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Motor vehicle crash deaths and Adult income rank of children raised poor here

Where Motor vehicle crash deaths is higher, Adult income rank of children raised poor here tends to be lower. The link is weak: -0.32 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

Adult income rank of children raised poor here

Where children who grew up here with poor parents ended up as adults, ranked against everyone in the country by income, on a scale from 0 to 1. A value of 0.5 would mean that on average they reached the middle of the national income ladder.

Opportunity Atlas · Opportunity Insights kfr_pooled_pooled_p25

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 deathsAdult income rank of children raised poor here
Highest
Big Horn County, MT900.401
Oglala Lakota County, SD86.40.248
Todd County, SD80.60.302
Jackson County, SD76.30.484
Dewey County, SD68.30.323
Lowest
New York County, NY2.710.419
Arlington County, VA2.730.463
Loudoun County, VA3.460.495
Kings County, NY3.660.423
Richmond County, NY3.830.481

By adult income rank of children raised poor here

Motor vehicle crash deathsAdult income rank of children raised poor here
Highest
Mountrail County, ND53.80.616
Stark County, ND15.30.614
Nemaha County, KS25.30.614
McKenzie County, ND340.603
Kossuth County, IA15.50.59
Lowest
Oglala Lakota County, SD86.40.248
Sioux County, ND48.20.293
Tunica County, MS27.80.293
Todd County, SD80.60.302
Gadsden County, FL26.30.307
States — Adult income rank of children raised poor here is not published for states

By motor vehicle crash deaths

Motor vehicle crash deathsAdult income rank of children raised poor here
Highest
Mississippi25.5—
South Carolina20.8—
Alabama20.7—
Arkansas19.8—
New Mexico19.8—
Lowest
New York5.9—
Massachusetts6.01—
District of Columbia6.39—
Rhode Island6.89—
New Jersey6.98—
Metro areas

By motor vehicle crash deaths

Motor vehicle crash deathsAdult income rank of children raised poor here
Highest
Palatka, FL45.50.353
Gallup, NM42.30.354
Lumberton, NC41.40.321
Show Low, AZ40.20.376
Selma, AL39.20.336
Lowest
Amherst Town-Northampton, MA5.040.45
New York-Newark-Jersey City, NY-NJ5.040.439
Bridgeport-Stamford-Danbury, CT5.090.432
Boston-Cambridge-Newton, MA-NH5.140.453
Pullman, WA5.540.48

By adult income rank of children raised poor here

Motor vehicle crash deathsAdult income rank of children raised poor here
Highest
Dickinson, ND15.30.625
Carroll, IA12.70.59
Williston, ND180.586
Le Mars, IA10.20.551
Heber, UT8.920.543
Lowest
Laurinburg, NC28.40.311
Greenville, MS27.60.319
Lumberton, NC41.40.321
Henderson, NC32.30.324
Clarksdale, MS27.90.325

Counties furthest from the pattern

Compared with the straight line that best fits all 2,491 counties: the five with far more adult income rank of children raised poor here than their motor vehicle crash deaths would suggest, and the five with far less.

Motor vehicle crash deathsAdult income rank of children raised poor here
Above the line
Mountrail County, ND53.80.616
Nemaha County, KS25.30.614
McKenzie County, ND340.603
Stark County, ND15.30.614
Polk County, NE46.50.573
Below the line
Richmond city, VA11.60.311
Tunica County, MS27.80.293
Baltimore city, MD9.960.321
Dougherty County, GA17.80.313
Petersburg city, VA22.30.31

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-0.2452,489 counties reporting both
After adjusting for density, income and education-0.324the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.328size taken out as well as density
Also comparing only within each state-0.156each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.386the 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-0.010the link worked out inside each of 36 states with at least 20 counties reporting
Using ranks, after adjusting-0.371uses 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 = 6.4e-62. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 4.8e-6. 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 4.0e-61.

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 +0.53 (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?

Not measurable: at least one of these is published for too few of the years a change needs (2014–2019 or 2019–2023), or for too few counties in both.

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 Motor vehicle crash deaths and Adult income rank of children raised poor here