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“Is your Englishman so expert in his drinking?” asks Cassio in Othello. “Why he drinks you with facility your Dane dead, he gives your Hollander a vomit ere the next pottle can be filled,” Iago replies. Many countries—like many barflies—take perverse pride in their thirsts. Now, thanks to the the World Health Organization’s recent Global Status Report on Alcohol and Health, we can actually find out which countries put away the most booze. The map below shows it graphically; it generated a lot of attention when it was picked up by the Huffington Post.

The full report contains some real surprises. For one thing, Americans are relatively abstemious—the U.S. is only the 56^th most bibulous nation on earth, consuming 9.4 liters of alcohol per person per year, mostly in the form of beer (4.47 liters), plus 1.36 liters of wine and 2.65 liters of spirits. Canada is 48^th, with an average intake of 9.77 liters (4.10 in the form of beer, 1.5 in wine, and 2.10 in spirits).  Moldova, if you’re interested, is number one (18.22 liters!), followed by the Czech Republic (16.45) and Hungary (16.27). Fans of the Bard will be pleased to know that the 17^th ranked English are still more potent potters than either the Danes (who are ranked 18^th) or the Dutch (20^th).

One surprise is that more people abstain than you might expect—almost half of all men and two thirds of women worldwide report that they have not had a drink in the past year. Many of those abstainers, of course, are Islamic.

My team and I decided to take a fun look at these data and use them to examine what factors might be associated with a nation’s propensity to drink. Is drinking more prevalent in poorer or richer countries? Those whose citizens are more or less educated?  How might a nation’s drinking habits be related to its economic structure?  Is drinking more widespread in countries with hard-scrabble blue-collar economies or in those where white-collar knowledge-work is more prevalent?  What about a nation’s happiness: Are people more likely to drink in nation’s where the happiness climate is “down” or might it be that tipsier countries are happier than teetotalers? With the help of my colleague Charlotta Mellander we ran a basic correlation analysis between these and other factors. Our analysis only points to associations between variables; we do not make any claims about causation and note that other factors that we have not looked at might come into play. Still, a number of interesting and in some cases perhaps counterintuitive findings cropped up.

Drinking levels are lower where the prospects for workers are better, or are at least perceived as such. The correlation between alcohol consumption and “good labor market conditions” (the variable is from Gallup surveys) is -.46. At the same time (a bit paradoxically), drinking is more prevalent in richer than in poorer countries. The correlation between alcohol consumption and economic output is .39.

Drinking is more prevalent in nations with highly educated populations.  The correlation between alcohol consumption and human capital was .61, the highest of any in our analysis.

Drinking is more prevalent in white-collar, knowledge-based economies. The correlation between alcohol consumption and the creative class (the share of workers in professional, technical, artistic, creative, health and education jobs) is .45.

Despite the stereotype of blue-collar workers as heavy drinkers (and statistics that back up the idea that they drink more when they are worried about jobs), our analysis did not show a significant correlation between alcohol consumption and the percent of a workforce in blue collar occupations.

Perhaps the most surprising finding in our analysis is that happier nations quaff more than unhappy ones.  Alcohol consumption was systematically higher in happier nations, with a correlation of .31.

What does all this mean? Over-indulgence in alcohol—especially of home-made alcohol—remains a dire health risk. Especially in poorer, less-developed countries, alcohol abuse goes hand in hand with high levels of crime, disease, and early death. But many of the world’s least sober places are also among its richest, most well-educated, happiest and healthiest. “Western European countries have some of the highest consumption rates but their net alcohol-attributable mortality rates are relatively low,” the report reveals.

And this shapes something of a paradox.  When people in poor nations drink, it tends to compound their economic woes and health problems. But for nations whose people can afford it, alcohol (when used in moderation) is more of an indulgence than a vice.

That’s the overwhelming conclusion of a new Gallup-Healthways survey based on telephone interviews with 173,581 employed Americans over the past year.

The first chart shows the toll that commuting takes on physical health. Americans with longer commutes suffer higher levels of back pain, higher cholesterol, and higher levels of obesity.

The second chart shows the toll of commuting on emotional health and happiness. Those who commute more worry more, experience less enjoyment, and feel less well-rested.

Commuting is a health and psychological hazard, not to mention the carnage and wasted time on our over-clogged roads. It’s time to put commuting right beside smoking and obesity on the list of priorities for improving the health and well-being of Americans.

This chart from Gallup shows the dramatic growth in the percentage of Americans who want to see smoking banned in public venues.

GOOD links this map from a new report on state obesity from the Trust for America’s Health.

A quarter or more of all adults are classified as obese in more than two-thirds of states. The fattest states are all in the South. Colorado, California, Montana, and Mid-Atlantic and New England states have the lowest rates of obesity.

Late last year, I posted on an analysis my Martin Prosperity Institute colleague Charlotta Mellander and I did on state obesity – using data from an earlier study by the Centers for Disease Control. Here are the findings from that earlier analysis. As usual, we point out that correlation does not imply causality, but simply points to associations between variables.

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.

Here’s a link to a longer paper we wrote on the the factors associated with both obesity and smoking across U.S. states.

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.

Source: American Fitness Index; Wages from the Bureau of Labor Statistics 2006;  Income and Economic Output (measured as gross regional product) from the U.S. Census Bureau

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.

Source: American Fitness Index; Human Capital from the U.S. Census Bureau

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.

Source: American Fitness Index; Creative Class figures from the Bureau of Labor Statistics

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.

Source: American Fitness Index; Working Class data from the Bureau of Labor Statistics

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.

Are we moving beyond the auto age? Writing in Esquire, Nate Silver provides hard statistical evidence that America’s once-overwhelming car-culture and driving habits have peaked. This article in Advertising Age (h/t: Patrick Adler) provides additional evidence that we may well be in the early stages of a reset in attitudes about driving and car ownership, especially among younger folks. Here are some key statistics from the article:

“In 1978, nearly half of 16-year-olds and three-quarters of 17-year-olds in the U.S. had their driver’s licenses, according to Department of Transportation data. By 2008, the most recent year data was available, only 31 percent of 16-year-olds and 49 percent of 17-year-olds had licenses, with the decline accelerating rapidly since 1998.”

“Twenty-somethings went from driving a disproportionate amount of the nation’s highway miles in 1995 to under-indexing for driving in 2009.”

“It’s not just new drivers driving less. The share of automobile miles driven by people ages 21 to 30 in the U.S. fell to 13.7 percent in 2009 from 18.3 percent in 2001 and 20.8 percent in 1995.”

Source: Advertising Age

While “the environment” is the reason many young people cite for driving less and not wanting to own a car, there are several other key forces at work, according to the article:

• Alternatives to car ownership such as Zip Car or other auto-sharing services.
• Greater use of alternative modes of mass transit to and from work. This can save money and boost productivity. You can focus on getting work done on the train, something you can’t do in a car.
• New ways of working  from free agency to more flexible schedules and telecommuting which further reduce the need for cars.
• The rise of the Internet and e-commerce as an alternative to shopping. You no longer need a car to get everything from groceries and personal products to books, CDs, and electronic goods.
• Trading-off car ownership to free up cash for other uses from travel, entertainment, technology, and experiences to more savings.
• The increased popularity of close-in locations and walkable mixed-used neighborhoods which further reduces the need for a car to get around.
• A gradually changing economic landscape which advantages larger and denser regions with more transit alternatives – from walking and biking to mass transit (similar to what I described in an earlier Atlantic piece).  As the article notes:

“The real-estate markets most profoundly affected by the bursting housing bubble – such as Las Vegas and other Sunbelt metro areas – are boom towns built around highways with no substantial train transportation. Real-estate markets that have been less affected or quicker to recover include Boston and San Francisco, which have strong urban rail systems. In New Jersey, Connecticut, Boston, Denver and Chicago, housing prices near new or existing train stations have either been among the first to recover or have seen less depreciation during the bursting of the housing bubble.”

Source: Advertising Age

Younger people today – in fact, people of all ages – no longer see the car as a necessary expense or a source of personal freedom. In fact, it is increasingly just the opposite: Not owning a car and not owning a house are seen by more and more as a path to greater flexibility, choice, and personal autonomy.

Underlying all of this is not so much a shift in ”car culture” values but a shift in economic realities. Owning a car and a house is very costly, for individuals and the economy as a whole. What distinguished “savers” from “spenders,” according to a Canadian study (PDF), is outlays for housing and especially for cars. The amount of money the average American family spends on housing and cars went from 22 percent in 1950 to 44 percent by the 1980s to more than half today. It’s not so much that America is a society of wanton over-consumers – though some surely fit that bill – it’s that they’ve been trapped by the housing-car-energy complex that once stood at the very heart of the U.S. “Fordist” economy. And as any number of studies have shown (PDF), America’s over-investment in housing has badly distorted its economy.

We can’t recover by breathing life back into that old economy. Lasting prosperity requires investment in a new and more efficient economic system. We’ll never get there if we continue to spend every last penny on houses, cars, and energy. We need to reduce spending on the old Fordist consumption bundle in order to free up capital for new technologies, new industries, and greater skill and personal development broadly.

Some of that is already happening as people downsize their homes, downshift consumption, and trade train rides or walkability neighborhoods for long suburban commutes. Young people are at the cutting edge of these shifts, as they are just starting up in their jobs and careers; choosing places to live, work, and raise their families; and deciding how they want to live their lives. Great Resets like this are generational events. They do not spring forth overnight but emerge gradually over time as millions upon millions of individuals and families reset themselves in light of new economic realities. We remain in the very earliest stage of the current reset.

While some look at rebounding car sales or an uptick in the housing market as a sign of economic recovery, from where I sit, the shift away from driving and cars among young people is a much better indicator that the economy is starting to head in the right direction.

The National Bureau of Economic Research says we’re not out of the recessionary woods yet, though some think the economy is looking up. Floyd Norris of the Times, for one, thinks the numbers are pointed in the right direction. (More over at The Atlantic Wire). Restaurants certainly seem to be rebounding.

Today, I stumbled across another intriguing indicator. It’s called the Leading Indicator of Remodeling Activity – LIRA for short. Produced regularly by Harvard University’s Joint Center for Housing Studies, the index measures “national homeowner spending on improvements for the current quarter and subsequent three quarters,” and aims to track “future turning points in the business cycle of the home improvement industry.” The graph charts the trend.

The plunge from 2007 through 2008 is striking. But a turnaround does seem to be in the works. Harvard’s Nicolas Retsinas, who directs the Joint Center, notes that: ”The LIRA suggests annual spending will accelerate, with nearly five percent growth in 2010.”

It’s hard to tell whether the LIRA signals a broader economic recovery. It may be that people who can’t sell their homes are deciding that, if they have to stay put, they might as well renovate. If that’s the case,  now may be the time to start that renovation project you’ve been putting off – well before before the good contractors start getting booked.

“Why Ricky Martin’s Coming Out Wasn’t Big News” -  Julia Baird’s recent  Newsweek article – makes the important point that nations with more progressive attitudes toward homosexuality are also happier and healthier.  She writes:

Still, while it may have been a wrenching decision for Martin personally, there was something refreshing about eye rolling replacing homophobic invective. We should want his coming out to not be a big deal in whichever country we might live in. New research shows that tolerance of homosexuality is likely to mean we live in a democratic, developed, wealthy country. It should also mean we live in a well-educated country. And it may well mean we live in a relatively happy country.

She kindly cites my own recent research with Charlotta Mellander and Peter Rentfrow on happiness, socioeconomic structures, and tolerance. And she quotes Will Wilkinson of the Cato Institute on findings from Ronald Ingelhart’s World Values Survey which looks closely at this issue.

As we’ve transitioned from an industrial to a service/information economy, education and the ability to make independent decisions has become more valuable and therefore more widespread. The need of the changing economy for increasingly educated, independent thinkers has helped create less conformist and more open, tolerant citizens.

But the real kicker is this comment from Wharton economist and Freakonomics blogger Justin Wolfers whose own research with Betsey Stevenson notes the close connection between income and the happiness of nations:

[Wolfers]believes that while there is clearly “something associated with economic development that appears to lead to more liberal attitudes to homosexuality,” it is not clear what that is. “I find it hard to believe that the link is simply ‘happiness,’ but one can easily see how development leads to a more enlightened public through all sorts of forces (democracy, education, time for reflection, less of a fight for survival, etc.).”

The key question remains to what extent more open social and cultural values affect economic development as well as being affected by it.

Check out this map of the geography of Christianity in the United States. It’s one of a series of mind-blowing maps prepared by the brilliant cartographers behind the site FloatingSheep.The geographic pattern is striking.

“Catholics are most visible in much of the Northeast and Canada, with Lutherans taking the Midwest, Baptists the Southeast, and Mormons unsurprisingly taking much of the mountain states. Methodists, interestingly, seem to primarily be most visible in a thin red line between the Southern Baptists and everyone else.”

Now check out their map of Christianity in Europe, where they note the “fascinating split between Orthodox Eastern Europe, Protestant Germany, and Catholic everywhere else.”

And, bringing it all together, here’s their map of Christians around the world.