placestats

Share of days with unhealthy air and Presidential votes cast, 2012

A county is not a voter. Read either way, this says one thing and no more. Counties that voted more Republican also tend to differ on the other measure, and counties that voted less Republican tend to differ the other way. It does not follow that the people who voted that way are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. It is the most common misuse of exactly this data. How a county votes also goes so closely with its density, age and education that much of what looks political here is really those. That is what the adjusted figures are for. The vote shares run from 2000 to 2024, and the links here are measured in 2023.

Where Share of days with unhealthy air is higher, Presidential votes cast, 2012 tends to be higher. The link is moderate: +0.45 across 795 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.

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 of days with unhealthy air

The percentage of days when the Air Quality Index was over 100, which is unhealthy for sensitive groups or worse. The index runs from 0 to 500 and is set by the worst pollutant that day. Smoke from wildfires and summer ozone cause most of these days. It counts only the days the monitors gave a reading, and a year counts only if there were at least 274 of them. Only about 800 counties have a monitor, mostly the larger ones.

EPA Air Quality System · EPA AQS annual_aqi_by_county, Unhealthy for Sensitive Groups + Unhealthy + Very Unhealthy + Hazardous Days, divided by Days with AQI

Presidential votes cast, 2012

The total number of presidential votes cast in 2012.

MIT Election Data and Science Lab · MIT county presidential returns

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 of days with unhealthy air

Share of days with unhealthy airPresidential votes cast, 2012, per 1,000 residents
Highest
San Bernardino County, CA32.3265.80
Riverside County, CA31.2270.18
Los Angeles County, CA23.8323.01
Tulare County, CA22.5212.50
Kern County, CA19.2243.26
Lowest
Routt County, CO0532.89
Montezuma County, CO0470.08
Mesa County, CO0463.70
Gunnison County, CO0505.13
Santa Barbara County, CA0367.86

By presidential votes cast, 2012

Share of days with unhealthy airPresidential votes cast, 2012, per 1,000 residents
Highest
Charles City County, VA0.822632.96
St. James Parish, LA0.57626.10
Lake County, MN0.548625.06
Northampton County, NC0.274624.91
Clear Creek County, CO2.23613.70
Lowest
Hidalgo County, TX0157.97
Cameron County, TX1.64181.70
Maverick County, TX0.303182.85
Webb County, TX1.37183.43
El Paso County, TX5.21199.02
Metro areas — Share of days with unhealthy air is not published for metro areas

By presidential votes cast, 2012

Share of days with unhealthy airPresidential votes cast, 2012, per 1,000 residents
Highest
Port Townsend, WA—588.15
Fort Madison, IA—580.72
Selma, AL—579.37
Roanoke Rapids, NC—575.43
Barnstable Town, MA—574.45
Lowest
McAllen-Edinburg-Mission, TX—154.89
Brownsville-Harlingen, TX—180.20
Rio Grande City-Roma, TX—180.23
Laredo, TX—182.46
Eagle Pass, TX—182.87

Counties furthest from the pattern

Compared with the straight line that best fits all 796 counties: the five with far more presidential votes cast, 2012 than their share of days with unhealthy air would suggest, and the five with far less.

Share of days with unhealthy airPresidential votes cast, 2012, per 1,000 residents
Above the line
Charles City County, VA0.822632.96
St. James Parish, LA0.57626.10
Lake County, MN0.548625.06
Northampton County, NC0.274624.91
Ozaukee County, WI4.96604.44
Below the line
Hidalgo County, TX0157.97
Maverick County, TX0.303182.85
Cameron County, TX1.64181.70
Webb County, TX1.37183.43
Ector County, TX0199.21

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+0.449795 counties reporting both
After adjusting for density, income and education+0.447the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.352size taken out as well as density
Also comparing only within each state+0.429each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.728the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 164 equally weighted counties
Middle value inside single states+0.582the link worked out inside each of 14 states with at least 20 counties reporting
Using ranks, after adjusting+0.082uses 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-40. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 1.4e-12. The site tested 24,090 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 1.6e-39.

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 +0.08 (p = 0.001). Once the adjustment is made, little map pattern is left.

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 Share of days with unhealthy air and Presidential votes cast, 2012