|Variable||Mean Change||%||Std Deviation||Minimum||Maximum|
|Weight Gained (lbs)||10.4||7.2%||3.8||3.1||15.6|
|Fat Gained (lbs)||5.3||N/A||2.5||0.8||9.3|
|TEE Change (kcal)||+527||+18.6%||+264||+107||+917|
|REE Change (kcal)||+79||+4.8%||+126||-100||+360|
|TEF Change (kcal)||+137||+63%||+83||+29||+256|
|NEAT Change (kcal)||+311||+37%||+276||-172||+696|
The Real Bathroom Scales
In The Biggest Medical Myth of All Time and The Calculus of Calorie Counting, we examined research exploring the futility of low-calorie dieting and exercise as methods of long-term weight loss. In this post, we’ll delve into a few more specifics on how our bodies actually react to alterations in calorie intake. “The lean ‘n hungry type” Besides a flashback to a musical era I’d just as soon forget, the phrase “lean and hungry” has been used in obesity research to describe those naturally thin folks who have difficulty gaining weight, no matter how much they eat—much like Sims’ prisoners in Medical Myth. That such a type exists at one end of the body-fatness spectrum is rarely denied by medical science nowadays, though it’s generally assumed that those folks are some sort of natural super-athletes who are always engaging in sports and exercise activities. As Sims’ research showed, however, that assumption is incorrect; these folks stay thin even if they sit around with a TV remote growing out of their arm. In fact, a 1985 study analyzing data from the National Health and Nutrition Survey (NHANES) examined the relationship between ordinary dietary intake and body weight and showed the distinct lack of positive correlation there. The NHANES gathers information about the diet and exercise habits of the entire U.S. population via a statistical sampling method. The data is collected by experienced interviewers, trained to request information in multiple forms, so that the validity of the responses can be verified. In other words, it’s as reliable as self-reported data can be. The following chart displays results for caloric intake by relative weight class (as a percentage of ideal body weight) for adult men and women. As you can see, it appears that the leannest individuals actually eat the most. Even if you have doubts about self-reported intake, it’s pretty clear that weight is not proportional to consumption; that is, people who are 30, 40, or 50% above normal weight eat nowhere near 30, 40, or 50% more than their lean ‘n hungry counterparts. So how are variations in caloric intake actually dealt with by our bodies? “A calorie is a calorie is a calorie…NOT!” In Calculus, we looked at each of the elements that make up daily energy expenditure, culminating in the equation: Total Energy Expenditure (TEE) = Resting Energy Expenditure (REE) + the Thermic Effect of Food (TEF) + the energy expended in activity, exercise (EE) and non-exercise (NEAT). The response of each of these elements to a situation of extended overnutrition was explored in a 1998 Mayo Clinic study. In this study, sixteen weight-stable, non-obese subjects had 1,000 extra calories added to their daily diet for eight weeks, while simultaneously agreeing not to engage in any exercise outside of normal daily activities (that is, EE=0). Traditional wisdom holds that the human body has a relatively fixed rate of energy expenditure, like a car, so any major change in intake would automatically be converted to added body mass, mostly fat. In this situation, that would be: 1,000 extra calories X 56 days, divided by 3,500 calories per added pound = 16 lbs of added mass. Even if we refine the calculation to allow for 10% of the calories to be used in food processing (TEF), we’re still looking at more than a 14 lb. gain. In theory. In reality, the researchers found two things. One, the average weight gain was considerably less than predicted, and two, the pattern of weight gain varied greatly between individuals and depended largely on changes in NEAT and TEF. The average gain was 10.4 lbs, only half of which was fat (5.26 lbs), with one person gaining less than a single pound of fat. So what happened to all the “missing” calories? Well, that is precisely what these researchers were after. During the run-in period, when subjects’ intake and weight were stable, their energy expenditure variables were measured by the most reliable scientific methods available (doubly-labeled water, indirect calorimetry, etc.). The same was done at the conclusion of the study, and the comparison was remarkable. Total energy intake was increased by 35%, from 2,824 to 3,824 kcal/day, while total energy expenditure increased by just over half that amount, from 2,824 to 3,350 (18.6%), by the end of the eight weeks. If the subjects were not exercising (a fact verified by accelerometer use), how did their daily energy expenditure increase? The measurement processes showed the following: REE increased 4.8% for a total of 79 calories, which is about what we’d expect from the increase in body mass. Calories attributable to TEF increased by an impressive 62%, moving from 218 to 354 calories per day. And the calories burned in Non-Exercise Activity Thermogenesis (NEAT), changed from 913 to 1,224 per day, an increase of 311 kcal, or 37%. Thus, TEE, after eight weeks of eating 1,000 additional calories, was automatically raised by the body to the tune of 527 calories per day, or 53% of the increase in intake—the equivalent of a 4-5 mile walk. To summarize:
“Time in a bottle”
Now there are two points I want to make here. The first is that this study only looked at two time points—baseline and eight weeks. It would have been really nifty if the measurements had been taken weekly to show how the variables changed over time, and it would have been super cool to see what happened during the next eight weeks, but alas, research costs money, and there was no blockbuster drug at the end of this rainbow, so they did what they could. In all likelihood, the change in energy expenditure was a gradual adaptation over the study period, with most of the weight gain coming early and slowly decreasing, as seen in other studies, and if I make my guess, the energy expenditure rate would have continued to increase in the following weeks to the point that all the excess calories were being burned and no more weight was being gained.
My other point is with regard to the NEAT. As the researchers pointed out, despite the inter-subject variability in changes to energy expenditure, the change in NEAT correlated very tightly and negatively with the change in fat gain (R=-.7). That is, subjects whose NEAT increased the most gained the least. Contrast this with what we saw in the Thomas and Miller rat study in Calculus, where forced exercise was met with a concomitant decrease in NEAT. From these data, it can be surmised that NEAT is a primary defense mechanism against exogenous alterations in energy balance. Changes you make to diet and exercise will be countered with adjustments to NEAT—your body’s subconscious drive to fidget, wiggle, whistle, talk, laugh, dance, hug, kiss, and yes, even change the channel.
What we’ve shown here is that the difference in people’s weights has precious little to do with how many cheeseburgers we eat or how many marathons we run, but rather much to do with energy expenditure variables we cannot voluntarily control—TEF and NEAT. All we have proven so far is that when our bodies sense a surfeit or deficit in energy supply, they attempt to balance it with changes to both energy storage and energy use, the relative percentages of which are highly variable between individuals. But what makes some folks more prone to the storage side and others more prone to “use”? We’ll explore that question in my next post, Through Thick and Thin.
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