Menopause averted a midlife energetic crisis with help from older children and parents: A simulation study
Abstract
The grandmother hypothesis is the most influential account of the evolution of menopause in humans, but other theories warrant investigation. Here I use simulations to investigate two theories that ground the evolution of menopause in biparental care. Kaplan et al. (2010) proposed a “two-sex” learning and skill-based account, termed the Embodied Capital Model (ECM), in which the high energetic burden of caring for multiple, slow-developing offspring was met with biparental investment. Menopause evolved because the physiological costs of pregnancy and childbirth increased with age, yet productivity also increased with age, and the benefits of transferring resources to adult children and their offspring eventually outweigh the benefits of continued reproduction. Kuhle (2007) proposed the “father absent” hypothesis in which the higher mortality rate of husbands would often have left wives without the resources to raise young children, selecting for early reproductive cessation in monogamous couples. Simulations of hunter-gatherer energy consumption and production across the lifespan, taking account of age- and sex-specific survivorship, interbirth intervals, and varying rates of strength and foraging skill acquisition typical of contemporary foragers, reveal a pronounced midlife energy deficit that could be averted by ceasing reproduction midlife and receiving energy transfers from both younger couples (e.g., brideservice) and from older parents (the grandmother hypothesis). Menopause emerges as an integral and strictly necessary component of the unique human pattern of relatively short interbirth intervals and a long period of juvenile dependency, supporting and extending the ECM. DOI: 10.5281/zenodo.18149332
Introduction
Prolonged post-reproductive lifespans are rare in wild animals (Chapman et al., 2024; Ellis, Franks, Nattrass, Cant, et al., 2018; Monaghan & Ivimey‐Cook, 2023; cf. Winkler & Goncalves, 2023), which is consistent with the expectation that somatic and reproductive functions should senesce at similar rates (Croft et al., 2015). The explanation for the oddly long post-reproductive lifespans of females in humans and a few other species, on the other hand, remains hotly debated (see Figure 1). In brief, byproduct or non-adaptive explanations include that these are artifacts of unusually benign environments (e.g., captivity, recent improvements in public health) that extend lifespan but not fertility; that these are epiphenomena of antagonistic pleiotropy; or that these are artifacts of selection for male longevity that extended female lifespan but not fertility.
Adaptive explanations include the influential grandmother hypothesis, in which the benefits of investing in grandchildren outweighed the fitness benefits of producing more children; the mother hypothesis, in which the benefits of maintaining investment in multiple slow-developing offspring outweighed the increasing risk of maternal morbidity and mortality from continued reproduction; the “aging eggs” hypothesis, in which increased risk of chromosomal abnormalities selected for a cessation of reproduction; and the avoidance of breeding competition with genetic kin. These and other hypotheses have been extensively reviewed elsewhere (Arnot, 2021; Croft et al., 2015; Ellis et al., 2024; Hawkes, 2020; Holmes, 2019; Monaghan & Ivimey‐Cook, 2023; Peccei, 2001; Sievert, 2024), so I will not revisit them here. Instead, I will further develop two related hypotheses for the evolution of human menopause that have received relatively little attention.
The “two-sex” embodied capital model of menopause
Kaplan et al. (2010) proposed a “two-sex” learning and skill-based model of the evolution of human menopause. In this account, humans evolved to exploit a highly knowledge- and skill-based “niche” providing energy-rich but difficult to extract resources that required the rearing of slow-developing, large-brained, and thus energetically expensive offspring (Kaplan et al., 2000). Offspring were produced every few years but required almost two decades to become self-sufficient, placing a potentially high energetic burden on mothers. This burden is met by a co-evolving sexual division of labor in long-term monogamous marriages in which husbands specialized in skill-based acquisition of high-risk, high-return resources, with their skills and productivity increasing for about two decades beyond the age at which they became self-sufficient. Mothers specialized in child rearing and acquisition of lower-risk, lower-return resources. Menopause evolved because the physiological costs of pregnancy and childbirth increased with age, and oocyte quality decreased with age, yet productivity also increased with age. In this scenario, around midlife the fitness benefits of downward intergenerational transfers of resources by both parents, whose acquisition was based on four decades of skill development, termed embodied capital, outweighed the fitness benefits of continued offspring production. This account is part of the highly influential Embodied Capital Model (ECM, Kaplan et al., 2000). See Figure 2A,B.
The absent father model of menopause
Kuhle (2007) proposed a two-part “absent father” hypothesis for the evolution of menopause in humans that assumes the evolutionary importance of a sexual division of labor in long-term marriages, similar to the scenario proposed by Kaplan and colleagues (Kaplan et al., 2010, 2000). The first part proposes that fathers who abandoned their wives for younger women would have left their ex-wives without “the necessary level of paternal investment to rear newborns to reproductive age” (p. 332). The second part proposes that because male mortality is greater than female mortality, and because husbands tend to be older than their wives, husbands would often have died before their wives, again leaving the wives without the resources necessary to rear newborns. Menopause would have limited the childrearing burden placed on older single mothers. Unlike the more influential mother and grandmother hypotheses, the Kaplan et al. (2010) and Kuhle (2007) hypotheses both propose that a sexual division of labor in long-term monogamous relationships played a central role in the evolution of human menopause.
Although serial monogamy is not uncommon in the ethnographic record, Kaplan et al. (2010) emphasize the cost of mate-switching, and provide evidence that in small scale societies most children are produced and raised in long-term monogamous relationships. I will therefore set the wife abandonment hypothesis aside and focus on the “two sex” aspect of the Kaplan et al. (2010) and Kuhle (2007) hypotheses.
New data on the ontogeny of foraging skills
The ECM, based on the data available at the time, emphasized that adult men produced a substantial surplus of energy from high return but difficult to acquire resources, with maximum production around age 35-40, reproductive aged women produced approximately their own daily total energy expenditure (TEE), and post-reproductive women produced a modest surplus (Gurven et al., 2006; Kaplan et al., 2000; Walker et al., 2002). These surpluses supported a growing family of slowly developing offspring, each of whom would require energetic subsidies for up to 20 years. See Figure 2A,B.
Subsequently, two important sets of empirical results suggest a modification of the ECM might be necessary. First, in many populations proficiency in hunting and other food production occurs earlier in adulthood, and is more constant throughout adulthood, than depicted for men in Figure 2A. A study of hunting based on ~23,000 records from more than 1800 individuals from 40 locations, for example — mostly men — found that skill and productivity increased more rapidly with age than envisioned in the ECM, peaking in the early 30’s, and remaining flatter across adulthood (Koster et al., 2020). See Figure 2E. A study of the ontogeny of a number of skills among Tsimane horticulturists found that most skills, including food production, had been acquired by age 20, although self- and peer-ratings of high proficiency in food production for both men and women increased into their 40’s, consistent with the ECM (Schniter et al., 2015). See Figure 2D.
Second, there is increasing evidence that children are able to acquire substantial calories from wild foods (Pretelli et al., 2024). Hadza children, for example, when followed during foraging trips (and not just measuring food returned to camp), often acquired more calories during the day than required by an adult (Crittenden et al., 2013; Froehle et al., 2019). See Figure 2C. A study of child foraging using published data from 28 societies found that their foraging returns, as a fraction of returns by young adults, increased approximately linearly with age, albeit more slowly for more skill-intensive, difficult-to-extract resources (tubers and game), but more rapidly for easier-to-extract resources (fruit and fish/shellfish) where adult levels of productivity were reached by adolescence (Pretelli et al., 2022).
Study Aims
Following Gurven & Walker (2005), who took a similar approach to evaluate the energetic consequences of slow vs. fast childhood growth, I will evaluate the energetic consequences of menopause by modeling energy consumption vs. production for a nuclear family comprising the mother, father, and their joint offspring from the mother’s first birth to her maximum age, under the assumptions that mothers do, or do not, experience menopause, but with all other life history, demographic, and energetic factors falling within the ranges typical of contemporary hunter-gatherers. To account for the possibility that skill acquisition was more rapid than proposed in the ECM, I vary the rate over a range of values (Figure 2F).
It should be acknowledged at the outset that, if menopause is an adaptation it co-evolved with demographic and life history factors, so the counterfactual that a species with, e.g., modern human interbirth intervals, maturation times, body masses, total energy expenditures, and lifespans, but no menopause, is unrealistic. Nevertheless, this exercise could illuminate why it is unrealistic.
Methods
Energy balance (production minus consumption) in a hunter-gatherer nuclear family (mother, father, and their joint offspring) was modeled with a discrete time simulation starting at age at first birth (AFB) and continuing with one-year time steps for a maximum modern human lifespan (age 80). All adults reproduce (i.e., no reproductive skew or non-reproductive adults). Mothers give birth at a regular integer-valued interbirth interval (IBI) until the age at last birth (ALB), which is either the end of the lifespan (no menopause) or approximately midlife (menopause). Juveniles mature and leave the family at the AFB. Age- and sex-specific mortality followed standard human life tables. Per capita energy consumption used age-, sex- and body-weight-adjusted total energy expenditure (TEE) values from the literature, which were then summed for all family members. Per capita energy production was based on age- and sex-specific skills and physical strength (proxied by body weight), and varied across a range of parameter values for the relative importance of skill vs. strength, skill acquisition rates, and maximum adult energy production values, which were then summed for all family members. Family energy balance was total family production minus total family consumption computed for each year from the AFB to the maximum age (80). More details on each of these factors is provided in the following sections.
Age at first birth (AFB), age at last birth (ALB), and interbirth interval (IBI)
Davison & Gurven (2021) compiled demographic and life history values for contemporary hunter-gather populations, small-scale subsistence populations, and chimpanzee populations. I primarily used their averaged values from the five hunter-gatherer populations: Ache, Agta, Hadza, Hiwi, and !Kung (Ju/’hoansi). Although Davison & Gurven (2021) did not provide a numerical value for mean AFB, their Figures 2 and S2 indicate hunter-gatherer values clustering from shortly before 20 years of age to shortly after. They found that the average AFB for all human subsistence populations was shortly before 20 years. Hunter-gatherer age at last birth (ALB) ranged from 36 to 42, with a median of about 38, and mean total fertility was 6.2. Hunter-gatherer IBIs ranged from 2.8 years (Agta) to 3.3 years (Hiwi), with a mean value of 3.1 years. For simplicity, and to match the foregoing values as closely as possible, in all simulation runs fertility was constant until ALB, at which point it was set to 0, IBI = 3 years, AFB = 20, and, for runs with menopause, ALB = 38. Birth at age x was conditional on female survival to age x. For women who survived to the age of menopause, these values resulted in a total fertility of 7, slightly above the mean empirical value. Taking into account that not all women survive to the age of menopause, however, total fertility in the simulations was 6.1421774. For simulation runs without menopause, women give birth until the end of life.
Age- and sex-specific survivorship (mortality)
The average life expectancy at birth for human hunter-gatherers of both sexes combined is \(e_0 = 30\) years (Davison & Gurven, 2021). For the Hadza, female \(e_0=35.5\) and male \(e_0=30.8\) (Blurton Jones, 2016). An analysis of !Kung mortality (\(e_0=30\), Howell, 2017) found that it did not differ meaningfully from other human populations with similar life expectancy at birth (Coale & Demeny, 1966; Li & Gerland, 2012), a conclusion echoed by Gurven & Kaplan (2007), who concluded that “there is a characteristic life span for our species, in which mortality decreases sharply from infancy through childhood, followed by a period in which mortality rates remain essentially constant to about age 40 years, after which mortality rises steadily in Gompertz fashion” (p. 322).
The Kuhle (2007) hypothesis depends on a gap in the age of marriage combined with a sex difference in mortality, which is common in many human populations as well as in many wild mammals. A study of 101 mammal species, for example, found that the median female lifespan was 18.6% longer than that of conspecfic males, and in humans the mean female advantage was 7.8% (Lemaître et al., 2020). For age- and sex-specific survivorship (mortality) I used the UN Model Life Tables (Li & Gerland, 2012; data and code from Gaddy et al., 2025) with \(e_0\) values similar to the Hadza, i.e., a female life expectancy at birth, \(e_0 = 35\), a male life expectancy at birth, \(e_0 = 30\), and a sex ratio at birth (SRB) of 1.05 (i.e., a 5% male excess). See Figure S1.
Hunter-gatherer family energy consumption
Total energy expenditure (TEE) is a function of age, body mass, body composition (fat and fat-free mass), and activity levels. Age-related impacts on TEE include the energy required for development, age-related changes in activity levels, and tissue-specific metabolism. For example, the masses of energetically expense organs, such as liver and brain, comprise a greater fraction of body mass in children than adults. A study of TEE measurements using doubly labeled water (the gold standard method) in a large, diverse sample found four distinct life stages: fat-free mass–adjusted expenditure accelerates rapidly from 0 to 1 year, declines slowly to adult levels by ~20 years, remains approximately stable from 20 to 60, even during pregnancy, and then declines in older adults (Bajunaid et al., 2025; Pontzer et al., 2021).
Somewhat counter-intuitively, after adjusting for age, sex, and body mass, TEE is relatively constant within these four phases, regardless of activity or immune activation. Instead, an individual’s fixed energy budget is allocated among, e.g., growth, immunity, and activity. Children in horticultural Shuar vs. industrial populations have very similar TEE, for example, but compared to children in industrial populations, Shuar children have higher immune activation and activity, and reduced growth (Urlacher et al., 2019).
Accordingly, hunter-gatherer TEE was modeled using the regression model in Bajunaid et al. (2025), which comprises a linear equation that predicts TEE using age (years), sex, body mass (kg), height (cm), ethnicity, and elevation (m) (see Table 1 in Bajunaid et al., 2025), except that TEE for infants (age 0-1) was from Pontzer et al. (2021). Body mass and height were modeled as the average of generalized additive models (GAMs) of body masses and heights by age and sex of the Ache, Hadza, and !Kung. Ethnicity and elevation were set as “African” and 1000 m, respectively. See Figure S2. Family energy consumption was the sum of TEE for the mother, father, and their joint children for each age of the mother starting at AFB.
Adult hunter-gatherer energy production
A compilation of adult hunter-gatherer energy production by sex found that males typically (but not always) produced a surplus of calories beyond the typical adult male TEE, women generally produced around an adult female TEE (but in some cases with a surplus and in others with a deficit), and the combined male and female production was generally a surplus that would support offspring (Kraft et al., 2021). See Figure 3A.
Taking the average daily TEE of a hunter-gatherer adult to be about 2300 kcals, and using the energy production values in Figure 3A from Kraft et al. (2021), adult hunter-gatherer women produced from 0.4 to 1.6 of daily adult TEE, men from 1 to 2.4 of daily adult TEE, and one woman plus one man produced from 1.7 to 3.3 of daily adult TEE. Accordingly, maximum female energy production was modeled as a range from 0.4 to 1.8 of adult TEE, and maximum male energy production as a range from 1 to 2.6 of adult TEE, with the constraint that \(1.6 \le \mathrm{TEE}_{prop,f} + \mathrm{TEE}_{prop,m} \le 3.4\) (i.e., the range of surplus to support juvenile offspring).
Age- and sex-specific energy production
Hunter-gatherer energy production (kcals/day) by age and sex is fairly uncertain because there have been very few such populations to study, and measurements might be restricted to food returned to camp (ignoring food consumed during foraging), perhaps obtained only during parts of the year, and/or data from adults only. Drawing inspiration from modeling approaches in Gurven & Walker (2005), Gurven & Kaplan (2006), Koster et al. (2020), and Schniter et al. (2015), I modeled foraging productivity across the lifespan as follows:
\[ productivity(age) = \mathrm{TEE}_{prop} strength(age)^\alpha skill(age)^{1 - \alpha} \tag{1}\]
where \(\mathrm{TEE}_{prop}\) is the proportion of adult TEE, and ranged from 0.4 to 1.8 for women and from 1 to 2.6 for men, and \(0 \le \alpha \le 1\) is the relative importance of strength vs. skill, and was set to 0.25 (mostly skill-based), 0.5 (equal parts skill and strength), and 0.75 (mostly strength-based), separately for males and females. Strength was proxied by age- and sex-specific body weight (kg) as a proportion of maximum adult male weight, multiplied by a function that declines rapidly as age approaches the maximum age:
\[ strength(age, sex) = \frac{weight(age, sex) (1 - e^{b_0 (age_{\mathrm{max}}-age)})}{weight_{\mathrm{max}}} \tag{2}\]
where \(b_0\) is a parameter that determines the rate of strength decline in old age, and was fixed at -0.15 for both sexes in all simulation runs.
Skill is the product of a sigmoidal function that predominates at young ages, similar to that fit to the data in Schniter et al. (2015), with a function that declines rapidly as age approaches the maximum age:
\[ skill(age) = \frac{1}{1 - e^{-b_1(age - age_{50})}} (1 - e^{b_0(age_{\mathrm{max}}-age)}) \tag{3}\]
where \(b_1\) is a parameter that determines the rate of skill acquisition, and \(age_{50}\) is the age at which skill is 50% of maximum. These two parameters were combined to create Fast (\(b_1 = 0.4\), \(age_{50} = 10\)), Medium (\(b_1 = 0.25\), \(age_{50} = 15\)) and Slow (\(b_1 = 0.15\), \(age_{50} = 20\)) skill acquisition ontogenies, separately for each sex. \(b_0\) is a parameter that determines the rate of skill decline in old age, and was fixed at -0.15 for both sexes in all simulation runs. Productivity was set to 0 for children less than 3 years old. See Figure 2F and Table 1.
| Skill ontogeny | \(b_1\) | 50% | 95% |
|---|---|---|---|
| Fast | 0.40 | 10 | 17 |
| Medium | 0.25 | 15 | 27 |
| Slow | 0.15 | 20 | 40 |
Age gaps in marriage
Binford (2001) compiled ages at first marriage from the ethnographic record for men and women in 177 hunter-gatherer societies (see Figure S3). The median age difference is 5 years, and the 75% quantile is 9.5 years, so simulations used marriage age gaps of 5 and 10 years.
Parameter space and simulated life course
One simulation was run for every combination of parameters in Table 2, with the exception that the sum of wife and husband energy production was constrained to \(1.6 \le \mathrm{TEE}_{prop,f} + \mathrm{TEE}_{prop,m} \le 3.4\), as noted earlier. For each of the resulting 9720 combinations of parameter values the following vectors were computed in sequence:
- wife’s age was an integer-valued vector from AFB until the maximum age (80), at one-year intervals.
- husband’s age was wife’s \(age + age_{gap}\) (marriage age gap).
- wife’s probability of survival at each age relative to her AFB was computed with the female life table (all wives and husbands assumed to be alive at AFB; with SRB = 1.05 the numbers of surviving females and males at AFB is approximately equal).
- husband’s probability of survival at each age relative to AFB was computed with the male life table.
- pregnancies (coded as 0, 1) occurred every IBI years, starting at one year prior to AFB.
- births (coded as 0, 1) occurred every IBI years, starting at AFB and ending at either the age of menopause, or at end of life, and then scaled by mother survival to age x.
- child survival was age-specific survival (averaged for females and males) multiplied by births (i.e., no new children in years with birth = 0).
- wife, husband, and child TEE’s at each age (as described earlier) were multiplied by their survival at each age.
- wife, husband, and child productivities at each age were computed using Equation 1 and multiplied by their respective survival at each age.
- total resident children, total resident child consumption, and total resident child production at each wife age were computed assuming children disperse (leave the family) at the AFB, and using a windowing function based on wife’s age and wife survival (such that the number of children is scaled by the number of women who survived to give birth; see code).
- family consumption and production at each wife age were the sums of wife, husband, and total resident children’s consumption and production, respectively. Family production was assumed to support all family members.
- family energy balance was family production - family consumption. Neither family member survival, nor pregnancies, births, IBI’s, or any other factor were contingent on energy balance. See code for details.
Simulations were deterministic, i.e., there were no stochastic parameters.
| Parameter | Description | Values |
|---|---|---|
| \(e_{0,f}\) | Female life expectancy at birth (years) | 35 |
| \(e_{0,m}\) | Male life expectancy at birth (years) | 30 |
| \(age_{\mathrm{max}}\) | Maximum human age (years) | 80 |
| \(\mathrm{SRB}\) | Sex ratio at birth | 1.05 |
| \(\mathrm{AFB}\) | Age at first birth (years) | 20 |
| \(\mathrm{IBI}\) | Interbirth interval (years) | 3 |
| \(age_{\mathrm{gap}}\) | Marriage age gap (years) | 5, 10 |
| \(age_{\mathrm{menopause}}\) | Age of menopause | 38, 80 |
| \(\alpha_f\), \(\alpha_m\) | Relative importance of skill vs. strength for females and males | 0.25, 0.5, 0.75 |
| \(age_{50,f}\), \(age_{50,m}\) | Age of 50% skill acquisition for females and males | 10, 15, 20 |
| \(b_0\) | Rate of skill decline with increasing age | -0.15 |
| \(b_{1,f}\), \(b_{1,m}\) | Skill acquisition rate for females and males | 0.15, 0.25, 0.4 |
| \(\mathrm{TEE}_{\mathrm{prop},f}\) | Maximum productivity for females as a proportion of adult TEE | 0.4, 0.6, 0.8, 1, 1.2, 1.4, 1.6, 1.8 |
| \(\mathrm{TEE}_{\mathrm{prop},m}\) | Maximum productivity for males as a proportion of adult TEE | 1, 1.4, 1.8, 2.2, 2.6 |
Simulations were conducted using R version 4.4.1 (2024-06-14). Code and data are available here: https://github.com/grasshoppermouse/menopause.
Results
The main results across the entire parameter space are displayed in Figure S5. However, not all regions of parameter space are equally plausible for real hunter-gatherer families. For example, in 2513 of 9720 parameter combinations (26%), energy balance was always negative, and in 263 (3%) it was always positive. Most analyses were therefore restricted to a subset of the simulations, as follows. The Menopause condition more realistically reflects real hunter-gather families. The restricted subset of simulation runs in the Menopause condition comprised those that resulted in mean energy balance values across the entire lifespan that were within 500 kcals of 0. Those in the No menopause condition comprised those with combinations of parameter values matching those in the Menopause condition. The main results from this subset of 3756 parameter combinations are depicted in Figure 4, which are qualitatively similar to results from the entire parameter space in Figure S5, albeit with less variation, and biased toward simulation runs with more positive energy balances, although also omitting simulations with exceptionally high mean energy balances.
With the exception that the parameters specifying the joint energy production of wife and husband (\(\mathrm{TEE}_{\mathrm{prop},f},\mathrm{TEE}_{\mathrm{prop},m}\)) were further constrained to a narrow band of higher values, parameter values in the restricted subset nevertheless spanned the entire ranges of possible values, with varying deviations from the equal distributions in the full parameter grid. Specifically, the female skill acquisition rate (\(b_{1,f}\)) was biased upwards for higher values of female productivity (\(\mathrm{TEE}_{\mathrm{prop},f}\)), and the male skill acquisition rate (\(b_{1,m}\)) was biased upwards for intermediate values of male productivity (\(\mathrm{TEE}_{\mathrm{prop},m}\)) but downwards for the highest level of male productivity, likely due to the constraint on maximum lifetime energy balance. See Figure S9.
For wife’s age from AFB to age of menopause, during which 6.1 children are born (accounting for wife mortality), the No menopause and Menopause conditions are identical, after which they diverge. There are only an average of 4.3 resident children, however, due to child mortality (Figure 4A).
Family size
The No menopause and Menopause conditions diverge at the age of menopause because it is approximately double the AFB, at which point the oldest child leaves the family. In the No menopause condition, if there were no mortality, the number of family members would remain constant at around 4.3 after twice the AFB because as the oldest child dispersed a new child would be born. In the simulations, however, the number of family members, including resident children, slowly decreases in this condition at this age due to maternal mortality that reduces the birth of new children, and husband mortality (Figure 4A, left).
Critically, in the Menopause condition, the number of resident children decreases more rapidly after the age of menopause because no new children are born, older children mature and disperse, and child and maternal mortality take their toll, reaching 0 resident children at wife age of 58 (Figure 4A, right). In comparison, 58 year old women in the No menopause condition have 2.4 resident children, on average. There is no within-condition variation in resident children because no parameter variation impacts IBI, child mortality, or maternal mortality.
Energy consumption
As family size grows and as children mature, daily family energy consumption grows, and as it shrinks, energy consumption shrinks, but critically, more rapidly in the Menopause condition because dispersing offspring are not replaced by new offspring. See Figure 3B. There is only minor within-condition variation in energy consumption due to slight differences in husband mortality from the 5 and 10 year marriage age gap. See Figure 4B.
Energy production
Family energy production increases slowly for about the first decade after AFB, but more rapidly in the second decade as the productivity of maturing children increases. Subsequently, energy production declines due to wife and husband mortality, and in the Menopause condition, the departure of older productive children (see Figure 3C). Within-condition variation is due to variation in the parameters affecting productivity (\(\alpha\), \(b_1\), and \(\mathrm{TEE}_{prop}\)), each of which varies by sex. See Table 2 and Figure 4C. Qualitatively, energy consumption and production track family size.
Energy balance
For the births of the first two children, mean energy balance (averaging across the restricted parameter space) is positive in both conditions, dropping well below 0 at the birth of the fourth child in both conditions, when, due to child mortality, parents are caring for about 2-3 children. In the No menopause condition, mean energy balance is negative after this for the rest of the lifespan (see Figure 4D, left).
In the Menopause condition, after menopause (age 38) mean energy balance begins to increase as the productivity of maturing children increases and as children leave the family, becoming positive when wives turn 44 and parents are caring for about 3 children. Energy balance peaks again about a decade later, at age 54, as the last child has left the family, declining thereafter due to wife and husband mortality. See Figure 4D, right. Energy balance was also computed excluding juvenile production, which revealed pronounced energy deficits across most of the lifespan for all parameter combinations (Figure S8).
Across simulations in the Menopause condition with a “Medium” rate of skill acquisition, the proportion of total lifetime energy surplus acquired prior to menopause ranged from 0% to 65%, with a mean of 20%, and correspondingly, the proportion of total surplus acquired post-menopause to the end of life ranged from 100% to 35%, with a mean of 80%.
The influence of parameter combinations on lifetime energy balance in the restricted set of simulations are depicted in Figure S10. In general, higher joint productivity of the wife and husband was understandably associated with higher mean energy balance, as was, to a lesser degree, faster skill acquisition by both sexes. In the No menopause condition, the combination of these factors in a small region of the parameter space (3.6% of simulations) enabled families with older, productive children to reverse decreasing energy balances. See Figure S7.
Finally, simulations were also run with an earlier (32) and later (44) age of menopause. At the earlier age of menopause, families start to climb out of the energy deficit earlier and more rapidly (on average), and there is a longer period of energy surplus post menopause, with the reverse pattern for the older age at menopause. Other than the ages of menopause, these simulations used the same parameter values as used in the primary set of simulations. See Figure S6. With earlier and older ages of menopause, total fertility is lower or higher (+/- 2 births), respectively. A future analysis would seek the values of the IBI, lifespan, age at first birth, body size (TEE), and so forth, that optimize fitness, given, e.g., abilities to extract energy from the environment.
Parent mortality
Mortality of both wives and husbands is high. At age 50, 60% of wives have survived, and 46% of their older husbands have survived. Only about one parent, on average, thus remains to care for a mean 1.5 older children in the Menopause condition (ages 12 and/or 15), whereas in the No menopause condition, one parent would be caring for a mean of 3.5 children, some probably quite young (e.g., 2, 5, and 8).
Discussion
The key insight from the simulations is that without menopause, and given the energy consumption and production rates of contemporary foragers, the modern human pattern of relatively short interbirth intervals, long periods of juvenile dependency, minimal reproductive skew, and long lifespans, could not have evolved. At the third or fourth birth in most simulations, parents with several highly dependent offspring would not be able to feed them (Figure 4D).
The energetic crisis is averted by ceasing reproduction midlife combined with increasing juvenile productivity and energy transfers. Even though the simulations did not include energy transfers between nuclear families, the family energy surpluses that were present at some life stages in most simulations, could be transferred to families in energy deficit at other life stages. Indeed, this was one rationale for restricting analyses to those with mean lifetime energy balances close to 0: energy surpluses in some life stages would be sufficient to offset energy deficits in other stages via energy transfers between nuclear families. These results are broadly consistent with Kaplan et al. (2010) (compare Figure 4D, left, with Figure S4), albeit with important distinctions noted below.
To rule out the viability of a human-style life history sans menopause, it is important to consider that in the first three years, before the birth of the second child, 89% of the parameter combinations in the restricted parameter space had positive energy balance in at least one of those years, with a median surplus of 726 kcals/day. Because infants and young children require 400-1300 kcals/day, the surplus would be enough to support one additional young child beyond the nuclear family. Although this degree of energetic subsidy would be sufficient to support reproduction (and therefore lifespan) into the wife’s early-to-mid thirties when she would have about 3 dependent offspring, the family would then experience an energy deficit from which, absent menopause, they could not recover.
It is also possible that, sans menopause, ancestral foragers could simply have extracted more energy from the environment, and learned to do so rapidly. Maximum family energy consumption is 10,190 kcals/day, and maximum parent energy production is 7,544 kcals/day by the Nukak, with Hadza and !Kung parents not far behind (Figure 3A). In regions of the parameter space with high maximum productivity and rapid skill acquisition, resident children can make up the difference (Figure S7). Under these conditions, however, families generally produce an energy surplus across the entire lifespan, implying that changes to human life history parameters would have evolved to take advantage of the surplus, such as changes to interbirth intervals, growth and maturation rates, and ages of first birth and dispersal.
The simulations therefore suggest the following role of menopause in the co-evolution of modern human life history traits. Shorter interbirth intervals and longer periods of juvenile dependence sow the seeds of a mid-life energetic crisis: families have produced many young offspring with high energy requirements but who, per the ECM, require many years to acquire the skills necessary to provision themselves. Parents averted this crisis with three evolved strategies. First, by ceasing the production of new offspring in midlife (menopause), around age 40, parents’ energetic investments would then go solely to offspring whose increasing skills enabled them to begin supporting themselves before their dispersal (Figure 3, bottom right), at which point parents began climbing out of an energy deficit even without subsidies (Figure 4D, right). This would have been especially effective if offspring skill acquisition was relatively rapid (see the \(b_1\) panels in Figure S10). This refocuses the mother hypothesis on the energy production capacity of the mother, father, and their older offspring.
Second, young adults with few or no children produced a surplus that subsidized their immature siblings to whom they are as closely genetically related as to their own offspring, akin to the “helper at the nest” pattern seen in some other cooperatively breeding species (Hagen & Barrett, 2009; Hatchwell, 2009). This is consistent with the brideservice practices of many hunter-gatherer societies in which the bridegroom works for the bride’s family in exchange for marriage; brideprice is a related practice in which the bridegroom’s family pays the bride’s family with some form of wealth (Goody & Tambiah, 1973; Walker et al., 2011). Third, older parents, perhaps especially the wife’s parents (Daly & Perry, 2017), produced a surplus that subsidized their younger adult children’s children (the grandmother hypothesis, albeit here also including the grandfather) because the older parents’ one or two dependent older children largely supported themselves or perhaps even produced a surplus, or their children have all dispersed.
Rethinking the father absent hypothesis to include mother absence
Kuhle (2007) proposed that menopause might have evolved to mitigate the negative consequences of higher paternal than maternal mortality. At age 50 in a species with menopause, a surviving parent would be caring for one or two older children, whereas without menopause it would be 3 or 4 children, some quite young. It is possible that limiting the childcare burden on a surviving parent to a few older dependent offspring, which probably would have been manageable, rather than the care of several younger ones, which probably would not have been manageable, was a selection pressure for menopause. However, because the death of the wife would also have been common, and because the fitnesses of monogamous parents are tightly coupled, it is parental absence, not necessarily father absence, that matters.
Rethinking menopause and the ECM
There are three important distinctions between the results of the simulations reported here, and the Kaplan et al. (2010) “two sex” model. First, Kaplan et al. (2010) emphasize the importance of the increasing costs of pregnancy and childbirth with increasing age: in their model, menopause evolves because at midlife these costs reduce the benefits of continued reproduction which then no longer outweigh the benefits of transferring resources to kin. In the simulations, in contrast, menopause evolves simply because, given the amounts of energy that foragers can extract from environment, the relatively rapid production of offspring who require substantial calories yet who cannot support themselves for a decade or more limits their number to about four. This limit is reached after 6-7 births spaced 3 years apart (with high infant mortality), i.e., about 20 years after age at first birth. Nevertheless, age-related increases in the costs of pregnancy and childbirth could be additional factors favoring menopause.
Second, juvenile productivity plays little role in the Kaplan et al. (2010) model but an important role in the simulations, where, in combination with reproductive cessation, the increasing productivity of older juveniles (Pretelli et al., 2024, 2022) helps families escape an energy deficit. Moreover, without juvenile production, families would be in a pronounced negative energy balance for most of the wife’s lifespan that the few years of surplus could not offset Figure S8.
Third, although I have framed the simulations in terms of nuclear families comprising a wife and husband in a lifelong monogamous relationship raising their joint offspring — a key assumption of the Kaplan et al. (2010) “two sex” model — the results of the simulations do not rely on this assumption. The results are equally consistent with, e.g., a pooled energy model (Kramer & Ellison, 2010) in which all females reproduce (i.e., no non-reproductive females) and all individuals pool their resources to provision every member of the community according to their needs. The potential midlife energetic crisis is simply a consequence of producing offspring every three years who require substantial calories to reach adulthood yet cannot provide all those calories themselves for a decade or more. In this regard, results are also consistent with the venerable grandmother hypothesis (Hawkes, 2020). Note, however, that the simulations do not address the collective action problems or other evolutionary challenges of energy transfers. They also do not take into account that in real families and communities, parents and children adjust the time devoted to production in response to changes in demand (e.g., Kramer, 2005).
Although ceasing reproduction midlife and transferring energy surpluses are key to averting an energetic crisis, the increasing productivity of dependent offspring is also key. Yet in mobile hunter-gatherers ranging over a large, spatially and temporally varying landscape replete with competitors, predators, and other sundry hazards (e.g., Blurton Jones et al., 1994), child productivity in ancestral foraging bands would have depended on foraging bands moving to the right place at the right time (Bettinger & Grote, 2016; Hamilton et al., 2016). Embodied capital should therefore be conceptualized not only as the skills required to extract energy from a resource patch, but also as including the skills required to locate optimal resource patches.
Older mothers and fathers would have had greater knowledge of the large ranges necessary to support the hunting and gathering lifestyle of a large-bodied hominin (Antón, 2002), and hence greater ability to lead their families to productive resource patches, a perspective that aligns with theories of menopause in toothed whales that emphasize the superior ecological knowledge of older matriarchs (Brent et al., 2015; Rendell et al., 2019), and given the lower mortality of females, perhaps also aligns with the predominance of female-biased leadership of collective movements in social mammals (Smith et al., 2022). It is also consistent with the anthropology of older women in traditional societies who increasingly take on important social roles (Brown, 1982; Jang et al., 2025), with research on the important ecological knowledge of older individuals in foraging societies (e.g., Biesele & Howell, 1981; Scalise Sugiyama, 2011; Wiessner, 2014; Wood et al., 2024), and with the computational services model, which emphasizes the cognitive challenges of raising multiple dependent offspring (Hagen et al., 2025).
Concluding remarks
The ECM (Kaplan et al., 2010, 2000) is a leading explanation for the evolution of the distinctive human life history pattern involving relatively short interbirth intervals and long periods of dependency. Simulation results suggest that menopause was integral to the evolution of this pattern because it averted a midlife energetic crisis threatened by the rapid production of large bodied and large brained, and thus energetically expensive juveniles who would not become self-sufficient for a decade or more. Juveniles were subsidized, in part, by their older, newly mated siblings who, in ethnographically documented hunter-gatherers, often lived with either the wife’s or husband’s parents (Hill et al., 2011). The new couples, initially with few or no children of their own, produced an energetic surplus that could benefit, e.g., the wives’ younger siblings during brideservice (Walker et al., 2011). Couples’ later midlife reproductive cessation (menopause) optimized their family size at an energetically sustainable level as the energy production of their children ramped up (a variant of the mother hypothesis, albeit here also including fathers and older children), and energy transfers from couples’ parents, whose children have mostly dispersed, burgeoned (the grandmother hypothesis, albeit here also including grandfathers). Post-menopause couples with fewer but increasingly productive offspring (Pretelli et al., 2024, 2022) then became energetically self-sustaining, and finally energetically “profitable”, with the capacity to invest in their children’s families. High juvenile productivity probably depended on judicious resource patch choice by older individuals with substantial ecology knowledge, per the ECM.
Acknowedgements
Thanks to Ray Hames, Nicole Hess, Ilaria Pretelli, Erik Ringen, and Eric Schniter for helpful comments.
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Supplementary information
Hunter-gatherer demography and life history
Simulated energy balance
Parameter variation
