One thing you can usually count on when going to the doctor is getting put on a scale. And if you tip that scale into the overweight range on the standard “body mass index (BMI)” charts, you can count on a suggestion to lose a few pounds.
Just how scientific is that BMI chart and the recommendations doctors draw from it? If you are 6 feet tall and weigh 200 pounds, the chart says you’re overweight, but how certain can your doctor be that you’ll live longer if you shed 10 or 20 pounds?
As it turns out, the obesity research community is currently at war over the issue – and it grew heated earlier this year when The Journal of the American Medical Association published a study by the CDC that followed more than two million people and found fewer deaths among those deemed overweight than those in the normal range. To some doctors, it seemed shocking and paradoxical, since excess fat has been strongly associated with diabetes, cardiovascular disease, fatty liver disease, sleep apnea and other health hazards.
Today in the journal Science, two University of Pennsylvania researchers weighed in with a rational, middle-ground explanation for what’s come to be called the “obesity paradox”. Mitchell Lazar and Rexford Ahima of the division of endocrinology, diabetes and metabolism at the Perelman School of Medicine argued that doctors are on the right track to associate obesity with diabetes and other health problems, but the revered BMI charts don’t give doctors complete information, and the healthy weight range may differ from patient to patient.
The crux of the Penn researchers’ argument is that BMI is calculated using only height and weight. It can’t discriminate between a powerfully built linebacker from a pot-bellied TV watcher. And studies in the last few years have shown that fat is like real estate – it’s all about location. Fat in the belly is much more strongly associated with heart problems and diabetes that the fat on curvaceous hips and behinds.
To doctors steeped in their weight charts and attached to their balance scales, the CDC results and this Penn paper may seem a lot more paradoxical than they are to the rest of us. Most non-doctors know when we look at a person whether he or she appears healthy. Evolutionary psychologists have shown that most of us are wired to be good at assessing the health and fertility of the opposite sex, which we interpret as attractiveness. And their studies have shown that we deem people attractive based more on proportions than on weight as long as they aren’t emaciated or obese.
For women it’s all about the ratio of the waist to the hips, and for men the shoulders figure into it. There are body types that look good to people across diverse cultures, and evolutionary psychologists have suggested those attractive proportions signal something about overall health – something that can’t be measured with a body mass index.
It’s important to note here that the medical community had the broad outlines right. Through the 20th century, life insurance companies collected data on weight, height, and mortality with a strong self-interest in predicting who was likely to die. And they found that being extremely overweight was in fact associated with earlier death. But there were hints that the connection between weight and lifespan wasn’t simple – according to this fascinating news story in Nature, one insurance company researcher found that if you look at people under 50, the overweight were likely to die earlier than the thin, but if you looked at those over 50, the overweight (but not obese) lived longer.
One of the big complications in assessing the dangers of fat is that cause and effect are all mixed up. Your weight has a bearing on your health, but your health can also have a big bearing on your weight. Having cancer or some other serious illness may cause people to lose weight. And smoking can make people less healthy and at the same time, slimmer.
One thing that made the latest CDC “obesity paradox” study so noteworthy was that the researchers attempted to correct for the obviously unhealthy slimming effects of smoking and cancer. But other researchers still don’t believe it. Dr. Walter Willett of Harvard University followed up with a different study that seemed to contradict the CDC’s work by showing those in the normal range were indeed the healthiest. But in that intersting news story from Nature, the lead researcher on the CDC paper, Katherine Flegal, noted some differences in their methods.
…What is more, says Flegal, Willett’s study relies on participants’ self-reported heights and weights, rather than objective measures. “It’s a huge deal,” Flegal says, because people tend to underestimate how much they weigh. This could skew death risks upwards if, for example, people who are obese and at high risk say that they are merely overweight.
It’s not that people will necessarily lie but they might tend to round down or remember their lowest weight measurement over the last year or five.
There may be a deep philosophical difference causing the rift between researchers. It’s engrained in our culture to believe that those who go through the hard work of dieting and exercising to achieve thinness should be rewarded with good health and a long life. It seems so unfair to think that dumb luck plays a big role – that the genes we’re stuck with determine whether we get nice subcutaneous fat that makes us look shapely or at least cuddly, or dangerous “visceral” fat that surrounds our vital organs with a toxic, inflammatory envelope.
But if that’s the way life is, the medical community needs to face it, and Penn’s Lazar says that’s the direction we’re going. As medicine becomes more sophisticated, doctors will use other data – waist measurements, blood sugar, cholesterol, markers of inflammation, relevant hormones and other measures to complement the traditional BMI in determining which of their patients will really benefit from losing weight and how much weight they should lose.
Here’s how Penn’s Lazar puts it in his Science paper:
“The optimal weight that is predictive of health status and mortality is likely to be dependent on age, sex, genetics, cardiometabolic fitness, pre-exiting diseases and other factors. To quote Galileo, measure what can be measured and make measurable what cannot be measured.”