placestats

Firearm fatalities and Incarceration of children raised poor here

Where Firearm fatalities is higher, Incarceration of children raised poor here tends to be higher. The link is weak: +0.32 across 1,781 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 30 states, the middle value of the link is +0.22.

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

Firearm fatalities

Deaths involving a gun per 100,000 people. Most are suicides and homicides, counted together.

County Health Rankings · County Health Rankings v148

Incarceration of children raised poor here

The share of those same children, who grew up here with poor parents, who were in prison on census day in 2010.

Opportunity Atlas · Opportunity Insights jail_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 firearm fatalities

Firearm fatalitiesIncarceration of children raised poor here
Highest
Phillips County, AR79.50.0286
Leflore County, MS70.50.0303
Lowndes County, AL61.10.019
Petersburg city, VA60.60.0594
Washington County, MS58.30.0334
Lowest
Middlesex County, MA1.860.00801
Bergen County, NJ2.10.00711
Norfolk County, MA2.180.00783
Rockland County, NY2.290.011
Nassau County, NY2.320.0146

By incarceration of children raised poor here

Firearm fatalitiesIncarceration of children raised poor here
Highest
Oglala Lakota County, SD330.0889
Portsmouth city, VA34.70.0658
King George County, VA16.20.0642
Richmond city, VA28.10.0641
Dauphin County, PA12.20.0608
Lowest
Kent County, RI3.710.0033
Washington County, RI5.80.00337
Providence County, RI4.650.0047
Huron County, MI9.660.00559
Stark County, ND13.70.00571
States — Incarceration of children raised poor here is not published for states

By firearm fatalities

Firearm fatalitiesIncarceration of children raised poor here
Highest
Mississippi27.1—
Louisiana24.9—
New Mexico24.1—
Wyoming23.8—
Alabama23.7—
Lowest
Massachusetts3.7—
Hawaii4.32—
Rhode Island4.47—
New Jersey4.81—
New York4.9—
Metro areas

By firearm fatalities

Firearm fatalitiesIncarceration of children raised poor here
Highest
Greenwood, MS61.50.0303
Greenville, MS58.30.0334
Selma, AL48.40.0177
Pine Bluff, AR43.90.0386
Payson, AZ40.40.0181
Lowest
Boston-Cambridge-Newton, MA-NH3.480.0129
Worcester, MA3.490.00886
Urban Honolulu, HI3.580.0135
New York-Newark-Jersey City, NY-NJ3.650.0156
Bridgeport-Stamford-Danbury, CT3.830.0302

By incarceration of children raised poor here

Firearm fatalitiesIncarceration of children raised poor here
Highest
Thomaston, GA19.30.06
Summerville, GA19.30.0555
Waco, TX15.40.0552
Sherman-Denison, TX15.90.0546
Savannah, GA19.40.0541
Lowest
Dickinson, ND13.70.00571
Oneonta, NY7.750.00584
New Ulm, MN11.90.00603
Houghton, MI10.50.00631
Wheeling, WV-OH13.70.00639

Counties furthest from the pattern

Compared with the straight line that best fits all 1,781 counties: the five with far more incarceration of children raised poor here than their firearm fatalities would suggest, and the five with far less.

Firearm fatalitiesIncarceration of children raised poor here
Above the line
Oglala Lakota County, SD330.0889
King George County, VA16.20.0642
Dauphin County, PA12.20.0608
Suffolk city, VA16.10.0597
Richmond city, VA28.10.0641
Below the line
Smith County, MS30.30.00578
Lowndes County, AL61.10.019
Swain County, NC240.00614
Roane County, WV320.00952
Phillips County, AR79.50.0286

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+0.3031,781 counties reporting both
After adjusting for density, income and education+0.322the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.319size taken out as well as density
Also comparing only within each state+0.213each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.493the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 260 equally weighted counties
Middle value inside single states+0.224the link worked out inside each of 30 states with at least 20 counties reporting
Using ranks, after adjusting+0.391uses 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 = 2.9e-44. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 1.1e-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 1.5e-43.

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 +0.35 (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 Firearm fatalities and Incarceration of children raised poor here