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Share Hispanic or Latino, any race and Days of 90°F or hotter

Where Share Hispanic or Latino, any race is higher, Days of 90°F or hotter tends to be higher. The link is moderate: +0.51 across 2,843 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 39 states, the middle value of the link is +0.12.

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 Hispanic or Latino, any race

The percentage of residents who are Hispanic or Latino, of any race. The Census asks about Hispanic origin separately from race. So this figure includes all races, and the race shares next to it count only people who are 'not Hispanic'.

Census ACS 5-year · ACS table B03002_012, divided by total population

Days of 90°F or hotter

The number of days in the year when the high temperature reached 90°F or more. The high is the average over the county of NOAA's daily map of weather station readings, made of squares about 3 miles wide. So a county with hot valleys and cool mountains counts fewer days than its hottest town. A state's figure is the average of its counties, each weighted by its land area. Lower 48 states only, from 1951.

NOAA NCEI nClimGrid-Daily · NOAA NCEI nClimGrid-Daily v1.0.0 county averages (prcp/tmax/tmin, scaled), hot_days; 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 share Hispanic or Latino, any race

Share Hispanic or Latino, any raceDays of 90°F or hotter
Highest
Starr County, TX97.3%196
Webb County, TX95.1%174
Maverick County, TX94.9%163
Zapata County, TX93.9%192
Zavala County, TX92.6%158
Lowest
Wirt County, WV0%2
Norton city, VA0%0
Highland County, VA0%0
Loving County, TX0%142
Sully County, SD0%25

By days of 90°F or hotter

Share Hispanic or Latino, any raceDays of 90°F or hotter
Highest
Starr County, TX97.3%196
Zapata County, TX93.9%192
Hidalgo County, TX91.9%189
Brooks County, TX90%187
Jim Hogg County, TX78.3%186
Lowest
Teller County, CO7.39%0
Summit County, CO16.9%0
Saguache County, CO36.9%0
Routt County, CO8.72%0
Rio Grande County, CO40.6%0
States

By share Hispanic or Latino, any race

Share Hispanic or Latino, any raceDays of 90°F or hotter
Highest
New Mexico48.2%60.9
California39.8%52.9
Texas39.5%118
Arizona31%90.2
Nevada29.2%30.2
Lowest
West Virginia2.02%3.56
Maine2.08%1.16
Vermont2.49%0.566
Mississippi3.6%89
Montana4.39%11.6

By days of 90°F or hotter

Share Hispanic or Latino, any raceDays of 90°F or hotter
Highest
Texas39.5%118
Louisiana6.95%114
Florida26.7%105
Arizona31%90.2
Mississippi3.6%89
Lowest
Rhode Island17.1%0.396
Vermont2.49%0.566
New York19.6%0.947
Maine2.08%1.16
New Hampshire4.52%1.69
Metro areas

By share Hispanic or Latino, any race

Share Hispanic or Latino, any raceDays of 90°F or hotter
Highest
Rio Grande City-Roma, TX97.3%196
Laredo, TX95.1%174
Eagle Pass, TX94.9%163
Zapata, TX93.9%192
McAllen-Edinburg-Mission, TX91.9%189
Lowest
Selma, AL0.906%86
St. Marys, PA0.997%0
Gallipolis, OH1.03%4
Elkins, WV1.08%0
Pikeville, KY1.11%8.67

By days of 90°F or hotter

Share Hispanic or Latino, any raceDays of 90°F or hotter
Highest
Rio Grande City-Roma, TX97.3%196
Zapata, TX93.9%192
McAllen-Edinburg-Mission, TX91.9%189
Alice, TX81%178
Yuma, AZ64.4%176
Lowest
Youngstown-Warren, OH4.47%0
Wooster, OH2.38%0
Wheeling, WV-OH1.33%0
Waynesville, NC4.73%0
Watertown-Fort Drum, NY7.3%0
Cities and towns — Days of 90°F or hotter is not published for cities and towns

By share Hispanic or Latino, any race

Share Hispanic or Latino, any raceDays of 90°F or hotter
Highest
Elsa city, TX100%—
Salida del Sol Estates CDP, TX100%—
Cayey zona urbana, PR100%—
Coco comunidad, PR100%—
Juncos zona urbana, PR100%—
Lowest
Monroeville city, AL0%—
Holtville CDP, AL0%—
Halls CDP, TN0%—
Treasure Lake CDP, PA0%—
Wellston city, OH0%—
ZIP codes — Days of 90°F or hotter is not published for ZIP codes

By share Hispanic or Latino, any race

Share Hispanic or Latino, any raceDays of 90°F or hotter
Highest
ZIP 00723 (Patillas Municipio, PR)100%—
ZIP 00731 (Ponce Municipio, PR)100%—
ZIP 00782 (Comerío Municipio, PR)100%—
ZIP 00952 (Sabana Seca comunidad, PR)100%—
ZIP 00719 (Naranjito Municipio, PR)100%—
Lowest
ZIP 04457 (Penobscot County, ME)0%—
ZIP 04364 (Kennebec County, ME)0%—
ZIP 04002 (York County, ME)0%—
ZIP 03235 (Franklin city, NH)0%—
ZIP 03070 (Hillsborough County, NH)0%—

Counties furthest from the pattern

Compared with the straight line that best fits all 2,855 counties: the five with far more days of 90°F or hotter than their share Hispanic or Latino, any race would suggest, and the five with far less.

Share Hispanic or Latino, any raceDays of 90°F or hotter
Above the line
Loving County, TX0%142
La Paz County, AZ25.5%165
Maricopa County, AZ30.9%168
West Baton Rouge Parish, LA4.46%130
East Baton Rouge Parish, LA6.59%131
Below the line
Mora County, NM76.1%10
Rio Arriba County, NM67.3%10
Costilla County, CO55.6%0
Tulare County, CA66%20
Taos County, NM50.8%0

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+0.4802,843 counties reporting both
After adjusting for density, income and education+0.507the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.489size taken out as well as density
Also comparing only within each state+0.286each county is compared only with others in its own state, so this is no longer a comparison between states
Also holding winter sunshine equal+0.179compares 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+0.551the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 281 equally weighted counties
Middle value inside single states+0.122the link worked out inside each of 39 states with at least 20 counties reporting
Using ranks, after adjusting+0.464uses 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 = 2.6e-185. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 5.3e-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 4.0e-184.

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 +0.85 (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 Hispanic or Latino, any race rose most, did days of 90°F or hottermove 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 pandemic2,703-0.07-0.000.999
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years2,722-0.04-0.000.927

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 Share Hispanic or Latino, any race and Days of 90°F or hotter