His first thought was that, of course, weighing oneself daily helped control weight. He checked for the conclusive studies he knew must exist. They did not.
“My goodness, after 50-plus years of studying obesity in earnest and all the public wringing of hands, why don’t we know this answer?” Dr. Allison asked. “What’s striking is how easy it would be to check. Take a couple of thousand people and randomly assign them to weigh themselves every day or not.”
Yet it has not been done.
Instead, people often rely on weak studies that get repeated ad infinitum. It is commonly thought, for example, that people who eat breakfast are thinner. But that notion is based on studies of people who happened to eat breakfast. Researchers then asked if they were fatter or thinner than people who happened not to eat breakfast — and found an association between eating breakfast and being thinner. But such studies can be misleading because the two groups might be different in other ways that cause the breakfast eaters to be thinner. But no one has randomly assigned people to eat breakfast or not, which could cinch the argument.
So, Dr. Allison asks, why do yet another study of the association between thinness and breakfast? “Yet, I can tell you that in the last two weeks I saw an association study of breakfast eating in Islamabad and another in Inner Mongolia and another in a country I never heard of.”
“Why are we doing these?” Dr. Allison asked. “All that time and effort is essentially wasted. The question is: ‘Is it a causal association?’” To get the answer, he added, “Do the clinical trial.”
He decided to do it himself, with university research funds. A few hundred people will be recruited and will be randomly assigned to one of three groups. Some will be told to eat breakfast every day, others to skip breakfast, and the third group will be given vague advice about whether to eat it or not.
As he delved into the obesity literature, Dr. Allison began to ask himself why some myths and misconceptions are so commonplace. Often, he decided, the beliefs reflected a “reasonableness bias.” The advice sounds so reasonable it must be true. For example, the idea that people do the best on weight-loss programs if they set reasonable goals sounds so sensible.
“We all want to be reasonable,” Dr. Allison said. But, he said, when he examined weight-loss studies he found no consistent association between the ambitiousness of the goal and how much weight was lost and how long it had stayed off. This myth, though, illustrates the tricky ground weight-loss programs have to navigate when advising dieters. The problem is that on average people do not lose much – 10 percent of their weight is typical – but setting 10 percent as a goal is not necessarily the best strategy. A very few lose a lot more and some people may be inspired by the thought of a really life-changing weight loss.
Krista Casazza, Ph.D., R.D., Kevin R. Fontaine, Ph.D., Arne Astrup, M.D., Ph.D., Leann L. Birch, Ph.D., Andrew W. Brown, Ph.D., Michelle M. Bohan Brown, Ph.D., Nefertiti Durant, M.D., M.P.H., Gareth Dutton, Ph.D., E. Michael Foster, Ph.D., Steven B. Heymsfield, M.D., Kerry McIver, M.S., Tapan Mehta, M.S., Nir Menachemi, Ph.D., P.K. Newby, Sc.D., M.P.H., Russell Pate, Ph.D., Barbara J. Rolls, Ph.D., Bisakha Sen, Ph.D., Daniel L. Smith, Jr., Ph.D., Diana M. Thomas, Ph.D., and David B. Allison, Ph.D.
Many beliefs about obesity persist in the absence of supporting scientific evidence (presumptions); some persist despite contradicting evidence (myths). The promulgation of unsupported beliefs may yield poorly informed policy decisions, inaccurate clinical and public health recommendations, and an unproductive allocation of research resources and may divert attention away from useful, evidence-based information.
Using Internet searches of popular media and scientific literature, we identified, reviewed, and classified obesity-related myths and presumptions. We also examined facts that are well supported by evidence, with an emphasis on those that have practical implications for public health, policy, or clinical recommendations.
We identified seven obesity-related myths concerning the effects of small sustained increases in energy intake or expenditure, establishment of realistic goals for weight loss, rapid weight loss, weight-loss readiness, physical-education classes, breast-feeding, and energy expended during sexual activity. We also identified six presumptions about the purported effects of regularly eating breakfast, early childhood experiences, eating fruits and vegetables, weight cycling, snacking, and the built (i.e., human-made) environment. Finally, we identified nine evidence-supported facts that are relevant for the formulation of sound public health, policy, or clinical recommendations.
False and scientifically unsupported beliefs about obesity are pervasive in both scientific literature and the popular press. (Funded by the National Institutes of Health.)
It is curious to look at the disclosures for potential conflicts of interest in the paper - about as many as I've ever seen. And that raises yet another issue ...
People tend to transition from walking to running somewhere between 2 and 3 metre per second - the sweet sport for most people, meausred on treadmills, occurs at about 2.3 meters per second. But how do people in hte real world solve the problem of getting from point A to B in a minimal amount of time? A paper published in the Journal of the Royal Society on mixing walking and running to minimize energy expenditure - looks into it more deeply and finds that we're pretty good at energy minimization.
Walking, running, and resting under time, distance, and average speed constraints: optimality of walk–run–rest mixtures
On a treadmill, humans switch from walking to running beyond a characteristic transition speed. Here, we study human choice between walking and running in a more ecological (non-treadmill) setting. We asked subjects to travel a given distance overground in a given allowed time duration. During this task, the subjects carried, and could look at, a stopwatch that counted down to zero. As expected, if the total time available were large, humans walk the whole distance. If the time available were small, humans mostly run. For an intermediate total time, humans often use a mixture of walking at a slow speed and running at a higher speed. With analytical and computational optimization, we show that using a walk–run mixture at intermediate speeds and a walk–rest mixture at the lowest average speeds is predicted by metabolic energy minimization, even with costs for transients—a consequence of non-convex energy curves. Thus, sometimes, steady locomotion may not be energy optimal, and not preferred, even in the absence of fatigue. Assuming similar non-convex energy curves, we conjecture that similar walk–run mixtures may be energetically beneficial to children following a parent and animals on long leashes. Humans and other animals might also benefit energetically from alternating between moving forward and standing still on a slow and sufficiently long treadmill.
Imagine you wish to go from your house to the bus stop and have very little time to do so. You would likely run the whole distance. If you had a lot of time, you would likely walk the whole distance. If there was an intermediate amount of time, perhaps you would walk for a while and run for a while. While it is not immediately obvious that using a walk–run mixture is advantageous here, it seems consistent with common experience. In this article, we make this anecdotal experience precise by performing human subject experiments. Most significantly, we then interpret the experimental observations using metabolic energy minimization, without appealing to fatigue or poor time-estimation as mechanisms. We review and extend various mathematical results related to metabolic energy minimization and locomotor choice, deriving, for the first time, predictions for travelling finite distances and for travelling on treadmills of finite lengths, in the presence of costs for the transients, using analytical arguments and numerical optimization. In these models, the key mathematical criterion for obtaining walk–run (and walk–rest) mixtures is non-convexity of the energy cost curves. Assuming similar energy curves, we conjecture that similar walk–run–rest mixture strategies may be energetically beneficial in superficially diverse situations: children walking with parents, animals on long leashes or long slow treadmills, non-elite marathon runners, etc.
In any case there’s little question that a stronger kitchen garden movement would both produce better food and put more of us in touch with where food really comes from, and how. Michelle Obama was not the first First Lady to plant a garden; Eleanor Roosevelt did it in 1943, when 20 million “victory” gardens (out of a population of only 135 million people), produced 40 percent of our fruits and vegetables. I recognize that it will take a near-apocalypse to see those kinds of numbers again, I recognize that turning lawns into gardens isn’t a panacea, but I also recognize that hounding people for growing vegetables in their front yards is hardly the American way.
You’ve probably heard the old story about the pedant who dared to tinker with Winston Churchill’s writing because the great man had ended a sentence with a preposition. Churchill’s scribbled response: “This is the sort of English up with which I will not put.”
It’s a great story, but it’s a myth. And so is that so-called grammar rule about ending sentences with prepositions. If that previous sentence bugs you, by the way, you’ve bought into another myth. No, there’s nothing wrong with starting a sentence with a conjunction, either. But perhaps the biggest grammar myth of all is the infamous taboo against splitting an infinitive, as in “to boldly go.” The truth is that you can’t split an infinitive: Since “to” isn’t part of the infinitive, there’s nothing to split. Great writers—including Chaucer, Shakespeare, Donne and Wordsworth—have been inserting adverbs between “to” and infinitives since the 1200s.
Where did these phony rules originate, and why do they persist?
For some of them, we can blame misguided Latinists who tried to impose the rules of their favorite language on English. Anglican bishop Robert Lowth popularized the prohibition against ending a sentence with a preposition in his 1762 book, A Short Introduction to English Grammar; while Henry Alford, a dean of Canterbury Cathedral, was principally responsible for the infinitive taboo, with his publication of A Plea for the Queen’s English in 1864.
From the guy who runs the Canine Cognition Lab at Duke comes a curious new startup - Dognition (going live soon .. the blog)
The service was featured in the January 18th issue of Science pp.260-261
You pay $60 to learn about your dog and the data for a large sample is collected to learn more about canine cognition. A bit about the business (via the Wichita Eagle)
Dognition is based on the premise that engaging in what the company calls “science-based games” can give dog owners new insights into their pets’ behavior and bolster their relationships. If, for example, you discover that your beloved Butterball responds better to gestures than verbal commands, or vice versa, you can adjust your communication accordingly.
That’s the practical side of things, but there’s an emotional component as well. The founders of Dognition stress that people love their dogs and want to understand how they think, just as they want to know what makes their children or spouse tick.
Dognition plans to offer an assessment test, available over the Internet – including an app for your smartphone – that dog owners can administer to determine their dogs’ cognitive strengths and weaknesses and uncover new strategies for human-pet interaction. Each customer will receive a “Dognition Profile” report.
The company plans to start free beta testing soon and launch to the public in January. The likely cost will be $40 to $60.
The collective data that Dognition accumulates also hold the promise of expanding our scientific understanding of dogs, Hare said. Academic centers such as the one he leads at Duke only have the capacity to test a few hundred dogs a year, so opening up such tests to dog owners worldwide via the Internet has the scientist practically drooling