placestats

Suicide rate and Firearm suicide rate

Where Suicide rate is higher, Firearm suicide rate tends to be higher. The link is strong: +0.75 across 1,994 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 33 states, the middle value of the link is +0.85.

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

Suicide rate

Suicides per 100,000 people, adjusted so places with older or younger populations can be compared fairly.

County Health Rankings · County Health Rankings v161

Firearm suicide rate

Suicides by gun per 100,000 residents a year, 2018-2023.

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 suicide rate

By firearm suicide rate

Suicide rateFirearm suicide rate
Highest
Boise County, ID46.541.3
Park County, CO42.934.5
Nome Census Area, AK87.933.7
Aransas County, TX36.132.9
Sierra County, NM5131.3
Lowest
New York County, NY7.170.529
Queens County, NY6.060.69
Kings County, NY5.610.711
Bronx County, NY5.40.713
Hudson County, NJ6.580.968
States

By suicide rate

Suicide rateFirearm suicide rate
Highest
Wyoming28.620.3
Alaska27.816.7
Montana27.618.1
New Mexico24.513.9
Idaho2214.3
Lowest
District of Columbia6.241.55
New Jersey7.632.17
New York8.22.37
Massachusetts8.642.05
Maryland9.784.49

By firearm suicide rate

Suicide rateFirearm suicide rate
Highest
Wyoming28.620.3
Montana27.618.1
Alaska27.816.7
Idaho2214.3
New Mexico24.513.9
Lowest
District of Columbia6.241.55
Massachusetts8.642.05
New Jersey7.632.17
New York8.22.37
Hawaii14.12.79
Metro areas

By suicide rate

Suicide rateFirearm suicide rate
Highest
Payson, AZ5129.3
Show Low, AZ42.316.5
Baker City, OR39.122.2
Montrose, CO38.723.9
Cañon City, CO37.926.9
Lowest
El Centro, CA5.73.05
McAllen-Edinburg-Mission, TX6.423.3
New York-Newark-Jersey City, NY-NJ6.671.32
McComb, MS6.849.29
Laredo, TX6.963.12

By firearm suicide rate

Suicide rateFirearm suicide rate
Highest
Pahrump, NV33.130.9
Brookings, OR27.229.4
Payson, AZ5129.3
Elko, NV37.127.8
Mountain Home, AR33.327.6
Lowest
New York-Newark-Jersey City, NY-NJ6.671.32
Boston-Cambridge-Newton, MA-NH8.242.03
Urban Honolulu, HI11.72.05
Trenton-Princeton, NJ7.192.13
San Jose-Sunnyvale-Santa Clara, CA8.152.35

Counties furthest from the pattern

Compared with the straight line that best fits all 1,994 counties: the five with far more firearm suicide rate than their suicide rate would suggest, and the five with far less.

Suicide rateFirearm suicide rate
Above the line
Boise County, ID46.541.3
Curry County, OR27.229.4
Aransas County, TX36.132.9
Nye County, NV33.130.9
Izard County, AR2827.7
Below the line
Northwest Arctic Borough, AK87.828.7
Todd County, SD70.520.5
Nome Census Area, AK87.933.7
Apache County, AZ45.112.4
Bethel Census Area, AK6728.2

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+0.8481,994 counties reporting both
After adjusting for density, income and education+0.747the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.750size taken out as well as density
Also comparing only within each state+0.729each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.835the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 265 equally weighted counties
Middle value inside single states+0.854the link worked out inside each of 33 states with at least 20 counties reporting
Using ranks, after adjusting+0.784uses 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 = 0.000. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 2.5e-15. 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 0.000.

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 +0.21 (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.

At three sizes of place

The same pair measured across counties, metro areas and states. A missing size means the measure cannot be combined up to that level.

LevelPlacesUnadjustedAdjustedNote
county1,994+0.85+0.75
state51+0.94+0.83no same-state comparison at state level: the units do not sit inside states one to one
cbsa881+0.84+0.79not adjusted for median household income: not available at this level; no same-state comparison at cbsa level: the units do not sit inside states one to one

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 Suicide rate and Firearm suicide rate