Calories in vs Calories Out, It’s That Simple (or is it?)
If you have ever struggled to lose or gain weight, I guarantee you have at some point heard the advice:
“You just need to eat more/less than you burn”
The person that typically says this kind of thing most likely also holds the belief that being overweight or having obesity is a result of pure laziness or a lack of morals. At the surface level, this advice is correct. However, it is correct in the same way that going to a football game and telling the head coach of your team “Hey pal, you just gotta score more points than the other team and you’ll win” is correct. Correct, but very unhelpful and lacks any understanding on what contributes to the scoring of points.
The problem with this “advice” in nutrition is that it assumes a few things:
“Calories out” is a completely static number that can be easily calculated to 100% accuracy.
“Calories in” can be measured by anyone to 100% accuracy with absolutely no error.
Humans are supercomputers who have absolute control over both sides of this equation, and every single human is on an equal playing field in their control over either side.
With this article, I aim to explain why these assumptions are flawed and why telling people to “eat less and move more” has surprisingly not ended the obesity epidemic. I will breakdown some of the nuances underlying each side of the equation, and hopefully provide useful advice along the way. As with most things, the outcome of things in our life are made up of things we can control and things we cannot. This article will deal with the things that fall in the grey area between those two.
Calories in
How much you eat and drink during a day as measured in calories seems like it should be pretty straightforward, but there are several factors that influence this. I am going to continue the football analogy as much as I can here, so in the following section we can think of our efforts to control/manage calories in as the offense, and the factors we discuss will be the defense. Calories in has a defensive squad made up of four star players we need to worry about:
Hunger
Willpower
Genetics
Measurement of intake
Hunger
Hunger can be likened to the locker room atmosphere for our team, even a great team can be severely dysfunctional if tensions in the locker room are high. Likewise, there are things that affect our hunger that can in turn affect our ability to consume an appropriate amount of calories.
Sleep is one of those factors that can influence our ability to regulate hunger, and match caloric intake to expenditure. Getting inadequate sleep has consistently been found to increase subjective feelings of hunger, increase ad libitum food intake, and decrease insulin sensitivity (1). There are certainly things that we can do to improve our sleep quality such as improving sleep hygiene, minimizing stimulant use, incorporating a bedtime routine, having consistent sleep-wake cycles, etc. However, there are plenty of circumstances where getting optimal sleep is simply not possible. No bedtime routine is going to keep your toddler asleep during their 18-month sleep regression (I’m not bitter I swear). Likewise, there are several medical conditions and medications that can impair sleep quality and quantity.
Stress is another key factor that influences both perceived hunger and food choices. Research subjects who are placed in stressful situations are more likely to choose foods that are more calorically dense when compared to non-stressed counterparts (2).
Willpower
But can’t all that be overcome with just having more willpower? Maybe a little, but this is like telling our football team they just need to “want it more” than the other team. Sure it can help, but if our squad is a high school JV football team playing against the 1985 Chicago Bears defense, no amount of wanting it is going to get us the win.
Everyone has varying abilities to exert willpower in regard to their nutrition. Let’s take a person who works a 12-hour shift, was up most of the night with a sick baby, and gets home late with the daunting task of finding and preparing something healthy to eat. Exerting enough willpower to make a good decision for someone in that situation is going to be much less likely than someone who had the opportunity to get a full night’s sleep and had a less mentally demanding day. Of course, there are strategies that can be worked on to improve planning and make the best out of one’s situation, which is a large part of what we help people with at BIN, but what I am trying to illustrate is that just “trying harder” is not a good answer for most people.
Another large factor that creates a gap in the amount of willpower necessary for some people compared to others is their environment. Different physical, socio-cultural, economic and political environments create varying degrees of obesogenic environments that make it more or less difficult to make healthy food choices. For example, Americans living in food deserts (defined by areas that lack access to affordable fruits, vegetables, whole grains, low-fat milk, and other foods that make up the full range of a healthy diet) are going to have a much harder time having the access and resources required to make consistently good nutrition choices. According to the USDA 6% of Americans live in food deserts (3).
The factors above can at least in some situations be influenced by the bettering of habits and lifestyle choices, but there is a huge, double-helixed shaped elephant in the room that we also need to address: genetics.
Genetics
At this point I feel compelled to force the football analogy so here we go… We can think of genetics as the location of our football team. No matter how good our gameplans are, or who our coach is, it is going to be really tough to recruit talented players to come play for the Antartica Angels.
I really want to emphasize this section, because I feel that people who have natural and easy success in something like weight management often overestimate how much of their success is due to their specific choices, and underestimate the contribution of things outside their control. Over 500 different genes have been identified to have a direct or indirect link to obesity in humans (4). So what does this mean in practical terms? Let’s say we have 100 people who’s measured TDEE are all 2000 calories, and we locked them all up in a metabolic ward and fed them 1500 calories per day, tightly controlling all their activity and intake to ensure those variables are accounted for. Most people would assume that all 100 people would lose the same amount of weight. Not so fast, bucko. In pretty much all studies where a similar protocol as described above is implemented, there is significant variability in weight loss between participants following the same magnitude of calorie deficit (5). The inverse can be seen in overfeeding studies as well (6). Some people are just more resistant to gaining or losing weight even when the same conditions are applied.
Measurement of Calories In
Even after we take into account all of the above and try to just measure our intake through meticulous tracking, the picture is still less clear than we would assume. In an attempt to stretch our football analogy to it’s absolute limits, this would be like if every time we scored a touchdown we were unsure how many points the officials granted for it. We think a touchdown is worth 6 points, but sometimes the officials only give us 4 or 5, and we don’t know it until several days later.
One source of possible error are nutrition labels themselves. In the best case scenario, nutrition labels are accurate within 2-5% of their actual content if they match the accuracy standards set forth by the National Institutes of Standards and Technology (NIST) (7). Even professionals in the field of nutrition have a hard time accurately tracking their intake. One study showed that dieticians, who are formally trained in recording food intake, under-reported calorie intake by 223 calories on average (8).
However, even with all the possible sources of error, it can still be a good idea to track your intake. While the above things make it hard to be accurate (close to reality) we can still work towards being precise (consistent). The reason this is helpful, is that even if our caloric intake estimations from tracking are off by 1000 calories every single day, as long as we are off by those same 1000 calories every day, changes we make to our intake will still be reflected. You can increase the effectiveness of this approach by eating similar foods and tracking them the same way while you are tracking. If you do this while also consistently measuring your bodyweight, you can get a decent idea of the amount of calories it takes to keep your weight stable.
Calories Out
I have good news and bad news for this next section. The good news is I am not going to confuse you with my convoluted football analogies this time, but the bad news is that this side of the equation is even murkier and less modifiable. Let’s take a quick look at the components that make up our total daily energy expenditure (TDEE), or the total number of calories you expend in a given day, and how much we can influence these numbers.
Resting Metabolic Rate (RMR)- Accounting for about 60-75% of your total energy expenditure, this is the amount of calories your body uses simply to perform normal bodily functions and keep you alive from day-to-day. The main determinant of RMR is the amount of lean body mass an individual carries. But again, even this can vary between individuals of similar size, age, and dieting status.
Non-Exercise Activity Thermogenesis (NEAT)- Accounting for ~10% of total energy expenditure, these are calories burned by the movements we make just going about our day that are not structured exercise or activity. Things like fidgeting and other subconscious movements contribute to this. This is thought to be one of the main variables that affect the degree of metabolic adaptation to dieting that we discussed above. Basically, when you’re dieting you are less likely to fidget or do other subconscious movement in order to preserve energy.
Thermic Effect of Food (TEF)- This accounts for ~10% of total energy expenditure and refers to the energy cost of chewing, swallowing, digesting, absorbing, and storing food. Eating a diet higher in protein can increase TEF, but the difference is pretty small in the grand scheme of things.
Exercise Activity Thermogenesis (EAT)- Accounting for somewhere around 20-35% of energy expenditure, this refers to intentional exercise. This seems like a pretty promising way to have some control over our calories out right? Yes, but it’s not as straightforward as we may hope (someone change the record..). If our normal TDEE is 2000 calories, and we go on a run where we burn 500 calories, it would make sense that our energy expended for the day would be 2500 calories. But alas, our bodies don’t like to make it that easy on us. In reality, we consistently observe some degree of compensation to increasing amounts of physical activity (9). Meaning that instead of increasing our TDEE to 2500 calories in the above example, it may increase to 2200-2400. The more we exercise, the greater the amount of compensation. The degree of compensation is different between individuals, and can vary based on dieting status as well (more compensation if you are in a deficit).
Measurement of Calories Out
But Chris, my watch tells me exactly how many calories I burn each day so I can use that right? Right?!?!! If your eyes are tired of reading the bad news I continue to provide in this article, perhaps you would rather receive this last piece of news through audio:
BIN Radio: Are Fitness Trackers Accurate? (BONUS EPISODE) on Apple Podcasts
To make a long story short, fitness trackers are pretty awful at estimating energy expenditure, to the point where these readings are not providing actionable information (10). Even if they were accurate, we know from our discussion earlier on EAT that we cannot simply add the calories burned through exercise to our TDEE and expect it to be accurate.
Conclusion
While there is seemingly a ton of doom and gloom in this article, I hope I at least got across the idea that weight management is a bit more than a simple arithmetic calculation. There are plenty of things outside of our control, and I hope that understanding this allows for a little more empathy to those struggling with weight management. There are also tons of things that we CAN control, and it is those things that we should focus on to make the best of our situation and drive us towards our goals.
Written by: Chris Bonilla, Black Iron Nutrition Performance Coach
References
Zhu, B., Shi, C., Park, C. G., Zhao, X., & Reutrakul, S. (2019). Effects of sleep restriction on metabolism-related parameters in healthy adults: A comprehensive review and meta-analysis of randomized controlled trials. Sleep Medicine Reviews, 45, 18–30. https://doi.org/10.1016/j.smrv.2019.02.002
Oliver, G., Wardle, J., & Gibson, E. L. (2000). Stress and food choice: A laboratory study. Psychosomatic Medicine, 62(6), 853–865. https://doi.org/10.1097/00006842-200011000-00016
USDA ERS - Documentation. (n.d.). Retrieved March 3, 2023, from https://www.ers.usda.gov/data-products/food-access-research-atlas/documentation/
Mahmoud, R., Kimonis, V., & Butler, M. G. (2022). Genetics of Obesity in Humans: A Clinical Review. International Journal of Molecular Sciences, 23(19), 11005. https://doi.org/10.3390/ijms231911005
Metabolic adaptation is associated with less weight and fat mass loss in response to low-energy diets—PubMed. (n.d.). Retrieved March 3, 2023, from https://pubmed.ncbi.nlm.nih.gov/34116675/
Levine, J. A., Eberhardt, N. L., & Jensen, M. D. (1999). Role of nonexercise activity thermogenesis in resistance to fat gain in humans. Science (New York, N.Y.), 283(5399), 212–214. https://doi.org/10.1126/science.283.5399.212
How Do You Know Your Food’s Nutrition Facts Label Is Accurate? (2021). NIST. https://www.nist.gov/how-do-you-measure-it/how-do-you-know-your-foods-nutrition-facts-label-accurate
Champagne, C. M., Bray, G. A., Kurtz, A. A., Monteiro, J. B. R., Tucker, E., Volaufova, J., & Delany, J. P. (2002). Energy intake and energy expenditure: A controlled study comparing dietitians and non-dietitians. Journal of the American Dietetic Association, 102(10), 1428–1432. https://doi.org/10.1016/s0002-8223(02)90316-0
Broskey, N. T., Martin, C. K., Burton, J. H., Church, T. S., Ravussin, E., & Redman, L. M. (2021). Effect of Aerobic Exercise-induced Weight Loss on the Components of Daily Energy Expenditure. Medicine & Science in Sports & Exercise, 53(10), 2164. https://doi.org/10.1249/MSS.0000000000002689
Shcherbina, A., Mattsson, C. M., Waggott, D., Salisbury, H., Christle, J. W., Hastie, T., Wheeler, M. T., & Ashley, E. A. (2017). Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort. Journal of Personalized Medicine, 7(2), 3. https://doi.org/10.3390/jpm7020003