The AFI rates the relative fitness of America's 50 largest metros based on data from the U.S. Census, U.S. Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System (BRFSS), and The Trust for Public Land City Park Facts, among other sources. The AFI takes both personal health indicators (statistics on specific diseases, obesity, smoking levels, etc.) and community and environmental factors (health care access, community resources that promote fitness, etc.) into account.



The above map shows us which cities are fit and which are not so fit, but it doesn't tell us why that might be or what it reflects. So, with the help of my Martin Prosperity Institute colleague Charlotta Mellander, I took a quick look at the demographic, economic, and geographic factors that might be associated with better or worse fitness across metros. Correlation is not causation, of course--what we are looking at here are simply associations. But they are thought-provoking enough to suggest other avenues of research.

Many people think fitness is better in warmer locations. Not so much. Each of the top five metros is pretty chilly, and the top ranked Twin Cities are among the coldest locations in the United States--certainly compared to warm and sunny LA, which languishes in 41st place. Our analysis found no correlation between fitness and January temp and a negative correlation between fitness and July temperature (-.49).

Perhaps more to the point, fitter cities are also more affluent. There are considerable correlations between fitness and several measures of economic development including average wages (.56) average income (.47) and economic output (gross metro product) per capita. The scatter-graph above charts the trend for income.





Fitter cities are better educated. There is a close correlation between fitness and the share of adults with a college degree (.64), as the above chart shows.

Fitter cities are also more innovative. There are significant correlations between fitness and the concentration of high-tech industry (.42) and the level of innovation (measured as patents per capita, .48).





Fitness is associated with the kinds of work we do. Metros with a high share of professional, technical and knowledge jobs are fitter (with a correlation of .58), while those with working class jobs are less fit (with a negative correlation of -.56)--see scatters above and below. A paradox, perhaps, because working class people put more physical effort into their jobs, but sedentary professionals are much more likely to pursue vigorous exercise in their leisure time, while blue collar workers dedicate their downtime to, well, leisure. Also, fitness shows no correlation to hours worked. It does however show a modest correlation to the unemployment rate (-.29).



Which brings me to the last chart (see above), which compares metros' rankings on the Fitness Index to their reported levels of well-being. Perhaps not surprising, the correlation (.71) is the highest of any variable in our analysis. To the chronically under-employed, their richer, thinner, happier neighbors must seem unbearably smug.