Caloric Availability

All Calories Are Equal, but Some Are More Equal Than Others

Do you track your macros? Are you glued to your favourite calorie-tracking app? Do you tot up every single calorie you consume and fret if, in a day, you munch a few too many? Well, it’s probably not worth being all that anal, as counting calories isn’t all that accurate.

In my article Is Calorie Tracking Accurate?, I outlined the limitations of the Atwater method of assigning energy value to foods. I showed how the standard values used to calculate calories are unreliable and that the figures we see on nutrient tables and food labels are a poor representation of the true energy value of the food we consume [1]. A conclusion one might draw from the article is that the Atwater approximations have no use. Yet, for many, calorie tracking can be an incredibly useful strategy, helping them control their weight, pack on muscle or achieve another diet-related goal. Even if calorie counting isn’t precise, modern life often forces us to rely on imperfect measurements. When it comes to assessing the quantity of food we ingest, the Atwater system can be one of the best tools available. Science mandates that we rely on imperfect approximations to test our hypotheses, which, while not wholly accurate, nevertheless nudge us towards sound theories. Calorie tracking is no different: using estimations to calculate our energy intake is a useful rule of thumb to work out how much food we consume and a metric that helps some adjust their intake.

However, as with any tool in which we put a high degree of faith, we’d be wise to understand its failings. We’ve already seen that the Atwater figures aren’t as reliable as we’d like, and there’s another key limitation: the actual amount of food energy that goes on to fuel our bodies isn’t what you think it might be.

Intake vs. Uptake

Not all the energy we consume is actually taken up and utilised by the body. This distinction between what we put in our mouths – calorie intake – and what we actually absorb from our intestines – calorie uptake, is known as “caloric availability”. How calories are absorbed from our guts differs from person to person and depends on the macronutrient composition of a food, how old a food is and the effects of cooking. Consequently, a calorie ingested need not be equal to another calorie ingested and this is influenced by several factors.

Even within one class of macronutrient, one calorie consumed might not be the same as another. Macronutrients can be absorbed differently and will provide a different amount of energy depending on the state of the food. Take carbs: if you consume 100 kcal worth of sugar, you’ll likely process the full 100 kcal. Yet, when you chomp down 100 kcal of corn on the cob, a much smaller amount will be digested and subsequently absorbed [2]. Don’t believe me? The next time you eat sweetcorn, after doing your “business” a few hours later, take a look at your poo and you’ll likely see a few undigested kernels mixed in the stool matter. You may have put 100 kcal of sweetcorn into your mouth, but a much smaller proportion of its energy will actually go on to enter your bloodstream. Something else happens when you take the corn, mill it and use the flour to make, say, a tortilla. Gobble down 100 kcal of the tortilla and a larger proportion of the carbs will be absorbed than from sweetcorn, although still less than 100 percent [3]. When it comes to how much utilisable energy is absorbed, one unit of energy is not the same as another; it depends on the extent and type of processing.

The degree of ripeness of a fruit, vegetable or cereal crop also influences the way its carbohydrates are broken down. If you’re the sort of weirdo who likes your bananas so ripe that they’re nearly black, you’ll more readily digest and absorb more of its carbs than a banana that’s still a little green. The more carbs that are absorbed, the more of its calories will be available.

As well as this, fibre helps to further reduce the caloric availability of a meal. Dietary fibre, also known as non-starch polysaccharide (NSP)*, is essentially the carbohydrates that human enzymes are unable to hydrolyse. This means that all the utilisable calories from fibre come from what’s broken down by our gut microbiome. Many types of fibre act like a sponge and, when consumed with water, form a gel, which slows the time it takes for food to pass through the alimentary tract. This affects where the digestible content of a meal is absorbed. Due to the fibre content, meals that take longer to digest have a lower overall caloric availability. This concept helps to explain the benefits of consuming large amounts of vegetables when you’re trying to lose weight.

Another reason for calorie inequality involves cooking. Heating food allows it to be broken down more easily, and more energy and nutrients can be extracted. This is best illustrated by celery. Some people say that celery has “negative calories” because, they claim, the amount of energy required to process it is greater than the amount that this tough, fibrous plant provides. This, however, is not true as our gut microbes break down the fibres and produce short-chain fatty acids (SCFAs), providing us with usable calories. However, it is fair to say that a stick of raw celery provides the body with only a very small amount of energy. Yet, something interesting happens when that stick of celery is chopped and cooked, say, as part of a stew. The now not-so-tough fibres are much more readily broken down to be easily metabolised into SCFAs by the bugs, so much so that our bodies can extract up to five times the energy from eating cooked celery (around 30 kcal) versus the same amount from raw (6 kcal) [4]. This principle applies to most other vegetables, too, including cabbage, broccoli, carrots and pulses: the more an edible plant is cooked, the easier it is for us to extract its calories.

It’s a similar story for animal products. The process of cooking meat causes the protein collagen to gelatinise, making it easier to chew and digest. How, for instance, beef is cooked can make a massive difference to the caloric availability. A steak cooked rare, or even “blue” – where each side has been briefly shown a hot frying pan sufficient only to kill off potential pathogens – will have a significantly lower caloric availability than beef that’s been minced, well cooked, mixed with a sauce and further stewed. Our digestive processes can extract a far greater amount of energy from mince cooked this way than from a near-raw steak. Similarly, when eggs are cooked, the protein they can deliver shoots up by nearly 40 percent compared to when they’re eaten raw [5] – aside from looking hardcore, Rocky was wasting his time necking those raw eggs! The more protein that’s absorbed, the more calories are available. In general, the shorter the cooking time, the more energy is required to digest a meal and the lower the calorie contribution is to our diets.

Caloric availability is affected by the digestion and absorption process, which itself is energy-consuming. The thermic effect of food (TEF) is the amount of energy required to digest, absorb and metabolise food. The energy cost depends on the combination of carbohydrate, fat, protein and fibre eaten. Processing 100 kcal of protein costs about 30 kcal (depending on the type of protein), whereas you’ll use between 5 and 10 kcal to metabolise 100 kcal worth of carbs (sugars require fewer calories to process than more complex starches) and a mere 3 kcal for an equal calorie amount of fat [6]. Eating a high-protein meal with the same number of calories as one high in carbs or fat will result in fewer net calories, with the exception being a meal consisting of only raw, fibrous veg. The TEF suggests a drawback in the usefulness of calorie counting. Foods are complex and inherently contain varying amounts of protein, carbs, fats and fibre.

Physiology & Genetics

The amount of calories we acquire from food is also influenced by our varying genetics and physiologies. For instance, the length of the large intestine can vary by up to 100 cm between healthy individuals [7]. A longer intestine means a more absorptive area, where more nutrients can be transported across the gut membrane into the blood. The greater the quantity of macronutrients that are absorbed, the more energy that’s available from a meal. The length of an individual’s intestine is, of course, primarily dictated by their genes, and other heritable traits also influence how macronutrients are absorbed.

To illustrate the impact of genetics on the bioavailability of calories, we’ll look at two mutations that have occurred in human populations during the last 10,000 years, which is recent in evolutionary terms. The disaccharide lactose – the sugar found in milk – is broken down in the digestion process into glucose and galactose by the enzyme lactase. Infants of many mammalian species actively secrete lactase from their pancreatic ducts into the upper intestine, where it breaks down lactose. However, the activity of lactase ceases as the young grow towards adolescence, leaving adult mammals unable to digest milk sugar. Like other mammals, more than two-thirds of modern humans lose this ability to digest lactose prior to adolescence. The ancestors of some modern human populations, however, experienced a mutation in the gene that codes for the lactase enzyme, known as the LCT gene, which allowed the continued production of lactase into adulthood. This ability to digest milk sugar as adults is known as lactase persistence [8]. Someone who’s able to consume milk benefits not only from being able to break down the carbohydrate in the milk, but also from the large amounts of protein, fat and crucial vitamins and minerals that come with it. Those with this ability gained a survival and reproductive advantage over others living in the same region at the same time.

The mutation occurred largely, though not exclusively, in people of northern European descent, possibly because milk products, being a rich source of vitamin D, would have been beneficial to those in northern climates with less sunlight and cooler temperatures that required more clothing to be worn [9]. Moreover, the fermented products that milk can be converted into, namely cheese and yoghurt, could be more easily transported [10]. Some regions of Asia, as well as African and Middle Eastern pastoralist communities, also experienced this mutation. In other populations, however, where there was no evolutionary pressure for dairy nutrients, the mutation didn’t occur. Consequently, lactase persistence is absent in over 65 percent of today’s adults [11]. Unable to digest lactose, if these adults consume milk, they suffer from stomach cramps, loose stools, nausea and vomiting. The roughly one-third of adults globally who are able to enjoy milk can benefit from the nutrition it supplies. Interestingly, however, this mutation doesn’t show up in around 10 percent of people of northern European descent. Curiously, many of these adults, despite lacking lactase persistence, are still able to consume a reasonable quantity of dairy products without suffering any ill effects. This is likely due to their gut microbes contributing to the breakdown of lactose, something that will happen to a varying degree depending on the health of the microbiome at any point in time, even in the same individual [12].

The fact that a large number of people have a mixed racial heritage that includes some northern European ancestry tells us that there’s a spectrum of LCT gene expression in modern populations, with adult humans being able to break down lactose to varying degrees; the ability to digest lactose is not an all-or-nothing event. The degree of LCT gene expression in individuals, as well as the effect of their gut microbes on the breakdown of lactose, manifests across a huge spectrum, meaning that human adults can successfully digest milk sugar in different amounts [13]. Consequently, the caloric availability of lactose varies considerably between adults, both between populations and within those of related ancestry. When ascribing a caloric value to a glass of milk, how are we to know how many of these calories will be absorbed by the person who drinks it?

The influence of genetics on caloric availability is of even greater relevance when it comes to our ability to digest starch. Starch digestion involves the enzyme amylase, which is secreted both in saliva and from the pancreas. Amylase breaks down the long polysaccharide chains that make up starch to the disaccharide maltose, which, further along the alimentary canal, is itself broken down into two molecules of glucose. An individual’s ability to digest starch is of such significance both because glucose is the form of energy preferred by our brains and bodies and because starchy foods are a predominant feature of the vast majority of people’s diets, whether from rice, corn, wheat, potatoes or other cereals or tubers. It’s been shown that the number of copies of the AMY1 gene – which codes for salivary amylase – varies across populations and individuals. The more copies of the AMY1 gene that are expressed, the more salivary amylase is present and the more an individual is able to break down starch [14]. Populations who grew to depend more and more on growing their calories in the form of cereals, grains and tubers benefited from a mutation where more AMY1 was expressed. With more amylase available, more starch can be hydrolysed in the mouth, making it easier to extract the calories from starch later on in their alimentary tract. This mutation proved beneficial for our forebearers, many of whom became increasingly dependent on starch in their diets. Those with the ability to digest greater amounts of starch could absorb more glucose and were able to benefit more from the crops they grew, providing a reproductive advantage. Similar to the ability to digest lactose, a spectrum of starch digestion exists where individuals break the polysaccharide down to differing degrees. Those able to digest it more readily are able to use a greater number of calories from it; the starch they eat is more calorically available.

Meal Timing

When we consume our meals also influences caloric availability. Through evolution, mammals have adapted circadian rhythms to enable them to better optimise their available energy during the times of day when they are most likely to need it. For our ancestors, being able to call on their energy reserves was most useful during the daytime when they needed to be alert, energised and able to hunt and gather more efficiently, and to avoid predators. The consequence of this is that eating too much later on in the day may make it harder to lose weight than when larger meals are eaten earlier. Indeed, research supports this hypothesis. In one study, despite no difference in the amount or dietary composition of meals, participants who ate later lost less weight and at a slower rate than those who consumed their meals earlier [15]. In another, overweight women were placed on identical diets, but their plans were different in the proportion of calories distributed between breakfast and dinner. Those who ate more at breakfast lost nine percent more weight than those who ate more at dinner [16]. Although other research has suggested less of an impact when it comes to the time of day when a larger proportion of calories are consumed, there is, at least, some impact of circadian rhythm on caloric availability. The effect seems to be larger in some people than others – possibly greater in those who are trying to lose weight – for reasons that aren’t fully understood. Totting up the total calories consumed over the course of a day may not be as reliable as you think.

The Significance of Caloric Availability

The variability of caloric availability has been demonstrated. For example, in one study, researchers determined how many calories participants had absorbed from almonds and compared the results to the standard calorie-calculation methodology. They found that, on average, participants absorbed 32 percent fewer calories than what was estimated by the Atwater method. Moreover, participants’ responses varied significantly: they absorbed between 56 and 168 calories from one ounce of almonds [17]. When it comes to almonds, some people absorb three times as much energy as others.

The true energy harvested from food is consistently misestimated when calories are counted. Key features of the digestive process are routinely ignored or overlooked: differences in the levels of absorption of macronutrients, the ripeness of plant foods, how a food is processed or heated, the effect of gut microbes, the TEF, our anatomy and physiology, our genetics and when we eat our meals. The neuroendocrinologist and geneticist from Cambridge University, Giles Yeo, in his book Gene Eating: The Story of Human Appetite, summarises caloric availability as “the amount of calories that can actually be extracted during the digestive process, as opposed to the total number of calories that are locked up in the food” [18]. As well as the limitations of the Atwater system in totting up how many calories we consume, the caloric availability of foods is something anyone who tracks their calories should be aware of.

* Dietary fibre also accounts for other carbohydrates that can’t be broken down by human physiologies, such as resistant starch and lignin.

References:
1. Collier, J. (2024) ‘Is Calorie Tracking Accurate?’, Thought for Food, 28 May. Available at: https://jamescollier.substack.com/p/is-calorie-tracking-accurate (Accessed: 27 August 2024).
2. Yeo, G. (2020) Gene Eating: The Story of Human Appetite. London: Orion Spring, p63.
3. ibid (2), p63.
4. ibid (2), p63.
5. Pieter, E. et al. (1998) ‘Digestibility of Cooked and Raw Egg Protein in Humans as Assessed by Stable Isotope Techniques’, The Journal of Nutrition, 128(10), 1716-22.
6. ibid (2), p65.
7. Teitelbaum, E. N. et al. (2013) ‘Intraoperative Small Bowel Length Measurements and Analysis of Demographic Predictors of Increased Length’, Clinical Anatomy, 26(7), 827-32.
8. (a) Itan, Y. et al. (2009) ‘The Origins of Lactase Persistence in Europe’, PLoS Computational Biology, 5(8), e1000491; (b) Brüssow, H. (2013) ‘A Short History of Lactose’, Environmental Microbiology, 15(8), 2154-61.
9. (a) Flatz, G. and Rotthauwe, H. W. (1973) ‘Lactose Nutrition and Natural Selection’, Lancet, 2(7820), 76-7; (b) Szilagyi, A. (2015) ‘Adult Lactose Digestion Status and Effects on Disease’, Canadian Journal of Gastroenterology & Hepatology, 29(3), 149-56.
10. Spector, T. (2020) The Diet Myth: The Real Science Behind What We Eat. London: Weidenfeld & Nicolson, pp 145-7.
11. (a) Bersaglieri, T. et al. (2004) ‘Genetic Signatures of Strong Recent Positive Selection at the Lactase Gene’, American Journal of Human Genetics, 74(6), 1111-20; (b) Ségurel, L. and Bon, C. (2017) ‘On the Evolution of Lactase Persistence in Humans’, Annual Review of Genomics and Human Genetics, 18, 297-319; (c) Segurel, L. et al. (2020) ‘Why and When Was Lactase Persistence Selected For? Insights from Central Asian Herders and Ancient DNA’, PLoS Biology, 18(6), e3000742.
12. Quigley, L. et al. (2013) ‘The Complex Microbiota of Raw Milk’, FEMS Microbiology Reviews, 37(5), 664-98.
13. ibid (11b, 11c).
14. (a) Perry, G. et al. (2007) ‘Diet and the Evolution of Human Amylase Gene Copy Number Variation’, Nature Genetics, 39, 1256-60; (b) Mandel, A. L. et al. (2010) ‘Individual Differences in AMY1 Gene Copy Number, Salivary α-Amylase Levels, and the Perception of Oral Starch’, PloS One, 5(10), e13352; (c) Carpenter, D. et al. (2017) ‘Copy Number Variation of Human AMY1 Is a Minor Contributor to Variation in Salivary Amylase Expression and Activity’, Human Genomics, 11, 2.
15. Garaulet, M. et al. (2013) ‘Timing of Food Intake Predicts Weight Loss Effectiveness’, International Journal of Obesity, 37(4), 604-11.
16. Jakubowicz, D. et al. (2013) ‘High Caloric Intake at Breakfast Vs. Dinner Differentially Influences Weight Loss of Overweight and Obese Women’, Obesity, 21(12), 2504-12.
17. Novotny, J. A. et al. (2012) ‘Discrepancy Between the Atwater Factor Predicted and Empirically Measured Energy Values of Almonds in Human Diets’, American Journal of Clinical Nutrition, 96(2), 296-301.
18. ibid (2), p62.