Fat: Thrift or Energy buffer?

This article is an adaption from a chapter I wrote for my new book(s), Controlling Intuitive Appetite, in response to various questions regarding accumulation of adipose tissue, and why other factors such as an inability to increase muscle mass may occur. I thought it may be useful for some of you to review the concept.

If it stimulates any thoughts or questions, please add a comment.

Obesity has long been associated with a diverse range of chronic diseases, yet as discussed in Consistent Eating (1), the beneficial attributes of adipose tissue are largely ignored, specifically in relation to meeting the demands of ecological cues that signal evolutionary vulnerability, i.e. historically famine, and in response to industrialised modernity, cues moderate weight gain in the face of current environmental pressures. As previously discussed, the concept of obesity in one defined by criteria of statistical basis rather than explicit metabolic pathology. (2; 3) 

Consistent Eating (1), discussed adipose tissue in the context of efficiency of of metabolic rate per unit mass in order that sufficient energy is maintained for optimal brain function, and it was hypothesised that decreased energy availability, overtime leads to compartmentalisation, and eventual decline is various aspects of brain function. The evolutionary concept of adipose tissue as a vital store of energy acts as a strategy in which the ability to regulate metabolism manages ‘risk’ in response to a variety of ecological and environmental cues. (4)

The major hypotheses of obesity revolve around the concept of thrift, with Neel suggesting in 1962 (5), that a ‘thrifty genotype’ created a genetic predisposition for energy storage based on the assumption that ancestral environments involved frequent exposure to ‘feast and famine cycles, and that those exposed to higher frequency of famine evolved with a selection for genetic “thrift”, which is a trait no longer suited to an industrialised society that is abundant in sources of food, and rendered lazy by technology.

Hales and Barker (6), introduced the hypothesis that plasticity occurred throughout lifespan, proposing that infants with low birth weight adapted to the deficit in nutritional intake by increased efficacy of both growth and metabolism, creating increased risk of obesity throughout lifespan. In Consistent Eating (1), Intrauterine Growth Restriction was discussed as a means to ensure sufficient brain development in the womb, alongside the hypothesis that the nine month gestational period, and occurrence of premature birthing are all evolutionary responses to the metabolic needs of the fetus. (1)

Yu et al (7), disputed the correlation between birth weight and obesity, and it is suggested by the author that the propensity toward obesity throughout lifespan in low birth weight infants may also be correlated with socioeconomic status. Indeed, low birth weight is suggested as a sufficient marker of socioeconomic status, suggestive of the fact that those born into poverty may have increased genetic propensity towards a “thrifty” metabolism, which is then compounded by environmental factors such as poverty, greater exposure to poorer food outlets, less educational opportunity and various other variables that create environmental influences upon genes. (8)

Wells, along with Siervo discuss the premise of energy balance and the evolutionary advantage conferred by the efficacy with which humans seem disposed to adiposity and the propensity for inhibition of metabolism. (9; 10) Implied thrift, as disused in Consistent Eating (1) may be derived from both an efficacy in reduction of energy expenditure, and an increase in less energy demanding tissues (creation of adipose tissue as stored energy) to achieve resource management in accordance with the current and historical environment regarding energy availability. Adipose tissue as a strategy energy management is complimented by various other variables, dependent on the species to enable “thrift” or efficiency, namely torpor/hibernation, fatigue/inhibition of activity, growth rate manipulation, body size, decrease in organ mass relative to the rate of investment (i.e. organs such at the brain are energetically expensive but vital, as such function may be inhibited or prioritised rather than loss of mass, where as other organs may decrease mass and limit function in relation to energy availability). (11; 12)

Both Hill and Stearns (13; 14) discuss the strategic enactment throughout lifespan of decisions regarding aspects such as rate of growth and development, initiation of breeding, amounts of offspring produced which is highly variable from species to species, but in humans, greatly impacted by environmental aspects such as resource availability/socioeconomic status, cultural norms and lifespan strategy.

In an upcoming chapter in Controlling Intuitive Eating (15), evolutionary strategy is discussed regarding optimisation of fitness for reproductive success, rather than lifespan longevity. As such, the finite availability of energy be traded between factors that compete for importance, such as growth, development, repair/maintenance, reproductive ability and immune function, in which long-term aims must be traded off against current needs. (13)

As discussed in Consistent Eating (1), adipose tissue, and the ability to inhibit metabolism provides an energy buffer against such trade off, allowing short-term variances in environment to be guided by factors that impact on longer term goals, namely reproduction of genes, and ensure that offspring may continue to reproduce. In realising that human evolutionary needs specifically involve ensuring sufficient energy availability to allow reproduction, and that assessment of resources may be controlled by various socioeconomic considerations (from less affluent populations reproducing earlier, and with larger numbers of offspring to offset potential losses, increase potential for successful continuation of genes, to more affluent populations that my reproduce later to ensure greater economic wealth, and produce less offspring due to the potential they may be conferred by such economic wealth, and or social status.

Adiposity, considered a risk to both health, society, and the economy (15), is by the author, theorised to be a behavioural risk management strategy utilised by the brain that both fluctuates in response to environmental and ecological stimuli, but also throughout lifespan. Bouchard’s model of five gene traits associated with metabolism, appetite, thermogenesis, physical activity, cellular predisposition towards lipid storage, and rate of lipid oxidation (16), is now suggested to include correlations between body-mass index and infant growth rate, which as previously discussed is impacted by socioeconomic status and environmental factors. (17)

Ecological and environmental pressures seems to favour an increase in metabolic efficacy, and a tendency towards adiposity due to aspects such as human locomotion being bipedal, which both requires greater cognitive capacity, and increased expenditure in both time and energy to achieve such mobility, creating an early years reliance on caregivers for mobility. Large brains and greater capacity for, and indeed reliance upon social behavioural abilities that emerged throughout the evolution of a human ‘savannah’ environment to the urban environment typical in industrialised modernity which provides a sudden and stark alteration in the volatile ecological habitat. 

As documented in Consistent Eating (1), increases in body mass creates a decrease in unit mass energy expenditure (resting metabolic rate per kg/24 hrs) as also documented by Oftedal (18), with efficiency in metabolism becoming more evident as mass increases, indicating that larger mass, coupled with both relative and absolute stores of energy creates a greater buffer period in which adipose tissue is able to meet energy requirements. Adipose tissue as a means of energy storage forms part of a strategy aimed at risk management in relation to potential uncertainty is by no means the only strategy for managing the risk of unpredictability in access to energy supply. The increase in sociability of humans led to other variables in energy storage, with an increased occurrence of food hoarding, often within groups of varying sizes to reduce or alleviate uncertainty by pooling together resources, which requires some degree of social control over distribution.

The buffering effect of adipose tissue in starvation, in which adults are able to sufficiently meet energy demands for long periods, with females suggested to endure longer degrees of starvation (19), is typically the de facto strategy used to attempt to “normalise” weight. Indeed, recent research indicates that females narrow the performance gap to males in “ultra marathon” endurance events that require ability to endure extreme energy deficits, and provides a worrying insight into the ability to tolerate repeated deficit protocols, particularly in females. (20)

As discussed in Consistent Eating (1), during starvation, all tissue is broken down during prolonged starvation, and while the source with the greatest degree of flexibility may be adipose tissue, we also see substantial decreases in other tissue, including the heart, gastrointestinal tract, spleen, pancreas and liver. (21)

Adipose tissue forms part of a broad range of stored energy sources, and it would seem that its relative low metabolic needs may indeed render it a source that is preferably stored in long-term starvation, or in repeated attempts at dietary restriction, to the degree that utilising other more metabolically demanding tissue confers that added benefit of decreasing total energy expenditure. (1; 22)

Stochastic buffering occurs in response to both short and long-term energy balance fluctuations due to a variety of environment stresses such as seasonal food availability, and Ferro-Luzi and Branca (23), identified seasonal body weight fluctuations of between 2-3kg within traditional farming populations, a trend which rose to 4-5 kg in more extreme environmental conditions. (24)

Consistent Eating (1), discussed energy requirements for both growth and development, of which an ability to store energy provides an important aspect of the energetic funding of both growth, development and repair through individual lifespan, and for reproduction. Conception is regulated by maternal nutrition status (25), and in gestation maternal adiposity contributes to fetus growth. (26)

In early infant-hood, the ability to store energy, which subsequently acts as a bio-marker for predicting body mass, including lean through lifespan, suggesting that strategy for growth is sensitive to, and tightly regulated by signals regarding energy availability, both in early life via maternal and gestational status, then postnatally by the external environment. (9)

Herculano-Houzel (27), suggests that neuronal energy needed of whole brain is relatively stable across species irrespective of brain mass. Indeed, estimated neuronal glucose use varied between six differing rodent species and primates, one of which were humans, by only 40 percent. Herculano-Houzel concluded that in humans, a brain that represents just two percent of total mass, which expends >20 percent of the total energy budget occurs due to the larger number of neurons throughout the human brain, and the increased synaptic activity in specific regions that is the determinant of metabolic cost, which for example, the average consumption of glucose to be over 10 times higher in the cerebral cortex when compared to the cerebellum.

Caceres et al (28), indicate that the higher amounts of neurons evident in human brains creates high energy demand in adulthood which is suggested to be between 20-25 percent of basal metabolism, and that infant adiposity may enable buffering against the increased energy demand created by the brain throughout this period. (29)

The resting metabolic rate per unit mass (kg) discussed in Consistent Eating (1), that sees an increase in energy efficiency throughout timespan, one which was hypothesised to aid in buffering energy availability to sufficiently protect the brain, is also evident in brain energy usage. Holliday (30), discusses as much as 80 percent of infant total energy expenditure being utilised by the brain, which decreases to approximately 20-25 percent during adulthood, and as discussed in Consistent Eating, it is hypothesised that such buffering accounts for ecological variances in energy availability throughout lifespan, and via increases in stimuli such as the need for increased physical activity, decreases in kcal intake relative to size, sociocultural factors such as the assumption that modernity increased gluttony and sedentary behaviours. Further buffering was hypothesised to occur via compartmentalisation of brain function to specific regions, and in later years to the degree that less essential function may be lost (memory, motor control) in favour of more vital functions such as cardiovascular and circularity functions.

Fertile Fatness

The observable sexual dimorphism typically evident in adult adiposity primarily favours females is discussed as being the direct result of the energetic fetal needs during reproduction. (9; 31)

Variability in adiposity dimorphism occurs in response to ecological and environmental factors, including resource availability (primarily for energy), and variance in climate. However mean skin-fold thickness (measured at triceps brachii) is greater in females than in measures seen males in most populations. Indeed, Lassek and Gaulin (32) highlight gluteo-femoral levels of adiposity with regard to brain growth in offspring and future cognitive ability.

References:

  1. Craig, B. (2018). Consistent Eating: Is dieting harming your health and your weight loss? WWBS Publishing. London.

  2. Cole, T, J., Bellizzi, M, C., Flegal, K, M,. & Dietz, W, H. (2000). Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 320: 1240-1243.

  3. Wang, Y., & Wang, J, Q. (2000). Standard definition of child overweight and obesity worldwide. Authors’ standard compares well with WHO standard. BMJ (Clinical Research Ed.). 321(7269): 1158

  4. Pond, C, M. (1998). The Fats of Life. Cambridge: Cambridge University Press.

  5. Neel, V. (1962). Diabetes mellitus: a “thrifty” genotype rendered detrimental by “progress”? Am. J. Hum. Genet. 14(4): 353-362. 

  6. Hales, C, N., & Barker, D, J. (1992). Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia. 35(7): 595-601. 

  7. Yu, Z. B., Han, S. P., Zhu, G. Z., Zhu, C., Wang, X. J., Cao, X. G. and Guo, X. R. (2011). Birth weight and subsequent risk of obesity: a systematic review and meta-analysis. Obes. Rev. 12, 525–542.

  8. Martinson, M, L., & Reichman, N, E. (2016). Socioeconomic Inequalities in Low Birth Weight in the United States, the United Kingdom, Canada, and Australia. American Journal of Public Health. 106(4): 748-754.

  9. Wells, J, C. (2011). An evolutionary perspective on the trans-generational basis of obesity. Ann. Hum. Biol. 38(4): 400-409.

  10. Wells, J, C,. & Siervo, M. (2011). Obesity and energy balance: is the tail wagging the dog? Eur. J. Clin. Nutr. 65(11): 1173-1189.

  11. Wells, J, C. (2009). The Evolutionary Biology of Human Body Fatness: Thrift and Control. Cambridge: Cambridge University Press.

  12. Wells, J, C. (2006). The evolution of human fatness and susceptibility to obesity: an ethological approach. Biol. Rev. 81(2): 183-205.

  13. Hill, K. (1993). Life history theory and evolutionary anthropology. Evol. Anthropol. 2(3): 78–89.

  14. Stearns, S, C. (1992). The Evolution of Life Histories. Oxford: Oxford University Press.

  15. Craig, B. (Unpublished). Controlling Intuitive Eating. WWBS Publishing. London.

  16. Bouchard, C. (2007). The biological predisposition to obesity: beyond the thrifty genotype scenario. Int. J. Obes. 31(9): 1337-1339.

  17. Elks, C, E., Loos, R, J., Sharp, S, J., Langenberg, C., Ring, S, M., Timpson, N, J., Ness, A, R., et al. (2010). Genetic markers of adult obesity risk are associated with greater early infancy weight gain and growth. PLoS Med. 7(5): e1000284.

  18. Oftedal, O, T. (2000). Use of maternal reserves as a lactation strategy in large mammals. Proc. Nutr. Soc. 59(1): 99-106.

  19. Norgan, N. G. (1997). The beneficial effects of body fat and adipose tissue in humans. Int. J. Obes. Relat. Metab. Disord. 21(9): 738-746.

  20. Waldvogel, K, J., Nikolaidis, P, T., Di Gangi, S., Rosemann, T., & Knechtle, B. (2019). Women Reduce the Performance Difference to Men with Increasing Age in Ultra-Marathon Running. Int J Environ Res Public Health. 16(13): E2377.

  21. Rivers, J, P. (1988). The nutritional biology of famine. In Famine (ed. Harrison, G. A.), pp. 57–106. Oxford: Oxford University Press.

  22. Keys, A., Brozek, J., Henshel, A., Mickelson, O., & Taylor, H.L. (1950). The biology of human starvation, (Vols. 1–2). Minneapolis, MN: University of Minnesota Press.

  23. Ferro-Luzi, A., & Branca, F. (1993). Nutritional seasonality: the dimensions of the problem. In Seasonality and Human Ecology (ed. Ulijaszek, S. J. and Strickland, S. S.), pp. 149-165. Cambridge: Cambridge University Press.

  24. Singh, J., Prentice, A, M., Diaz, E., Coward, W, A., Ashford, J., Sawyer, M., & Whitehead, R, G. (1989). Energy expenditure of Gambian women during peak agricultural activity measured by the doubly-labelled water method. Br. J. Nutr. 62(2): 315-329.

  25. Wade, G. N., Schneider, J. E. and Li, H. Y. (1996). Control of fertility by metabolic cues. Am. J. Physiol. 270(1 Pt 1): E1-E19.

  26. Anderson, G, D., Blidner, I, N., McClemont, S., & Sinclair, J, C. (1984). Determinants of size at birth in a Canadian population. Am. J. Obstet. Gynecol. 150(3): 236-244.

  27. Herculano-Houzel, S. (2011). Scaling of brain metabolism with a fixed energy budget per neuron: implications for neuronal activity, plasticity and evolution. PLoS ONE 6(3): e17514.

  28. Caceres, M., Lachuer, J., Zapala, M. A., Redmond, J. C., Kudo, L., Geschwind, D. H., Lockhart, D. J., Preuss, T. M. and Barlow, C. (2003). Elevated gene expression levels distinguish human from non-human primate brains. Proc. Natl. Acad. Sci. USA. 100(22): 13030-13035.

  29. Kuzawa, C, W. (1998). Adipose tissue in human infancy and childhood: an evolutionary perspective. Am. J. Phys. Anthropol. 107(27): 177-209.

  30. Holliday, M, A. (1978). Body composition and energy needs during growth. In Human Growth, Vol 2 (ed. Falkner, F. and Tanner, J. M.), pp. 101-117. New York: Plenum.

  31. Lassek, W. D. and Gaulin, S. J. (2006). Changes in body fat distribution in relation to parity in American women: a covert form of maternal depletion. Am. J. Phys. Anthropol. 131(2): 295-302.

  32. Lassek, W, D., & Gaulin, S, J. (2007). Waist-hip ratio and cognitive ability: is gluteofemoral fat a privileged store of neurodevelopmental resources? Evol. Hum. Behav. 29(1): 26-34.

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