Traffic Volume*
The University of Wisconsin Population Health Institute Model of Health
Use the model to explore the measures of how long and how well we live and what shapes these trends. Select a measure in the diagram or browse the list of all measures.
Measures marked with an asterisk (*) are not included in summary calculations for Population Health and Well-being or Community Conditions.
About
Average traffic volume per meter of major roadways in the county. The 2025 Annual Data Release used data from 2020 for this measure.
Residential proximity to motor vehicle traffic is associated with increased exposures to air and noise pollution. Based on the available evidence, negative health outcomes increase when people live closer to major roads and heavy traffic.1,2 This proximity to traffic has been associated with various health impacts for residents, particularly asthma exacerbation and possibly onset of asthma, as well as increased mortality rates.3,4 Living in proximity to traffic has also been associated with subclinical atherosclerosis (a key pathology underlying cardiovascular disease (CVD)), prevalence of CVD and coronary heart disease, incidence of myocardial infarction, and CVD mortality.5 Proximity to traffic can also mean increased noise exposure, which is linked to increased stress and poorer health outcomes.6
The University of Wisconsin Population Health Institute Model of Health
Use the model to explore the measures of how long and how well we live and what shapes these trends. Select a measure in the diagram or browse the list of all measures.
Measures marked with an asterisk (*) are not included in summary calculations for Population Health and Well-being or Community Conditions.
Data and methods
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Data Source
EJSCREEN: Environmental Justice Screening and Mapping Tool
EJSCREEN is an environmental justice mapping and screening tool that provides EPA with a nationally consistent dataset and approach for combining environmental and demographic indicators. EJSCREEN users choose a geographic area; the tool then provides demographic and environmental information for that area. All of the EJSCREEN indicators are publicly-available data. EJSCREEN simply provides a way to display this information and includes a method for combining environmental and demographic indicators into EJ indexes.
EJSCREEN includes:
Key Measure Methods
Traffic Volume is an average
Traffic Volume at the county level is calculated with EJScreen data by aggregating all the census block data within a county, and weighing by the number of people in the corresponding blocks. The measure is reported as the average count of vehicles per meter per day within 500 meters of a census block centroid (the center point of a census block), divided by distance in meters, presented as the population-weighted average of blocks in each county. The closest traffic is given more weight through inverse distance weighting. A highway with 16,000 Annual Average Daily Traffic (AADT) at 400 meters distance would result in a score of 16,000/400=40.
Caution should be used when comparing these estimates across states
States collect and report these data differently. Traffic counts are performed by state Departments of Transportation.
Measure limitations
This measure does not capture exposures that occur away from the block centroid (with the assumption that homes are equally distributed from the center of the census block).
While increased traffic volume in a county may be associated with harmful exposures, it may also be related to factors that positively influence health, such as commerce and employment opportunities. Residential proximity to roads can provide access to jobs, health care, food, recreational opportunities, and other benefits.
There is a relatively large data-year lag (about five years). One-third of the data is updated annually. Entirely new data is released every three years.
Numerator
The numerator is the average count of vehicles per meter per day within 500 meters of a census block centroid (the center point of a census block).
Denominator
The denominator includes all interstate, principal arterial, other National Highway System, and HPMS sample section roads.
Can This Measure Be Used to Track Progress
This measure is not appropriate for measuring progress.
Finding More Data
Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:
- Subcounty Area
Traffic volume can be analyzed at smaller geographies. EJScreen provides census block group estimates.
References
- Li C, Gao D, Samuel Cai YS, et al. Relationships of residential distance to major traffic roads with dementia incidence and brain structure measures: Mediation role of air pollution. Health Data Science. 2023;3:0091.
- Long D, Lewis D, Langpap, C. Negative traffic externalities and infant health: The role of income heterogeneity and residential sorting. Environmental Resource Economics. 2021;80:637-674.
- Baumann LM, Robinson CL, Combe JM, et al. Effects of distance from a heavily transited avenue on asthma and atopy in a periurban shantytown in Lima, Peru. Journal of Allergy and Clinical Immunology. 2012;127(4);875–882.
- Brunekreef B, Beelen R, Hoek G, et al. Effects of long-term exposure to traffic-related air pollution on respiratory and cardiovascular mortality in the Netherlands: The NLCS-AIR Study. Health Effects Research Report 139. 2009. https://www.healtheffects.org/publication/effects-long-term-exposure-traffic-related-air-pollution-respiratory-and-cardiovascular
- Hoffman B, Moebus S, Dragano N, et al, Heinz Nixdorf Recall Investigative Group. Residential traffic exposure and coronary heart disease: Results from the Heinz Nixdorf Recall Study. Biomarkers. 2009;14 Suppl 1:74-78.
- Sørensen M, Andersen ZJ, Nordsborg RB, et al. Road traffic noise and incident myocardial infarction: A prospective cohort study. Public Library of Science ONE. 2012;7(6):e39283.