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Share American Indian or Alaska Native, not Hispanic and Child mortality

Where Share American Indian or Alaska Native, not Hispanic is higher, Child mortality tends to be higher. The link is moderate: +0.46 across 833 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.

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

Child mortality

Deaths of children under 18 per 100,000 children.

County Health Rankings · County Health Rankings v128

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 HispanicChild mortality
Highest
Oglala Lakota County, SD91.4%208
Kusilvak Census Area, AK86.4%274
Bethel Census Area, AK83.6%200
Todd County, SD83.1%153
Northwest Arctic Borough, AK80.1%202
Lowest
Drew County, AR0%78.5
Wayne County, WV0%64.3
Mingo County, WV0%67.5
Hancock County, WV0%64.1
Boone County, WV0%72.8

By child mortality

Share American Indian or Alaska Native, not HispanicChild mortality
Highest
Kusilvak Census Area, AK86.4%274
Oglala Lakota County, SD91.4%208
Northwest Arctic Borough, AK80.1%202
Bethel Census Area, AK83.6%200
Nome Census Area, AK74.6%178
Lowest
Benton County, OR0.444%19.1
Washington County, RI0.194%20.8
Norfolk County, MA0.0576%21.2
Montgomery County, VA0.209%21.2
Morris County, NJ0.0347%21.2
States

By share American Indian or Alaska Native, not Hispanic

Share American Indian or Alaska Native, not HispanicChild mortality
Highest
Alaska13.5%72.9
New Mexico8.6%59.3
South Dakota7.38%67.8
Oklahoma6.79%64
Montana5.5%62.9
Lowest
Pennsylvania0.0553%50.3
Ohio0.0625%59.2
West Virginia0.0647%60.7
Illinois0.0697%50.7
Indiana0.0703%63.2

By child mortality

Share American Indian or Alaska Native, not HispanicChild mortality
Highest
Mississippi0.35%86.5
Louisiana0.408%78.6
Arkansas0.356%73
Alaska13.5%72.9
Alabama0.257%72.7
Lowest
Massachusetts0.0835%30.4
New Jersey0.0733%33.9
New Hampshire0.0777%34.6
Rhode Island0.157%34.7
Vermont0.139%36.3
Metro areas

By share American Indian or Alaska Native, not Hispanic

Share American Indian or Alaska Native, not HispanicChild mortality
Highest
Gallup, NM75.1%65.4
Show Low, AZ41.9%82.5
Lumberton, NC39.1%103
Farmington, NM38.5%60.3
Tahlequah, OK31.8%49.1
Lowest
Weirton-Steubenville, WV-OH0%68.1
Valdosta, GA0%68.9
Sikeston, MO0%65.5
Roanoke, VA0%66.5
Rio Grande City-Roma, TX0%46.2

By child mortality

Share American Indian or Alaska Native, not HispanicChild mortality
Highest
Rockingham, NC2.06%137
Greenwood, MS0%118
Orangeburg, SC0.323%110
Laurel, MS0%108
Monroe, LA0.107%107
Lowest
Corvallis, OR0.444%19.1
Blacksburg-Christiansburg-Radford, VA0.18%21.2
Santa Cruz-Watsonville, CA0.0835%27.5
Boston-Cambridge-Newton, MA-NH0.0727%27.6
San Jose-Sunnyvale-Santa Clara, CA0.151%28.3
Cities and towns — Child mortality is not published for cities and towns

By share American Indian or Alaska Native, not Hispanic

Share American Indian or Alaska Native, not HispanicChild mortality
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 — Child mortality is not published for ZIP codes

By share American Indian or Alaska Native, not Hispanic

Share American Indian or Alaska Native, not HispanicChild mortality
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 834 counties: the five with far more child mortality 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 HispanicChild mortality
Above the line
Atkinson County, GA0%171
Red River County, TX0.904%166
Franklin city, VA0%164
Kusilvak Census Area, AK86.4%274
Sanders County, MT2.37%148
Below the line
McKinley County, NM75.1%65.4
Apache County, AZ71.4%85.6
Cherokee County, OK31.8%49.1
San Juan County, NM38.5%60.3
Coconino County, AZ24.3%46.8

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+0.515833 counties reporting both
After adjusting for density, income and education+0.461the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.483size taken out as well as density
Also comparing only within each state+0.437each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.146the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 177 equally weighted counties
Middle value inside single states+0.352the link worked out inside each of 16 states with at least 20 counties reporting
Using ranks, after adjusting+0.037uses 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 = 7.1e-45. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 5.8e-5. 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 3.6e-44.

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 +0.26 (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 american indian or alaska native, not hispanic rose most, did child mortalitymove 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 pandemic798+0.06+0.070.327
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years693+0.01+0.030.771

Measured over the nearest years published: Child mortality: 2013–2019 for the 2014–2019 row; Child mortality: 2019–2022 for the 2019–2023 row.

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 American Indian or Alaska Native, not Hispanic and Child mortality