Over the last two decades, multiple independent research groups have come to the surprising conclusion that people with obesity (or, more commonly, overweight) might actually be healthier than lean people in certain ways. This finding is called the "obesity paradox". Yet recent research using more rigorous methods is suggesting that the paradox is an illusion-- and excess body fat may be even more harmful to health than we thought.
Introduction. What is the obesity paradox, and why does it matter?
We have an enormous scientific literature suggesting that excess body fat increases the risk of many diseases, including the ones that kill us most-- cardiovascular disease, cancer, and diabetes. Yet around the turn of the 21st century, evidence began to emerge that the story might not be so simple.
Researchers reported that people with cardiovascular disease, kidney disease, and lung disease tended to fare better when they had obesity than when they didn't (1). Then in 2005, a National Institutes of Health researcher named Katherine Flegal dropped a bombshell on the research community: in her analysis of Centers for Disease Control data, people who were overweight had a lower overall mortality risk than people who were lean or obese (2). In other words, people who carry some excess fat are the least likely to die, implying that they're the healthiest overall.
Flegal followed this up with more papers in a similar vein, including a 2013 meta-analysis representing 2.88 million people that confirmed her group's previous finding: overweight people, not lean people, have the lowest mortality risk (3).
The potential implications of these findings are enormous. Two-thirds of American adults have obesity or overweight, and we know that major weight loss is hard to achieve and sustain. If the obesity paradox is true, then it implies that we should just stop pestering people to lose weight-- there's no problem to begin with! This is a comforting idea for people who carry excess weight, particularly if they've struggled with weight loss.
It's also a comforting idea for the sugar water industry, including companies like Coca-Cola. If obesity isn't as bad as we thought, then maybe sugar water isn't as bad as we thought either. Coca-Cola has funded several researchers whose work supports the obesity paradox* (4). I'm not questioning the integrity of these researchers, but Coca-Cola's interest in this idea certainly highlights its importance.
But is it real?
The idea of an obesity paradox was controversial from the beginning, and many people have critiqued it over the years. This came to a head in 2013, when Walter Willett, chair of the Harvard Department of Nutrition, aggressively criticized Flegal's study, stating on NPR that it "is really a pile of rubbish, and no one should waste their time reading it". He also organized a symposium at Harvard explicitly to criticize the concept (5). Willett was rebuked for his aggressive tactics, but despite this, many people agreed with his scientific position.
The fundamental problem with the obesity paradox is that it's based almost entirely on observational evidence, meaning that it doesn't come from controlled experiments that are better at identifying cause-effect relationships. And in this particular case, it's not hard to imagine ways in which observational methods could obscure the true relationship between body fatness and health. In other words, the obesity paradox could be nothing more than an illusion of the particular research methods that were used to identify it**.
How might this work? As an example, we know that illnesses such as diabetes and Alzheimer's disease often lead to weight loss (sometimes many years before diagnosis, meaning that you can't entirely eliminate the problem by excluding people with diagnosed disease). So if you're currently lean and sick, researchers may associate your illness with the lean category, even if you used to be overweight, and even if that excess fat caused your illness to begin with.
A similar phenomenon happens with cigarette smoking. Smoking causes weight loss, and it's also a fast track to illness and premature death. It's not hard to imagine how smokers might make leanness look a lot more dangerous than it really is. It's also not hard to imagine that some smokers don't accurately report their smoking habits, making it difficult to fully account for in studies.
Researchers have recognized these pitfalls for many years, and those who did the best job of correcting for them usually found that lean people tend to be healthiest (6, 7). Yet a new research method developed by Andrew Stokes, assistant professor of global health at Boston University, promises to provide the clearest picture yet of the true relationship between body weight and health.
To minimize the pitfalls of traditional methods, Stokes looks not only at current body weight, but at weight history. He asks a simple question: how does a person's maximum attained weight associate with health outcomes? Weight is compared using the body mass index (BMI) scale, which corrects for the effects of height on weight.
Maximum weight should do a better job of capturing the effect of excess body fat on health, because traditional methods don't consider the possibility that a person might have previously carried more fat, and may have been exposed to its damaging (or protective) effects for many years. If this is true-- which seems fairly obvious to me-- then Stokes's method is a better test of the obesity paradox hypothesis than previous methods.
In 2014, I wrote about Stokes's first study using this method, which suggests that lean people have lower mortality risk than people who are overweight or obese (8). Recently, Stokes and his mentor Samuel Preston published two more papers on the subject, and they are much more detailed (9).
Using the maximum weight method, Stokes confirmed his previous finding that people who remain lean throughout life have the lowest risk of dying. Consistent with this, they also have the lowest risk of developing diabetes and cardiovascular disease. Both associations were substantial. Furthermore, people who already have diagnosed cardiovascular disease have a higher risk of dying if they're also obese, not lower. There is no paradox in these data, which is a good sign that we finally understand what's going on. It's also reassuring that his results align well with what we know from experimental studies in animals and humans.
His paper goes on to provide valuable insight into why previous studies often went astray. With the weight history method, he was able to show that people who lost weight and went down a BMI category were inflating the risk level of that category, confirming that this was warping the results of previous studies. The most likely explanation is that these people were losing weight due to illness (perhaps subclinical) or smoking (perhaps unreported), making leanness appear less healthy than it is.
As a reminder, there is no evidence that voluntary fat loss is unhealthy, and quite a bit of evidence that it's beneficial (10).
The obesity paradox is probably an illusion of the research methods that are used to investigate the relationship between body weight and health. We can never be sure that the results of observational studies are free of confounding, but there are good reasons to believe that Stokes's maximum attained weight method is more accurate than methods that only consider a weight snapshot. I hope these findings will stimulate other researchers to adopt his methods.
* To my knowledge, Flegal has never received funding from Coca-Cola. But in any case, I don't think it's ethical to assume a researcher is biased by a funding source without evidence to support that accusation. It's logical to think in a general sense that industry funding has the potential to bias research, but specific accusations demand specific evidence. I don't find it particularly rational to dismiss research findings out of hand just because of a funding source. In fact, ironically, this is one of the most common debate tactics used by people who are ideologically biased themselves.
** We can add this to a long list of incorrect conclusions that have resulted from confounding in observational studies. A few examples off the top of my head: the relationship between calorie intake and body weight, the effect of vitamin E on cardiovascular health, and the effect of hormone replacement therapy on cardiovascular health.