The data indicated that for the AD36 Negative group, the ages were 8-11 yrs (18%), 12-15 yrs (65%), and 15-18 yrs (17%). For the AD36 Positive group, the ages were 8-11 yrs (5%), 12-15 yrs (32%), and 15-18 yrs (63%). This is as we surmised above: more older kids are in the AD36 group. The weight average for the AD36 Negative group was 69 kg (+/- 24 kg SD); for the AD36 Positive group is was 93 kg (+/- 24 kg SD).
Thus, one sure finding is that older kids are heavier: in fact, they were about 24 kg heavier, which translated to about 50 lbs. It is at least good to see that the press release got this figure correct.
Another finding is that older kids are more likely to have been previously infected by AD36, also as we surmised (in two years, you have have plenty of colds).
There is no modeling of the expected distribution of biometric properties of the two populations (AD36-negative and -positive) given the other statistics (age,sex,race) reported. This is extremely surprising to me.
However, it’s not just that older kids (adults, really) weigh more—the size-relative metrics BMI, and waist/height ratio were also higher in the AD36 antibody group. But still, those should be adjusted for age as well; their distribution (and mean) will surely change with age, and definitely will change for the worse with age in the destined-to-be-obese (it takes time to blossom into full adult obesity). The fact that no such adjustment was made means that the study contributes almost no additional evidence, but this could be corrected with a proper analysis. And, supposing the raw data is available, this can happen.
The two populations also have a significant sex difference: the AD36-negative group is 58% male, and the AD36-positive is only 47%. However, it looks like adult men and women have similar recommended BMI and waist/height ratios (actually, women are recommended to have slightly lower) - I don’t know what the actual averages are. Racially, there’s a 13% shift from “non-hispanic white” to “hispanic” in the AD36-positive population. While I don’t know how different those groups are re: AD36-positivity or BMI etc., this should be considered as well. The age mismatch is definitely the most severe problem.
The “discussion” section lists much other work which seems to provide better evidence of a AD36-obesity link (I assume the authors are leaving out any negative results that don’t support their views). For example:
[In] a small substudy of adult twins with discordant AD36-specific antibody status, 13 Twins with antibodies to AD36 were noted to have higher BMI values and greater proportions of body fat then their respective antibody-negative twins.
(evidence of correlation, not causality—would be quite strong evidence if the number of twins and BMI/body fat mismatch were large enough)
infection of nonhuman primates, rodents, and chickens with AD36 increased total body fat independent of energy intake
(causality in animal models, although i would hope for exposure rather than infection as the trigger—perhaps p(infection|exposure) is high enough that it doesn’t matter)
adipose-derived stem/stromal cells … infected with AD36 showed increased differentiation and higher levels of lipid accumulation than noninfected control cells
(causal, but in vitro: doesn’t guarantee net fattening in the context of a human body)
An excellent analysis. I agree that the Gabbert study is seriously flawed. However, the animal experiment model evidence is definitely suggestive in the other direction. But besides the obvious objection that these animals, even the primates, aren’t human, there is also the fact that these were caged animals.
On the other hand, the negative evidence from the U.S. Army study is not very convincing either. Unless things have changed dramatically since my day, obesity is not exactly tolerated there and exercise is not considered optional.
Hmm … having read the study, now, I have to disagree with your earlier remark:
On the other hand, the negative evidence from the U.S. Army study is not very convincing either. Unless things have changed dramatically since my day, obesity is not exactly tolerated there and exercise is not considered optional.
These factors would seem to create the opposite implication: that those found to be obese in the U.S. Army would be disproportionately those who are obese for non-behavioral reasons.
Hmmm. Having read it myself now, I am now very confused. I strongly recommend that everyone participating in this case study read this US military study before making up their mind. PM me (or RobinZ?) with your email address and I will email you a copy.
Elsewhere in this thread, Wei Dai took me to task for suggesting that epistemic rationality was a “solved problem”. He was right. It occurs to me that as I recently tried to slog my way through Pearl, I learned that there was still controversy as to the proper way to handle confounding variables. ERV’s criticisms definitely showed that the
Ad-36 proponents weren’t properly handling the confounding variable of age.
This US military study convinces me that they are not properly handling the confounding variables of sex and race/ethnicity. I’m almost tempted to conclude that all of the human subject evidence of the Ad-36/obesity link is practically worthless for this reason.
But there is another reason for looking at the military study. They find that past the age of 27 or so, the number of Ad-36 positives among their population falls. That suggests that it may be the case that widespread exposure of humans to Ad-36 may be a recent thing. Which is interesting because the worldwide “obesity epidemic” also seems to be a recent thing.
You have the text (pdf) of that study? Could you PM it to me?
I guess I was making the assumption that even Ad-36 positives would be able to combat obesity if sufficiently motivated to exercise. But, having reread the abstract now, I regret my criticism—when I made the criticism I was thinking that they were comparing non-obese individuals of varying BMI.
infection of nonhuman primates, rodents, and chickens with AD36 increased total body fat independent of energy intake
(causality in animal models, although i would hope for exposure rather than infection as the trigger—perhaps p(infection|exposure) is high enough that it doesn’t matter)
This wasn’t clear to me—isn’t infection more specific than exposure? I mean presumably only infection would hae metabolic effects, and exposure doesn’t always result in infection
The causal intervention is really an act of exposure.
If you expose once, or expose until infected, or expose but exclude those not infected, then the difference between infected and not-infected populations is obscured; the reason some individuals were infected (or not) from a single exposure needs to be explained. If it isn’t, then I can say that part of any difference between the infected and not-infected populations is due to whatever factor made some of them fall prey to the infection on one exposure.
Criticisms of the recent Gabbert et al AD36<->obesity paper:
There is no modeling of the expected distribution of biometric properties of the two populations (AD36-negative and -positive) given the other statistics (age,sex,race) reported. This is extremely surprising to me.
However, it’s not just that older kids (adults, really) weigh more—the size-relative metrics BMI, and waist/height ratio were also higher in the AD36 antibody group. But still, those should be adjusted for age as well; their distribution (and mean) will surely change with age, and definitely will change for the worse with age in the destined-to-be-obese (it takes time to blossom into full adult obesity). The fact that no such adjustment was made means that the study contributes almost no additional evidence, but this could be corrected with a proper analysis. And, supposing the raw data is available, this can happen.
The two populations also have a significant sex difference: the AD36-negative group is 58% male, and the AD36-positive is only 47%. However, it looks like adult men and women have similar recommended BMI and waist/height ratios (actually, women are recommended to have slightly lower) - I don’t know what the actual averages are. Racially, there’s a 13% shift from “non-hispanic white” to “hispanic” in the AD36-positive population. While I don’t know how different those groups are re: AD36-positivity or BMI etc., this should be considered as well. The age mismatch is definitely the most severe problem.
The “discussion” section lists much other work which seems to provide better evidence of a AD36-obesity link (I assume the authors are leaving out any negative results that don’t support their views). For example:
(evidence of correlation, not causality—would be quite strong evidence if the number of twins and BMI/body fat mismatch were large enough)
(causality in animal models, although i would hope for exposure rather than infection as the trigger—perhaps p(infection|exposure) is high enough that it doesn’t matter)
(causal, but in vitro: doesn’t guarantee net fattening in the context of a human body)
An excellent analysis. I agree that the Gabbert study is seriously flawed. However, the animal experiment model evidence is definitely suggestive in the other direction. But besides the obvious objection that these animals, even the primates, aren’t human, there is also the fact that these were caged animals.
On the other hand, the negative evidence from the U.S. Army study is not very convincing either. Unless things have changed dramatically since my day, obesity is not exactly tolerated there and exercise is not considered optional.
What U.S. Army study?
This one. Sorry about that.
Hmm … having read the study, now, I have to disagree with your earlier remark:
These factors would seem to create the opposite implication: that those found to be obese in the U.S. Army would be disproportionately those who are obese for non-behavioral reasons.
Hmmm. Having read it myself now, I am now very confused. I strongly recommend that everyone participating in this case study read this US military study before making up their mind. PM me (or RobinZ?) with your email address and I will email you a copy.
Elsewhere in this thread, Wei Dai took me to task for suggesting that epistemic rationality was a “solved problem”. He was right. It occurs to me that as I recently tried to slog my way through Pearl, I learned that there was still controversy as to the proper way to handle confounding variables. ERV’s criticisms definitely showed that the Ad-36 proponents weren’t properly handling the confounding variable of age. This US military study convinces me that they are not properly handling the confounding variables of sex and race/ethnicity. I’m almost tempted to conclude that all of the human subject evidence of the Ad-36/obesity link is practically worthless for this reason.
But there is another reason for looking at the military study. They find that past the age of 27 or so, the number of Ad-36 positives among their population falls. That suggests that it may be the case that widespread exposure of humans to Ad-36 may be a recent thing. Which is interesting because the worldwide “obesity epidemic” also seems to be a recent thing.
You have the text (pdf) of that study? Could you PM it to me?
I guess I was making the assumption that even Ad-36 positives would be able to combat obesity if sufficiently motivated to exercise. But, having reread the abstract now, I regret my criticism—when I made the criticism I was thinking that they were comparing non-obese individuals of varying BMI.
I didn’t think you could PM files—if you want to PM an email address, I can get it for you that way.
Done.
This wasn’t clear to me—isn’t infection more specific than exposure? I mean presumably only infection would hae metabolic effects, and exposure doesn’t always result in infection
The causal intervention is really an act of exposure.
If you expose once, or expose until infected, or expose but exclude those not infected, then the difference between infected and not-infected populations is obscured; the reason some individuals were infected (or not) from a single exposure needs to be explained. If it isn’t, then I can say that part of any difference between the infected and not-infected populations is due to whatever factor made some of them fall prey to the infection on one exposure.
Ah right, I see.