placestats

Share aged 65 and over and Public-good pages per 1,000 users

Where Share aged 65 and over is higher, Public-good pages per 1,000 users tends to be higher. The link is moderate: +0.42 across 3,076 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 +0.53.

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 aged 65 and over

The percentage of all residents, children included, who are 65 or older. It is a share of everyone, not just of adults. The typical county is 19.7%, and four in five are between 14% and 26%. The extremes come from one big group living there, not from places that aged differently: Sumter County, Florida reaches 57.8% since The Villages retirement community is there. Chattahoochee County, Georgia is 3.3% since it is mostly Fort Benning, an army base, and Madison County, Idaho is 5.3% since it is a university town.

Census ACS 5-year · ACS table B01001_020…B01001_049 (12 cells), divided by total population

Public-good pages per 1,000 users

Facebook pages for community groups and public-good efforts, per thousand Facebook users. It is per user, not per resident.

Social Capital Atlas · Opportunity Insights civic_organizations_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 aged 65 and over

Share aged 65 and overPublic-good pages per 1,000 users
Highest
Sumter County, FL57.8%0.0171
Catron County, NM44.5%0.0516
La Paz County, AZ42.2%0.0282
Charlotte County, FL40.4%0.0193
Lancaster County, VA40%0.0491
Lowest
Chattahoochee County, GA3.32%0.0216
Madison County, ID5.32%0.0082
Aleutians West Census Area, AK6.37%0.0109
Kusilvak Census Area, AK6.42%0.0082
Oglala Lakota County, SD7.07%0.0165

By public-good pages per 1,000 users

Share aged 65 and overPublic-good pages per 1,000 users
Highest
Douglas County, MO25%0.195
Bristol Bay Borough, AK13.8%0.12
San Juan County, CO20.7%0.112
Lewis County, ID27.8%0.106
Alpine County, CA21.8%0.0828
Lowest
Humphreys County, MS18.4%0.00349
Winkler County, TX13.4%0.00361
Jefferson County, MS19.3%0.00375
Maverick County, TX11.9%0.00381
Starr County, TX11.2%0.00414
States — Public-good pages per 1,000 users is not published for states

By share aged 65 and over

Share aged 65 and overPublic-good pages per 1,000 users
Highest
Puerto Rico22.7%—
Maine21.9%—
Florida21.1%—
Vermont20.8%—
West Virginia20.7%—
Lowest
Utah11.6%—
District of Columbia12.7%—
Texas13.2%—
Alaska13.3%—
Georgia14.6%—
Metro areas

By share aged 65 and over

Share aged 65 and overPublic-good pages per 1,000 users
Highest
Wildwood-The Villages, FL57.8%0.0171
Punta Gorda, FL40.4%0.0193
Port Townsend, WA39.6%0.0442
Homosassa Springs, FL36.3%0.017
Sebring, FL35.9%0.0175
Lowest
Rexburg, ID7.86%0.0122
Provo-Orem-Lehi, UT7.87%0.00431
Fort Leonard Wood, MO9.6%0.0192
Andrews, TX9.67%0.0107
Hinesville, GA9.68%0.0124

By public-good pages per 1,000 users

Share aged 65 and overPublic-good pages per 1,000 users
Highest
Vermillion, SD12.2%0.0451
Port Townsend, WA39.6%0.0442
Vineyard Haven, MA26%0.0418
Barre, VT21%0.0411
Ithaca, NY16%0.0406
Lowest
Eagle Pass, TX11.9%0.00381
Rio Grande City-Roma, TX11.2%0.00414
Laredo, TX10%0.00422
Provo-Orem-Lehi, UT7.87%0.00431
Zapata, TX13.5%0.00436
Cities and towns — Public-good pages per 1,000 users is not published for cities and towns

By share aged 65 and over

Share aged 65 and overPublic-good pages per 1,000 users
Highest
Desert Palms CDP, CA86.4%—
Sun City West CDP, AZ85.8%—
The Villages CDP, FL85.2%—
On Top of the World CDP, FL83.7%—
Laguna Woods city, CA83%—
Lowest
University of California-Davis CDP, CA0%—
Fort Irwin CDP, CA0%—
Camp Pendleton South CDP, CA0%—
North Fort Lewis CDP, WA0%—
Fort Lewis CDP, WA0%—
ZIP codes — Public-good pages per 1,000 users is not published for ZIP codes

By share aged 65 and over

Share aged 65 and overPublic-good pages per 1,000 users
Highest
ZIP 32162 (The Villages CDP, FL)88.1%—
ZIP 85375 (Sun City West CDP, AZ)85.2%—
ZIP 92637 (Laguna Woods city, CA)83%—
ZIP 85622 (Pima County, AZ)82.8%—
ZIP 85351 (Sun City CDP, AZ)76.2%—
Lowest
ZIP 99703 (Fairbanks city, AK)0%—
ZIP 98433 (Pierce County, WA)0%—
ZIP 93410 (California Polytechnic State University CDP, CA)0%—
ZIP 93106 (University of California-Santa Barbara CDP, CA)0%—
ZIP 92310 (San Bernardino County, CA)0%—

Counties furthest from the pattern

Compared with the straight line that best fits all 3,091 counties: the five with far more public-good pages per 1,000 users than their share aged 65 and over would suggest, and the five with far less.

Share aged 65 and overPublic-good pages per 1,000 users
Above the line
Douglas County, MO25%0.195
Bristol Bay Borough, AK13.8%0.12
San Juan County, CO20.7%0.112
Lewis County, ID27.8%0.106
Cheyenne County, CO19.9%0.0822
Below the line
Sumter County, FL57.8%0.0171
Charlotte County, FL40.4%0.0193
Adams County, WI31.6%0.0112
Mohave County, AZ31.9%0.0122
Citrus County, FL36.3%0.017

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+0.5033,076 counties reporting both
After adjusting for density, income and education+0.422the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.393size taken out as well as density
Also comparing only within each state+0.366each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.402the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 286 equally weighted counties
Middle value inside single states+0.529the link worked out inside each of 40 states with at least 20 counties reporting
Using ranks, after adjusting+0.466uses 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 = 1.1e-132. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 3.2e-14. 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 1.0e-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 +0.10 (p = 0.001). Once the adjustment is made, little map pattern is left.

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 aged 65 and over and Public-good pages per 1,000 users