There has been released recently a widely pressed study — another Nurse’s data dredge — showing that middle age women have increasingly greater chances of not making it to “healthy” old age (health is defined including certain levels of mobility, as well as the not having any diseases) if they are overweight or obese, compared to “thin” people.
Lie warnings in the news article — contains blatant lies via “expert” testimony (that weight is a modifiable, non-genetic factor — as we know on this blog quite well, weight is 77% heritable, second only to height).
Looks like the study is another data dredge of the Nurse’s Health Study. Recall that this study is the parent of the most-cited article on health and obesity, “Body Weight and Mortality Among Women,” which concluded that even mild overweight (and extrapolating upwards from there) was associated with a greater risk of premature death. Sound a bit like the conclusions drawn in the most recent study, except replacing premature death with greater ill-health.
Recall Campos in “The Diet Myth” — he used the very study cited above to show how manipulations of data, and selective interpretations, could account for wildly different results. So different as to contradict the very conclusions of the authors themselves — in fact, he showed that the Nurse’s Health Study was another example of the inverted J-curve of mortality with respect to BMI, placing those at greatest risk of “premature” death in the underweight range, next in line the far opposite end of obesity (which is still on the level of some “normal” folk), and with the least chance of “premature” death in the overweight category.
Given the fact that this is the same Nurse’s Health Study, just a few years older, the inverted J-curve must still present itself. Which is likely why the authors didn’t tackle longevity in the study, just a very specially-defined “health” status, which likely maximized the amount of “unhealthy” over-70s in the overweight/obese category. Let’s check out the study a bit more.
Their definition of “health”:
Although there is no consensus on the definition of successful ageing or healthy survival, the working definitions in most previous studies8 9 11 12 were based on the concept raised by Rowe and Kahn, which incorporates not only chronic diseases but also physical, cognitive, and other functions.23 We used this same concept to derive our comprehensive working definition of healthy survival. Specifically, for our primary definition, healthy survivors were participants who survived to age 70 or older and as of age 70 were free from 11 major chronic diseases—that is, cancer (except non-melanoma skin cancer), diabetes, myocardial infarction, coronary artery bypass graft surgery, congestive heart failure, stroke, kidney failure, chronic obstructive pulmonary disease, Parkinson’s disease, multiple sclerosis, and amyotrophic lateral sclerosis (because cognitive function was assessed near 2000 for 99.1% of the study population, we used the disease status up to 2000 for this domain); had no major impairment of cognitive function; had no major limitation of physical functions; and had good mental health. We defined nurses who survived to the age of 70 and did not meet these four criteria as “usual survivors.” In our cohort, there were 1686 (9.9%) “healthy survivors.”
First of all, the study is a giant set of self-reported surveys. Got that? While causes of death and major diseases (like diabetes, cancer, Parkinson’s) are checked up on with medical records checks or with a phone interview or with additional questionnaires, the study authors are not bringing in the women and doing thorough checkups on them. That’s the nature of epidemiology — the belief that even though the data quality is vastly poorer to more rigorous, in-lab studies, if they crowd enough people on to the rolls, they will make up for the data quality with numbers. In other words, it comes down to the power of statistics to produce correlations that are then reported as study results.
Secondly, the definition of ill-health is very complicated, obviously crafted to maximize the results they obviously desire in their introduction (remember, introductions are usually written before the study is even begun — they are often extrapolations of the abstract, and the abstract is often what is submitted to various organizations in order to procure grant money to get funding to conduct the study).
And yes, we have the J-curve phenomenon, which is never mentioned in the study. Why could this be relevant? Simply because if there are more overweight and obese women living to old age than thin women (which is suggested by the J-curve), there is more potential for the number of overweight and obese women to have a greater incidence of “ill-health” as defined by the study. Then, if you play the numbers game just right, you can likely easily show that for every 1 “unheathy” older thin person, there were 1.8 “unhealthy” fat people. Yep — 80% is an odds ratio. It makes it look huge, right? Like 80% of all fat people who live to old age get sick? That’s why they used that number. It’s much less scary if you for every 5 unhealthy elderly thin people, there are 9 unhealthy elderly fat people, with “unhealthy” being defined on the four-point physical function, cognitive function, mental health, and chronic disease-having criteria as quoted above.
Here’s a quote to further give you the sense that the data was very chopped up and carefully manipulated to maximize the desired outcome. Note here that four BMI categories (underweight, normal, overweight, obese) are turned into several more:
For analysis of BMI, we grouped the nurses into six categories according to their baseline BMI: <18.5, 18.5-22.9 (reference), 23.0-24.9, 25.0-26.9, 27.0-29.9, and 30. For analysis of weight change, we calculated weight change between age 18 and 1976 and grouped the women into five categories: lost 4.0 kg, stable weight (reference), gained 4.0-9.9 kg, gained 10.0-14.9 kg, gained 15.0-19.9 kg, and gained 20 kg.
Furthermore…the first chart in the study really says it all…this is a null study. What is the difference between 22.9 and 24.4? I know, it’s subtraction, but apparently the to the authors, this is basically what underpins their entire set of results. That’s right — in 1976, when the study started, the average BMI of the group of ~1600 “healthy” survivors was 22.9, and the average BMI of the group of 15,379 “unhealthy” survivors was 24.4.
Also note that the study authors decided to disinclude women who had lost weight between ages 18 and the study start.
I think the strongest fishy smell to this study is that there was no discussion about how weight gain between 18 and 50 greater than a certain amount can be indicative of disorders they did not test for (PCOS, Cushings), and that they didn’t discuss the possibility that many of these women may have been undiagnosed with diseases which have weight gain as a symptom (like Type II diabetes, hypoglycemia, some thyroid conditions). It’s possible that in their four-point determination of “health” status, which was based on presence of chronic disease (only 11 diseases, not including PCOS, Cushings, lipedema, hypoglycemia, and some lymph disorders which have weight gain as a side effect), mental health, cognitive function, and physical function, ignores the way ones physical function, for instance, can be negatively impacted by lipedema and lymph disorders, or how one’s mental health can be negatively impacted by the stigma associated with PCOS and other weight-gain related conditions, or that one’s mental health can be negatively impacted to a large degree in our culture by being “fat.”
Another issue to address is that fatter people do have a well-known greater incidence of mobility issues when they age compared to thinner people. It’s just gravity, people. A lean elderly person with no other chronic conditions will feel stronger, having the same rate of deterioration as a fatter elderly person. Does this mean that the fatter elderly person is less “healthy” and this means being fat is bad? I think the level of health is the same in the two, it’s the level of ability that is different. And in that sense, this study is clearly defining good health as being “most youthful.” And I don’t really agree with that definition, and though I’m not a medical professional, I don’t think a lot of medical professionals would agree with that definition.
The study doesn’t draw as strong conclusions as it would proclaim. Even if we were to give them the benefit of the doubt in the most complete sense, what they are saying in their results is that elderly thin people — a small part of the population — will be about 80% more likely to not be depressed, and to be mobile, than all elderly people with BMIs over 30 (a much greater amount of people). What does that say, really? They are free of fat stigma, especially as is usually compounded by doctors, which elderly people have to visit far more often than the average younger person. They can also fight gravity better in their relatively deteriorated condition than people who are heavier. That’s common sense.
Finally, the funding:
Funding: The study was supported by the National Institutes of Health (grants AG13482, AG15424, and CA40356) and the Pilot and Feasibility program sponsored by the Boston Obesity Nutrition Research Center (DK46200). QS is supported by a postdoctoral fellowship from the Unilever Corporate Research. MKT is supported by the Yerby postdoctoral fellowship programme.
When it comes down to it, what this study *does* do very well is satisfy some of the most highly prized marketable points in favor of the diet industry:
1. Panic women further about their health. The younger, the better.
2. Make them believe that the “normal” BMI cutoff isn’t good enough. They should ideally be as thin as possible, with the best outcome their desire to be underweight (which was shown by this study to be the greatest indicator of “healthy” survival). Therefore, virtually all the population of women is “too fat,” at all points of their adult lives.
3. Get more middle-aged women, who are typically less vain and image-centric than young women, panicked about weight.
What do you think about this study?
EDIT: I also want to point out that all the study participants were white. Considering the strong genetic component of body size and what we are increasingly learning about the relationship between ethnicity and body size, the fact that this study is extrapolating to all non-white in its fundamental message is absurd, and another one of its many weaknesses. (not to say all people of particular ethnicities are shaped the same, of course – I’m shaped very differently from my own paternal grandmother, for instance)