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Childhood adversity moderates the influence of proximal episodic stress on the cortisol awakening response and depressive symptoms in adolescents



Childhood adversity (CA) is known to predict sensitization to proximal stressors. Researchers have suggested that disruptions in hypothalamus–pituitary–adrenal axis functioning may be a biological mechanism. If so, CA may predict altered associations between proximal life stress and markers of cortisol secretion. We examined whether CA moderates associations between recent episodic stress and (a) the cortisol awakening response (CAR), and (b) depressive symptoms, in 241 adolescents aged 14–17 years (cortisol n = 196). Salivary cortisol was sampled at 0, 30, and 60 min postawakening for 2 days. The CAR was calculated as the area under the curve with respect to increase and waking cortisol. CA and episodic stress were assessed using contextual-threat-method-coded objective interviews. CA significantly interacted with episodic stress to predict both the CAR and depression. Among those with low CA, episodic stress predicted increased CAR but did not predict depression. For adolescents with high CA, episodic stress predicted lower CAR and higher depression. These interactions were found only for independent (uncontrollable, fateful) events, and not for dependent (self-generated) stress. Increased allostatic load resulting from CA exposure may interfere with adolescents' ability to optimally regulate their CAR in relation to recent stress, contributing to increased depression risk.
Childhood Adversity Moderates the Influence of Proximal Episodic Stress on the Cortisol
Awakening Response and Depressive Symptoms in Adolescents
Lisa R. Starr1
Kimberly Dienes2
Catherine B. Stroud3
Zoey A. Shaw1
Y. Irina Li1
Fanny Mlawer4
Meghan Huang1
1University of Rochester, 2University of Manchester, 3Williams College, 4University of
FINAL CITATION: Starr, L. R., Dienes, K. A., Stroud, C. B., Shaw, Z. A., Li, Y. I., Mlawer,
F., & Huang, M. (2017). Childhood Adversity Moderates the Influence of Proximal Episodic
Stress on the Cortisol Awakening Response and Depressive Symptoms in Adolescents.
Development and Psychopathology, 29(5), 1877-1893. doi:10.1017/S0954579417001468
Author Note. Correspondence should be directed to Lisa R. Starr, Department of Clinical and
Social Sciences in Psychology, University of Rochester, 491 Meliora Hall, Box 270266,
Rochester, NY 14627. Email: Phone: (585) 276-6862. This research
was supported by funds from the University of Rochester. We would like to thank participating
families for generously volunteering their time.
Childhood Adversity Moderates the Influence of Proximal Episodic Stress on the Cortisol
Awakening Response and Depressive Symptoms in Adolescents
Childhood adversity (CA) is known to predict sensitization to proximal stressors. Researchers
have suggested that disruptions in hypothalamic-pituitary-adrenal axis functioning may be a
biological mechanism. If so, CA may predict altered associations between proximal life stress
and markers of cortisol secretion. We examined whether CA moderates associations between
recent episodic stress and a) the cortisol awakening response (CAR), and b) depressive
symptoms, in 241 adolescents aged 14-17 years (cortisol n = 196). Salivary cortisol was sampled
at 0, 30, and 60 minutes post-awakening for two days. The CAR was calculated as the area under
the curve with respect to increase and waking cortisol. CA and episodic stress were assessed
using contextual-threat-method-coded objective interviews. CA significantly interacted with
episodic stress to predict both the CAR and depression. Among those with low CA, episodic
stress predicted increased CAR but did not predict depression. For adolescents with high CA,
episodic stress predicted lower CAR and higher depression. These interactions were found only
for independent (uncontrollable, fateful) events, and not for dependent (self-generated) stress.
Increased allostatic load resulting from CA exposure may interfere with adolescents’ ability to
optimally regulate their CAR in relation to recent stress, contributing to increased depression
KEYWORDS: Childhood Adversity, Episodic Stress, Cortisol Awakening Response,
Depression, Stress Sensitization
Childhood Adversity Moderates the Influence of Proximal Episodic Stress on the Cortisol
Awakening Response and Depressive Symptoms in Adolescents
Researchers seeking to understand the impact of early adversity on trajectories of
psychopathology have increasingly utilized multiple levels of analyses to capture risk and
resilience processes in both biological and behavioral strata (Cicchetti & Blender, 2004). In
particular, depression is a multifaceted phenomenon that not only affects behavioral and
affective systems, but also cognition, interpersonal processes, and biological systems including
neurobiological and neuroendocrinological processes. Understanding the complex framework
within which each of these pathways connect and contribute to the development of depression is
a challenge that calls for research designs that utilize multiple assessment methods at different
levels of analyses. Moreover, experiences that occur in childhood may initiate developmental
cascades that contribute to long-term outcomes. The link between early childhood adversity and
alterations in neurobiological and neuroendocrinological processes has been well established in
the literature (Cicchetti & Rogosch, 2001; Heim, Plotsky, & Nemeroff, 2004; Tyrka, Burgers,
Philip, Price, & Carpenter, 2013). However, less attention has been paid to how these alterations
intersect with proximal experiences, especially recent stressful events. The current study
examines how early adverse experiences modify the relationship between recent episodic stress
and both cortisol regulation and depression.
Childhood Adversity and Stress Sensitization
Research suggests that childhood adversity (CA) predicts increased depressive reactivity
to life stress in a process termed stress sensitization. A number of studies have shown that a
history of childhood adversity lowers the threshold of stressor severity required to trigger a
depressive episode (Espejo et al., 2007; Hammen, Henry, & Daley, 2000; Harkness, Bruce, &
Lumley, 2006; La Rocque, Harkness, & Bagby, 2014; K. D. Rudolph & Flynn, 2007) and
predicts stronger associations between proximal stressors and depression and other negative
outcomes (Kim et al., 2014; McLaughlin, Conron, Koenen, & Gilman, 2010; Shapero et al.,
2014; Starr, Hammen, Conway, Raposa, & Brennan, 2014). Although there are multiple
plausible mechanisms linking CA to stress sensitization (e.g., Szyf, McGowan, & Meaney,
2008), one likely pathway is via disruption of hypothalamic-pituitary-adrenal (HPA) axis
development (Heim, Newport, Mletzko, Miller, & Nemeroff, 2008; McEwen, 1998).
Overview of Hypothalamic-Pituitary-Adrenal (HPA) Axis and Stress Regulation
The HPA axis is a major part of the biological stress response that prepares the body to
optimally respond to threat. Cortisol, the hormonal end-product of the HPA axis, is often used to
index HPA axis functioning. Cortisol affects multiple bodily systems, including immune
functioning, energy metabolism, and neurobiological circuits (Heim & Nemeroff, 2001; Raison
& Miller, 2003); consequently, abnormalities in cortisol regulation have been linked to a wide
variety of clinical and physical health problems, including depression (Chida & Steptoe, 2009).
The Cortisol Awakening Response. Although numerous indicators of HPA axis
functioning have been examined in the literature (for a review, see Granger et al., 2012), one
particularly relevant to depression (and the focus of the present study) is the cortisol awakening
response (CAR). In addition to being released in response to environmental threat (De Kloet,
2004), cortisol secretion follows a typical daily pattern, with peak concentration levels in the
morning followed by declining levels throughout the day, reaching nadir at bedtime (e.g., Adam
& Kumari, 2009; Pruessner et al., 1997). The CAR is an elevation of approximately 50-156% in
cortisol secretion that occurs approximately 30-45 minutes post awakening (Clow, Thorn, Evans,
& Hucklebridge, 2004). It is thought to be distinct from daily, or diurnal, cortisol secretion
(Wilhelm, Born, Kudielka, Schlotz, & Wust, 2007). Although its exact function is uncertain, it
has been suggested that the CAR represents the marshaling of resources to deal with the stress of
the day (Chida & Steptoe, 2009; Fries, Dettenborn, & Kirschbaum, 2009; Powell & Schlotz,
2012). In line with this, the “boost” hypothesis posits that the CAR serves a short-term adaptive
function by mobilizing the body’s resources (via influencing metabolic processes) to help meet
perceived daily demands (Adam, 2006; Fries, Hesse, Hellhammer, & Hellhammer, 2005).
Alterations in the size of the CAR are thought to reflect dysregulation in the functioning of the
HPA axis and have been implicated in negative clinical and health outcomes, including
depression (Adam et al., 2010; Chida & Steptoe, 2009). Two recent prospective analyses of the
same adolescent sample indicated that a greater-than-average CAR predicted onsets of major
depression (Adam et al., 2010; Vrshek-Schallhorn et al., 2013); other studies suggest that
elevated waking cortisol in at-risk individuals prospectively predicts depression (Goodyer,
Bacon, Ban, Croudace, & Herbert, 2009; Goodyer, Herbert, Tamplin, & Altham, 2000; Halligan,
Herbert, Goodyer, & Murray, 2007; Harris et al., 2000). In addition, loneliness and internalizing
symptoms have also been associated with a greater CAR (Doane & Adam, 2010; Saridjan et al.,
2014; Saxbe, 2008). However, existing literature also shows that a smaller-than-average CAR
can reflect burnout and other health problems (Chida & Steptoe, 2009) and has also been
associated with various negative outcomes, including trait loneliness, internalizing symptoms,
PTSD, rumination, and fatigue (Gartland, O’Connor, Lawton, & Bristow, 2014; Keeshin,
Strawn, Out, Granger, & Putnam, 2014; Kuehner, Holzhauer, & Huffziger, 2007; McGinnis,
Lopez-Duran, Martinez-Torteya, Abelson, & Muzik, 2016; Sladek & Doane, 2015). Thus, it
appears that dysregulation in the CAR is associated with risk for depression and related
problems, although the exact nature of this relationship may be complex and methodologically
dependent (see Stalder et al., 2016), requiring further elucidation.
CA and Cortisol Regulation
HPA axis activation may be adaptive in the short-term by allowing the body to manage
the stressor at hand. However, chronic HPA axis activation due to repeated exposure to stressors
during vulnerable developmental periods may lead to sustained alterations in HPA axis
functioning and related neural structures and corresponding problems with stress regulation.
Aligning with this model, a large number of studies have linked negative childhood experiences
to cortisol dysregulation (Cicchetti & Rogosch, 2012; Heim et al., 2008; McCrory, De Brito, &
Viding, 2010; Tarullo & Gunnar, 2006; Trickett, Negriff, Ji, & Peckins, 2011).
Central to research examining the impact of childhood adversity on the HPA axis is the
examination of allostasis, or the body’s response to changes in the environment, including
response to stressors. Allostasis involves many biological mechanisms that help an organism
respond to threat, such as elevations and return to homeostasis in heart rate, breathing, and
cortisol secretion. However, repeated stress exposure during critical periods of development may
lead to allostatic load or a breakdown in the allostatic system (McEwen & Seeman, 1999).
Although cortisol elevations occur in response to environmental stress, over time this pattern
may change, such that the HPA axis inadequately responds to the presence of environmental
stressors, leading to negative health outcomes including psychopathology (McEwen, 2004). In
accordance with this pattern, meta-analytic findings indicate that time since stressor onset is
negatively correlated with HPA axis activity (Miller, Chen, & Zhou, 2007). This suggests that
stress exposure leads to hypercortisolism initially, but over time, in response to prolonged HPA
axis activation as a result of chronically stressful conditions, hypocortisolism develops (e.g.,
Gunnar & Fisher, 2006; Miller et al., 2007; Tarullo & Gunnar, 2006).
Consistent with this model, and looking at the CAR specifically, childhood adversity has
been associated with both greater-than-average CAR (Engert, Efanov, Dedovic, Dagher, &
Pruessner, 2011; Gonzalez, Jenkins, Steiner, & Fleming, 2009; Lu, Gao, Huang, Li, & Xu, 2016;
Lu et al., 2013) and smaller-than-average CAR (Meinlschmidt & Heim, 2005; Quevedo,
Johnson, Loman, LaFavor, & Gunnar, 2012). The disparate findings can likely be partially
attributed to methodological and demographic variables (e.g., pubertal development, CAR
calculation method, and the type, timing, and severity of early adversity; Chida & Steptoe, 2009;
Gustafsson, Anckarsäter, Lichtenstein, Nelson, & Gustafsson, 2010; Miller et al., 2007; Quevedo
et al., 2012). However, the variation in findings may also reflect legitimate complexities of HPA
axis functioning. This may include the existence of untested moderators, such as the presence of
recent stressors. Indeed, no studies have examined the interactive effect of CA and proximal
episodic stress in the prediction of the CAR. The current study addresses this gap.
CA as a Moderator of the Association between Recent Episodic Stress and the CAR
If the CAR represents an adaptive mechanism for managing stressful contexts, one would
expect that among those with optimal HPA axis functioning, the CAR would be positively
correlated with recent significant life stressors. Stressful life events predict continued hassles in
daily life (Wagner, Compas, & Howell, 1988), and an elevated CAR may allow for recruitment
of resources necessary to cope with ongoing demands and promote allostasis (McEwen, 1998),
potentially protecting against negative outcomes such as depression. Indeed, recent life stress is
associated with elevations in the CAR (see Chida & Steptoe, 2009 for a meta-analysis) and other
markers of diurnal cortisol activity (Stroud, Chen, Doane, & Granger, 2016). However, it is
possible that exposure to childhood adversities could disrupt this process. A developmental
history of repeated activation of the HPA axis may lead to increased allostatic load, which could
be reflected in inadequate responding (i.e., decreased CAR) to stressful contexts (as denoted by
high recent episodic stress; McEwen, 2004). This, in turn, may leave adolescents with fewer
metabolic resources to manage the aftermath of these recent stressors, making them more
vulnerable to depression. Indeed, it has been hypothesized that youths who develop
hypocortisolism in response to chronic stress exposure may be less able to adapt to future
stressors (Cicchetti & Rogosch, 2012), potentially accounting for stress sensitization effects.
Building on these ideas, the current study examines whether CA moderates the association
between recent episodic stress and a) the CAR, and b) depressive symptoms.
Sensitization to Independent versus Dependent Stressors
The effect of environmental stress on the HPA axis appears to be contingent upon the
qualitative nature of the stressors (Miller et al., 2007; Stroud et al., 2016). For example, the
literature on naturalistic life stress draws a crucial distinction between independent and
dependent stressors (Hammen, 2005). Independent stressors are fateful events outside of the
individual’s control (e.g., death of loved one, sudden loss of parental employment), whereas
dependent stressors are events to which the individual has at least partially contributed (e.g.,
interpersonal conflict, academic failure). Thus, event independence can be considered a marker
of the controllability of naturalistic events. The controllability of stress has been identified as an
important dimension likely to influence HPA axis response (Dickerson & Kemeny, 2004; Miller
et al., 2007). In laboratory studies, uncontrollable stressors provoke a more pronounced HPA
axis response (Dickerson & Kemeny, 2004), perhaps because a lack of control makes acute stress
inherently more threatening. However, experiencing more persistent uncontrollable stressors,
including naturalistic stressors which are more personally and persistently impactful than
laboratory stressors, may instead lead to a blunting of cortisol responses (Miller et al., 2007),
perhaps aligning with withdrawn and learned helplessness behaviors associated with depression.
In contrast, controllable stressors (such as dependent events) may lead to an increase in cortisol
production to mobilize metabolic resources for coping.
A history of CA may be particularly relevant in moderating the influence of
uncontrollable, independent stressors on the HPA axis. Childhood adversities are themselves
inherently more likely to be uncontrollable experiences, as from a developmental standpoint,
children typically lack autonomy over many aspects of their environment (Harkness et al., 2010).
Independent proximal stressors may be reminiscent of these negative childhood experiences.
Consequently, children with a long history of such experiences may be more attuned to the
uncontrollable nature of independent stressors, and more likely to disengage both emotionally
(through increased depression) and physiologically (by failing to deploy metabolic resources for
Some evidence suggests that early adversity may predict sensitization to independent, but
not dependent, events, although evidence is mixed. At least two studies have shown that
adolescents with a history of maltreatment require a lower threshold of independent (but not
dependent) stress to trigger a depressive episode (Harkness et al., 2006; La Rocque et al., 2014).
Another study showed that independent (but not dependent) events interacted with childhood
maltreatment to predict alcohol consumption among women (Young-Wolff, Kendler, & Prescott,
2012). In contrast, Shapero et al. (2014) found that childhood emotional abuse predicted stronger
associations between stress and depressive symptom increases only for dependent events, and an
additional study found that event independence did not influence stress sensitivity patterns
(Oldehinkel, Ormel, Verhulst, & Nederhof, 2014). Further, in addition to CA, research suggests
that depression history also sensitizes individuals to stressors, (with less severe stressors required
to trigger recurrences versus first onsets; e.g. Monroe & Harkness, 2005; Post, 1992), and that
form of stress sensitization also appears to be stronger for independent versus dependent
stressors (Stroud, Davila, Hammen, & Vrshek-Schallhorn, 2011). However, few studies have
examined the discrepant impact of independent versus dependent stressors on cortisol regulation.
In one exception, in a sample of early adolescent girls, Stroud et al. (2016) found that
independent, but not dependent, stressors predicted level of latent trait cortisol, after adjusting for
CA. However, no studies to our knowledge have examined the CAR specifically in association to
independent versus dependent stress or assessed cortisol regulation in response to dependent
versus independent stressors as moderated by CA. To address this gap in the literature, we
examined whether CA moderated the association between independent versus dependent
stressors and a) the CAR and b) depressive symptoms.
Developmental Considerations
Adolescence is likely a critical period to consider these research questions given
increasing biological changes and environmental challenges. Early adolescence is characterized
by changes in adrenocortical functioning, including increases in basal cortisol levels and cortisol
reactivity to stress (Gunnar, Wewerka, Frenn, Long, & Griggs, 2009; Shirtcliff et al., 2012). This
period is also accompanied by increased autonomy seeking and conflict with parents, reduced
support in school environment, and greater motivation for peer acceptance and romantic
experiences (Collins, 1990, 2003; Seidman, Allen, Aber, Mitchell, & Feinman, 1994). Moreover,
associations between HPA axis activity and environmental stress differ according to gender, age,
and pubertal status (Gunnar et al., 2009; Pendry & Adam, 2007). These factors may heighten
adolescents’ reactivity to proximal stressors, resulting in a surge in onset of depressive symptoms
and disorders in adolescence (Birmaher et al., 1996; Hankin et al., 1998; Kessler, Avenevoli, &
Ries Merikangas, 2001; Lewinsohn, Hops, Roberts, Seeley, & Andrews, 1993). As such, CA has
been associated with lower severity of proximal episodic stress prior to depression onset in
adolescence (Harkness et al., 2006; Shrout et al., 1989). In contrast, its effect on subsequent
stress reactivity in prepubertal youth and adults (Bifulco, Brown, Moran, Ball, & Campbell,
1998; Kendler, Kuhn, & Prescott, 2004; McLaughlin et al., 2010; Slavich, Monroe, & Gotlib,
2011) has been variable across studies. In a recent study, La Rocque et al. (2014) directly
compared the relation of CA and stress sensitization across developmental periods and found that
childhood maltreatment was associated with heightened sensitization to proximal stressors in
adolescence, but not adulthood. Moreover, this relation was specific to independent stressors,
aligning with our hypotheses. These results suggest that adolescence might be a sensitive period
during which youth with a history of adversity are most sensitive to stress, but do not consider
neurobiological mechanisms that may explain this association. The current study extends such
findings by investigating how HPA axis functioning, and more specifically the CAR, may relate
to increased sensitization to stressors in adolescence with a history of CA.
The Present Study
We examined the associations between CA, recent episodic stress, and
neuroendocrinological and emotional outcomes in a sample of adolescents recruited from the
community. Specifically, our hypotheses were as follows: a) CA will moderate the association
between recent episodic stress and the CAR, and b) this moderation effect will be particularly
strong for independent episodic stressors. c) Replicating previous findings, CA will intensify the
association between episodic stress and depression, and d) this moderation effect will again be
particularly robust for independent stressors. CA and recent episodic stressors were both
assessed using gold-standard objective stress interviews coded using contextual threat methods
(Harkness & Monroe, 2016; Monroe, 2008). CA was assessed as a cumulative index of major
adverse events occurring over the adolescents’ lifetime (excluding the prior year), and episodic
stress was assessed a sum of past-year stressors, both in line with the notion that continued,
repeated exposure to stress (as opposed to exposure to a single major event) result in greater
allostatic load (Evans, 2003; Evans, Kim, Ting, Tesher, & Shannis, 2007; Lupien et al., 2006).
The full sample included 241 adolescents aged 14-17 years (Mage = 15.90 years, SD =
1.09; 54% female) who participated with their primary caregiver. Adolescents were excluded
from the study if there was evidence of pervasive developmental disorder, a prior diagnosis of
bipolar or psychotic disorder, and any major physical or neurological disorder. Exclusion criteria
also included English reading or language difficulties and prior participation of another
household member in the study. In addition, to participate in the cortisol component of the study,
adolescents could not be using any steroid-based medications, be currently pregnant, or have an
endocrine disorder. Twelve participants were ineligible to participate in cortisol collection, but
were permitted to participate in other study procedures.
Participants were recruited from a mid-sized metropolitan area in the Northeast United
States. To obtain a sufficiently sized sample, we utilized multiple recruitment methods. First, 134
families (50.6%) were recruited using advertisements posted online and in the community and
distributed to participating families. Special attention was given to posting flyers in
socioeconomic diverse areas of the community. Second, 97 families (40.2%) were recruited
using a commercial mailing list. These candidates were randomly drawn from a commercial
mailing list of families identified by a survey marketing firm as having a child in the eligible age
range. Commercial mailing lists have been established as a cost-effective recruitment method
that yields samples demographically comparable to random digit dialing (Wilson, Starr, Taylor,
& Dal Grande, 1999), and have previously been used to examine internalizing disorder risk in
adolescent samples (Foti, Kotov, Klein, & Hajcak, 2011). Selected families were sent a letter to
provide initial details about the study, followed by phone calls from study staff to give more
detailed information about the study. Finally, a small number of participants (n = 10, 4.1%) were
recruited using ResearchMatch, a national health volunteer registry containing a large population
of volunteers who have consented to be contacted by researchers about health studies. There
were no differences across recruitment method on gender, age, or racial ethnic group. However,
adolescents recruited via advertisements were more likely to receive subsidized lunch at school
than those recruited through alternate methods (c2 = 10.50, p= .005). Study procedures were
approved by the University of Rochester Research Subjects Review Board.
The full sample included 130 girls and 111 boys
(age range 14.00 – 17.97). Participants
identified the following racial/ ethnic backgrounds: 73.9% White, 12.2% Black, 4.1% Asian,
7.1% Multiracial, 2.1% other or no race reported, and 0.4% Native American. In addition, 9.1%
identified as Hispanic or Latino. The median parent-reported annual family income was $80,000-
89,999. In addition, 24.1% of parents reported that their child received free or reduced price
lunch at school (an index of economic hardship). For the majority of families, the participating
parent was the biological mother (87.6%); the remaining families participated with a biological
father (8.7%) or other guardian (3.7%).
Depressive Symptoms. Adolescents’ current symptoms of major depressive disorder
(MDD) were assessed using the Schedule for Affective Disorders and Schizophrenia for School-
Aged Children—Present and Lifetime version (KSADS; Kaufman et al., 1997) which is a semi-
structured diagnostic interview that has demonstrated strong validity and reliability (Kaufman et
al., 1997). Consistent with prior work (e.g., Rao, Daley, & Hammen, 2000; Starr et al., 2012), to
capture both major depression and subsyndromal symptoms of the disorder, trained interviewers
rated the disorder dimensionally on a 5-point scale: 0 (no symptoms), 1 (mild symptoms), 2
(moderate, subthreshold symptoms), 3 (DSM-IV criteria met), 4 (DSM-IV criteria met with high
severity). To assess inter-rater reliability, 20% of the audiotaped interviews were rated by a
Note that we also assessed non-binary gender identification, and three adolescents (1.2%) self-
identified as gender fluid. Because of the relevance of sex hormones to cortisol regulation, these
individuals were classified by biological sex for the present analyses.
second coder blinded to initial ratings, with 100% reliability. To capture self-reported depression
severity, adolescents also completed the 21-item Beck Depression Inventory-II (BDI; Beck,
Steer, & Brown, 1996), a widely used self-report measure of depressive symptoms with strong
psychometric properties (Beck et al., 1996). The 21 BDI items are rated from 0 to 3 and assess
affective and somatic symptoms of depression. Cronbach’s alpha was .88.
Episodic Stress. Episodic stressors were assessed using the UCLA Life Stress Interview
(LSI; Hammen, 1991), a semi-structured interview developed to assess life stress in different
domains. Acute or episodic life stressors over the past 12 months were assessed in six domains:
close friendships, peer relationships, romantic relationships, family relationships, academic
functioning, and behavioral functioning. For each event, interviewers elicited information about
the surrounding context, including relevant circumstances, duration, prior experience with
similar events, and available resources. An objective negative impact rating for each event was
then obtained by a trained team of coders, based on the degree of impact on a typical individual
within the context of the event. In cases where both parent and child nominated the same event,
information from both respondents was integrated. Negative impact was rated on a scale from 1
(no negative impact) to 5 (extremely severe impact). The team also rated independence of each
event, which was dichotomized as dependent versus independent. A second team of coders,
blinded to the original ratings, rated a subset of events with excellent reliability, ICC = .87.
Severity scores were summed (excluding “non-events” rated as “1”) to obtain indices of total
episodic stress, total independent stress, and total dependent stress.
CA. A modified version of the Youth Life Stress Interview (K. D. Rudolph & Flynn,
2007; K. D. Rudolph et al., 2000) was administered to parents to assess adolescents’ level of CA.
Trained interviewers asked a series of questions to assess the adolescent’s exposure to negative
life events and circumstances across their entire lifetime, excluding events within the past year to
distinguish from recent stressors. Probes assess potential exposure to particularly stressful or
negative events and circumstances (e.g., death of a close family member or friend, separation
from parents, parental conflict or separation, chronic physical illness of family members, period
of significant financial difficulties, and chaotic family living circumstances). Using the same
probes as those used for episodic stressors on the LSI, the interviewer then elicited objective
information surrounding the event, including context and relevant circumstances that can modify
the impact of the event. A team of coders then rated the negative impact on the same scale of 1
(no negative impact) to 5 (extremely severe impact), accounting for contextual factors.
Participants reported an average of 4.56 events (range = 0 – 13). Ratings for all lifetime events
were summed to achieve an overall lifetime adversity score, excluding non-events (those rated as
“1”). Reliability using independent raters yielded an intraclass correlation of .97.
Pubertal Development. The Pubertal Development Scale (PDS; Petersen, Crockett,
Richards, & Boxer, 1988) was administered for inclusion as a covariate in cortisol analyses. The
PDS is a self-report scale with four questions (responses ranging from 1=has not yet begun to
4=seems completed) assessing growth, skin changes, and body hair. Girls were asked two
additional questions about breast development and whether they had begun menstruating (1=no
and 2=yes). Boys were asked two questions about changes in facial hair and voice. Responses
were averaged across all items to yield an overall pubertal development scale score. For the
menstruation item, a response of no was coded as 1 and a response of yes was coded as 4.
Participating youth and their parents or guardians provided consent/assent, after which
they were separately interviewed and completed a battery of questionnaires. Families were paid
$160 for participation in all study procedures and entered into raffles to encourage compliance.
Cortisol. At the end of their laboratory visit, participants were given materials to collect
salivary cortisol from their home. Families were given detailed verbal and written instructions on
how to collect ambulatory saliva samples, and were provided with a website link with additional
written instructions and a video demonstrating all procedures. Study staff and all instructional
materials heavily emphasized the importance of accurate timing and reporting. Participants were
instructed to collect ambulatory salivary cortisol samples four times a day for two consecutive
days. Sample collection days were timed between Tuesday and Thursday because of well-
established findings suggesting substantial differences in morning cortisol on Mondays (Kelly,
Young, Sweeting, Fischer, & West, 2008) and on weekends (Schlotz, Hellhammer, Schulz, &
Stone, 2004; Friday is often included as a weekend in cortisol research; see Boderick, Arnold,
Kudielaka, & Kirschbaum, 2004). Participants collected samples immediately after waking
(“before you get out of bed, right after you open your eyes”), 30 minutes after waking, 60
minutes after waking and 12 hours after waking on two consecutive weekdays (the final sample
of the day was not used in the current analyses). Because toothpaste and certain foods and drinks
can degrade or dilute salivary cortisol, adolescents were asked to refrain from brushing teeth,
eating, and drinking for 30 minutes prior to collecting each sample (Kudielka, Hawkley, Adam,
& Cacioppo, 2007). However, to accommodate school preparations, some flexibility was
required around the timing of the third sample. If participants had to eat, drink or brush teeth
within the first 60 minutes of waking, they were asked to do so immediately after completing the
second sample, and then delay the third sample to 30 minutes after completing those activities.
Samples were collected using Salivette® Cortisol (Sarstedt, Inc.) synthetic swabs
designed explicitly for determination of cortisol from saliva. To collect each sample, participants
placed a swab from the container in their mouth, and let it collect saliva until it was saturated.
Participants then indicated whether they ate, drank, brushed their teeth, or participated in
vigorous activity in the 30 minutes before each sample. Participants also indicated their waking
time and how many hours they slept, and female participants provided information on their
menstrual cycle. Completed samples and information forms were mailed to the lab, where
samples were stored at -20˚ C. Of the original sample of 241, 12 were excluded from cortisol
procedures for medical reasons and 18 declined to participate in cortisol procedures or failed to
return samples, leaving 211 participants with samples that were assayed. Samples were shipped
to Dresden, Germany, where they were assayed for cortisol using time-resolved immunoassay
with fluorescence detection (DELFIA; Dressendörfer, Kirschbaum, Rohde, Stahl, & Strasburger,
1992). The laboratory conducting the assays has reported intra- and interassay coefficients of
variance below 12%.
Electronic MEMS® caps recorded the time and date that each bottle containing Salivettes
was opened for a randomly selected 28 of the 211 participants (13.3%) in order to check that
accurate time reporting occurred (to encourage compliance, all participants were told there was a
chance they would be monitored, as suggested by Adam & Kumari, 2009). Data were
downloaded using MEMS software (PowerView, version 3.5.2). The timing and sample intervals
that the participants reported collecting the samples closely corresponded to the MEMS data. For
the critical interval between Samples 1 (awakening) and 2 (30 minutes post-awakening), the
MEMS-recorded time intervals deviated from self-reported time intervals by an average of only
2.63 minutes (average MEMS-recorded interval= 31.94 minutes), and 96% of MEMS-based
intervals were within seven minutes of the self-reported interval. Similar accuracy was found for
the Sample 2 to Sample 3 interval.
The CAR was calculated using area under the curve (AUC) analyses with respect to
ground (AUCg) and increase (AUCi) (Pruessner, Kirschbaum, Meinlschmid, & Hellhammer,
2003). AUC is a trapezoidal formula frequently used in endocrinological research because it
provides a single variable to comprise information contained in repeated measures over time
(Pruessner et al., 2003). AUCg measures overall cortisol secretion by assessing differences of
measurements from the ground, or 0, and AUCi focuses on change over time with reference to
the first value, or baseline sample. AUCi and S1 are the most commonly used outcome variables
in CAR research, because AUCi includes the change over time from baseline and S1 is waketime
cortisol and has been shown to be related to clinical and health outcomes apart from the curve of
the CAR (Stalder et al., 2016). Therefore, these were the focus of the current analyses.
Mean CAR AUCi and S1 were calculated across two days of sampling. Two days is not
enough to capture within person variability and therefore the outcomes were collapsed across the
two days (Segerstrom, Sephton, & Westgate, 2017). Both variables were winsorized to 3
standard deviations to correct for outliers (two datapoints for AUCi, three for S1).
CAR calculations are extremely sensitive to variability in sampling. Therefore, careful
measures were taken to exclude values that might not accurately represent the CAR. Eleven out
of 211 participants (5.2%) were missing cortisol values and were excluded from CAR AUCi
analyses. Of those 11, 5 had waking cortisol values and were included in S1 analyses for a total
of 6 participants with missing data (2.8%). Some participants were missing data only on one day
of sampling. This led to an elimination of 8 days of CAR sampling out of 422 (1.9%), but four of
these days were useable for S1 calculations so only 4 days were eliminated from these analyses
(0.9%). We also eliminated days when vigorous activity was reported prior to morning samples,
which led to the removal of four additional days from CAR analyses.
Timing is an important issue in CAR sampling. If the timing was off for more than 10
minutes between the waking and +30 sample, the day of sampling was eliminated. If the timing
was off for more than 10 minutes between the +30 and +60 sample, we noted this and examined
the effects in analyses using a dummy variable (“TimingOFF”). If the timing was off for greater
than 30 minutes between the second and third sample, the day of sampling was eliminated. This
resulted in 24 days of sampling eliminated out of 422 (5.7%) for the CAR AUCi. Cortisol values
at each sampling time were winsorized to correct for extreme outliers (greater than 3 standard
deviations) (5 datapoints for waking, 2 for +30 minutes, and 5 for + 60 minutes). After all data
cleaning procedures, the final sample size was 196, which was used for all CAR analyses (N=
205 for S1 analyses). For non-cortisol related analyses, the full sample size of 241 was used.
There were no differences between the cortisol sample and the 45 participants excluded from
cortisol analyses on age, gender, or MDD symptoms, but participants in the cortisol sample
showed lower BDI scores and were more likely to be White, ps < .05).
Bivariate Correlations and Main Effects
All analyses were conducted in IBM SPSS 24. Bivariate correlations among behavioral
study variables are presented in Table 1. As shown there, all CA and episodic stress variables
were significantly, positively correlated with each other (ps < .05), apart from CA and
independent stress, which were only marginally correlated (p= .059). In addition, CA and all
episodic stress variables were significantly correlated with current depressive symptoms.
Significance of correlations was unchanged when controlling for sex, age, and race.
To examine main effects of stress variables on the CAR, we conducted linear regression
analyses, controlling for biobehavioral correlates. Consistent with our interaction models (see
below), these models included the following covariates: sex, pubertal stage, follicular stage of
menstrual cycle (boys were coded 0), hours slept the night before, and wake time (averaged
across the two days of sampling). After accounting for these covariates, none of the study
variables significantly predicted the CAR AUCi, including CA, b= 1.99, SE= 2.33, p= .393, total
episodic stress severity, b= 472, SE= 3.76, p = .901, total independent severity, b= 1.93, SE=
5.21, p= .712, or total dependent severity, b= -1.59, SE= 6.49, p= .806. The CAR AUCi was also
not significantly related to current self-reported depressive symptoms, b= -4.24, SE= 2.67, p=
.113, and interview-assessed MDD symptoms, b= -37.05, SE= 23.76, p= .121. Additional
covariates (including age, race, birth control use, the TimingOFF dummy varaible, and reports of
eating or drinking during the 30 minutes prior to their morning saliva samples) were non-
significant in models and their inclusion did not impact results. We also examined the
association between S1 cortisol and CA, episodic stress, dependent stress, independent stress,
and depressive symptoms, controlling for key covariates, and found no significant associations
(all ps > .05).
Episodic Stress
CA, Predicting CAR
All interaction models were conducted using PROCESS macros for SPSS (Hayes, 2013).
Our main outcome of interest was the CAR using the AUCi calculation method. In initial
models, we included the following demographic and biobehavioral covariates: sex, age, race
(dummy coded as White vs. non-White), follicular stage of menstrual cycle (boys were coded 0),
current use of hormonal birth control, hours slept the night before, and wake time (averaged
across two sample days), whether the day of cortisol sampling was a school day, the TimingOFF
dummy code (averaged across two days), and reports of eating or drinking during the 30 minutes
prior to their morning saliva samples (averaged across samples). To simplify models, we
dropped highly non-significant covariates (ps > .15). Following this decision rule, the following
covariates were retained: sex, pubertal status, follicular stage, wake time, and total sleep time.
An identical set of covariates emerged as significant across all interaction models with CAR
AUCi as the outcome. This allowed us to use the same set of predictors across models,
facilitating model comparison. Note that adding any of the excluded covariates did not
substantially impact results.
We first tested the interaction between CA and overall episodic stress, predicting the
CAR. We constructed a model including the main effects of CA and total episodic stress severity
(both mean-centered) and their interaction, plus the covariates. Results are presented in Table 2.
The interaction term was significant (p = .009). We decomposed the significant interaction by
conducting simple slope tests at one standard deviation above and below the mean of CA. At low
levels of CA, there was a positive trending association between recent episodic stress and the
CAR, b = 8.00, SE = 5.11, p= .119, 95% C.I. [-2.09, 18.09]. At mean levels of adversity, the
association was non-significant, b = -1.95, SE = 3.65, p = .593. In contrast, at high levels of CA,
recent episodic stress significantly predicted lower levels of CAR, b= -11.90, SE= 5.38, p= .028,
95% C.I. [-22.52, -1.28]. This interaction is illustrated in Figure 1a. We used the Johnson-
Neyman technique to determine region of significance; episodic stress predicted significantly
decreased CAR at a =.05 when CA scores were above the 78th percentile of our sample.
To examine whether this interaction held for dependent versus independent stress, we
separately conducted models using total dependent stress severity and total independent stress
severity as independent variables, moderated by CA. Models were analogous to the previous
model, with identical covariates included. The dependent stress
CA interaction was not
significant, p= .361. In contrast, the independent stress
CA effect, predicting the CAR, was
significant, p= .013. At low levels of CA, there was a marginally significant, positive association
between recent independent stress and CAR, b= 12.89, SE= 7.01, p= .068, 95% C.I. [-.95,
26.72]. At mean levels of adversity, there was no association between independent stress and the
CAR, b = .74, SE= 5.11, p = .885. In contrast, at high levels of CA, the association between
recent independent stressors and CAR trended negative, b= -11.41, SE= 7.08, p= .109, 95% C.I.
[-25.37, 2.56]. Region of significance analyses suggested independent stress significantly
predicted increased CAR when adversity was below the 5th percentile, and predicted decreased
CAR when adversity was above 91st percentile. Figure 1b and 1c illustrate these findings.
We also tested all of the above interactions with S1 (waking) cortisol as the outcome.
There were no significant interactions between CA and episodic stress (including total,
independent, and dependent stress) predicting S1 cortisol (all ps > .05).
Episodic Stress
CA, Predicting Depressive Symptoms
We next examined interaction models with interview-assessed MDD symptoms as the
outcome. Main effects for episodic stress variables and CA were entered along with their
interaction. Demographic variables (sex, Caucasian race, and age) were entered as covariates.
Results are displayed in Table 3. First looking at overall episodic stress, the interaction term was
significant (p= .048). Recent episodic stressors did not significantly predict MDD symptoms at
low levels of CA, b= .02, SE= .01, p= .273, C.I. [-.01, .04], but did predict higher symptoms at
mean (b= .03, SE= .01, p < .001, C.I. [.01, .05] and high (b= .05, SE= .01, p< .001, C.I. [.03,
.08]) levels of adversity. Region of significance analysis indicated that episodic stress
significantly predicted MDD when CA was above the 31st percentile.
Next, we separately examined dependent and independent stress, revealing a pattern
analogous to that observed for the CAR. Specifically, CA did not moderate the association
between dependent stress and MDD symptoms, p= .661. As illustrated in Figure 2b, the
association between dependent stress and MDD symptoms was significant at both high and low
levels of CA. In contrast, when independent stress was entered as the independent variable, the
interaction term approached significance b= .003, SE= .001, p= .071, C.I. [.00, .01]. Aligning
with expectations, the association between independent stress did not predict MDD symptoms at
low levels of CA, b= .00, SE= .02, p= .845, C.I. [-.03, .04], but significantly predicted MDD
symptoms at mean (b = .03, SE= .01, p = .042, C.I. [.001, .054]) and high levels of CA, b= .05,
SE= .02, p= .005, C.I. [.02, .09]. Figure 2c illustrates this interaction. Johnson-Neyman analyses
indicated that independent stress predicted depressive symptoms at above the 56th percentile of
CA. Thus, for both CAR and depressive symptom outcomes, CA moderates the effects of
independent but not dependent episodic stressors.
As an added test of this moderation finding, we re-tested these interaction models with
self-reported depressive symptoms (BDI) as the outcome in place of interview-assessed
depression. The pattern of results was identical [Table 3]. First examining overall episodic stress,
the interaction term was marginally significant, b= .02, SE= .01, p= .067, 95% C.I. [.00, .05]. At
low levels of CA, recent episodic stressors did not significantly predict BDI, b= .07, SE= .14, p=
.606, C.I. [-20, .35], but at high levels of CA, recent episodic stress strongly predicted BDI, b=
.42, SE= .13, p= .002, C.I. [.16, .69], although this decomposition must be interpreted with
caution given the marginal significance of the interaction term. Next, consistent with previously
reported results, there was no significant interaction between dependent stress and CA,
predicting BDI, b= .00, SE= .02, p= .982, C.I. [-.04, .04]). Finally, again aligning with previous
findings, the independent episodic stress
CA effect was significant (p= .039). Conforming with
expectations, the association between independent stress did not predict depressive symptoms at
low levels of CA, b= -.01, SE= .19, p= .959, C.I. [-.39, .37], but significantly predicted
depressive symptoms at high levels of CA, b= .53, SE= .18, p= .003, C.I. [.18, .89].
The current study adds to a growing body of evidence supporting the stress sensitization
model, showing that exposure to adversity over the course of childhood modifies the effects of
continued exposure to stressful contexts later in development. Guided by a multiple levels of
analysis approach, we found two intriguingly parallel sets of findings focused on two distinct
outcomes, one neuroendocrinological (the CAR) and one behavioral (depressive symptoms).
First, higher levels of CA predicted significantly altered associations between recent episodic
stress and the CAR. Second, CA intensified the association between episodic stress and
depressive symptoms. For both outcomes, stress sensitization effects were significant for
independent but not dependent stress.
These parallel sets of findings may suggest that one way in which CA gets “under the
skin” is by disrupting HPA axis functioning, consistent with the allostatic load framework
(McEwen, 1998). Repeated activation of the HPA axis during childhood may culminate in
allostatic load, and persistent exposure to excess cortisol during pivotal stages of development
may alter neural circuits associated with the HPA axis (Heim et al., 2008), leading to sustained
abnormalities in cortisol regulation. Looking at our specific pattern of results, among those with
low levels of CA, there was a trend toward a positive association between recent episodic stress
and CAR. We speculate that this may be indicative of optimal HPA axis functioning: recent
episodic stressors signal to the adolescent that he or she may encounter continued challenges in
the upcoming day, and the body mounts an increased CAR to marshal metabolic resources to
cope with these expected challenges (Adam, Hawkley, Kudielka, & Cacioppo, 2006). In turn, the
adolescent is protected from negative outcomes such as depression (in line with our finding that
recent episodic stress is non-predictive of depressive outcomes among those with low CA).
Among those with high CA, however, this process may break down, as evidenced by a negative
correlation between recent episodic stress and CAR, and a corresponding increased association
between episodic stress and depression.
It is worth noting that although we found that CA predicted a negative association
between episodic stress and the CAR, our results do not suggest a pervasive pattern of
hypocortisolism (with respect to the CAR) among those with high levels of CA; importantly,
there was no significant main effect of CA on the CAR. Indeed, as illustrated in Figure 1a, at low
levels of episodic stress, those with high CA showed significantly larger CARs than did those
with low CA. This may suggest that youth with high CA experience elevated CARs irrespective
of the absence of recent stress (consistent with the stress autonomy model; see Monroe &
Harkness, 2005) , potentially wasting metabolic resources. Alternatively, it may be that these
youth have a very low threshold of recent stress for an elevated CAR (consistent with the stress
sensitization model; see Monroe & Harkness, 2005). Our analyses cannot distinguish between
these possibilities; however, it is clear that the elevations in the CAR associated with CA vanish
in the presence of episodic stress, corresponding with an increase in depression risk. Our findings
may help reconcile seemingly inconsistent findings that link CA and depression to both smaller-
than-average and larger-than-average CARs, as differences in recent episodic stress may alter
these associations. It should also be noted, however, that these differences in findings are also
likely a result of other factors, including methodological and demographic variations across
studies (Chida & Steptoe, 2009; Gustafsson et al., 2010; Miller et al., 2007; Quevedo et al.,
2012). Clearly, HPA axis functioning is remarkably complicated, and far more research will be
needed to fully understand its many nuances.
We also examined whether effects were found for independent (uncontrollable, fateful)
versus dependent (controllable, self-generated) stress. Although previous findings have varied,
we expected stronger effects for independent stress because of the preponderance of studies that
have suggested that stress sensitization effects are specific to independent stress (Harkness et al.,
2006). Here, we found that the interaction between CA and episodic stress was indeed significant
for independent stress, and not for dependent stress, in the prediction of both the CAR and
depression. However, a visual inspection of the results (see Figures 1 and 2) adds a wrinkle to
our interpretation. It appears that adolescents with low CA are protected against depressive
symptoms following independent stress, but not dependent stress. Indeed, all youth showed
elevated depressive symptoms following dependent stress regardless of their CA level. This
finding corresponds to a parallel result for the CAR: for adolescents with low adversity, high
levels of recent independent stress predicted a higher CAR, while CAR was not influenced by
level of recent dependent stress regardless of adversity level. In other words, youth with low CA
were sensitive to dependent stress only, whereas youth with high CA were sensitive to both kinds
of stress, as indicated by both outcomes.
In line with the hypothesized model we presented above, it is possible that adolescents
with low adversity histories have a larger CAR following recent independent stress, and that this
larger CAR protects them against negative emotional consequences by summoning metabolic
resources to fuel coping efforts. However, this protective process appears to only occur for
fateful, uncontrollable stress, and not for self-generated stress. It is not completely clear why this
would be the case. Perhaps adolescents with low CA are less likely to engage in self-blame
following independent events, allowing them to better focus on coping efforts. Moreover, an
important developmental task of adolescence is to build greater autonomy from parental control,
and high levels of self-generated stress may indicate that this process is going poorly. For
example, common dependent stressors included peer-related events such as bullying, friendship
losses, or romantic dissolutions. Given the high developmental salience of peer experiences (e.g.,
Hartup, 1996), stress in this domain may be problematic for all teens, regardless of CA history.
However, these ideas are fairly speculative, and more research is decidedly needed. It is also
worth noting that independence was coded based on objective characteristics of the event, which
may not exactly correspond with the adolescent’s perception of the controllability of the event.
More research should examine how subjective appraisals of event controllability affect cortisol
secretion, above and beyond objective controllability.
A central tenet of developmental psychopathology is multifinality, or the
acknowledgement that singular risk processes often result in divergent outcomes (Cicchetti &
Rogosch, 1996). Although we have largely focused our discussion on depression, our results may
be relevant to the development of other outcomes. Researchers have observed stress sensitization
processes in the prediction of a wide range of disorders and problems other than depression,
including alcohol consumption, episode recurrence in bipolar disorder, PTSD, and anxiety
disorders (Dienes, Hammen, Henry, Cohen, & Daley, 2006; McLaughlin et al., 2010; Young-
Wolff et al., 2012). In addition, cortisol dysregulation is associated with multiple forms of
psychopathology other than depression, including PTSD, anxiety disorders, disruptive behavior
disorders, and substance abuse (e.g., Adam et al., 2014; Delahanty, Raimonde, Spoonster, &
Cullado, 2003; McBurnett, Lahey, Rathouz, & Loeber, 2000; Moss, Vanyukov, & Martin).
Future research should examine whether cortisol dysregulation serves as a common pathway
linking stress sensitization to multiple disorders. If so, stress sensitization processes via HPA-
axis disruptions may serve as a transdiagnostic process that partially explains high comorbidity
across different forms of psychopathology.
Although in this study we examined the role of HPA-axis alterations in stress
sensitization and depression, CA has been shown to lead to alterations in other pathways that
may interact with later stressful contexts in predicting depression. Studies on epigenetic
processes have provided strong evidence that early experiences have the potential to alter gene
expression, including RNA modification and DNA methylation (Heijmans et al., 2008; Heim &
Binder, 2012; Heim et al., 2004; Szyf et al., 2008). For example, one study of adolescents found
that high levels of parental stress during the child’s early life is associated with higher levels of
methylation (Essex et al., 2013). Differential methylation profiles in stress-related genes have
also been found for depressed versus non-depressed individuals, and are associated with altered
stress reactivity (Fuchikami et al., 2011; Oberlander et al., 2008; Unternaehrer et al., 2012).
These findings suggest another potential pathway through which early stress may lead to
differential responses to proximal stress in individuals at risk for depression. Additionally,
findings from neuroimaging studies suggest that early CA may impair frontal brain regions
critical for the development of inhibitory control and affective regulation (Carrion, Weems,
Richert, Hoffman, & Reiss, 2010; Veer et al., 2012). These neuroanatomical alterations are
consistent with the large body of literature suggesting that children who have experienced early
adversity exhibit impaired cognitive function, including problems with working memory,
attention, and executive function (Hart & Rubia, 2012; Pechtel & Pizzagalli, 2011). These neural
changes may contribute to the development of information-processing biases that amplify the
effect of stressors later in development. An examination of these alternate pathways to stress
sensitization will be important to more clearly elucidate the process by which early adversity
leads to increased risk for depression.
This study should be evaluated in the context of several important limitations. First, the
study was cross-sectional. Longitudinal data would allow us to more directly test cascading
effects of CA on HPA axis disruptions and, in turn, depression. As a result of the cross-sectional
design, assessment of CA relied on retrospection, which may have introduced recall biases. In
addition, because of time constraints, assessment of CA relied exclusively on parental report. On
the one hand, parents may be more accurate reporters of events that occurred during early
childhood, but on the other hand, there may be some adverse events that occurred outside of their
awareness. In addition, our sample was recruited from the community, and consequently rates of
current MDD were fairly low. Likewise, the majority of childhood adversities reported in our
study represented significant but relatively commonplace stressors (e.g., grandparent death,
parental divorce, serious family illness). Much of the previous research on stress sensitization
has focused on severe adversities where the child’s safety is threatened, such as maltreatment,
and although previous research has documented that more common adversities also predict stress
sensitization (e.g., Hammen et al., 2000), there is also abundant evidence showing that effects on
HPA axis functioning differ depending on the nature of the early adversity (Miller et al., 2007).
Future research should determine whether results can be replicated in high risk samples with
higher rates of severe adversity such as maltreatment.
In addition, due to resource constraints, we utilized electronic compliance monitoring
caps on only a subset of participants, and thus, compliance with cortisol sampling procedures
cannot be verified in the majority of our participants. Within the subset who used monitoring
caps, the intervals between their self-reported times and their electronically recorded times were
comparable, suggesting reasonably good compliance, but tracking compliance of all participants
would have allowed us to more precisely assess sample timing (e.g., Stalder et al., 2016).
Instead, we strongly emphasized to our participants the importance of collecting saliva
immediately upon awakening, and relied on them to accurately so. Issues with compliance are
likely endemic to adolescent samples (Halpern, Whitsel, Wagner, & Harris, 2012), in part
because teenagers typically have demanding early morning schedules (e.g., preparing for school)
that may conflict with sampling procedures. Given the importance of timing in properly
capturing the CAR (Stalder et al., 2016), replication is needed.
These study limitations are balanced by important strengths. CAR was assessed using
three data points (at awakening and 30 and 60 minutes post-awakening), which is ideal for
determining the CAR as it allows AUCi calculation and increases the chances of capturing peak
cortisol secretion (Stalder et al., 2016). This practice is particularly unusual in adolescent
samples of this size (see Chida & Steptoe, 2009). We also assessed both CA and proximal
episodic stress, occurring naturalistically in adolescents’ lives, using gold-standard objective
interviews that were team-coded using the contextual threat method. This labor-intensive
approach to the assessment of environmental stress has been shown to reduce bias related to
cognitive vulnerability and more effectively predict outcomes, compared to more widely used
checklists (Hammen, 2005; McQuaid, Monroe, Roberts, Kupfer, & Frank, 2000).
This study examined two levels of analysis (behavioral and neuroendocrinological),
while also studying interactive effects of stressors occurring across multiple developmental
stages. To delve further into the complexities of risk and resilience, future researchers should
examine additional levels of analysis. For example, some evidence suggests that genetic
vulnerability increases vulnerability to stress sensitization processes. Starr et al. (2014) found
evidence for a gene-by-environment-by-environment (“G ´ E ´ E”) effect where early adversity
intensified the association between proximal stress and depression among those with risk alleles
in serotonin transporter (5-HTTLPR) or corticotrophin releasing hormone receptor-1 (CRHR1)
polymorphisms (see also Grabe et al., 2012). One plausible mechanism for this effect is that
genetic risk confers neural plasticity and sensitivity to environmental input, which makes youth
more vulnerable to disruptions in HPA axis development by CA exposure. HPA axis
dysregulation persists across the lifespan, leaving the youth poorly equipped to manage later
proximal stress. However, the role of HPA axis dysregulation in this G ´ E ´ E model has never
been directly tested. Future research should examine whether current findings are further
moderated by genetic risk, particularly by serotonergic and HPA-axis-related genes.
Additional research should examine the impact of neural structures. Ample research has
demonstrated that exposure to CA has detrimental effects on the development and plasticity of
brain structures implicated in stress response and regulation, notably the hippocampus as well as
other structures including areas of the prefrontal cortex (Gunnar & Nelson, 1994). Elevated
cortisol and glucocorticoid levels have been shown to be associated with dampened hippocampal
reactivity as well as reduced hippocampal and prefrontal cortical volume following exposure to
early life stress (Carrion, Weems, & Reiss, 2007; Carrion et al., 2010; Teicher et al., 2003).
Importantly, these structures are critically involved in HPA system regulation (see Dedovic,
Duchesne, Andrews, Engert, & Pruessner, 2009; Diorio, Viau, & Meaney, 1993; Jacobson &
Sapolsky, 1991). Thus, understanding of the interplay between early stress associated alterations
in neurobiological development and subsequent stressors is critical in disentangling the complex
relationship between early stress exposure, proximal stress, and depression.
Finally, in addition to biological levels of analysis, researchers should consider broader,
contextual factors that might impact the interactive effect of CA and proximal stress on cortisol
regulation. For example, neighborhood effects may moderate findings. Research has previously
demonstrated direct effects of neighborhood disadvantage on cortisol regulation (K. E. Rudolph
et al., 2014). Neighborhood disadvantage also moderates risk and resilience processes among
maltreated youth (Jaffee, Caspi, Moffitt, Polo-Tomás, & Taylor, 2007). It is also possible that
neighborhood disadvantage itself constitutes a proximal stressor, to which those with higher CA
are sensitized via HPA axis dysregulation.
Fortunately, neuroendocrine abnormalities related to CA are far from immutable;
evidence suggests that cortisol regulation can be normalized through prevention and intervention
programs (Cicchetti, Rogosch, Toth, & Sturge-Apple, 2011; Fisher, Gunnar, Chamberlain, &
Reid, 2000), which may protect against negative outcomes. More precise understanding of the
complex, interwoven biological and behavioral consequences of CA may lead to more effective
treatments that promote resilience in at-risk youth.
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Table 1
Bivariate Correlations and Descriptive Data for Behavioral Study Variables
1. CA
2. Total Episodic Stress
3. Independent Stress
4. Dependent Stress
5. MDD
6. BDI
CA = Childhood adversity. MDD = symptoms of major depressive disorders. BDI= Beck
Depression Inventory.
Table 2
Moderation of the Association between Total, Independent, and Dependent Episodic Stress and
the Cortisol Awakening Response by Childhood Adversity
95% C.I.
IV = Total Episodic Stress
< .001
[119.36, 185.37]
Childhood Adversity
[-2.24, 6.97]
Total Episodic Stress
[-9.14, 5.24]
Childhood Adversity ´ Episodic Stress
[-2.36, -.34]
Covariates: Sex
< .001
[-146.10, -56.33]
Pubertal Maturation
[-86.75, 5.51]
Follicular Stage
[-81.36, -6.51]
Total Sleep Time
[-70.08, 7.54]
Wake time
< .001
[-125.18, -46.42]
IV = Independent Stress
< .001
[115.15, 180.53]
Childhood Adversity
[-2.65, 6.44]
Independent Stress
[-9.34, 10.81]
Childhood Adversity ´ Independent
[-2.95, -.35]
Covariates: Sex
< .001
[-145.37, -54.91]
Pubertal Maturation
[-85.96, -4.85]
Follicular Stage
[-83.46, -8.65]
Total Sleep Time
[-69.69, 8.13]
Wake time
< .001
[-127.11, -48.35]
IV = Dependent Stress
< .001
[114.46, 181.77]
Childhood Adversity
[-2.81, 6.54]
Dependent Stress
[-17.35, 8.41]
Childhood Adversity ´ Dependent
[-2.56, .94]
Covariates: Sex
< .001
[-144.04, -51.76]
Pubertal Maturation
[-86.32, -3.23]
Follicular Stage
[-77.31, -1.55]
Total Sleep Time
[-72.85, 5.93]
Wake time
< .001
[-124.17, -44.20]
Notes. N = 196. CA = Childhood adversity. CA and stress variables were mean-centered.
Covariates were standardized to facilitate intercept interpretability. Cortisol Awakening
Response (CAR) calculated as the area under the curve with respect to increase (AUCi).
Table 3.
Moderation of the Association between Total, Independent, and Dependent Episodic Stress and Depressive Symptoms by Childhood Adversity
DV = K-SADS MDD Symptoms
95% C.I.
95% C.I.
IV = Total Episodic Stress
< .001
[.13, .31]
< .001
[6.47, 8.25]
[-.01, .02]
[-.03, .21]
Total Episodic Stress
< .001
[.02, .05]
[.06, .44]
CA ´ Episodic Stress
[.00, .01]
[-.002, .05]
Covariates: Sex
[-.16, .01]
[-1.76, .01]
[-.11, .06]
[-.72, 1.03]
Race (White)
[-.18, -.01]
[-1.94, -.17]
IV = Independent Stress
< .001
[.14, .32]
< .001
[6.55, 8.30]
[.00, .02]
[-.003, .23]
Independent Stress
[.00, .05]
[-.003, .53]
CA ´ Independent Stress
[.00, .01]
[.002, .07]
Covariates: Sex
[-.17, .01]
[-1.77, .03]
[-.10, .07]
[-.66, 1.09]
Race (White)
[-.19, -.02]
[-2.03, -.26]
IV = Dependent Stress
< .001
[.15, .33]
< .001
[6.64, 8.44]
[-.01, .02]
[-.005, .23]
Dependent Stress
[.02, .09]
[-.04, .67]
CA ´ Dependent Stress
[.00, .00]
[-.04, .04]
Covariates: Sex
[-.19, -.01]
[-1.95, -.17]
[-.12, .06]
[-.75, 1.04]
Race (White)
[-.19, -.01]
[-2.00, -.21]
Notes. N = 241. CA= Childhood adversity. CA and stress variables were mean-centered. Covariates were standardized to facilitate
intercept interpretability. K-SADS= Kiddie Schedule for Affective Disorders and Schizophrenia (Kaufman et al., 1997), MDD= Major
Depressive Disorder (dimensionally coded), BDI= Beck Depression Inventory (Beck et al., 1996).
Low Independent Stress High Independent Stress
Low Dependent Stress High Dependent Stress
Low Total Episodic
High Total Episodic
Low Childhood Adversity
High Childhood Adversity
b) c)
Figure 1. The cortisol awakening response (CAR) as predicted by a) overall, b)
independent, and c) dependent episodic stress, at high and low levels of childhood
adversity. The CAR was calculated as the area under the curve with respect to increase
(AUCi). Note that the interactions for a) overall and b) independent stress are significant
(ps < .05), but the interaction for c) dependent stress is non-significant.
Low Total Episodic
High Total Episodic
MDD Symptoms
Low Childhood
High Childhood
Low Independent Stress High Independent Stress
MDD Symptoms
Low Dependent Stress High Dependent Stress
MDD Symptoms
b) c)
Figure 2. Symptoms of major depressive disorder (MDD) as predicted by a) overall, b)
independent, and c) dependent episodic stress, at high and low levels of childhood
... There is more to the HPA axis than reactivity to a laboratory stressor. ELA was initially reported to be associated with elements of the cortisol diurnal rhythm such as the cortisol awakening rise (CAR) [92], however, the most recent meta-analysis suggests that this is not the case [93], although the meta-analysis of the stress-induced changes was much stronger [94]. The weakness in the CAR meta-analysis was probably due to large heterogeneity between the techniques employed between the different studies. ...
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The physiological response to a psychological stressor broadly impacts energy metabolism. Inversely, changes in energy availability affect the physiological response to the stressor in terms of hypothalamus, pituitary adrenal axis (HPA), and sympathetic nervous system activation. Glucocorticoids, the endpoint of the HPA axis, are critical checkpoints in endocrine control of energy homeostasis and have been linked to metabolic diseases including obesity, insulin resistance, and type 2 diabetes. Glucocorticoids, through the glucocorticoid receptor, activate transcription of genes associated with glucose and lipid regulatory pathways and thereby control both physiological and pathophysiological systemic energy homeostasis. Here, we summarize the current knowledge of glucocorticoid functions in energy metabolism and systemic metabolic dysfunction, particularly focusing on glucose and lipid metabolism. There are elements in the external environment that induce lifelong changes in the HPA axis stress response and glucocorticoid levels, and the most prominent are early life adversity, or exposure to traumatic stress. We hypothesise that when the HPA axis is so disturbed after early life adversity, it will fundamentally alter hepatic gluconeogenesis, inducing hyperglycaemia, and hence crystalise the significant lifelong risk of developing either the metabolic syndrome, or type 2 diabetes. This gives a “Jekyll and Hyde” role to gluconeogenesis, providing the necessary energy in situations of acute stress, but driving towards pathophysiological consequences when the HPA axis has been altered.
... Future studies should also consider the nature of stressors and both personal and environmental factors associated with coping successfully despite experiencing negative childhood experiences. For example, Starr and colleagues (Starr et al., 2017) found that among adolescents with high level of negative childhood experiences only uncontrollable stress, but not self-generated stress, predicted higher level of depression. In addition, it is important to take into consideration whether the stressors were chronic or traumatic if the adverse effects of stressors are still present, whether they were controllable and manageable, and how successful the coping process was (Knight, Gatz, Heller, & Bengtson, 2000). ...
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The present study evaluated the assumptions of stress sensitization and stress immunization hypotheses about the role of perceived negative childhood experiences on adult adjustment. The study used a longitudinal design with three waves spaced six months apart. The final sample consisted of 293 undergraduate students aged 19 to 30 years. We examined the linear and nonlinear main and moderating effects of perceived negative childhood experiences in the relationship between recent stressful events and both ability to bounce back and subjective well-being. The results yielded nonlinear moderating effects of negative childhood experiences on life satisfaction and the ability to bounce back, whereas a main effect was found for negative affect. A significant drop in the ability to bounce back in the context of high recent life stress was found only among individuals with a very high level of negative childhood experiences. We also found that an increase in the number of negative life events leads to a decrease in life satisfaction among individuals with both low- and high-intensity levels of negative childhood experiences. The present study offers the possibility of integrating different models of additive and interactive effects of perceived negative childhood experiences in the relationship between recent stressors and psychological adjustment.
... Disrupted HPA axis, advancement or delay in circadian rhythm of cortisol, and disturbance in upper and lower bounds of cortisol range are also observed in major depression (Abell et al., 2016;Starr et al., 2017). In some cases, depression is accompanied by hypocortisolemia (Bremmer et al., 2007;Vreeburg et al., 2013;Moreira et al., 2016;Galvão et al., 2018), which may be induced by prolonged use of particular type of antidepressants, such as mirtazapine-a selective antagonism at 5-HT 2 receptors (Schüle et al., 2006). ...
Full-text available
Sleep disturbance is a symptom consistently found in major depression and is associated with a longer course of illness, reduced response to treatment, increased risk of relapse and recurrence. Chronic insomnia has been associated with changes in cortisol and serum brain-derived neurotrophic factor (BDNF) levels, which in turn are also changed in major depression. Here, we evaluated the relationship between sleep quality, salivary cortisol awakening response (CAR), and serum BDNF levels in patients with sleep disturbance and treatment-resistant major depression (n = 18), and in a control group of healthy subjects with good (n = 21) and poor (n = 18) sleep quality. We observed that the patients had the lowest CAR and sleep duration of all three groups and a higher latency to sleep than the healthy volunteers with a good sleep profile. Besides, low CAR was correlated with more severe depressive symptoms and worse sleep quality. There was no difference in serum BDNF levels between groups with distinct sleep quality. Taken together, our results showed a relationship between changes in CAR and in sleep quality in patients with treatment-resistant depression, which were correlated with the severity of disease, suggesting that cortisol could be a physiological link between sleep disturbance and major depression.
... In a recent study that carefully dated both the occurrence of different stressful life events and youths' development of depression, for example, interpersonal life events were found to be statistically unique predictors of subsequent onset of MDD across two adolescent samples; in contrast, noninterpersonal events were unrelated to depression (Vrshek-Schallhorn et al., 2015). In a second longitudinal study, exposure to interpersonal life events interacted with a multilocus genetic profile score to prospectively predict increases in depressive symptoms in adolescents but, again, these effects were specific to interpersonal stressors (Feurer et al., 2017; see also Starr et al., 2017;Starr, Dienes, Li, & Shaw, 2019). Finally, a third study found that interpersonal life events involving targeted rejection precipitated onset of depression three times faster than other types of major life events (Slavich, Thornton, Torres, Monroe, & Gotlib, 2009; see also Massing-Schaffer et al., 2019). ...
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Background: Depression rates increase markedly for girls across the adolescent transition, but the social-environmental and biological processes underlying this phenomenon remain unclear. To address this issue, we tested a key hypothesis from Social Signal Transduction Theory of Depression, which posits that individuals who mount stronger inflammatory responses to social stress should exhibit greater increases in depressive symptoms following interpersonal life stress exposure than those who mount weaker inflammatory responses to such stress. Method: Participants were 116 adolescent girls (Mage = 14.71) at risk for psychopathology, defined as having a history of mental health concerns (e.g., psychiatric treatment, significant symptoms) over the past 2 years. At baseline, we characterized their inflammatory reactivity to social stress by quantifying their salivary proinflammatory cytokine responses to a laboratory-based social stressor. Then, 9 months later, we assessed the interpersonal and noninterpersonal stressful life events that they experienced over the prior 9 months using an interview-based measure of life stress. Results: As hypothesized, greater interpersonal life stress exposure was associated with significant increases in depression over time, but only for girls exhibiting stronger salivary tumor necrosis factor-α and interleukin-1β reactivity to social stress. In contrast, noninterpersonal stress exposure was unrelated to changes in depression longitudinally, both alone and when combined with youths' cytokine reactivity scores. Discussion: These results are consistent with Social Signal Transduction Theory of Depression and suggest that heightened inflammatory reactivity to social stress may increase adolescents' risk for depression. Consequently, it may be possible to reduce depression risk by modifying inflammatory responses to social stress.
Objective: The relationship between smoking and adolescents' peer relationships is complex, with studies showing increased risk of smoking for adolescents of both very high and very low social position. A key question is whether the impact of social position on smoking depends on an adolescent's level of coping motives (i.e., their desire to use smoking to mitigate negative affect). Method: We assessed how social position predicts nicotine dependence in a longitudinal sample (N = 3,717; 44.8% male; mean age = 13.41 years) of adolescent lifetime smokers measured between 6th and 12th grades. Using both social network analysis and multilevel modeling, we assessed this question at the between-person and within-person level, hypothesizing that within-person decreases in social position would lead to increased risk of nicotine dependence among those with high levels of coping motives. Results: In contrast to our hypotheses, only interactions with the between-person measures of social position were found, with a slight negative relationship at low levels of coping motives. In addition, the main effect of coping motives was considerably stronger than that of social position at the between-person level, and social position had no significant within-person main effect on nicotine dependence risk. Conclusions: These results suggest that adolescents with higher overall levels of social position among their peers may have slightly decreased risk for nicotine dependence, but only when coping motives are low. Counter to expectations, higher levels of nicotine dependence risk were not linked to fluctuations in social position.
Objective Stress system dysregulation is considered to have an important role in the aetiology of paediatric functional neurological (conversion) disorder. This study examined salivary cortisol and α-amylase awakening responses in children with functional neurological disorder to determine activation patterns of the hypothalamic–pituitary–adrenal axis and sympathetic system. A healthy cortisol awakening response involves a robust increase in cortisol within 30 minutes of awakening. Alpha-amylase awakening response is variable in children. Methods Cortisol and α-amylase were measured in saliva from 32 patients with functional neurological disorder (26 girls and 6 boys, aged 11.3−16.1 years) and 31 healthy controls (23 girls and 8 boys, aged 8.6–17.7 years). Saliva samples were collected using a Salivette sampling device at two time points – upon awakening and 30 minutes after awakening. Results Patients with functional neurological disorder showed a decrease in cortisol awakening response (–4 nmol.min/L) and controls showed an increase (107 nmol.min/L), t(55) = –.4.6, p < 0.001. Within the functional neurological disorder group, 57% showed an attenuated cortisol awakening response and 43% showed an obliterated/reversed cortisol awakening response: Cortisol awakening response was negatively correlated with adverse childhood experiences, r(58) = –0.6, p = 0.002, and subjective distress (total Depression Anxiety and Stress Scales score), r(58) = –0.4, p = 0.050. In controls, cortisol awakening response showed no correlation with adverse childhood experiences and a positive correlation with subjective distress, r(56) = 0.4, p = 0.023. Total cortisol remained similar between the functional neurological disorder and control group. No significant differences were observed between the functional neurological disorder and control group in any of the α-amylase analyses. Discussion The results suggest dysregulation of the hypothalamic–pituitary–adrenal axis in children with functional neurological disorder. Hypothalamic–pituitary–adrenal dysregulation in children with functional neurological disorder may contribute to comorbid symptoms of fatigue, sleep disturbance and subjective loss of well-being because circadian rhythms and energy metabolism are disrupted. Hypothalamic–pituitary–adrenal dysregulation – and changes in glucocorticoid (cortisol) signalling at the molecular level – may also contribute to increased vulnerability for functional neurological disorder symptoms because of epigenetically mediated changes to neural networks implicated in functional neurological disorder.
Existing research supports competing hypotheses about the link between negative emotional (NE) reactivity to daily events (e.g., hassles and uplifts) and depression. Some have suggested that depression is associated with blunted reactivity, and others have suggested that depression is associated with heightened reactivity. In this study, we tested linear and nonlinear associations, cross-sectionally and longitudinally, between NE reactivity and depression among a sample of 232 adolescents. Participants completed lab-based assessments of depression then rated their experience of emotions, daily hassles, and uplifts three times per day for 7 days. Interviews were readministered 1.5 years later. Results show a significant U-shaped relationship between NE reactivity to hassles and depression symptoms cross-sectionally, which suggests that depression is more severe at the extremes of NE reactivity. NE reactivity to daily uplifts showed significant linear associations, but not quadratic associations, with depression such that heightened reactivity to uplifts was associated with more severe depression symptoms concurrently and predicted worsening of depression longitudinally.
Rumination is correlated with diverse types of internalizing problems, but the extent to which it relates to a higher-order internalizing spectrum versus disorder-specific pathology is unclear. Using a quantitative model of the internalizing dimension, we compared the strength of transdiagnostic versus diagnosis-specific pathways from brooding—the most depressogenic component of rumination—to major depressive disorder (MDD) in adolescents. Community-recruited mid-adolescents (N = 241, Mage = 15.90 years, 53% female) completed semi-structured interviews of anxiety and depressive conditions and a self-report brooding measure. Confirmatory factor analysis revealed good fit for a one-factor model of internalizing conditions. Results revealed a large, significant factor correlation between brooding and the internalizing factor (r = 0.55), with some evidence for a more modest specific link between brooding and the unique component of the MDD diagnosis (r = 0.17; approximately one-third as large as the transdiagnostic pathway). These cross-sectional associations were generally consistent across two assessment waves separated by 19 months. We concluded that brooding is better conceptualized as a common characteristic of all internalizing problems in adolescence, rather than a specific feature of MDD. Preregistered hypotheses, data analysis code, and correlation matrices for this study are posted at
Childhood adversity appears to sensitize youth to stress, increasing depression risk following stressful life events occurring throughout the lifespan. Some evidence suggests hypothalamic–pituitary–adrenal (HPA) axis-related and serotonergic genetic variation moderates this effect, in a “gene-by-environment-by-environment” interaction (G × E × E). However, prior research has tested single genetic variants, limiting power. The current study uses a multilocus genetic profile score (MGPS) approach to capture polygenic risk relevant to HPA axis and serotonergic functioning. Adolescents ( N = 241, M age = 15.90) completed contextual-threat-based interviews assessing childhood adversity and acute life events, and diagnostic interviews assessing depression. Established MGPSs indexed genetic variation linked to HPA axis (10 single nucleotide polymorphisms [SNPs]) and serotonergic (five SNPs) functioning. Results showed significant MGPS × Childhood Adversity × Recent Life Stress interactions predicting depression for both HPA axis and serotonergic MGPSs, with both risk scores predicting stronger Childhood Adversity × Recent Stress interactions. Serotonergic genetic risk specifically predicted sensitization to major interpersonal stressors. The serotonergic MGPS G × E × E was re-tested in an independent replication sample of early adolescent girls, with comparable results. Findings support the notion that genetic variation linked to these two neurobiological symptoms alters stress sensitization, and that gene-by-environment (G × E) interactions may be qualified by environmental exposures occurring at different points in development.
Background Early life experiences shape individual attachment, creating a template for regulating emotions in interpersonal situations, likely to persist across the lifespan. Research has shown that individual attachment creates vulnerability for depression, and also impacts the Hypothalamic-Pituitary-Adrenal (HPA) axis. Still, the relationship between attachment and the HPA axis in depressed individuals is unclear. Cortisol awakening response (CAR) has been recently investigated as a possibly useful physiological marker related to attachment insecurity and depression risk. However, research exploring the relationship between the CAR and attachment in individuals with chronic depression in either the presence or the absence of comorbid anxiety is lacking. The purpose of the current study was to fill this gap, by comparing the CAR in individuals with chronic depression with/without comorbid anxieties and controls. In addition, we also wanted to explore the relationship between attachment and the CAR in this group and to explore their predictive role for later depression severity. Methods Individuals experiencing a current depressive episode at least six months in length (cMDD; n = 63) and healthy controls (HC; n = 57) were enrolled in the study (total n = 120). Participants completed a structured clinical diagnostic interview (SCID-I) as well as measures of depression severity (Beck Depression Inventory-II (BDI-II) and Hamilton Rating Scale for Depression) and attachment dimensions (Experiences in Close Relationships scale; ECR) at baseline. In addition, participants provided salivary samples at four time points (i.e. 0 (S1), 30, 45 and 60 minutes) following awakening on two consecutive days. S1 cortisol, the area under the curve with respect to ground (AUCg) and increase (AUCi) were calculated based on the average values across both days. The HC and cMDD groups were compared on all measures. The CAR for individuals with cMDD alone (n = 14) and individuals with cMDD with two or more comorbid anxiety disorders (cMDD≥2Anx; n = 30) were also compared. A subset of participants (n = 59) agreed to return for follow up one year later. Participants returning for follow up repeated the BDI-II and ECR. No salivary samples were collected at follow-up. Results The cMDD group had significantly lower S1 cortisol and AUCg compared to the HC group (both p ≤ 0.02). cMDD and cMDD≥2Anx groups did not differ in their CAR. Regression analyses revealed that depression severity and the attachment interaction term was associated with lower S1 and AUCg cortisol (p < 0.01). Greater attachment avoidance was positively associated with S1 cortisol (p = 0.02), while mean awakening time on sample days was negatively associated with S1 cortisol. We also found a significant interaction between the attachment dimensions such that at low levels of attachment anxiety, attachment avoidance had a positive relationship with S1 cortisol and AUCg. The opposite relationship existed when attachment anxiety was high. Higher baseline BDI-II score and higher baseline attachment anxiety were predictive of higher scores on the BDI-II one-year later (both p < 0.05). Conclusions The current findings bring evidence that depression severity is associated with blunting of the CAR irrespective of the comorbid status with anxiety disorders. In addition, attachment avoidance may protect against the CAR blunting in individuals with low attachment anxiety. However, individuals with high attachment anxiety and avoidance might have additional CAR blunting. Attachment anxiety might be a good predictor of future depression severity.
Most of the variance in diurnal cortisol is attributable to intraindividual variability (IIV), defined as relatively short-term, reversible changes. Multiple methods for measuring IIV have been proposed, and some have already been applied to cortisol IIV. In the present review, measurement methods are described and applied to simulated cortisol data with known underlying differences in IIV and to real cortisol data from first-year law students. More slope variance and more residual or net variance were well captured by their individual standard deviations. Explorations of reliability suggested that 10 slopes and 50 residuals result in reliable and stable estimates of the individual standard deviations. A data-analytic plan for cortisol IIV is provided.
Life stress is a central factor in the onset and course of a wide range of medical and psychiatric conditions. Determining the precise etiological and pathological consequences of stress, though, has been hindered by weaknesses in prevailing definitional and measurement practices. The purpose of the current paper is to evaluate the primary strategies for defining and measuring major and minor acute life events, chronic stressors, and daily hassles as informed by 3 basic scientific premises. The first premise concerns the manner in which stress is conceptualized and operationally defined, and specifically we assert that stress measures must not conflate the stress exposure with the stress response. The second premise concerns how stress exposures are measured, and we provide guidelines for optimizing standardized and sensitive indicators of life stress. The third premise addresses the consequences of variations in the procedures for life event measurement with regard to the validity of the research designs employed. We show that life stress measures are susceptible to several sources of bias, and if these potential sources of bias are not controlled in the design of the research, spurious findings may result. Our goal is to provide a useful guide for researchers who consider life stress to be an important factor in their theoretical models of disease, wish to incorporate measures of life stress in their research, and seek to avoid the common pitfalls of past measurement practices. (PsycINFO Database Record
The aim of the present study was to examine the impact of childhood trauma on HPA axis activity both in depression patients and healthy controls in order to determine the role of HPA axis abnormalities in depression and to find the differences in HPA axis functioning that may lead certain individuals more susceptible to the depressogenic effects of childhood trauma. Eighty subjects aged 18-45 years were recruited into four study groups (n = 18, depression patients with childhood trauma exposures, CTE/MDD; n = 17, depression patients without childhood adversity, non-CTE/MDD; n = 23, healthy persons with childhood trauma, CTE/non-MDD; and n = 22, healthy persons without childhood adversity, non-CTE/non-MDD). Each participant collected salivary samples in the morning at four time points: immediately upon awakening, 30, 45, and 60 min after awakening for the assessment of CAR and underwent a 1 mg-dexamethasone suppression test (DST). Regardless of depression, subjects with CTE exhibited an enhanced CAR and the CAR areas under the curve to ground (AUCg) were associated with their childhood trauma questionnaire (CTQ) physical neglect scores and CTQ total scores. In addition, the CTE/MDD group also showed a highest post-DST cortisol concentration and a decreased glucocorticoid feedback inhibition among four groups of subjects. The present findings suggested that childhood trauma was associated with hyperactivity of HPA axis as measured with CAR, potentially reflecting the vulnerability for developing depression after early life stress exposures. Moreover, dysfunction of the GR-mediated negative feedback control might contribute to the development of depression after CTE.