Posts Tagged ‘scientific integrity’

Confessing to the Truth of Complexity in Obesity Policy

March 17, 2017 — Complexity makes lousy sound bites. That basic fact of political life makes good health policy for obesity maddeningly difficult. We start with the fact that obesity is a complex, chronic disease. And then that complexity is multiplied by a complex environment. Health policies to reduce obesity must influence that environment. To make good policy for obesity, confessing to […]

A Sticky Mess of Mindless Media-Savvy Research

March 4, 2017 — It started with a blog post. Brian Wansink wrote an entry for his blog and called it “The Grad Student Who Never Said No.” It quickly turned into a sticky mess. The essay described an unpaid grad student from Turkey with energy and enthusiasm for exploring data in Wansink’s lab. Wansink is famous for clever research […]

Maybe Sitting Isn’t Really the New Smoking

March 2, 2017 — The idea that sitting is the new smoking has taken off. This compelling narrative – that your desk chair is killing you – is so titillating that you’ll find 33 million results on Google. We have an ample supply of infographics, books, TED Talks, and more. Just one tiny problem is cropping up: hyperbole. Reviewing the Evidence […]

The Mystery of a Retracted Study That Came Back to Life

February 13, 2017 — A new paper in the February issue of Pediatric Obesity probes an important question. Can a gardening, cooking, and nutrition program exert an effect on obesity risk for Latino youth? At first glance, the results are encouraging. Right there in the title, the authors answer the question. The LA Sprouts program “reduces obesity and metabolic […]

Fakin’ It: News, Research, Publications, Conferences

January 2, 2017 — All that attention directed at fake news might be a blip on the viewscreen of popular culture. Or it might be an ongoing concern for years to come. One thing is clear, though. Interest in what is fake and what is genuine has been growing for most of a decade. Fakin’ it on social media […]

Data on Bias That Defies an Investigator’s Bias

November 7, 2016 — When does a hypothesis become a bias? One answer can be found in a recent publication about nutrition research in JAMA Internal Medicine. The authors – Nicholas Chartres, Alice Fabbri, and Lisa Bero – surmised that food industry sponsorship of research might generate outcomes that favor the sponsors. They conducted a systematic review and meta-analysis and found “insufficient evidence” […]

Sweet Tweets about Nutrition and Health (or Not)

October 18, 2016 — How much scientific rigor can you pack into a seminar about nutrition tweets? At the annual meeting of the Academy of Nutrition and Dietetics in Boston yesterday, Cheryl Toner and Heather Mangieri proved you can pack quite a bit. All in the context of nutrition in popular culture. The video on the right – gently poking […]

Three Kinds of Health Advice for Wishful Thinkers

October 4, 2016 — Wishful thinking is pretty easy to find when the subject is fitness, nutrition, health, and obesity. Another label for it might be magical thinking. Unfortunately, health writers promote wishful thinking far too often. Here are three notorious forms of it: Exercise for Weight Loss. The myth that working out is a great way to lose weight is […]

In God We Trust, All Others Bring Data

September 22, 2016 — Don’t trust research funded by industry. Two publications advocated for that idea in JAMA Internal Medicine last week. Advancing a more objective view, Andrew Brown wrote yesterday in Slate that bias comes into nutrition research from many sources: Nutrition is uniquely suited to more personal attachments. After all, everyone eats. And then, as with any other […]

Confounded by Big Data and the Obesity Paradox

September 20, 2016 — We live in an age of big data. That big data brings the possibility of big new insights in nutrition, obesity, and health. It also brings the possibility of big mistakes as people try to translate associations they find into cause and effect relationships. Especially with big data sets, the possibility of confounding errors looms large. Confounding […]