How Does Obesity Cost the Workplace 73 Billion Dollars?
I read the headline “Obesity’s Hidden Job Costs - 73 Billion.” I’m a trained researcher; I’m also ginormous and as or more productive than anyone I know so my first thought was “How did they come upon that number?” I looked up a bunch of different articles online to make sure that they were all reporting the same basic thing, and they were.
So I went to the Journal of Occupational and Environmental Medicine and paid $20 for the article, which was titled “The Costs of Obesity in the Workplace.”
Allow me to attempt to elucidate, it won’t be easy because this study is kind of a clusterf&$#. I’ll start with some basics, and include the longer more detailed nerdy explanation (that I love so much) at the end.
The study looked at three factors: Medical Cost, Absenteeism (not showing up to work) and Presenteeism (being at work but being unproductive). According to my spell check, presenteeism isn’t a word but we’re going to go with it for now.
According to the articles that I read online, the study was out of Duke University. That’s true – the lead author is Eric Finkelstein, an associate professor at Duke-National University of Singapore.
Under “acknowledgments” it says “This study was supported by Allergan, Inc.” It lists that as an acknowledgment, and that’s a problem for me because it should be listed as a conflict of interest. Why?
“Supported” here has the meaning of “funded by”.
Allergan is a pharmaceutical company. They produce Botox, Latisse (it will grow your eyelashes and don’t worry, that eye discoloration is probably temporary) and…wait for it…the LapBand. The item used to constrict your stomach as a weight loss surgery option.
Allergan is currently using this study from the good people of Duke Singapore to convince health insurance companies to encourage and pay for lap band surgery because it’s “cheaper than the loss productivity.” Astonishingly (sarcasm meter is a 9 out of 10) according to this study, the cost of obesity per person was more than the cost of lap band procedures. Let me muster up some shock…
Sorry – I’ve got nothing.
The study used two sources:
The 2006 Medical Expenditure Panel Survey where BMI data is self-reported, and the 2008 National Health and Wellness Survey which is a series of self-administered internet-based questions fielded by 63,000 members of an internet based consumer panel. Every piece of information is self-reported and unverified. The $73 billion is an estimated projection based upon statistics that were created by doing computations with statistics and estimates, and statistics of other statistics. There are issues in the collection of data, the control of variables, the use of data (the study authors feel that the words “obesity” and “health problems” are scientifically interchangeable, that fat people’s health problems may be assumed to be caused by fatness, and utilizes BMI which has any number of problems as a statistic in and of itself which I talk about more here), and the conclusions that they drew.
The fact that news agencies reported this information as true without bringing up the limitations and issues is deplorable. Studies are suggesting that obese people already make less than their peers and are turned down for jobs based on prejudices about weight. Now companies may think that they have scientific proof to back up their bias. How many of them are going to pay $20 to read and understand a complicated study?
As always, may I suggest that you DO NOT need to believe everything that you are told is science, and DO NOT need to take this personally or allow it to affect how you feel about yourself, your health, or your productivity in any way.
Here come the details:
Medical Expenses
The calculation of this is statistically complicated because of the data. To speak in the vernacular of the peasantry, the data sucks. Basically they used a two part estimate that created four categories of overweightness (hey, if they can make up words so can I) based on the self reported weight. “Normal weight” were the omitted reference group. They controlled for race, household income, education, insurance coverage, marital status and smoking. They subtracted the average predicted medical expenditures for obese individuals in each category from the average predicted expenditures for those of normal weight. Then they multiplied that estimated number times the number of people in each category and added them up and extrapolated based on the estimate of obese Americans.
Problems:
First of all, notice the number of times that the words estimate, average, and predicted appear in that explanation. If I had more free time I would be doing a word count to give you an exact percentage of the number of words that are used in this study that essentially mean “um, maybe…” because there are many.
They also didn’t control for any genetic health issues, or health issues that aren’t even correlated to weight. They appear to have assumed that any medical problems that obese people had over and above what normal weight people had were due to fatness. They appear to have assumed that normal weight people’s health issues weren’t related to the same things that cause weight problems in overweight and obese people. That’s just embarrassingly bad science.
Absenteeism and Presenteeism
This is my favorite. These were measured based on a question that asked people “During the last seven days, how many hours did you miss from work because of your health problems?” and “During the past seven days, how much did your health problems affect your productivity while you were working?” Participants indicated their level of work impairment via a rating scale ranging from 0 to 10. Each response was assumed to represent a percentage reduction in productive work. Then they annualized and monetized the predictions using age and gender specific wage data from the bureau of labor and statistics.
Problems
Respondents weren’t talking about how much work they missed or productivity they lost due to their weight, they were answering about their health problems. What they can reasonably conclude here is that people with health problems have more absenteeism and presenteeism than do people without health problems. The study’s authors are basically substituting “obesity” (and by that they actually mean high BMI) for “health problems.” You can do that I guess, but you probably shouldn’t do it while calling yourself a scientist.
Then, they computed statistics using statistics, and statistics of statistics. Dude. They used a 7 day sample to calculate a year’s worth of data. Once again, they assumed that any absenteeism or presenteeism over and above what normal weight people had was due to fatness. Except that overweight men reported less presenteeism than normal weight men. That was not reported in any news outlet that I could find, and even in the study itself they gloss over it.
If I had turned this work in for my very first intro level freshman Research Methods class I would definitely have failed the assignment and possibly been asked to leave the program because of specific incompetence and general stupidity.
If you are obese there is just no proof in this study that you cost your workplace a dime. You don’t have to feel bad about yourself – you are fine. Feel embarrassed for the scientists who put their name on this. I hope that they are the laughing stock of Singapore.
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great post… thanks… do you know if the study that alergin funded has anything to do with the cdc cost of obesity calculator? http://www.cdc.gov/leanworks/costcalculator/index.html
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Ummm, yeah, what you said, dwf. When I worked at Young America, I was OMGDEATHFATZ, just like I am now. I missed less work than most of my thinner peers, did more work than most of my thinner peers, worked more overtime than most of my thinner peers, paid just as much for my health insurance as my thinner peers, and used it less than they did (I didn’t use it all because I couldn’t afford the co-pays and deductibles).
From what I’ve seen with my husband, who is classified as “obese” by the BMI, the same is true of him. The only work he missed was for a knee replacement (bone on bone, 20 years of walking on steel decks in the Navy can do that to ya), and when he had pneumonia (and I’m sure being fat had a lot to do with him getting pneumonia…..not). He works harder than his younger, thinner co-workers, misses less time from work, and does more overtime than they do.
I have a feeling this is probably true for a lot of fat people, simply because we have to do all these things in order to have/keep jobs because of the stigma/phobia against us. And studies like this, which ignore the facts and twist them to portray their agenda, just make it harder for us to get and keep those jobs we need in order to have some kind of decent life.
This is a really helpful analysis. Thank you.
You know who misses a shitload of work? Parents. Especially parents with kids in daycare, which is most parents. Those little germ factories are completely destroying our productivity! But you’ll never read a study looking at this. Why? Because there’s no solution!
I didn’t realize this study was funded by Allergan. That’s an eye opener. I’m so glad you analyzed this. Could I get a copy of it? I’d love to comb through and see what it’s made of too. I’ve seen this stat cited so much and I knew it was bullshit and everything you’ve said confirms it.
Peace,
Shannon
Great post.
In my 20+ years of being a working, contributing fat member to society, I have not missed a lot of time to due to illness and when I was out sick, it was for the normal ailments that affect people of all weights: stomach viruses, the flu, severe colds, sinus infections. But I’m guessing that Allergen believes that being deathfat increases the risk of getting common illnesses so they’ll sell more lap bands. They’re getting more and more desperate every day.
Hmm… I haven’t read the study, but from your description my problems with it are slightly different than yours.
1.) I think it is okay to base calculation on “estimates” as far as they also include information about how good your estimates are. (For example, how well does self-reported weight agree with directly measured weight and do the two agree more or less depending on a person’s weight? I can very well imagine that, on average, fat people tend to underreport their weight more than thin people - not because we are all deluded little liars, but because underreporting/ underestimating your weight in a society that discriminates against fat people might actually be self-protective and functional in terms of psychological health.) This becomes even more important for self-reported loss of productivity due to health. (It is okay to ask for health as compared to weight in my opinion, because you actually want to compare if fat people have higher health care costs/ lower productivity than ex-fat people who had lap-band surgery.) Most people THINK they become more productive during a diet, too, and they might feel like they do, but there is data comparing actual performance on several cognitive tasks that shows people who restrict calories perform worse. So they should have compared self-reported productivity/ absenteeism with directly measured productivity/ absenteeism for a sub-sample of participants to see how valid the self-reported data actually is.
2.) They also should have included confidence intervals as well as data on how much 73 billion actually is when compared to the total gross national income of the US (I suppose that their calculations are for the US only). 73 billion sounds like an awful lot - but that number is pretty meaningless without context.
2.) You do not mention how they calculated the costs of lap band surgery. This is actually an important point because I would bet that they underestimated the costs. Did they compare the health care costs of fat people to people that had been equally fat before but underwent lap band surgery or did they compare it to people who have always been thin? Did they factor in the additional medical costs of treating post-lap band patients as compared to people who have always been thin/ at the weight that the respective patient ended up at after surgery?
3.) In this context I think that it is actually questionably to control for smoking, at least not by simply using smoking as a covariate in the analysis which is what is usually done to “control for a variable”. Smoking and weight are not unrelated and some people actually smoke to keep their weight down. So by factoring out smoking one might actually end up with overestimating the productivity/ underestimating health care costs of thin people. Related to this, they absolutely need to control for age - something that according to your summary they apparently have not done. Considering that older people tend to be fatter this is actually quite an oversight on their part.
4.) There is also the question of mental health. Being fat in a fatphobic society might very well lead to worse mental health in many people, and that might have an influence on productivity/ health care costs. But it would be highly irresponsible to suggest that any lost productivity due to mental health problems would be the result of people’s fat tissue rather than due to fat people experiencing discrimination. I cannot really come up with an easy way to control for that in this study - mental health and weight are intertwined in some complicated ways that include the effect of some antidepressants on weight, the mental toll of some diseases that cause weight gain but that can have all kinds of other unpleasant effects, the mental toll of weight-related discrimination, as well as the possible effect that health problems that might be partially caused by being fat on mental health. I can very well imagine that this last connection between fat and mental health does exist – but it is hardly the only way that mental health and weight might influence each other and in my eyes it is probably a rather minor one compared to the other three.
There are additional points – among them the fact that this study did not have an experimental design and therefore it cannot say anything about causation, only about correlation. Even if they had done a true experimental study were fat people were assigned to either a lap-band surgery condition or a control condition without a weight loss intervention they would have to follow up their participants for many years to get meaningful results. Plus, they still would not be able to rule out that better outcomes in the lap-band surgery condition would not have been due to reduced levels of discrimination. (I actually doubt that they would find an overall more positive outcome for lap-band patients after 10 or 20 years, but even if they would…)
Wow… just wow.
Overwhelmed by the information contained and intrigued by the questions raised. You’ve given us much to think about, sannanina. I think the takeaway is that Allergan and the study authors weren’t looking for objective, reliable data to compare the productivity of fat vs. thin. They looked for, and got, an eye-popping number to illustrate the urgency of Allergan’s “life-saving” lap bands as medically necessary and worthy of insurance coverage.
I would love to see a more rigorous study on productivity, just out of curiosity, but it’s not going to happen. They have their $73 billion to startle corporate interests and that is all that matters in the end. Sad, but true.
Thank you so much for throwing in such thought-provoking questions.
Peace,
Shannon