TCS Daily

Feeding a Risk Factor Frenzy

By Jonathan Robison, PhD, MS - August 25, 2004 12:00 AM

An article in the August 25th issue of the Journal of The American Medical Association, "Sugar-Sweetened Beverages, Weight Gain, and Incidence of Type 2 Diabetes in Young and Middle-Aged Women," adds yet another chapter to the feeding frenzy that drives our nation's love affair with epidemiological risk factorology. This article is a textbook case study in the misuse of epidemiological research for the development of health recommendations for the public.

The article is strewn with misleading and sometimes inaccurate statements and enough statistical hocus pocus to make all but the most adept junk-science sleuth dizzy. Perhaps the most glaring problem with this article, however, is the blatant blurring of the distinction between correlation (or association) and causation. A correlation describes the strength of a relationship between two factors. It turns out, for instance, that there is a correlation between baldness in men and heart disease. This simply means that there is some relationship between baldness and heart disease. If we observe a large group of men over a period of years, those who are bald are statistically more likely to have a heart attack than are those with a full head of hair. We say that the correlation or association between these two variables is positive, and that baldness is a risk factor for heart disease in men. 1

Despite the evidence that bald men have an increased risk of heart disease, however, certainly no one would claim that giving a bald man a toupee would decrease his risk! This is because baldness does not have any influence on heart health, but is simply a factor that happens to be found more often in men with heart disease. Therefore, when we say that any two factors such as baldness and heart disease are positively correlated, we are saying nothing about whether one causes or even affects the other.

Here's how the same problem occurs, as it does in this article, with nutrition research. In a certain population being studied, a particular disease is found to be positively correlated with eating a specific food. This means that people who ate this food were more likely to develop the disease in question than people who didn't eat the food. It is then reported that eating this food increased the risk of getting this disease. If the report garners enough attention health professionals may well begin to make recommendations for changes in people's eating habits based on the reported findings.

In this particular article, the diseases in question are obesity and diabetes and the food involved is the much-maligned sugar in sweetened beverages. The problem is that the identification of this food as a risk factor in this study may or may not mean there is a causal link with the diseases in question. It is entirely possible that subsequent studies will not find an association between this food and these diseases. In fact, previous studies have actually suggested the opposite association between sugar consumption and obesity,2,3 and after reviewing the relevant research, The American Diabetes Association concluded in a recent Position Statement that "intake of sucrose and sucrose containing foods does not need to be restricted because of concern about aggravating hyperglycemia." 4

In a discussion on the limitations of epidemiological research in the journal Science, Leading UCLA epidemiologist Sander Greenland summed up the complexities involved with obscuring the differences between correlation and causation by saying,

"There is nothing sinful about going out and getting evidence...nothing sinful about seeing if that evidence correlates...the sin comes in believing a causal hypothesis is true because your study came up with a positive result..." 5

Unfortunately, this "sin" is committed numerous times in this article, as the critical distinction between correlation and causation falls by the wayside. In setting up their argument in the very first paragraph, the authors state "recent evidence suggests an association between the intake of sugar-sweetened soft drinks and the risk of obesity in children." In the very next sentence they make the unwarranted jump to causation saying, "besides contributing to obesity, sugar-sweetened drinks might...." So, in fact, they have already concluded that half of their hypothesis is correct, before even presenting the evidence.

Even more blatantly, in their closing comments the authors conclude, "because of the observational nature of the study, we cannot prove that the observed associations are causal." Yet this does not stop them from making the jump to causation in the next paragraph by recommending that, "Public Health Strategies to prevent diabetes and type 2 diabetes should focus on reducing sugar-sweetened beverage consumption."

Interestingly, a closer look at the findings shows that even the proposed associations between the variables are questionably weak at best. After correcting for confounding factors, the relative risk of developing diabetes in women drinking the greatest vs. the least amount of sugar-sweetened beverages was 1.32. Epidemiologists generally agree that relative risks less than 2 should be ignored or at least viewed with extreme skepticism, particularly when there is conflicting research available. 5

Applying epidemiological research in this fashion is simply bad science. It tends to scare and confuse people and it greatly oversimplifies the complicated etiology of the types of chronic conditions in question. A number of leading scientists involved in conducting this type of research have acknowledged the significance of this problem. Perhaps those who have not should heed the warning of Dimitrios Trichopoulos, head of the epidemiology department at Harvard School of Public Health:

"We are fast becoming a nuisance to society...People don't take us seriously anymore, and when they do take us seriously, we may unintentionally do more harm than good." 5


1. Lotutu PA, Chae CU, Ajani VA, Hennekens CH, Manson JE. Male Pattern Baldness and Coronary Heart Disease. Arch Intern Med 2000:160:165-171.

2. Gibney, M., Siman-Grant, M., Stanton, J., Keast, D. Consumption of Sugars.

American Journal of Clinical Nutrition 62(1 suppl):178S-193S.

3. Ruxton, C., Garceau, F., Cottrell R. Guidelines for Sugar Consumption in Europe: Is a quantitative approach justified? European Journal of Clinical Nutrition 1999;53(7):503-513.

4. American Diabetes Association Position Statement. Evidence-Based Nutrition Principles and Recommendations for the Treatment and Prevention of Diabetes and Related Complications. Diabetes Care 2002;25(1):202-212.

5. Taubes G. Epidemiology Faces It's Limits. Science 1995;269:164-169.


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