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(Harvard University)   Harvard doctors are spoiling everyone's fun and challenging a recent study linking being overweight to lower mortality. Damn those Harvard intellectual snobs and their "science"   (news.harvard.edu) divider line 28
    More: Followup, Harvard, Katharine Flegal, women's health, coronary heart disease, overweight, preventive medicines, intellectuals, Faculty of Medicine  
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1198 clicks; posted to Geek » on 28 Feb 2013 at 10:19 AM (1 year ago)   |  Favorite    |   share:  Share on Twitter share via Email Share on Facebook   more»



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2013-02-28 07:15:57 AM
That's not actually the outcome of the study, it's that dying can make you lose weight. Try to read the article next time,  Subs.
 
2013-02-28 07:47:14 AM
The studies that Flegal did use included many samples of people who were chronically ill, current smokers and elderly

Before you die from age or a wasting disease you've lost a lot of weight.
 
2013-02-28 07:53:45 AM
I don't make fun of fat people because it's a health problem. Health problems are serious, and that would be cruel. I make fun of fat people because they're ugly.
 
2013-02-28 10:25:20 AM
I can confirm this since i'm dead and skinny.
 
2013-02-28 10:33:59 AM
Great - I'm already regretting the salad I'm going to have for lunch.
Who wants to go out for hamburgers?
 
2013-02-28 10:41:24 AM
Actually the people at Harvard discarded empirical evidence and then simply talked with each other and decided on what is truth.
 
2013-02-28 10:44:54 AM
Also, people who change their diet and start losing weight have a good chance for a heart attack because of all the stuff floating loose once you get healthy.
 
2013-02-28 11:19:08 AM
You know what undermines the credibility of science for me?  When someone comes up with an unpopular result, there is a knee-jerk reaction by the scientific establishment to bury it.  And I'm not talking about creation science, global warming denial, or string theory.

The community of science should do a better job keeping fringe theories at arms length rather than to bury them in the sand.

Eventually science will come around to accept unpopular theories that are true, but it'd be really nice if it didn't take a generation of biased old farts to die out before it changed.  It would have been nice if endosymbiotic theory had been properly embraced in the 60s rather than the 90s.
 
2013-02-28 11:42:52 AM

Pochas: Actually the people at Harvard discarded empirical evidence and then simply talked with each other and decided on what is truth.


Actually, no. They found evidence of selection bias in the meta-analytical methods of the original article and suggested that the bias affected the conclusions of the original paper. It was the original article that discarded empirical evidence.
 
2013-02-28 11:44:23 AM
3.bp.blogspot.com

Reasons Johnny Rebel Would Lose A Second Civil War, #1: CHUNKAYYY!!
 
2013-02-28 12:05:00 PM
The confusion and contradictory conclusions may be attributed to BMI being a bullshiat measure of anything.
 
2013-02-28 12:39:37 PM

insano: Pochas: Actually the people at Harvard discarded empirical evidence and then simply talked with each other and decided on what is truth.

Actually, no. They found evidence of selection bias in the meta-analytical methods of the original article and suggested that the bias affected the conclusions of the original paper. It was the original article that discarded empirical evidence.


Saying "hey some of these people were sick" is not evidence of selection bias.  Where are their statistics to back that claim up?  They didn't give any.
 
2013-02-28 12:55:01 PM

Arthen: The confusion and contradictory conclusions may be attributed to BMI being a bullshiat measure of anything.


Yeah, totally...except for the whole part about BMI correlating strongly with a number of serious conditions.
 
2013-02-28 01:06:22 PM
So a panel of experts (or self-proclaimed experts?) disagrees with a peer-reviewed article in one of the most respected journals in the medical world.  Where were these experts during the peer-review process?  Are they attacking the review process and the JAMA, or just a conclusion they find inconvenient?

/Scientific rigor is important, but it cuts both ways!
 
2013-02-28 01:34:36 PM

Pochas: insano: Pochas: Actually the people at Harvard discarded empirical evidence and then simply talked with each other and decided on what is truth.

Actually, no. They found evidence of selection bias in the meta-analytical methods of the original article and suggested that the bias affected the conclusions of the original paper. It was the original article that discarded empirical evidence.

Saying "hey some of these people were sick" is not evidence of selection bias.  Where are their statistics to back that claim up?  They didn't give any.


Yes they did. They went so far as to redo the analysis including those persons excluded from the original and found an opposite effect. Hence there is a bias in the original estimate, because the people included in the study were somehow different than those excluded from the analysis. You can not just exclude 6 million people from an analysis for no reason. It's especially suspect when you exclude approximately 70% of eligible individuals from analysis.

FTFA:  The selection criteria that Flegal used for her meta-analysis ruled out high-quality studies of 6 million people (more than twice as many as were represented in her analysis), said Hu. These studies, in aggregate, show that the highest survival rates are in normal weight people, not the overweight, Hu said.
 
2013-02-28 01:40:20 PM

Mr. Titanium: So a panel of experts (or self-proclaimed experts?) disagrees with a peer-reviewed article in one of the most respected journals in the medical world.  Where were these experts during the peer-review process?  Are they attacking the review process and the JAMA, or just a conclusion they find inconvenient?

/Scientific rigor is important, but it cuts both ways!


Journals can be wrong quite often. Case in point: the article that started the whole 'vaccines cause autism' theory was published in the Lancet, which is an equally esteemed journal. That's what retractions, corrections, letters to the editor are for. The peer-review process doesn't end when the article is published in a journal.
 
2013-02-28 02:14:04 PM

insano: Pochas: insano: Pochas: Actually the people at Harvard discarded empirical evidence and then simply talked with each other and decided on what is truth.

Actually, no. They found evidence of selection bias in the meta-analytical methods of the original article and suggested that the bias affected the conclusions of the original paper. It was the original article that discarded empirical evidence.

Saying "hey some of these people were sick" is not evidence of selection bias.  Where are their statistics to back that claim up?  They didn't give any.

Yes they did. They went so far as to redo the analysis including those persons excluded from the original and found an opposite effect. Hence there is a bias in the original estimate, because the people included in the study were somehow different than those excluded from the analysis. You can not just exclude 6 million people from an analysis for no reason. It's especially suspect when you exclude approximately 70% of eligible individuals from analysis.

FTFA:  The selection criteria that Flegal used for her meta-analysis ruled out high-quality studies of 6 million people (more than twice as many as were represented in her analysis), said Hu. These studies, in aggregate, show that the highest survival rates are in normal weight people, not the overweight, Hu said.



Hey guys, let's do a study on weight vs mortality rate.   But to avoid selection bias, let's artificially make sure that all the thin people we include in the study are healthy.  Are you listening to yourself?
 
2013-02-28 02:19:16 PM

Pochas: insano: Pochas: insano: Pochas: Actually the people at Harvard discarded empirical evidence and then simply talked with each other and decided on what is truth.

Actually, no. They found evidence of selection bias in the meta-analytical methods of the original article and suggested that the bias affected the conclusions of the original paper. It was the original article that discarded empirical evidence.

Saying "hey some of these people were sick" is not evidence of selection bias.  Where are their statistics to back that claim up?  They didn't give any.

Yes they did. They went so far as to redo the analysis including those persons excluded from the original and found an opposite effect. Hence there is a bias in the original estimate, because the people included in the study were somehow different than those excluded from the analysis. You can not just exclude 6 million people from an analysis for no reason. It's especially suspect when you exclude approximately 70% of eligible individuals from analysis.

FTFA:  The selection criteria that Flegal used for her meta-analysis ruled out high-quality studies of 6 million people (more than twice as many as were represented in her analysis), said Hu. These studies, in aggregate, show that the highest survival rates are in normal weight people, not the overweight, Hu said.


Hey guys, let's do a study on weight vs mortality rate.   But to avoid selection bias, let's artificially make sure that all the thin people we include in the study are healthy.  Are you listening to yourself?


You sound fat.
 
2013-02-28 02:29:34 PM

Pochas: insano: Pochas: insano: Pochas: Actually the people at Harvard discarded empirical evidence and then simply talked with each other and decided on what is truth.

Actually, no. They found evidence of selection bias in the meta-analytical methods of the original article and suggested that the bias affected the conclusions of the original paper. It was the original article that discarded empirical evidence.

Saying "hey some of these people were sick" is not evidence of selection bias.  Where are their statistics to back that claim up?  They didn't give any.

Yes they did. They went so far as to redo the analysis including those persons excluded from the original and found an opposite effect. Hence there is a bias in the original estimate, because the people included in the study were somehow different than those excluded from the analysis. You can not just exclude 6 million people from an analysis for no reason. It's especially suspect when you exclude approximately 70% of eligible individuals from analysis.

FTFA:  The selection criteria that Flegal used for her meta-analysis ruled out high-quality studies of 6 million people (more than twice as many as were represented in her analysis), said Hu. These studies, in aggregate, show that the highest survival rates are in normal weight people, not the overweight, Hu said.


Hey guys, let's do a study on weight vs mortality rate.   But to avoid selection bias, let's artificially make sure that all the thin people we include in the study are healthy.  Are you listening to yourself?


That's funny because that's not at all what I said and because the original study did that exact same thing in the other direction. They included a disproportionately number of sicker, thin people and excluded millions of others from methodologically sound studies. It's ok if you are overweight, but that's no reason to defend bad methodology. Then you're just engaging in wishful thinking.
 
2013-02-28 02:39:27 PM
Hey guys, let's do a study on weight vs mortality rate. But to avoid selection bias, let's artificially make sure that all the thin people we include in the study are healthy. Are you listening to yourself?

You're not making any sense.  FTFA:

The studies that Flegal did use included many samples of people who were chronically ill, current smokers and elderly, according to Hu. These factors are associated with weight loss and increased mortality.  In other words, people are not dying because they are slim, he said. They are slim because they are dying-of cancer or old age, for example. By doing a meta-analysis of studies that did not properly control for this bias, Flegal amplified the error in the original studies.

They aren't "artificially" making sure they're only looking at healthy people.  They're saying that when you compare apples to apples (fat smokers vs. thin smokers, etc.), the effect of being fat is a net negative across the board.  If you see a thin person with terminal cancer, they aren't dying because they're thin.

The original meta-analysis did not properly do these controls, so its results are in question.

Also, it's not like this is the first study ever on this topic.  It got covered in the popular press precisely because it concluded something that was at odds with many comparable studies.  Extraordinary claims require extraordinary evidence, and this extraordinary claim looks like it is failing to withstand scrutiny.

Finally, the media oversimplified what the first study concluded.  If you just caught a bit of this, you might think "fat is good".  What they actually wrote was "Relative to normal weight, both obesity (all grades) and grades 2 and 3 obesity were associated with significantly higher all-cause mortality. Grade 1 obesity overall was not associated with higher mortality, and overweight was associated with significantly lower all-cause mortality."  This effect is small, also, and the strength varies between measured BMI and self-reported BMI, so there may be multiple biases in play.
 
2013-02-28 02:45:50 PM

insano: Pochas: insano: Pochas: insano: Pochas: Actually the people at Harvard discarded empirical evidence and then simply talked with each other and decided on what is truth.

Actually, no. They found evidence of selection bias in the meta-analytical methods of the original article and suggested that the bias affected the conclusions of the original paper. It was the original article that discarded empirical evidence.

Saying "hey some of these people were sick" is not evidence of selection bias.  Where are their statistics to back that claim up?  They didn't give any.

Yes they did. They went so far as to redo the analysis including those persons excluded from the original and found an opposite effect. Hence there is a bias in the original estimate, because the people included in the study were somehow different than those excluded from the analysis. You can not just exclude 6 million people from an analysis for no reason. It's especially suspect when you exclude approximately 70% of eligible individuals from analysis.

FTFA:  The selection criteria that Flegal used for her meta-analysis ruled out high-quality studies of 6 million people (more than twice as many as were represented in her analysis), said Hu. These studies, in aggregate, show that the highest survival rates are in normal weight people, not the overweight, Hu said.


Hey guys, let's do a study on weight vs mortality rate.   But to avoid selection bias, let's artificially make sure that all the thin people we include in the study are healthy.  Are you listening to yourself?

That's funny because that's not at all what I said and because the original study did that exact same thing in the other direction. They included a disproportionately number of sicker, thin people and excluded millions of others from methodologically sound studies. It's ok if you are overweight, but that's no reason to defend bad methodology. Then you're just engaging in wishful thinking.


My BMI is in the normal range I am quite fit.
 
2013-02-28 03:14:32 PM

Mr. Titanium: So a panel of experts (or self-proclaimed experts?) disagrees with a peer-reviewed article in one of the most respected journals in the medical world.  Where were these experts during the peer-review process?


Peer review is designed to prevent scientific papers from claiming, "People are fat, therefore aliens".  It's not to rigorously cross-check every result, and certainly not to assert truth.  There should be a fallacy called "Reductio ad Peer Review".

Not that it matters: metastudies are basically "choose your own result" no matter who's doing it.
 
2013-02-28 03:35:34 PM

Arthen: The confusion and contradictory conclusions may be attributed to BMI being a bullshiat measure of anything.


It's a good standardization for a given level of activity.

The problem with large-scale studies have the issue of having to decide what the "typical" level of activity of an entire region or nation is, though.  If you assume everyone is a professional boxer or powerlifter, you're going to have different BMI norms than assuming everyone works from home and the most exercise they get is walking 15 yards to the mailbox every three days.

I think the usual assumption of most studies is "white-collar work", which seems all right as a baseline (plenty of walking, but little lifting) but obviously skews the outcomes of regions with higher proportions of blue-collar work (where a somewhat increased BMI is typical of healthy people).
 
2013-02-28 10:38:44 PM
From the article: Flegal responded in an email to the criticisms by saying that she stands by her findings, which she noted had withstood review by the CDC, the National Institutes of Health and the editors and four of five reviewers atJAMA.

Big business in convincing people that death and chronic disease await them if they are overweight (not obese, or morbidly so).  The diet industry, pharmaceutical companies, gym and equipment manufactures, publishing, media, fashion industry, etc. all prey on people that are otherwise healthy, but don't fit the ideal.
 
2013-03-01 05:16:01 AM

Otto_E_Rodika: From the article: Flegal responded in an email to the criticisms by saying that she stands by her findings, which she noted had withstood review by the CDC, the National Institutes of Health and the editors and four of five reviewers atJAMA.

Big business in convincing people that death and chronic disease await them if they are overweight (not obese, or morbidly so).  The diet industry, pharmaceutical companies, gym and equipment manufactures, publishing, media, fashion industry, etc. all prey on people that are otherwise healthy, but don't fit the ideal.


Have fun with your heart attack, fatty.
 
2013-03-01 05:31:50 AM
Subby sounds fat.
 
2013-03-01 05:57:16 PM
A fat active person is more healthy than a skinny person that is in-active

It's not the obese lifestyle that kills, it's the sedentary.

/DNRTFA
 
2013-03-02 02:59:11 PM
What's the IRS science on doctors and cash and trip contributions from food and drug companies?
 
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