Homeownership rate and Share now married
Where Homeownership rate is higher, Share now married tends to be higher. The link is moderate: +0.46 across 3,198 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
Homeownership rate
The percentage of lived-in homes that are owned, not rented. Empty homes are left out of the count entirely.
Census ACS 5-year · ACS table B25003_002, divided by occupied housing units
Share now married
The percentage of people aged 15 and over who are married now, including those whose spouse lives elsewhere. The middle county is 52.4%. Never married, married, widowed and divorced cover everyone 15 and over and add up to exactly 100%.
Census ACS 5-year · ACS table B12001_004…B12001_013 (2 cells), divided by population aged 15 and over
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 homeownership rate
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| Storey County, NV | 97.4% | 49.7% |
| Cameron Parish, LA | 96.9% | 64.3% |
| Edwards County, TX | 94.5% | 40.1% |
| Elbert County, CO | 94.4% | 65.9% |
| Oliver County, ND | 93.4% | 70.8% |
| Lowest | ||
| Bronx County, NY | 20.3% | 36.2% |
| New York County, NY | 24.7% | 36.8% |
| Aleutians West Census Area, AK | 29.5% | 51.9% |
| Kings County, NY | 29.7% | 43.1% |
| Hudson County, NJ | 31.2% | 45.9% |
By share now married
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| Borden County, TX | 63.6% | 82.6% |
| Glasscock County, TX | 66.4% | 80.5% |
| Thomas County, NE | 69.8% | 77.5% |
| Banner County, NE | 75.6% | 75.4% |
| Blaine County, NE | 71.4% | 75.2% |
| Lowest | ||
| Oglala Lakota County, SD | 53.5% | 18.4% |
| Vieques Municipio, PR | 68.9% | 22.9% |
| Radford city, VA | 42.7% | 25.9% |
| Sioux County, ND | 46% | 26.1% |
| ComerÃo Municipio, PR | 61.7% | 26.8% |
States
By homeownership rate
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| West Virginia | 74.3% | 49.7% |
| Maine | 74% | 51.5% |
| Michigan | 72.9% | 48.7% |
| Vermont | 72.8% | 49.1% |
| New Hampshire | 72.5% | 52.2% |
| Lowest | ||
| District of Columbia | 41.1% | 32.9% |
| New York | 54.3% | 46.8% |
| California | 55.8% | 48.4% |
| Nevada | 59.3% | 47.2% |
| Hawaii | 62.6% | 50.6% |
By share now married
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| Utah | 70.6% | 56.3% |
| Idaho | 72.4% | 55.1% |
| Wyoming | 71.9% | 54.5% |
| Nebraska | 66.5% | 52.8% |
| Kansas | 66.9% | 52.5% |
| Lowest | ||
| District of Columbia | 41.1% | 32.9% |
| Puerto Rico | 68.1% | 36.4% |
| New Mexico | 69.3% | 44.4% |
| Louisiana | 67.3% | 45.7% |
| Rhode Island | 63.3% | 46% |
Metro areas
By homeownership rate
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| Wildwood-The Villages, FL | 88.1% | 63.4% |
| Hemlock Farms, PA | 86.2% | 55.8% |
| Holland, MI | 86.1% | 57.6% |
| Homosassa Springs, FL | 84.8% | 54.7% |
| DeRidder, LA | 83.2% | 53% |
| Lowest | ||
| Pullman, WA | 46.6% | 36.8% |
| Los Angeles-Long Beach-Anaheim, CA | 48.6% | 46.3% |
| Carbondale, IL | 49.3% | 37.9% |
| Laramie, WY | 49.4% | 41.7% |
| Lawrence, KS | 49.5% | 42.9% |
By share now married
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| Wildwood-The Villages, FL | 88.1% | 63.4% |
| Granbury, TX | 81.3% | 62.9% |
| Andrews, TX | 76.3% | 62.3% |
| Crossville, TN | 80.2% | 62.3% |
| Port Lavaca, TX | 76.4% | 62% |
| Lowest | ||
| Gallup, NM | 68.8% | 31.9% |
| Clarksdale, MS | 52% | 32.8% |
| Vermillion, SD | 51.8% | 34.3% |
| Guayama, PR | 72.4% | 35.2% |
| Ponce, PR | 71.4% | 35.5% |
Cities and towns
By homeownership rate
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| East Hills village, NY | 100% | 67.6% |
| White Rock CDP, NM | 99.6% | 69.9% |
| Hooper city, UT | 99.4% | 65.1% |
| Marvin village, NC | 99.3% | 73.2% |
| Todd Creek CDP, CO | 99.2% | 72.9% |
| Lowest | ||
| Fort Carson CDP, CO | 0% | 46.2% |
| Air Force Academy CDP, CO | 0% | 18.9% |
| Camp Pendleton Mainside CDP, CA | 0% | 26.8% |
| North Fort Lewis CDP, WA | 0% | 49.9% |
| Lackland AFB CDP, TX | 0% | 18.6% |
By share now married
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| St. James town, NC | 95.7% | 87.7% |
| The Village of Indian Hill city, OH | 94% | 80.4% |
| Tellico Village CDP, TN | 96.1% | 79.9% |
| Saddlebrooke CDP, AZ | 95.4% | 79.3% |
| Tega Cay city, SC | 85.2% | 79.1% |
| Lowest | ||
| Rutgers University-Busch Campus CDP, NJ | 0% | 3.78% |
| Storrs CDP, CT | 29.9% | 7.47% |
| Prairie View city, TX | 20.7% | 8.26% |
| University of Virginia CDP, VA | 15.7% | 8.98% |
| Kingston CDP, RI | 78.2% | 13% |
ZIP codes
By homeownership rate
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| ZIP 29207 (Columbia city, SC) | 100% | 16.5% |
| ZIP 08056 (Gloucester County, NJ) | 100% | 65.1% |
| ZIP 48380 (Oakland County, MI) | 99.7% | 62.1% |
| ZIP 87547 (White Rock CDP, NM) | 99.6% | 69.9% |
| ZIP 06419 (Middlesex County, CT) | 99.5% | 66.4% |
| Lowest | ||
| ZIP 92136 (San Diego city, CA) | 0% | 33.4% |
| ZIP 85613 (Sierra Vista city, AZ) | 0% | 46.6% |
| ZIP 80902 (El Paso County, CO) | 0% | 85.3% |
| ZIP 80840 (El Paso County, CO) | 0% | 18.9% |
| ZIP 79906 (Fort Bliss CDP, TX) | 0% | 75.4% |
By share now married
| Homeownership rate | Share now married | |
|---|---|---|
| Highest | ||
| ZIP 80902 (El Paso County, CO) | 0% | 85.3% |
| ZIP 78619 (Hays County, TX) | 91.6% | 82.9% |
| ZIP 84310 (Weber County, UT) | 91.2% | 78.2% |
| ZIP 34228 (Longboat Key town, FL) | 93.6% | 77.9% |
| ZIP 32163 (Wildwood city, FL) | 95.6% | 77.6% |
| Lowest | ||
| ZIP 95064 (Santa Cruz city, CA) | 35.2% | 5.22% |
| ZIP 53233 (Milwaukee city, WI) | 3.3% | 7.02% |
| ZIP 78705 (Austin city, TX) | 11.6% | 7.55% |
| ZIP 45219 (Cincinnati city, OH) | 17.6% | 8.62% |
| ZIP 02881 (Washington County, RI) | 43.4% | 8.86% |
Counties furthest from the pattern
Compared with the straight line that best fits all 3,218 counties: the five with far more share now married than their homeownership rate would suggest, and the five with far less.
| Homeownership rate | Share now married | |
|---|---|---|
| Above the line | ||
| Borden County, TX | 63.6% | 82.6% |
| Glasscock County, TX | 66.4% | 80.5% |
| Thomas County, NE | 69.8% | 77.5% |
| Blaine County, NE | 71.4% | 75.2% |
| McPherson County, NE | 73% | 74.7% |
| Below the line | ||
| Vieques Municipio, PR | 68.9% | 22.9% |
| Oglala Lakota County, SD | 53.5% | 18.4% |
| Wilkinson County, MS | 79% | 31.2% |
| Culberson County, TX | 74.1% | 29.2% |
| Arroyo Municipio, PR | 76.8% | 30.9% |
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 | +0.547 | 3,198 counties reporting both |
| After adjusting for density, income and education | +0.456 | the part of the link that is not just how urban, rich and educated a place is |
| Also adjusting for population size | +0.438 | size taken out as well as density |
| Also comparing only within each state | +0.434 | each county is compared only with others in its own state, so this is no longer a comparison between states |
| Giving bigger counties more weight | +0.545 | the 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 | +0.628 | the link worked out inside each of 41 states with at least 20 counties reporting |
| Using ranks, after adjusting | +0.477 | uses 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 = 4.1e-164. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 7.2e-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 4.3e-163.
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 +0.28 (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 homeownership rate rose most, did share now marriedmove 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.
| Period | Counties | Change together | Within states | q |
|---|---|---|---|---|
| 2014–2019 the main test: each Census survey figure averages five years, and these two do not overlap; before the pandemic | 3,216 | +0.08 | +0.07 | — |
| 2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years | 3,218 | +0.04 | +0.04 | — |
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
- Share now married and Republican share of the two-party vote, 2020 — +0.58
- Homeownership rate and Median age — +0.58
- Share now married and Republican share of the two-party vote, 2016 — +0.57
- Share now married and Republican share of the two-party vote, 2024 — +0.56
- Share now married and Children in single-parent households — -0.55
- Median household income and Share now married — +0.54
- Homeownership rate and Share never married — -0.53
- Share now married and Homicide rate, annual — -0.53
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 Homeownership rate and Share now married