placestats

Share American Indian or Alaska Native, not Hispanic and Economic connectedness

Where Share American Indian or Alaska Native, not Hispanic is higher, Economic connectedness tends to be lower. The link is weak: -0.33 across 1,263 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 29 states, the middle value of the link is -0.26.

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 American Indian or Alaska Native, not Hispanic

The percentage of residents who are American Indian or Alaska Native alone and not Hispanic. They live mostly on and near reservations: Oglala Lakota County, South Dakota is 91%, while most counties are under 1%.

Census ACS 5-year · ACS table B03002_005, divided by total population

Economic connectedness

How many of a low-income person's friends are high-income, compared with an even mix. One means their friends match the local mix of rich and poor. Below one means their friendships are more divided by income than that.

Social Capital Atlas · Opportunity Insights 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 share American Indian or Alaska Native, not Hispanic

Share American Indian or Alaska Native, not HispanicEconomic connectedness
Highest
Oglala Lakota County, SD91.4%0.33
Kusilvak Census Area, AK86.4%0.642
Sioux County, ND83.7%0.448
Bethel Census Area, AK83.6%0.763
Todd County, SD83.1%0.295
Lowest
Washington County, CO0%1.07
Phillips County, CO0%0.841
Ouray County, CO0%1.21
Sierra County, CA0%1.03
Monroe County, AR0%0.556

By economic connectedness

Share American Indian or Alaska Native, not HispanicEconomic connectedness
Highest
Douglas County, CO0.17%1.35
San Francisco County, CA0.202%1.31
Arlington County, VA0.144%1.27
Wright County, MN0.187%1.25
Ozaukee County, WI0.116%1.24
Lowest
Todd County, SD83.1%0.295
Oglala Lakota County, SD91.4%0.33
Terrell County, GA0%0.347
Bullock County, AL0%0.355
Robeson County, NC39.1%0.363
States — Economic connectedness is not published for states

By share American Indian or Alaska Native, not Hispanic

Share American Indian or Alaska Native, not HispanicEconomic connectedness
Highest
Alaska13.5%—
New Mexico8.6%—
South Dakota7.38%—
Oklahoma6.79%—
Montana5.5%—
Lowest
Pennsylvania0.0553%—
Ohio0.0625%—
West Virginia0.0647%—
Illinois0.0697%—
Indiana0.0703%—
Metro areas

By share American Indian or Alaska Native, not Hispanic

Share American Indian or Alaska Native, not HispanicEconomic connectedness
Highest
Gallup, NM75.1%0.416
Show Low, AZ41.9%0.58
Lumberton, NC39.1%0.363
Farmington, NM38.5%0.596
Tahlequah, OK31.8%0.721
Lowest
Zapata, TX0%0.498
Weirton-Steubenville, WV-OH0%0.771
Valdosta, GA0%0.583
Sikeston, MO0%0.696
Roanoke, VA0%0.736

By economic connectedness

Share American Indian or Alaska Native, not HispanicEconomic connectedness
Highest
Provo-Orem-Lehi, UT0.261%1.22
Alexandria, MN0.241%1.18
Laramie, WY0.31%1.17
Ames, IA0.146%1.15
Red Wing, MN0.855%1.15
Lowest
Lumberton, NC39.1%0.363
Laurinburg, NC11.1%0.396
Eufaula, AL-GA0%0.414
Gallup, NM75.1%0.416
Arcadia, FL0.13%0.429
Cities and towns — Economic connectedness is not published for cities and towns

By share American Indian or Alaska Native, not Hispanic

Share American Indian or Alaska Native, not HispanicEconomic connectedness
Highest
Zuni Pueblo CDP, NM98%—
Kayenta CDP, AZ94.4%—
Shiprock CDP, NM93.2%—
Tuba City CDP, AZ88.7%—
Bethel city, AK67.8%—
Lowest
Windsor Locks CDP, CT0%—
Willimantic CDP, CT0%—
Wethersfield CDP, CT0%—
Trumbull Center CDP, CT0%—
Terryville CDP, CT0%—
ZIP codes — Economic connectedness is not published for ZIP codes

By share American Indian or Alaska Native, not Hispanic

Share American Indian or Alaska Native, not HispanicEconomic connectedness
Highest
ZIP 58316 (Rolette County, ND)96.5%—
ZIP 86033 (Navajo County, AZ)95.7%—
ZIP 86505 (Apache County, AZ)95.6%—
ZIP 87327 (McKinley County, NM)95.3%—
ZIP 87313 (McKinley County, NM)95%—
Lowest
ZIP 08904 (Highland Park borough, NJ)0%—
ZIP 08901 (New Brunswick city, NJ)0%—
ZIP 08889 (Hunterdon County, NJ)0%—
ZIP 08882 (South River borough, NJ)0%—
ZIP 08867 (Hunterdon County, NJ)0%—

Counties furthest from the pattern

Compared with the straight line that best fits all 1,267 counties: the five with far more economic connectedness than their share American Indian or Alaska Native, not Hispanic would suggest, and the five with far less.

Share American Indian or Alaska Native, not HispanicEconomic connectedness
Above the line
Douglas County, CO0.17%1.35
San Francisco County, CA0.202%1.31
Arlington County, VA0.144%1.27
North Slope Borough, AK47.4%1.09
Wright County, MN0.187%1.25
Below the line
Terrell County, GA0%0.347
Bullock County, AL0%0.355
Marlboro County, SC3.4%0.385
Dooly County, GA0%0.401
Randolph County, GA0%0.411

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-0.2081,263 counties reporting both
After adjusting for density, income and education-0.331the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.306size taken out as well as density
Also comparing only within each state-0.471each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.099the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 184 equally weighted counties
Middle value inside single states-0.264the link worked out inside each of 29 states with at least 20 counties reporting
Using ranks, after adjusting-0.067uses 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 = 1.3e-33. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 1.3e-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 5.7e-33.

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 +0.49 (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 American Indian or Alaska Native, not Hispanic and Economic connectedness