Earlier this week, the American College of Sports Medicine released its new version of the American Fitness Index, which tracks the health and fitness level of America’s 50-largest metropolitan regions. The index is defined as a “composite of preventive health behaviors, levels of chronic disease conditions, health care access, and community resources and policies that support physical activity.” The table below shows the fitness levels for these 50 metros.
Source: American Fitness Index
Greater Washington, D.C. tops the list (for the third consecutive year) followed by Boston, Minneapolis-St.Paul, Seattle, Portland, Denver, Sacramento, San Francisco, Hartford, and Austin. At the opposite side of the spectrum, the least-fit metros were Oklahoma City, Birmingham, Memphis, Detroit, Louisville, Las Vegas, Indianapolis, San Antonio, Houston, and New Orleans. Warm metros like L.A. and Miami do worse than might be expected, while cold metros like Pittsburgh, Baltimore, and Cincinnati do better.
With the help of my Martin Prosperity Institute colleague Charlotta Mellander, we decided to take a look at the relationships between the American Fitness Index and a variety of regional characteristics from temperature levels to income and output, educated people and knowledge-driven economies. As usual, I point out in advance that our analysis points to association between variables only: It does not imply causation, and other factors may complicate the picture.
Climate and Temperature: Most people would think fitness levels are higher in warm, sunnier places, and lower in cold places. But that’s not what we find, at all, when we examine the association between metro fitness and various measures of climate and temperature.
First and foremost, we find no correlation between fitness and cold locations, measured as mean January temperature. We also find no correlation between fitness and the January to July temperature difference. We do, however, find a significant correlation between fitness and the hottest places, measured as mean July temperature: But it is negative (-.52), meaning places that get really hot in July have lower levels of fitness on average.
Income, Wages, and Output: Now, let’s look at the relationship between fitness levels and economic development. It stands to reason that more affluent regions where residents have more resources to devote to health and fitness would score better. And, not surprisingly, that is what we find. We find a significant but moderate relationship between metro-level fitness and economic output per capita (.35), and between it and income (.41), and a somewhat higher association between fitness and metropolitan wages (.54).
The scatter-graph below charts the relationship between fitness and wages. The relationships are reasonably linear, and the line slopes steeply upward. Greater Washington, D.C. performs even better than its wage level would predict. The same is true for Minneapolis and Seattle, Portland and Denver, and Cincinnati and Pittsburgh. I personally found Pittsburgh a fantastic place for road-cycling during my time there. On the other hand, San Francisco, San Jose, and L.A., as well as Detroit, Oklahoma City, and Memphis, are significantly below it, performing worse than their wage levels might predict.
Post-Industrial Economic Structures: Our ongoing research suggests that post-industrial economic structures play an additional role in health and well-being, over and above the effects of economic resources. This entails the shift from physically oriented work to knowledge, professional, and creative occupations and industries – and from lower-skilled to more highly skilled and educated workforces.
Human Capital: Metros with more highly educated populations have higher levels of fitness, again not surprisingly. The correlation between fitness and human capital (measured as the percentage of adults with a bachelor’s degree or higher, .66) is the strongest of any of the variables we looked at.
The scatter-graph above shows a fairly linear relationship, with a steep upward slope. Greater Washington, D.C., Minneapolis, Seattle, Portland, Denver, and Cincinnati are significantly above the line, with higher levels of fitness relative to their human capital levels, while San Jose, Raleigh, Charlotte, L.A., Indianapolis, and Oklahoma City are considerably below it with fitness levels that are worse than what their human capital levels would predict.
Creative Class: Metro-level fitness is also associated with the creative class – that is the percentage of residents in science and technology; arts, design, media, and entertainment; and management and professional occupations. The correlation between the two is .59 – the second-strongest among the variables in our analysis.
The scatter-graph above shows a fairly linear relationship. Washington, D.C. rests close to the fitted line – its fitness levels are more or less in line with the proportion of its workforce in the creative class. San Francisco is now above the line, along with Boston, Minneapolis, Portland, Seattle, Denver, and, once again, Cincinnati. On the other hand, L.A. again is well below the line, along with Charlotte, Indianapolis, Houston, Detroit, and Oklahoma City, with fitness levels that are worse than their creative class levels would predict.
Working Class: The correlation between metro fitness and the percentage of the workforce in blue-collar, working-class occupations is also relatively strong. But it is negative (-.58). The fitted line slopes steeply downward. Metros with large blue-collar workforces have significantly lower levels of fitness.
America’s metropolitan areas vary considerably in their fitness levels. That variation, like many other characteristics of cities and metropolitan areas, is anything but random: Instead, it follows systematic and predictable patterns. Fitter metros are relatively more affluent, more highly skilled, and have significantly greater concentrations of the creative class. Generally speaking then, fitness appears to go hand in hand with the transition to more highly skilled, knowledge-intensive, and idea-driven post-industrial economic structures. It’s not just skill or human capital levels that are increasingly spiky and uneven across the United States but fitness levels as well.
If we’re really serious about improving the health and fitness levels of people in many of our populous cities and metros, we’ll have to do more than invoke them to smoke less, eat better, and exercise more. We’ll also have to facilitate a deeper and more thorough ongoing economic transformation - developing greater skills, improving human capital levels, and enhancing the transition from blue-collar to more knowledge-driven economic structures.