Richard Florida is a co-founder and editor at large of CityLab and a senior editor at The Atlantic. He is a university professor in the University of Toronto’s School of Cities and Rotman School of Management, and a distinguished fellow at New York University’s Schack Institute of Real Estate and visiting fellow at Florida International University.
Happiness, form of commute and money all play a role
Yesterday, I mapped the metro areas across the United States where smoking and obesity are the most and least prevalent. A great many studies have examined the health consequences of obesity and smoking and the characteristics of individuals who are most susceptible to them, but I wanted to better understand them geographically.
With the help of my Martin Prosperity Institute colleague Charlotta Mellander, I looked into the factors that might impact regional variations in smoking and obesity, such as income, education, and even the ways people commute to work. I should emphasize at the outset that our analysis only points to associations between variables. We do not make any claims about causation as other factors that we haven’t looked at might play an equal or even larger role. Nonetheless, the associations are intriguing and worth spelling out in some detail.
First of all, the Metro Health Index is closely associated with income. Higher income metros have substantially lower levels of smoking and obesity, while poorer metros are plagued with considerably higher levels of both. The correlation between income and the Metro Health Index is considerable (.5) and as the scatter-graph above shows, the fitted line slopes steadily upward.
Human capital factors in as well. Health increases significantly alongside the percentage of adults in a metro who are college graduates. The correlation between the Metro Health Index and human capital is even higher than that for income (.56).
The kinds of work people do also plays a role in smoking and obesity levels. Metros with higher percentages of creative class workers do consistently better on the Metro Health Index (the correlation is .38), while metros with higher shares of blue-collar workers do significantly worse (a correlation of -.43). Metros with greater shares of high-tech industry also have higher scores on the Metro Health Index (with a correlation of.46).
The way people get to work factors in as well. Metro health is closely associated with commuting patterns. Metros where greater shares of people walk and bike to work do better on the Metro Health Index (.62). Conversely, the share of people who drive to work alone is negatively associated with the Metro Health Index (-.47).
Diversity, race and ethnicity factor in, but not entirely in the ways that you might expect. Higher levels of diversity are generally associated with healthier metros. The Metro Health Index is positively associated with the share of Hispanics (.47), gays and lesbians (.57), and even more so with the share of immigrants (.66). The share of African-Americans, however, is negatively associated with the Metro Health Index (-.36).
Perhaps not surprisingly, higher scores on Metro Health Index are associated with higher levels of metropolitan happiness and subjective well-being (with a considerable correlation of .62).
These basic findings are backed up in a more detailed statistical study Mellander and I recently completed, "The Economic Geography of Smoking and Obesity." Using regression analysis to more precisely isolate the effect of various geographic factors and variables, we find that smoking is most closely associated with human capital and the creative class. Obesity, on the other hand, is most closely associated with the working class, being significantly higher in metros with more working class jobs. Commuting patterns also play a key role. Higher levels of smoking and obesity are consistently associated with higher shares of people who drive to work alone.
When rates of smoking and obesity are used as a proxy for health and wellness, they reflect a socioeconomic problem as well as a medical one. The geography of health in America varies considerably and consistently with income, human capital, class, race and diversity. Tragically, the very Americans who are paying the greatest cost for these afflictions – in health care expenses, lost wages, and general suffering – are the ones who can afford it the least.
As America’s class divide worsens, so too do its health outcomes. We can tell people to smoke less, eat better and exercise more, but the United States will not solve its health problems – or reduce its skyrocketing health care costs – until it comes to grips with the worsening class divides that plague it.