About the traffic data

This page provides general information about the traffic data and measures developed by the Minnesota Environmental Public Health Tracking (MN EPHT) Program. For more information about these data, contact MNPH Data Access.

 

What do these data tell us?

  • The number and percent of Minnesota residents living within 300 meters (m) of busy roads.
  • How traffic exposures differ between areas with different poverty rates.

How can we use these data?

  • Residential proximity indicators can be used to estimate and compare traffic exposure across communities.

What can these data not tell us?

  • These traffic and poverty data are ecologic, meaning that they represent the average estimated exposure for the total number of residents in given area. These data are not estimates of individual residents’ poverty or income level or traffic exposures.
  • Traffic indicators cannot tell us:
    • How much or what type of air pollutants people living near busy roads may be exposed to.
    • About local traffic composition or patterns. For example, these data cannot tell us whether local traffic in one area has more or less high-emitting heavy trucks or diesel vehicles, or whether local roads have many signaled intersections where vehicles may be idling.

What are the data sources?

How are traffic exposure indicators calculated?

The number and percent of area residents are calculated using traffic volume and population data. These methods were developed by a workgroup of the Council of State and Territorial Epidemiologists.

  • Traffic volume is represented as the Annualized Average Daily Traffic (AADT) on roadway segments. AADT estimates use MN DoT traffic counts and modeled values to calculate an average daily count. Because roadways contain many segments, the AADT can change between different segments of a given roadway.
    • Busy roads are defined as segments with AADT > 10,000.
  • Buffer areas covering 300 m on either side of each busy road segment are used to estimate traffic exposure. For each census block group area – smaller than census tracts, which typically have 600 to 3,000 people – the area within the buffer is divided by the total area to calculate the percent area near busy roads.
    • The total block group population is multiplied by the percent area near busy roads to calculate the number of residents living near busy roads. The number of people living near busy roads is divided by the total block group population to calculate the percent of residents living near busy roads.
    • This process was repeated separately for zip code population estimates, because block groups may overlap multiple zip codes.
  • Block group-level number of residents living near busy roads and total population are summed to census tract and county areas to calculate traffic exposure estimates at multiple geographic units.

How are socioeconomic disparities determined?

  • Poverty categories are calculated based on the Federal Poverty Line (FPL) from the U.S. Census Bureau, which is also called the poverty threshold. Learn more about the poverty & income data.
  • The Poverty categories compare census tract poverty rates to the average poverty rate across Minnesota. Poverty categories were calculated by comparing the 90% confidence interval of poverty in each census tract to the 90% confidence interval for poverty statewide. Using difference from the mean methodology, census tracts were classified as significantly different from MN if the intervals did not overlap – either higher than the state mean (average) or lower than the state – or as no difference from the state if intervals overlapped.

What are the limitations of the data?

  • The zip code assigned to each census tract represents the primary zip code. Some census tracts may extend into multiple zip codes.
  • Our method for estimating traffic exposure assumes that population is spread uniformly across block group areas. Because this method uses the percent of block group area falling within 300 m of busy roads to estimate the number and percent of people living within 300 m of busy roads, there is some error in these estimates.

Where can I find more technical information about the data?