The Calculus of Calories: Quantitative Obesity Research

[@geonerd]

The NIDDK calculator is quite helpful. Thank you. Ya know, for someone at my weight, that evil 3500 calorie-per-pound 'rule' isn't that far off. A ~950 calorie daily deficit sheds 1/4 pound per day. It's almost right, if for the wrong reason!

[@seanf5134]

Fantastic to see this level of presentation :) thank you so much..

[@aconsideredmoment]

Thank you for your outstanding research presented in a straightforward way. It replaces longstanding myths with data-based information that is essential to know and easy to apply to my health regimen. There is so much noise out there. I am glad it led me to search NIH results. I am glad those results led me here and that you shared your work in this medium. All of this seems consistent with the changes I have experienced in different levels of diet and exercise. One question: can you recommend any research or insights related to sleep and metabolism?

[@aconsideredmoment]

In response to your question about possible explanation for why people with higher weight had caloric intake levels that were below the model prediction, I suspect the following. One source of error in subject data collection I have noted that can lead to underestimating calories consumed on a consistent basis is reliance on packaging estimates. For instance, Nutrition Facts list a serving of bread, 1 slice, as 43g. My observation is that the median and mode weight of the bread is higher. The USDA site lists 1 slice of bread as 1 oz. 1 oz = approx. 28g. The average slice of bread weight is significantly higher. It is the same with fruit purchases, restaurant servings created with exact measures to meet target caloric levels on the bench for marketing purposes served at higher levels in restaurants. Part of the explanation in many foods is the requirement that manufacturing targets to meet the declared weight with a bias to overage. The average person is likely not weighing the grams and using package information to calculate the ratio and actual calories consumed based upon weighed grams. Therefore, a person will underestimate his/her caloric intake. The more calories a person is allowed per day, the more error. I think that reliance upon package weights or selection from multiple sources online of calorie levels, with a possible bias to the lower calorie level, might be significant causes of underestimating and underreporting caloric intake. Best of luck. Keep up the great work!

[@light819]

I would be curious to see how the human body deals with alternative sugars since the FDA apparently believes that since they aren't your standard sugar they don't even count as calories to begin with but I feel like with some people's high ingestion of them the body could adapt

[@ProfFeinman]

Very nice talk but I think you made a mathematical error in the fourth equation at 10:27 (just kidding). I understand that I will have to read the papers but what is missing for some of us, is the implication that calories are independent of macronutrient source. I like the car analogy and I have a hybrid and I always keep on the display showing the gas flow and the battery flow but I doubt that the fuels are equally efficient and some of the gas flow is used to charge the battery. By analogy with you reference to hormonal changes that is the non-linearity that many of us are concerned about. In comparisons of diets of different macronutrient composition, you don't need a metabolic chamber because, whatever the error in the food report, the differences in the output variables are so large that you get a good picture of what's going on. I hope this is built into your model.

[@schitaco]

This was awesome. Have you considered pitching a shortened version as a Ted talk?

[@AlwaysAudacity]

Does anyone know if the model is correct for increasing both calories and exercise?

[@psiclops521]

Interesting, that bit about a flex-fuel approach to weight. In the animal feed lot industry there is at least one company that exists for entirely that purpose. They have an algorithm that manipulates the feed formula for whichever assigned species in order to maintain the nutritional value by altering the food source. The point of it is to select a lower-priced component in the feed if the price rises on one component. You get, supposedly, the same nutrition but the price is kept as low as possible.

[@epigeneticnerd4244]

Maybe he’ll get to it, but seems like a major variable he’s not thinking about is a lot of the weight being lost is water. 1 gram of glycogen can carry 3-4 grams of water.

[@rharnevious]

Though he didn't mention that specifically that I recall, I'd think he's got a solid grasp on that

[@elizabethanastaspoulos7790]

Amazing presentation! MORE!!!!! Dr. Hall, do you think the NIH will ever fund a study on reverse dieting? It seems clear here, through your presentation, that it is a very viable hypothesis!

[@Magnus_Loov]

The example @4.40 is wrong. 500*365*2=365 000 kcal. Every kg of fat=7200 kcal (to lose). 365000/7200=50.7 kg, not 100. The calcualtion is right for about a 50 kg man. It would take about four years for a 100 kg man to disappear. But the main point is of course that it is still ridiculous to expect -X amount kCal= -Y amount bodyfat.

[@SuperGurgo]

at biggest looser graph it clearly says that at the and they lost more than 10KG of lean tissue considering that male has on average 30KG female 20KG of bone muscle. that is 40% loose of muscles that hase huge impact on BMR How can he says that they presserved lean body mass

[@zxyatiywariii8]

Thank you, excellent presentation!

[@bartoszbartosz2366]

Great speaker and a great research!

[@growth-memo]

Kevin Hall is absolutely killin' it!

[@dennishall8902]

Kevin Indig a

[@dennishall8902]

Kevin Indig b

[@safardebon9720]

Hall has made a blunder in the main equations - there is no differential equation that considers the effect of lipotoxicity. This is main cause of obesity - too much fat in the diet or too much fat already in the body. And this results in sugar getting into cells - insulin resistance. Perhaps due to this error, Hall is still overweight

[@dans9228]

Great presentation, thank you very much!