Exploring Energy Balance Beyond Calorie Counting

Exploring Energy Balance Beyond Calorie Counting

Disclosure: This article was created in collaboration with Fitia. Dietitian Success Center received compensation for this partnership. Content has been reviewed by a registered dietitian to ensure neutrality and alignment with professional standards.

 

Conceptually, the familiar phrases “a calorie is a calorie” or “calories in, calories out” provides a reasonable simplification of the energy balance equation – at its core, a mathematical construct. Because of its simplicity, some nutrition practitioners have adopted calorie counting as a practical and convenient tool in professional practice.

However, applying this concept in isolation can be misleading. In reality, energy balance is more nuanced, as differences in food composition can lead to variations in energy absorption and metabolic cost (1).

In this article, we’ll explore the factors that can influence energy absorption even when total caloric intake appears identical. The goal is to help nutrition practitioners understand how to discuss the complexity of energy balance when working with clients who rely on calorie counting and tend to reduce nutrition to numbers.

Revisiting the Concept of Metabolizable Energy

Metabolizable energy refers to the amount of energy from food that becomes available to the body after accounting for losses in urine and feces (2). To estimate these values – particularly for food labeling, which is relevant to calorie counting – the Atwater system is commonly used, assigning energy values of 4, 4, and 9 kcal/g to protein, carbohydrate, and fat, respectively.

However, while the Atwater system was groundbreaking for its time, it has clear limitations. As a result, the caloric values displayed on most food labels often differ from the true metabolizable energy, due to variations in food composition, structure, and an oversimplified estimation of protein energy content (3).

The discrepancies observed when manipulating these factors are generally modest – recent studies report differences of 116 ± 56 kcal, which is not statistically significant in most contexts (2) – but they can become meaningful when strategically applied. Understanding these nuances offers valuable flexibility when developing or adjusting dietary strategies.

How Food Composition and Structure Affect Calorie Absorption

Lipid bioaccessibility, resistant starch, and dietary fiber are factors that can influence metabolizable energy through their effects on digestion and absorption.

Take almonds, for example. Because of their unique internal structure, some encapsulated lipids and proteins remain intact during mastication (4). This limits how much fat from almonds is accessible and subsequently absorbed in the digestive system. One study reported that the actual metabolizable energy from a 28 g serving of almonds was approximately 20% lower than the predicted value (5).

In the case of starchy foods such as rice, potatoes, and legumes, resistant starch can form through retrogradation – the process that occurs when these foods are cooked and then immediately cooled (6). This transformation makes part of the starch resistant to digestion, acting more like dietary fiber and providing ~2 kcal per gram instead of 4 (7).

Finally, high fiber intake can also reduce the absorption of fat and, in some cases, protein (8). A well-known study by Baer and colleagues reported an inverse relationship between fiber consumption and the digestibility of both fat and protein (9).

How the Thermic Effect of Food Influences Energy Expenditure

To metabolize protein, carbohydrates, and fats, the body must expend energy – a process known as the thermic effect of food (TEF). 

Because protein requires deamination and other metabolic processes, it has the highest thermic effect of the macronutrients – studies show TEF for protein in the range of ~20-30% of its energy content, compared with ~5-10% for carbohydrate and ~0-3% for fat (10).

Research has also shown that higher protein intake can increase the thermic effect of food by approximately 15.4% compared with lower protein consumption. This means that, depending on total protein intake, overall energy balance may differ even when caloric intake remains the same across eating patterns (11).

Applying These Insights Within Calorie Counting

At this point, we can outline several strategies that may help influence the energy balance equation through informed food choices, even when total caloric intake remains the same. These include selecting foods with a complex tissue matrix such as almond kernels, allowing starchy foods to cool and undergo retrogradation before consumption, and increasing both fiber and protein intake.

These strategies should, of course, be viewed as guiding principles rather than strict prescriptions. Individual variability – including dietary pattern, tolerance to fiber, individual differences in metabolic rate and medical history – will determine the magnitude of the effect observed. 

Even so, when these approaches are optimized, differences in net energy balance may remain modest, yet still contribute to meaningful health outcomes. Evidence consistently shows that regular nut consumption helps reduce risk factors for type 2 diabetes and cardiovascular disease (4); that fiber intake is associated with lower all-cause, cardiovascular, and cancer mortality (12); and that adequate protein intake supports body composition, metabolic health, and reduced chronic disease risk (13).

Being aware of how food selection affects energy balance adds depth to tools like calorie counting used in the context of nutrition counseling. When combined with calorie counting tools – such as Fitia, which allows professionals and patients to track, adjust, and visualize dietary patterns – it provides a broader perspective and greater flexibility to guide nutrition strategies effectively.

Key Takeaways

  • The concept of “a calorie is a calorie” overlooks how food composition influences absorption and metabolism.
  • Metabolizable energy represents the calories actually absorbed by the body and can differ from food label values due to digestive losses and food composition.
  • Whole foods with complex matrices (e.g., almonds), retrograded starches (from cooled starchy foods), and high-fiber foods tend to provide slightly less metabolizable energy than their labeled values.
  • Protein has the highest thermic effect of food (20–30%), increasing total energy expenditure compared with carbohydrates and fats.
  • Even if these applications produce only modest effects on energy balance, long-term health benefits are consistently linked to regular consumption of almonds, dietary fiber, and adequate protein.
  • Integrating food composition insights with calorie counting tools like Fitia could allow for more flexible and evidence-based nutrition strategies in practice.

 

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References

  1. Corbin KD, Carnero EA, Dirks B, Igudesman D, Yi F, Marcus A, Davis TL, Pratley RE, Rittmann BE, Krajmalnik-Brown R, Smith SR. Host-diet-gut microbiome interactions influence human energy balance: a randomized clinical trial. Nat Commun. 2023 May 31;14(1):3161. doi: 10.1038/s41467-023-38778-x. PMID: 37258525; PMCID: PMC10232526.
  2. Roberts, S. B., & Flaherman, V. (2022). Dietary energy. Advances in Nutrition, 13(6), 2681–2685. https://doi.org/10.1093/advances/nmac092
  3. Pferdmenges LE, Colombani PC, Hauger Carlsen M, Pajari AM, Poulsen A, Dias MG, Møller A, Lisciani S, Wüst M, Storcksdieck Genannt Bonsmann S, Schweiggert-Weisz U. Toward harmonizing protein data in food composition databases: evaluating perspectives, methods and implications. Crit Rev Food Sci Nutr. 2025 Jun 6:1-14. doi: 10.1080/10408398.2025.2503461. Epub ahead of print. PMID: 40478626.
  4. Grundy MM, Lapsley K, Ellis PR. A review of the impact of processing on nutrient bioaccessibility and digestion of almonds. Int J Food Sci Technol. 2016 Sep;51(9):1937-1946. doi: 10.1111/ijfs.13192. Epub 2016 Jul 31. PMID: 27642234; PMCID: PMC5003169.
  5. Novotny JA, Gebauer SK, Baer DJ. Discrepancy between the Atwater factor predicted and empirically measured energy values of almonds in human diets. Am J Clin Nutr. 2012 Aug;96(2):296-301. doi: 10.3945/ajcn.112.035782. Epub 2012 Jul 3. PMID: 22760558; PMCID: PMC3396444.
  6. Robertson TM, Brown JE, Fielding BA, Hovorka R, Robertson MD. Resistant Starch Production and Glucose Release from Pre-Prepared Chilled Food: The SPUD Project. Nutr Bull. 2021 Mar;46(1):52-59. doi: 10.1111/nbu.12476. Epub 2020 Nov 22. PMID: 33776583; PMCID: PMC7984060.
  7. Higgins JA. Resistant starch and energy balance: impact on weight loss and maintenance. Crit Rev Food Sci Nutr. 2014;54(9):1158-66. doi: 10.1080/10408398.2011.629352. PMID: 24499148; PMCID: PMC4220782.
  8. Hervik AK, Svihus B. The Role of Fiber in Energy Balance. J Nutr Metab. 2019 Jan 21;2019:4983657. doi: 10.1155/2019/4983657. PMID: 30805214; PMCID: PMC6360548.
  9. Baer DJ, Rumpler WV, Miles CW, Fahey GC Jr. Dietary fiber decreases the metabolizable energy content and nutrient digestibility of mixed diets fed to humans. J Nutr. 1997 Apr;127(4):579-86. doi: 10.1093/jn/127.4.579. PMID: 9109608.
  10. Westerterp-Plantenga MS, Nieuwenhuizen A, Tomé D, Soenen S, Westerterp KR. Dietary protein, weight loss, and weight maintenance. Annu Rev Nutr. 2009;29:21-41. doi: 10.1146/annurev-nutr-080508-141056. PMID: 19400750.
  11. Sutton EF, Bray GA, Burton JH, Smith SR, Redman LM. No evidence for metabolic adaptation in thermic effect of food by dietary protein. Obesity (Silver Spring). 2016 Aug;24(8):1639-42. doi: 10.1002/oby.21541. Epub 2016 Jun 29. PMID: 27356102; PMCID: PMC4963285.
  12. Yao, F., Ma, J., Cui, Y., Huang, C., Lu, R., Hu, F., Zhu, X., & Qin, P. (2023). Dietary intake of total vegetable, fruit, cereal, soluble and insoluble fiber and risk of all-cause, cardiovascular, and cancer mortality: systematic review and dose-response meta-analysis of prospective cohort studies. Frontiers in Nutrition, 10, Article 1153165. https://doi.org/10.3389/fnut.2023.1153165
  13. Lv, J. L., Wu, Q. J., Li, X. Y., Gao, C., Xu, M. Z., Yang, J., Zang, S. T., Luan, J., Cai, D. Z., Chang, Q., & Zhao, Y. H. (2022). Dietary protein and multiple health outcomes: An umbrella review of systematic reviews and meta-analyses of observational studies. Clinical Nutrition, 41(8), 1759-1769. https://doi.org/10.1016/j.clnu.2022.06.005

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