placestats

Infant mortality and Disability-free score

Across 1,102 counties, Infant mortality and Disability-free score have a link of -0.65, 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 -0.25 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

Infant mortality

Deaths of babies before their first birthday per 1,000 babies born alive.

County Health Rankings · County Health Rankings v129

Disability-free score

How common disability is, across seven kinds, flipped so higher means less disability. It is kept out of the health score on purpose. Disability goes with age and with how people report it as much as with anything a county does. Adding it would make an older county look sicker just for being older.

· derived from 13 measures (BRFSS, CDC)

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 infant mortality

Infant mortalityDisability-free score
Highest
Kusilvak Census Area, AK20.2-4.04
Oglala Lakota County, SD16.9-5.31
Todd County, SD15.4-4.83
Big Horn County, MT15.3-1.86
Cheboygan County, MI14.60.0885
Lowest
Marin County, CA1.571.42
San Francisco County, CA2.651.46
Placer County, CA2.711.25
Rockingham County, NH2.741.57
Sherburne County, MN2.761.05

By disability-free score

Infant mortalityDisability-free score
Highest
Somerset County, NJ3.511.94
Howard County, MD5.211.93
Morris County, NJ2.871.92
Delaware County, OH3.551.92
Hunterdon County, NJ31.85
Lowest
Oglala Lakota County, SD16.9-5.31
Todd County, SD15.4-4.83
Kusilvak Census Area, AK20.2-4.04
McKinley County, NM6.02-3.21
Starr County, TX4.84-3.02
States

By infant mortality

Infant mortalityDisability-free score
Highest
Mississippi8.7-1.8
Arkansas7.78-2.14
Louisiana7.53-1.7
Alabama7.49-1.41
West Virginia7.09-2.47
Lowest
Massachusetts3.720.25
New Hampshire3.820.329
New Jersey3.980.837
Vermont4.080.575
California4.12-0.029

By disability-free score

Infant mortalityDisability-free score
Highest
New Jersey3.980.837
Connecticut4.490.779
Maryland6.130.742
Hawaii5.520.63
North Dakota5.260.628
Lowest
West Virginia7.09-2.47
Arkansas7.78-2.14
Mississippi8.7-1.8
Tennessee6.82-1.72
Louisiana7.53-1.7
Metro areas

By infant mortality

Infant mortalityDisability-free score
Highest
Forrest City, AR13.3-2.5
Greenville, MS13.1-2.6
Minden, LA12.9-2.53
Natchitoches, LA12.2-1.59
Kinston, NC12-1.69
Lowest
Santa Fe, NM2.80.924
Rexburg, ID2.96-1.03
San Jose-Sunnyvale-Santa Clara, CA3.011.83
Bend, OR3.111.03
Santa Rosa-Petaluma, CA3.140.958

By disability-free score

Infant mortalityDisability-free score
Highest
San Jose-Sunnyvale-Santa Clara, CA3.011.83
Boulder, CO3.251.71
Ithaca, NY5.211.65
Seattle-Tacoma-Bellevue, WA4.131.64
Barnstable Town, MA3.321.58
Lowest
Gallup, NM6.02-4.13
Rio Grande City-Roma, TX4.84-3.85
Clarksdale, MS10.2-3.09
Lumberton, NC9.54-2.92
Greenville, MS13.1-2.6

Counties furthest from the pattern

Compared with the straight line that best fits all 1,103 counties: the five with far more disability-free score than their infant mortality would suggest, and the five with far less.

Infant mortalityDisability-free score
Above the line
McKenzie County, ND130.529
Cheboygan County, MI14.60.0885
Banks County, GA14.5-0.148
Howard County, MD5.211.93
Sumter County, FL8.870.963
Below the line
Starr County, TX4.84-3.02
McKinley County, NM6.02-3.21
Oglala Lakota County, SD16.9-5.31
Todd County, SD15.4-4.83
Hidalgo County, TX4.63-1.73

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-0.6521,102 counties reporting both
After adjusting for density, income and education-0.253the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.262size taken out as well as density
Also comparing only within each state-0.252each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.054the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 210 equally weighted counties
Middle value inside single states-0.630the link worked out inside each of 22 states with at least 20 counties reporting
Using ranks, after adjusting-0.014uses 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 = 1.6e-17. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.006. 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 4.8e-17.

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 +0.51 (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 Infant mortality and Disability-free score