Pay No Attention To The Calories Behind The Curtain

Obesity is a touchy issue for many, as a recent twitter debacle demonstrated. However, there is little denying that the average body composition in the US has been changing in the past few decades: this helpful data and interactive map from the CDC shows the average BMI increasing substantially from year to year. In 1985, there was no state in which the percentage of residents with a BMI over 30 exceeded 14%; by 2010, there was no state for which that percentage was below 20%, and several for which it was over 30%. One can, of course, have debates over whether BMI is a good measure of obesity or health; at 6’1″ and 190 pounds, my BMI is approximately 25, nudging me ever so-slightly into the “overweight” category, though I am by no stretch of the imagination fat or unhealty. Nevertheless, these increases in BMI are indicative of something; unless that something is people putting on substantially more muscle relative to their height in recent decades – a doubtful proposition – the clear explanation is that people have been getting fatter.

Poorly-Marketed: The Self-Esteem-Destroying Scale

This steep rise in body mass in the recent years requires an explanation, and some explanations are more plausible than others. Trying to nominate genetic factors isn’t terribly helpful for a few reasons: first, we’re talking about drastic changes over the span of about a generation, which typically isn’t enough time for much appreciable genetic change, barring very extreme selection pressures. Second, saying that some trait or behavior has a “genetic component” is all but meaningless, since all traits are products of genetic and environmental interactions. Saying a trait has a genetic component is like saying that the area of a rectangle is related to its width; true, but unhelpful. Even if genetics were helpful as an explanation, however, referencing genetic factors would only help explain the increased weight in younger individuals, as the genetics of already-existing people haven’t been changing substantially over the period of BMI growth. You would need to reference some existing genetic susceptibility to some new environmental change.

Other voices have suggested that the causes of obesity are complex, unable to be expressed by a simple “calories-in/calories-out” formula.  This idea is a bit more pernicious, as the former half of that sentence is true, but the latter half does not follow from it. Like the point about genetic components, this explanation also suffers from the idea that it’s particularly unlikely the formula for determining weight gain or loss has become substantially more complicated in the span of a single generation. There is little doubt that the calories-in/calories-out formula is a complicated one, with many psychological and biological factors playing various roles, but its logic is undeniable: you cannot put on weight without an excess of incoming energy (or a backpack); that’s basic physics. No matter how many factors affect this caloric formula, they must ultimately have their effect through a modification of how many calories come in and go out. Thus, if you are capable of monitoring and restricting the number of calories you take in, you ought to have a fail-proof method of weight management (albeit a less-than-ideal one in terms of the pleasure people derive from eating).

For some people, however, this method seems flawed: they will report restricted-calorie diets, but they don’t lose weight. In fact, some might even end up gaining. The fail-proof methods fails. This means either something is wrong with physics, or there’s something wrong with the reports. A natural starting point for examining why people have difficulty managing their weight, even when they report calorically-restrictive diets, then, might be to examine whether people are accurately monitoring and reporting their intakes and outputs. After all, people do, occasionally, make incorrect self-reports. Towards this end, Lichtman et al (1992) recruited a sample of 10 diet-resistant individuals (those who reported eating under 1200 calories a day for some time and did not lose weight) and 80 control participants (all had BMIs of 27 of higher). The 10 subjects in the first group and 6 from the second were evaluated for reported intake, physical activity, body composition, and energy expenditure over two weeks. Metabolic rate was also measured for all the subjects in the diet-resistant group and for 75 of the controls.

Predicting the winner between physics and human estimation shouldn’t be hard.

First, we could consider the data from the metabolic rate: the daily estimated metabolic rate relative to fat-free body mass did not differ between the groups, and deviations of more than 10% from the group’s mean metabolic rate were rare. While there was clearly variation there, it wasn’t systematically favoring either group. Further, the total energy expenditure by fat-free body mass did not differ between the two groups either. When it came to losing weight, the diet-resistant individuals did not seem to be experiencing problems because they used more or less energy. So what about intake? Well, the diet-resistant individuals reported taking in an average of 1028 calories a day. This is somewhat odd, on account of them actually taking in around 2081 calories a day. The control group weren’t exactly accurate either, reporting 1694 calories in a day when they actually took in 2386. In terms of percentages, however, these differences are stark: the diet-resistant sample’s underestimates were about 150% as large as the controls.

In terms of estimates of energy expenditure, the picture was no brighter: diet-resistant individuals reported expending 1022 calories through physical activity each day, on average, when they actually exerted 771; the control group though the expended 1006, when they actually exerted 877. This means the diet-resistant sample were overestimating by almost twice as much as the controls. Despite this, those in the diet-resistant group also held more strongly to the belief that their obesity was caused by genetic and metabolic factors, and not their overeating, relative to controls. Now it’s likely that these subjects aren’t lying; they’re just not accurate in their estimates, though they earnestly believe them. Indeed, Lichtman et al (1992) reported that many of the subjects were distressed when they were presented with these results. I can only imagine what it must feel like to report having tried dieting 20 times or more only to be confronted with the knowledge that you likely weren’t doing so effectively. It sounds upsetting.

Now while that’s all well and good, one might object to these results on the basis of sample size: a sample size of about 10 per group clearly leaves a lot to be desired. Accordingly, a brief consideration of a new report examining people’s reported intakes is in order. Archer, Hand, and Blair (2013) examined people’s self-reports of intake relative to their estimated output across 40 years of  U.S. nutritional data. The authors were examining what percentage of people were reporting biologically-implausible caloric intakes. As they put it:

“it is highly unlikely that any normal, healthy free-living person could habitually exist at a PAL [i.e., TEE/BMR] of less than 1.35’”

Despite that minor complication of not being able to perpetually exist past a certain intake/output ratio, people of all BMIs appeared to be offering unrealistic estimates of their caloric intake; in fact, the majority of subjects reported values that were biologically-implausible, but the problem got worse as BMI increased. Normal-weight BMI women, for instance, offered up biologically-plausible values around 32-50% of the time; obese women reported plausible values around 12 to 31% of the time. In terms of calories, it was estimated that obese men and women tended to underreport by about 700 to 850 calories, on average (which is comparable to the estimates obtained from the previous study), whereas the overall sample underestimated around 280-360. People just seemed fairly inaccurate as estimating their intake all around.

“I’d estimate there are about 30 jellybeans in the picture…”

Now it’s not particularly odd that people underestimate how many calories they eat in general; I’d imagine there was never much selective pressure for great accuracy in calorie-counting over human evolutionary history. What might need more of an explanation is why obese individuals, especially those who reported resistance to dieting, tended to underreport substantially more than non-obese ones. Were I to offer my speculation on the matter, it would have something to do with (likely non-conscious) attempts to avoid the negative social consequences associated with obesity (obese people probably aren’t lying; just not perceiving their world accurately in this respect). Regardless of whether one feels those social consequences associated with obesity are deserved or not, they do exist, and one method of reducing consequences of that nature is to nominate alternative casual agents for the situation, especially ones – like genetics – that many people feel you can’t do much about, even if you tried. As one becomes more obese, then, they might face increased negative social pressures of that nature, resulting in their being more liable to learn, and subsequently reference, the socially-acceptable responses and behaviors (i.e. “it’s due to my genetics”, or, “I only ate 1000 calories today”; a speculation echoed by Archer, Hand, and Blair (2013)). Such an explanation is at least biologically-plausible, unlike most people’s estimates of their diets.

References: Archer, E., Hand, G., & Blair, S. (2013). Validity of U.S. national surveillance: National health and nutrition examination survey caloric energy intake data, 1971-2010. PLoS ONE, 8, e76632. doi:10.1371/journal.pone.0076632.

Lichtman et al. (1992). Discrepancy between self-reported and actual caloric intake and exercise in obese subjects. The New England Journal of Medicine, 327, 1893-1898.


Comments are closed.