placestats

Share of births to unmarried women and Safety score

Across 1,256 counties, Share of births to unmarried women and Safety score have a link of -0.54, on a scale from −1 (opposite) to +1 (in step). But compare places with the same population density, income and education, and a weak link of -0.26 remains. Most of the first figure came from both measures following how urban, rich and educated a place is, not from a link with each other.

Mostly gone 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 of births to unmarried women

Of women who gave birth in the past year, the percentage who were not married: never married, widowed or divorced. A separated woman counts as married. The middle county is 31.8%. It is a share of women who gave birth, not of all women, so it says nothing about how many births there were.

Census ACS 5-year · ACS table B13002_007, divided by women who gave birth in the past year

Safety score

Deaths from violence and injury (guns, crashes and overdoses), flipped so higher is safer. Homicide, suicide, drunk-driving and total injury deaths are left out, since they would count the same deaths twice. Gun deaths already include most homicides and suicides, and injury deaths include all four.

· derived from 4 measures (BRFSS, CHR)

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 of births to unmarried women

Share of births to unmarried womenSafety score
Highest
Tunica County, MS100%-1.59
Chowan County, NC98.6%-0.35
Tallahatchie County, MS97.3%-1.58
Burleson County, TX96.1%-0.858
Humphreys County, MS95.3%-2.44
Lowest
Park County, CO0%-0.952
Archuleta County, CO0%-0.0169
Stone County, AR0%-1.72
Platte County, WY0%-1.9
Northumberland County, VA0%-0.901

By safety score

Share of births to unmarried womenSafety score
Highest
Loudoun County, VA11.7%1.39
Fairfax County, VA13.8%1.29
Western Connecticut Planning Region, CT20.1%1.26
Morris County, NJ15.1%1.24
Rockland County, NY13.5%1.24
Lowest
Big Horn County, MT40.7%-5.15
Phillips County, AR85.7%-4.96
Todd County, SD37.1%-4.82
Oglala Lakota County, SD56.9%-4.61
Petersburg city, VA76.1%-4.06
States

By share of births to unmarried women

Share of births to unmarried womenSafety score
Highest
Louisiana46.3%-0.999
Mississippi45.5%-1.82
New Mexico43.2%-0.627
District of Columbia41.4%-0.474
South Carolina38.6%-0.563
Lowest
Utah14.1%0.609
Idaho20%-0.356
Colorado21.8%0.0342
North Dakota23.1%-0.558
Washington23.4%0.756

By safety score

Share of births to unmarried womenSafety score
Highest
Hawaii28.7%0.788
Washington23.4%0.756
Minnesota23.9%0.747
California30.1%0.68
Oregon24.4%0.628
Lowest
Mississippi45.5%-1.82
Kentucky33.7%-1.52
West Virginia37.8%-1.48
Missouri29.5%-1.37
Montana26%-1.23
Metro areas

By share of births to unmarried women

Share of births to unmarried womenSafety score
Highest
Española, NM86.1%-2.61
Kinston, NC76.3%-0.679
Gallup, NM76.2%-1.53
Brunswick-St. Simons, GA75.4%-0.153
Clarksdale, MS71.2%-2.58
Lowest
Provo-Orem-Lehi, UT9.79%1.28
Logan, UT-ID10.1%1.06
Jacksonville, NC12.5%-0.00824
Lebanon, PA12.6%0.471
Madison, WI12.8%0.915

By safety score

Share of births to unmarried womenSafety score
Highest
Iowa City, IA15.4%1.41
State College, PA19.4%1.38
McAllen-Edinburg-Mission, TX35.9%1.37
Urban Honolulu, HI23.6%1.37
San Jose-Sunnyvale-Santa Clara, CA17.4%1.32
Lowest
Greenville, MS64.1%-3.93
Lumberton, NC57.1%-3.33
Española, NM86.1%-2.61
Selma, AL42.2%-2.61
Clarksdale, MS71.2%-2.58
Cities and towns — Safety score is not published for cities and towns

By share of births to unmarried women

Share of births to unmarried womenSafety score
Highest
Beverly Hills CDP, FL100%—
Daytona Beach Shores city, FL100%—
Florida Ridge CDP, FL100%—
Fussels Corner CDP, FL100%—
Hernando CDP, FL100%—
Lowest
Winsted CDP, CT0%—
Terryville CDP, CT0%—
Storrs CDP, CT0%—
Staples CDP, CT0%—
Southwood Acres CDP, CT0%—
ZIP codes — Safety score is not published for ZIP codes

By share of births to unmarried women

Share of births to unmarried womenSafety score
Highest
ZIP 10038 (New York city, NY)100%—
ZIP 11980 (Yaphank CDP, NY)100%—
ZIP 12222 (Albany city, NY)100%—
ZIP 13214 (De Witt CDP, NY)100%—
ZIP 13244 (Syracuse city, NY)100%—
Lowest
ZIP 08889 (Hunterdon County, NJ)0%—
ZIP 08886 (Warren County, NJ)0%—
ZIP 08872 (Sayreville borough, NJ)0%—
ZIP 08867 (Hunterdon County, NJ)0%—
ZIP 08863 (Fords CDP, NJ)0%—

Counties furthest from the pattern

Compared with the straight line that best fits all 1,256 counties: the five with far more safety score than their share of births to unmarried women would suggest, and the five with far less.

Share of births to unmarried womenSafety score
Above the line
Douglas County, WA62.8%1.11
Franklin County, NY58.5%0.838
Chowan County, NC98.6%-0.35
Hale County, TX70.4%0.429
Prince George County, VA69%0.466
Below the line
Big Horn County, MT40.7%-5.15
Todd County, SD37.1%-4.82
Oglala Lakota County, SD56.9%-4.61
Phillips County, AR85.7%-4.96
St. Louis city, MO39.8%-3.52

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-0.5391,256 counties reporting both
After adjusting for density, income and education-0.262the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.253size taken out as well as density
Also comparing only within each state-0.206each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.305the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 223 equally weighted counties
Middle value inside single states-0.448the link worked out inside each of 24 states with at least 20 counties reporting
Using ranks, after adjusting-0.183uses 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 = 3.7e-21. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 1.4e-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 1.2e-20.

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 +0.32 (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 Share of births to unmarried women and Safety score