placestats

Life expectancy and Material security score

Where Life expectancy is higher, Material security score tends to be higher. The link is moderate: +0.42 across 3,033 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 40 states, the middle value of the link is +0.66.

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

Life expectancy

How long a baby born here would live if today's death rates stayed the same all its life. It sums up death rates now. It is not a prediction for any real child.

County Health Rankings · County Health Rankings v147

Material security score

Poverty, child poverty, income inequality, and four basic-needs measures from CDC PLACES: food, housing, utilities and transport. It is flipped so higher means less hardship, which is why it is named for security, not for what it counts.

· derived from 9 measures (ACS, BRFSS, CDC, SAIPE)

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 life expectancy

Life expectancyMaterial security score
Highest
Pitkin County, CO94.2 years0.0626
Mono County, CA93.6 years0.685
Summit County, CO92.4 years1.07
Oliver County, ND92.2 years1.2
Eagle County, CO89.7 years0.536
Lowest
Buffalo County, SD54 years-1.96
Dewey County, SD56.7 years-1.08
Oglala Lakota County, SD56.9 years-2.77
Corson County, SD58.7 years-2.5
Todd County, SD58.7 years-2.56

By material security score

Life expectancyMaterial security score
Highest
Morgan County, UT81 years1.83
Los Alamos County, NM83 years1.82
Douglas County, CO82.5 years1.69
Loudoun County, VA83.8 years1.64
Forsyth County, GA81 years1.56
Lowest
East Carroll Parish, LA71.1 years-3.95
Holmes County, MS65.7 years-3.64
Ziebach County, SD65.8 years-3.46
Martin County, KY70.6 years-3.33
Sioux County, ND59.6 years-3.24
States

By life expectancy

Life expectancyMaterial security score
Highest
Hawaii81.4 years1.14
Massachusetts79.7 years0.747
California79.4 years0.0683
New York79.4 years-0.294
Minnesota79.3 years0.969
Lowest
Mississippi71.9 years-1.25
West Virginia72.1 years-0.691
Alabama73.3 years-0.811
Kentucky73.3 years-0.558
Louisiana73.3 years-1.02

By material security score

Life expectancyMaterial security score
Highest
New Hampshire78.9 years1.36
Hawaii81.4 years1.14
Vermont78.7 years1.07
Minnesota79.3 years0.969
Utah78.8 years0.93
Lowest
Mississippi71.9 years-1.25
Texas76.7 years-1.03
Louisiana73.3 years-1.02
Arkansas73.7 years-0.851
Alabama73.3 years-0.811
Metro areas — Life expectancy is not published for metro areas

By material security score

Life expectancyMaterial security score
Highest
Los Alamos, NM—2.07
Heber, UT—1.79
Nantucket, MA—1.7
Appleton, WI—1.55
Manchester-Nashua, NH—1.44
Lowest
Gallup, NM—-4.3
Clarksdale, MS—-3.97
Cleveland, MS—-3.8
Greenville, MS—-3.64
Selma, AL—-3.37

Counties furthest from the pattern

Compared with the straight line that best fits all 3,041 counties: the five with far more material security score than their life expectancy would suggest, and the five with far less.

Life expectancyMaterial security score
Above the line
Kingman County, KS61 years0.723
Armstrong County, TX69.7 years1.31
Dallam County, TX70.4 years1.26
Edwards County, KS63.6 years0.186
Dewey County, SD56.7 years-1.08
Below the line
East Carroll Parish, LA71.1 years-3.95
Presidio County, TX81.3 years-2
Pitkin County, CO94.2 years0.0626
Martin County, KY70.6 years-3.33
Claiborne Parish, LA73.8 years-2.68

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+0.7003,033 counties reporting both
After adjusting for density, income and education+0.423the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.426size taken out as well as density
Also comparing only within each state+0.349each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.165the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 282 equally weighted counties
Middle value inside single states+0.657the link worked out inside each of 40 states with at least 20 counties reporting
Using ranks, after adjusting+0.312uses 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 = 5.3e-132. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 2.7e-11. 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 4.9e-131.

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 +0.50 (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 Life expectancy and Material security score