placestats

Mammography in the past two years and Mainline Protestant adherents

A county is not a congregation. Counties where more people are counted as adherents (members of a religious group) also tend to differ on the other measure, and that is all. It does not follow that the adherents 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 as easy to fall into here as with the voting pairs. Two things about the counting matter too. Adherents are counted where their congregation meets, not where they live, so thirty very small counties exceed 100%. And a denomination that did not report is missing, not zero. That undercounts membership most where churches are least formally organised.

Where Mammography in the past two years is higher, Mainline Protestant adherents tends to be higher. The link is weak: +0.34 across 3,121 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 40 states, the middle value of the link is +0.06.

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

Mammography in the past two years

The estimated percentage of adults who women aged 50 to 74 had a mammogram in the past two years. 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 MAMMOUSE, age-adjusted

Mainline Protestant adherents

Members of mainline Protestant churches, such as United Methodist, Presbyterian Church (USA), Episcopal and Evangelical Lutheran, as a share of the population.

· Religion Census MPRTRATE (2010, 2020)

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 mammography in the past two years

Mammography in the past two yearsMainline Protestant adherents
Highest
Plymouth County, MA86.6%3.27
Norfolk County, MA86.4%3.89
Anne Arundel County, MD86%6.43
Suffolk County, MA85%2.14
Jefferson County, AL84.2%8.93
Lowest
Kusilvak Census Area, AK48.5%0
Bethel Census Area, AK57.2%0
San Juan County, NM57.6%2.13
Apache County, AZ58%0.67
Oglala Lakota County, SD58.2%8.84

By mainline Protestant adherents

Mammography in the past two yearsMainline Protestant adherents
Highest
Nelson County, ND79.3%69.5
Burke County, ND76.9%66.8
Renville County, ND79.7%65.3
Steele County, ND74.5%59.6
Lac qui Parle County, MN79.7%57
Lowest
Costilla County, CO65.6%0
Alpine County, CA73.3%0
Skagway Municipality, AK66.7%0
Lake and Peninsula Borough, AK62.4%0
Kusilvak Census Area, AK48.5%0
States — Mammography in the past two years is not published for states

By mainline Protestant adherents

Mammography in the past two yearsMainline Protestant adherents
Highest
North Dakota—21
South Dakota—17.9
Iowa—15.7
Minnesota—13.6
West Virginia—12.2
Lowest
Utah—0.48
Nevada—1.05
California—1.4
Arizona—1.61
Oregon—2.15
Metro areas

By mammography in the past two years

Mammography in the past two yearsMainline Protestant adherents
Highest
Worcester, MA84%3.47
Amherst Town-Northampton, MA83.8%4.09
Boston-Cambridge-Newton, MA-NH83.4%3.22
Racine-Mount Pleasant, WI82.8%6.77
Milwaukee-Waukesha, WI82.6%5.38
Lowest
Farmington, NM57.6%2.13
Fairbanks-College, AK58.4%2.98
Prescott Valley-Prescott, AZ61.4%1.41
Lake Havasu City-Kingman, AZ61.5%1.27
Gallup, NM61.9%0.3

By mainline Protestant adherents

Mammography in the past two yearsMainline Protestant adherents
Highest
Albert Lea, MN74.8%38.4
Red Wing, MN76.5%35
Willmar, MN79.6%34.1
Pella, IA76.7%33
Beatrice, NE67.7%32.8
Lowest
Provo-Orem-Lehi, UT69.1%0.0437
Rexburg, ID64.4%0.18
Laredo, TX70.8%0.27
Gallup, NM61.9%0.3
Ogden, UT73.2%0.316
Cities and towns — Mainline Protestant adherents is not published for cities and towns

By mammography in the past two years

Mammography in the past two yearsMainline Protestant adherents
Highest
North Scituate CDP, MA87.6%—
Hingham CDP, MA87.2%—
Hull CDP, MA87%—
Medfield CDP, MA86.8%—
Needham CDP, MA86.7%—
Lowest
Binghamton University CDP, NY32.9%—
Clemson University CDP, SC46.1%—
Shiprock CDP, NM50.8%—
Tuba City CDP, AZ55.3%—
Zuni Pueblo CDP, NM56.6%—

Counties furthest from the pattern

Compared with the straight line that best fits all 3,143 counties: the five with far more mainline Protestant adherents than their mammography in the past two years would suggest, and the five with far less.

Mammography in the past two yearsMainline Protestant adherents
Above the line
Nelson County, ND79.3%69.5
Burke County, ND76.9%66.8
Renville County, ND79.7%65.3
Steele County, ND74.5%59.6
Kittson County, MN76.4%57
Below the line
St. James Parish, LA82.8%0.64
Suffolk County, MA85%2.14
West Baton Rouge Parish, LA81.7%0.83
Plymouth County, MA86.6%3.27
St. John the Baptist Parish, LA80.6%1.04

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+0.2163,121 counties reporting both
After adjusting for density, income and education+0.335the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.297size taken out as well as density
Also comparing only within each state+0.103each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.288the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 287 equally weighted counties
Middle value inside single states+0.057the link worked out inside each of 40 states with at least 20 counties reporting
Using ranks, after adjusting+0.309uses 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 = 9.6e-83. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.000. 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 6.9e-82.

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 +0.51 (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 Mammography in the past two years and Mainline Protestant adherents