« Should I tell students that the maximum score in the class is 137? | Main | What I said about data science at Princeton Reunions »

Comments

Feed You can follow this conversation by subscribing to the comment feed for this post.

Ken

At one time I worked with some people who were doing a study in about 3,000 older subjects with evaluations of subjects every 3 years. I looked at the nutritional data for what they were interested in and there were some strange results, so I then looked at total energy. For some subjects this was varying by a factor of 3 from one period to the next. Some went up by a factor of 3, some went down by a factor of 3. When they were low they were theoretically starving and when high they were absolutely gorging themselves on food, as someone in training for an sporting event might.

My conclusion was that they didn't have a clue what they were eating and were often retrospectively filling in the diaries.

My impression is that the body copes quite well with what you eat provided that it isn't extreme, so most effects will be small.

Basil Geoffrey

I think this is a somewhat oversimplified view of nutritional studies (yes - there are many poor ones, I don't think anyone denies this - but not all); diet is incredibly difficult to assess, but it can have a considerable impact on health because it is consumed continuously over a very long time. The difficulties and limitations of different dietary assessment methods are well known, and a of effort is invested in refining these methods or finding alternatives (e.g. biomarkers, online-assessment tools etc).

Nutritional research is made difficult not only because of the limitations of dietary assessment, but also because the effect size is usually fairly small and therefore very hard to detect. Furthermore, it is not always clear whether an observed association is caused by a specific bioactive, nutrient, food, dietary pattern or something completely different. Take fibre as an example - whose intake is very difficult to measure (there exists more than one definition), but with sufficiently well designed studies it is possible to show an effect.

Do we need better studies in nutrition? No doubt we do - and we can learn from the medical profession and follow their example with standards and regulations. (but they should remember that a couple of years ago drug trials had some limitations too ...). However, it is important to understand that nutrition is fundamentally different from medicine - very different intervention (long term, complex) and very small effect size, but with a possibly huge impact on public health (eg trans-fats).

Kaiser

BG: Thanks for the comment. Yes, we need better studies. Ioannidis makes that point too and mentioned a few ideas, including the shift from focusing on assessing single nutrients to measuring diets. Trying to establish long-term, small effects of bundled stimuli is also a difficult problem in a business setting (multiple marketing actions taken over time); and we have not really come to terms with the difficulties.

It doesn't help when poor studies get reported in big media, with screaming headlines claiming you will get healthier by drinking another cup of coffee or whatever. Like you said, most of these effects, even if found, will be small.

Ken

One problem with nutritional trials is that people tend to be non-compliant over the years that the studies need to be run. Maybe someone will stick to a diet for a short period, but basically unless someone is given the choice of food that they enjoy eating and is easy to prepare they will end up with whatever they used to eat.

The comments to this entry are closed.

NEW BOOTCAMP



Link to Principal Analytics Prep

See our curriculum, instructors. Apply.
Kaiser Fung. Business analytics and data visualization expert. Author and Speaker.
Visit my website. Follow my Twitter. See my articles at Daily Beast, 538, HBR.

See my Youtube and Flickr.

Next Events

Jun: 5 NYPL Public Lecture on Analytics Careers, New York, NY

Past Events

Apr: 2 Data Visualization Seminar, Pasadena, CA

Mar: 30 ASA DataFest, New York, NY

See more here

Courses

Numbersense: Statistical Reasoning in Practice, Principal Analytics Prep

Applied Analytics Frameworks & Methods, Columbia

The Art of Data Visualization, NYU

Junk Charts Blog



Link to junkcharts

Graphics design by Amanda Lee

Search3

  • only in Big Data

Community