, therefore, not comparable across years. There are no advanced view options for 2015 as the underlying age, race, and race/ethnicity data were unavailable at the time of calculation. If a half- or one-mile buffer crossed county or state boundary, the population residing within this buffer is estimated and attributed to the county within which the population resides (not the county within which the park is located).

Commute time

Average one-way commute time (minutes) for workers 16 years and older for all travel modes

Data obtained from the American Community Survey (ACS) by the U.S. Census Bureau. ACS is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. However, because ACS data are based on a sample, they are subject to sampling variability and include a range of uncertainty. This dataset only captures commute time to work, and does not capture the distance of the trip. Individual preference and economics also influences commute choices, not just community design.

Number of workers 16 years and older driving 20+ minutes to work (car, truck, van)

Data obtained from the ACS by the U.S. Census Bureau. ACS is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. However, because ACS data are based on a sample, they are subject to sampling variability and include a range of uncertainty. This dataset only captures commute time to work, and does not capture the distance of the trip. Individual preference and economics also influences commute choices, not just community design. Measures are based on the national median commute time for 2011-2015 for each particular mode of transportation. Advanced view options are based on the national 75th (30 minute) and 90th (45 minute) percentile commute times.

Number of workers 16 years and older taking public transportation 45+ minutes to work

Data obtained from the ACS by the U.S. Census Bureau. ACS is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. However, because ACS data are based on a sample, they are subject to sampling variability and include a range of uncertainty. This dataset only captures commute time to work, and does not capture the distance of the trip. Individual preference and economics also influences commute choices, not just community design. Measures are based on the national median commute time for 2011-2015 for each particular mode of transportation. Advanced view options are based on the national 75th and 90th percentile commute times.

Number of workers 16 years and older walking 10+ minutes to work

Data obtained from the ACS by the U.S. Census Bureau. ACS is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. However, because ACS data are based on a sample, they are subject to sampling variability and include a range of uncertainty. This dataset only captures commute time to work, and does not capture the distance of the trip. Individual preference and economics also influences commute choices, not just community design. Measures are based on the national median commute time for 2011-2015 for each particular mode of transportation. Advanced view options are based on the national 75th and 90th percentile commute times.

Percent of workers 16 years and older driving 20+ minutes to work (car, truck, van)

Data obtained from the ACS by the U.S. Census Bureau. ACS is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. However, because ACS data are based on a sample, they are subject to sampling variability and include a range of uncertainty. This dataset only captures commute time to work, and does not capture the distance of the trip. Individual preference and economics also influences commute choices, not just community design. Measures are based on the national median commute time for 2011-2015 for each particular mode of transportation. Advanced view options are based on the national 75th and 90th percentile commute times.

Percent of workers 16 years and older taking public transportation 45+ minutes to work

Data obtained from the ACS by the U.S. Census Bureau. ACS is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. However, because ACS data are based on a sample, they are subject to sampling variability and include a range of uncertainty. This dataset only captures commute time to work, and does not capture the distance of the trip. Individual preference and economics also influences commute choices, not just community design. Measures are based on the national median commute time for 2011-2015 for each particular mode of transportation. Advanced view options are based on the national 75th and 90th percentile commute times.

Percent of workers 16 years and older walking 10+ minutes to work

Data obtained from the ACS by the U.S. Census Bureau. ACS is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. However, because ACS data are based on a sample, they are subject to sampling variability and include a range of uncertainty. This dataset only captures commute time to work, and does not capture the distance of the trip. Individual preference and economics also influences commute choices, not just community design. Measures are based on the national median commute time for 2011-2015 for each particular mode of transportation. Advanced view options are based on the national 75th and 90th percentile commute times.

Motor vehicle-related fatalities

Number of fatal motor vehicle crashes

Data were obtained from the National Highway Traffic Safety Administration's Fatality Analysis Reporting System (FARS). U.S. Census Bureau intercensal population estimates were used to calculate rates. The number of crashes was calculated by summing the number of distinct fatal crashes from annual FARS datasets for each five-year period. FARS does not capture information on crashes in driveways, parking lots, or off public roadways. Crash data were geocoded to census tracts using 2010 boundaries and aggregated to county or state level. Accidents occurring on census tract boundaries were randomly assigned to an adjacent census tract.

Percent of all fatal motor vehicle crashes involving cyclists or pedestrians

Data were obtained from the National Highway Traffic Safety Administration's Fatality Analysis Reporting System (FARS). U.S. Census Bureau intercensal population estimates were used to calculate rates. Percentages were calculated by dividing the number of distinct crashes involving bicyclists or pedestrians by the total number of distinct fatal crashes, then multiplying by 100.

Rate of fatal motor vehicle crashes per 100,000 population

Data were obtained from the National Highway Traffic Safety Administration's Fatality Analysis Reporting System (FARS). U.S. Census Bureau intercensal population estimates were used to calculate rates. Rates were calculated by dividing the number of fatal motor vehicle crashes by the sum of the intercensal populations for each five-year period, then multiplying by 100,000.

Proximity of population and schools to highways

Number of people living within 150m of a highway

This measure was created using data from the National Center for Education Statistics (NCES) and road network data from 2010, from NAVTEQ, a commercial company. Class 1 and class 2 roads were selected to represent major highways in the United States. The Federal Highway Administration (FHWA) Functional Classification system categorizes interstates as class 1 and freeways and expressways as class 2. Esri ArcGIS 10.1 software was used to calculate the number of schools within a 150m buffer around all class 1 and class 2 roads. Population estimates were based on population counts within census tracts made publicly available by the U.S. Census (2010, 100% count data). The proportion of each census tract included within the buffer area was calculated and summed from the census tract level to the county level.

Number of public schools located within 150m of a highway

This measure was created using data from the National Center for Education Statistics (NCES) and road network data from 2010, from NAVTEQ, a commercial company. Class 1 and class 2 roads were selected to represent major highways in the United States. The Federal Highway Administration (FHWA) Functional Classification system classifies interstates as class 1 and freeways and expressways as class 2. Esri ArcGIS 10.1 software was used to calculate the number of schools within a 150m buffer around all class 1 and class 2 roads. Population estimates were based on population counts within census tracts made publicly available by the U.S. Census (2010, 100% count data). The proportion of each census tract included within the buffer area was calculated and summed from the census tract level to the county level.

Percent of population living within 150m of a highway

This measure was created using data from the National Center for Education Statistics (NCES) and road network data from 2010, from NAVTEQ, a commercial company. Class 1 and class 2 roads were selected to represent major highways in the United States. The Federal Highway Administration (FHWA) Functional Classification system classifies interstates as class 1 and freeways and expressways as class 2. Esri ArcGIS 10.1 software was used to calculate the number of schools within a 150m buffer around all class 1 and class 2 roads. Population estimates were based on population counts within census tracts made publicly available by the U.S. Census (2010, 100% count data). The proportion of each census tract included within the buffer area was calculated and summed from the census tract level to the county level. Percent of population living within 150m of a highway was calculated using the number of people living within 150m of a highway as the numerator and the total population in a county as the denominator.

Percent of public schools located within 150m of a highway

This measure was created using data from the National Center for Education Statistics (NCES) and road network data from 2010, from NAVTEQ, a commercial company. Class 1 and class 2 roads were selected to represent major highways in the United States. The Federal Highway Administration (FHWA) Functional Classification system classifies interstates as class 1 and freeways and expressways as class 2. Esri ArcGIS 10.1 software was used to calculate the number of schools within a 150m buffer around all class 1 and class 2 roads. Population estimates were based on population counts within census tracts made publicly available by the U.S. Census (2010, 100% count data). The proportion of each census tract included within the buffer area was calculated and summed from the census tract level to the county level. Percent of public schools (grades pre-K to 4th) sited within 150m of a highway was calculated using the number of public schools (grades pre-K to 4th) sited within 150m of a highway as the numerator and the total number of public schools in a county as the denominator.

Glossary and definitions of terms

Explore definitions and explanations of terminology found on the portal, like age-adjusted rate and confidence intervals.

Last Revised: July 21, 2022