Before the fisking, a digression.
May I beg for a ban on titles for articles about fat issues featuring faux-clever wordplay? I’m talking about titles and subtitles like “Weight of Evidence” or “fat haters’ arguments flabby” or Cathy Young’s latest entry, “A Fistful of Lard.” It’s not clever, folks. It’s an embarrassing negation of cleverness; it’s saying “I’d like the idea of giving my article a clever title, but I’m fresh out of clever at the moment, so here’s some unbelievably obvious crap instead.”
Ahem. Pardon my digression.
Cathy Young’s latest Boston Globe column takes a critical look at a recent JAMA study, written by Katherine Flegal and colleagues, which found that being mildly “overweight” is in fact associated with a longer lifespan than being the so-called “normal” weight, and that overall only 25,000 “extra” deaths per year are caused by obesity and overweight combined. (That’s actually over 110,000 obesity-related deaths, minus the deaths “saved” per year because overweight people live longer than “normal” weight people). Unfortunately, Young’s analysis is flabby – pardon me, lacks weight – oh, I mean, pound for pound it’s not so sound – no, it’s thin on facts – no, it’s a glutton for…
Oh, heck. It just isn’t very good, all right?
Flaws in the “300000 to 400000 deaths caused by fat” studies
Cathy Young writes:
The new study by Katherine Flegal and her colleagues claims that excess weight causes “only” about 25,000 deaths in the United States annually, far below the earlier Centers for Disease Control and Prevention figure of 365,000. Yet, significantly, the CDC is not revising its official estimate…which is based on six previous major studies. It’s not unusual for different studies to yield contradictory results; the scientific consensus emerges from an overview of all available research.
It’s true that the CDC’s official estimate uses data from six previous studies, whereas the Flegal study draws data from only three previous studies. In fact, there are many studies supporting both points of view. What matters isn’t how many studies are done, but if they’re done well or poorly. I will argue that the CDC studies supporting the idea that there is an obesity crisis, with hundreds of thousands dying every year, are poorly done.
There is no single study supporting the CDC’s high death counts; they’ve revised their official number multiple times, and each revision represents a new study. However, all the studies share a common methodology, and share some terrible errors. W. Gibbs, in the current (June ’05) issue of Scientific American, criticizes one of the CDC’s high-death studies (written by Dr. David Allison and colleagues), but his criticisms apply to all of them:
[The CDC’s study] drew statistics on the riskiness of high weights from six different studies. Three were based on self-reported heights and weights, which can make the overweight category look riskier than it really is (because heavy people tend to lie about their weight). Only one of the surveys was designed to reflect the actual composition of the U.S. population. But that survey, called NHANES I, was performed in the early 1970s, when heart disease was much more lethal than it is today. NHANES I also did not account as well for participants’ smoking habits as later surveys did.
That matters because smoking has such a strong influence on mortality that any problem in subtracting its effects could distort the true mortal risks of obesity. Allison and his colleagues also used an incorrect formula to adjust for confounding variables, according to statisticians at the CDC and the National Cancer Institute.
Perhaps the most important limitation noted in the 1999 paper was its failure to allow the mortality risk associated with a high BMI to vary…in particular, to drop…as people get older.
Surprisingly, none of these problems was either mentioned or corrected in a March 2004 paper by CDC scientists, including the agency’s director, that arrived at a higher estimate of 400,000 deaths using [the same] method, incorrect formula and all.
That the CDC “fat crisis” studies don’t adjust for the effect of age on mortality is enough, by itself, to justify throwing them into the garbage. However, there are other reasons to doubt the CDC’s high obesity death counts.
The original 300,000 statistic wasn’t based on weight at all; former Surgeon General C Everett Koop simply misrepresented a study of deaths associated with unhealthy eating and inactivity as being a study of deaths caused by obesity. (Outside the world of anti-fat hysteria, this is called “lying.”).
In the years since, studies have tried to match Dr. Koop’s lie, using what the editors of the New England Journal of Medicine describe as “weak or incomplete data.” In addition to the flaws described in the Scientific American article quoted above, the CDC’s high-fat-death studies failed to account for confounding factors like socio-economic status, discrimination, eating habits, history of yo-yo dieting, body shape, and activity levels – factors that haven’t been accounted for even in Flegal’s better-designed study. Accounting for these factors could easily lead to a massive reduction of the “obesity death count.”
Risk Ratios can vastly exaggerate actual risk
What’s probably most important to understand – and least likely to be intelligently discussed by the mainstream media, unfortunately – is the limitations of the “risk ratio” (also called “hazard ratio”) studies we’re discussing.
In “risk ratio” studies, a very small actual increase in deaths can be made to look like a huge percentage increase. For instance, if one of a group of 4,000,000 pink lollypop lickers dies, while two of a group of 4,00,000 blue lollypop lickers die, a risk ratio study might say that blue lolly lickers have a relative risk of 2.0. “Twice as much” may sound high, but in terms of real-world significance, the difference for an individual lolly-eater between 1 in 4 million and one in 2 million is pretty slight; in either case, it’s amazingly unlikely that an otherwise healthy lolly eater will die of their lolly choice.
And that’s assuming that the lolly had any relationship at all to the death. But correlation does not prove causation. When risk rations are low, and many possibly relevant factors aren’t accounted for, any little thing (random deaths entirely unrelated to lolly licking, a tiny measurement error, a single confounding factor not accounted for) could be the real cause of that difference, not blue lolly licking.
Nonetheless, if blue lollies were treated the way fat is, the CDC would write up a press release proclaiming that studies prove blue lolly licking causes a “100% increase in death!” The press would pick up the claim and trumpet it uncritically. And a much better-supported finding from the same data set – which is that neither pink nor blue lolly lickers face a high risk of death, and blue lolly lickers should not panic – would be entirely ignored.
[I’ve removed a couple of paragraphs I can’t stand behind; they are preserved in the comments, however. –Amp]
Let’s return to Dr. Allison’s CDC study, which the CDC uses to claim that fat kills 350,000 Americans each year. As table 3 from Dr. Allison’s study shows, in every one of the six data sets used, the risk ratio (or “hazard ratio”) associated with overweight is below 1.7 (that is, less than 100%), and sometimes barely above 1 at all. In a couple of the table’s cells, the risk ratio is less than one – meaning that in that data cell, the “overweight” subjects had a lower mortality than “normal” weight subjects did.
Even looking only at the most obese category (people with BMIs above 35), in 9 of the 12 measurements the risk ratio is below 2.0 – and in every measurement, the risk ratio remains below 3.0.
What do those low risk ratios mean? It means that even in the study which supposedly shows fat is deadly, for all but the very fattest people, the increased risk is minimal. Even for the fattest, the risk isn’t particularly large. And at all BMI levels, the association between increased fat and increased death is weak, and would probably be dramatically reduced if unaccounted-for factors – such as age, yo-yo dieting, risky anti-obesity treatments, body shape, discrimination, and socioeconomic class, to name a few – could be accounted for.
The NHANES Trilogy (Star NHANES, The NHANES Strikes Back, and Return of the NHANES)
Let’s return to Young’s attempt to discredit the Flegal study:
Science writer Michael Fumento […] notes that the national survey data used in the study were collected at three points. The sample surveyed earliest had death rates close to the previous CDC findings. The much lower figure comes from adding the later data which, Fumento says, did not allow enough time for higher weight-related mortality to show up.
The national survey data Young is talking about is the National Health And Nutrition Examination Survey, or NHANES for short. To date there have been three NHANES surveys, NHANES I, II, and III, and each survey was gathered and updated at different times (NHANES I (1971-1975) and NHANES II (1976-1980) had follow-ups through 1992, and NHANES III (1988-1994) has been followed-up through 2000).
What Young doesn’t tell her readers is that Flegal and her co-authors wondered if there might be a longer follow-up effect, ran the data – and found that it made no difference. From the Flegal study:
To examine whether the higher relative risks in NHANES I might be due to the longer follow-up in NHANES I, we compared the relative risks from the first phase of NHANES I through the 1982-1984 follow-up with the relative risks from NHANES II and III. Thus, the follow-up period was similar for all surveys (10 years for NHANES I, 14 years for NHANES II, 9 years for NHANES III). The NHANES I relative risks over the first 10 years of follow-up were higher in almost every BMI-age subgroup than were the relative risks from the other surveys (data not shown). Thus, even after controlling for length of follow-up, NHANES I tended to have higher relative risks than the other surveys.
Michael Fumento dismisses this, claiming that the longer follow-up is the most important factor – but his claim contradicts the evidence. If longer follow-ups created a higher measurement of risk, then NHANES I with a ten-year follow-up would show lower risk ratios than NHANES II with a fourteen-year follow-up. But that’s not what the data shows. Even when NHANES II has a longer follow-up period, it still shows lower risk ratios.
Fumeto also quotes a long list of experts saying that the data must be wrong. That’s called “argument by authority”; instead of providing any actual logic or evidence, you parade a bunch of experts and hope that settles the matter. But argument from authority is a very weak argument, and it’s irrelevent when – as in this case – there are well credentialed authorities on both sides of a question. What matters isn’t a list of names, but evidence – and as the Flegal study showed, evidence indicates that mortality from obesity is in fact lower in NHANES II and III than it was in NHANES I, regardless of follow-up period.
If NHANES I hadn’t been included, the new Flegal study would have barely have found any increased mortality at all associated with obesity – and virtually none at all associated with being overweight. So why did NHANES I find such different results?
Probably part of the problem with NHANES I is that it failed to adequately account for the effects of smoking, as the Scientific American article pointed out. And, as Flegal and her co-authors argue, medicine has recently made enormous strides in preventing and treating heart disease and other conditions; conditions that might have killed fat people thirty years ago simply aren’t as deadly now. It’s also possible that Americans are now eating healthier diets and exercising more, compared to the early 1970s.
Does a High BMI Really Mean You’re Fat?
Next, Young questions how relevant BMI is:
Others note that many people classified as overweight in the study may not be “fat” at all. The study relied on Body Mass Index, a measurement that does not distinguish between weight from body fat and muscle, and even consigns some professional athletes to the ranks of the overweight.
This is all true. However, the same thing is just as true of the older BMI studies which found a high number of deaths associated with high BMI. It’s inconsistent of Young and other critics of Flegal to bring this up when she wants to discredit a study, but ignore the exact same flaw in studies whose results she likes better.
Even the Flegal study may overstate the risk of obesity
Cathy Young finds a silver lining: It’s still terribly dangerous to be very fat. Or so Young argues:
But let’s look at what the Flegal study actually said…and didn’t say.
The study didn’t say that you don’t need to exercise. Nor did the study say that severe obesity is harmless: Its death toll was estimated at 112,000 a year. (The 25,000 figure was obtained by subtracting the estimated 86,000 fewer deaths among the moderately overweight compared to people of “normal” weight.)
112,000 a year? Well, yes and no.
The Flegal study is a significant improvement over earlier CDC studies, because it accounts for essential factors such as age, and the more recent data means that improvements in medical technology are included in the results.
But many of the limitations of earlier stories are also present in the Flegal study. A lot of potentially important confounding factors, like yo-yo dieting, weight loss surgeries and drugs, discrimination, activity levels, unhealthy diets, and socioeconomic status aren’t accounted for in the Flegal study, either.
And the risk ratios are once again very low – even for the very fat. For non-smokers with BMIs above 35, the Flegal study found that fat people under age 59 had a risk ratio of 1.25; fat people ages 60-69 had a risk ratio of 2.3; and fat people age 70 and up had a risk ratio of 1.12.
What do the low risk ratios tell us? First of all, that even if you’re very fat, these findings shouldn’t make you panic. (The Flegal study describes the increased risk as “modest.”) And secondly, these low risk ratios suggest that a study that accounted for currently-unaccounted for factors could dramatically lower that 112,000 number. As Flegal and company themselves wrote:
Other factors associated with body weight, such as physical activity, body composition, visceral adiposity, physical fitness, or dietary intake, might be responsible for some or all of the apparent associations of weight with mortality.
(By same token, I’d also say that the risk ratios suggest that the “risk” of being “normal” weight rather than slightly overweight found by the Flegal study is not meaningful. Although it’s a fun mathematical game to say “this study shows that it’s safer to be overweight than ‘normal’ weight,” a more accurate assessment is that this study shows that neither “normal” nor “overweight” people should worry about their weight’s effect on their health.)
There’s another reason that a 30-year-old obese person may face less risk than the Flegal study indicates; medical technology has probably not stopped improving. Thirty years from now, how good will treatments for heart disease, high blood pressure, etc, be? There is no reason to think that a 60-year-old with high blood pressure in 2035 will face as high a risk as a sixty-year-old in 2005 does. But it is current risks – not future risks – that the Flegal study measures.
Finally, consider that most of the increased risk for higher BMIs the Flegal study found came from the NHANES I database. If only NHANES II and III had been considered, the risks found would have been much lower. But there are strong reasons to believe that NHANES II and NHANES III are more accurate data sources than NHANES I. If so, then the Flegal study is significantly overstating the current risk associated with obesity – and understating the benefits of being slightly heavier than “normal” weight.
Conclusion
Let’s go back to Cathy Young. She continues:
The researchers concluded that being more than 40 pounds overweight is indeed hazardous. Yet the activists who agitate for “fat acceptance” want us to believe there’s nothing wrong with 400 pounds of excess fat.
What the researchers actually found is significantly increased risk beginning at BMIs of 35 and above. For someone “40 pounds overweight” to have a BMI of 35, they’d have to be around four-foot-eight; for more average people, “70-90 pounds overweight” is a more accurate figure. But saying “40 pounds” is much scarier, isn’t it?
More importantly, the researchers didn’t say the risks, even for the fattest group of subjects, were “hazardous”; they said there was a “modestly” increased risk. But, again, Young’s version, while less accurate, is much scarier-sounding.
Do fat acceptance activists say that “there’s nothing wrong with 400 pounds of excess fat”? Well, morally, there is nothing wrong with it. No one is helped, and no one’s health is improved, because Cathy Young looks down her nose at the very obese.
Do I think that being 400 pounds overweight has no health consequences?
No.
My impression, from having skeptically read a great deal of medical research, is that extreme obesity probably is an independent risk factor leading to earlier death – although current research, by failing to control associated factors, exaggerates the risk. (It would please me immensely if I could say that extreme obesity carried no risk at all, but alas, that’s probably not true).
However, I don’t think that the danger to the extremely obese justifies the CDC-fueled anti fat hysteria. First of all, even for the very obese, the risk doesn’t appear to be that huge. Second, the proportion of the population that’s 400 pounds overweight is tiny. There are other national health problems that should be much higher priorities for the government.
Furthermore, even for someone who weighs 500 or 600 pounds, I’m not convinced that weight-loss plans – the only solution ever advocated by anti-fat hysterics – are their healthiest alternative. No diet has ever been shown in clinical trials to turn obese people into non-obese people over the long run; nor has anyone ever been able to run a clinical trial showing that losing weight improves health over the long run. Furthermore, some studies have found that losing weight deliberately actually shortens life – especially for yo-yo dieters. Why prescribe a “cure” that probably won’t work, and that could shorten life, for a “disease” that simply isn’t that threatening?
On the other hand, clinical trials clearly show that frequent, mild exercise has reliable, significant health benefits even for people who don’t lose any weight. At any size, the best health plan isn’t losing weight; it’s healthy eating and regular exercise.
That, of course, is the sensible message said over and over by the majority of fat activists: in four words, Health at Every Size (HAES). But rather than giving her readers a fair picture of fat activists, Young attributes nonsense like this to us:
There’s nothing liberated about eating one’s way into diabetes, strokes, heart attacks, and other ailments.
Gee, is anyone saying that “eating one’s way into… ailments” is liberating? Of course not.
What do non-imaginary fat activists say? We say health at every size. We say that no one, at any size, should face contempt or discrimination for their weight. We say that evidence shows that the current anti-fat hysteria is just that – hysteria, unsupported by the best evidence. And we say that health care for fat people should be based on evidence of what actually works best for fat people, not on stereotypes, dubious data, or society’s thinly-hidden disgust.
(Link to Cathy Young article via Hit and Run.)
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Very well said, Amp.
There is a fundamental math error that underlies Dave Allison’s faulty coefficients, which were used without correction or modification in all the CDC estimates before Flegal. Allison, to his credit, posts data tables on his personal web site. There are two major flaws.
1. The estimates of mortality are based not on actual data but rather on a computer model of the data. This allows the effect of obesity to be reduced to a single coefficient, which is a handy short cut but also very wrong.
2. The computer model used by Allison assumes that mortalitity risk is proportion to the square of BMI. In other words, he assumes that risk rises exponentially with increasing BMI above an optimum point (the mathematical minimum, for those who remember parabolic plots from Algebra II). This leads to astronomical risk estimates for very high BMI’s, which departs radically from the actual data.
It takes a fair amount of knowledge of statistics to be able to reconstruct how Allison derived his computer model, and the coefficients of the model only appear on his web site, which was referenced in the bibliography of the “400,000 deaths” article. How many people have actually followed this trail of bread crumbs?
As you mention above, but do not tie in to NHANES I, “medical technology has probably not stopped improving, ” meaning that is has been improving over the time of the studies. It is entirely possible that there was an increased mortality risk in the 1970s, but due to improved technology, the risk had diminished or disappeared by the 1990s. There may be no need to discount NHANES I and prove that II and III are the only valid ones. They could all be right.
Ha! Calling Michael Fumento simply a “science writer” is one of the most intellectually dishonest things I’ve ever seen. He is a pure bigot who equates disagreement with him as the litteral equivilant of murder. That’s not my opinion of him, talking. That is actually what he’s said in the past. His anti-fat hysteria is extreme and he has no real basis to comment on the issues as a scientific authority.
Calling him a “science writer” is desperately inappropriate. He’s a psuedo-scientist for hire for the extreme right wing. His other conclusions? Straight people have no risk of AIDS, pollution is good for the environment, and Iraq is a really safe place. Seriously, look it up. Oh, and I have mentioned he’s petty and arrogant? If these comments are indexed on Google, you can bet Mikey Fumento will show up sooner or later. For a man who hates blogs, he spends an inordinate ammount of time trolling them to see if he gets mentioned so he can huff and puff. He’s so outraged at the idea of people disagreeing with him that he literally will not ever let any questioning of him go unanswered. And his answer invariably involves mocking and insulting his critics. He’s not science writer. He’s a professional liar, as one critic of his put it. That Young relies on his predictably one-sided and unfair analysis is telling.
The risk ratio point is very well presented here. The gross exaggeration reflects the thin arguement the anti-fat crowd has. Wasn’t it just a few weeks ago that a 19% increase in dementia was treated as important by them? The data doesn’t support the conclusions, so just talk about the data in ways to make it appear scarier than it really is. And the fact remains that dieting doesn’t magically work for people who are 400lbs any more than it does for people who are 200lbs. People like Young may think fat acceptance is about eating oneself into oblivion, but this merely reflects her own unmovable prejudices.
Richard:
First of all, although you may have missed it (perfectly understandable, given how long my post is!), I did point that out in my post.
I don’t think you and I really disagree on this one. I don’t think NHANES I is “bad,” although the way it accounted for smoking is problematic (it only asked participants about smoking retroactively). I do think that it’s probably not an accurate data source when used for creating a picture of current health conditions.
Paul Ernsberger posted something on my blog! Cool!
(For “Alas” readers who don’t know, Paul Ernsberger is one of the leading medical researchers in the “Health At Any Size” movement, who is regularly published in peer-reviewed journals. I’m a big fan of his articles.)
Paul, thank you for the info on the problems in the 400,000 study – that’s pretty incredible. You’re right, that information is simply not accessible to general readers, and it should be.
BStu,
While I was preparing this post, I read a bunch of articles by Michael Fumento, and yes, he’s simply stunning. Sheesh.
I actually like Cathy Young – we’ve exchanged a few emails, and she seems very nice. Too bad her politics are so awful. (Of course, she might say the same about me).
The statistical significance of relative risk should obviously depend on how large the risk is and how big the sample is. Just saying “a risk ration of less than 2 is not significant” doesn’t make sense. In your example, if 3 blue lollipop lickers died, it still wouldn’t be significant.
Are there two series of studies? You mention both NHANES and NAMES. Is NAMES just a typo?
[Yup, it’s just a typo – or whatever you call a typo that’s perpetuated by a spell-checker. Aaargh. Anyhow, I’ve corrected the typo. Thanks. –Amp]
As to the dumb headline with a bad pun, I should point out that the headline is usually written by the editor, not the writer of the article. Doesn’t make it better, but the blame should rest with the proper party.
I am having a really hard time grasping the political allainces here. In this corner we have amp, a social democrat explaining why we can not trust anything the government researchers tell us about our health. In that corner, we have Young, a libertarian fighting the the PC fat aceptance activists, which presumably means she believes that we are facing a deadly epidemic that the government shouldn’t do anything about. This confuses me so much I can barely eat my Pop Tarts while I sit here in front of the computer.
Being 400 pounds I have been looked at “askance” when shopping with a cart full of fruits and vegetables. I guess since I am an imaginary fat activist I must eat imaginary junk food. What’s that saying? When all you have is a hammer, everything looks like a nail.
I have to second what dthurston said in post 8. Excluding risk ratio as insignificant because it doesn’t reach a certain number (like 3) above 1 is silly. The confidence interval is what matters and that depends on the sample sizes and the risk factor in the control and experimental groups. You can then decide what level of significance you want to chose (p at 0.05, 0.01 or 0.001) I have no problem with asking for more stringency in these studies but it should be based on statistical principles and not arbritrary numbers whose meaning changes with the experimental conext.
Moreover, by this arguement one would also have to exclude the finding that slightly overweight people have a slightly lower risk of mortality because it does not reach the arbritrary number principle for benefit (o.5) prescribed by this proffesor. I don’t see that argument being given any time in these posts.
All this talk about risk ratios and confidence intervals and sample sizes is irrelevant considering that the studies have not controlled for the most obvious of confounds (including, but not limited to, nutrition, socio-economic status, cardiorespiratory fitness, and stress). You can have a perfectly clear relationship with a huge relative risk and still not have proved A causes B. Of course, noting that the risk is still small is important. I just wanted to point out that even if the risk ratio were extraordinarily high, that would not change the fact that the evidence has not shown that we should fight against certain body sizes in the name of health.
Ha! You really think people are being allowed to “decide for themselves” how much the risk is? The risk is presented devoid of context in as extreme language as possible. It is announced with the intent to scare, not inform. I’ve never seen one of those studies be reported on in a way that accurately describes the relative risk. The notion that relative risk is unimportant is astounding.
The fact is the risks of fatness, even without controlling for any of the many coexisting health risks that might be found, are still very small. Risk ratio is just a means of explaining that. Its the context of the risk, and the context here shows an alarmingly overstated risk. As I’ve often said, twice not much is still not much.
I know to make this deduction when I hear media reports about how scary fat is. Like the recent dementia finding. I looked right for the data on what the increased risk was and I was frankly stunned at how incredibly minor it was for something that was getting the “big important story” treatment. None of the bemused indifference mixed with unthinking denial that met the JAMA study.
But most people don’t think about these things. Or, clearly, they may choose not to think about things that would upset their unblinking opposition to fatness. It is things like this that lead to the popular misunderstanding that fatness is a grave and extreme health risk. Its things like this that lead to doctors pushing WLS on fat patients by telling them they’ll surely die in a year or two without it. Its things like this that fuel a multi-billion dollar industry that has everything to gain from fat hatred. Its things like this that result in most people accepting the myth of fat=bad so blindly that you literally cannot get them to consider any alternative without them looking at you like you just said that the sky is kelly green.
Virginia,
I agree with your points. I am just pointing out that basing judgements on the risk ratio number itself is dubious no matter which direction it is. Deciding on risk ratio significance based on an arbritrary number is even more dubious. The confidence intervals are what is important and can be calculated for a variety of percentages (such as 95, 99 or even 99.9%) and this tells you mathematically how significant the risk is.
Btsu,
I think you misunderstood my point, I’m not reffering to people that read articles in the press deciding anything. The researchers don’t write the press releases. I am reffering to the level of acceptance for significance that the researchers chose. Its normally 0.05. Maybe that should be rethought?
Good point. I didn’t think of it, to be honest. Now that you’ve pointed it out to me, I’ve corrected the post by adding a paragraph indicating that I think the “risks” of being “normal” weight found in the new study (and in many older studies, too) are pretty meaningless.
Pop Tarts are profoundly immoral. What America needs is a nice homemade scone slathered in fresh butter and jam. Why foul a perfectly good cup of coffee with anything Kellogg’s-related ?
Somebody had to have the courage to say it. So there.
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Actually, I know I’ve made the arguement in another thread that the increased risk seen in “normal” weight people is also of little import. Usually in the process of pointing out that their increased “risk” or “normal” vs. “overweight” is equal to the increased “risk” of “obese” vs. “normal” the anti-fat crowd wish to make such a big deal about. The numbers are startlingly similiar and just serve to remind us that none of this is anything to panic over. The only inconsistancy I can see are from those who think the “obese” risks justify the declaration of a deadly epidemic that will kill our children, while the equal risk of “normal” weight is downplayed by the same individuals as statistically unimportant.
While some too-clever for their own good columnists did make a point of the increased risks of “normal” weight, I don’t recall anyone who is geuinely supportive of fat acceptance doing the same. It just confirms what we’ve always said. That the risks found in these studies are statistically insignificant and do not justify the attacks they produce.
Ted,
Actually, a confidence interval (and its related p value) tells us the statistical significance, or how likely it is that the research results were obtained by chance. This is not the same as clinical significance or effect size, which are what relative risks refer to. I can have a study that shows a very small risk but with very high statistical significance. Conversely, I can have a study that shows high risk but with such pathetically low statistical significance that one would have to conclude my results were based on random chance. Setting the p value goal of .05 is typical, which means that there is less than a 5% chance that my results were obtained by chance. A confidence interval shows the range of values I would have obtained had I done that study over and over and over again, so if I want to know with 95% confidence that the true result is within a certain range, I will use a 95% confidence interval. This is all very important to science, but it is separate from effect size. I can set my confidence level at 99%, but the actual effect (risk) can still be incredibly tiny. Therefore, the clinical, or real-world, significance of the finding is still small while the statistical significance is high.
To clarify, it is not “silly” to exclude low risk ratio as insignificant, especially because most of these epidemiological studies are not experimental and may have several factors (confounds) for which the researchers did not control. Therefore, you can acknowledge that you have found a STATISTICALLY significant result and still say that the low risk ratio is insignificant with full scientific integrity. That is not silly. That’s smart and honest.
Virginia, what you say is accurate, but I don’t see hpw its different than what I just said (what are you correcting me for saying? seriously, if there is an error I’d like to correct it). I am a scientist, where I use the word significance I only mean statistical significance. Clinical relevance is for others to decide. I appreciate and understand your point on effect size and I am not expert in the field (or epidemiology in general) so I don’t know how to interpret that data. The confidence interval is calculated by the sample size the individual risk ratios (for the experimental groups) and the p level setting and for this type of data you look for nonoverlap of the interval with 1 (which is the studies showed equal risk). Its the only way to calculate significance for this type of data. You could calculate confidence intervals with a p of any value you wish.
I think we’re saying the same thing, I’m just trying to point out that statistical significance cannot be assessed (or disregarded for that matter) with an arbitrary value because it means a specific thing. Maybe the term relevence should be used. Its misleading when talking about data to use the word significant unless that is what you mean.
Virginia, (responding to post 21)
I’m not saying that is silly, I’m talking about using these arbitrary numbers to redefine what significance is. You could say its significant statistically but that it might not be RELEVANT clinically, that would be scientifically responsible. Sorry for the argument in semantics, but when discussing scientific findings that’s my pet peave and I think it is a major source of misleading info when these studies find their way to the press.
I agree, Ted, it can be misleading because most of the public is not educated in research methodology. That said, however, the word “significant” and the phrase “statistically significant” are different and can both be used appropriately in science. The problem is not that the word was used incorrectly but that it was used irresponsibly with a readership that might not recognize the difference between statistical significance and clinical significance.
If you listen to industrial music, having a high body mass can be very useful. You can keep people away from you at concerts much more effectively. Therefore, it is a positive health factor.
A very small risk might be statistically significant (.05 confidence level), but experience shows that relative risks under 2 are unlikely to be consistent across studies.
Another point is that absolute risk is more important than relative risk. The relative risk of fatal heart attack from having a BMI over 30 is highest for women under 40 –it’s about 2 according to the Nurses’ Health Study (which produced the biggest scary headlines of any obesity study). But your risk of dying of a heart attack in your 30’s and 40’s is very low –about 0.2% a year. So if you are obese, you have a 98% chance of living through the next decade while if you are average-size you have a 99% chance. Which sounds scarier, a doubling of risk or the chances of survival falling from 99 to 98%?
Now consider the risk of dying for people over 70. It’s much higher, usually more than 2% per year. But in old age a high BMI is protective. So when we face the highest absolute risks, the relative risk from obesity is lowest.
Paul e,
If you’re still around I would very interested in your opinion regarding studies showing that in old age a higher BMI is protective (as you just mentioned) in contrast to many studies that indicate that caloric restriction can lead to an increase in longevity (albeit I’ve not seen any data whatsoever in humans). I’ve paid most attention to the caloric restriction idea in worms and the exploration of some of the signalling pathways that may be involved in the increase in longevity. Some of these pathways seem to overlap with the molecular signalling involved in insulin signalling. Based on these seemingly contradictory (although I think they need not be) concepts do you think that caloric restriction will not turn out to be beneficial in humans? I find it hard to imagine that someone (regardless of genetic makeup) who participates in a caloric restriction regimine would not experience a decrease in BMI.
Re the risk of death as a function of BMI for those over 70: I don’t know, but it seems like there are likely other factors going on here — Is BMI standing in for loss of appetite due to disease or decreased function, or other insidious factors? If we accept this for those under 70 (e.g., it’s diabetes not obesity that kills) we ought not to dismiss this for those who are over 70 — I mean, it would be wrong to simply tell those over 70 to start eating and gaining weight when there’s some underlying factor. It seems that at any age, it’s hard to control for factors independent of BMI when studying the impact of weight on longevity and death rate.
There’s one issue that’s been neglected (except tangentially by Barbara), which is being overweight increases the risk of type II diabetes (what used to be known as “adult onset” diabetes, until obese children started getting it). Type II diabetes results in many long-term (and expensive) side effects, and, if left untreated, which, sadly, occurs too often because patients can’t/won’t make the necessary dietary changes can lead to death from secondary causes (e.g., kidney failure).
Being overweight is a serious health issue, even if it’s not ‘lethal.’
Mike, the evidence showing that being fat causes diabetes II is not at all conclusive. A lot of it is anecdotal; and a lot of it is too poorly designed to distinguish increased prevalence from increased testing and diagnosis (as well as changing definitions). Twenty years ago no one bothered testing children for diabetes, so of course the measured rate of diabetes was very low; nowadays we test more often, and naturally it’s found more often. But it’s illogical to conclude from increased testing that real prevalence has increased.
From the current issue of Scientific American:
And from the same article…
What’s even more lacking is the evidence that losing weight alone – as opposed to eating a healthier diet or exercising more – will reduce anyone’s chances of becoming diabetic.
In other words, even if you’re right that being fat increases the risk of diabetes II – and the evidence doesn’t support you – it doesn’t follow that a fat person reduces her chances of becoming diabetic by losing weight. Studies have shown that people “at risk” who exercise and eat healthier substantially lower their chances of developing diabetes. But that doesn’t tell us the cause of the lowered chances of diabetes; it is losing 6 pounds, or is it the better eating and exercise?
Anti-fat ideology assumes that fat is the cause of all problems, and weight loss the cure for all ills. Looked at through that lens, the connection between fat and diabetes is clear. Looked at more objectively, however, the connection becomes a lot more ambiguous.
Ampersand wrote:
Well, yes they did, and what was found and is found in children is type I diabetes. Type II diabetes is “adult-type” diabetes. I have to say that weight in itself doesnt seem to be the worst risk-factor in causing type II diabetes, but rather blood lipids,and problems with lipid metabolism. But with many type II diabetes patients weight loss seems to lessen the symptoms.
Another way of saying this is that the same diet that often leads to weight gain is usually one of the culprits responsible for diabetes. So Amp is right — in theory, you could change your diet without losing an ounce and improve the diabetes situation, but it’s also the case that the kind of diet that would be optimal for a diabetic aften results in at least modest weight loss (the usual — lots of fruit and vegetables and whole grains in moderation, and, of course, drastic reduction in refined carbohydrates and sugar, the latter being stressed most often). So it is really hard to study weight and diet as independent causation factors for diabetes.
It wouldn’t be that hard, Barbara, because many patients don’t lose weight, or lose weight only in the short term.
Current studies of weight loss and diabetes have worked by putting a group of people on a exercise, healthy eating, weight loss regimine (for a much-cited example, see N Engl J Med 2002;346:393–403). A majority of the patients given this treatment do not lose weight over the long term.
However, rather than dividing the patients into those who lost weight over the long term, and those who didn’t, the study merely reports on the results for the entire group.
If the study simply reported on the results sepearately – did only the patients who had long-term weight loss get an advantage from the diet and exercise program, or did all the patients get an advantage? – that would indicate something.
Another useful study would be to divide groups by goals. That is, you could have group A, whose trainers and supervisors are told that the goal is to get them to eat better and exercise more, without regard to weight; and group B, whose trainers and supervisors are told that the goal is to get them to lose weight through diet and exercise. As well as seeing if group A does any better or worse (in terms of developing diabetes) than group B, it would also be interesting to see if the drop-out rates over the course of five years were any greater or lesser for group A than for group B.
Tuomas, I’m not aware of any good clinical studies so far which have distinguished the effect of better diet and exercise from the effect of losing weight. It is therefore inaccurate to say “with many type II diabetes patients weight loss seems to lessen the symptoms,” as if you could be sure that it was the weight loss, and not the diet or exercise, that lessened the symptoms.
Ampersand,
The Scientific American article is quite interesting, thanks for posting it (or at least part of it, but the whole thing seems to be open access on the website for the magazine — i could access it with subscription).
I am becoming increasingly concerned by the seeming disconnect between animal models of disease and what is observed in humans. Obesity and diabetes is not my field (although I’m interested due to the cannabinoid connection as I’ve mentioned before) and it has always been my opinion that the connection between obesity and insulin resistance-type diabetes was very strong in rodent models (although there is now an obese rodent which does not develop diabetes due to a genetic mutation — there are likely other examples, but that is the one I know best). It is well known in my field, pain neuroscience, that analgesics in rodents are often either completely or largely ineffective when they finally make their way to humans (the most notable being the Neurokinin 1 receptor antagonists). This observation has led many of us to wonder if our animal assays are not over-optimized. In other words, the experiments are so robust that even the tiniest analgesic effect becomes so significant that we lose the ability to discern between clinically relevant analgesics and ones that are assay specific. It could also be the case that the models are not relevant to human pain conditions, but the observation that clinically effective analgesics are also analgesic gives a (not too strong) argument against that. I wonder if obesity and diabetes animal models are not similarly over-optimized such that the two states seemingly always come together even though they are actually not causally connected (even in rodents)?
Just a thought…
I guess it’s true that most weight loss isn’t long lasting, but it’s my experience that changes and diet are also not long lasting. Adopting good exercise habits tends to be more enduring, at least from what I’ve read. So I continue to believe that it will be tough to uncouple these things and study them independently.
Ampersand: That is a good point, and after some rechecking about scientific articles I indeed found out that “Change in eating habits and exercising lessens symptoms” (I wont link because I assume you wouldnt understand it. It is in finnish and not many americans can read/speak that), but I suppose you will believe me anyway…
Regarding “risk ratios less than 2 (or 3) should be ignored”:
Tim Lambert, I
Tim Lambert, II
Tim Lambert, III
(Lambert is the guy who dogs John Lott about his guns-and-crime dishonesty.)
Summary: What’s been said here already — a risk ratio of 1.5 can definitely be significant if the sample size is large. But also, an interesting history of how Philip Morris used a front organization to push the idea that a risk ratio of less than two can be ignored.
I love the research and reasoning you bring to the blogosphere. Keep up the good work.
I have to admit, I’m convinced that I need to rewrite my discussion of “risk ratios,” and plan to do so sometime in the next couple of weeks. However, I don’t think any of my errors are bad enough to cause me to alter my conclusions.
Grasp at all the straws you wish. Being overweight is unhealthy. It’s hard on your joints, it’s hard on your heart, it’s hard on every organ in your body. It is shortening your life, just as do such habits as smoking, heavy drinking, and nursing hatreds. Just because researchers can’t pinpoint exactly how much life you’re losing (not to mention the unquantifiable quality of life) by being overweight, doesn’t mean you should stick your head in the sand and ignore everything that every ounce of common sense in your body is telling you.
Instead of overweight people continually posting on multiple enabling boards every day, take that time to be active. Go on a walk, garden, do anything other than sit passively and inactively in front of a keyboard. Already active, you say? Good for you, now be active in the time you normally spend sitting at your computer commiserating about how mean the world is to you.
Neither you nor anyone you have ever met is immune to the laws of physics, chemistry, thermodynamics, etc. If you consume more calories than you burn, you gain weight; if you consume fewer, you lose weight. Be a little more active without upping your food intake, and you’ll lose weight. There’s nothing mystical or insurmountable preventing you from doing this. All it requires is a little bit of willpower. You either have it or you don’t. If you don’t, then continue posting on this and other sites about how unfair the world is and how it’s not your fault at all. Enjoy!
Hm. Think it’s a script?
If not a script, certainly talking points. It is quite often that fat people are decried as an abomination against the laws of God and thermodynamics. Folks like Mike, here, think fat is a product of mathematics, you see. Doesn’t care that things just don’t work as smoothly in real life. Why give up a perfectly good formula to make you feel superior in favor of something far more complex and less prone to encouraging petty hatreds. Mike obviously has a lot invested in his belief that he is fundamentally superior to fat people. Nothing is going to change this. Nothing will get him to see that there is shockingly little evidence to support his conclusions. Nothing will get him to understand that those who question the “fat=bad” concepts he holds so dear have a very real point. And that’s the real challenge facing people on the this side of the fat debate. So many people just won’t care. So many people will never even acknowledge that there is a debate.
Clearly, Mike is a sad, bitter person. And I don’t mean that in a good way. Sorry, Mike. No fresh scones for you. You’d just waste them by trying to eat them dry anyway.
I think we’ve had a visitation from Mike “Foaming” Fumento. The writing is very reminiscent of his scolding style.
Oooooh. That’s quite possible pseu. I called it, too, didn’t I. Its definetly in keeping with Mikey Fumento’s “my way or the highway” debating style. If anything, though, its less crudely insulting that Fumento tends to be. Also, Mikey loves attention and I would imagine he’d be loudly identifying himself. He only conseals his identity when he’s posting as “other people” who just happen to agree with everything he says. He pulled that bit on Amazon.com in the User Reviews for “The Obesity Myth” by Paul Campos. To Amazon’s credit, they caught onto the multiple Mikey’s and deleted his reviews.
Quite obviously Mike has never been chubby-loved, and honey… you ain’t been loved ’til you been chubby-loved.
Michael “Straight people don’t get AIDS” Fumento is a blogger?!
interesting points by every one here, I would like to add that since our bodies are not calculators and work based on “programming” for lack of a better word, that scientists have only scratched the surface of. (you know instincts and such).
so this biological entity or whatever the brain doesn’t operate on this plus that = this no matter what the circumstances, doesn’t work in the body.
so calories in/ calorie out doesn’t work that way, you cannot force the body to use up it’s reserves by restricting food or eating less than the body demands, the body of most obese person’s and moderate overweights or shall I say over fat rebels against anything that is a survival threat.
second if you weigh 200 pounds and it is some fat and muscles and it is hard on teh body and slows you down why would 200 pounds of mostly muscles weight be any easier on the body? I mean weight is weight regardless if you are carrying a 100 pound backpack or 100 pounds of muscles, and most obese people are not all fat, they develope alot of muscles (if they aren’t dieting or restricting caloires) just to carry the weight around.
I know my doctor is amazed at my muscles and yet I still have alot of fat, and you know something funny, no matter what I do I have high bp very high stage 3 no matter when I weighed 160 pounds or 250 pounds over the years, and I ran, and ate well, seldom indulged in junk food except when recovering from a famine.
I have to take medications to get it down, of course they slow me down furthur but it is better than dying of hbp.
and I don’t know why people think fat is hard on the heart (except for the obvious of movement with the weight) because fat takes very little energy or blood flow to maintain whereas muscles require alot of energy and blood flow to maintain. fat is actual light and bulky, only 10 percent water, while muscles contain 90 percent and water is very heavy, I mean when I wasn’t being treated for my condition I could urinate enough water in 24 hour period to lose 10 pounds, I mean water is heavy.
I would think alot of muscles would be harder on the heart even in exercise due to high o2 and fuel needs of the muscles and the heart has to supply it. but his is just my opinion not physiology or anything just something I wonder about.
so is it the fat or just the weight period that is hard on the heart and other organs? or is it something else like junky diets or low nutrition and to much stress on people or whatever?
also the studies about reducing caloires increasing life span is inconclusive, you would have to follow people on a 1500 caloire or 1800 caloire diet for their whole life to see if they live to a ripe old or to see if they die of malnutrition (starvation) before then. but you don’t really need that since people in this country always are on some reduced caloire diet one time or another each year, just follow weight watchers for a while and see what you get or jenny craig .
note who goes, how much weight they lose what their health parmeters aer before during and after and follow them for about 20 years and see how their health goes, and along with that follow those who do nto diet and refuse to and note health parameters and then follow them for 20 years as a control group.
those who exercise, those who do not, that sorta thing, you cannot follow a rat starve it and see it live a month or two longer than most rats and then decide that a reduced diet lengthens life, when in reality it may for rats who are probably miserbly hungry and passive due to starvation.
anyone knows you can slow your heart rate down by semi starvation and slow metabolism and lengthen life in the short term, but in the long term it leads to body’s cannabalism of it’s own tissues to make up the caloiric deficit. you can follow moderate aneroxics (who do eat some food everyday) and see how long they live and what their quality of life is and their health status from year to year.
I mean there aer so many ways to test semi starvation diets without alot of expense since many (millions) voluntarily undertake such a life and pay for it (weight watchers, jenny craige etc) for the privilege of starving themselves or enduring a famine,
I mean we can cite studies and tests, but the real test is in human suffering (for the sake of appearances). just ask all those people who are overweight, or thin due to famines. they can tell you how much suffering there is in maintaining thinness or trying to get there and they can tell you all their health problems too that go with it.
RR
For posterity’s sake, here are a couple of paragraphs from the original post that I’ve removed, because I can’t stand behind them. Essentially, I got taken in by a con – see this post at Deltoid for more info.
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Moderation in all things. Just as yo-yo dieting is bad, so is extreme overweight. (And I say this as someone who remembers the days when insurance companies dinged you more for being thin — a likely sign of tuberculosis, a very common fatal disease up until the middle of last century — than for being fat.)
I know quite a few 400-pound-plus folk (and am married to one who weighed 370 until quite recently), and they all have weight-related problems with their joints, as well as their blood pressure. Of course, exercise would help lower both the BP and the load on their bones and ligaments, but with their joints degenerating, exercise is difficult — which of course means they get fatter, which puts even more of a load of their joints and their circulatory system. (My spouse was lucky enough to start a moderate exercise program and go on meds before he collapsed from a stroke; he can now do thirty minutes a day on the bike, but he’s still so heavy that even with gloves and ergonomic grips, his hands get numb after that point.)
To what purpose does that serve, though, Phoenix, given that weight loss has not been shown to be effective at either improving health or losing weight? Most everyone I know who is around 400lbs have spent most of their lives dieting themselves up to that weight. Hand-ringing over how unhealthy they are has long lost even the appearance of being useful. Given that it always leads to a “solution” which only makes the “problem” worse. Introducing activity is a very good thing. Especially with achievable expectations. But not from the perspective that their weight is unmistakably bad. The fact remains that there is no reason to expect long-term changes to their weight, and it shouldn’t be a part of any solution. All that does is encourage people to become discouraged from healthy and achievable changes because they do not significantly impact their weight. Any fat person can improve their health in ways that will work. Stigmatizing them for their size can have no productive part in that.
An excellent post!
I have been berated on more than one online forum for daring to suggest any of the things you mentioned in the post and backing up my claims with references to the same/like studies. One woman claimed to be a nurse and said she would *never* believe that a fat person could be healthy “no matter how much evidence” I presented – she saw fat people in her hospital and dammit, they were there because they were fat and it was all their fault. It kind of worries me when people who supposedly have scientific training refuse to even *consider the possibility* that fat might not equal certain early death when shown the results of quality studies.
Another board was for crafters, and they had a “dieting support” section on the board. I didn’t read it except once I saw a post entitled “Dieting tips that DO work!” and it was full of the usual fibs like drinking water will reduce your appetite and so on. I replied with a note that I was a proponent of Health At Any Size and didn’t believe dieting was healthy, but that if you were going to try you might as well be familiar with some basic biology, even put in spoiler space (!), and then (gently, not troll-ly) refuted the tips with stuff that is readily available for all to see in any Human Nutrition & Physiology 101 textbook…and man, were people angry. I must have been lying because these weight loss tips came from “leading bariatric clinics” and I was just jealous and angry because I was fat and unsucessful at dieting, and so on. The level of freaking out from people was, well, freaky. It certainly was a lesson in how ingrained is the idea that FAT IS BAD THERE IS NO ALTERNATIVE POSSIBLE both from the medical and moral beliefs held by people.
The amount of time and energy and money spent by (mostly) women on the quest to be thin is such a waste. A friend of mine was “encouraged” to come along to Weight Watchers meetings with a group of coworkers. She said no, but she will instead spend the $30/month or whatever it is on sponsoring a child in a developing country. Blank looks and confusion all around from the coworkers. (OK, I’m getting into what could be dodgy moral comparisons and stuff here, but you get the idea.)
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Has anyone doing these studies accounted for the changes in weight as they relate to women’s health, hormones, pregnancy, menopause, breast cancer?
AS a result of histerectomy, which is frequently performed as a part of therapy of breast cancer, a lot of women will put on weight. My mother put on over 100 pounds in 2 years, and I ahve seen examples of similar range.