placestats

Share never married and Violent crime rate

Where Share never married is higher, Violent crime rate tends to be higher. The link is weak: +0.31 across 2,279 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 +0.45.

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 never married

The percentage of people aged 15 and over who have never married. The Census counts from age 15, not 18, so every county's figure includes some teenagers.

Census ACS 5-year · ACS table B12001_003…B12001_012 (2 cells), divided by population aged 15 and over

Violent crime rate

Murders, rapes, robberies and aggravated assaults in the year, per 100,000 residents, from the FBI. It counts only crimes reported to police or found by them, so crimes nobody reports are missing. For a state, the figure is the FBI's estimate, which fills in for police agencies that did not report. For a county, it is only what the agencies reported, and it is shown only where agencies that reported for all 12 months serve at least 90% of the people who live there.

FBI Uniform Crime Reporting program (Crime Data Explorer) · FBI Crime Data Explorer: states, estimated_crimes violent_crime; counties, Return A master file, actual offenses

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 never married

Share never marriedViolent crime rate
Highest
Lexington city, VA64.5%119
Radford city, VA62.6%205
Williamsburg city, VA60.1%248
Harrisonburg city, VA58.3%224
Sioux County, ND55.5%27.4
Lowest
Treasure County, MT12%266
Glasscock County, TX12.7%0
Irion County, TX13.3%0
Jeff Davis County, TX13.3%375
Thomas County, NE13.3%148

By violent crime rate

Share never marriedViolent crime rate
Highest
Shelby County, TN42.1%1,876
Crittenden County, AR36.6%1,764
Baltimore city, MD52.7%1,694
St. Louis city, MO49.7%1,457
Robeson County, NC41.5%1,421
Lowest
San Juan County, CO23%0
Kiowa County, CO22.8%0
Conejos County, CO27.6%0
Menominee County, WI41.6%0
Roberts County, TX15.1%0
States

By share never married

Share never marriedViolent crime rate
Highest
District of Columbia55.2%1,142
New York38.6%391
California37.8%507
Rhode Island37.3%167
Massachusetts37.2%321
Lowest
Wyoming27.6%194
Idaho28.3%240
Maine28.9%104
West Virginia29%269
Arkansas29.5%623

By violent crime rate

Share never marriedViolent crime rate
Highest
District of Columbia55.2%1,142
New Mexico36.4%747
Alaska33.8%734
Tennessee31%636
Arkansas29.5%623
Lowest
Maine28.9%104
New Hampshire30.3%115
Connecticut35.4%152
Rhode Island37.3%167
Wyoming27.6%194
Metro areas

By share never married

Share never marriedViolent crime rate
Highest
Vermillion, SD54.9%167
Pullman, WA52.5%166
Gallup, NM52.5%503
Ruston, LA51%390
Ithaca, NY48%128
Lowest
Wildwood-The Villages, FL13.8%117
Crossville, TN17.3%210
Mountain Home, AR18.6%199
Granbury, TX19.5%161
Punta Gorda, FL19.9%115

By violent crime rate

Share never marriedViolent crime rate
Highest
Memphis, TN-MS-AR38.5%1,453
Lumberton, NC41.5%1,421
Orangeburg, SC42.3%1,414
Forrest City, AR39.9%1,324
Albuquerque, NM36.1%1,152
Lowest
Quincy, IL-MO29.9%0
Lexington, NE29.1%0
Columbus, IN29.5%16.1
Pikeville, KY22.8%31.1
Moscow, ID41.2%35.7
Cities and towns — Violent crime rate is not published for cities and towns

By share never married

Share never marriedViolent crime rate
Highest
Clemson University CDP, SC99.9%—
Binghamton University CDP, NY99.3%—
Rochester Institute of Technology CDP, NY99.3%—
Notre Dame CDP, IN99.1%—
California Polytechnic State University CDP, CA98.8%—
Lowest
Desert Palms CDP, CA3.45%—
Longboat Key town, FL3.52%—
Pelican Bay CDP, FL3.69%—
The Villages CDP, FL4.24%—
On Top of the World CDP, FL4.4%—
ZIP codes — Violent crime rate is not published for ZIP codes

By share never married

Share never marriedViolent crime rate
Highest
ZIP 19717 (Newark city, DE)100%—
ZIP 38677 (University CDP, MS)100%—
ZIP 32612 (Gainesville city, FL)99.9%—
ZIP 93410 (California Polytechnic State University CDP, CA)99.9%—
ZIP 13244 (Syracuse city, NY)99.9%—
Lowest
ZIP 34228 (Longboat Key town, FL)3.52%—
ZIP 32162 (The Villages CDP, FL)3.98%—
ZIP 85375 (Sun City West CDP, AZ)5.31%—
ZIP 32163 (Wildwood city, FL)5.45%—
ZIP 85622 (Pima County, AZ)6.24%—

Counties furthest from the pattern

Compared with the straight line that best fits all 2,285 counties: the five with far more violent crime rate than their share never married would suggest, and the five with far less.

Share never marriedViolent crime rate
Above the line
Shelby County, TN42.1%1,876
Crittenden County, AR36.6%1,764
Baltimore city, MD52.7%1,694
Pulaski County, AR34.9%1,380
Robeson County, NC41.5%1,421
Below the line
Lexington city, VA64.5%119
Sioux County, ND55.5%27.4
Madison County, ID53.4%68.6
Radford city, VA62.6%205
Clay County, SD54.9%167

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+0.4192,279 counties reporting both
After adjusting for density, income and education+0.308the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.279size taken out as well as density
Also comparing only within each state+0.255each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.423the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 237 equally weighted counties
Middle value inside single states+0.446the link worked out inside each of 36 states with at least 20 counties reporting
Using ranks, after adjusting+0.336uses 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 = 4.0e-51. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 1.9e-6. The site tested 29,403 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 2.6e-50.

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 +0.30 (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 never married rose most, did violent crime ratemove 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 pandemic1,967+0.02+0.030.589
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years1,844+0.01+0.010.822

Over the main period, any link between the changes could easily be chance. 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 never married and Violent crime rate