Today the Standard had a guest post on ACC (ACC is NZ’s workers compensation scheme -a lthough it covers much more than workers compensation):
The investment losses have been a big part of it but there is also a rising accident rate stemming from our ageing population and climbing obesity rates, which has been foreseen by medical experts for some time. We cannot do much about an aging population really, but obesity is wholly avoidable with smart policy that has some guts behind it.
Why should we focus on obesity? Obese workers have a higher accident rate, take longer to recover, cost more treat and are out of work for a longer period of time. A 2007 Duke University study found that “obese workers filed twice the number of workers’ compensation claims, had seven times higher medical costs from those claims and lost 13 times more days of work from work injury or work illness than did nonobese workers”.
Although they don’t provide a link I’m going to assume the guest poster is quoting from the press release about the study. Here’s a link to the study itself for people who speak science article.
The numbers quoted are absolute numbers, they’re not controlled for anything. In particular, they’re not controlled for occupation. ((There are two other problems with those numbers. First that when it says ‘obese’ and ‘non-obese’ it appears to be comparing people with a BMI of between 18.5-24.9 and a BMI of 40+. In the article obese is defined as a BMI of 30+, so the terms used in the press release are not the same as those in the article, or the common medical use of those terms. I’m not going to dwell on that because I have less than no time for the BMI in the first place.
The other problem is that all the numbers apart from the numbers of claims made appear to be based on guesses at what the numbers might be rather than actual numbers:
Lost workday rates (days per 100 FTEs) were calculated by multiplying these stratum-specific claims rates by their corresponding mean number of lost workdays per claim. Similarly, multiplying the claims rate by the stratum-specific mean costs (including the amount already paid and the amount reserved) allowed calculation of cost rates (dollars per 100 FTEs) separately for medical and indemnity claims costs. Confidence intervals were calculated assuming that the number of events followed a Poisson distribution.
I’m not going to comment any more than that, because I don’t speak science article, but will concentrate on the ‘claims made’ figure when explaining why this research doesn’t prove what the standard thinks it proves.)) I’m sorry to insult my readership by pointing this out, but the correlation between class and body size is pretty well established, as is the correlation between class and work-place accident rates.
Surprise! When the authors control for occupation (although not income, and managers appear to be treated as the same occupation as workers) the numbers look rather different. ((I don’t actually like debunking scientific research about fat, it seems to me to be conceding too much. Even if everything they said about the dangers of fat were true it wouldn’t change my political analysis of fat at all. )) These numbers are expressed in risk ratios, whereby a control group is set at 1, and 2 means something is twice as likely when all the variables that are mentioned have been controlled for (full disclaimer, I could be lying, I don’t understand statistics that well). The risk ratios for number of claims for people who have a BMI of over 25 range from 1.09 to 1.45. To understand how insignificant a risk ratio of that size is here are some of the risk ratios for occupational groups:
Laundry Staff: 7.35
Housekeeper: 6.44
Laboratory Animal Technician: 17.36
Inpatient Nurse: 4.01
The guest posts asks ‘why is ACC costing so much?’ And answers ‘workers’ bodies’. Even though its evidence is a study that demonstrates that the nature of work plays a far bigger role in the numberof workplace accidents than the nature of workers.
I’m a ‘which side are you on’ kind of a girl, and this post makes it very clear which side it’s on. It blames workers and their bodies for workplace accidents. It chooses policing workers bodies, over fighting for workers bodies.
Great post, Maia.
Excellent analysis!
Maia,
I have to point out that this statement you make in your footnote is inaccurate:
The other problem is that all the numbers apart from the numbers of claims made appear to be based on guesses at what the numbers might be rather than actual numbers:
They are not guesses, they are calculations. The authors wanted to report everything in rates (per 100 FTE (full time employees), which is a good way to do it since they wanted to examine the impact of obesity on the work population as a whole. But the employer doesn’t report the lost days or costs per 100 FTEs; they report them on individual claims. And so the authors took the individual claims, categorized them by BMI data and then and then calculated the number of lost days and medical costs per 100 FTE incurred by each BMI category. So they did in fact use actual numbers. They just described it poorly.
Matthew – Thanks for that. Would you mind explaining a little more – they said they were multiplying by the mean – doesn’t that mean they’re calculating based on averages not using actual numbers?
While we’re chewing on possible problems with the data, BMI bothers me. I’m 74 inches tall, and weigh about 200 pounds. I’m physically active, and an amateur athlete, with sufficient useful muscle. To look at me, I’m reasonably slim in build. My cholesterol is within norms. As far as we know, I am essentially healthy. Recently, I took a health assessment questionnaire in connection with my employment. It dinged me for being “overweight”. Said I needed to lose eight pounds.
BMI has been flawed from the start for people at the ends of the scale. It seems to me that the idiot doctor(s) who invented it did not understand that living creatures exist in three dimensions, rather than two. If you multiply height by weight by a constant, you get a two-variable curve which is skewed at the ends. At the very least, you should multiply again by height and adjust the constant accordingly. (I ran across an alternate definition of BMI which did this, but I’ve lost the link.)
And, as a society, we’re making health assessments and compensation decisions on the basis of that mathematically flawed curve.
To bring this right back to the topic at hand, are tall/short people significantly over- or underrepresented in these various occupations? Because that will lead to odd BMI results as well.
Grace
Grace,
The problem basically is laziness by the people doing measurements. Body Mass Index, if it’s meant to measure obesity, actually should be a measure of how much of your body mass is fat, because obesity is a condition of excess body fat. Obviously what is “excess” depends on what your body is supposed to be able to do; what is an “excess” of fat on a man might be the level necessary for a woman to produce the right level of estrogen and menstruate regularly. That’s why those scales that measure body fat ask you whether you’re male or female.
However, it’s more difficult to measure body fat than to measure weight and height (that’s why the body fat scales are much more expensive than regular scales), and especially if you’re trying to assess a large population, it’s much easier just to base it on the relation of height to weight.
Different extremes of height might have an effect, but I’d say the bigger impact is differences in bone size and density. I’m Asian and have small, light bones even for my short stature, so my BMI, when you measure just height and weight, is right in the middle of the normal range. However, my fat level is well above what it should be. If you looked at the fat storing parts of my body (collarbone to knees) I look overweight; if you looked at the non-fat storing parts (collarbone to top of head, shoulders and arms, knees to toes) I look slim. I suppose it’s good for me that decency in public dictates keeping the fat-storing parts covered but allows baring all the rest.
Of course, the evidence that fat measured as PG advocates measuring is especially unhealthy, is also very dubious. And imo fat people would really be helped most, not by clothes covering fat, but by a culture that didn’t say that fat is ugly and shameful.
(Although as Maia points out, whether or not fat is unhealthy should make no difference from a rights perspective.)
Of course, the evidence that fat measured as PG advocates measuring is especially unhealthy, is also very dubious.
What is dubious about the evidence that excess body fat decreases insulin receptors’ ability to process insulin? I’m sincerely interested, as I heard that from my sister who’s in med school, and if the evidence is dubious, that indicates that medical schools are feeding their students bad information. (Or that my sister isn’t learning properly, which is less of a systemic problem but doesn’t bode well for her passing the Boards.)
And imo fat people would really be helped most, not by clothes covering fat, but by a culture that didn’t say that fat is ugly and shameful.
But that’s true of anything that the culture says is ugly (not quite sure about “shameful”). People with asymmetrical and disproportionate features, with moles and warts and severe acne, would be helped more by a culture that says those things aren’t ugly than they would be helped by a culture that’s invented rhinoplasty, electrolysis and Accutane. We’d all be helped more by a culture that says nothing is ugly than by one that offers ways to correct one’s ugliness. However, in a culture where no one is ugly, it’s probably also difficult to assess who is beautiful, and beauty seems to be a big deal in mating.
Perhaps we should have a cultural norm for mating that’s sort of the reverse of that advised by Thomas More in “Utopia”: instead of having the elders choose one’s mate based on overall compatibility, and the people being matched only get to refuse based on seeing each other naked and whether they are OK with how the person looks, we match ourselves through interactions where we never see what the other person looks like and *can’t* refuse a commitment based on appearances.
Yes, but there’s a basic mathematical problem even with the approximation that is BMI. We are cubic creatures, not square ones. Assuming all density equal, weight is an expression of volume. Assuming a body scaled proportionally in all dimensions (which isn’t quite right, but is pretty close), BMI should be proportional to height cubed. Nerd that I am and was, I ran numbers on this back in college, but I don’t still have them.
Let’s see if Google can help me find someone who has done the work for me. Aha!
This one explains the problem I was talking about:
http://mbatoolbox.org/stories/storyReader$33
This one provides a handy applet to compare the two, and also to calculate BMI with an exponent of 2.2, which they claim in the appropriate compromise between zero-G physics and the inverse-square law as it applies to animals in a gravity field:
http://inside.mines.edu/~gmurray/BMIApplet/BMIApplet.html
And this one shows the difference between BMI as calculated on squared height and BMI as calculated on cubed height:
http://www.flickr.com/photos/51072101@N00/95090079/sizes/o/
All that said, I agree that a submersion measurement would be more accurate. However, as you point out, a lot less convenient.
Grace