Tag Archives: counties

Can you name “America’s 50 Healthiest Counties for Kids” when you only account for 38% of US counties?

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US News & World Report recently released a list of “America’s 50 Healthiest Counties for Kids.” However, there is a problem with the rankings: more than half of American counties aren’t included in the data.

About 1,200 of the nation’s 3,143 counties (a total that takes in county equivalents such as Louisiana’s parishes) were evaluated for the rankings. Many states don’t collect county-level information on residents’ health, whereas populous states, such as California, Florida and New York, tend to gather and report more data. In some counties, the population is so small that the numbers are unreliable, or the few events fall below state or federal reporting thresholds. And because states don’t collect county-level information on childhood smoking and obesity, the rankings incorporated percentages for adults. Catlin says this is justified because more adult smokers mean more children are exposed to secondhand smoke, a demonstrated health risk. Studies have also shown a moderately strong correlation between adult and childhood obesity, she says.

The experts who study community health yearn for more and better data. “We don’t have county-level data on kids with diabetes, controlled or uncontrolled, or on childhood obesity rates,” says Ali Mokdad of the Institute for Health Metrics and Evaluation at the University of Washington. “Almost every kid in this country goes to school. We could measure height and weight, but nobody’s connecting the dots.”

This won’t stop counties high on the list from touting their position. See this Daily Herald article about DuPage County coming in at #20. But, there should be some disclaimer or something on this list if a majority of US counties aren’t even considered. Or, perhaps such a list shouldn’t be too together at all.

American median income, poverty rates, and inequality by county

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Check out these maps of American inequality and income using the latest American Community Survey data.

The below five maps were created by Calvin Metcalf, Kyle Box and Laura Evans using the latest five-year American Community Survey estimates provided by the Census Bureau for last weekend’s National Day of Civic Hacking (we’re geeking out on these projects this week).

Working from Boston, the group has so far mapped nearly a dozen demographic points from the data, including a few they calculated on their own (be sure to check out the very bizarre map of America’s gender ratios by county). These five maps, however, jumped out at us for how they each illustrate deep and lingering differences between the American North and South, as seen through several different data points. Of course, the patterns aren’t perfect, and exceptions abound; major cities in the North turn out to be hotspots of inequality on par with much of the Deep South…

Median income (in annual dollars)

Population living below the poverty line (by percent)

Income inequality (as measured by the Gini coefficient, the closer to zero the better)

There do seem to be seem some regional differences. But, these three maps raise other questions:

1. This may be a good place for population weighted maps. While counties are one unit of geographic measure, they can obscure finer-grained data. For example, the map of median income shows higher incomes in urban areas but this glosses over poor urban and suburban neighborhoods. Plus, many of the counties in the South, Great Plains, and Mountain West have relatively fewer people.

2. The income map shows one story – generally higher incomes in urban areas – and the inequality, measured by the Gini coefficient, shows that these same urban areas have high levels of inequality. This may be an issue with the county measure but it also highlights that while cities are economic engines, they are also homes to pronounced inequality.

Mapping NFL fandom by county with Facebook likes

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Facebook has put their massive data trove to use and examined the geographies of NFL fandom. Here is what they came up with:

The National Football League is one of the most popular sports in America with some incredibly devoted fans. At Facebook we have about 35 million account holders in the United States who have Liked a page for one of the 32 teams in the league, representing one of the most comprehensive samples of sports fanship ever collected. Put another way, more than 1 in 10 Americans have declared their support for an NFL team on Facebook…

While winning seems to matter, NFL teams have local followings that are probably heavily influenced by family ties and/or where a person grew up,  so we were obviously curious to see where the fans for various teams live now. By considering the physical locations of NFL fans, we can construct a map of the top team for each county in the US. It tells an interesting story about the ways that football rivalries and allegiances alternately divide and unite the country, and sometimes even individual states.

In some cases, whole states and even entire regions of the country uniformly support a single team.  For instance the Vikings are easily the only game in town in Minnesota, while New England appears to be comprised of entirely Patriots fans except for a small portion of Connecticut.

There are some states which are divided into regions by teams.  Florida has three teams–the Tampa Bay Bucs, Miami Dolphins, and the Jacksonville Jaguars–and Facebook users there seems fractured in their support, with some counties even defecting to teams from the North. Ohio is another interesting story, with the Cleveland Browns in the North, Cincinatti Bengals in the South, and Pittsburgh Steelers fans occupying the middle of the state.

Some teams, like the Steelers, Cowboys, and Packers, seem to transcend geography, with pockets of fans all over the country. On the other end of the spectrum, the Jets have to share New York with the Giants and are only the most popular team for a single stronghold county in Long Island.

Five quick thoughts:

1. There are few other organizations that could put together such a map without undertaking a major survey (since this is measured at the county level).

2. The best part for Facebook: users voluntarily provided this data.

3. Could Facebook end up being the most important future source for telling us about American society? There are still difficulties: users have to opt in (in this particular case, they had to “like” a NFL team), not everyone is involved (though it seems like pretty close), and not all users are putting everything in their profiles.

4. Is there a way to weight this map with population density? For example, the Cowboys may have a really broad geographic reach but many of those counties have fewer people. In contrast, teams like the Jets or Eagles have smaller reaches yet more people live in those areas.

5. Is there a way to show the percentage of county respondents who liked the dominant team? I imagine there are plenty of counties where one team does not have a strong majority, let alone even much of a plurality. For example, Jets fans barely show up on the map because they are only the top team in one county. Yet, there are plenty of Jets fans.

Trying to explain American differences in 12 easy categories

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I recently flipped through Our Patchwork Nation, a recent book that tries to explain differences in America by splitting counties into twelve types: “boom towns, evangelical epicenters, military bastions, service worker centers, campus and careers, immigration nation, minority central, tractor community, Mormon outposts, emptying nests, industrial metropolises and monied burbs.” A review in the Washington Post offers a quick overview of this genre of book:

And every few years there’s another book promising to chart the country’s divisions by splitting it into categories more telling than the 50 states. Former Washington Post writer Joel Garreau offered his “Nine Nations of North America” in 1981; two decades later came Richard Florida with “The Rise of the Creative Class,” followed by Bill Bishop’s “The Big Sort,” which sought to explain why so many of us are clustering in enclaves of the like-minded.

The latest aspiring taxonomists are Dante Chinni, a journalist, and James Gimpel, a University of Maryland government professor, who use socioeconomic data to break the country’s 3,141 counties into 12 categories.

This sort of analysis is now fairly common: there is a lot of publicly available data from the Census Bureau and many more people are now interested in looking at the United States as a whole.

I have two concerns about this data. My main complaint about this effort is how the types are developed at the county level. This may be a good level for obtaining data (easy to do from the Census Bureau) but it is debatable about whether this is a practical level for the lives of Americans. When asked where they live, most people would name a community/city first and then next a state or region before getting to a county. County rules and ordinances have limited effect in many places as municipal regulations take precedence.

A second concern is that this type of sorting or clustering tells us where places are now but doesn’t say as much about how they arrived at this point or how they might change in the future. This is a cross-sectional analysis: it tells us what American counties look like right now. This may be useful for looking at recent and upcoming trends but most of these places have deeper histories and characters than just a moniker like “monied burbs.” This would explain some of the Post’s confusion about lumping together “emptying nests” communities in the Midwest and Florida.

Mapping poverty rates by county across the US

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A story about the recently released figures regarding poverty in the United States includes a nice map from Mint.com that show poverty rates by county. The map shows higher rates of poverty in Louisiana, Mississippi, some parts of Texas and New Mexico, Appalachia, some of the middle parts of the southern Atlantic states, and some pockets in the upper Great Plains.

This map shows the proportion of residents who are living in poverty; while the national rate is now about 1 in 7 Americans is under the poverty line, 25% or more of residents in these locations live in poverty. Many of these counties are more rural counties. The map would look different if it were mapping the absolute number of people living in poverty – then you might see a shift toward some larger metropolitan areas.

While areas of concentrated poverty in the city get a lot of attention, what is going on in some of these more rural areas? How did poverty rates shift over the last couple of decades in these locations?