placestats

Arthritis and Economy score

Across 2,934 counties, Arthritis and Economy score have a link of -0.65, on a scale from −1 (opposite) to +1 (in step). But compare places with the same population density, income and education, and a very weak link of -0.15 remains. Most of the first figure came from both measures following how urban, rich and educated a place is, not from a link with each other.

Mostly gone 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

Arthritis

The estimated percentage of adults who have been told they have arthritis. 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 ARTHRITIS, age-adjusted

Economy score

Four income measures from four agencies: income per person, middle household income (an estimate from a statistical model), personal income per person, and average adjusted gross income on tax returns. Read it as four ways of measuring income, not as a broad economic summary. It moves very closely with middle household income (a link of 0.91 on a scale where 1 is perfect), and the site already adjusts for that. So a link with this score and a link with income are close to the same question.

· derived from 4 measures (ACS, BEA, IRS, SAIPE)

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 arthritis

ArthritisEconomy score
Highest
Calhoun County, WV35.1%-0.0914
McDowell County, WV35.1%-1.02
Mingo County, WV35%-0.417
Mercer County, WV34.6%0.14
Logan County, WV34.5%0.238
Lowest
Santa Clara County, CA15.5%4.16
San Francisco County, CA16.1%4.1
Orange County, CA16.8%2.59
Bergen County, NJ16.8%3.05
Hudson County, NJ16.9%2.17

By economy score

Metro areas

By arthritis

ArthritisEconomy score
Highest
Beckley, WV32.6%-0.717
Elkins, WV32.4%-0.936
Parkersburg-Vienna, WV32%-0.159
Bluefield, WV-VA32%-0.853
Fairmont, WV32%-0.356
Lowest
San Jose-Sunnyvale-Santa Clara, CA15.6%4.15
San Francisco-Oakland-Fremont, CA17.5%3.62
Los Angeles-Long Beach-Anaheim, CA17.9%1.51
Trenton-Princeton, NJ18%1.84
Oxnard-Thousand Oaks-Ventura, CA18%1.5

By economy score

ArthritisEconomy score
Highest
Jackson, WY-ID20.4%6.15
Heber, UT20.9%4.36
San Jose-Sunnyvale-Santa Clara, CA15.6%4.15
Naples-Marco Island, FL20.5%3.86
Bridgeport-Stamford-Danbury, CT19.5%3.85
Lowest
Rio Grande City-Roma, TX23%-2.7
Zapata, TX22.5%-2.58
Gallup, NM25.8%-2.29
Deming, NM23.4%-2.08
Raymondville, TX22.2%-2.08
Cities and towns — Economy score is not published for cities and towns

By arthritis

ArthritisEconomy score
Highest
Bluefield city, WV35.1%—
Huntington city, WV34.9%—
Princeton city, WV34.9%—
Parkersburg city, WV34.4%—
Beckley city, WV33.4%—
Lowest
Cupertino city, CA13.4%—
Milpitas city, CA13.7%—
San Marino city, CA13.9%—
Saratoga city, CA14.2%—
Walnut city, CA14.3%—

Counties furthest from the pattern

Compared with the straight line that best fits all 2,955 counties: the five with far more economy score than their arthritis would suggest, and the five with far less.

ArthritisEconomy score
Above the line
Teton County, WY19.5%5.78
Summit County, UT21%4.73
Pitkin County, CO20.4%4.81
Williamson County, TN23.5%3.74
Marin County, CA18.7%4.44
Below the line
Starr County, TX23%-1.04
Zapata County, TX22.5%-0.909
Cameron County, TX19%-0.23
Crowley County, CO23.1%-0.983
Brooks County, TX21.5%-0.533

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-0.6482,934 counties reporting both
After adjusting for density, income and education-0.153the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.155size taken out as well as density
Also comparing only within each state-0.167each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.137the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 264 equally weighted counties
Middle value inside single states-0.774the link worked out inside each of 38 states with at least 20 counties reporting
Using ranks, after adjusting-0.139uses 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 = 7.3e-17. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.004. 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 2.2e-16.

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 +0.25 (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 Arthritis and Economy score