Lacking social and emotional support and Burglary rate
Where Lacking social and emotional support is higher, Burglary rate tends to be higher. The link is weak: +0.33 across 1,633 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 27 states, the middle value of the link is +0.18.
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
Lacking social and emotional support
The estimated percentage of adults who rarely or never get the social and emotional support they need. It is adjusted so places with older or younger populations can be compared fairly. It is an estimate from a statistical model, not a direct count from a local survey.
CDC PLACES · PLACES EMOTIONSPT, age-adjusted
Burglary rate
Burglaries in the year, per 100,000 residents, from the FBI. A burglary is entering a home or other building without permission to steal or commit another crime. 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 burglary; 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 lacking social and emotional support
| Lacking social and emotional support | Burglary rate | |
|---|---|---|
| Highest | ||
| East Carroll Parish, LA | 37.8% | 161 |
| Tunica County, MS | 35.5% | 951 |
| Claiborne Parish, LA | 34.9% | 86.5 |
| Madison Parish, LA | 34.8% | 168 |
| Jefferson County, AR | 34.6% | 818 |
| Lowest | ||
| Wasatch County, UT | 16.7% | 43.7 |
| Waukesha County, WI | 17.1% | 48.3 |
| Falls Church city, VA | 17.1% | 89.3 |
| Johnson County, KS | 17.1% | 135 |
| Summit County, UT | 17.2% | 94.1 |
By burglary rate
| Lacking social and emotional support | Burglary rate | |
|---|---|---|
| Highest | ||
| Robeson County, NC | 26.4% | 1,199 |
| Richmond County, NC | 26.2% | 1,058 |
| Tunica County, MS | 35.5% | 951 |
| Tillman County, OK | 26.7% | 914 |
| Garland County, AR | 26.5% | 911 |
| Lowest | ||
| Wrangell City and Borough, AK | 26.6% | 0 |
| Sioux County, ND | 30.1% | 0 |
| Oliver County, ND | 22% | 0 |
| McIntosh County, ND | 22.9% | 0 |
| Golden Valley County, ND | 21.7% | 0 |
States — Lacking social and emotional support is not published for states
By burglary rate
| Lacking social and emotional support | Burglary rate | |
|---|---|---|
| Highest | ||
| New Mexico | — | 518 |
| Washington | — | 481 |
| Oklahoma | — | 460 |
| Louisiana | — | 441 |
| Arkansas | — | 410 |
| Lowest | ||
| New Hampshire | — | 58.4 |
| Maine | — | 112 |
| Rhode Island | — | 118 |
| Virginia | — | 122 |
| Connecticut | — | 129 |
Metro areas
By lacking social and emotional support
| Lacking social and emotional support | Burglary rate | |
|---|---|---|
| Highest | ||
| Forrest City, AR | 34.2% | 589 |
| Pine Bluff, AR | 33.9% | 742 |
| Gallup, NM | 32.5% | 223 |
| Blytheville, AR | 31.9% | 343 |
| Show Low, AZ | 31.8% | 126 |
| Lowest | ||
| Heber, UT | 17% | 68.6 |
| Jackson, WY-ID | 18.5% | 36.4 |
| Provo-Orem-Lehi, UT | 18.5% | 84.9 |
| Columbia, MO | 18.6% | 249 |
| Logan, UT-ID | 18.6% | 67.9 |
By burglary rate
| Lacking social and emotional support | Burglary rate | |
|---|---|---|
| Highest | ||
| Lumberton, NC | 26.4% | 1,199 |
| Rockingham, NC | 26.2% | 1,058 |
| Hot Springs, AR | 26.5% | 911 |
| Springfield, IL | 24.6% | 857 |
| Jonesboro, AR | 27.7% | 813 |
| Lowest | ||
| Lexington, NE | 24.4% | 0 |
| Petoskey, MI | 21.3% | 23.8 |
| Quincy, IL-MO | 23.6% | 31 |
| Norfolk, NE | 20.8% | 33.8 |
| Jackson, WY-ID | 18.5% | 36.4 |
Cities and towns — Burglary rate is not published for cities and towns
By lacking social and emotional support
| Lacking social and emotional support | Burglary rate | |
|---|---|---|
| Highest | ||
| Rosemead city, CA | 39.9% | — |
| Bastrop city, LA | 38.2% | — |
| East St. Louis city, IL | 37.8% | — |
| Westmont CDP, CA | 37.6% | — |
| Yazoo City city, MS | 37.5% | — |
| Lowest | ||
| Prairie Village city, KS | 14.7% | — |
| Glendale city, MO | 15% | — |
| Elm Grove village, WI | 15.1% | — |
| Leawood city, KS | 15.1% | — |
| Midway city, UT | 15.3% | — |
Counties furthest from the pattern
Compared with the straight line that best fits all 1,636 counties: the five with far more burglary rate than their lacking social and emotional support would suggest, and the five with far less.
| Lacking social and emotional support | Burglary rate | |
|---|---|---|
| Above the line | ||
| Robeson County, NC | 26.4% | 1,199 |
| Richmond County, NC | 26.2% | 1,058 |
| Garland County, AR | 26.5% | 911 |
| Tillman County, OK | 26.7% | 914 |
| Sangamon County, IL | 24.6% | 857 |
| Below the line | ||
| West Feliciana Parish, LA | 31.9% | 17.6 |
| Claiborne Parish, LA | 34.9% | 86.5 |
| East Carroll Parish, LA | 37.8% | 161 |
| Sioux County, ND | 30.1% | 0 |
| Amite County, MS | 31.9% | 51.1 |
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 | +0.416 | 1,633 counties reporting both |
| After adjusting for density, income and education | +0.326 | the part of the link that is not just how urban, rich and educated a place is |
| Also adjusting for population size | +0.289 | size taken out as well as density |
| Also comparing only within each state | +0.151 | each county is compared only with others in its own state, so this is no longer a comparison between states |
| Giving bigger counties more weight | +0.476 | the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 152 equally weighted counties |
| Middle value inside single states | +0.181 | the link worked out inside each of 27 states with at least 20 counties reporting |
| Using ranks, after adjusting | +0.335 | uses 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 = 9.7e-42. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 7.2e-5. 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 5.4e-41.
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?
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
- Lacking social and emotional support and Material security score — -0.74
- Lacking social and emotional support and Returns claiming the earned income credit — +0.68
- Lacking social and emotional support and Average test score — -0.65
- Lacking social and emotional support and Children in single-parent households — +0.62
- Lacking social and emotional support and Homicide rate — +0.57
- Lacking social and emotional support and Republican share of the two-party vote, 2016 — -0.57
- Lacking social and emotional support and Republican share of the two-party vote, 2020 — -0.56
- Lacking social and emotional support and Republican share of the two-party vote, 2024 — -0.54
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 Lacking social and emotional support and Burglary rate