placestats

Lacking social and emotional support and Heating degree days

Where Lacking social and emotional support is higher, Heating degree days tends to be lower. The link is moderate: -0.45 across 2,255 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 29 states, the middle value of the link is -0.18.

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

Lacking social and emotional support

The estimated percentage of adults who rarely or never get the social and emotional support they need. It is adjusted so places with older or younger populations can be compared fairly. It is an estimate from a statistical model, not a direct count from a local survey.

CDC PLACES · PLACES EMOTIONSPT, age-adjusted

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 lacking social and emotional support

Lacking social and emotional supportHeating degree days
Highest
East Carroll Parish, LA37.8%1,804
Holmes County, MS37.8%1,858
Issaquena County, MS37.2%1,779
Jefferson County, MS36.4%1,581
Apache County, AZ36.3%5,771
Lowest
Wasatch County, UT16.7%8,749
Waukesha County, WI17.1%6,215
Falls Church city, VA17.1%3,682
Johnson County, KS17.1%4,285
Summit County, UT17.2%9,575

By heating degree days

Lacking social and emotional supportHeating degree days
Highest
Custer County, ID19.9%9,880
Deer Lodge County, MT22.9%9,811
Beaverhead County, MT21.6%9,805
Cavalier County, ND21.6%9,731
Cook County, MN20.9%9,665
Lowest
Plaquemines Parish, LA29.4%871
Terrebonne Parish, LA29.1%921
Lafourche Parish, LA29.2%931
Jefferson Parish, LA28.6%948
St. Bernard Parish, LA30.2%983
States — Lacking social and emotional support is not published for states

By heating degree days

Lacking social and emotional supportHeating degree days
Highest
North Dakota—8,901
Wyoming—8,670
Minnesota—8,233
Montana—8,065
Idaho—8,000
Lowest
Florida—647
Louisiana—1,414
Georgia—1,879
Mississippi—1,888
Texas—1,901
Metro areas

By lacking social and emotional support

Lacking social and emotional supportHeating degree days
Highest
Clarksdale, MS34.4%2,241
Forrest City, AR34.2%2,582
Greenville, MS34.1%2,042
Pine Bluff, AR33.9%2,322
Greenwood, MS33.2%1,943
Lowest
Heber, UT17%9,256
Jackson, WY-ID18.5%10,692
Provo-Orem-Lehi, UT18.5%6,602
Columbia, MO18.6%4,211
Logan, UT-ID18.6%8,048

By heating degree days

Lacking social and emotional supportHeating degree days
Highest
Jackson, WY-ID18.5%10,692
Evanston, WY-UT19.4%9,512
Heber, UT17%9,256
Butte-Silver Bow, MT21.7%9,211
Rexburg, ID20.1%9,153
Lowest
Houma-Bayou Cane-Thibodaux, LA29.1%926
New Orleans-Metairie, LA29.9%960
Morgan City, LA31.8%991
El Centro, CA31.2%1,007
Kingsland, GA23.6%1,030
Cities and towns — Heating degree days is not published for cities and towns

By lacking social and emotional support

Lacking social and emotional supportHeating degree days
Highest
Rosemead city, CA39.9%—
Bastrop city, LA38.2%—
East St. Louis city, IL37.8%—
Westmont CDP, CA37.6%—
Yazoo City city, MS37.5%—
Lowest
Prairie Village city, KS14.7%—
Glendale city, MO15%—
Elm Grove village, WI15.1%—
Leawood city, KS15.1%—
Midway city, UT15.3%—

Counties furthest from the pattern

Compared with the straight line that best fits all 2,263 counties: the five with far more heating degree days than their lacking social and emotional support would suggest, and the five with far less.

Lacking social and emotional supportHeating degree days
Above the line
Rolette County, ND28.7%9,529
Sioux County, ND30.1%8,448
Mahnomen County, MN27.6%9,047
Apache County, AZ36.3%5,771
Benson County, ND25.8%9,342
Below the line
Beaufort County, SC20.4%1,391
Baldwin County, AL21.9%1,205
Charleston County, SC21.7%1,474
New Hanover County, NC20.5%1,956
Dare County, NC19.5%2,342

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-0.5512,255 counties reporting both
After adjusting for density, income and education-0.445the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.470size taken out as well as density
Also comparing only within each state-0.182each county is compared only with others in its own state, so this is no longer a comparison between states
Also holding winter sunshine equal-0.277compares 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-0.438the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 189 equally weighted counties
Middle value inside single states-0.180the link worked out inside each of 29 states with at least 20 counties reporting
Using ranks, after adjusting-0.397uses 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 = 3.2e-110. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 7.0e-6. 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 3.5e-109.

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?

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 Lacking social and emotional support and Heating degree days