Problems start with finding your daily energy expenditure, or the figure with which one should match their calorie intake. There are numerous Resting Metabolic Rate (RMR) calculators out there, however, the difference in results between these ranges from 0.5% to 28.0%. An example below illustrates the discrepancies in RMR for the same person using three most popular methods: Harris and Benedict’s, Mifflin - St.George’s and Cunningham’s.
Research shows that the Harris and Benedict’s equation correctly predicts RMR in 45% to 80% of individuals, and overestimates occur more frequently than underestimates [2]. The Mifflin-St. George’s equation is more accurate with 82% correct predictions [3]. Cunningham’s equation showed best results with correct RMR estimations provided in approximately 82% cases [3].
RMR is only the starting point, as we should also add the energy expenditure (EE) which varies greatly from person to person depending. Online calculators, fitness bracelets and smart watches provide only approximate estimations. On average, fitness trackers are 30% wrong when estimating daily EE, they are especially incorrect when evaluating sitting tasks: the error could be as much as 52% [4]. It doesn’t come as a surprise because individual EE is unique and depends on many factors including not only body composition and fitness level, but also quality of sleep, hormonal profile and even composition of gut microflora.
To estimate the energy intake for a person, even knowing his or her diet, is also no easy task. In 1896, Wilbur O. Atwater, the father of food calories, calculated the calorie content of hundreds of foods using bomb calorimetry at the World's Fair and found that even fruits and vegetables grown, harvested, and stored under the same conditions have different calorie content. Interestingly, the average calorie values of some products, obtained by him more than 100 years ago, are still used on labels and in various databases. We know today that the calorie content error for products can reach as much as 25-50% [5]. The amount of calories that a person gets with a meal also depends on the cooking [6]. The degree of ripeness of fruits and vegetables has an effect on calorie yield too: the riper a fruit or a vegetable, the more sugars and hence calories it contains. For example, the total average amount of glucose and fructose in underripe and overripe bananas is 12–13 g/100 g, while in unripe bananas it is 3.2 g/100 g [7].
Most of the time we don't eat with scales and calorimeters at hand, and rely rather on our subjective evaluation which depends on emotional state. For instance, people who want to lose weight tend to underestimate the amount of "bad" foods eaten and overestimate the proportion of "good" foods. On the contrary, people who want to gain weight overestimate the number of high-calorie foods in their diet and the size of portions [8]. In addition, never-ending calorie counting contributes to stress, feelings of dissatisfaction with oneself, loss of enjoyment of food, and an increased risk of anorexia and malnutrition [9].
When we advise our clients to have a certain amount of calories, proteins, fats and carbs, they don't always understand clearly what they really need to eat. Recommendations like “have 20% of daily calories coming from protein” are hard to implement. Moreover, such recommendations do not take into account how nutritious the food really is. For example, a hamburger and bowl of cottage cheese with raisins and nuts may contain the same amount of calories, proteins, fats and carbohydrates, but completely different amounts of vitamins, minerals, fibre, antioxidants and other substances that we need to be healthy.
Calorie counting is also sometimes misleading as people may avoid certain healthy foods because of their high calorie content. Nuts are high in calories. On average 100 gram of nuts contain 500 cal, which automatically puts them on the stop list of any person aiming to lose weight. However, according to the studies, consumption of at least 5 servings of nuts or peanut butter per week is significantly associated with a lower risk of cardiovascular disease, more favourable plasma lipid profile, including lower LDL cholesterol and apolipoprotein-B-100 concentrations and even weight loss [10, 11].
Solution for the calorie counting ambiguity? A nutrient-based approach. Abe-Health takes into account the amount of proteins, fats, carbohydrates, fibre, vitamins, minerals, etc. (200+ components actually), but makes recommendations in real nutrition categories: how many servings of dairy products is needed, should a client consider adding grains, meats, fruits, vegetables or nuts. Abe-Health also helps to evaluate and adjust your clients’ eating habits regarding cultural, regional and seasonal differences, food intolerances, allergies and health complications. And if you choose a specific diet for your client (vegan, Nordic, keto), we will help you create a nutrition plan that contains all the necessary vitamins, minerals, amino acids and more. You can test the effectiveness of the nutrient-based approach in the Abe NutriChallenge 2022 launching on November 10th, 2022 (registration by the link).
- U.S. Department of Health and Human Services and U.S. Department of Agriculture. 2020–2025 Dietary Guidelines for Americans. Ninth Edition. December 2020. Link
- Frankenfield D, Roth-Yousey L, Compher C. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J Am Diet Assoc. 2005;105(5):775-89 Link
- Haaf T, Weijs PJ. Resting energy expenditure prediction in recreational athletes of 18-35 years: confirmation of Cunningham equation and an improved weight-based alternative. PLoS One. 2014;9(9):e108460. doi: 10.1371/journal.pone.0108460. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4183531/
- Shcherbina A, Mattsson CM, Waggott D, Salisbury H, Christle JW, Hastie T, Wheeler MT, Ashley EA. Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort. J Pers Med. 2017;7(2):3. doi: 10.3390/jpm7020003 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5491979/
- U.S. Food & Drug Administration. A Food Labeling Guide. Link
- Gebauer S, Novotny J, Bornhorst G, Baer D. Food processing and structure impact the metabolizable energy of almonds. Food Funct. 2016;7:4231-8. doi:10.1039/C6FO01076H https://pubmed.ncbi.nlm.nih.gov/27713968/
- Phillips KM, McGinty RC, Couture G, Pehrsson PR, McKillop K, Fukagawa NK. Dietary fiber, starch, and sugars in bananas at different stages of ripeness in the retail market. PLoS One. 202;;16(7):e0253366. doi: 10.1371/journal.pone.0253366. https://pubmed.ncbi.nlm.nih.gov/34237070/
- Chernev, A., The Dieter's Paradox, Journal of Consumer Psychology. 2011; 21(2): 178-183 doi:10.1016/j.jcps.2010.08.002 https://www.sciencedirect.com/science/article/abs/pii/S1057740810000987
- McGeown L. The calorie counter-intuitive effect of restaurant menu calorie labelling. Can J Public Health. 2019;110(6):816-820. doi: 10.17269/s41997-019-00183-7. https://pubmed.ncbi.nlm.nih.gov/30701412/
- Li TY, Brennan AM, Wedick NM, Mantzoros C, Rifai N, Hu FB. Regular consumption of nuts is associated with a lower risk of cardiovascular disease in women with type 2 diabetes. J Nutr. 2009;139(7):1333-8. doi: 10.3945/jn.108.103622. https://pubmed.ncbi.nlm.nih.gov/19420347/
- Sabaté J. Nut consumption and body weight. Am J Clin Nutr. 2003;78(3 Suppl):647S-650S. doi: 10.1093/ajcn/78.3.647S. https://pubmed.ncbi.nlm.nih.gov/12936960/