We really need to improve our educational system.
Your anecdotal experience is insufficient evidence that the research findings I linked to are all wrong.
I went through the trouble of finding those links for a good reason. And it wasn’t to hear your personal testimony.
So you can take your “umm no” somewhere else.
First the premise, as stated in the abstract, is very sloppy, as it compares and contrasts “overweight and obesity” in gay and straight women with “obesity” in males. Let’s stick with the same metric for all shall we?
Best source I can find is this 2013 National Health Interview Survey of 34,557 adults. Obesity rates as per self-reported heights and weights and by self-reported gender and orientation are in table 3. I am looking at the 18 to 64 group but all is similar.
Males: Gay 23.2; Straight 30.7; Bisexual 25.4
Females:Gay 35.9; Straight 28.8; Bisexual 40.4
Note also decent sized standard error bars around the bisexual males and both gay and bisexual female groups of 4 to 6 due to relatively smaller sample sizes.
So in order, least obesity incidence to most: GM<BM<SF<SM<GF<BF.
A bisexual female has the greatest odds of obesity and a gay male the least.
Bisexual females are most likely to state they have had “serious psychological distress in the last 30 days.” (Although too few bisexual males to give a number.) Gay women a distant second. Also least likely to have a usual place to go for medical care with gay women second. Same one-two but with less of a gap for “failed to obtain needed medical care in past year due to cost.” Also bisexual female most likely currently uninsured. Least likely currently uninsured? Gay males.
Gay males OTOH are most likely to exercise regularly, second to straight women to have somewhere to go for medical care, and most often describe their health self-perception as excellent or very good.
So the group wit the least access to health care and the most psychological distress has the most obesity and the group with the best health care access the least.
Of course correlation is not causation - could be other factors cause obesity and the obesity results in other adverse outcomes as much as the other way around.
But let’s at least speculate with some big data in hand. (And yes, not anecdotes.)
No, it’s not a handwave.( I’m not sure if we meaningfully disagree here or if you’re using “handwave” in some non-conventional manner.)
So what? The same is true of my hypotheses and probably hundreds more besides.
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You’re entitled to your hypothesis too.
What my hypothesis has that yours doesn’t is that it simultaneously explains both the higher incidence among lesbians and the lower incidence among gays, while yours only addresses lesbians. But if you like yours better, that’s fine too.
To which I note once again that there’s no a priori reason to assume these rates should be the same.
In terms of the op’s hypothesis - it would predict that straight women (trying to appeal to men) would have much less obesity rates than would straight men (who are not).
But straight men and straight women both have fairly similar obesity rates.
It would predict that gay men and straight women (both trying to appeal to men) would have similar rates but gay men have much lower obesity rates.
The hypothesis is pretty well falsified.
Yet income level alone is not an explanation as on average gay males make less than straight men and gay and bisexual women seem to marginally make more than do straight women.
OTOH gay identified males are historically less likely to be the prime earner for a household including children whereas my impression (no time right now to look for hard data) gay and bisexually identified women are more likely to live in a households with children under their care. Straight women with children are historically more likely partnered with the statistically highest earning demographic: straight males, thus family income versus family expenses are likely best balanced for the gay male DINKs then straight couples and worst for gay/bi females with kids.
As a speculation.
It would predict these things is you insisted that the only factor which influenced obesity is who the person is trying to appeal to. But nothing in the OP suggested this, and I’ve already pointed out that it’s a premise that has no basis.
FWIW, according to this source:
So it seems like at the lower levels of overweight it’s mostly men but as you get heavier and heavier women tend to predominate. (This is also consistent with Lamia’s cite earlier.)
OTOH, there seems to be a lot of conflicting info about this. From this sourcemeasuring overweight and obesity rates for men and women, the percentages are 70.0% and 57.6% respectively (also roughly in line with Lamia’s source).
In any event, as above I think there are too many differences between men and women (both physiological and sociological) to insist that any hypothesis addressing the disparities by sexual orientation also completely account for the gender ratios.
True it does not disprove it as being of any contribution … just as a major one. Any hypothesis also has to explain why bisexual women have the highest obesity rates by a significant margin, including gay women obesity rates.
It is problematic in other ways as well … unattached straight females who are trying to appeal to potential male partners are trying to appeal to what they, as straight females, believe straight males are interested in, whereas unattached gay males who are trying to appeal to potential male partners are trying to appeal to what they, as gay males, believe that other gay males are interested in. They are interested in appealing to different population groups and with different likely insights as to what the respective different groups find important.
(And my apologies for using “then” where “than” should have been used in a previous post.)
On preview … the problem with “overweight” is that it is a very mixed bag including some who are overfat and some very fit individuals who have a healthy body fat percentage and more muscle mass. Once you get into “obese” the fraction that is not actually overfat goes much lower. In any case one if one is to make compare and contrasts one needs to minimally use the same metric for all, not rates of “overweight and obese” for females of each orientation and only “obese” for males of each. I believe “obese” is the better metric as it filters out the fairly large numbers very fit and healthy “overweight” with BMIs of 26 and 27 but if you have numbers for all categories using “overweight and obese” they can be considered as well.
Fotheringay-Phipps: All I’ve done so far is summarize the status of your hypothesis, including the concessions you’ve already made.
If you don’t like this summary, the correct approach is to try to find supporting data, or explanations for the data that doesn’t fit.
No, the conventional manner.
You didn’t give any explanation or supporting data. Yet you continued on as though you had solved the problem.
Good. Well you can use your hypothesis to make a prediction then.
The prediction would be that obesity rates should be significantly higher for straight men than straight women, right?
You need explantions for data that should fit but doesn’t. You don’t need explanations for data that would not be predictd to fit.
I explained why it’s not a “problem” and no explantion or supporting data is necessary.
No, that would not be the prediction. I’ve explained several times why that would not be the prediction. You’ve just ignored this in favor of repeating yourself again and again. Handwaving?
No, it would be the prediction. Now you can explain it away by stating that the differences between males and females swamp the effect you propose … and then you can move to within one gender and predict that within females the rates for obesity should be straight<bisexual<gay … but it isn’t.
So, no reason for suggesting the hypothesis in the first place (not even anecdotal observation), no supporting data, but apparent contradictory data, and any attempt to suggest predictions the hypothesis should entail are handwaved away.
Do you appreciate why people are not yet accepting this as a good explanation of the original phenomenon?
Hint: it’s not personal.
No, it wouldn’t be the prediction.
From a logical standpoint that’s like saying that Bergmann’s Rule predicts that elephants would be smaller than polar bears.
This is a fairly common form of logic and I’m frankly surprised that its attracting so much resistance.
This is a fair point.
That’s going to be hard to explain for any theory that looks at the effects of orientation alone. I imagine you’re going to have to throw another variable into the mix regardless. But orientation could still be a factor.
Um no. Bergmann’s Rule is making a statement about outcomes within broadly distributed taxonomic clades so making predictions about outcomes between clades based on it would just be dumb. This is not the same thing at all.
It was a reasonable thought to have but it does not fit the data. Responding with “I don’t need no stinking supporting data, or falsifiable predictions.” is … well, not impressive.
You see this is why NIH charges rates a bit higher than you do.
Why are straight males more prone to obesity than gay males? Why are bisexual women most prone of all, and dramatically so compared to straights?
There are lots of hypotheses that can be generated, lots that fit the data we already have better than your first guess. Maybe whatever predisposes to sexual orientation (be it genetic, epigenetic, historic, so on) also impacts behaviors or physiology that impacts upon obesity rates. Maybe it has to do with household wealth and/or income insecurity. Maybe several factors interact. So on. Each hypothesis will make predictions which they can and will then go out and collect data to test in a focused manner. Any hypothesis however that does not generate falsifiable predictions is not worth entertaining.
Actually it’s exactly the same thing. You are making a very simple logical error (which makes your condescending tone even less justified than it would be otherwise).
There’s nothing magical about “broadly distributed taxonomic clades”. The reason that rule makes a statement in that form is for the same logical reason that applies here.
If you have a factor that influences a given outcome, then it follows that all else being equal the outcome will tend to vary between groups where this factor is present and groups where it is not present, in the direction determined by the factor. It does not follow that where all else is not equal that the outcome will similarly vary.
This is the reason for limiting Bergmann’s Rule to “broadly distributed taxonomic clades”. It’s an attempt to apply the rule to cases in which all else is (roughly) equal. If you compare bears near the equator to bears in the polar regions, then you’re assuming that the same other factors which influence size in bears are roughly equal for all bears, and the variable is location so that you can apply the rule. If you’re comparing elephants to polar bears, the reason the rule does not apply is because elephants and bears are too dissimilar and there are too many other factors which influence size that vary between the two groups to make a prediction based on location. It’s for this reason that Bergmann’s Rule does not predict that polar bears would be bigger than elephants.
And the same exact logic applies to men and women. The differences in terms of factors which influence obesity, both sociological and physiological, between the two groups are too great to expect that the single factor of mating partner preferences would predict obesity rates, even if that factor is a valid one. As is the case of Bergmann’s Rule - or any number of similar principles - the factor can be valid when applied within a largely homogenous group where that factor is the prime variable and not valid when applied across different groups where many other factors are in play.
[This is all besides for the fact that the comparison between men and women does seem to be weakly consistent with this hypothesis, as above.]
Depends for what purpose. Any hypothesis which does not generate falsifiable predictions is not a good field for further scientific study. But it might just happen to be true.
Of relevance to the theory offered up in the OP, there’s a new study out which says (emphasis added):
“Slender” is an odd word in describing a male and to my ear at least describes a lack of muscle mass as much as it does a lack of fat mass. “Slender” tends to imply not “athletic looking.”
What is notable is that of these heterosexuals (and only heterosexuals studied) both genders pretty equally care about their partner being good-looking and “physically attractive to them.”
So a heterosexual female is less likely to endorse a “slender” man as “good-looking” and “physically attractive to them” than a heterosexual male is to say a “slender” woman is. And odds are that if asked a heterosexual female is more likely to endorse “athletic appearing” man as “good-looking” and “physically attractive” than a heterosexual male is so say an “athletic appearing” woman.
And this informs the hypothesis about differences between male and female gays, straights and bisexuals how?
Having dabbled in the occasional ménage trois, though not in the strict sense of the definition. (The definition is actually a domestic arraignment of 3 having relations) But I digress. Ahem
Pardon if I overlooked if someone else posted this, but women are vary competitive about other women. More so than most men on average, I would venture to say. Women that dabble with women want someone about the same build and so forth as they are. They typically don’t want someone hotter that makes them feel intimidated. It would seem logical that more strictly lesbian women would be average to a few extra pounds, and their partner would be about the same.
But as the moderator pointed out, their is lots of conjecture for this thread.
I wandered into this thread to suggest just this. PCOS makes it really difficult to lose weight and maintain that weight loss. REALLY difficult.
I agree that "slender may not have been the best word to use (though I’m unclear as to whether that was the actual word used in the survey or was just used in the summary).
My premise in the OP is that being overweight is less of a perceived negative in terms of attractiveness to women than it is to men.
I’m not sure if this was intended as a summary of your post or was an independent comment. But in case of the latter, it seems pretty straightforward, as discussed previously in this thread.
Again, the notion is that
[ol]
[li]in aggregate, women perceive being overweight as less of a negagtive in terms of attractiveness than men do.[/li][li]Therefore, the group of people who aim to appeal to women have, all else being equal, less of an incentive to keep weight down than do the group of people who aim to appeal to men.[/li][li]Therefore, one would expect the former group to be, on average, more prone to being overweight than the latter group (again, all else being equal).[/li][li]It would follow that lesbians, who aim to appeal to women, would be expected to be, on average, more prone to being overweight than heterosexual women.[/li][li]Which happens to actually be the case.[/li][/ol]
Men are very picky about a potential mate’s appearance. They want slim and good looking. That goes for men attracted to women or men.
And as I grow older, get bald, a belly, etc. I find that women still are quite interested in me - strange! Seems I could be ugly as heck and they still would like me?
Anyway with that said, if women are not trying to attract men, then they would be free to look any way they please. And I suppose they might welcome not having to keep fit and trim, put on make-up, etc.?