placestats

Received food stamps and Economic connectedness in high school

Across 2,016 counties, Received food stamps and Economic connectedness in high school have a link of -0.59, on a scale from −1 (opposite) to +1 (in step). But compare places with the same population density, income and education, and what is left could easily be chance. 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

Received food stamps

The estimated percentage of adults who received food stamps in the past year. 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 FOODSTAMP, age-adjusted

Economic connectedness in high school

How many of a low-income teenager's high school friends are high-income, compared with an even mix. It is counted in the county of the school, not where the person lives as an adult, so it describes where people grew up.

Social Capital Atlas · Opportunity Insights child_ec_county

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 received food stamps

Received food stampsEconomic connectedness in high school
Highest
McKinley County, NM39.8%0.572
Claiborne Parish, LA39.4%0.502
Lowndes County, AL37%0.459
Wilcox County, AL36.4%0.348
McDowell County, WV36.2%0.282
Lowest
Hamilton County, IN3.6%1.36
Summit County, UT3.8%1.36
Johnson County, KS3.8%1.26
Morgan County, UT4%1.44
Wasatch County, UT4.5%1.13

By economic connectedness in high school

Received food stampsEconomic connectedness in high school
Highest
Calvert County, MD8%1.61
Hunterdon County, NJ4.5%1.58
Howard County, MD6.4%1.56
Loudoun County, VA5.2%1.55
Stafford County, VA8.5%1.53
Lowest
Holmes County, MS33.9%0.273
McDowell County, WV36.2%0.282
Mingo County, WV31.6%0.304
Lincoln County, WV26.1%0.305
Summers County, WV26.1%0.309
Metro areas

By received food stamps

Received food stampsEconomic connectedness in high school
Highest
Gallup, NM39.8%0.572
Selma, AL33.3%0.564
Deming, NM32%0.35
Lumberton, NC30.9%0.495
Clarksdale, MS30.5%0.362
Lowest
Heber, UT4.11%1.26
Los Alamos, NM4.6%1.41
Ogden, UT5.56%1.22
Provo-Orem-Lehi, UT5.62%1.38
Bismarck, ND5.65%1.18

By economic connectedness in high school

Received food stampsEconomic connectedness in high school
Highest
Lexington Park, MD9.09%1.54
Los Alamos, NM4.6%1.41
Williston, ND7.6%1.39
Fairbanks-College, AK7.8%1.38
Provo-Orem-Lehi, UT5.62%1.38
Lowest
Deming, NM32%0.35
Clarksdale, MS30.5%0.362
Forrest City, AR24.9%0.409
Beckley, WV22.3%0.414
Elkins, WV18.5%0.441
Cities and towns — Economic connectedness in high school is not published for cities and towns

By received food stamps

Received food stampsEconomic connectedness in high school
Highest
Benton Harbor city, MI60.4%—
Buena Vista CDP, MI58.1%—
Muskegon Heights city, MI54.6%—
East Bakersfield CDP, CA54.5%—
Tallulah city, LA53.9%—
Lowest
Leawood city, KS2.3%—
Short Hills CDP, NJ2.4%—
Chatham borough, NJ2.4%—
Little Silver borough, NJ2.5%—
Fair Haven borough, NJ2.6%—

Counties furthest from the pattern

Compared with the straight line that best fits all 2,017 counties: the five with far more economic connectedness in high school than their received food stamps would suggest, and the five with far less.

Received food stampsEconomic connectedness in high school
Above the line
Madison County, ID14.7%1.52
Calvert County, MD8%1.61
Charles County, MD12.7%1.45
St. Mary's County, MD10%1.5
Bethel Census Area, AK29.6%1.03
Below the line
Graham County, NC11.3%0.403
Prentiss County, MS11.2%0.426
Mineral County, WV15%0.345
Tishomingo County, MS11.1%0.444
Pontotoc County, MS10.8%0.459

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-0.5872,016 counties reporting both
After adjusting for density, income and education-0.140the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.155size taken out as well as density
Also comparing only within each state-0.155each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.306the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 190 equally weighted counties
Middle value inside single states-0.647the link worked out inside each of 29 states with at least 20 counties reporting
Using ranks, after adjusting-0.050uses 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 = 3.2e-10. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.056. 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 7.4e-10.

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 +0.35 (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 Received food stamps and Economic connectedness in high school