Two huge new studies further undermine the "obesity paradox"

The "obesity paradox" is the observation that people with higher fat mass sometimes have better health outcomes than lean people, including a lower overall risk of death.  Evidence has been steadily mounting that this finding may be a misleading artifact of the methods used to observe it.  Two massive new studies add to this evidence.

Despite the fact that excess body fat contributes to the risk of a number of common diseases, many observational studies have reported that people in the overweight or even obese categories sometimes experience better health outcomes than lean people.  This is the "obesity paradox".  I covered this concept in detail earlier this year (1).

Yet as with all observational methods, these findings are vulnerable to confounding-- and it can sometimes be profoundly misleading.  There are reasons to believe that confounding could be particularly relevant here.  First, people who are sick tend to lose weight, making leanness look more dangerous than it really is.  Second, cigarette smokers tend to be leaner than nonsmokers, and also much less healthy, also making leanness look dangerous.

Fortunately, there are ways to correct for these potential confounding factors, at least to some degree.  The research of Andrew Stokes has shown that when we do so, the obesity paradox goes away (1).  Two new studies strongly confirm that when confounding is minimized, there is no paradox.

Study #1: "BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants"

This is a huge meta-analysis which, as the title suggests, includes mortality statistics from a whopping 30.3 million people of all weights (2).

The thing I really like about this study is that they analyzed several subsets of the data, each of which was progressively less likely to be confounded.  If we hypothesize that the obesity paradox is an illusion that results from confounding, then each additional step toward minimizing confounding should make the paradox less apparent.

And that's exactly what happened.  In all subjects, as well as current smokers, the lowest mortality level occurred at a body mass index (BMI) of 25, which is on the cusp of overweight.  Yet among people who have never smoked, the optimal BMI was 23-24.  Among people who had never smoked and who were healthy at baseline, the optimal BMI was 22-23.  And among people who had never smoked and were followed up for at least 20 years, the optimal BMI was 20-22!  That is quite lean.

The last analysis is a particularly powerful way of avoiding confounding due to existing illness.  If you're recording a person's weight right now and their risk of death in 20 years, it's likely that whatever kills them in 20 years is not impacting their weight right now.  So you get a cleaner assessment of the impact of BMI on health.  This assessment shows that it's much more dangerous to be obese than to be underweight.  You can see that in this graph of BMI vs. mortality from the paper:

From figure 3. BMI is on the horizontal axis, and mortality rate is on the vertical axis.  The horizontal white lines represent relative risk of 1, 1.5, 2, and 3.  The top of the graph represents a relative risk of 5.

It is worth noting that there isn't a lot of excess risk up to a BMI of 25, and even into the lower overweight range (BMI ~27).  It's really in the obese range that the risk level increases substantially.

Study #2: "Body-Mass Index in 2.3 Million Adolescents and Cardiovascular Death in Adulthood"

This is an Israeli study that, again as the title suggests, measured BMI in 2.3 million adolescents and subsequent death rates in adulthood, with a particular focus on cardiovascular deaths (3).

Like the previous study, this one is remarkable due to the extra-long follow-up period between BMI measurement and death: up to 44 years, with a mean of around 25 years!  This means that there was usually a long period of time between the BMI measurement and the death outcome.  This is compounded by the fact that the researchers measured BMI in adolescents 16-19 years of age-- a time at which very few people suffer from overt disease.  Both of these factors minimize confounding.

When we consider total mortality, remarkably the healthiest BMI range was between 19.7 and 21.4 in men, and between 19.2 and 21.0 in women.  That is very lean, but keep in mind that it was measured in 16-19 year-olds, who tend to have a naturally lower BMI.  That range was also optimal or nearly so for most types of death reported, including stroke, sudden death, total cardiovascular deaths, and non-cardiovascular deaths.  The one exception was coronary heart disease death, which was lowest at the lowest BMI (12-18! Not recommended).

This graph clearly illustrates the consistent relationship between adolescent BMI and later cardiovascular mortality in this study:

On the vertical axis, we have cardiovascular mortality, and on the horizontal axis, the number of years since BMI was measured.  Each line on the graph represents a different BMI category.  BMI is listed by percentile rather than absolute values.  Lower percentiles represent lower BMIs.

The longer the follow-up, the more apparent the BMI effect became. Note that at the longest follow-up, cardiovascular mortality risk differed by nearly 4-fold between BMI extremes.  This is a huge effect.  Again, the risk is concentrated in the higher BMI categories.

Conclusion

Two huge new studies with compelling designs add substantial weight to the hypothesis that there is no obesity paradox.  As suggested by controlled studies in animals and humans, excess body fatness likely contributes to chronic disease risk and the overall risk of dying.  Risk increases in parallel with excess fat, yet BMI values at the upper end of the lean range, and even into the lower overweight range, don't appear to be especially dangerous (particularly among people with higher lean mass)*.  Furthermore, healthy behaviors such as physical activity and a high-quality diet can attenuate risk in people of all weights.


* People of Asian/Indian ancestry may be an exception.  Their risk level increases more sharply at a lower BMI level.