Richard Florida
by Richard Florida
Wed Nov 25th 2009 at 9:00am UTC

The Geography of Obesity


Obesity has reached epidemic proportions in America. More than 72 million American adults are obese, according to estimates from the National Center for Health Statistics. But obesity varies greatly by state. The map below, from the Centers from Disease Control (CDC), shows the obesity rate for the 50 states, measured as the share of people with a Body Mass Index (BMI) over 30 which the CDC classifies as “obese.”


A week or so ago, I looked at the relationship between smoking and a variety of economic, social, and health factors. With a helpful analytical hand from Charlotta Mellander, we found that smoking was significantly correlated with obesity as well as being correlated with education levels, class structure, and other factors. So, we decided to take a quick look at the state-level factors that might be associated with obesity. We ran some simple correlations and scatter-plots between state obesity rates and these factors. As usual, we point out that correlation does not imply causality, but simply points to associations between variables. Still, a number of interesting things stand out.

It should come as little surprise that states with higher levels of obesity have significantly higher rates of death from cancer, heart disease, and cerebrovascular diseases like hypertension. There is a significant correlation between obesity and death rates from cancer (.7), heart disease (.7), and cerebrovascular disease (.7).




It might be, however, that states with greater percentages of obesity are those where people pay less attention to their health generally or are more likely to engage in risky behavior. And that’s what we find at least in the case of smoking which correlates highly with state levels of obesity (.8).


Might obesity be related to states’ broader social and psychological climates? To get at this, we looked at the relationship between obesity and a commonly used measure of subjective well-being or happiness developed by the Gallup Organization. Obesity is negatively associated with state happiness (with a correlation of -.6). Since these correlations only reflect associations between variables and not causality, it’s hard to say whether this reflects the fact that happier people eat less, are healthier, or are less prone to obesity, or if unhappier people eat more, are unhealthier, or are somehow more prone to obesity, or if both obesity and happiness levels reflect something else. To get at this, we look at the associations between state obesity rates and social and demographic factors below.


Common sense would suggest that more affluent people would have lower levels of obesity and poorer ones higher, and we find such an association. Obesity is correlated with income levels (-.6) and more moderately so with economic output, measured as gross state product per capita (-.4).

One would think that states with greater concentrations of more highly educated people have lower levels of obesity, and that is what we find. States with higher levels of human capital, measured as the percentage of adults with a college degree, have lower levels of obesity (the correlation being -.8).

To what extent does obesity reflect the kind of work people do? We examine the relationships between obesity and three classes of jobs – creative/professional/knowledge jobs, blue-collar working class jobs, and standardized service class jobs like those in food processing and home health care. Obesity is strongly associated with the share of working class jobs (with a correlation of .7). Obesity is negatively correlated with the share of creative class jobs (-.6). Obesity is also negatively correlated with the share of service class jobs (-.4), though more moderately so.

Obesity is lower in states with higher concentrations of artists, musicians, and entertainers (with a correlation of-.6), those with larger concentrations of gays and lesbians (-.5), and immigrants (-.5). This likely reflects broader structural characteristics of those states, as more highly educated states also tend to be more tolerant and open to diversity.

8 Responses to “The Geography of Obesity”

  1. AJ Says:

    Last week I read; 4 out of 10 US citizens has got problems getting enough food per day. Howe do I get that in line with these figures?

  2. Mike L. Says:

    AJ, unfortunately, it looks like the food those 4 out of 10 do eat is the wrong food: high in calories and fats … :-(

  3. AJ Says:

    So there is a dubble problem in the US. Not enough and food of the wrong kind. Howe did that happen?

  4. JH Says:

    The problem is our government policy of subsidising farmers. They create very cheap, low-quality commodity grains. Then, agri-business takes those and makes cheap, high-calorie,low quality food.

    When you have fritos sitting on the grocery shelf next to fresh fruit at 3x the price, what do you think most are going to grab?

    Look at when subsidies started and where our bmi as a country was after 1950, now look at it.

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  6. Michael G Says:

    Nice scatterplots and how they are so consistent with the obesity and health problems correlation.

    Just a quibble with the CDC’s map graphics. I think it should all be one color going from dark to light or light to dark. But if two colors are used, it is light blue that should be 15-19% and dark blue that should be <10%. IMHO for legibility

  7. Sam Says:

    As a fat person who recently lost 60 pounds, it pains me to admit this, but obesity may not be the reason for the health problems cited.

    As you note, all those things are correlations, and don’t prove

    obesity -> causes -> (bad stuff)

    search for “obesity paradox” on this site (I only discovered it recently)

    summary: fat people
    live longer
    have lower all cause mortality in a variety of situations
    despite being discriminated against in medicine[*] and employment and sociologically

    please browse that site for a while if you have the time. It will show you how the regular media is twisting the scientific truth horribly, by omitting or mis-reporting studies that prove the opposite of the mainstream message, and by over-hyping studies that prove the mainstream message.

    [*] the anti-fat-person bias in medicine is legendary. The amount of nurses that are anorexic/bulemic must be second only to ballet dancers & models.

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