Motor vehicle crash deaths and Average temperature
Where Motor vehicle crash deaths is higher, Average temperature tends to be higher. The link is weak: +0.40 across 2,489 counties, on a scale from −1 (opposite) to +1 (in step). That figure compares places with the same population density, income and education, so those differences can't explain it. It holds inside states too. Measured separately within each of 36 states, the middle value of the link is -0.01.
Holds after adjusting
Every place, plotted
One dot for each place reporting both measures. Hover over or tap a dot to see its name and values. The thin line is the straight line that best fits the dots. The bold line, shown for counties, is the link after adjusting for density, income and education. A dot far from the lines is a place that does not follow the pattern.
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What each measure is
Motor vehicle crash deaths
Deaths in car and other motor vehicle crashes per 100,000 people.
County Health Rankings · County Health Rankings v039
Average temperature
The average temperature over the year, in degrees Fahrenheit, across the whole county or state. NOAA builds it from weather station readings, filling the gaps between stations with a map of the area, and averages the twelve monthly figures. One unusually warm or cold year can stand out, so look at several years.
NOAA NCEI nClimDiv · NOAA NCEI nClimDiv climdiv-tmpccy/tmpcst
Highest and lowest
Where each measure is highest and lowest among the places reporting both (2023), with the other measure beside it. This is shown for every size of place where both are published. Metro-area values are added up from their counties. A measure that cannot be added up across counties, such as a middle value (median), has no metro figure. Counts are shown per 1,000 residents, since raw totals would only list the largest places. Cities and towns and ZIP codes are shown where the Census survey or the CDC publishes them; most other sources stop at the county. They are shown for places of 5,000 residents or more, and only where the survey’s margin of error is small enough for the figure to be usable. The CDC publishes its health estimates for cities in a version adjusted for age, so places with older or younger people can be compared fairly, but not for ZIP codes.
Counties
By motor vehicle crash deaths
| Motor vehicle crash deaths | Average temperature | |
|---|---|---|
| Highest | ||
| Big Horn County, MT | 90 | 46.1 |
| Oglala Lakota County, SD | 86.4 | 48.9 |
| Todd County, SD | 80.6 | 48.7 |
| Jackson County, SD | 76.3 | 49.1 |
| Dewey County, SD | 68.3 | 46.4 |
| Lowest | ||
| New York County, NY | 2.71 | 57.4 |
| Arlington County, VA | 2.73 | 58.5 |
| Loudoun County, VA | 3.46 | 57.2 |
| Kings County, NY | 3.66 | 57.4 |
| Richmond County, NY | 3.83 | 57.5 |
By average temperature
| Motor vehicle crash deaths | Average temperature | |
|---|---|---|
| Highest | ||
| Monroe County, FL | 17.9 | 78.4 |
| Miami-Dade County, FL | 12.2 | 78 |
| Broward County, FL | 14 | 77.7 |
| Collier County, FL | 10.2 | 77.2 |
| Starr County, TX | 13.2 | 77.1 |
| Lowest | ||
| Fairbanks North Star Borough, AK | 12.4 | 28.7 |
| Matanuska-Susitna Borough, AK | 15.8 | 29.8 |
| Anchorage Municipality, AK | 8.85 | 32.8 |
| Kenai Peninsula Borough, AK | 14.7 | 33.8 |
| Sublette County, WY | 27.1 | 34.9 |
States
By motor vehicle crash deaths
| Motor vehicle crash deaths | Average temperature | |
|---|---|---|
| Highest | ||
| Mississippi | 25.5 | 66.7 |
| South Carolina | 20.8 | 64.3 |
| Alabama | 20.7 | 65.3 |
| Arkansas | 19.8 | 62.9 |
| New Mexico | 19.8 | 55.3 |
| Lowest | ||
| New York | 5.9 | 48.2 |
| Massachusetts | 6.01 | 51.3 |
| Rhode Island | 6.89 | 52.5 |
| New Jersey | 6.98 | 55.6 |
| Hawaii | 7.56 | 66.8 |
By average temperature
| Motor vehicle crash deaths | Average temperature | |
|---|---|---|
| Highest | ||
| Florida | 15.7 | 73.3 |
| Louisiana | 18 | 69.6 |
| Texas | 13.8 | 68.1 |
| Hawaii | 7.56 | 66.8 |
| Mississippi | 25.5 | 66.7 |
| Lowest | ||
| Alaska | 11.2 | 28.4 |
| Wyoming | 17 | 41.8 |
| North Dakota | 13.8 | 42 |
| Minnesota | 8.2 | 43.8 |
| Idaho | 13.8 | 43.8 |
Metro areas
By motor vehicle crash deaths
| Motor vehicle crash deaths | Average temperature | |
|---|---|---|
| Highest | ||
| Palatka, FL | 45.5 | 72.8 |
| Gallup, NM | 42.3 | 49.7 |
| Lumberton, NC | 41.4 | 64.1 |
| Show Low, AZ | 40.2 | 52.2 |
| Selma, AL | 39.2 | 67 |
| Lowest | ||
| Amherst Town-Northampton, MA | 5.04 | 50.4 |
| New York-Newark-Jersey City, NY-NJ | 5.04 | 54.8 |
| Bridgeport-Stamford-Danbury, CT | 5.09 | 53 |
| Boston-Cambridge-Newton, MA-NH | 5.14 | 51.5 |
| Pullman, WA | 5.54 | 51.1 |
By average temperature
| Motor vehicle crash deaths | Average temperature | |
|---|---|---|
| Highest | ||
| Key West-Key Largo, FL | 17.9 | 78.4 |
| Miami-Fort Lauderdale-West Palm Beach, FL | 13.1 | 77.5 |
| Naples-Marco Island, FL | 10.2 | 77.2 |
| Rio Grande City-Roma, TX | 13.2 | 77.1 |
| McAllen-Edinburg-Mission, TX | 9.43 | 77.1 |
| Lowest | ||
| Fairbanks-College, AK | 12.4 | 28.7 |
| Anchorage, AK | 10.8 | 30 |
| Jackson, WY-ID | 24 | 35.6 |
| Edwards, CO | 6.24 | 38.8 |
| Evanston, WY-UT | 14.6 | 39.1 |
Counties furthest from the pattern
Compared with the straight line that best fits all 2,491 counties: the five with far more average temperature than their motor vehicle crash deaths would suggest, and the five with far less.
| Motor vehicle crash deaths | Average temperature | |
|---|---|---|
| Above the line | ||
| Miami-Dade County, FL | 12.2 | 78 |
| Hidalgo County, TX | 9.43 | 77.1 |
| Collier County, FL | 10.2 | 77.2 |
| Cameron County, TX | 10.4 | 76.9 |
| Broward County, FL | 14 | 77.7 |
| Below the line | ||
| Big Horn County, MT | 90 | 46.1 |
| Fairbanks North Star Borough, AK | 12.4 | 28.7 |
| Matanuska-Susitna Borough, AK | 15.8 | 29.8 |
| Oglala Lakota County, SD | 86.4 | 48.9 |
| Mountrail County, ND | 53.8 | 41.5 |
Two series, one county
Both measures over time for a county you pick. The two charts are stacked, so they share only the years along the bottom. You can pick from the thirty largest counties reporting both. This panel covers 2010–2024, and a measure published only once shows as a single dot.
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Every version of the link
Each row measures the same link, from −1 to +1, in a different way. If the rows mostly agree, the link does not depend on one choice of method.
| Before adjusting for anything | +0.331 | 2,489 counties reporting both |
| After adjusting for density, income and education | +0.397 | the part of the link that is not just how urban, rich and educated a place is |
| Also adjusting for population size | +0.397 | size taken out as well as density |
| Also comparing only within each state | +0.081 | each county is compared only with others in its own state, so this is no longer a comparison between states |
| Giving bigger counties more weight | +0.415 | the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 280 equally weighted counties |
| Middle value inside single states | -0.012 | the link worked out inside each of 36 states with at least 20 counties reporting |
| Using ranks, after adjusting | +0.478 | uses each county’s rank, not its value, so a few extreme counties cannot create the link |
How much to believe it
Could it be chance?
The p-value is the chance of seeing a link this strong if there were really none. A value of 0.05 or less means the link is unlikely to be chance. Very small values are written in short form: 3.1e-16 means 0.00000000000000031, and the bigger the number after “e-”, the smaller the value. Treating every county as a separate case gives p = 1.2e-94. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 1.5e-7. The site tested 24,090 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 1.0e-93.
Do nearby places look alike?
Moran’s I measures how much nearby places look alike: 0 means no map pattern, and higher means neighbours are more similar. For the part of each county that the adjustment leaves unexplained, it is +0.76 (p = 0.001). That unexplained part still clusters on the map. So some regional factor shared by both measures is not accounted for.
Did they change together?
The figures above compare counties at one moment. This asks a different question: where motor vehicle crash deaths rose most, did average temperaturemove too? Each county’s change is compared with the average change in its own state. That takes out ups and downs that hit a whole region at once. Each change is the gap between two estimates that both contain some error. That error pulls these links towards zero, so a weak one is weak partly for that reason. The q column shows whether a link could be a fluke, allowing for the many pairs tested: 0.05 or less means it is unlikely to be chance.
| Period | Counties | Change together | Within states | q |
|---|---|---|---|---|
| 2014–2019 the main test: each Census survey figure averages five years, and these two do not overlap; before the pandemic | 2,380 | +0.00 | +0.01 | 0.954 |
| 2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years | 2,410 | -0.14 | -0.02 | 0.507 |
Measured over the nearest years published: Motor vehicle crash deaths: 2013–2019 for the 2014–2019 row; Motor vehicle crash deaths: 2019–2022 for the 2019–2023 row.
Over the main period, any link between the changes could easily be chance. How change is measured.
Related pairs
- Average temperature and Winter nightly low — +0.91
- Average temperature and Summer daily high — +0.88
- Motor vehicle crash deaths and Years of potential life lost — +0.56
- Motor vehicle crash deaths and Premature mortality — +0.54
- Adults under 65 without health insurance and Average temperature — +0.53
- Child mortality and Motor vehicle crash deaths — +0.53
- High cholesterol and Average temperature — +0.52
- Motor vehicle crash deaths and Life expectancy — -0.51
Association only. Nothing here shows that either measure changes the other. This describes counties, not the people in them. Two measures going together across places does not mean the same people have both. How the US county data works · Explore Motor vehicle crash deaths and Average temperature