placestats

Share aged 65 and over and Vacancy rate

Where Share aged 65 and over is higher, Vacancy rate tends to be higher. The link is weak: +0.38 across 3,180 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 41 states, the middle value of the link is +0.63.

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

Vacancy rate

The percentage of all homes and apartments that nobody lives in. The middle county is 15%, which surprises people. It counts vacation and seasonal homes, so the top of the list is resort and outdoor-recreation areas, such as Daggett County, Utah at 77%, not abandoned towns. A high number can tell two very different stories, and this measure cannot tell them apart.

Census ACS 5-year · ACS table B25002_003, divided by housing units

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 overVacancy rate
Highest
Sumter County, FL57.8%16.7%
Catron County, NM44.5%50.6%
La Paz County, AZ42.2%34.9%
Charlotte County, FL40.4%23.9%
Lancaster County, VA40%26.9%
Lowest
Chattahoochee County, GA3.32%34.6%
Madison County, ID5.32%13.5%
Aleutians West Census Area, AK6.37%29.8%
Kusilvak Census Area, AK6.42%19.2%
Oglala Lakota County, SD7.07%21.1%

By vacancy rate

Share aged 65 and overVacancy rate
Highest
Daggett County, UT18.1%77.3%
Lake and Peninsula Borough, AK10%76.2%
Rich County, UT21.2%74.6%
Hamilton County, NY32.8%73.3%
Forest County, PA24%72.1%
Lowest
Somerset County, NJ16.6%2.54%
Scott County, MN12.3%2.6%
Kendall County, IL11%2.73%
Dakota County, MN15.4%2.73%
Loudoun County, VA10.4%2.75%
States

By share aged 65 and over

Share aged 65 and overVacancy rate
Highest
Puerto Rico22.7%21.3%
Maine21.9%21.1%
Florida21.1%15.2%
Vermont20.8%20.1%
West Virginia20.7%16.1%
Lowest
Utah11.6%8.23%
District of Columbia12.7%9.7%
Texas13.2%9.62%
Alaska13.3%18.2%
Georgia14.6%10.6%

By vacancy rate

Share aged 65 and overVacancy rate
Highest
Puerto Rico22.7%21.3%
Maine21.9%21.1%
Vermont20.8%20.1%
Alaska13.3%18.2%
West Virginia20.7%16.1%
Lowest
Washington16.3%7.42%
Oregon18.6%7.46%
Connecticut18.1%7.54%
California15.3%7.55%
New Jersey16.8%7.88%
Metro areas

By share aged 65 and over

Share aged 65 and overVacancy rate
Highest
Wildwood-The Villages, FL57.8%16.7%
Punta Gorda, FL40.4%23.9%
Port Townsend, WA39.6%16.5%
Homosassa Springs, FL36.3%16.4%
Sebring, FL35.9%20.9%
Lowest
Rexburg, ID7.86%26.3%
Provo-Orem-Lehi, UT7.87%3.82%
Fort Leonard Wood, MO9.6%15.2%
Andrews, TX9.67%4.01%
Hinesville, GA9.68%13.6%

By vacancy rate

Share aged 65 and overVacancy rate
Highest
Nantucket, MA15.5%59.5%
Vineyard Haven, MA26%58.4%
Ocean Pines, MD28.2%57.9%
Breckenridge, CO14.9%57.3%
Kill Devil Hills, NC24.3%52.7%
Lowest
Lancaster, PA19.2%3.36%
Appleton, WI16.1%3.77%
Provo-Orem-Lehi, UT7.87%3.82%
Andrews, TX9.67%4.01%
Greeley, CO12.7%4.01%
Cities and towns

By share aged 65 and over

Share aged 65 and overVacancy rate
Highest
Desert Palms CDP, CA86.4%24.8%
Sun City West CDP, AZ85.8%16.7%
The Villages CDP, FL85.2%16.2%
On Top of the World CDP, FL83.7%6.44%
Laguna Woods city, CA83%12.6%
Lowest
University of California-Davis CDP, CA0%17.5%
Fort Lewis CDP, WA0%13.3%
Clemson University CDP, SC0%100%
University at Buffalo CDP, NY0%0%
Fort Campbell North CDP, KY0%9.37%

By vacancy rate

Share aged 65 and overVacancy rate
Highest
Clemson University CDP, SC0%100%
Ocean City town, MD33%87%
Big Bear Lake city, CA20.7%76.7%
Orange Beach city, AL27.8%73.9%
Ocean City city, NJ34.2%73.1%
Lowest
Severance town, CO7.43%0%
Mead town, CO10.7%0%
South Monrovia Island CDP, CA9.79%0%
Salida CDP, CA12%0%
Dos Palos city, CA20.6%0%
ZIP codes

By share aged 65 and over

Share aged 65 and overVacancy rate
Highest
ZIP 32162 (The Villages CDP, FL)88.1%16.9%
ZIP 85375 (Sun City West CDP, AZ)85.2%16.7%
ZIP 92637 (Laguna Woods city, CA)83%12.6%
ZIP 85622 (Pima County, AZ)82.8%20.4%
ZIP 85351 (Sun City CDP, AZ)76.2%14.5%
Lowest
ZIP 98433 (Pierce County, WA)0%11%
ZIP 80310 (Boulder city, CO)0%0%
ZIP 79906 (Fort Bliss CDP, TX)0%12%
ZIP 79406 (Lubbock city, TX)0%100%
ZIP 55455 (Minneapolis city, MN)0%0%

By vacancy rate

Share aged 65 and overVacancy rate
Highest
ZIP 29634 (Clemson University CDP, SC)0%100%
ZIP 79406 (Lubbock city, TX)0%100%
ZIP 43210 (Columbus city, OH)0%84.6%
ZIP 21842 (Ocean City town, MD)28.1%82.3%
ZIP 08008 (Ocean County, NJ)43.1%80.1%
Lowest
ZIP 08886 (Warren County, NJ)13.5%0%
ZIP 08823 (Pleasant Plains CDP, NJ)14.8%0%
ZIP 08502 (Somerset County, NJ)10.3%0%
ZIP 07738 (Lincroft CDP, NJ)17.3%0%
ZIP 07630 (Emerson borough, NJ)24.9%0%

Counties furthest from the pattern

Compared with the straight line that best fits all 3,200 counties: the five with far more vacancy rate than their share aged 65 and over would suggest, and the five with far less.

Share aged 65 and overVacancy rate
Above the line
Lake and Peninsula Borough, AK10%76.2%
Daggett County, UT18.1%77.3%
Rich County, UT21.2%74.6%
Bristol Bay Borough, AK13.8%65.9%
Culebra Municipio, PR18.3%70.5%
Below the line
Sumter County, FL57.8%16.7%
Wahkiakum County, WA32.3%8.2%
Jefferson County, WA39.6%16.5%
Curry County, OR35.6%14%
Yavapai County, AZ33.5%12.2%

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+0.5283,180 counties reporting both
After adjusting for density, income and education+0.378the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.358size taken out as well as density
Also comparing only within each state+0.360each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.477the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 292 equally weighted counties
Middle value inside single states+0.630the link worked out inside each of 41 states with at least 20 counties reporting
Using ranks, after adjusting+0.392uses 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 = 2.0e-108. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 9.0e-9. 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 1.7e-107.

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 +0.32 (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 aged 65 and over rose most, did vacancy ratemove 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 pandemic3,205-0.05-0.01—
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years3,199-0.03-0.02—

Both come from the American Community Survey, which asks a sample of households. Random error in a county's sample pushes both changes at once. So part of any agreement here is that shared error. It is shown, but not counted as a finding. 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 aged 65 and over and Vacancy rate