Another pioneer in the use of pseudoscientific databases in the cause of urban planning is Robert Putnam, the author of the 1995 bestseller Bowling Alone. Putnam heard that American participation in bowling leagues had declined even though bowling itself remained popular. It never occurred to him that people might be bowling with families and friends; he presumed that this meant people were bowling by themselves. He declared this was proof that Americans’ sense of community had declined. When people questioned the validity of this proof, Putnam gathered scores of data sets, none of which directly measured community, but which together proved, he claimed, that America’s sense of community was declining. For example, the data he found measured such things as “dwindling trust between adults and teenagers” and “the changing observance of stop signs.”5
Only two of Putnam’s data sets compared suburbs with cities. One measured the percentage of people who served as officers or committee members of a local group. The other measured the percentage of people who had attended a public meeting on town or school affairs. Both data sets showed higher participation in the suburbs than in the central cities.6 If these things measure a sense of community, Putnam’s conclusion should have been that people have a higher sense of community in low-density suburbs than in high-density cities. Instead, Putnam made the amazing claim that mobility and sprawl somehow “undermines civic engagement and community-based social capital.”7
Furthermore, Putnam somehow calculated that “suburbanization, commuting, and sprawl … account for perhaps 10 percent” of the decline in community participation.8 To “fix” this, he recommended New Urbanist planning: “It is surely plausible that design innovations like mixed-use zoning, pedestrian-friendly street grids, and more space for public use should enhance social capital.”9 In other words, Putnam proposed to apply to the suburbs the same features that are found in the cities that (according to his measures) have a lower sense of community than the suburbs.
Contrary to Putnam’s presumption, sociologists have worried more that dense cities, not low-density development, reduced people’s sense of community.10 A new study from University of California economist Jan Brueckner confirms Putnam’s data (but not his conclusions) by finding that suburban residents have more friends, more contact with neighbors, and greater involvement in community groups than residence of dense urban neighborhoods.11
New Urbanists, however, are fond of claiming that their higher-density housing projects will provide a stronger sense of community than low-density suburbs. But they have a very restricted sense of community. To them, community is solely geographically based. Yet as University of California-Berkeley planning professor Melvin Webber pointed out more than 40 years ago, thanks to automobiles, telephones, and (more recently) the Internet, Americans no longer rely on their immediate neighbors for a sense of community.12 Instead, they form communities with people all over the country and indeed all over the world.
I myself belong to communities of road cyclists; people who love trains and restore historic rail equipment; and owners of Belgian Tervuren dogs, among others. Very few members of any of these communities live in my town, yet I feel a strong sense of community with them all. If people were restricted to forming communities only with their geographic neighbors, their lives would be far shallower and narrower. Since they are no longer so restricted, they do not feel a need to form a strong sense of community with neighbors with whom they share few interests. Planners who mourn the loss of geographic community ignore the much larger gains in other forms of community.
More recent studies have claimed to prove that low-density suburbs cause obesity and other health problems. The databases used to support these allegations often do not actually compare suburbs with cities. One obesity study compares low-density counties with higher-density counties. A health study compares low-density urban areas with higher-density urban areas. Neither finds much statistical significance in the data, but that does not stop the pseudoscientists from making their claims.
The obesity study is based on the ominously named Behavioral Risk Factor Surveillance System, a telephone survey of 200,000 Americans conducted each year by state health departments. Among other things, surveyors ask people how much they exercise each day as well as their height and weight, which can be used to estimate the amount they are overweight or obese. It is likely that people responding to a telephone survey overestimate their height and underestimate their weight, but surveyors merely assumed that everyone lies equally. Because the database was so large, the Centers for Disease Control, which coordinated the survey, did not feel the need to do any statistical analyses testing the validity of the data.
The database indicates a very strong correlation between income and obesity. According to the data, among people with household incomes of less than $10,000, 27.5 percent are obese. As household incomes rise, this percentage steadily falls to as low as 15.1 percent in the $75,000 plus category. There is also a strong correlation between education and obesity: 28.3 percent of people with a grade-school education are obese, steadily decreasing with more education to 15.4 percent among college graduates.13
The surveillance system does not ask people whether they live in a city or suburb. So pseudoscientists at Smart Growth America and the Surface Transportation Policy Project compared obesity rates in counties with various amounts of “sprawl.”14 They adjusted for age, race, and education, but not for income, even though incomes vary widely by county and the data indicate that income has a huge effect on obesity. Their results show that sprawl is far less important to physical fitness than income or education.
For example, their results indicate that about 2 percent more people in Atlanta are obese than in San Francisco, which is about the same as the difference between people who ended their education in high school and people who went to, but did not finish, college. Or to use an example raised by planning critic Wendell Cox, Cook County, Illinois, is 70 times denser than Grundy County, Illinois, and the obesity formula indicates that people in Cook County exercise an average of 40 seconds per day longer and weigh 1 pound less than people in Grundy County.15 Despite these tiny differences, which could easily be accounted for by socioeconomic variations, flaws in the survey data, or other factors, the Smart Growth America study blames obesity on the suburbs.
To gain scientific credibility, the smart-growth pseudoscientists even submitted their report to a peer-reviewed journal. To get their report into the journal, however, they had to seriously weaken the claims. “Sprawling development has had a hand in the country’s obesity crisis” says the press release issued by Smart Growth America. This demonstrates “the urgent need to invest in making America’s neighborhoods appealing and safe places to walk and bicycle,” which to Smart Growth America means rebuilding the suburbs at higher densities.16
In contrast, the journal article says sprawl “had small but significant associations with minutes walked [and] obesity.”17 In popular use, significant means “having a major effect,” but in statistics, significant can refer to very tiny effects as long as they are “not mere chance.” So the article finds only small, nonrandom “associations” between sprawl and obesity. Unlike the press release, the article carefully does not assert that sprawl “had a hand” in causing obesity, merely that they are “associated,” which could mean that some other factor caused the obesity that was also associated with sprawl.
One such factor was revealed by a Canadian study that found “no evidence that urban sprawl causes obesity.” Instead, the study revealed, “Individuals who are more likely to be obese choose to live in more sprawling neighborhoods.” It appears that obesity contributes to sprawl, not the other way around. As a result, the researchers concluded, any effort to