Poverty rate and Share now married
Where Poverty rate is higher, Share now married tends to be lower. The link is weak: -0.40 across 3,139 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 -0.59.
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
Poverty rate
The percentage of people whose family income is below the federal poverty line. The line depends on how many people are in the family and their ages.
Census ACS 5-year · ACS table B17001_002, divided by population for whom poverty status is determined
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 poverty rate
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| Guánica Municipio, PR | 64.7% | 33.9% |
| Adjuntas Municipio, PR | 61.9% | 36.4% |
| Vieques Municipio, PR | 59.5% | 22.9% |
| Ciales Municipio, PR | 58.2% | 42.8% |
| Jayuya Municipio, PR | 54.9% | 34.4% |
| Lowest | ||
| Nantucket County, MA | 3.03% | 55.2% |
| Douglas County, CO | 3.23% | 62.5% |
| Powhatan County, VA | 3.26% | 58.9% |
| Falls Church city, VA | 3.64% | 53.1% |
| Hunterdon County, NJ | 3.85% | 60.4% |
By share now married
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| Blaine County, NE | 10.6% | 75.2% |
| McPherson County, NE | 7.13% | 74.7% |
| Campbell County, SD | 8.45% | 71.8% |
| Craig County, VA | 14% | 70.9% |
| Oliver County, ND | 4.73% | 70.8% |
| Lowest | ||
| Oglala Lakota County, SD | 52.8% | 18.4% |
| Vieques Municipio, PR | 59.5% | 22.9% |
| Radford city, VA | 33.7% | 25.9% |
| Sioux County, ND | 42.7% | 26.1% |
| ComerÃo Municipio, PR | 53% | 26.8% |
States
By poverty rate
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| Puerto Rico | 41.6% | 36.4% |
| Mississippi | 19.1% | 47.1% |
| Louisiana | 18.9% | 45.7% |
| New Mexico | 18.1% | 44.4% |
| West Virginia | 16.6% | 49.7% |
| Lowest | ||
| New Hampshire | 7.16% | 52.2% |
| Utah | 8.56% | 56.3% |
| Minnesota | 9.2% | 51.9% |
| Maryland | 9.35% | 48.9% |
| Colorado | 9.38% | 51.7% |
By share now married
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| Utah | 8.56% | 56.3% |
| Idaho | 10.6% | 55.1% |
| Wyoming | 10.7% | 54.5% |
| Nebraska | 10.3% | 52.8% |
| Kansas | 11.5% | 52.5% |
| Lowest | ||
| District of Columbia | 14.5% | 32.9% |
| Puerto Rico | 41.6% | 36.4% |
| New Mexico | 18.1% | 44.4% |
| Louisiana | 18.9% | 45.7% |
| Rhode Island | 10.9% | 46% |
Metro areas
By poverty rate
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| Lares, PR | 54.9% | 41.5% |
| Utuado, PR | 53.5% | 39.9% |
| Guayama, PR | 49.8% | 35.2% |
| Coamo, PR | 49.7% | 35.8% |
| Coco, PR | 48% | 38.6% |
| Lowest | ||
| Nantucket, MA | 3.03% | 55.2% |
| Heber, UT | 4.82% | 61.8% |
| Vineyard Haven, MA | 5.38% | 52.1% |
| Hood River, OR | 5.49% | 53.1% |
| Lexington Park, MD | 5.89% | 55.2% |
By share now married
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| Wildwood-The Villages, FL | 9.06% | 63.4% |
| Granbury, TX | 8.19% | 62.9% |
| Andrews, TX | 14.2% | 62.3% |
| Crossville, TN | 13.4% | 62.3% |
| Port Lavaca, TX | 8.73% | 62% |
| Lowest | ||
| Gallup, NM | 35.7% | 31.9% |
| Clarksdale, MS | 36.3% | 32.8% |
| Vermillion, SD | 19.8% | 34.3% |
| Guayama, PR | 49.8% | 35.2% |
| Ponce, PR | 48% | 35.5% |
Cities and towns
By poverty rate
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| Isla Vista CDP, CA | 69.3% | 4.48% |
| University of California-Davis CDP, CA | 67.7% | 5.71% |
| Caño Martin Peña comunidad, PR | 63% | 29.5% |
| Guánica zona urbana, PR | 62.1% | 37.8% |
| Utuado zona urbana, PR | 62% | 32.6% |
| Lowest | ||
| Linton Hall CDP, VA | 1.54% | 64.2% |
| Huntington Woods city, MI | 1.65% | 66.6% |
| Trussville city, AL | 1.65% | 66.6% |
| Hugo city, MN | 1.73% | 61% |
| Franklin Farm CDP, VA | 1.8% | 69% |
By share now married
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| Saddlebrooke CDP, AZ | 5.27% | 79.3% |
| Kaser village, NY | 61.3% | 78.9% |
| Williamson CDP, AZ | 3.65% | 78.1% |
| Longboat Key town, FL | 4.52% | 77.9% |
| Fairfield Glade CDP, TN | 7.88% | 77% |
| Lowest | ||
| Isla Vista CDP, CA | 69.3% | 4.48% |
| Cullowhee CDP, NC | 51.3% | 5.67% |
| University of California-Davis CDP, CA | 67.7% | 5.71% |
| University of California-Santa Barbara CDP, CA | 15.1% | 6.8% |
| Storrs CDP, CT | 42% | 7.47% |
ZIP codes
By poverty rate
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| ZIP 00913 (San Juan zona urbana, PR) | 73.3% | 17% |
| ZIP 00653 (Guánica Municipio, PR) | 66.2% | 33.8% |
| ZIP 00915 (San Juan zona urbana, PR) | 66% | 25% |
| ZIP 53233 (Milwaukee city, WI) | 62.1% | 7.02% |
| ZIP 32603 (Gainesville city, FL) | 62% | 10.1% |
| Lowest | ||
| ZIP 92136 (San Diego city, CA) | 0% | 33.4% |
| ZIP 54913 (Outagamie County, WI) | 1.42% | 62.9% |
| ZIP 55038 (Hugo city, MN) | 1.52% | 63.4% |
| ZIP 76226 (Denton County, TX) | 1.53% | 74.2% |
| ZIP 37135 (Williamson County, TN) | 1.56% | 66.2% |
By share now married
| Poverty rate | Share now married | |
|---|---|---|
| Highest | ||
| ZIP 13603 (Fort Drum CDP, NY) | 8.12% | 86.9% |
| ZIP 80902 (El Paso County, CO) | 11% | 85.3% |
| ZIP 31315 (Fort Stewart CDP, GA) | 13.8% | 82.3% |
| ZIP 34228 (Longboat Key town, FL) | 4.52% | 77.9% |
| ZIP 32163 (Wildwood city, FL) | 4.56% | 77.6% |
| Lowest | ||
| ZIP 53233 (Milwaukee city, WI) | 62.1% | 7.02% |
| ZIP 78705 (Austin city, TX) | 47.9% | 7.55% |
| ZIP 45219 (Cincinnati city, OH) | 47.5% | 8.62% |
| ZIP 02881 (Washington County, RI) | 35.4% | 8.86% |
| ZIP 32304 (Leon County, FL) | 49.4% | 9% |
Counties furthest from the pattern
Compared with the straight line that best fits all 3,149 counties: the five with far more share now married than their poverty rate would suggest, and the five with far less.
| Poverty rate | Share now married | |
|---|---|---|
| Above the line | ||
| Blaine County, NE | 10.6% | 75.2% |
| Craig County, VA | 14% | 70.9% |
| McPherson County, NE | 7.13% | 74.7% |
| Dolores County, CO | 18.8% | 66.5% |
| Campbell County, SD | 8.45% | 71.8% |
| Below the line | ||
| Lexington city, VA | 15.9% | 27.4% |
| Williamsburg city, VA | 14.1% | 29.8% |
| Issaquena County, MS | 17.2% | 28.8% |
| District of Columbia, DC | 14.5% | 32.9% |
| Petersburg city, VA | 21.1% | 29.2% |
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 | -0.645 | 3,139 counties reporting both |
| After adjusting for density, income and education | -0.399 | the part of the link that is not just how urban, rich and educated a place is |
| Also adjusting for population size | -0.412 | size taken out as well as density |
| Also comparing only within each state | -0.407 | 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 | -0.479 | 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 | -0.593 | the link worked out inside each of 41 states with at least 20 counties reporting |
| Using ranks, after adjusting | -0.395 | 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 = 1.8e-120. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 7.5e-5. 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 1.6e-119.
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 +0.26 (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 poverty 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 | 3,147 | -0.13 | -0.13 | — |
| 2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years | 3,123 | -0.17 | -0.17 | — |
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
- Median household income and Poverty rate — -0.76
- Poverty rate and Returns claiming the earned income credit — +0.62
- Share now married and Republican share of the two-party vote, 2020 — +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
- Poverty rate and Homicide rate, annual — +0.55
- Poverty rate and Share White, not Hispanic — -0.54
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 Poverty rate and Share now married