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Share White, not Hispanic and Motor vehicle crash deaths

Where Share White, not Hispanic is higher, Motor vehicle crash deaths tends to be lower. The link is weak: -0.34 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 +0.20.

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

Share White, not Hispanic

The percentage of residents who are White alone and not Hispanic or Latino. It comes from a table that sorts people by both race and Hispanic origin, so nobody is counted twice. The eight race and ethnicity shares here add up to exactly 100% in every county.

Census ACS 5-year · ACS table B03002_003, divided by total population

Motor vehicle crash deaths

Deaths in car and other motor vehicle crashes per 100,000 people.

County Health Rankings · County Health Rankings v039

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 share White, not Hispanic

Share White, not HispanicMotor vehicle crash deaths
Highest
Magoffin County, KY97.6%39
Dickenson County, VA97.6%21
Holmes County, OH97.4%9.73
Boone County, WV97.2%19.1
Clay County, WV97%39.1
Lowest
Starr County, TX2.15%13.2
Maverick County, TX2.84%13.3
Webb County, TX3.57%9.1
Hidalgo County, TX6.08%9.43
Zavala County, TX6.11%19.1

By motor vehicle crash deaths

Share White, not HispanicMotor vehicle crash deaths
Highest
Big Horn County, MT27%90
Oglala Lakota County, SD6.63%86.4
Todd County, SD8.12%80.6
Jackson County, SD36.2%76.3
Dewey County, SD20.2%68.3
Lowest
New York County, NY46.3%2.71
Arlington County, VA58.8%2.73
Loudoun County, VA52.1%3.46
Kings County, NY36.2%3.66
Richmond County, NY56.6%3.83
States

By share White, not Hispanic

Share White, not HispanicMotor vehicle crash deaths
Highest
Maine90.6%12.6
Vermont90.6%10.4
West Virginia90.2%15.9
New Hampshire87.5%9.05
Montana84.1%17.9
Lowest
Hawaii21.1%7.56
California34.6%10.9
New Mexico36.5%19.8
District of Columbia36.6%6.39
Texas39.9%13.8

By motor vehicle crash deaths

Share White, not HispanicMotor vehicle crash deaths
Highest
Mississippi55.4%25.5
South Carolina62.2%20.8
Alabama63.8%20.7
Arkansas68.4%19.8
New Mexico36.5%19.8
Lowest
New York53.4%5.9
Massachusetts67.8%6.01
District of Columbia36.6%6.39
Rhode Island69.1%6.89
New Jersey51.9%6.98
Metro areas

By share White, not Hispanic

Share White, not HispanicMotor vehicle crash deaths
Highest
Pikeville, KY95.3%27.3
Greenville, OH95.1%16.9
Effingham, IL94.9%12.1
Warren, PA94.9%12.8
Wapakoneta, OH94.8%10.6
Lowest
Rio Grande City-Roma, TX2.15%13.2
Eagle Pass, TX2.84%13.3
Laredo, TX3.57%9.1
McAllen-Edinburg-Mission, TX6.08%9.43
Gallup, NM8.01%42.3

By motor vehicle crash deaths

Share White, not HispanicMotor vehicle crash deaths
Highest
Palatka, FL70%45.5
Gallup, NM8.01%42.3
Lumberton, NC23.6%41.4
Show Low, AZ42.4%40.2
Selma, AL26.8%39.2
Lowest
Amherst Town-Northampton, MA81.3%5.04
New York-Newark-Jersey City, NY-NJ43.5%5.04
Bridgeport-Stamford-Danbury, CT57.6%5.09
Boston-Cambridge-Newton, MA-NH66.6%5.14
Pullman, WA73.8%5.54
Cities and towns — Motor vehicle crash deaths is not published for cities and towns

By share White, not Hispanic

Share White, not HispanicMotor vehicle crash deaths
Highest
Treasure Lake CDP, PA99.2%—
Litchfield city, IL98.8%—
Cicero town, IN98.2%—
East Harwich CDP, MA98.1%—
Wellston city, OH98.1%—
Lowest
Mecca CDP, CA0%—
Earlimart CDP, CA0%—
Yabucoa zona urbana, PR0%—
San Lorenzo zona urbana, PR0%—
San Isidro comunidad, PR0%—
ZIP codes — Motor vehicle crash deaths is not published for ZIP codes

By share White, not Hispanic

Share White, not HispanicMotor vehicle crash deaths
Highest
ZIP 62056 (Montgomery County, IL)99%—
ZIP 47558 (Daviess County, IN)98.9%—
ZIP 47452 (Orange County, IN)98.7%—
ZIP 44627 (Holmes County, OH)98.6%—
ZIP 24609 (Tazewell County, VA)98.5%—
Lowest
ZIP 00952 (Sabana Seca comunidad, PR)0%—
ZIP 00782 (Comerío Municipio, PR)0%—
ZIP 00780 (Ponce Municipio, PR)0%—
ZIP 00731 (Ponce Municipio, PR)0%—
ZIP 00723 (Patillas Municipio, PR)0%—

Counties furthest from the pattern

Compared with the straight line that best fits all 2,491 counties: the five with far more motor vehicle crash deaths than their share White, not Hispanic would suggest, and the five with far less.

Share White, not HispanicMotor vehicle crash deaths
Above the line
Big Horn County, MT27%90
Oglala Lakota County, SD6.63%86.4
Todd County, SD8.12%80.6
Jackson County, SD36.2%76.3
Owsley County, KY93.3%66.6
Below the line
Bronx County, NY8.82%4.29
Queens County, NY23.6%3.98
Hudson County, NJ28.1%4.38
Kings County, NY36.2%3.66
New York County, NY46.3%2.71

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-0.1922,489 counties reporting both
After adjusting for density, income and education-0.342the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.399size taken out as well as density
Also comparing only within each state-0.220each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.249the 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+0.200the link worked out inside each of 36 states with at least 20 counties reporting
Using ranks, after adjusting-0.266uses 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 = 3.4e-69. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.000. The site tested 20,910 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 2.2e-68.

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 +0.28 (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 share white, not hispanic rose most, did motor vehicle crash deathsmove 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.

PeriodCountiesChange togetherWithin statesq
2014–2019 the main test: each Census survey figure averages five years, and these two do not overlap; before the pandemic2,379-0.07-0.070.041
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years2,409+0.11+0.100.007

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.

In counties where one changed more, the other tended to move the opposite way, compared with other counties in the same state (r = -0.07). It does not hold clearly in the second period, which spans the pandemic. How change is measured.

Related pairs

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 Share White, not Hispanic and Motor vehicle crash deaths