placestats

Children in single-parent households and Heating degree days

Where Children in single-parent households is higher, Heating degree days tends to be lower. The link is weak: -0.34 across 2,787 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 38 states, the middle value of the link is -0.13.

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.

Loading every place…

What each measure is

Children in single-parent households

The percentage of children who live in a household headed by one parent.

County Health Rankings · County Health Rankings v082

Heating degree days

A measure of how cold the year was, as a total over its days. A day whose average temperature is 50°F counts 15 heating degree days, the degrees it fell short of 65°F. A day at 65°F or warmer counts none. Homes often need heat on days below 65°F, so more degree days mean more heating weather. NOAA estimates them from its monthly temperatures for each county. A state's figure is the average of its counties, each weighted by its land area. Alaska and Hawaii are not covered.

NOAA NCEI nClimDiv · NOAA NCEI nClimDiv climdiv-hddccy, sum of the 12 months; states, counties averaged by land area

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 children in single-parent households

Children in single-parent householdsHeating degree days
Highest
McCormick County, SC0.779%2,139
Wilcox County, AL0.754%1,707
East Carroll Parish, LA0.746%1,804
Culberson County, TX0.726%2,451
Bullock County, AL0.713%1,826
Lowest
Kenedy County, TX0%498
Jeff Davis County, TX0%2,433
Esmeralda County, NV0%5,487
Blaine County, NE0%6,461
Meagher County, MT0%8,754

By heating degree days

Children in single-parent householdsHeating degree days
Highest
Sublette County, WY0.166%10,945
Teton County, WY0.147%10,855
Lincoln County, WY0.0747%9,988
Gunnison County, CO0.163%9,928
Chaffee County, CO0.265%9,891
Lowest
Monroe County, FL0.225%83
Miami-Dade County, FL0.296%85
Broward County, FL0.307%108
Palm Beach County, FL0.266%167
Collier County, FL0.242%167
States

By children in single-parent households

Children in single-parent householdsHeating degree days
Highest
Mississippi0.37%1,888
Louisiana0.345%1,414
Alabama0.306%2,025
New Mexico0.305%4,654
Georgia0.304%1,879
Lowest
Utah0.146%6,668
Idaho0.17%8,000
North Dakota0.181%8,901
Wyoming0.181%8,670
New Hampshire0.184%6,926

By heating degree days

Children in single-parent householdsHeating degree days
Highest
North Dakota0.181%8,901
Wyoming0.181%8,670
Minnesota0.194%8,233
Montana0.201%8,065
Idaho0.17%8,000
Lowest
Florida0.274%647
Louisiana0.345%1,414
Georgia0.304%1,879
Mississippi0.37%1,888
Texas0.254%1,901
Metro areas

By children in single-parent households

Children in single-parent householdsHeating degree days
Highest
Greenwood, MS0.589%1,943
Greenville, MS0.565%2,042
Orangeburg, SC0.565%1,913
Clarksdale, MS0.554%2,241
Natchez, MS-LA0.541%1,530
Lowest
Rexburg, ID0.0695%9,153
Washington, IN0.0878%4,116
Selinsgrove, PA0.0956%5,040
Granbury, TX0.0972%1,835
Decatur, IN0.103%5,089

By heating degree days

Children in single-parent householdsHeating degree days
Highest
Jackson, WY-ID0.147%10,692
Edwards, CO0.209%9,543
Evanston, WY-UT0.124%9,512
Cody, WY0.219%9,355
Heber, UT0.153%9,256
Lowest
Key West-Key Largo, FL0.225%83
Miami-Fort Lauderdale-West Palm Beach, FL0.292%122
Naples-Marco Island, FL0.242%167
Cape Coral-Fort Myers, FL0.253%218
Port St. Lucie, FL0.267%219

Counties furthest from the pattern

Compared with the straight line that best fits all 2,796 counties: the five with far more heating degree days than their children in single-parent households would suggest, and the five with far less.

Children in single-parent householdsHeating degree days
Above the line
Benson County, ND0.597%9,342
Sioux County, ND0.575%8,448
Rolette County, ND0.406%9,529
Deer Lodge County, MT0.318%9,811
Mahnomen County, MN0.397%9,047
Below the line
Kenedy County, TX0%498
St. Johns County, FL0.151%646
Chambers County, TX0.121%951
Martin County, FL0.211%200
Monroe County, FL0.225%83

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.

Loading…

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-0.4552,787 counties reporting both
After adjusting for density, income and education-0.339the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.339size taken out as well as density
Also comparing only within each state-0.118each county is compared only with others in its own state, so this is no longer a comparison between states
Also holding winter sunshine equal-0.166compares counties that get the same sunlight in winter as well. If this is much weaker, part of the link is a difference between sunny and grey regions (more)
Giving bigger counties more weight-0.198the 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-0.131the link worked out inside each of 38 states with at least 20 counties reporting
Using ranks, after adjusting-0.335uses 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 = 1.0e-75. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 3.5e-9. The site tested 32,131 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 8.8e-75.

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 +0.75 (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 children in single-parent households rose most, did heating degree daysmove 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 pandemic2,828-0.04-0.010.693
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years2,726+0.05+0.040.102

Over the main period, any link between the changes could easily be chance. 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 Children in single-parent households and Heating degree days