The impact of food price spikes

2013-05-24 06.53.06 amAs we discussed in a previous post, several causes led to a massive spike in food prices internationally in 2008 and again a few years later. The average world price of rice, for example, rose by 217% between 2006 and 2008. Classical theories have suggested that we shouldn’t worry about these spikes: that the high prices will lead to more production (attracting farmers to produce more, which will drive prices back down), people’s wages will adjust to costs of living, and people will be able to substitute for expensive items with other foods. But a new report tracking how the most-affected people have responded to the food spikes reveals that classical theories may be a bit out of touch…

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Introducing The Body Economic

Body economic UK jacketPoliticians have talked endlessly about deficits and finance during our ongoing economic crisis. But we’ve talked far less about achieving another major goal that is just as important, if not more so, than promoting stable financial markets: protecting our health and well-being during hard times and into the future. What policies are most effective in preserving our health during economic recessions—and can we afford them?

That question, it turns out, can be answered through data and careful research on recessions both past and present. My colleague David Stuckler and I are today releasing our peer-reviewed book, entitled The Body Economic, in which we boil down over a century of data from across the globe to answer the question of what policies actually improve both our economies and our public health during and after economic recessions.

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Big data mining and new hypotheses in mental health research

BigdataThis is a guest post by the computational epidemiologist Dr. John Ayers:

Most of us are aware of the “big data” revolution fueled by electronic information. It has been suggested that big data, along with hypothesis-free methods popularized by films such as Moneyball, will allow for an unprecedented growth of knowledge across disciplines, including epidemiology and preventive medicine. While I am a bit more circumspect in expectations (there is no substitute for survey data in many cases), I do believe that electronic data collected for a fraction of the cost of survey data can work hand-in-hand with research derived from more traditional sources.

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University-based research and neglected diseases

Back in 1999, the organization Médecins sans Frontières (MSF or “Doctors Without Borders”) received the Nobel Peace Prize and did something a bit surprising with it: they spent it on drugs.

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Soda and global obesity: are sugar-sweetened beverages relevant outside the United States?

Global_Obesity_BothSexes_2008While sugar-sweetened beverages (SSBs) have garnered much attention in the US given their associations with obesity and diabetes in the Nurses Health Study and a number of other assessments, a key question is whether this effect also translates to low- and middle-income countries where both domestic and imported beverages are becoming increasingly popular. In an article just published in the American Journal of Public Health, we looked at this question using the soft drink industry’s own statistics, merged with comparative survey data on weight status and diabetes across the globe.

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Alcohol use during the Great Recession

HEALTH Alcohol 074058There have been many theories and contradictory findings about how alcohol use changes during economic downturns. Will people drink less because they can’t afford it—a common refrain in economics journals? Or will the depression associated with unemployment lead to more binging? A recent article looking at alcohol use during the Great Recession provides an interesting, if unexpected, result.

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Interpreting our findings from today’s study on sugars and type 2 diabetes

Lustig sugar diagramIn today’s edition of the journal PLoS One, we published an “open access” study on the relationship between sugars and type 2 diabetes. The study was an international analysis applying statistical techniques from the field of econometrics to public health data in order to understand the relationship between sugar availability and diabetes prevalence. It was peer-reviewed by five independent statisticians and diabetes experts. The study can be easily misinterpreted—for example, one doctor made the silly comment: “Well this is just like correlating the number of cups someone owns to their risk of diabetes, which is confounded by obesity”—which reflects that the doctor did not read the study or didn’t understand the statistical methods involved; obviously, as professors who teach statistics all day, we controlled for obesity and dealt with these kinds of issues up front. The study is not a typical simple “correlation study” that is far too common in the medical literature. There are, however, very important caveats to the findings, and some context that’s pretty critical to understand. So we wanted to re-iterate the very careful wording in the study and make sure that the actual study findings made it somewhere into the melodramatic discourse on this subject…

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