The Richard Dawkins Foundation for Reason and Science (Official) is one of my favorite organizations. Dawkins, of course, is the author of “The God Delusion“ and other popular books about reason, science, evolution and religion. The Facebook “About” page for the Richard Dawkins Foundation says, “This Foundation supports reason and science. We organize to overcome the suffering and intolerance that springs from religious fundamentalism.”
The foundation’s Facebook page is here:
Today, the foundation posted an article which asked the question, “Do you feed your child toxins?” and suggested, “Read the science before commenting” along with a link to a New York Times op-ed piece by Mark Bittman:
The op-ed discusses a recently released study from the journal PLoS One which announced the results of a statistical “study on the relationship between sugars and diabetes”. This study is available here:
And a blog explanation by the principal author of the study, Sanjay Basu, is available here:
A number of comments to the Dawkins Facebook post suggest that this study is an appropriate basis upon which government could (and perhaps should) regulate the sugar content of American food, some going so far as to suggest that government should “ban” added sugar in food. These suggestions follow a pattern of governmental regulation of what Americans eat and drink, such as New York City’s ban on servings of sugary sodas exceeding 16 ounces and the restrictions by many school districts across the country on what food & drink can be served to children for lunch (and even on what they can bring from home).
I usually find posts by the Richard Dawkins Foundation to be useful and, more importantly, accurate. However, this NY Times opinion piece misses the mark in one significant way — the author makes the statement (third paragraph):
“In other words, according to this study, obesity doesn’t cause diabetes: sugar does.”
The principal author of the study, however, in the blog about it, clearly states that this is NOT in fact what their study found. This was a statistical study, not a controlled scientific study. As Basu says in the blog, “There are, nevertheless, limitations to any statistical study. As we teach our students, we can’t ‘prove causality’ through any amount of statistics—we’re simply halfway between the typical weak medical correlation studies and the ideal case of a randomized controlled trial (which often also can’t prove causality for a variety of reasons, despite common misconceptions).” (emphasis added)
In other words, and contrary to Mr. Bittman’s conclusion, this study did not (and could not) find that sugar causes diabetes. Or, as it is sometimes stated, “correlation does not prove causation”.
The Basu blog also makes some other significant qualifications about the study:
“… like any epidemiological study using aggregate data we can suffer from the ‘ecological fallacy’, which means that when we look at aggregate populations, we can’t be sure that those people eating the greater sugars were the exact same people who experienced more diabetes in that given country.”
Which is to say, they can’t even tell if the specific people who ate more sugar are actually the ones who suffered from an increased risk of diabetes.
“… the data themselves are not perfect—in addition to looking for selection bias and doing ‘robustness checks’ by repeating the analysis while excluding outliers or extreme data points (finding, still, consistent results), we have to acknowledge that food availability data from even the best sources are not perfect, and diabetes surveillance rates (even though we checked them against multiple sources), as well as estimates of overweight, obesity and physical activity in many countries are far from perfect. We just used the best data available to date, given the urgency of this question.”
Thus, the data on which the study was based may not have been accurate to begin with, leading to obvious reservations about the conclusions of the study.
And, most significantly:
“The study was conducted to understand a statistical theory, using a statistical approach. It doesn’t say anything about any specific person’s diabetes risk or provide any kind of dietary advice. This data cannot distinguish between types of sugars (like high fructose corn syrup versus other types of sugars), nor does it establish more insight into the mechanisms that are at play, which need to be pieced together in laboratory and experimental research studies. This study also can’t inform any specific policies like the New York City ban on large soft drinks, since the real-world effects of specific policies weren’t evaluated in this experiment.” (emphasis added)
In short, this study is NOT a basis upon which government should act to impose restrictions (or “bans”) on sugar, even if it was otherwise appropriate for government to be regulating what we eat — which, in my opinion, is not in any event the government’s business.
Perhaps the best approach of all is for people to simply “forthrightly accept responsibility” for their own food choices, “regardless of the consequences”. And, once having done so, to make better choices.