placestats

Republican share of the two-party vote, 2012 and Share of suicides by firearm

A county is not a voter. Read either way, this says one thing and no more. Counties that voted more Republican also tend to differ on the other measure, and counties that voted less Republican tend to differ the other way. It does not follow that the people who voted that way are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. It is the most common misuse of exactly this data. How a county votes also goes so closely with its density, age and education that much of what looks political here is really those. That is what the adjusted figures are for. The vote shares run from 2000 to 2024, and the links here are measured in 2023.

Where Republican share of the two-party vote, 2012 is higher, Share of suicides by firearm tends to be higher. The link is weak: +0.33 across 2,209 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 35 states, the middle value of the link is +0.30.

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

Republican share of the two-party vote, 2012

The Republican candidate's share of the votes for the two main parties in the 2012 presidential election, Romney against Obama. Third-party votes are left out, just as in the other years.

MIT Election Data and Science Lab · MIT county presidential returns

Share of suicides by firearm

The percentage of suicides that were by gun, 2018-2023. Where more households own guns, more suicides are by gun. So researchers use this as the standard stand-in for gun ownership, which nobody counts directly.

CDC WONDER mortality; RAND firearm ownership database · CDC WONDER underlying cause of death, suicide by intent, firearm by mechanism, 2018-2023

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 republican share of the two-party vote, 2012

Republican share of the two-party vote, 2012Share of suicides by firearm
Highest
Madison County, ID94.252.9%
Franklin County, ID94.161.9%
Uintah County, UT91.363.8%
Millard County, UT91.263.6%
Leslie County, KY91.183.3%
Lowest
Bronx County, NY7.3812.7%
District of Columbia, DC7.4124%
Prince George's County, MD9.3143.6%
Petersburg city, VA9.6656.4%
Baltimore city, MD11.341.3%

By share of suicides by firearm

Republican share of the two-party vote, 2012Share of suicides by firearm
Highest
Custer County, ID76.7100%
Harrison County, MO72.7100%
Teton County, MT66.1100%
Gates County, NC47.9100%
Pendleton County, WV66.1100%
Lowest
New York County, NY14.96.48%
Queens County, NY19.110.5%
Kings County, NY16.312.2%
Bronx County, NY7.3812.7%
Hudson County, NJ21.714.7%
States — Republican share of the two-party vote, 2012 is not published for states

By share of suicides by firearm

Republican share of the two-party vote, 2012Share of suicides by firearm
Highest
Mississippi—70.8%
Wyoming—70.6%
Alabama—70.5%
Louisiana—65.6%
South Carolina—64.7%
Lowest
Hawaii—19%
Massachusetts—22%
District of Columbia—24%
Rhode Island—27%
New Jersey—27%
Metro areas

By republican share of the two-party vote, 2012

Republican share of the two-party vote, 2012Share of suicides by firearm
Highest
Rexburg, ID91.857.3%
Vernal, UT91.363.8%
Provo-Orem-Lehi, UT9054.1%
Brigham City, UT-ID89.658.2%
Pampa, TX88.376.9%
Lowest
Rio Grande City-Roma, TX13.167.9%
Taos, NM18.665.5%
Eagle Pass, TX20.740.6%
Santa Cruz-Watsonville, CA20.933.9%
Las Vegas, NM21.147.5%

By share of suicides by firearm

Republican share of the two-party vote, 2012Share of suicides by firearm
Highest
Cleveland, MS30.894.1%
Brenham, TX76.390%
Troy, AL56.987%
Ruidoso, NM6786.8%
Scottsboro, AL71.386.2%
Lowest
Urban Honolulu, HI30.216.6%
New York-Newark-Jersey City, NY-NJ33.318.1%
Boston-Cambridge-Newton, MA-NH38.820.8%
Kahului-Wailuku, HI24.321.1%
Barnstable Town, MA4622.5%

Counties furthest from the pattern

Compared with the straight line that best fits all 2,209 counties: the five with far more share of suicides by firearm than their republican share of the two-party vote, 2012 would suggest, and the five with far less.

Republican share of the two-party vote, 2012Share of suicides by firearm
Above the line
Hale County, AL37.2100%
Bolivar County, MS30.894.1%
Gates County, NC47.9100%
Conecuh County, AL49.2100%
Leflore County, MS28.288.9%
Below the line
Anderson County, TX76.328.6%
Norfolk County, MA42.315.8%
Bergen County, NJ44.318.7%
Ford County, KS68.328.9%
New York County, NY14.96.48%

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+0.4562,209 counties reporting both
After adjusting for density, income and education+0.333the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.316size taken out as well as density
Also comparing only within each state+0.106each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.514the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 273 equally weighted counties
Middle value inside single states+0.301the link worked out inside each of 35 states with at least 20 counties reporting
Using ranks, after adjusting+0.341uses 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 = 2.0e-58. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 1.1e-7. 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 1.2e-57.

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 +0.33 (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 Republican share of the two-party vote, 2012 and Share of suicides by firearm