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Annual Review of Psychology
Developmental Adaptation to
Stress: An Evolutionary
Perspective
Bruce J. Ellis1and Marco Del Giudice2
1Department of Psychology and Department of Anthropology, University of Utah, Salt Lake
City, Utah 84112, USA; email: bruce.ellis@psych.utah.edu
2Department of Psychology, University of New Mexico, Albuquerque, New Mexico 87131, USA
Annu. Rev. Psychol. 2019. 70:111–39
First published as a Review in Advance on
August 20, 2018
The Annual Review of Psychology is online at
psych.annualreviews.org
https://doi.org/10.1146/annurev-psych- 122216-
011732
Copyright c
⃝2019 by Annual Reviews.
All rights reserved
Keywords
developmental plasticity, developmental programming, differential
susceptibility, evolution, life history theory, puberty, childhood stress,
stress response systems
Abstract
The assumption that early stress leads to dysregulation and impairment is
widespread in developmental science and informs prevailing models (e.g.,
toxic stress). An alternative evolutionary–developmental approach, which
complements the standard emphasis on dysregulation, proposes that early
stress may prompt the development of costly but adaptive strategies that pro-
mote survival and reproduction under adverse conditions. In this review, we
survey this growing theoretical and empirical literature, highlighting recent
developments and outstanding questions. We review concepts of adaptive
plasticity and conditional adaptation, introduce the life history framework
and the adaptive calibration model, and consider how physiological stress re-
sponse systems and related neuroendocrine processes may function as plas-
ticity mechanisms. We then address the evolution of individual differences
in susceptibility to the environment, which engenders systematic person–
environment interactions in the effects of stress on development. Finally,
we discuss stress-mediated regulation of pubertal development as a case
study of how an evolutionary–developmental approach can foster theoretical
integration.
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Contents
OVERVIEW...................................................................... 112
BEYOND DYSREGULATION: DEVELOPMENTAL PLASTICITY
ANDCONDITIONALADAPTATION ....................................... 113
Life History Theory as a Framework for Adaptive Plasticity . . . . . . . . . . . . . . . . . . . . . . 115
OutstandingQuestions andChallenges.......................................... 116
BEYOND ALLOSTATIC LOAD: STRESS RESPONSE SYSTEMS
AS MECHANISMS OF CONDITIONAL ADAPTATION . . . . . . . . . . . . . . . . . . . . . 117
The Adaptive Calibration Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
Comparing the Adaptive Calibration Model and Allostatic Load Model . . . . . . . . . . . 120
OutstandingQuestions andChallenges.......................................... 122
BEYOND DIATHESIS STRESS: DIFFERENTIAL SUSCEPTIBILITY
TOTHE ENVIRONMENT................................................... 122
Models of Differential Susceptibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Markers of Susceptibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
OutstandingQuestions andChallenges.......................................... 126
BEYOND FRAGMENTATION: TOWARD AN INTEGRATED THEORY
OF STRESS, DEVELOPMENTAL ADAPTATION, AND HEALTH . . . . . . . . . . 127
Timingof Puberty:ACase Study................................................ 127
An Evolutionary–Developmental Theory of Pubertal Variation . . . . . . . . . . . . . . . . . . . 128
Accelerated Pubertal Maturation Trades Off Against Health . . . . . . . . . . . . . . . . . . . . . . 129
Stress Response Systems as Mediating Mechanisms in Stress–Puberty Relations. . . . 129
Importance of Differential Susceptibility in Regulation of Pubertal Timing . . . . . . . . 130
CONCLUSION.................................................................. 131
OVERVIEW
A widespread assumption in developmental science is that children raised in supportive and well-
resourced environments (e.g., those who live in communities with social networks and resources
for young people, who have strong ties to schools and teachers, and who benefit from nurturing and
supportive parenting) tend to develop normally and express optimal trajectories and outcomes.
By contrast, children raised in high-stress environments (e.g., those who experience poverty,
discrimination, and community disorganization; who feel disconnected from teachers and schools;
and who experience high levels of family conflict) are at risk for developmental dysregulation,
leading to impaired functioning and problem behaviors that are destructive to themselves and
others. These assumptions are powerful and pervasive, if usually implicit, and underlie prominent
models of development that focus on dysregulation and pathology [e.g., models of cumulative
risk (Evans et al. 2013), toxic stress (Shonkoff et al. 2012), and allostatic load (Lupien et al. 2006,
McEwen & Stellar 1993)].
In this review, we survey a growing theoretical and empirical literature focused on the idea that
stressful environments may prompt the development of costly but potentially adaptive strategies.1
This evolutionary–developmental perspective suggests that at least some of the outcomes of early
1The term adaptive in biology refers strictly to reproductive fitness and does not imply that a trait is socially desirable or
conducive to well-being; this is discussed in greater detail below.
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adversity may represent not dysfunction, but rather biologically adaptive strategies for dealing
with adversity (e.g., Belsky et al. 1991, Ellis & Del Giudice 2014, Ellis et al. 2017a, Frankenhuis
et al. 2016b). This emphasis on developmental adaptation to stress complements the standard
emphasis on dysregulation and negative health consequences. We do not deny or downplay the
costs of adaptations to adversity, which may include risk for genuine pathology and dysregulation.
However, as a counterpoint to the nearly exclusive focus on pathology and dysregulation in the
developmental literature, we concentrate on the potential for adaptation. Our goal is to introduce
the reader to key ideas and findings, summarize the present state of knowledge, and consider some
of the challenges and outstanding questions that face researchers in this area.
In the next section, we review the concepts of developmental plasticity and conditional adapta-
tion, introducing life history theory as a useful framework to conceptualize the effects of early stress
across behavioral, physiological, and developmental phenotypes. Next we consider how stress re-
sponse systems and related neuroendocrine processes may function as mechanisms of plasticity,
collecting information about key aspects of the environment and translating it into broad patterns
of life history–relevant traits. We highlight the adaptive calibration model (ACM; Del Giudice
et al. 2011), a theory of adaptive individual differences in stress physiology that contrasts with
disease-focused models such as allostatic load and toxic stress. The next section addresses indi-
vidual differences in susceptibility to the environment. The effects of stress are moderated by
individual factors, giving rise to systematic person–environment interactions. We review the main
evolutionary models of differential susceptibility and discuss empirical research on the genetic,
physiological, and behavioral mediators of plasticity. Finally, in the section titled Beyond Frag-
mentation: Toward an Integrated Theory of Stress, Developmental Adaptation, and Health, we
use the example of timing of pubertal maturation to illustrate how biological embedding of early
adversity can both impair development and guide it in an adaptive manner by promoting survival
and reproduction under more harsh and unpredictable conditions, despite the attendant costs to
health and well-being. We conclude that it is necessary to understand developmental adaptations
to stress—the coherent, functional changes that occur in response to adversity—to understand
the costs associated with these adaptations (e.g., allostatic load and its consequences).
BEYOND DYSREGULATION: DEVELOPMENTAL PLASTICITY
AND CONDITIONAL ADAPTATION
Theory and research in evolutionary biology have come to acknowledge that, in most species, a
single best strategy for survival and reproduction is unlikely to evolve. Instead, the locally optimal
strategy normally varies as a function of three overarching factors (see Ellis & Del Giudice 2014).
First, the costs and benefits of different strategies depend on the physical and social parameters of
an organism’s environment (e.g., food availability, mortality rates, quality of parental investment,
social competition). This context dependency means that a strategy that promotes success in some
environmental contexts may lead to failure in others. Second, the success and failure of different
strategies depend on an organism’s internal condition and competitive abilities relative to other
members of the population (e.g., age, body size, health, history of wins and losses in agonistic
encounters). Third, an organism’s sex often has important implications for the range of available
strategies and their relative costs and benefits.
Because the viability of different survival and reproductive strategies is context and con-
dition dependent, natural selection tends to favor adaptive developmental plasticity, whereby
evolved mechanisms reliably guide the development of alternative phenotypes (including anatomy,
physiology, and behavior) to match an organism’s internal condition and external environment
(see West-Eberhard 2003). Developmental plasticity involves “durable biological change in the
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structure or function of a tissue, organ, or biological system” (Kuzawa & Quinn 2009, p. 132).
Importantly, adaptive developmental plasticity is a nonrandom process; it is the outcome of struc-
tured interplay between the organism and its environment, shaped by natural selection to increase
the capacity of individuals to track both their internal condition and their external environments
and, integrating this information, to adjust the development of their phenotypes accordingly.
The occurrence of developmental plasticity, which is ubiquitous in the animal world, is un-
controversial (for extensive reviews, see DeWitt & Scheiner 2004, West-Eberhard 2003). For
example, it is widely recognized that harsh developmental conditions, such as exposure to a sub-
optimal intrauterine environment, can induce durable biological changes in the phenotype (e.g.,
Conradt et al. 2018). The question is whether exposures to physical and psychosocial stressors
simply constrain development, as assumed in dysregulation models, or guide it in an adaptive
manner.
From an evolutionary perspective, developmental plasticity is critically important for enabling
organisms to adapt to stressful conditions. Stress and adversity have always been part of the
human experience. Indeed, almost half of children in hunter–gatherer societies—the best model
for human demographics before the agricultural revolution—die before reaching adulthood (e.g.,
Volk & Atkinson 2013). Thus, from an evolutionary–developmental perspective, stressful rearing
conditions, even if those conditions engender sustained stress responses that must be maintained
over time, should not so much impair neurobiological systems as direct or regulate them toward
patterns of functioning that are adaptive under stressful conditions (Ellis & Del Giudice 2014,
Ellis et al. 2012a).
Because adaptive developmental plasticity involves durable change, it is inherently forward
looking; that is, it involves predicting—and preparing—for future conditions (both internal and
external). Boyce & Ellis (2005, p. 290) make preparation for future environments explicit in their
definition of conditional adaptation: “evolved mechanisms that detect and respond to specific
features of childhood environments, features that have proven reliable over evolutionary time
in predicting the nature of the social and physical world into which children will mature, and
entrain developmental pathways that reliably matched those features during a species’ natural
selective history.” A similar emphasis on forward-looking adaptation (focusing on potential later
fitness advantages) is conveyed by the phrase predictive adaptive response, which is often used to
describe the long-lasting effects of prenatal nutrition, exposure to maternal stress hormones, and
other early environmental factors (Bateson et al. 2014). Predictive adaptive responses need to be
distinguished from immediate adaptive responses, a term that refers to phenotypic responses that
afford immediate adaptive benefits (as when a fetus accelerates parturition in the context of an
infected uterus) (Bateson et al. 2014).
Developmental plasticity necessitates developmental trade-offs. For example, tadpoles (Rana
sylvatica) alter their size and shape based on the presence of dragonfly larvae in their rearing
environment (Van Buskirk & Relyea 1998). These alterations involve development of smaller and
shorter bodies and deep tail fins. Although tadpoles that do not undergo these morphological
changes are highly vulnerable to predation by dragonflies, those that do but end up inhabiting
environments that are not shared with dragonflies have relatively poor developmental and survival
outcomes. In short, the predator-induced phenotype is only conditionally adaptive. This process
highlights the fact that, in many cases, natural selection favors a primary phenotype that yields
high payoffs under favorable circumstances and a secondary phenotype that makes the best of a
bad situation (West-Eberhard 2003). Adaptations to adversity often entail significant costs and
drawbacks, even when they enhance an individual’s survival and reproduction prospects.
A conditional adaptation perspective has been applied not only to the development of person-
ality traits such as aggression, impulsivity, and risk taking (e.g., Belsky et al. 1991, Daly & Wilson
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2005, Del Giudice 2015b, Ellis et al. 2012a), but also to cognitive abilities such as enhanced
stimulus-response learning and executive function components relevant to monitoring changes in
the environment (e.g., the ability to rapidly switch between tasks and update working memory)
(Mittal et al. 2015, Young et al. 2018; for a review, see Ellis et al. 2017a). Such cognitive traits can
be especially useful in unpredictable and fluctuating contexts.
Life History Theory as a Framework for Adaptive Plasticity
In evolutionary biology, a major framework for explaining coordinated patterns of developmen-
tal plasticity is life history theory (see Del Giudice et al. 2015, Ellis et al. 2009). Life history
theory addresses how organisms allocate their limited stocks of time and energy to the various
activities (including growth, maintenance of bodily tissues, mating, and parenting) that compose
their life cycle. Since all of these activities ultimately contribute to the organism’s fitness, devot-
ing time and energy to one will typically involve both benefits and costs, engendering trade-offs
between different fitness components. Natural selection favors organisms that schedule develop-
mental activities so as to optimize resource allocation. The resulting chain of resource-allocation
decisions—expressed in the development of an integrated suite of physiological and behavioral
traits—constitutes the individual’s life history strategy. An organism’s life history strategy coor-
dinates morphology, physiology, and behavior in ways that maximize expected fitness in a given
environment (Ellis et al. 2009).
The critical decisions involved in a life history strategy can be summarized by the fundamental
trade-offs between current and future reproduction, between quality and quantity of offspring,
and—in sexually reproducing species—between mating and parenting effort (see Del Giudice
et al. 2015). At the broadest level of analysis, life history–related traits covary along a dimension
of slow versus fast life history. Variation along the slow–fast continuum is observed both between
related species and between individuals of the same species ( Jeschke et al. 2008, R ´
eale et al.
2010). In humans, some individuals adopt slower strategies characterized by later reproductive
development (especially in girls) and delayed sexuality, preferences for stable pair bonds and high
investment in parenting, an orientation toward future outcomes, low impulsivity, and allocation
of resources toward enhancing long-term survival; others display faster strategies characterized
by the opposite pattern (Belsky 2012, Belsky et al. 1991, Del Giudice et al. 2015, Ellis et al. 2009,
Figueredo et al. 2006). Fast life history strategies are comparatively high risk, focusing on mating
opportunities (including more risky and aggressive behavior), reproducing at younger ages, and
producing a greater number of offspring with more variable outcomes. Trade-offs incurred by
faster strategies include reduced health, vitality, and longevity (as discussed in the section titled
Beyond Fragmentation: Toward an Integrated Theory of Stress, Developmental Adaptation, and
Health).
In most organisms, individual life histories are determined by a combination of genetic and
environmental factors and often exhibit a remarkable degree of developmental plasticity. Key
dimensions of the environment that regulate the development of life history strategies include en-
ergy availability, extrinsic morbidity–mortality, and predictability of environmental change (Del
Giudice et al. 2015, Ellis et al. 2009). Energetic resources—caloric intake, energy expenditures,
and related health conditions—set the baseline for many developmental processes. Energy scarcity
slows growth and delays sexual maturation and reproduction, resulting in slower life history strate-
gies. However, when bioenergetic resources are adequate to support growth and development,
cues to extrinsic morbidity–mortality and unpredictability generally promote faster strategies.
Extrinsic morbidity–mortality refers to external sources of disability and death that are rela-
tively insensitive to the adaptive decisions of the organism. Environmental cues indicating high
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levels of extrinsic morbidity–mortality (e.g., exposures to violence, harsh child-rearing practices,
premature disability and death of other individuals in one’s local ecology) cause individuals to de-
velop faster life history strategies. Faster strategies in this context—a context that devalues future
reproduction—function to reduce the risk of disability or death prior to reproduction. Moreover,
high extrinsic morbidity–mortality means that investing in parental care has quickly diminishing
returns, which favors reduced parental investment and offspring quantity over quality. In research
on industrialized populations, extrinsic morbidity–mortality is often operationalized in terms of
socioeconomic adversity because of the relationship between poverty and higher levels of virtu-
ally all forms of morbidity and mortality. However, some studies have also collected measures
of local mortality rates, developmental exposures to death and injury, or perceived danger in the
environment (e.g., Chang & Lu 2018, Copping & Campbell 2015, Johns 2011).
In addition to extrinsic morbidity–mortality, environmental unpredictability also regulates
development of life history strategies. In terms of evolutionary selection pressures, environmental
unpredictability has been defined as variation in extrinsic morbidity–mortality (Ellis et al. 2009). In
terms of adaptively calibrating developmental strategies, cues to environmental unpredictability
have typically been operationalized as stochastic changes in ecological and familial conditions
(e.g., Belsky et al. 2012, Simpson et al. 2012). In environments that fluctuate unpredictably,
long-term investment in development of a slow life history strategy may not optimize fitness.
Individuals should instead detect and respond to signals of environmental unpredictability (e.g.,
erratic neighborhood conditions, frequent residential changes, fluctuating economic conditions,
changes in family composition) by adopting faster strategies.
Since danger and unpredictability are core defining features of stress, life history theory of-
fers integrative principles for making predictions about how early stress shapes the development
of multiple behavioral traits, as well as the associations of these traits with patterns of growth,
sexual maturation, metabolism, immunity, and other life history–related systems. The life his-
tory perspective has inspired developmental research on the links between familial and ecological
stress and later outcomes such as impulsivity and risk taking, pubertal maturation, sexual be-
havior, reproductive timing, and health (e.g., Belsky et al. 2012, 2015b; Brumbach et al. 2009;
Copping & Campbell 2015; James et al. 2012; Mell et al. 2018; Sheppard et al. 2016; Simpson
et al. 2012; Sung et al. 2016; Szepsenwol et al. 2015). This work has been especially important
in advancing our understanding of the key distinction between childhood exposures to extrinsic
morbidity–mortality cues and environmental unpredictability (Ellis et al. 2009), each of which has
been found to uniquely predict the development of life history–related traits and associated health
outcomes.
Outstanding Questions and Challenges
The biological concept of plasticity, when applied to human development, brings with it some
important insights but also many complex problems and questions. For example, standard models
of plasticity assume that early stress carries predictive information about the future state of the en-
vironment (e.g., danger and consequent high mortality). An alternative (though not incompatible)
possibility is that early stress inflicts irreparable damage to the developing organism; in this view,
plasticity mechanisms respond to the individual’s compromised internal state and not to hypothet-
ical cues about its future environment (Rickard et al. 2014). Distinguishing between external and
internal (or somatic state–based) accounts of plasticity is going to require much careful empirical
work, as well as more refined theoretical models than are currently available (see Del Giudice
2014a, Hartman et al. 2017). Other important questions concern specific sensitive periods for the
effects of early stress and their evolutionary logic. The idea that the period from conception to
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the end of early childhood (i.e., the first 5–7 years of life) is especially critical is widespread in the
literature. However, the duration of sensitive windows may itself depend on earlier experiences
(Fawcett & Frankenhuis 2015); moreover, a long-lived species like ours may be characterized by
multiple windows of plasticity, including key developmental transitions such as the beginning of
middle childhood and the onset of puberty (see Del Giudice 2014b, Del Giudice & Belsky 2011,
Ellis 2013, Shulman et al. 2016).
Developmental research based on life history concepts faces similar challenges. There is still
much that we do not know about life history strategies, especially when moving from consider-
ing evolution within a population (the standard focus of biological models) to considering de-
velopment within a single individual (see Mathot & Frankenhuis 2018). Mathematical models
of life history evolution also raise the possibility that some long-term outcomes of early stress
are the legacy of immediate adaptive responses for infant survival, rather than adult adapta-
tions for mating and reproduction (i.e., predictive adaptive responses; see Wells & Johnstone
2017). Within evolutionary psychology, there is a lively ongoing debate about the best way to
measure life history–related behavioral traits and integrate them with demographic traits such
as puberty and reproductive timing (e.g., Black et al. 2017, Richardson et al. 2017). The in-
ferences that can be drawn from human research are also limited by the widespread lack of
control for potential genetic confounding in developmental studies that correlate early envi-
ronmental variables with later outcomes (see Barbaro et al. 2017). The problem of genetic con-
founding has been addressed in a minority of studies (e.g., Ellis et al. 2012b, Tither & Ellis
2008); fortunately, more researchers are starting to explicitly incorporate genetic information (e.g.,
Gaydosh et al. 2018), and the results will undoubtedly prompt revisions and refinements of current
ideas.
BEYOND ALLOSTATIC LOAD: STRESS RESPONSE SYSTEMS
AS MECHANISMS OF CONDITIONAL ADAPTATION
How does repeated or chronic childhood adversity shape biobehavioral development and, through
it, mental and physical health? There is widespread agreement in the developmental literature
that early life adversities (both prenatal and postnatal) can cause enduring changes in biological
and developmental systems (i.e., biological embedding) that affect health and behavior over the
life course (e.g., Hertzman 2012). Controversy exists, however, regarding the functional versus
dysfunctional role of biological embedding in regulating (or dysregulating) the development of
the phenotype.
In developmental models that are primarily focused on explaining dysregulation, such as mod-
els of toxic stress (Shonkoff et al. 2012) and allostatic load (Lupien et al. 2006, McEwen &
Stellar 1993), biological embedding is construed negatively. These models postulate that biolog-
ical responses to stress are usually beneficial in the short term (i.e., that they facilitate immediate
adaptive responses), but protracted activation of stress responsive systems is maladaptive and toxic
in the long term. From this perspective, biological embedding of early life stress causes disruptions
of brain structure and function, resulting in dysregulation of physiological mediators—autonomic,
neuroendocrine, metabolic, and immune—that are “the precursors of later impairments in learning
and behavior as well as the roots of chronic, stress-related physical and mental illness” (Shonkoff
et al. 2012, p. e236). As eloquently stated by Juster and colleagues (2011, p. 725), the wear and
tear of toxic stress and altered stress hormone functioning “inexorably strains interconnected
biomarkers that eventually collapse like domino pieces trailing toward stress-related endpoints.”
Allostatic load is a term used to describe the wear and tear that results from repeated allo-
static adjustments (i.e., adaptation to stressors), which expose one to adverse health consequences
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that increase as a person ages. According to the allostatic load model (ALM), there is an optimal
level of stress responsivity, and both hyper- and hypo-activation of physiological mediators are
routinely described as dysfunctional deviations from the norm, usually caused by a combination
of excessive stress exposure and genetic or epigenetic vulnerability. In this framework, develop-
mental stress exposures are regarded as risk factors for a wide array of symptoms and disorders.
While some authors have argued that optimal adaptation is fostered by environments that con-
tain moderate amounts of stressors (e.g., Rutter 1993), the underlying assumption remains that
a single best environment exists, and that deviations from that optimum cause dysregulation and
pathology.
Accepting these assumptions without placing them in a larger evolutionary–developmental
framework has likely impeded our understanding of the role of stress response systems in adap-
tively regulating development (see Ellis & Del Giudice 2014). Specifically, models of allostatic
load focus on the long-term costs of childhood stress and adversity—the wear and tear on multiple
organ systems induced by chronic stress—but do not address the benefits of calibrating autonomic,
neuroendocrine, metabolic, and immune systems to match current and future environments (i.e.,
predictive adaptive responses). We argue that this overemphasis on costs misses something fun-
damental about developmental adaptation to stress and thus weakens the conceptual power of the
ALM. The result has been an imbalanced approach to research that has yielded dramatically more
empirical knowledge about dysfunction than about adaptive function, making it difficult to gain a
coherent big picture of the subject matter.
The Adaptive Calibration Model
A promising alternative to the ALM is provided by the ACM (Del Giudice et al. 2011), a theory of
individual differences in stress responsivity that builds on the concepts of life history theory and
developmental plasticity. The ACM supplements the ALM and revises some of its key assumptions,
thus laying the foundation for a broad theory of individual differences (for a more extended
discussion, see Ellis & Del Giudice 2014). The central tenet of the ACM is that physiological
stress response systems, including the autonomic nervous system and the hypothalamic–pituitary–
adrenal (HPA) axis, operate as mechanisms of conditional adaptation, with a key role in regulating
the development of individual life history strategies.
In the ACM, the activation of autonomic and adrenocortical responses during childhood pro-
vides crucial information about threats and opportunities in the environment, their type, and their
severity. Over time, this information becomes embedded in the parameters—recurring set points
and reactivity patterns—of these physiological systems, which in turn provide the developing
person with statistical summaries of key dimensions of the environment. For example, sustained
activation of the HPA axis is generated by exposures to danger, unpredictable or uncontrollable
contexts, and social evaluation, as well as by energetic stress (Dickerson & Kemeny 2004); thus, the
HPA axis tracks the key environmental variables involved in regulation of alternative life history
strategies. In turn, individual differences in the functioning of stress response systems regulate the
coordinated development of a broad cluster of life history–related physiological and psychological
traits, including growth and maturation, sexual and reproductive functioning, social learning, ag-
gression, competition and risk taking, pair bonding, and related factors (Del Giudice et al. 2011,
Ellis & Del Giudice 2014). Other systems that contribute to life history regulation include the
hypothalamic–pituitary–gonadal axis; the serotonergic, dopaminergic, and oxytocinergic systems;
and the immune system (discussed in more detail below). Not coincidentally, all of these sys-
tems engage in extensive bidirectional cross talk with stress response systems (for reviews, see Del
Giudice et al. 2011, Ellis & Del Giudice 2014).
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Patterns of stress responsivity. In contrast to the notion of a single optimal stress responsivity
pattern (as per the ALM), the ACM proposes that two different adaptive patterns of stress re-
sponsivity emerge in the context of high childhood adversity. The first pattern, labeled vigilant, is
characterized by heightened physiological stress reactivity (across the sympathetic nervous system
and HPA axis) and is predicted to develop in dangerous or unpredictable contexts, where it enables
people to cope with threats in their physical and social environment. In the ACM, the vigilant
profile mediates heightened vigilance and attention to threats; it is associated with elevated lev-
els of anxious and depressed behaviors (especially in females) and increased risk taking, agonistic
social competition, and reactive aggression (especially in males), consistent with a fast life history
strategy. The second pattern, labeled unemotional, is characterized by low physiological stress
reactivity across autonomic and adrenocortical systems and is predicted to develop under condi-
tions of severe, chronic stress. According to the ACM, generalized unresponsivity in this context
inhibits sensitivity to social feedback and can increase risk taking by blocking information about
dangers and threats in the environment (e.g., leading to low anxiety). In line with a fast life history
strategy, the unemotional profile is associated with low empathy and cooperation, impulsivity,
competitive risk taking, and antisocial behavior, including high levels of proactive and instrumen-
tal aggression, especially in males. The hypothesized vigilant and unemotional profiles, reflecting
the emergence of both high and low stress responsivity patterns in the context of adversity, have
been documented in longitudinal studies of Dutch adolescent males (Ellis et al. 2017c) and chil-
dren in the United States (Laurent et al. 2014), although with some deviations from expected
patterns (for a discussion, see Ellis et al. 2017b).
More generally, psychosocial stress and adversity over the course of development can either
upregulate or downregulate levels of autonomic and adrenocortical reactivity. The empirical lit-
erature on this topic remains conflicted. On the one hand, many studies link stressful rearing
experiences to hyper-reactivity, supporting the vigilant responsivity pattern; on the other hand,
an equally impressive number of studies link stressful rearing experiences to hypo-reactivity, sup-
porting an unemotional responsivity pattern (for reviews, see Del Giudice et al. 2011, Ellis et al.
2017b). In the ACM, we proposed that some children who grow up under high-stress conditions
will first develop high stress responsivity in early childhood (vigilant profile), then shift to low
responsivity during juvenility or adolescence (unemotional profile) as social competition becomes
a central developmental task. We also hypothesized that this trajectory would be more common
in males (Del Giudice et al. 2011). A shift from hyper- to hypo-reactivity may help to explain an
otherwise puzzling finding in the literature: that the overall association between basal cortisol lev-
els and aggressive/externalizing behavior tends to be positive in preschoolers but negative starting
from middle childhood (Alink et al. 2008).
The proposed developmental transition from a vigilant to an unemotional profile has been
demonstrated in longitudinal studies of individuals with a history of child maltreatment. Doom
et al. (2014) reported that such individuals transitioned from initially high levels of basal afternoon
cortisol to blunted levels in middle childhood. Likewise, Trickett et al. (2010) found that females
with a history of child sexual abuse transitioned across development from initially elevated levels
of morning cortisol to attenuated levels starting in adolescence, whereas females who were not
sexually abused maintained similar normative morning cortisol levels across development. Con-
sistent with the unemotional responsivity pattern, youth exposed to maltreatment also display
blunted cortisol reactivity by early adolescence, and this effect tends to be stronger in boys than
in girls when contrasting maltreated and comparison groups (see Trickett et al. 2014, figure 2). A
similar sex-specific effect was found in a recent study in South Africa: Adverse childhood experi-
ences predicted blunted cortisol reactivity in boys but increased reactivity in girls (Fearon et al.
2017).
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The hypothesized developmental transition from a vigilant to an unemotional profile converges
with the well-established pattern of HPA responses to chronic stress: Initially, stressors tend to
acutely upregulate basal cortisol levels in the time period proximal to stressor onset; however,
over time, severe chronic stress exposures tend to downregulate hormonal output and elicit a flat
diurnal cortisol rhythm (for a meta-analysis, see Miller et al. 2007). Extending these findings on
basal cortisol activation, a meta-analysis of cortisol responsivity to social stress (Bunea et al. 2017)
found that early life adversity was robustly associated with blunted cortisol reactivity in adults
(large effect) but not in children and adolescents (small effect). Given the focus of this meta-
analysis on adverse childhood experiences that were typically chronic and severe, the results are
consistent with the ACM’s proposed developmental transition to an unemotional profile under
high-stress conditions.
Extending the adaptive calibration model: adaptive calibration of the immune system.
Another mechanism through which childhood adversity may promote faster life history strategies
is through calibration of immune system parameters. As reviewed by Nusslock & Miller (2016),
childhood stress exposures sensitize cortico-amygdala neural circuitry in a manner that enhances
vigilance and threat processing, and they alter the activity of immune cells in a manner that
promotes and sustains inflammation. For example, greater family stress, trauma, and adversity are
associated with heightened amygdala reactivity to negative emotional stimuli (e.g., Herringa et al.
2016), higher concentration of inflammation-related molecules (e.g., Baumeister et al. 2016), and
profiles of gene expression consistent with a proinflammatory phenotype (e.g., Robles et al. 2018).
Nusslock & Miller (2016, p. 25) proposed that cortico-amygdala threat circuitry and immune
cells that propagate inflammation are “components of an integrated, bidirectional network that
detects threats to well-being and mobilizes behavioral, physiologic, and inflammatory resources
for coping.” Most importantly, cross talk between these two components appears to be potentiated
by early adversity. Nusslock & Miller (2016) conceptualized this enhanced cross talk as promoting
immediate adaptive responses to danger, as when brain-to-immune signaling readies the immune
system for pathogen eradication and tissue healing, or when immune-to-brain signaling enhances
threat vigilance. In the long run, these processes may contribute to the pathogenesis of emotional
and physical health problems.
The relationship between immune functioning and life history strategies is most likely bidi-
rectional. Like stress response systems, the immune system collects and relays information about
important sources of danger and mortality, specifically the prevalence and type of pathogens in the
local environment and the individual’s ability to effectively cope with them. Thus, early immune
activity should contribute to the development of alternative life history strategies (e.g., Hill et al.
2016, Kopp & Medzhitov 2009). At the same time, different life history strategies can be expected
to entail different patterns of investment in immune defenses. For example, researchers have be-
gun to examine the possibility that faster life history strategies may predict increased investment
in innate immunity (including inflammation) at the expense of acquired immunity (Georgiev et al.
2016).
Comparing the Adaptive Calibration Model and Allostatic Load Model
The ACM and ALM diverge considerably in how they deal with cost–benefit trade-offs, individual
differences, and long-term developmental changes.
Different views of cost–benefit trade-offs in development. In an evolutionary framework, the
terms adaptive and maladaptive denote the effect of a trait or behavior on biological fitness. From
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the standpoint of the individual organism, adaptive traits are those that enhance its expected fitness
more than do potential alternatives. However, all adaptations have fitness costs as well as benefits;
to be adaptive, a trait does not have to be cost free, but only to yield a positive overall contribution
to fitness. This notion of adaptation and maladaptation contrasts sharply with how the same terms
are usually employed in health- and disease-focused disciplines, wherein adaptive refers to traits
and behaviors that are socially desirable (e.g., that promote health, safety, subjective well-being,
and mutually rewarding social relations), while maladaptive refers to traits and behaviors that are
socially undesirable (e.g., that have aversive or health-damaging effects).
The ALM makes no distinction between these two meanings of adaptive and maladaptive.
Indeed, maladaptation is typically inferred whenever there are substantial costs to the organism.
For example, if elevated cortisol levels in adolescents are associated with an undesirable outcome,
such as reduced working memory, then elevated cortisol is deemed maladaptive (and classified
as a biomarker of allostatic load) (see Juster et al. 2011). This reasoning ignores the crucial fact
that biological processes are maintained by natural selection when their fitness benefits outweigh
the costs, not when they are cost free; indeed, even large costs can be offset by large enough
expected benefits. Because of the failure to distinguish between (mal)adaptive and (un)desirable
outcomes, most applications of the ALM do not adequately address the trade-offs involved in the
development of physiological and behavioral phenotypes; as a consequence, the ALM literature
often lacks a theory of adaptive individual variation in stress responsivity. In the ALM, the focus
is on optimal parameter values of stress response systems, as defined by covariation with desirable
health outcomes; deviations from these optimal settings form the basis of dysregulation.
In contrast, the ACM emphasizes adaptation in context and posits that optimal stress response
parameters vary as a function of environmental conditions, as illustrated by the vigilant and un-
emotional responsivity patterns. From this perspective, the notion of globally optimal responsivity
levels is problematic. For example, consider heightened stress responsivity in dangerous, unpre-
dictable environments (as in the vigilant pattern). In the ACM, it is hypothesized that the costs of
repeated stress system activation are offset by improved management of danger (Del Giudice et al.
2011). Although the system is on a hair trigger, with a resulting increase in anxiety or aggression,
few instances of actual danger will be missed. In addition, engaging in a fast, present-oriented
life history strategy makes it optimal to discount the long-term health costs of chronic activation
of stress response systems if the immediate benefits are large enough. In the ALM framework,
the same pattern of responsivity would be treated as dysfunctional because the stress response is
deployed even in the absence of true dangers (resulting, for example, in excessive responding or
unnecessary triggering) (e.g., Lupien et al. 2006) and because of the associated undesirable states
and health risks (e.g., anxiety, increased cardiovascular risk).
Different views of long-term adaptations to stress. According to the ACM, childhood adap-
tations to stress may eventuate in long-term adaptive changes in biobehavioral systems. Herein
lies the key difference between the ACM and ALM. In the ALM, energy devoted to mount-
ing autonomic, neuroendocrine, metabolic, and immune responses to threat (immediate adaptive
responses) is traded off against wear and tear on multiple organ systems. This wear and tear,
according to the ALM, results in dysfunctional changes in the regulatory parameters of stress re-
sponse systems (i.e., dysregulation). These biologically embedded changes are commonly viewed
as indicators of allostatic load, reflecting the costs of stress-induced trade-offs; they are explicitly
not viewed as predictive adaptive responses. By contrast, the ACM conceptualizes these trade-offs
as decision nodes in allocation of resources. Through biological embedding, each decision node
influences the next (opening up some options, foreclosing others), thus progressively favoring one
developmental trajectory over another. Predictive adaptive responses are instantiated through this
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chain of resource-allocation decisions, which calibrates the developing phenotype to current (and
expected future) conditions. In total, the ACM shifts the emphasis from dysregulation to condi-
tional adaptation. From this perspective, development of a fast life history strategy in dangerous
and unpredictable contexts is not impairment or dysfunction; it is a coherent, organized response
to stress that has been shaped by a natural selective history of recurring exposures to such contexts
(for a detailed human example, see the section titled Beyond Fragmentation: Toward an Integrated
Theory of Stress, Developmental Adaptation, and Health).
Outstanding Questions and Challenges
The ACM and ALM offer sharply different perspectives on the costs and benefits of adaptations
to stress, particularly in regard to long-term developmental trajectories. The most urgent task
for researchers is to design studies capable of distinguishing between the two models. At present,
studies based on the ALM focus solely on the costs of childhood adversities (allostatic load) and
do not even attempt to explore the potential benefits of the attendant physiological and behavioral
changes (adaptive calibration). As an initial step in this direction, Del Giudice et al. (2011) made
specific hypotheses about how different environmental conditions should give rise to adaptive
profiles of stress responsivity, growth and maturation, and behavior. Some predictions have been
supported—for example, both high- and low-responsivity patterns have been identified in safe
as well as harsh conditions (e.g., Del Giudice et al. 2012; Ellis et al. 2005, 2017c; Fearon et al.
2017; Gunnar et al. 2009). Other predictions (for example those concerning sex differences in
high- versus low-responsivity profiles) have received mixed support, while others still are in need
of revision (see Ellis et al. 2017b). This is to be expected, since moving from the general principles
reviewed in this article to empirical predictions requires many additional assumptions about the
functions and correlates of particular physiological variables.
As discussed above, another important task will be to extend the ACM to include metabolism
and immunity, two key domains that have received considerable attention in the ALM framework.
The ultimate goal should be to build a detailed map of how biologically embedded changes regulate
developmental adaptations to stress, from maturation and reproductive functioning to learning
and behavior. By delineating intervening functional changes that mediate the effects of early
adversity on later mental and physical health problems, such a map could transform research on
stress–health relations.
Finally, an adaptive calibration perspective raises methodological and statistical challenges that
have yet to be adequately addressed. Notably, ACM responsivity profiles combine stress physiology
with a range of other life history–related traits. Analyses that focus exclusively on the parameters of
stress response systems (e.g., autonomic reactivity, cortisol levels) are unlikely to recover function-
ally meaningful patterns (for an example of this issue, see Peckins et al. 2015). However, properly
combining behavioral, developmental, and physiological variables is a challenging task that will
require sophisticated statistical approaches (see Ellis et al. 2017b,c).
BEYOND DIATHESIS STRESS: DIFFERENTIAL SUSCEPTIBILITY
TO THE ENVIRONMENT
What makes developmental plasticity potentially adaptive is that it can match the organism’s phe-
notype to its environment (or internal condition) in ways that improve the organism’s capacity
for survival and reproduction (West-Eberhard 2003). We note above that plasticity is rarely with-
out costs; these include the costs and trade-offs involved in producing the appropriate phenotype
(e.g., adaptations to predators in tadpoles), but also the extra time spent sampling the environment
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before specializing. Moreover, the cues received from the environment are usually imperfect and
can lead to incorrect predictions; as a result, plastic organisms sometimes end up developing a
mismatched phenotype that decreases their fitness instead of enhancing it (e.g., a predator-adapted
phenotype when actual predation risk is low) (see Frankenhuis & Panchanathan 2011, Murren
et al. 2015).
For all these reasons, plasticity is not always the optimal strategy for organisms. This creates
the potential for the evolution of individual differences in plasticity: Within the same population,
some individuals may respond strongly to their rearing conditions, while others may be barely
affected (Belsky & Pluess 2009, Boyce & Ellis 2005, Ellis et al. 2011a). These differences have
important implications for studying the effects of stress on development: If conditional adaptation
is not a universal strategy, then the predicted correlations between early adversity and subsequent
trajectories will be significantly attenuated by individual variation in plasticity. Biological models
typically assume that individual differences in plasticity are determined by differences in genotype.
Another possibility is that early environmental factors also shape plasticity to later aspects of the
environment; for example, prenatal exposure to maternal stress hormones may modulate the child’s
sensitivity to the quality of parenting and family relations (Boyce & Ellis 2005, Conradt et al. 2018,
Del Giudice 2015a, Pluess & Belsky 2011). In this scenario, early stress and adversity play a dual
role—they work as cues for plasticity mechanisms, but also modulate the sensitivity of the same
mechanisms over time (Boyce & Ellis 2005).
The notion that some individuals are especially vulnerable to negative or stressful experiences
is not new, as exemplified by the classic developmental concept of diathesis stress. However,
standard vulnerability models focus exclusively on negative outcomes and lack a functional theory
of individual differences that explains why such differences may evolve and persist in a population.
This focus has changed with the rise of differential susceptibility models over the past 20 years
(Belsky 1997, 2005; Boyce & Ellis 2005; Boyce et al. 1995; Ellis et al. 2006, 2011a). According
to these models (reviewed below), many of the same factors that determine increased sensitivity
to stress and adversity may also confer enhanced responsivity to the positive, supportive aspects
of the environment. In other words, highly susceptible individuals respond to the quality of their
environment for better and for worse (Belsky et al. 2007, Boyce et al. 1995).
Models of Differential Susceptibility
Models of differential susceptibility are based on the idea that adaptive plasticity has costs and
potential drawbacks; they postulate the existence of individual differences in plasticity that give rise
to systematic person–environment interactions. At the same time, different models conceptualize
the costs of plasticity in somewhat different terms and propose alternative mechanisms for the
development of individual differences (see Belsky & Pluess 2016, Del Giudice 2016, Ellis et al.
2011a).
Differential susceptibility theory. According to differential susceptibility theory (Belsky 1997,
2005), the biological function of differential susceptibility is to limit the evolutionary costs of plas-
ticity by making some individuals resistant to environmental influences, including those exerted
by parents. In other words, the theory predicts the existence of differences in susceptibility as a
form of insurance against developmental errors and mismatches. Indeed, mathematical models
show that individual differences in plasticity among siblings spread the risk of mismatch (a pattern
called bet hedging in evolutionary biology) and can be favored by natural selection in response to
unpredictable fluctuations in the environment (provided that other fairly restrictive assumptions
are met) (see Frankenhuis et al. 2016a). In Belsky’s (1997, 2005) original formulation, plasticity
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was assumed to be essentially a function of genetic factors. Following biological sensitivity to
context theory (see below), the model was later expanded to include both genetic and early en-
vironmental effects (such as prenatal exposure to maternal stress hormones) as factors regulating
the development of differential susceptibility (Belsky & Pluess 2016, Pluess & Belsky 2011).
Biological sensitivity to context. The biological sensitivity to context model (Boyce & Ellis
2005; Ellis et al. 2005, 2006) is rooted in developmental research on health and adversity. Boyce
and colleagues (1995) found that children high in cardiovascular and immune reactivity have worse
health outcomes in stressful environments but better outcomes in positive and supportive environ-
ments. Boyce & Ellis (2005) reframed these findings in an evolutionary framework and developed
the biological sensitivity to context model. According to this model, differential susceptibility to
the environment is primarily mediated by individual differences in neurobiological traits, specifi-
cally variation in autonomic and adrenocortical reactivity to stress. This mechanistic focus is a key
distinguishing feature of the biological sensitivity to context model (and provided the conceptual
framework for the ACM responsivity patterns discussed above).
From an evolutionary standpoint, the biological sensitivity to context model links individual
differences in susceptibility to the coexistence of generalist phenotypes (low biological sensitivity
to context; metaphorically referred to as dandelions) and specialist phenotypes (high biological
sensitivity to context; metaphorically referred to as orchids). Whereas generalists do reasonably
well in most environments, specialists calibrate development to achieve high fitness in some kinds
of environments (e.g., dangerous and unpredictable ones) but not in others. A distinctive prediction
of the biological sensitivity to context model is that of a U-shaped curvilinear relationship between
early adversity and stress responsivity: Children growing up in very safe or very stressful conditions
should develop the highest susceptibility to environmental influences (and, as a result, become
specialized to their particular niche). This prediction has received some empirical support in
human developmental research (e.g., Del Giudice et al. 2012; Ellis et al. 2005, 2017c; Gunnar
et al. 2009). The hypothesized U-shaped curve is also consistent with simulations suggesting
that, in the presence of person–environment interactions such as those postulated by differential
susceptibility models, it may be optimal to express higher levels of plasticity at both ends of an
environmental continuum (Del Giudice 2015a).
Patterns of person–environment interaction. A notable contribution of differential suscepti-
bility models has been to direct the attention of researchers to the shape of person–environment
interactions. In the classic diathesis stress scenario, vulnerable and resilient individuals develop
in similar ways when they are exposed to favorable conditions but diverge at increasing levels of
stress and adversity. In contrast, models of differential susceptibility predict that high- and low-
susceptibility individuals should diverge in both safe and stressful conditions and only become
similar when they experience moderate levels of adversity (crossover interactions) (see Ellis et al.
2011a). More recently, Pluess & Belsky (2013) proposed that some individuals may exhibit vantage
sensitivity, a pattern symmetrical to that of diathesis stress whereby plasticity is only expressed in
safe, supportive environments. In both the diathesis stress and differential susceptibility scenarios,
adaptations to stress (e.g., risk taking, heightened or blunted HPA reactivity, altered immune
parameters) are expected to develop more reliably in highly susceptible individuals (so that the
overall effects of stress are attenuated by individual variation in susceptibility). Under the vantage
sensitivity scenario, however, adaptations to stress—to the extent that they occur—are expressed
uniformly by all individuals in the population. Devising methods to reliably distinguish among
these three interaction patterns has become the focus of a growing methodological literature (e.g.,
Belsky et al. 2013, Roisman et al. 2012).
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While most research in this area has been descriptive, the possibility that person–environment
interactions may fall into qualitatively different patterns raises a deeper question, namely, what
conditions can be expected to favor the evolution or development of each pattern (e.g., Pluess
2015). For example, initial mathematical models indicate that interaction patterns resembling the
classic diathesis stress template should evolve more frequently than patterns of vantage sensitivity,
unless negative states of the environment (stress, adversity) occur much more often than positive
ones (Del Giudice 2017a). The prediction that vantage sensitivity should be comparatively rare is
consistent with the fact that this pattern has only been detected in a small minority of studies (for
areview,seeDelGiudice2017a).
Markers of Susceptibility
What makes some individuals more susceptible than others to environmental influences, including
exposure to stress and adversity? More specifically, are there traits or markers that systematically
predict enhanced plasticity? To summarize the state of this very active area of research, we dis-
tinguish between three levels of analysis: genetics, physiology, and behavior (see also Belsky &
Pluess 2009, 2016).
Genetic markers. In the search for genetic markers of susceptibility, researchers have tested
genotype–environment (G ×E) interactions between particular genetic variants and observed en-
vironmental variables, such as parenting quality (correlational G ×E), or between genetic variants
and exposure to randomized conditions or treatments, such as interventions to reduce aggression
(experimental G ×E). Studies of single candidate genes have focused mainly on genes involved in
serotonergic and dopaminergic signaling, such as the dopamine receptor 4 gene (DRD4) or the
serotonin transporter gene (SLC6A4). Less often, researchers have considered genes with roles in
oxytocinergic signaling [e.g., the oxytocin receptor gene (OXTR)], the HPA axis [e.g., the corti-
cotropin releasing factor receptor 1 gene (CRHR1)], and other brain-related pathways [e.g., the
brain-derived neurotrophic factor (BDNF)] (see Belsky & Pluess 2016, Del Giudice 2017a, Moore
& Depue 2016).
The findings of individual studies in this area are highly variable (e.g., Belsky et al. 2015a)
and likely inflated by a high rate of false positives, as is typical of candidate gene studies (Dick
et al. 2015). So far, the most promising results come from meta-analyses of correlational G ×E
studies of dopaminergic and serotonergic genes (Bakermans-Kranenburg & van IJzendoorn 2011,
van IJzendoorn et al. 2012) and from more recent meta-analyses of experimental G ×E studies
involving the same genes (Bakermans-Kranenburg & van IJzendoorn 2015, van IJzendoorn &
Bakermans-Kranenburg 2015). It remains to be seen whether these results will be consistently
replicated in large samples. Another strategy to deal with the low statistical power of single-gene
studies is to pool multiple variants together into a polygenic score. Several studies employing
polygenic scores of serotonergic, dopaminergic, HPA-related, and other genes (such as BDNF)
have detected significant G ×E interactions, generally consistent with differential susceptibility
patterns (e.g., Belsky & Beaver 2011, Cicchetti & Rogosh 2012, Feurer et al. 2017, Keers & Pluess
2017, Silveira et al. 2017).
Physiological markers. According to the biological sensitivity to context model, a key marker
of susceptibility is elevated physiological reactivity to environmental challenges, including both
autonomic and HPA axis reactivity (Boyce & Ellis 2005, Ellis et al. 2005). Many empirical studies
have found patterns consistent with this idea (for reviews, see Boyce 2016, Obradovi´
c 2012),
although there are also contradictory findings (see Sijtsema et al. 2013). Importantly, there is
emerging evidence that stress reactivity itself may be the product of G ×E interactions between
early adversity and plasticity-enhancing genetic variants, in line with the hypothesis that initial
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environmental cues modulate susceptibility to later experiences, particularly in individuals who are
already genetically plastic (Allegrini et al. 2018). More recently, Del Giudice and colleagues (2018)
speculated that exposure to higher levels of androgens (e.g., testosterone) during prenatal and
early postnatal life should increase plasticity for the many physiological and behavioral traits that
show higher variability in males. This hypothesis is still awaiting empirical testing; if supported,
it would extend the range of differential susceptibility markers beyond the typical emphasis on
central neurotransmitters and stress physiology.
Behavioral markers. In the foundational papers of differential susceptibility theory, Belsky (1997,
2005) suggested that behavioral traits such as difficult temperament and negative emotionality may
serve as markers of differential susceptibility in infants and children. This hypothesis has subse-
quently been tested in dozens of studies (see Belsky & Pluess 2016); a recent meta-analysis con-
firmed that difficult temperament and early negative emotionality (before 1 year of age) moderate
the effects of quality of parenting on child development in a way consistent with differential sus-
ceptibility (Slagt et al. 2016). Other researchers have pointed to sensory processing sensitivity as a
plausible marker of susceptibility (Boyce & Ellis 2005, Pluess 2015, Pluess et al. 2018). People high
in sensory processing sensitivity show heightened awareness of sensory stimulation, susceptibility
to overstimulation, elevated emotional reactivity (including both positive and negative emotion-
ality), and behavioral inhibition in novel situations (Aron et al. 2012). From a neurobiological
perspective, Moore & Depue (2016) argued that individual differences in the activity of multiple
brain systems (including dopaminergic, serotonergic, and oxytocinergic pathways) contribute to a
general dimension of reactivity to external stimulation, which may in turn determine susceptibility.
This neurobiological framework fits with the idea that susceptibility is, at least in part, a function
of the individual’s sensitivity to environmental stimuli, as reflected, for example, in measures of
sensory processing sensitivity (Pluess 2015). Initial results support a role for sensory processing
sensitivity in moderating some associations between parenting and externalizing behavior (Slagt
et al. 2018); however, there is still little empirical evidence that this trait is a general marker of
susceptibility, as has often been suggested in the literature (e.g., Pluess et al. 2018).
Outstanding Questions and Challenges
The study of differential susceptibility faces some formidable methodological challenges. Reli-
ably distinguishing between different types of interaction patterns with commonly used metrics
requires large samples (Del Giudice 2017b), and many correlational studies in this area (including
single-gene correlational G ×E studies) are seriously underpowered for the task. Exciting devel-
opments on this front include new statistical models that combine multiple genes and multiple
environmental variables into a single interaction test ( Jolicoeur-Martineau et al. 2017) and in-
direct methods that use data from twin studies to infer the shape of the underlying interaction
patterns (South et al. 2017).
Although new statistical tools and improved methodology can be expected to yield substan-
tial benefits, we believe that the most pressing challenges in this area are theoretical in nature
(see Del Giudice 2017a,b). For example, detecting an interaction that matches a diathesis stress
template says little about the underlying developmental process, which may involve maladap-
tive vulnerability to stressors, but also adaptive phenotype–environment matching (Del Giudice
2017a). While differential susceptibility research was initially propelled by novel theoretical mod-
els and ideas, over time, the focus of most researchers has shifted to issues of measurement and
data analysis. As a result, theoretical progress has been slow, and many deeper questions remain
unanswered. For example, it is unclear when selection should favor domain-general plasticity
mechanisms that simultaneously regulate multiple traits, versus domain-specific mechanisms that
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only control a particular phenotype (see Belsky & Pluess 2016). Different models of susceptibility
also make different assumptions about the relationship between plasticity and specialization. In
classic generalist–specialist models (Wilson & Yoshimura 1994; see also Frankenhuis et al. 2016a),
generalists can fit into multiple niches owing to increased plasticity, whereas specialists develop
relatively fixed phenotypes. However, a plausible alternative to this model is that plasticity sup-
ports enhanced specialization (Del Giudice 2017a, Murren et al. 2015); in fact, this scenario may
be more consistent with developmentally focused differential susceptibility models because it as-
sumes that heightened physiological and negative emotional reactivity enables plasticity during an
early sensitive period but may not operate that way later in development (after an orchid child spe-
cializes their phenotype). Other unresolved issues concern the relative strength of various sources
of individual differences (e.g., direct effects of the environment versus G ×E interactions), as well
as the role of shared environmental factors (those that act similarly on siblings in the same family)
versus nonshared factors (unique to each sibling) in the development of plasticity (Del Giudice
2016). Only through sustained theoretical effort will it be possible to address these questions and
use the answers to inform empirical research.
BEYOND FRAGMENTATION: TOWARD AN INTEGRATED THEORY
OF STRESS, DEVELOPMENTAL ADAPTATION, AND HEALTH
The central question addressed in this review is whether childhood exposures to adversity simply
constrain development, as assumed in dysregulation models, or guide it in an adaptive manner. In
this section, we use the example of pubertal development to demonstrate how both processes oper-
ate simultaneously. Early life stress exposures result in long-term, potentially permanent changes
in physiological systems that both constrain development (increasing morbidity and mortality
risks) and adaptively calibrate it to enhance fitness under stressful conditions. Stress-mediated
development of alternative life history strategies is the key to understanding this dual process.
Biological embedding of early life stress functions to calibrate life history–related traits, including
timing of puberty; allostatic load and associated mental and physical impairments can be under-
stood, in part, as costs and side effects of these adaptive processes.
Timing of Puberty: A Case Study
Pubertal maturation is a dynamic biological process—punctuated by visible changes in stature,
body composition, and secondary sexual characteristics—that culminates in the transition from
the prereproductive to the reproductive phase of the human life cycle (Ellis 2004). Perhaps the
most striking feature of human pubertal and sexual development is its variation. Some individuals
complete puberty in elementary school, while others are still relatively undeveloped when they start
high school; some begin sexual activity and reproduction as teenagers, while others delay having
children until decades later; some pursue short-term sexual relationships with multiple partners,
while others commit to a single long-term partner for life. This variation begins with individual
differences in maturation of the reproductive axis—when and how fast puberty occurs—and then
feeds forward to many other reproductive characteristics.
Early timing of puberty is an important component of a fast life history strategy. Women
who experience early pubertal development, compared with their later-maturing peers, tend to
have higher levels of serum estradiol and lower sex hormone binding globulin concentrations
that persist through 20–30 years of age; have shorter periods of adolescent subfertility (the time
between menarche and attainment of fertile menstrual cycles); experience earlier ages at first
sexual intercourse, first pregnancy, and first childbirth; engage in more risky sexual behavior; and
display more negative implicit evaluations of men and more aggressive and delinquent behaviors
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as young adults (Belles et al. 2010, Najman et al. 2009; for reviews, see Baams et al. 2015, Ellis
2004, Ibitoye et al. 2017). This covariation between timing of pubertal development and other
life history–related traits supports the conceptualization of puberty as a key switch point in the
development of alternative life history strategies (Ellis 2013).
An Evolutionary–Developmental Theory of Pubertal Variation
Drawing on life history concepts, Belsky et al. (1991) proposed an evolutionary–developmental
theory linking levels of psychosocial stress and support in and around the family to subsequent
timing of puberty and related life history traits. The theory posited that (a)ecologicalcondi-
tions and family dynamics shape children’s early attachment patterns and behavioral development
and, through these developmental processes, subsequent pubertal development and reproductive
strategy, and that (b) this environmentally sensitive developmental system evolved as a means of
matching individuals to their environment in a manner that promotes survival and reproduction
across varying ecological contexts. Over the course of our evolutionary history, individuals growing
up under dangerous or unpredictable family conditions may have reliably increased their repro-
ductive success by accelerating physical maturation and beginning sexual activity and reproduction
at a relatively early age (Belsky 2012, Belsky et al. 1991, Ellis 2004).
When evaluating this theory, a starting assumption is that the effects of physical and psychoso-
cial stressors on pubertal timing are hierarchically ordered: Pubertal timing is contingent firstly
on health and nutrition (see especially Kyweluk et al. 2018) and secondly, when these are ade-
quate, on socioemotional conditions (Coall & Chisholm 2003, Ellis 2004). Consistent with life
history models (e.g., Belsky et al. 1991), a substantial body of literature indicates that, when en-
ergetic conditions are adequate to support growth, early exposures to childhood adversities (e.g.,
socioeconomic adversity, child maltreatment, lack of family warmth and supportiveness, height-
ened parent–child conflict, father absence) tend to predict earlier pubertal development in females
(for reviews, see Belsky & Shalev 2016, Ellis 2004, Webster et al. 2014). For example, in a large
prospective study of a population-based birth cohort in Australia, extremely unfavorable socio-
economic conditions predicted a fourfold increase in boys and twofold increase in girls in rates
of early puberty (Sun et al. 2017a; for convergent findings in a prospective study of a multiethnic
cohort of girls in the United States, see Hiatt et al. 2017). Similar effects may occur in response
to natural disasters. In a large Chinese study, exposure to the Wenchuan earthquake predicted a
fourfold increase among preschool-age girls (under age 7 at the time of exposure) and a twofold
increase among school-age girls (age 7 or older at the time of exposure) in rates of early menarche
(Lian et al. 2018), suggesting an early sensitive period for stress-mediated acceleration of puber-
tal development. Although earlier puberty is associated with childhood exposure to a variety of
psychosocial stressors, the most consistent psychosocial predictor of early puberty in females is
a history of sexual abuse (e.g., Magnus et al. 2018, Mendle et al. 2016). Furthermore, consis-
tent with the assumption that the effects of physical and psychosocial stressors are hierarchically
ordered, childhood deprivation (e.g., food insecurity, neglect) appears to delay pubertal develop-
ment, while childhood exposure to violence (a key marker of extrinsic morbidity and mortality)
appears to accelerate it (Sumner et al. 2018), as per the findings on sexual abuse.
The current evolutionary–developmental model (Belsky et al. 1991) underscores the impor-
tance of conceptualizing pubertal development as part of a developmental continuum, whereby
certain familial and ecological stressors in childhood accelerate pubertal maturation, which in turn
regulates important dimensions of mating and parenting effort. The results of a small number of
prospective, longitudinal studies indicate that the effects of stressful family environments (e.g.,
harsh maternal behavior, paternal unemployment, child maltreatment) on the development of
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PS70CH06_Ellis ARI 20 November 2018 8:32
faster life history strategies in women (e.g., risky or advanced sexual behavior; intimate partner
violence; and early smoking, drinking, and parenthood) are partially mediated by timing of pu-
berty (Arim et al. 2011, Belsky et al. 2010, Foster et al. 2008, James et al. 2012, Negriff et al.
2015). In sum, puberty appears to operate as an important intervening mechanism linking rearing
conditions to alternative life history strategies.
Accelerated Pubertal Maturation Trades Off Against Health
Although this environmentally sensitive regulation of life history strategies is presumed to be
adaptive, adaptive does not mean cost free. Stress-mediated acceleration of pubertal development
may induce trade-offs that compromise health and curtail the reproductive life span. A history
of sexual abuse is associated not only with earlier age of menarche but also with earlier age
of menopause (Magnus et al. 2018), as well as many other costs to mental and physical health
(e.g., Trickett et al. 2011). Likewise, Bleil and colleagues (2012, 2013) found that psychosocial
stress was associated with earlier puberty and higher antral follicle count in younger women, but
with ovarian reserve depletion in older women. That stress-mediated acceleration of pubertal
development results in wear and tear on the reproductive system converges with a large body of
human research indicating that the development of faster life history strategies comes at the cost of
increasing allostatic load (for a review, see Ellis & Del Giudice 2014). Indeed, both cross-sectional
and longitudinal studies have shown that individuals who pursue faster life history strategies suffer
from more mental health problems, medical ailments (e.g., thyroid disease, high blood pressure
or hypertension, ulcers), and physical health symptoms (e.g., sore throat or cough, dizziness)
(Brumbach et al. 2009, Figueredo et al. 2004, Gibbons et al. 2012, Hill et al. 2016, Mell et al.
2018, Sefcek & Figueredo 2010). In sum, stress-mediated regulation of life history strategies guides
development along specific pathways that can be understood as predictive adaptive responses,
despite substantial costs. Such trade-offs reflect the very nature of development under stress.
Consistent with the notion of trade-offs, early timing of puberty in females is associated with
a broad range of mental and physical health problems, ranging from psychopathology to obesity,
cardiovascular disease, and reproductive cancers (e.g., Day et al. 2015, Ellis 2004, Graber et al.
1997). Earlier sexual maturation has been linked to greater allostatic load (Allsworth et al. 2005);
in that context, the links between early puberty and higher morbidity and mortality concur with
the ALM. An emerging literature has begun to test for the mediating role of pubertal timing in
explaining the well-established links between childhood adversity and later mental and physical
health problems. In this case, again, the results of a small number of prospective, longitudinal
studies suggest that the effects of early adversity (e.g., prenatal stress, childhood trauma, child
maltreatment, maternal depression, negative parenting) on behavioral problems and health (e.g.,
substance use, mental health symptoms, global physical health problems, cardiovascular disease
risk) are partially mediated by early timing of puberty (Belsky et al. 2015b, Bleil et al. 2013, Lei et al.
2018, Mendle et al. 2014, Negriff et al. 2015). In sum, earlier timing of puberty appears to mediate
the effects of early adversity on faster life history strategies, on the one hand, and poor health,
on the other hand. Central to the evolutionary–developmental approach presented in this review
is the proposition that these dual outcomes are interconnected through developmental trade-offs.
Stress Response Systems as Mediating Mechanisms in Stress–Puberty Relations
Stress response systems may play an important role in the developmental relationships among
stress, puberty, and health. As reviewed by Ellis & Del Giudice (2014), stress response systems are
functionally implicated in all components of mating and parenting, beginning with sexual mat-
uration. The autonomic nervous system, HPA axis, and hypothalamic–pituitary–gonadal (HPG)
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axis are connected by extensive functional cross talk (Ellis 2004, Joos et al. 2018). As reviewed
by Joos et al. (2018), the HPA and HPG axes tend to operate independently prior to puberty,
become positively coupled in early adolescence, but then may shift toward negative coupling (or
less positive coupling) in later adolescence (although positive diurnal coupling of cortisol and
testosterone has been observed throughout the life course; Harden et al. 2016). This develop-
mental pattern concurs with a substantial body of research indicating that psychosocial stressors
generally provoke early or accelerated development of the HPG axis in girls but suppressed ovar-
ian functioning in adult women (for a review, see Ellis 2004). For example, in a study of Chinese
elementary school children, greater chronic daily activation of the HPA axis, as indicated by hair
cortisol concentrations (representing chronic stress over the 3 months preceding measurement),
predicted greater testicular volume in boys and breast development in girls aged 6 to 9 years (Sun
et al. 2017b). Likewise, in a longitudinal study in the United States, higher basal cortisol levels at
4 years of age partially mediated the relationship between early adversity exposures and attainment
of adrenarche (the onset of adrenal androgen production) by 7 years of age (Belsky et al. 2015b).
This pattern then apparently switches in later adolescence. In a separate longitudinal study in the
United States, attenuated (rather than elevated) cortisol reactivity to social stress predicted faster
tempo of puberty in adolescent girls (but not boys) aged 9 to 13 years (Saxbe et al. 2015).
In sum, consistent with the notion of positive coupling of the HPA and HPG axes early in
adolescence followed by negative (or less positive) coupling later in adolescence, high pre- and
peri-pubertal basal activation of the HPA axis, but attenuated HPA responsivity during puberty,
was linked to accelerated sexual development—an indicator of a faster life history strategy. Most
interesting, Ruttle et al. (2015) found that stressful family conditions in early childhood accelerated
both the onset of positive HPA–HPG coupling (by age 11) and the transition to negative HPA–
HPG coupling (by age 13) in adolescent girls. Simmons et al. (2015) found that HPA–HPG cou-
pling was positive only in 15–16-year-old girls from low- to moderate-adversity backgrounds, and
that HPA–HPG functioning was uncoupled by that age in girls from high-adversity backgrounds.
Although more research is clearly needed, and the transition toward less positive HPA–HPG cou-
pling may begin quite early in pre-adolescent girls growing up under stressful conditions (Black
et al. 2018), early HPA–HPG coupling could serve as a mechanism through which childhood stress
promotes earlier pubertal development ( Joos et al. 2018, Ruttle et al. 2015). The Wenchuan earth-
quake study (Lian et al. 2018) suggests that the first 5–7 years of life are a sensitive period for the
effects of early life stress on pubertal maturation [as originally proposed by Belsky et al. (1991)]. In
the context of early life stress (presumably during this sensitive period) and the resulting upregu-
lation of basal cortisol, accelerated positive HPA–HPG coupling in early adolescence may operate
as a permissive signal that hastens the onset of puberty. In turn, accelerated negative HPA–HPG
coupling (or reductions in positive coupling) in later adolescence may hasten progression through
puberty (given attenuated HPA functioning in children who have experienced significant early
adversity) (Doom et al. 2014, Trickett et al. 2010; see above discussion of the transition from vig-
ilant to unemotional patterns of stress responsivity in the section titled Beyond Allostatic Load:
Stress Response Systems as a Mechanism of Conditional Adaptation).
Importance of Differential Susceptibility in Regulation of Pubertal Timing
Despite the findings of the literature reviewed above on psychosocial antecedents of pubertal
timing, the effects of childhood stress on puberty tend to be relatively small, are somewhat in-
consistent across studies, and could reflect gene–environment correlations (rGE) operating on a
background of heritable variation in pubertal timing (e.g., Barbaro et al. 2017, Mendle et al. 2006,
Rowe 2000), although initial polygenic analyses have found only limited support for the rGE
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hypothesis (Gaydosh et al. 2018). Theories of differential susceptibility and biological sensitivity
to context suggest that the weak main effects of environmental variables on many developmental
outcomes may reflect the fact that children differ in whether, how, and how much they are affected
by rearing experiences. As articulated by Belsky (2012), the weak main effects of family context
on pubertal timing may overestimate the impact of family environments in some children and
underestimate it in others.
Consistent with this supposition, both physiological variation in autonomic and adrenocorti-
cal reactivity to stress (Ellis et al. 2011b) and genotypic variation in the estrogen receptor-αgene
(ESR1)(Hartmanetal.2015,Manucketal.2011)havebeenfoundtomoderatetheeffectsoffamily
relationships on timing of puberty in girls. This pattern of differential susceptibility enhances pu-
bertal responses to childhood adversity in some individuals while attenuating it in others. Although
the findings on ESR1 should be considered tentative due to limited sample sizes, they converge
nicely with experimental research on rodents indicating that the accelerating effects of low levels
of maternal licking and grooming (a form of low parental investment) on pubertal maturation in
female offspring are mediated by increased expression of estrogen receptor-αin specific regions
of the hypothalamus (for a review, see Cameron 2011). Finally, some evidence suggests that early
pubertal development itself may operate as a susceptibility factor that amplifies the effects of par-
enting quality on aggression in a for better and for worse manner (Chen & Raine 2018). If so,
susceptibility factors in middle childhood that enhance pubertal responses to early family stress
(e.g., heightened autonomic and adrenocortical reactivity to stress; Ellis et al. 2011b) may set pro-
cesses in motion that further potentiate susceptibility to family relationships in early adolescence.
CONCLUSION
What is the nature of developmental adaptation to stress? Does childhood adversity adaptively
shape development or simply constrain it? Following the ALM and other dysregulation models,
one can always make a disease-focused argument emphasizing the deleterious effects of adversity
and its biological mediators (e.g., chronic low-grade inflammation, sensitized cortico-amygdala
threat circuitry, abnormal HPA axis functioning). Indeed, the extensive body of research doc-
umenting the negative effects of allostatic load on health is incontrovertible. This is because
development under stressful conditions necessitates trade-offs: One system is diminished so that
another system can be enhanced or preserved. In the scientific literature on stress and development,
however, these countervailing effects have not been equally studied; as a result, we know vastly
more about the detrimental effects of childhood stress than about its benefits in context. The devel-
opmental literature on puberty and life history strategies reveals both sides of the equation. From
an evolutionary perspective, stress-mediated developmental processes do not exclusively cause
impairments and vulnerabilities; they also promote coherent, integrated, functional responses to
childhood adversity. This includes both short-term adjustments (immediate adaptive responses)
and longer-term adaptations (predictive adaptive responses) that regulate development toward
faster life history strategies, which in turn promote survival and reproduction under harsh and
unpredictable conditions. Mental and physical impairments or disease can be partly understood
as costs and side effects of these adaptive processes. At the same time, variation in biological
sensitivity to context attenuates these effects, with some individuals responding strongly to their
rearing conditions, while others are only weakly affected. In sum, natural selection may favor both
developmental adaptations to stress and differential susceptibility to its effects.
The long-term focus of the ACM and other developmental programming models is critical to
understanding stress–health relations because, to a great extent, allostatic load is a by-product of
the chain of resource-allocation decisions that characterize the development of faster life history
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strategies over the life course. In the literature reviewed above, these resource allocation decisions
are mediated through earlier pubertal development and related life history traits (e.g., earlier
onset of sex and reproduction, more risky and aggressive behavior, stress-adapted cognition). In
the ACM, early life stress is biologically embedded in the parameters of stress response systems
and other neuroendocrine processes that guide alternative developmental trajectories. Mapping
out such functional biobehavioral responses to stress is critical for health risk identification and
health promotion because the costs of developmental adaptations to stress (e.g., allostatic load)
and the potential benefits (e.g., adaptive calibration) are inextricably linked—indeed, one cannot
be understood without the other.
The evolutionary–developmental perspective presented in this review affords a big-picture
view of developmental plasticity and individual differences that integrates a wide spectrum of
findings on stress–health relations. From this perspective, dysregulation models—by emphasizing
the pathways leading directly from adversity to dysfunction—miss something fundamental about
development: the coherent, functional biobehavioral changes that occur in response to stress over
time (Ellis & Del Giudice 2014). We need to understand these functional developmental changes
to more fully understand dysfunction. The problem with many traditional interventions is that they
ignore developmental adaptations to stress. This can result in errors of omission (e.g., missing
key intervening variables in stress–health relations) and misidentification of health risk factors
(e.g., mistaking functional brain changes for dysfunction). Treatment and prevention strategies
that ignore developmental adaptations to stress not only miss the opportunity to leverage these
adaptations for good—working with them to enhance positive outcomes—but also risk fighting
against these adaptations in an uphill battle that they are not likely to win (Ellis et al. 2012a, 2017a).
DISCLOSURE STATEMENT
The authors are not aware of any affiliations, memberships, funding, or financial holdings that
might be perceived as affecting the objectivity of this review.
ACKNOWLEDGMENTS
We thank Jay Belsky, Lisa Diamond, and Willem Frankenhuis for comments on an earlier draft
of this review.
LITERATURE CITED
Alink LRA, van IJzendoorn MH, Bakermans-Kranenburg MJ, Mesman J, Juffer F, Koot HM. 2008. Cortisol
and externalizing behavior in children and adolescents: mixed meta-analytic evidence for the inverse
relation of basal cortisol and cortisol reactivity with externalizing behavior. Dev. Psychobiol. 50:427–50
Allegrini AG, Evans BE, de Rooij S, Greaves-Lord K, Huizink AC. 2018. Gene ×Environment contributions
to autonomic stress reactivity in youth. Dev. Psychopathol. In press
Allsworth JE, Weitzen S, Boardman LA. 2005. Early age at menarche and allostatic load: data from the Third
National Health and Nutrition Examination Survey. Ann. Epidemiol. 15:438–44
Arim RG, Tramonte L, Shapka JD, Dahinten VS, Willms JD. 2011. The family antecedents and the subsequent
outcomes of early puberty. J. Youth Adolesc. 40:1423–35
Aron EN, Aron A, Jagiellowicz J. 2012. Sensory processing sensitivity: a review in the light of the evolution
of biological responsivity. Personal. Soc. Psychol. Rev. 16:262–82
Baams L, Dubas JS, Overbeek G, Van Aken MA. 2015. Transitions in body and behavior: a meta-analytic
study on the relationship between pubertal development and adolescent sexual behavior. J. Adolesc. Health
56:586–98
132 Ellis ·Del Giudice
Annu. Rev. Psychol. 2019.70:111-139. Downloaded from www.annualreviews.org
Access provided by University of New Mexico (UNM) on 01/05/19. For personal use only.
PS70CH06_Ellis ARI 20 November 2018 8:32
Bakermans-Kranenburg MJ, van IJzendoorn MH. 2011. Differential susceptibility to rearing environment
depending on dopamine-related genes: new evidence and a meta-analysis. Dev. Psychopathol. 23:39–52
Bakermans-Kranenburg MJ, van IJzendoorn MH. 2015. The hidden efficacy of interventions:
gene ×environment experiments from a differential susceptibility perspective. Annu. Rev. Psychol. 66:381–
409
Barbaro N, Boutwell BB, Barnes JC, Shackelford TK. 2017. Genetic confounding of the relationship between
father absence and age at menarche. Evol. Hum. Behav. 38:357–65
Bateson P, Gluckman P, Hanson M. 2014. The biology of developmental plasticity and the Predictive Adaptive
Response hypothesis. J. Physiol. 592:2357–68
Baumeister D, Akhtar R, Ciufolini S, Pariante CM, Mondelli V. 2016. Childhood trauma and adulthood
inflammation: a meta-analysis of peripheral C-reactive protein, interleukin-6 and tumour necrosis
factor-α.Mol. Psychiatry 21:642–49
Belles S, Kunde W, Neumann R. 2010. Timing of sexual maturation and women’s evaluation of men. Personal.
Soc. Psychol. Bull. 36:703–14
Belsky J. 1997. Variation in susceptibility to rearing influences: an evolutionary argument. Psychol. Inq. 8:182–
86
Belsky J. 2005. Differential susceptibility to rearing influences: an evolutionary hypothesis and some evidence.
In Origins of the Social Mind: Evolutionary Psychology and Child Development, ed. B Ellis, D Bjorklund,
pp. 139–63. New York: Guilford
Belsky J. 2012. The development of human reproductive strategies: progress and prospects. Curr. Dir. Psychol.
Sci. 21:310–16
Belsky J, Bakermans-Kranenburg MJ, van IJzendoorn MH. 2007. For better and for worse: differential sus-
ceptibility to environmental influences. Curr. Dir. Psychol. Sci. 16:300–4
Belsky J, Beaver KM. 2011. Cumulative genetic plasticity, parenting and adolescent self-regulation. J. Child
Psychol. Psychiatry. 52:619–26
Belsky J, Newman DA, Widaman KF, Rodkin P, Pluess M, et al. 2015a. Differential susceptibility to effects
of maternal sensitivity? A study of candidate plasticity genes. Dev. Psychopathol. 27:725–46
Belsky J, Pluess M. 2009. Beyond diathesis stress: differential susceptibility to environmental influences. Psychol.
Bull. 135:885–908
Belsky J, Pluess M. 2016. Differential susceptibility to environmental influences. In Developmental Psychopathol-
ogy,Vol.2:Developmental Neuroscience, ed. D Cicchetti, pp. 59–106. Hoboken, NJ: Wiley. 3rd ed.
Belsky J, Pluess M, Widaman KF. 2013. Confirmatory and competitive evaluation of alternative gene-
environment interaction hypotheses. J. Child Psychol. Psychiatry 54:1135–43
Belsky J, Ruttle PL, Boyce WT, Armstrong JM, Essex MJ. 2015b. Early adversity, elevated stress physiology,
accelerated sexual maturation, and poor health in females. Dev. Psychol. 51:816–22
Belsky J, Schlomer GL, Ellis BJ. 2012. Beyond cumulative risk: distinguishing harshness and unpredictability
as determinants of parenting and early life history strategy. Dev. Psychol. 48:662–73
Belsky J, Shalev I. 2016. Contextual adversity, telomere erosion, pubertal development, and health: two models
of accelerated aging, or one? Dev. Psychopathol. 28:1367–83
Belsky J, Steinberg L, Draper P. 1991. Childhood experience, interpersonal development and reproductive
strategy: an evolutionary theory of socialization. Child Dev. 62:647–70
Belsky J, Steinberg L, Houts RM, Halpern-Felsher BL. 2010. The development of reproductive strategy
in females: early maternal harshness→earlier menarche→increased sexual risk taking. Dev. Psychol.
46:120–28
Black CJ, Figueredo AJ, Jacobs WJ. 2017. Substance, history, and politics: an examination of the conceptual
underpinnings of alternative approaches to the life history narrative. Evol. Psychol. 15:1474704916670402
Black SR, Lerner MD, Shirtcliff EA, Klein DN. 2018. Patterns of neuroendocrine coupling in 9-year-old
children: effects of sex, body-mass index, and life stress. Biol. Psychol. 132:252–59
Bleil ME, Adler NE, Appelhans BM, Gregorich SE, Sternfeld B, Cedars MI. 2013. Childhood adversity and
pubertal timing: understanding the origins of adulthood cardiovascular risk. Biol. Psychol. 93:213–19
Bleil ME, Adler NE, Pasch LA, Sternfeld B, Gregorich SE, et al. 2012. Psychological stress and reproductive
aging among pre-menopausal women. Hum. Reprod. 27:2720–28
www.annualreviews.org •Developmental Adaptation to Stress 133
Annu. Rev. Psychol. 2019.70:111-139. Downloaded from www.annualreviews.org
Access provided by University of New Mexico (UNM) on 01/05/19. For personal use only.
PS70CH06_Ellis ARI 20 November 2018 8:32
Boyce WT. 2016. Differential susceptibility of the developing brain to contextual adversity and stress.
Neuropsychopharmacology 41:142–62
Boyce WT, Chesney M, Alkon A, Tschann JM, Adams S, et al. 1995. Psychobiologic reactivity to stress and
childhood respiratory illnesses: results of two prospective studies. Psychosom. Med. 57:411–22
Boyce WT, Ellis BJ. 2005. Biological sensitivity to context: I. An evolutionary-developmental theory of the
origins and functions of stress reactivity. Dev. Psychopathol. 17:271–301
Brumbach BH, Figueredo AJ, Ellis BJ. 2009. Effects of harsh and unpredictable environments in adolescence
on development of life history strategies. Hum. Nat. 20:25–51
Bunea IM, Szent´
agotai-T˘
atar A, Miu AC. 2017. Early-life adversity and cortisol response to social stress: a
meta-analysis. Trans. Psychiatry 7:1274
Cameron NM. 2011. Maternal programming of reproductive function and behavior in the female rat. Front.
Evol. Neurosci. 3:10
Chang L, Lu HJ. 2018. Resource and extrinsic risk in defining fast life histories of rural Chinese left-behind
children. Evol. Hum. Behav. 39:59–66
Chen FR, Raine A. 2018. Effects of harsh parenting and positive parenting practices on youth aggressive
behavior: the moderating role of early pubertal timing. Aggress. Behav. 44:18–28
Cicchetti D, Rogosch FA. 2012. Gene ×Environment interaction and resilience: effects of child maltreatment
and serotonin, corticotropin releasing hormone, dopamine, and oxytocin genes. Dev. Psychopathol. 24:411–
27
Coall DA, Chisholm JS. 2003. Evolutionary perspectives on pregnancy: maternal age at menarche and infant
birth weight. Soc. Sci. Med. 57:1771–81
Conradt E, Adkins DE, Crowell SE, Raby KL, Diamond LM, Ellis B. 2018. Incorporating epigenetic mech-
anisms to advance fetal programming theories. Dev. Psychopathol. 30:807–24
Copping LT, Campbell A. 2015. The environment and life history strategies: neighborhood and individual-
level models. Evol. Hum. Behav. 36:182–90
Daly M, Wilson M. 2005. Carpe diem: adaptation and devaluing the future. Q. Rev. Biol. 80:55–60
Day FR, Elks CE, Murray A, Ong KK, Perry JR. 2015. Puberty timing associated with diabetes, cardiovascular
disease and also diverse health outcomes in men and women: the UK Biobank study. Sci. Rep. 5:11208
Del Giudice M. 2014a. Early stress and human behavioral development: emerging evolutionary perspectives.
J. Dev. Orig. Health Dis. 5:270–80
Del Giudice M. 2014b. Middle childhood: an evolutionary-developmental synthesis. Dev. Perspect. 8:193–200
Del Giudice M. 2015a. Plasticity as a developing trait: exploring the implications. Front. Zool. 12:S4
Del Giudice M. 2015b. Self-regulation in an evolutionary perspective. In Handbook of Biobehavioral Approaches
to Self-Regulation, ed. GHE Gendolla, M Tops, S Koole, pp. 25–42. Berlin: Springer
Del Giudice M. 2016. Differential susceptibility to the environment: Are developmental models compatible
with the evidence from twin studies? Dev. Psychol. 52:1330–39
Del Giudice M. 2017a. The evolution of interaction shape in differential susceptibility. Child Dev.88:1897–912
Del Giudice M. 2017b. Statistical tests of differential susceptibility: performance, limitations, and improve-
ments. Dev. Psychopathol. 29:1267–78
Del Giudice M, Barrett ES, Belsky J, Hartman S, Martel MM, et al. 2018. Individual differences in develop-
mental plasticity: a role for early androgens? Psychoneuroendocrinology 90:165–73
Del Giudice M, Belsky J. 2011. The development of life history strategies: toward a multi-stage theory. In
The Evolution of Personality and Individual Differences, ed. DM Buss, PH Hawley, pp. 154–76. Oxford, UK:
Oxford Univ. Press
Del Giudice M, Ellis BJ, Shirtcliff EA. 2011. The Adaptive Calibration Model of stress responsivity. Neurosci.
Biobehav. Rev. 35:1562–92
Del Giudice M, Gangestad SW, Kaplan HS. 2015. Life history theory and evolutionary psychology. In The
Handbook of Evolutionary Psychology,Vol.1:Foundations, ed. DM Buss, pp. 88–114. New York: Wiley.
2nd ed.
Del Giudice M, Hinnant JB, Ellis BJ, El-Sheikh M. 2012. Adaptive patterns of stress responsivity: a preliminary
investigation. Dev. Psychol. 48:775–90
DeWitt TJ, Scheiner SM. 2004. Phenotypic Plasticity: Functional and Conceptual Approaches. Oxford, UK: Oxford
Univ. Press
134 Ellis ·Del Giudice
Annu. Rev. Psychol. 2019.70:111-139. Downloaded from www.annualreviews.org
Access provided by University of New Mexico (UNM) on 01/05/19. For personal use only.
PS70CH06_Ellis ARI 20 November 2018 8:32
Dick DM, Agrawal A, Keller MC, Adkins A, Aliev F, et al. 2015. Candidate gene-environment interaction
research: reflections and recommendations. Perspect. Psychol. Sci. 10:37–59
Dickerson SS, Kemeny ME. 2004. Acute stressors and cortisol responses: a theoretical integration and synthesis
of laboratory research. Psychol. Bull. 130:355–91
Doom JR, Cicchetti D, Rogosch FA. 2014. Longitudinal patterns of cortisol regulation differ in maltreated
and nonmaltreated children. J. Am. Acad. Child Adolesc. Psychiatry 53:1206–15
Ellis BJ. 2004. Timing of pubertal maturation in girls: an integrated life history approach. Psychol. Bull.
130:920–58
Ellis BJ. 2013. The hypothalamic-pituitary-gonadal axis: a switch-controlled, condition-sensitive system in
the regulation of life history strategies. Horm. Behav. 64:215–25
Ellis BJ, Bianchi J, Griskevicius V, Frankenhuis WE. 2017a. Beyond risk and protective factors: an adaptation-
based approach to resilience. Perspect. Psychol. Sci. 12:561–87
Ellis BJ, Boyce WT, Belsky J, Bakermans-Kranenburg MJ, van IJzendoorn MH. 2011a. Differential suscep-
tibility to the environment: an evolutionary-neurodevelopmental theory. Dev. Psychopathol. 23:7–28
Ellis BJ, Del Giudice M. 2014. Beyond allostatic load: rethinking the role of stress in regulating human
development. Dev. Psychopathol. 26:1–20
Ellis BJ, Del Giudice M, Dishion TJ, Figueredo AJ, Gray P, et al. 2012a. The evolutionary basis of risky
adolescent behavior: implications for science, policy, and practice. Dev. Psychol. 48:598–623
Ellis BJ, Del Giudice M, Shirtcliff EA. 2017b. The Adaptive Calibration Model of stress responsivity: concepts,
findings, and implications for developmental psychopathology. In Child and Adolescent Psychopathology, ed.
TP Beauchaine, SP Hinshaw, pp. 237–76. Hoboken, NJ: Wiley. 3rd ed.
Ellis BJ, Essex MJ, Boyce WT. 2005. Biological sensitivity to context: II. Empirical explorations of an
evolutionary–developmental theory. Dev. Psychopathol. 17:303–28
Ellis BJ, Figueredo AJ, Brumbach BH, Schlomer GL. 2009. Fundamental dimensions of environmental risk:
the impact of harsh versus unpredictable environments on the evolution and development of life history
strategies. Hum. Nat. 20:204–68
Ellis BJ, Jackson JJ, Boyce WT. 2006. The stress response systems: universality and adaptive individual dif-
ferences. Dev. Rev. 26:175–212
Ellis BJ, Oldehinkel AJ, Nederhof E. 2017c. The adaptive calibration model of stress responsivity: an empirical
test in the Tracking Adolescents’ Individual Lives Survey study. Dev. Psychopathol. 29:1001–21
Ellis BJ, Schlomer GL, Tilley EH, Butler EA. 2012b. Impact of fathers on risky sexual behavior in daughters:
a genetically and environmentally controlled sibling study. Dev. Psychopathol. 24:317–32
Ellis BJ, Shirtcliff EA, Boyce WT, Deardorff J, Essex MJ. 2011b. Quality of early family relationships and
the timing and tempo of puberty: effects depend on biological sensitivity to context. Dev. Psychopathol.
23:85–99
Evans GW, Li D, Whipple SS. 2013. Cumulative risk and child development. Psychol. Bull. 139:1342–96
Fawcett TW, Frankenhuis WE. 2015. Adaptive explanations for sensitive windows in development. Front.
Zool. 12:S3
Fearon RP, Tomlinson M, Kumsta R, Skeen S, Murray L, et al. 2017. Poverty, early care, and stress reactivity in
adolescence: findings from a prospective, longitudinal study in South Africa. Dev. Psychopathol. 29:449–64
Feurer C, McGeary JE, Knopik VS, Brick LA, Palmer RH, Gibb BE. 2017. HPA axis multilocus genetic profile
score moderates the impact of interpersonal stress on prospective increases in depressive symptoms for
offspring of depressed mothers. J. Abnorm. Psychol. 126:1017–28
Figueredo AJ, V´
asquez G, Brumbach BH, Schneider SMR. 2004. The heritability of life history strategy: the
K-factor, covitality, and personality. Soc. Biol. 51:121–43
Figueredo AJ, V´
asquez G, Brumbach BH, Schneider S, Sefcek JA, et al. 2006. Consilience and life history
theory: from genes to brain to reproductive strategy. Dev. Rev. 26:243–75
Foster H, Hagan J, Brooks-Gunn J. 2008. Growing up fast: stress exposure and subjective “weathering” in
emerging adulthood. J. Health Soc. Behav. 49:162–77
Frankenhuis WE, Panchanathan K. 2011. Balancing sampling and specialization: an adaptationist model of
incremental development. Proc. R. Soc. Lond. B 278:3558–65
Frankenhuis WE, Panchanathan K, Belsky J. 2016a. A mathematical model of the evolution of individual
differences in developmental plasticity arising through parental bet-hedging. Dev. Sci. 19:251–74
www.annualreviews.org •Developmental Adaptation to Stress 135
Annu. Rev. Psychol. 2019.70:111-139. Downloaded from www.annualreviews.org
Access provided by University of New Mexico (UNM) on 01/05/19. For personal use only.
PS70CH06_Ellis ARI 20 November 2018 8:32
Frankenhuis WE, Panchanathan K, Nettle D. 2016b. Cognition in harsh and unpredictable environments.
Curr. Opin. Psychol. 7:76–80
Gaydosh L, Belsky DW, Domingue BW, Boardman JD, Harris KM. 2018. Father absence and accelerated
reproductive development in non-Hispanic White women in the United States. Demography 55:1245–67
Georgiev AV, Kuzawa CW, McDade TW. 2016. Early developmental exposures shape trade-offs between
acquired and innate immunity in humans. Evol. Med. Public Health 2016:256–69
Gibbons FX, Roberts ME, Gerrard M, Li Z, Beach SR, et al. 2012. The impact of stress on the life history
strategies of African American adolescents: cognitions, genetic moderation, and the role of discrimination.
Dev. Psychol. 48:722–39
Graber JA, Lewinsohn PM, Seeley JR, Brooks-Gunn J. 1997. Is psychopathology associated with the timing
of pubertal development? J. Am. Acad. Child Adolesc. Psychiatry 36:1768–76
Gunnar MR, Frenn K, Wewerka SS, Van Ryzin MJ. 2009. Moderate versus severe early life stress: associations
with stress reactivity and regulation in 10–12-year-old children. Psychoneuroendocrinology 34:62–75
Harden KP, Wrzus C, Luong G, Grotzinger A, Baiboui M, et al. 2016. Diurnal coupling between testosterone
and cortisol from adolescence to older adulthood. Psychoneuroendocrinology 73:79–90
Hartman S, Li Z, Nettle D, Belsky J. 2017. External-environmental and internal-health early life predictors
of adolescent development. Dev. Psychopathol. 29:1839–49
Hartman S, Widaman KF, Belsky J. 2015. Genetic moderation of effects of maternal sensitivity on girl’s age
of menarche: replication of the Manuck et al. study. Dev. Psychopathol. 27:747–56
Herringa RJ, Burghy CA, Stodola DE, Fox ME, Davidson RJ, Essex MJ. 2016. Enhanced prefrontal-amygdala
connectivity following childhood adversity as a protective mechanism against internalizing in adolescence.
Biol. Psychiatry Cogn. Neurosci. Neuroimaging 1:326–34
Hertzman C. 2012. Putting the concept of biological embedding in historical perspective. PNAS 109:17160–67
Hiatt RA, Stewart SL, Hoeft KS, Kushi LH, Windham GC, et al. 2017. Childhood socioeconomic position and
pubertal onset in a cohort of multiethnic girls: implications for breast cancer. Cancer Epidemiol. Biomark.
Prev. 26:1714–21
Hill SE, Boehm GW, Prokosch ML. 2016. Vulnerability to disease as a predictor of faster life history strategies.
Adapt. Hum. Behav. Physiol. 2:116–33
Ibitoye M, Choi C, Tai H, Lee G, Sommer M. 2017. Early menarche: a systematic review of its effect on
sexual and reproductive health in low- and middle-income countries. PLOS ONE 12:e0178884
James J, Ellis BJ, Schlomer GL, Garber J. 2012. Sex-specific pathways to early puberty, sexual debut and sexual
risk-taking: tests of an integrated evolutionary-developmental model. Dev. Psychol. 48:687–702
Jeschke JM, Gabriel W, Kokko H. 2008. r-Strategist/K-Strategists. In Encyclopedia of Ecology, Vol. 4, ed.
SE Jørgensen, BD Fath, pp. 3113–22. Amsterdam: Elsevier
Johns SE. 2011. Perceived environmental risk as a predictor of teenage motherhood in a British population.
Health Place 17:122–31
Jolicoeur-Martineau A, Belsky J, Szekely E, Widaman KF, Pluess M, et al. 2017. Distinguishing differential
susceptibility, diathesis-stress and vantage sensitivity: beyond the single gene and environment model.
arXiv:1712.04058 [stat.AP]
Joos CM, Wodzinski AM, Wadsworth ME, Dorn LD. 2018. Neither antecedent nor consequence: develop-
mental integration of chronic stress, pubertal timing, and conditionally adapted stress response. Dev. Rev.
48:1–23
Juster RP, Bizik G, Picard M, Arsenault-Lapierre G, Sindi S, et al. 2011. A transdisciplinary perspective
of chronic stress in relation to psychopathology throughout life span development. Dev. Psychopathol.
23:725–76
Keers R, Pluess M. 2017. Childhood quality influences genetic sensitivity to environmental influences across
adulthood: a life-course Gene ×Environment interaction study. Dev. Psychopathol. 29:1921–33
Kopp EB, Medzhitov R. 2009. Infection and inflammation in somatic maintenance, growth and longevity.
Evol. Appl. 2:132–41
Kyweluk MA, Georgiev AV, Borja JB, Gettler LT, Kuzawa CW. 2018. Menarcheal timing is accelerated
by favorable nutrition but unrelated to developmental cues of mortality or familial instability in Cebu,
Philippines. Evol. Hum. Behav. 39:76–81
136 Ellis ·Del Giudice
Annu. Rev. Psychol. 2019.70:111-139. Downloaded from www.annualreviews.org
Access provided by University of New Mexico (UNM) on 01/05/19. For personal use only.
PS70CH06_Ellis ARI 20 November 2018 8:32
Kuzawa CW, Quinn EA. 2009. Developmental origins of adult function and health: evolutionary hypotheses.
Annu. Rev. Anthropol. 38:131–47
Laurent HK, Neiderhiser JM, Natsuaki MN, Shaw DS, Fisher PA, et al. 2014. Stress system development
from age 4.5 to 6: family environment predictors and adjustment implications of HPA activity stability
versus change. Dev. Psychobiol. 56:340–54
Lei MK, Beach SRH, Simons RL. 2018. Childhood trauma, pubertal timing, and cardiovascular risk in adult-
hood. Health Psychol. 37:613–17
Lian Q, Zuo X, Mao Y, Zhang Y, Luo S, et al. 2018. The impact of the Wenchuan earthquake on early
puberty: a natural experiment. PeerJ 6:e5085
Lupien SJ, Ouellet-Morin I, Hupbach A, Tu MT, Buss C, et al. 2006. Beyond the stress concept: allostatic
load—a developmental biological and cognitive perspective. In Developmental Psychopathology,Vol.2:
Developmental Neuroscience, ed. D Cicchetti, DJ Cohen, pp. 578–628. Hoboken, NJ: Wiley. 2nd ed.
Magnus MC, Anderson EL, Howe LD, Joinson CJ, Penton-Voak IS, Fraser A. 2018. Childhood psychosocial
adversity and female reproductive timing: a cohort study of the ALSPAC mothers. J. Epidemiol. Community
Health 72:34–40
Manuck SB, Craig AE, Flory JD, Halder I, Ferrell RE. 2011. Reported early family environment covaries with
menarcheal age as a function of polymorphic variation in estrogen receptor-α(ESR1). Dev. Psychopathol.
23:69–83
Mathot KJ, Frankenhuis WE. 2018. Models of pace-of-life syndromes (POLS): a systematic review. Behav.
Ecol. Sociobiol. 72:41
McEwen BS, Stellar E. 1993. Stress and the individual: mechanisms leading to disease. Arch. Intern. Med.
153:2093–101
Mell H, Safra L, Algan Y, Baumard N, Chevallier C. 2018. Childhood environmental harshness predicts
coordinated health and reproductive strategies: a cross-sectional study of a nationally representative
sample from France. Evol. Hum. Behav. 39:1–8
Mendle J, Leve LD, Van Ryzin M, Natsuaki MN. 2014. Linking childhood maltreatment with girls’ internal-
izing symptoms: early puberty as a tipping point. J. Res. Adolesc. 24:689–702
Mendle J, Ryan RM, McKone KM. 2016. Early childhood maltreatment and pubertal development: replication
in a population-based sample. J. Res. Adolesc. 26:595–602
Mendle J, Turkheimer E, D’Onofrio BM, Lynch SK, Emery RE, et al. 2006. Family structure and age at
menarche: a children-of-twins approach. Dev. Psychol. 42:533–42
Miller GE, Chen E, Zhou ES. 2007. If it goes up, must it come down? Chronic stress and the hypothalamic-
pituitary-adrenocortical axis in humans. Psychol. Bull. 133:25–45
Mittal C, Griskevicius V, Simpson JA, Sung S, Young ES. 2015. Cognitive adaptations to stressful environ-
ments: when childhood adversity enhances adult executive function. J. Personal. Soc. Psychol. 109:604–21
Moore SR, Depue RA. 2016. Neurobehavioral foundation of environmental reactivity. Psychol. Bull. 142:107–
64
Murren CJ, Auld JR, Callahan H, Ghalambor CK, Handelsman CA, et al. 2015. Constraints on the evolution
of phenotypic plasticity: limits and costs of phenotype and plasticity. Heredity 115:293–301
Najman JM, Hayatbakhsh MR, McGee T, Bor W, O’Callaghan MJ, Williams GM. 2009. The impact of
puberty on aggression/delinquency: adolescence to young adulthood. Aust. N. Z. J. Criminol. 42:369–86
Negriff S, Brensilver M, Trickett PK. 2015. Elucidating the mechanisms linking early pubertal timing, sexual
activity, and substance use for maltreated versus nonmaltreated adolescents. J. Adolesc. Health 56:625–31
Nusslock R, Miller GE. 2016. Early-life adversity and physical and emotional health across the lifespan: a
neuroimmune network hypothesis. Biol. Psychiatry 80:23–32
Obradovi´
cJ.2012.Howcanthestudyofphysiologicalreactivitycontributetoourunderstandingofadversity
and resilience processes in development? Dev. Psychopathol. 24:371–87
Peckins MK, Susman EJ, Negriff S, Noll J, Trickett PK. 2015. Cortisol profiles: a test for adaptive calibration
of the stress response system in maltreated and nonmaltreated youth. Dev. Psychopathol. 27:1461–70
Pluess M. 2015. Individual differences in environmental sensitivity. Child Dev. Perspect. 9:138–43
Pluess M, Assary E, Lionetti F, Lester KJ, Krapohl E, et al. 2018. Environmental sensitivity in children:
development of the Highly Sensitive Child Scale and identification of sensitivity groups. Dev. Psychol.
54:51–70
www.annualreviews.org •Developmental Adaptation to Stress 137
Annu. Rev. Psychol. 2019.70:111-139. Downloaded from www.annualreviews.org
Access provided by University of New Mexico (UNM) on 01/05/19. For personal use only.
PS70CH06_Ellis ARI 20 November 2018 8:32
Pluess M, Belsky J. 2011. Prenatal programming of postnatal plasticity? Dev. Psychopathol. 23:29–38
Pluess M, Belsky J. 2013. Vantage sensitivity: individual differences in response to positive experiences. Psychol.
Bull. 139:901–16
R´
eale D, Garant D, Humphries MM, Bergeron P, Careau V, Montiglio P-O. 2010. Personality and the
emergence of the pace-of-life syndrome concept at the population level. Philos. Trans. R. Soc. Lond. B
365:4051–63
Richardson GB, Sanning BK, Lai MHC, Copping LT, Hardesty PH, Kruger DJ. 2017. On the psychometric
study of human life history strategies: state of the science and evidence of two independent dimensions.
Evol. Psychol. 15:1474704916666840
Rickard IJ, Frankenhuis WE, Nettle D. 2014. Why are childhood family factors associated with timing of
maturation? A role for internal prediction. Perspect. Psychol. Sci. 9:3–15
Robles TF, Repetti RL, Reynolds BM, Chung PJ, Arevalo JM, Cole SW. 2018. Family environments and
leukocyte transcriptome indicators of a proinflammatory phenotype in children and parents. Dev. Psy-
chopathol. 30:235–53
Roisman GI, Newman DA, Fraley C, Haltigan JD, Groh AM, Haydon KC. 2012. Distinguishing differential
susceptibility from diathesis-stress: recommendations for evaluating interaction effects. Dev. Psychopathol.
24:389–409
Rowe DC. 2000. Environmental and genetic influences on pubertal development: evolutionary life history
traits. In Genetic Influences on Human Fertility and Sexuality, ed. JL Rodgers, DC Rowe, WB Miller,
pp. 147–68. Boston: Kluwer Acad.
Rutter M. 1993. Resilience: some conceptual considerations. J. Adolesc. Health 14:626–31
Ruttle PL, Shirtcliff EA, Armstrong JM, Klein MH, Essex MJ. 2015. Neuroendocrine coupling across ado-
lescence and the longitudinal influence of early life stress. Dev. Psychobiol. 57:688–704
Saxbe DE, Negriff S, Susman EJ, Trickett PK. 2015. Attenuated hypothalamic-pituitary-adrenal axis func-
tioning predicts accelerated pubertal development in girls 1 year later. Dev. Psychopathol. 27:819–28
Sefcek JA, Figueredo AJ. 2010. A life-history model of human fitness indicators. Biodemogr. Soc. Biol. 56:42–66
Sheppard P, Pearce MS, Sear R. 2016. How does childhood socioeconomic hardship affect reproductive
strategy? Pathways of development. Am. J. Hum. Biol. 28:356–63
Shonkoff JP, Garner AS, Siegel BS, Dobbins MI, Earls MF, et al. 2012. The lifelong effects of early childhood
adversity and toxic stress. Pediatrics 129:e232–46
Shulman EP, Smith AR, Silva K, Icenogle G, Duell N, et al. 2016. The dual systems model: review, reappraisal,
and reaffirmation. Dev. Cogn. Neurosci. 17:103–17
Sijtsema JJ, Nederhof E, Veenstra R, Ormel J, Oldehinkel AJ, Ellis BJ. 2013. Effects of family cohesion
and heart rate reactivity on aggressive/rule-breaking behavior and prosocial behavior in adolescence: the
Tracking Adolescents’ Individual Lives Survey study. Dev. Psychopathol. 25:699–712
Silveira PP, Pokhvisneva I, Parent C, Cai S, Rema ASS, et al. 2017. Cumulative prenatal exposure to adversity
reveals associations with a broad range of neurodevelopmental outcomes that are moderated by a novel,
biologically informed polygenetic score based on the serotonin transporter solute carrier family C6,
member 4 (SLC6A4) gene expression. Dev. Psychopathol. 29:1601–17
Simmons JG, Byrne ML, Schwartz OS, Whittle SL, Sheeber L, et al. 2015. Dual-axis hormonal covariation in
adolescence and the moderating influence of prior trauma and aversive maternal parenting. Dev. Psychobiol.
57:670–87
Simpson JA, Griskevicius V, Kuo SI, Sung S, Collins WA. 2012. Evolution, stress, and sensitive periods:
the influence of unpredictability in early versus late childhood on sex and risky behavior. Dev. Psychol.
48:674–86
Slagt M, Dubas JS, Dekovi´
c M, van Aken MA. 2016. Differences in sensitivity to parenting depending on child
temperament: a meta-analysis. Psychol. Bull. 142:1068–110
Slagt M, Dubas JS, van Aken MAG, Ellis BJ, Dekovi´
cM.2018.Sensoryprocessingsensitivityasamarkerof
differential susceptibility to parenting. Dev. Psychol. 54:543–58
South SC, Hamdi NR, Krueger RF. 2017. Biometric modeling of gene-environment interplay: the intersection
of theory and method and applications for social inequality. J. Personal. 85:22–37
138 Ellis ·Del Giudice
Annu. Rev. Psychol. 2019.70:111-139. Downloaded from www.annualreviews.org
Access provided by University of New Mexico (UNM) on 01/05/19. For personal use only.
PS70CH06_Ellis ARI 20 November 2018 8:32
Sumner JA, Colich NL, Uddin M, Armstrong D, McLaughlin KA. 2018. Early experiences of threat, but not
deprivation, are associated with accelerated biological aging in children and adolescents. Biol. Psychiatry.
In press
Sun Y, Mensah FK, Azzopardi P, Patton GC, Wake M. 2017a. Childhood social disadvantage and pubertal
timing: a national birth cohort from Australia. Pediatrics 139:e20164099
Sun Y, Xu YY, Hu JJ, Tao FB. 2017b. Association of a chronic stress biomarker with advanced development
of breast and testicular volume. JAMA Pediatr. 171:596–98
Sung S, Simpson JA, Griskevicius V, Kuo SIC, Schlomer GL, Belsky J. 2016. Secure infant-mother attachment
buffers the effect of early-life stress on age of menarche. Psychol. Sci. 27:667–74
Szepsenwol O, Simpson JA, Griskevicius V, Raby KL. 2015. The effect of unpredictable early childhood
environments on parenting in adulthood. J. Personal. Soc. Psychol. 109:1045–67
Tither JM, Ellis BJ. 2008. Impact of fathers on daughters’ age at menarche: a genetically and environmentally
controlled sibling study. Dev. Psychol. 44:1409–20
Trickett PK, Gordis E, Peckins MK, Susman EJ. 2014. Stress reactivity in maltreated and comparison male
and female young adolescents. Child Maltreat. 19:27–37
Trickett PK, Noll JG, Putnam FW. 2011. The impact of sexual abuse on female development: lessons from
a multigenerational, longitudinal research study. Dev. Psychopathol. 23:453–76
Trickett PK, Noll JG, Susman EJ, Shenk CE, Putnam FW. 2010. Attenuation of cortisol across development
for victims of sexual abuse. Dev. Psychopathol. 22:165–75
Van Buskirk J, Relyea RA. 1998. Selection for phenotypic plasticity in Rana sylvatica tadpoles. Biol. J. Linn.
Soc. 65:301–28
van IJzendoorn MH, Bakermans-Kranenburg MJ. 2015. Genetic differential susceptibility on trial: meta-
analytic support from randomized controlled experiments. Dev. Psychopathol. 27:151–62
van IJzendoorn MH, Belsky J, Bakermans-Kranenburg MJ. 2012. Serotonin transporter genotype 5HTTLPR
as a marker of differential susceptibility? A meta-analysis of child and adolescent gene-by-environment
studies. Trans. Psychiatry 2:e147
Volk AA, Atkinson JA. 2013. Infant and child death in the human environment of evolutionary adaptation.
Evol. Hum. Behav. 34:182–92
Webster GD, Graber JA, Gesselman AN, Crosier BS, Schember TO. 2014. A life history theory of father
absence and menarche: a meta-analysis. Evol. Psychol. 12:273–94
Wells JC, Johnstone RA. 2017. Modeling developmental plasticity in human growth: buffering the past or
predicting the future? In The Arc of Life, pp. 21–39. Berlin: Springer
West-Eberhard MJ. 2003. Developmental Plasticity and Evolution. Oxford, UK: Oxford Univ. Press
Wilson DS, Yoshimura J. 1994. On the coexistence of specialists and generalists. Am. Nat. 144:692–707
Young ES, Griskevicius V, Simpson JA, Waters TEA, Mittal C. 2018. Can an unpredictable childhood en-
vironment enhance working memory? Testing the sensitized-specialization hypothesis. J. Personal. Soc.
Psychol. 114:891–908
www.annualreviews.org •Developmental Adaptation to Stress 139
Annu. Rev. Psychol. 2019.70:111-139. Downloaded from www.annualreviews.org
Access provided by University of New Mexico (UNM) on 01/05/19. For personal use only.
