Progress in understanding fat storage has followed from research on the adaptive use of energy reserves by non-humans (Wells Reference Wells2009). We fundamentally agree with Nettle et al. that applying evolutionary thinking to human fattening dynamics will provide insights for understanding the incidence of obesity and other metabolic diseases. Nevertheless, we feel that the insurance hypothesis (IH), as formulated by Nettle et al., misses key nuances that limit its explanatory power unnecessarily and may underpin its failures to capture details of their data analysis. Here, we suggest how progress can be made from building on these foundations.
Missing from the IH is an explicit treatment of information (Dall et al. Reference Dall, Giraldeau, Olsson, McNamara and Stephens2005): Why is it that people living in wealthy countries with social security – making it very unlikely that they will starve to death – store fat reserves as though starving to death is a distinct possibility? In the notation of their model, it is crucial to distinguish actual p (the probability that food is found) from perceived p, and understand how they can come to differ. For instance, Nettle et al. point out that disadvantaged people are more likely to be obese, but fail to consider why their perceived p should be differentially biased. Mismatch hypotheses for humans have recently come under fire. Rather than discard them completely, we suggest a refined IH, which would have to explicitly incorporate information dynamics driven by evolutionary mismatches. As the authors point out, if restriction of food during dieting is taken to influence perceived p, then target fat reserves should increase after dieting, which as we have shown (Higginson & McNamara Reference Higginson and McNamara2016) is a contrast effect (McNamara et al. Reference McNamara, Fawcett and Houston2013).
In Nettle et al.’s model, food insecurity is taken to be 1−p. Thus, under their model the maximum availability of food is inversely proportional to food insecurity. A refined IH would allow for both food insecurity and current food abundance such as in our models (Higginson & McNamara Reference Higginson and McNamara2016; McNamara et al. Reference McNamara, Higginson and Houston2015). The simplest way to do this is to vary both p and maximum meal size N. Low p and high N would be food insecure, and high p and low N would be food secure while having the same mean availability.
Human fattening patterns often involve “ratchetting” whereby any given stored fat level and/or body mass is associated with a metabolic profile that “defends” the steady state body condition (fat or lean) from short-term perturbations via compensatory metabolic processes (e.g., Leibel et al. Reference Leibel, Rosenbaum and Hirsch1995), even when differentially fat individuals share the same nutritional environments. Such dynamics are not captured in any IH model we are aware of and will require the incorporation of factors that have not yet been considered. Models show that gathering information about the environment may be neglected when energy insurance is necessary (Dall & Johnstone Reference Dall and Johnstone2002), which could provide a mechanism for divergence of actual p and perceived p. Because the central nervous system is costly, natural selection will have exploited the fact that physiological states (such as fat stores) contain information about environmental conditions (Higginson et al., Reference Higginson, Fawcett, Houston and McNamarain preparation). Chronic obesity may result from an informational ratchet effect if current state is taken to provide information that in the current environment it is appropriate to store a large amount of fat.
Such information dynamics could underlie the differences we see among populations, not least the lack of effect among children, who may not yet have stable estimates of prevailing levels of food insecurity. On the other hand, perceived p may not be limited to what is experienced within a particular individual's lifetime. There is the possibility that children respond to the experiences of the mother during her life or during pregnancy (epigenetic effects). We expect selection on what the mother passes on and on how offspring respond (McNamara et al. Reference McNamara, Dall, Hammerstein and Leimar2016; Wells Reference Wells2007a). Because different individuals (mothers and offspring) have different experiences, they would have different target body reserve levels. Models of offspring provisioning under the risk of starvation (Dall & Boyd Reference Dall and Boyd2002) could be developed for humans. Divergence of metabolic rates may lead to persistent differences among individuals (Mathot & Dall Reference Mathot and Dall2013).
Evolutionary ecology theory predicts that individuals with poor prospects should take more risks and discount the future, so there may be similarities in the cause of obesity and the causes of unsustainable debt (Shah et al. Reference Shah, Mullainathan and Shafir2012), in that low-income people prioritise the present. Nettle et al. posit one hypothesis for why the IH is only supported for women in high-income countries. The behavioural ecology literature on hierarchies (e.g., among birds) points to another explanation: In patriarchal societies, women can be perceived to be in some sense “subordinate” (Acker Reference Acker1989); they are more likely to suffer in difficult circumstances and so should store more fat.
Strategic body mass regulation theory makes few assumptions about how the adaptive body mass dynamics predicted in any given scenario are controlled proximately. Most models assume that any decision-making system (hormones, cognition, etc.) is highly flexible such that it can be optimised (Fawcett et al. Reference Fawcett, Hamblin and Giraldeau2013). But it is likely that animals including humans actually have simple mechanisms that have evolved to perform sufficiently well in most conditions that have been experienced over evolutionary time (McNamara & Houston Reference McNamara and Houston2009). Having a highly specific and flexible rule may be costly, and this cost will be traded off against the cost of inaccuracy of decision making: Humans may have evolved inexpensive “rules” that perform well in most environments, but lead to overeating in rich environments (Higginson et al. Reference Higginson, Fawcett and Houston2015).
In summary, we need to develop human-specific evolutionary models of body mass regulation that take information use and physiological “rules” into account. We need to work with clinicians, psychologists, and physiologists, among others, which will help incorporate the human-relevant details to build better theory. This could elucidate what aspects of the environment drive overeating and weight gain and provide an evolutionarily informed solution to the obesity epidemic.
Progress in understanding fat storage has followed from research on the adaptive use of energy reserves by non-humans (Wells Reference Wells2009). We fundamentally agree with Nettle et al. that applying evolutionary thinking to human fattening dynamics will provide insights for understanding the incidence of obesity and other metabolic diseases. Nevertheless, we feel that the insurance hypothesis (IH), as formulated by Nettle et al., misses key nuances that limit its explanatory power unnecessarily and may underpin its failures to capture details of their data analysis. Here, we suggest how progress can be made from building on these foundations.
Missing from the IH is an explicit treatment of information (Dall et al. Reference Dall, Giraldeau, Olsson, McNamara and Stephens2005): Why is it that people living in wealthy countries with social security – making it very unlikely that they will starve to death – store fat reserves as though starving to death is a distinct possibility? In the notation of their model, it is crucial to distinguish actual p (the probability that food is found) from perceived p, and understand how they can come to differ. For instance, Nettle et al. point out that disadvantaged people are more likely to be obese, but fail to consider why their perceived p should be differentially biased. Mismatch hypotheses for humans have recently come under fire. Rather than discard them completely, we suggest a refined IH, which would have to explicitly incorporate information dynamics driven by evolutionary mismatches. As the authors point out, if restriction of food during dieting is taken to influence perceived p, then target fat reserves should increase after dieting, which as we have shown (Higginson & McNamara Reference Higginson and McNamara2016) is a contrast effect (McNamara et al. Reference McNamara, Fawcett and Houston2013).
In Nettle et al.’s model, food insecurity is taken to be 1−p. Thus, under their model the maximum availability of food is inversely proportional to food insecurity. A refined IH would allow for both food insecurity and current food abundance such as in our models (Higginson & McNamara Reference Higginson and McNamara2016; McNamara et al. Reference McNamara, Higginson and Houston2015). The simplest way to do this is to vary both p and maximum meal size N. Low p and high N would be food insecure, and high p and low N would be food secure while having the same mean availability.
Human fattening patterns often involve “ratchetting” whereby any given stored fat level and/or body mass is associated with a metabolic profile that “defends” the steady state body condition (fat or lean) from short-term perturbations via compensatory metabolic processes (e.g., Leibel et al. Reference Leibel, Rosenbaum and Hirsch1995), even when differentially fat individuals share the same nutritional environments. Such dynamics are not captured in any IH model we are aware of and will require the incorporation of factors that have not yet been considered. Models show that gathering information about the environment may be neglected when energy insurance is necessary (Dall & Johnstone Reference Dall and Johnstone2002), which could provide a mechanism for divergence of actual p and perceived p. Because the central nervous system is costly, natural selection will have exploited the fact that physiological states (such as fat stores) contain information about environmental conditions (Higginson et al., Reference Higginson, Fawcett, Houston and McNamarain preparation). Chronic obesity may result from an informational ratchet effect if current state is taken to provide information that in the current environment it is appropriate to store a large amount of fat.
Such information dynamics could underlie the differences we see among populations, not least the lack of effect among children, who may not yet have stable estimates of prevailing levels of food insecurity. On the other hand, perceived p may not be limited to what is experienced within a particular individual's lifetime. There is the possibility that children respond to the experiences of the mother during her life or during pregnancy (epigenetic effects). We expect selection on what the mother passes on and on how offspring respond (McNamara et al. Reference McNamara, Dall, Hammerstein and Leimar2016; Wells Reference Wells2007a). Because different individuals (mothers and offspring) have different experiences, they would have different target body reserve levels. Models of offspring provisioning under the risk of starvation (Dall & Boyd Reference Dall and Boyd2002) could be developed for humans. Divergence of metabolic rates may lead to persistent differences among individuals (Mathot & Dall Reference Mathot and Dall2013).
Evolutionary ecology theory predicts that individuals with poor prospects should take more risks and discount the future, so there may be similarities in the cause of obesity and the causes of unsustainable debt (Shah et al. Reference Shah, Mullainathan and Shafir2012), in that low-income people prioritise the present. Nettle et al. posit one hypothesis for why the IH is only supported for women in high-income countries. The behavioural ecology literature on hierarchies (e.g., among birds) points to another explanation: In patriarchal societies, women can be perceived to be in some sense “subordinate” (Acker Reference Acker1989); they are more likely to suffer in difficult circumstances and so should store more fat.
Strategic body mass regulation theory makes few assumptions about how the adaptive body mass dynamics predicted in any given scenario are controlled proximately. Most models assume that any decision-making system (hormones, cognition, etc.) is highly flexible such that it can be optimised (Fawcett et al. Reference Fawcett, Hamblin and Giraldeau2013). But it is likely that animals including humans actually have simple mechanisms that have evolved to perform sufficiently well in most conditions that have been experienced over evolutionary time (McNamara & Houston Reference McNamara and Houston2009). Having a highly specific and flexible rule may be costly, and this cost will be traded off against the cost of inaccuracy of decision making: Humans may have evolved inexpensive “rules” that perform well in most environments, but lead to overeating in rich environments (Higginson et al. Reference Higginson, Fawcett and Houston2015).
In summary, we need to develop human-specific evolutionary models of body mass regulation that take information use and physiological “rules” into account. We need to work with clinicians, psychologists, and physiologists, among others, which will help incorporate the human-relevant details to build better theory. This could elucidate what aspects of the environment drive overeating and weight gain and provide an evolutionarily informed solution to the obesity epidemic.