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Effects of childhood adversity on physiology and health in emerging adulthood

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Effects of childhood adversity on physiology and health in emerging adulthood

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Content Running head: CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 1

Effects of Childhood Adversity on Physiology and Health in Emerging Adulthood

Kelly Frances Miller Kazmierski

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PSYCHOLOGY)

Oral Defense: May 1, 2019
Degree Conferral: August 15, 2019

Dissertation Committee:
Gayla Margolin, Ph.D., Chair
John Brekke, Ph.D.
Richard John, Ph.D.
Darby Saxbe, Ph.D.
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 2
Table of Contents

Acknowledgements ......................................................................................................... 3
General Introduction ....................................................................................................... 5
Paper 1: Does the Cortisol Awakening Response Link Childhood Adversity to Adult
BMI? .............................................................................................................................. 8
Abstract ............................................................................................................... 9
Introduction ....................................................................................................... 10
Method .............................................................................................................. 11
Results .............................................................................................................. 14
Discussion ......................................................................................................... 14
References ......................................................................................................... 16
Table 1 .............................................................................................................. 18
Figure 1 ............................................................................................................. 19
Paper 2: Family Aggression and Attachment Avoidance Influence Neuroendocrine
Reactivity in Young Adult Couples ............................................................................... 20
Abstract ............................................................................................................. 21
Introduction ....................................................................................................... 22
Method .............................................................................................................. 29
Results .............................................................................................................. 35
Discussion ......................................................................................................... 37
References ......................................................................................................... 43
Table 1 .............................................................................................................. 50
Table 2 .............................................................................................................. 51
Figure 1 ............................................................................................................. 52
Figure 2 ............................................................................................................. 53
Figure 3 ............................................................................................................. 54
Appendix Table 1 .............................................................................................. 55
Paper 3: Family-of-origin Aggression, Romantic Relationships, and Inflammation in
Young Adulthood ......................................................................................................... 56
Abstract ............................................................................................................. 57
Introduction ....................................................................................................... 58
Method .............................................................................................................. 67
Results .............................................................................................................. 75
Discussion ......................................................................................................... 77
References ......................................................................................................... 86
Table 1 ............................................................................................................ 100
Table 2 ............................................................................................................ 101
Table 3 ............................................................................................................ 102
Figure 1 ........................................................................................................... 103
General Discussion ..................................................................................................... 104
General References ..................................................................................................... 111
Supplemental Materials ............................................................................................... 116
Childhood Adversity ....................................................................................... 117
Adolescent Life Stress ..................................................................................... 146
Family of Origin Aggression ........................................................................... 149
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 3
Romantic Attachment ...................................................................................... 150

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 4

Acknowledgements
The work in this dissertation has been supported by NSF Graduate Research Fellowship
Grant No. DGE-0937362 (Kazmierski, PI), NIH NICHD Grant No. R01 HD046807 (Margolin,
PI), NIH NICHD Grant No. R21HD072170 (Margolin, PI), and SC CTSI (NIH/NCATS) through
Grant No. UL1TR001855 (Margolin, PI). Project collaborators were supported by NSF SPRF-
1606976 awarded to Shapiro and NSF GRFP DGE-0937362 awarded to Han.
I am deeply grateful to my advisor, Dr. Gayla Margolin, for her support, both in this
dissertation and throughout my graduate studies. Gayla’s immense intellect and tremendous heart
have been my touchstones when muddling through and my inspirations when sprinting ahead in
my program of research. I will be so proud to continue to call myself Gayla’s student career-
long. I want to further extend my deepest gratitude to my committee members, Drs. Darby
Saxbe, Richard John, and John Brekke, who have been generous with their time and knowledge
throughout this dissertation. I am also indebted to the many professors at USC who have shaped
my thinking over the past (let’s round down and say) six years, especially Drs. Christopher
Beam, Darby Saxbe, and Shannon Couture.
This project would not have been possible without the participation of the couples and
families of the USC Family Studies Project. I am also deeply grateful to the co-authors on the
papers of this dissertation, Dr. Gayla Margolin, Dr. Christopher Beam, Dr. Lauren Shapiro, Dr.
Reout Arbel, and Sohyun Han. I am fortunate to work with lab members who are tremendous
teammates. I especially want to thank Dr. Lauren Shapiro for being my saliva science role
model, Soyhun Han and Dr. Reout Arbel for digging through years of adversity data by my side,
Dr. Addie Timmons for her infinite patience introducing me to multi-level modeling, and Dr.
Christopher Beam for a dedication to teaching quantitative methods that attests to his authentic
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 5
investment in helping students grow. I am grateful to Yehsong Kim, Olivia Shin, and Merai
Estafanous for their help collecting these data. Our lab managers, Corey Pettit and Stassja Sichko
have been invaluable to this dissertation. I thank them for their humility and generosity on the
many occasions that their wisdom and insight about our studies far exceeded my own. I can’t
wait to see the amazing things they will achieve as they launch their own graduate careers.
My work in the lab was only possible because of the tremendous community of support
that lifts me up outside of the lab. Thank you to my cohort, Marie, Rubin, and Justin, for creating
spaces where work felt like play. Your humor, intellect, and contagious joy made coming to
campus a pleasure (even on days when I could have stayed home to edit manuscripts in my
pajamas). Thank you to my second family on the “Bridge,” whose loving friendship gave me the
confidence to venture out toward my goals. Dr. Jessie Borelli has been a friend and inspiration to
me; her deep theoretical thinking has been formative to my understanding of relationships,
development, and well-being, while her compassionate support has been foundational to my
belief in my own capacity to do the things I’ve dreamed of. I am deeply grateful for the love of
my family and for the pride they show in me. My mother Denise, has ardently believed in my
writing from my very first scribble onwards. I thank her for nurturing my desire to learn and for
being genuinely interested in what I find.
This dissertation is dedicated to David, my best friend and partner in all things. I am so
grateful for the countless ways David’s deeply loving heart and open, playful mind have
sustained and replenished me throughout this work. His courage reminds me that hard things are
worth doing, and his support has made doing those hard things possible. David catches me when
I fall, and he launches me when I fly. I am so proud that this dissertation bears our family
name—we’ve earned this together.
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 6
General Introduction
A foundational tenet of psychology across developmental, clinical, and health domains is
that stressful childhood experiences shape adult lives. One of the costliest of these impacts is to
health: adversities experienced in the family of origin exert a toll on health decades later,
conferring risk for chronic illness and premature death (Brown et al., 2009; Felitti et al., 1998).
Adversity is thought to become embedded in biology during childhood via allostatic adaptation
(McEwen, 1998). Stress-induced activations of physiological systems, such as the hypothalamic-
pituitary-adrenal (HPA) axis, mobilize resources to meet the demands of stressors in the short-
term; however, repeated HPA activations during childhood are posited to create wear-and-tear to
bodily systems that erode health in adulthood.
This dissertation examines how childhood stressful experiences become embedded in
young adults’ physiology and health. Building on allostatic models, the three papers that follow
test HPA activity as a mechanism linking stress to health, identify sources of individual
difference in how childhood stress exposure shapes adult HPA reactivity, and provide initial
evidence for the role of young adults’ romantic relationships in contributing to or buffering
against stress-induced health risk. Paper one, published in Health Psychology (Miller, Arbel,
Shapiro, Han, & Margolin, 2018), is the first to directly test diurnal HPA activity in adolescence
as a mediator of associations between adversity in childhood and elevated BMI in emerging
adulthood. Childhood adversity is calculated across a range of domains using a multi-informant,
longitudinal data set. Paper two, under review at the Journal of Family Psychology (Kazmierski,
Beam, & Margolin, 2019), examines how histories of parent-to-child aggression interact with
romantic attachment avoidance to shape young adults’ HPA reactivity during interactions with
dating partners. It additionally assesses whether these effects “spill over,” across partners, such
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 7
that one partner’s characteristics influence the other partner’s HPA reactivity. Finally, paper
three assesses effects of family-of-origin aggression on young adults’ inflammatory heath, in
order to assess whether growing up in an aggressive family impacts health even in community
samples of young adult couples. HPA reactivity during dyadic interactions is assessed as a
mechanism linking family-of-origin aggression to inflammation, such that experiencing
aggression during childhood confers sensitized patterns of reactivity that create ongoing wear
and tear to health. Romantic attachment avoidance is posited as a quality of current relationships
that may amplify or mitigate this risk mechanism.
Across the studies, stressful childhood experiences are measured both longitudinally and
retrospectively. Whereas paper one assesses cumulative exposure to adversity in childhood
across a range of domains, papers two and three focus on parent-to-child aggression in the family
of origin as one particularly prevalent and consequential interpersonal stressor (Moffitt, 2013;
Straus & Field, 2003). Studies assess HPA activity in terms of both diurnal pattern at home and
reactivity during interactions between romantic partners in lab. Indicators of young adult health
include BMI and levels of pro-inflammatory cytokines, as both obesity and chronic immune-
mediated inflammation have been linked to the development of wide-ranging chronic illnesses in
middle and later adulthood (e.g., Field et al., 2001; Michaud et al., 2013). Research focuses on
detecting effects of childhood stress exposure during emerging adulthood, a developmental
period in which markers of health-risk can be detected but the full impact of chronic illness is not
yet felt (Bonnie, Stroud, & Brenner, 2015). As emerging adulthood is characterized by
increasing separation from families of origin and the establishment of stable romantic
partnerships (Arnett, 2000), young adults may have unique opportunities to strengthen or disrupt
trajectories of health risk established in families of origin. Whereas childhood adversity is a fixed
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 8
risk factor once it is incurred, qualities of young adults’ romantic relationships and patterns of
physiological reactivity are amenable to intervention (e.g., Olff, de Vries, Güzelcan, Assies, &
Gersons, 2007; Taylor, Rietzschel, Danquah, & Berry, 2015; Wood, Crane, Schaalje, & Law,
2005). Ultimately, this dissertation aims to elucidate how young adults maintain or exit
trajectories from childhood adversity to adult dysregulation and disease, in order to inform the
development of future interventions to protect the health of at-risk young adults.

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 9

Paper 1
Does the Cortisol Awakening Response Link Childhood Adversity to Adult BMI?
Kelly F. Miller (Kazmierski),
1
Reout Arbel,
2
Lauren S. Shapiro,
1
Sohyun C. Han,
1
& Gayla
Margolin
1

1. University of Southern California
2. University of Haifa

Author Note:
Funding for this study was provided, in part, by NIH NICHD R01 HD046807 and
R21HD072170 awarded to Margolin; NSF Graduate Research Fellowship DGE-0937362
awarded to Miller (Kazmierski); NSF SPRF-1606976 awarded to Shapiro; and NSF GRFP DGE-
0937362 awarded to Han. The authors would like to thank the research participants and USC
Family Studies Project colleagues, particularly Hannah Rasmussen, Corey Pettit, Elyse L. Guran,
and Diana C. Bennett. Preliminary data from this study were presented at the 28th Annual
Convention of the Association for Psychological Science.

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 10
Abstract
Objectives: Childhood adversity is a risk factor for the development of obesity in adulthood.
Dysregulated hypothalamic-pituitary-adrenal (HPA) activity, which has been associated
separately with both adverse childhood experiences and obesity, has been posited as a
mechanism by which stressful experiences influence body mass index (BMI); however, this
mechanism has not yet been tested longitudinally. The present study uses multi-reporter,
longitudinal data across three time points to test whether the adolescent cortisol awakening
response (CAR), an index of diurnal HPA activity, mediates the association between adversity in
childhood and BMI in adulthood.
Methods: 82 youth, mothers, and fathers reported on adverse childhood experiences from
middle childhood to late adolescence. During adolescence, youth provided saliva samples three
times each morning across three days, which were assayed for cortisol to calculate CAR. During
early adulthood, youth reported height and weight to calculate BMI.
Results: Greater adversity predicted flatter CAR and higher young adult BMI. Flatter CAR
partially mediated the association between childhood adversity and young adult BMI.
Conclusions: Stress-related alterations to HPA activity account in part for the childhood
adversity-adult obesity link. Findings are consistent with theoretical models implicating HPA
alterations as linking childhood adversity to metabolic and behavioral determinants of BMI in
adulthood.

Keywords: childhood adversity, cortisol awakening response, body mass index

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 11
Does the Cortisol Awakening Response Link Childhood Adversity to Adult BMI?
Over the past twenty years, one of the most significant discoveries in health psychology
has been that childhood stress gets under the skin, to lastingly influence physiology, including
the diurnal rhythm of the hypothalamic-pituitary adrenal (HPA) axis (Danse & McEwan, 2012)
and to confer risk for poor health outcomes, such as an elevated body mass index (BMI) (Davis
et al., 2014; Felitti et al., 1998). Building upon separate studies linking adversity to HPA rhythm
(e.g., Miller, Margolin, Shapiro, & Timmons, 2016) and HPA rhythm to elevated BMI (e.g.,
Ruttle, Javaras, Klein, Armstrong, Burk, & Essex, 2012), theoretical models have frequently
posited that the way the HPA axis adapts to stress provides a crucial mechanism underpinning
the relationship between stress and obesity (e.g., McEwen, 1998; Repetti, Robles, & Reynolds,
2011). However, this mechanism has never been directly tested.
The HPA axis activates in response to stress in order to redirect physiological resources
to meet environmental demand. However, according to allostatic models, repeated stress-induced
activations create physiological wear and tear that recalibrates the HPA axis and damages the
biological systems HPA regulates (McEwen, 1998). The cortisol awakening response (CAR), the
sharp increase in cortisol in the 30 minutes after awakening, is a frequently measured index of
diurnal HPA activity that is susceptible to recalibration (Stalder et al., 2016), such that present
stress typically leads to a steeper morning increase whereas a history of adversity creates a flatter
increase (Miller, Chen, & Zhou, 2007). CAR has been proposed to influence BMI via multiple
pathways, including immediate daily effects on physical activity and energy mobilization as well
as downstream impacts on systems governing appetite, insulin resistance, and stature
(Pervanidou & Chrousos, 2012; Richard & Baraboi, 2004). Consistent with these models, lower
levels of morning cortisol predict higher BMI across adolescence (Ruttle et al., 2012); however,
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 12
few longitudinal studies have been conducted, and the nature of the association between BMI
and HPA activity is mixed when measured cross-sectionally (Incollingo Rodriguez et al., 2015).
Synthesizing these findings, the present investigation is the first to examine CAR as a
mechanism linking childhood adversity to adult health, using BMI as an early health indicator
that shows variability in emerging adulthood. Using longitudinal data, this study prospectively
measures adversity in middle childhood and adolescence to predict BMI in early adulthood (H1)
and tests CAR in adolescence as a mediator of this association (H2), while adjusting for
concurrent stress in order to isolate only the effect of childhood adversity on HPA and BMI.
Method
Overview and participants
Data were collected during 6 waves of a longitudinal study on family aggression and
youth adjustment, approved by the University of Southern California institutional review board
at each wave. The longitudinal sample comprises two cohorts recruited from the community;
cohort 1 included families with a child age 9-10 at wave 1 (n = 119); cohort 2 entered at wave 3,
4 years later (n = 70, Mage = 13.06) and included families with a child in middle school to match
the age of the first cohort. Inclusion criteria were that two parental figures resided with the child
for at least 3 years and that families could complete procedures in English. Data for this study are
based on 82 youth who reported on childhood adversity at one or more of the first 4 waves (Mage
Wave 1 = 9.98, M age Wave 4 = 15.42), provided cortisol samples and reported on current stress at wave
5 (M age = 18.09, SD = 1.11), and reported BMI at wave 6 (M age = 22.24, SD = 2.30). Of the 189
total participating families, 99 adolescents provided saliva samples, of whom 82 (43 female)
reported BMI at wave 6. Comparisons did not reveal significant differences in demographic or
study variables between participants who completed all procedures required for inclusion and
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 13
those who did not. Of the 82 participants, 36.6% identified as Latino/a. Self-identified race was
6.1% Asian/Pacific Islander, 19.5% African American, 56.1% Caucasian, 18.3% multi-
racial/other. Annual family income was 22.7% < $50K, 45.3% $50K-$100K, and 32% > $100K.
Measures
Cortisol in adolescence. At wave 5, across three consecutive weekdays, participants
used oral swabs to provide 3 saliva samples, signaled by a pre-set alarm clock (see Miller et al.,
2016). Samples were provided at awakening (no later than 8 A.M.), 20 minutes post-awakening,
and 40 minutes post-awakening. There was high consistency between scheduled and participant
reported sampling intervals (median difference = 2.63 minutes). Medication Event Monitoring
System caps provided to a subsample of 26 participants showed high consistency between
participant-reported and digitally-recorded sampling times (median difference = 1.93 minutes);
3.6% of scheduled saliva samples were missing. Participants were instructed not to consume
caffeine or alcohol for 24 hours before sampling and not to eat, drink, exercise, or brush their
teeth for 30 minutes preceding any sample. Cortisol samples were assayed in duplicate by
Salimetrics, LLC and the mean value of the two assays (inter-assay correlation r(1,432) = .98, p
< .001) was used for analysis. Cortisol samples with values > 3 SD above the mean for each time
point were treated as missing (1.7%). To calculate CAR, the 1st cortisol sample is subtracted
from the higher value between the 2nd or 3rd sample (Stalder et al., 2016). The mean CAR value
across days was used to test mediation. Hours of sleep, awakening time, use of medications that
influence HPA activity, and cotinine, a byproduct of nicotine, were measured as covariates.
Childhood Adversity. Repeated measurement of childhood adversity was modeled on
the Adverse Childhood Experiences Scale (ACES; Felitti et al., 1998), which asks adults to
dichotomously report whether each of 10 forms of adversity (emotional abuse, physical abuse,
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 14
sexual abuse, neglect, parental separation/divorce, interparental physical aggression, parental
substance abuse, parental mental illness, parental incarceration, and being unloved) occurred at
any point in childhood. In this study, across waves 1 to 4, youth, mothers, and fathers each
completed a range of questionnaires measuring each of these adversities. If any reporter endorsed
that one of these adversities occurred during any wave, youth received a score of 1 for that
construct. Possible scores ranged from 0-10 and observed scores ranged from 1-9 (M = 3.62).
BMI. Participants reported their height (feet and inches) and weight (pounds), which
were used to compute BMI according to the Quetelete formula.
Adolescent Life Stress. In order to adjust for the effect of current stress on CAR, at wave
5 participants completed the Life Events Checklist (modified from Johnson & McCutcheon,
1980). Participants rated whether 56 stressful events occurred in the past year, whether each
event was good or bad, and how much the event affected them (1 No effect to 4, Large effect);
each item described as ‘bad’ was multiplied by its effect, then all products were summed.
Analytic Plan
Mediation was tested using the PROCESS macro for SPSS to calculate bias-corrected
bootstrapped 95% confidence intervals and heteroscedasticity-consistent standard errors, using
1000 repetitions to estimate the indirect effect. All model variables were standardized. Age,
gender, family income, race/ethnicity, number of data collection waves completed, and variables
influencing cortisol concentration (cotinine, hours of sleep, awakening time, medication, and
level of cortisol upon awakening) were separately tested as covariates but excluded when they
did not substantially alter the direction or magnitude of estimated effects. Because both historical
and current stress have been shown to exert opposite direction effects on CAR (Miller et al.,
2016), models testing childhood adversity adjusted for past year stress. Mediation effect size was
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 15
calculated as the relative magnitude of the indirect to the total effect.
Results
Table 1 presents the means, standard deviations, and bivariate correlations among all
study variables. Childhood adversity was associated with flatter CAR and greater BMI;
adolescent life stress was associated with greater BMI. Adolescents with lower family income
had greater BMI in young adulthood, and older participants had higher BMIs.
As shown in Figure 1, CAR mediated the association between childhood adversity and
adult BMI. Adversity had a positive total effect on BMI (H1, path c, b = 0.290, SE = 0.113, p =
.013, CI = 0.064, 0.516). Childhood adversity predicted flatter adolescent CAR (path a, b = -
0.293, SE = 0.141, p = .041, CI = -0.574, -0.012), and flatter adolescent CAR predicted higher
young adult BMI (path b, b = -0.196, SE = 0.093, p = .037, CI = -0.381, -0.012). Adversity had a
significant indirect effect on BMI through CAR (H2, path a*b, b = 0.058, SE = 0.042, CI =
0.001, 0.168). After adjusting for CAR, the direct effect of adversity on BMI narrowly missed
significance (path c’, b = 0.233, SE = 0.119, p = 0.054, CI = -0.004, 0.470). All models adjusted
for adolescent stress, which predicted higher BMI (b = 0.290, SE = -.125, p = 0.023, CI = 0.040,
0.539) but not steeper CAR (b = 0.219, SE = 0.113, p = 0.056, CI = -0.005, 0.443). This indirect
effect accounted for 20% of the total effect of adversity on BMI (PM = 0.198, CI = 0.002, 1.080).
Discussion
This investigation advances the literature by highlighting HPA activity as a mechanism
that partially accounts for associations between childhood adversity and young adult health,
thereby connecting two extensive literatures: early adversity and disrupted HPA (e.g., Danse &
McEwan, 2012) and childhood adversity and later health (e.g., Felitti et al., 1998). Findings
provide initial empirical support for a frequently posited disease mechanism (e.g., McEwen,
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 16
1998), and also highlight a potential point of intervention: adolescence may be an opportune time
to identify and alter maladaptive health trajectories to prevent disease.
These results are preliminary because of a key limitation: we cannot test the specific
mechanisms proposed in the literature (e.g., Adam & Epel, 2007) by which HPA may influence
BMI, such as: activity and sedentary behavior, wear and tear on metabolic and growth systems
governed by the action of cortisol (e.g., insulin resistance, inflammation, growth hormone
production), and appetite and eating behavior, including both HPA-induced alterations to satiety-
signaling hormones such as leptin, and the use of eating as an emotion regulation strategy. Other
limitations include the self-reported nature of BMI, lack of a childhood measure of BMI, and
lack of early childhood measures of adversity or HPA activity, which would allow us to specify
when in childhood adversity might take the biggest toll. Additionally, the size of our sample
precludes identification of potential moderating variables, such as gender. As our mediation was
able to account for only 20% of the effect of adversity on BMI, future studies are needed to
identify additional risk pathways, which likely include health behaviors.
These results are nonetheless notable in that they demonstrate a subtle way that childhood
adversity may impact health through attenuated HPA, even in a community sample; the
importance of stress-induced HPA alterations may be even more marked among populations
identified for severe adversity or obesity. Though HPA hypo-activation can be protective in the
face of ongoing stress (e.g., Shirtcliff, Peres, Dismukes, Lee, & Phan, 2014), these data highlight
potential long-term costs of adaptation to adverse environments. This project makes use of a
labor intensive, multi-year, multi-method data set to provide the initial test of a physiological
mechanism underpinning social determinants of health. In doing so, it sets the course for future
research to uncover the role of HPA attenuation in trajectories from adversity to illness.
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 17
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CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 19
Table 1

Descriptive Statistics and Correlations Among Study Variables (n = 82)

1. 2. 3. 4. 5. 6.
1. Childhood adversity -
2. Adolescent CAR -.250* -
3. Young adult BMI .337* -.201 -
4. Adolescent stress .175 .166 .296** -
5. Adolescent age .090 -.200 .290** .012 -
6. Family income -.175 .208 -.344** -.142 -.199 -

Mean 3.622 0.174 25.812 12.598 18.088 89.555
SD 1.622 0.201 5.633 9.568 1.112 54.604
Observed Range 1.0-9.0 -0.44-0.84 16.97-42.82 0.0-42.0 14.92-21.05 0.0-290.0
Notes: CAR = Cortisol Awakening Response and is represented in µg/dL. Income is presented in thousands of dollars.

*p < .05, ** p < .01, *** p < .001

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 20

Figure 1. Bootstrapped mediation model demonstrating the longitudinal associations among childhood adversity, adolescent Cortisol
Awakening Response (CAR), and young adulthood BMI, adjusting for current adolescent stress.

Childhood
adversity
Adolescent
CAR
Young adult
BMI
-.29* (a) -.20* (b)
0.29* (c)
0.23 (c’)
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 21

Paper 2
Family Aggression and Attachment Avoidance Influence Neuroendocrine Reactivity in Young
Adult Couples
Kelly F. M. Kazmierski, Christopher R. Beam, & Gayla Margolin
University of Southern California

Author Note:
Funding for this study was provided, in part, by NIH NICHD R21HD072170 awarded to
Margolin and NSF Graduate Research Fellowship DGE-0937362 awarded to Kazmierski. The
authors would like to thank the research participants and our USC Family Studies Project
colleagues, particularly Corey Pettit and Stassja Sichko. Preliminary data from this study were
presented at the 34th Annual Meeting of the International Society for Traumatic Stress Studies.

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 22
Abstract
Family of origin aggression (FOA) exposure is a chronic childhood stressor that has been linked
to altered stress reactivity of the hypothalamic pituitary adrenal (HPA) axis in adulthood. Effects
of FOA also spill over between partners in romantic couples, such that one partner’s FOA history
influences the other’s HPA reactivity during couple interactions. However, the direction of these
effects is inconsistent, with both heightened and blunted HPA reactivity observed; this
heterogeneity suggests the presence of moderators. The present study measures HPA reactivity
during emotionally vulnerable conversations between young adult romantic partners to assess
whether romantic attachment avoidance accounts for this divergence by moderating actor- and
partner-effects of FOA on HPA. One hundred-twelve opposite-sex couples (224 young adults)
provided information on FOA and avoidance, completed dyadic interaction procedures, and
provided saliva samples to assess HPA reactivity during interactions. Multi-level structural
equation models revealed that FOA did not predict either own or partner’s HPA reactivity.
However, FOA and avoidance interacted to produce both actor- and partner-effects, such that
greater FOA exposure heightened HPA reactivity when avoidance was high but blunted
reactivity when avoidance was low. Results support that proximal relationship-related
characteristics, such as attachment avoidance, influence whether distal relationship-related
stressors, such as FOA, amplify or attenuate physiological reactivity during emotionally
vulnerable interactions. As HPA reactivity has been linked to a variety of health outcomes,
identifying relationship-related buffers of associations between FOA and HPA response may
inform future interventions to protect health for FOA-exposed youth.
Keywords: Family aggression, attachment avoidance, HPA reactivity, couples
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 23
Family Aggression and Attachment Avoidance Interact to Influence Neuroendocrine Reactivity
in Young Adult Couples
One of the most influential biopsychosocial findings of the past decade is that close
relationships powerfully influence physiology and health (e.g., Repetti, Robles, & Reynolds,
2011). Exposure to family of origin aggression (FOA) in childhood has been linked to altered
reactivity of the hypothalamic-pituitary adrenal (HPA) axis in adulthood (Luecken & Lemery,
2004); dysregulation of this stress response has been posited as a mechanism linking childhood
adversity to adult physical and mental illness (e.g., Danese & McEwen, 2012; Repetti, et al.,
2011). However, the literature is inconsistent regarding the direction of effect FOA exerts on the
HPA axis, as FOA has been observed to both heighten and blunt HPA reactivity to social stress
(e.g., Carpenter, Shattuck, Tyrka, Geracioti, & Price, 2011, Heim et al., 2000). Inconsistent
findings may be due, in part, to measuring the effect of distal family relationship experiences
without accounting for the simultaneous influence of adult’s proximal romantic relationships.
Adults from aggressive families who go on to report comfort with emotionally close romantic
relationships may exhibit reduced social stress reactivity, whereas FOA-exposed adults who
avoid emotional vulnerability with partners in adulthood may exhibit heightened reactivity to
social stress. Moreover, emerging evidence suggests that the effect of FOA on physiological
regulation spills over across romantic partners, such that one partner’s history of family adversity
influences the other partner’s HPA reactivity during dyadic interactions (Arbel, Rodriguez, &
Margolin, 2016; Winer, Powers, Pietromonaco, & Schreck, 2018); however, these partner effects
are also plagued by contradictory findings as to the direction of FOA’s effect on stress reactivity.
The present study leverages young adults’ current relationships in order to identify
sources of heterogeneity in FOA’s effect on stress physiology. We measure actor- and partner-
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 24
effects of FOA on individuals’ HPA reactivity to dyadic interactions that elicit emotional
vulnerability between dating partners. We then assess whether romantic attachment avoidance
acts as a moderator that accounts for whether FOA confers heightened or blunted HPA
reactivity.
Divergent Effects of FOA on HPA Reactivity
Literature describing the effects of early stress exposure, such as FOA, on adult HPA
activity has been marked by contradictory findings, leading to several theoretical reviews and
meta-analyses on the topic (e.g., Bunea, Szentagotai-Tatar, & Miu, 2017; Miller, Chen, & Zhou,
2007; Shirtcliff, Peres, Dismukes, Lee, & Phan, 2014). Findings supporting that FOA reduces
HPA reactivity have frequently been understood through the lens of allostatic theory, which
describes how the body modifies its basal functioning in response to environmental demand
(McEwen, 1998). Children mount a stress response to FOA, activating the HPA axis to mobilize
energy to meet the demands of the stressor in the short term; the magnitude of this response can
be measured via secretion of cortisol, an end product of HPA axis activity. However, repeated
activations recalibrate the HPA axis, such that a greater degree of threat is needed for the body to
mount a response. Therefore, allostatic models posit that exposure to chronic social stress, such
as FOA, should lead to increased HPA reactivity in the short term but reduced HPA reactivity in
the long term (e.g., Miller, et al., 2007), such that by adulthood FOA-exposed individuals exhibit
blunted HPA response to stress.
In contrast, conflict sensitization theories have been extended to physiological stress
paradigms in order to explain how early FOA exposure might heighten adults’ HPA reactivity to
stress (e.g., Arbel et al., 2016; Margolin, Ramos, Timmons, Miller, & Han, 2016). According to
conflict sensitization theories (Cummings & Davies, 1996; Grych & Fincham, 1990), FOA leads
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 25
children to anticipate more frequent and severe conflict during family interactions. In turn,
stimuli appraised to be more threatening elicit greater HPA activation (Denson, Spanovic, &
Miller, 2009). Therefore, FOA-exposed adults may exhibit heightened HPA reactivity to social
stressors because their social learning history leads them to anticipate that social stimuli have the
potential to become aggressively threatening.
In line with allostatic theory, meta-analyses support that childhood maltreatment
generally leads to attenuated cortisol reactivity to social stress in adulthood (Bunea, et al., 2017);
however, the heterogeneity of this effect across studies is large, suggesting the presence of
moderating factors. In contrast, consistent with conflict sensitization theories, increased
reactivity has also been observed following childhood maltreatment, though heightened
reactivity is most common in samples of adults with concurrent depression or anxiety (e.g.,
Elzinga, Spinhoven, Berretty, de Jong, Roelofs, 2010; Heim et al., 2000), whereas decreased
reactivity is more common in non-clinical samples (e.g., Carpenter, et al., 2011).
FOA’s Influence on HPA Reactivity within Romantic Relationships
Importantly, studies have primarily examined FOA-induced reactivity to standardized in-
lab paradigms in which strangers are the source of social-evaluative stress. However, FOA may
exert domain-specific effects on HPA reactivity in the context of close relationships (Margolin et
al., 2016), by heightening expectations that relationships pose a source of threat (Grych &
Fincham, 1990). Only two studies have examined FOA’s effect on adults’ HPA reactivity during
interactions with romantic partners, with one study finding that greater FOA predicted
heightened HPA reactivity for wives only (Arbel et al., 2016), and the other finding no effect for
husbands or wives (Winer et al., 2018) during conflict discussions. However, FOA may sensitize
reactivity not only to conflict, but also to any emotionally intimate interaction that is perceived as
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 26
conferring risk for conflict. These experiences of emotional vulnerability, such as reciprocally
disclosing painful experiences and emotions, are common in romantic relationships (Lippert &
Prager, 2001), yet to our knowledge, no study has assessed FOA’s effect during such
interactions. Heightened reactivity to these day-to-day challenges in close relationships may
accelerate the deleterious effect of FOA on health by inducing chronic HPA activation, even
between conflict episodes. However, capturing reactivity within close relationships is
challenging, as even conflictual discussions do not produce the same acute cortisol increases as
social-evaluative paradigms (Gunnar, Talge, & Herrera, 2009; Robles & Kiecolt-Glaser, 2003);
rather, as demands of social interactions are layered upon a downward diurnal pattern in cortisol,
reactivity is often captured by between-person variability in cortisol starting point and rate of
decline across the interaction tasks (e.g., Kiecolt-Glaser et al., 1997).
Attachment Avoidance as a Moderator
What determines whether a history of FOA-induced physiological wear-and-tear
dampens HPA reactivity or a history of FOA-induced social learning heightens HPA reactivity?
Resolving this heterogeneity requires conceptualizing the effects of FOA as depending in part on
the characteristics of the person coping with this stressor. Adults’ attachment avoidance may be
one such salient moderating characteristic. Attachment provides a mechanism for the social
regulation of stress. Through repeated interactions in close relationships, individuals develop
mental representations of relationships that guide both their expectations regarding the
availability and responsiveness of others and their behaviors regarding how and whether to turn
to others for help regulating vulnerable emotions (Bowlby, 1969/1982). Attachment arises in
infancy and extends throughout the lifespan, such that romantic partners serve as attachment
figures for adults, much as parents serve as attachment figures for children (Hazan & Shaver,
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 27
1987). Those who are higher in attachment avoidance expect that relationship partners will be
unresponsive to their stress; therefore, they regulate emotion by turning attention away from
emotional and relationship needs (Bowlby, 1988). Avoidant adults have difficulty opening up to
and relying on others and are uncomfortable with partners’ bids for closeness; rather, they prefer
to modulate emotions independently (Brennan, Clark, & Shaver, 1998).
Avoidance may interact with FOA to heighten HPA reactivity to dyadic interactions by
increasing the perceived stressfulness of interpersonal emotional vulnerability. Attachment
avoidance influences how interactions are appraised (e.g., Collins & Feeney, 2004), with
avoidant adults most threatened by situations that require providing and receiving intimate
emotional support (Simpson & Rholes, 1994). Moreover, more avoidant individuals may have
less experience discussing vulnerable topics with partners, and more novel tasks elicit a greater
cortisol response (e.g., Levine, 1978). Finally, avoiding emotionally vulnerable interactions
reduces opportunities for new social learning. Therefore, more avoidant, FOA-exposed adults
may exhibit greater conflict sensitization, as they have avoided adult interpersonal experiences
that might contradict expectations acquired in aggressive families of origin. In contrast, adults
who are low in attachment avoidance regulate emotion by turning to attachment figures (Brennan
et al., 1998). Through repeated experiences approaching others, less avoidant adults may update
social learning acquired in the family of origin to also reflect interactions with non-aggressive
partners or peers, reducing conflict sensitization and contributing to expectations that engaging
in emotionally vulnerable interactions may be rewarding rather than threatening.
Allostatic models posit that childhood stress exposure generally raises adults’ threshold
for mounting a stress response, reducing reactivity. FOA-exposed adults who are low in
attachment avoidance may not experience dyadic interactions as sufficiently stressful to surpass
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 28
this heightened threshold; therefore low-avoidant, FOA-exposed adults appear to be less
physiologically reactive than their non-FOA exposed peers. In contrast, highly avoidant FOA-
exposed adults may experience emotionally vulnerable interactions as sufficiently stressful to
surpass their elevated stress-response threshold; the HPA response they then mount will be
elevated due to social learning that has sensitized perceived risk incurred by social stress.
Actor and Partner Effects
Emerging evidence suggests that FOA history not only affects one’s own stress
physiology but also spills over across partners, such that one person’s FOA influences the other’s
HPA reactivity (Arbel et al., 2016; Winer et al., 2018). However, partner effects have been
contradictory across studies. Whereas Arbel and colleagues (2016) found that when wives had
more FOA exposure, their husbands showed greater HPA reactivity during family conflict
discussions, Winer and colleagues (2018) found the opposite: when wives had experienced more
early family adversity, husbands showed reduced HPA reactivity to dyadic conflict discussions.
Importantly, partner effects of FOA depend on characteristics of the current relationship,
such as romantic partner aggression (Arbel et al., 2016) and negative behaviors during conflict
(Winer et al., 2018). Attachment avoidance may also moderate FOA’s effect across partners.
Avoidance has previously been shown to exert partner effects on HPA reactivity (e.g., Brooks,
Robles, & Dunkel Schetter, 2011; Powers, Pietromonaco, Gunlicks, & Sayer, 2006); however,
how FOA and avoidance may interact to produce partner effects is unclear. One possibility is
that because both actors’ FOA and attachment avoidance are associated with more negative
dyadic behaviors (Campbell, Simpson, Kashy, & Rholes, 2001; Halford, Sanders, & Behrens,
2004), their combination may impart additive risk, evoking greater HPA activity from partners.
Alternatively, avoidance may protect against partner effects of FOA, as withdrawing from
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 29
conflict may mitigate the risk of engaging in aggressive behaviors (Orcutt, Garcia, & Pickett,
2005) for those whose family experiences endow greater risk of aggression perpetration (e.g.,
Linder & Collins, 2005). Or, if knowledge of partners’ FOA history influences HPA reactivity,
more avoidant adults might protect partners from FOA’s effect by not disclosing this history.
Finally, in line with physiological linkage models, which posit that relationship partners jointly
achieve homeostasis by bringing each other toward a shared physiological baseline and
transmitting alterations in stress-related reactivity (Timmons, Margolin, & Saxbe, 2015), HPA
reactivity may spill over across partners (Saxbe & Repetti, 2010), such that the same
combinations of FOA and avoidance that heighten or dampen reactivity within-person exert
same-direction effects across partners.
The Present Study
The present study examines the effects of FOA on HPA reactivity to emotionally-
vulnerable conversations between young adult dating partners; discussion topics include desired
areas of relationship change and experiences of personal loss. We estimated individual HPA
reactivity using multilevel models for change (Singer & Willett, 2003), which include person-
specific cortisol intercepts and slopes, in order to capture both anticipatory HPA activation and
change in activation across the conversation task. Dampened reactivity is conceptualized as
lower cortisol intercept and flatter slope, whereas heightened cortisol reactivity is conceptualized
as higher cortisol intercept and steeper slope. In line with allostatic adaptation, we predict that
exposure to FOA during childhood will blunt within-person HPA reactivity to this task
(Hypothesis 1A). Given the co-regulated nature of physiological reactivity, we also predict that
partner effects of FOA on HPA will be observed (Hypothesis 1B), though, in light of mixed
findings in the limited research literature, we do not predict a direction of this effect. Next, we
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 30
examine whether attachment avoidance moderates the effects of FOA on HPA reactivity. We
predict that greater FOA will be associated with dampened HPA reactivity when avoidance is
low but with heightened HPA reactivity when avoidance is high (Hypothesis 2A). We further
explore whether interactive effects of FOA and attachment avoidance will also be observed
cross-partner, such that one partner’s HPA will depend on the interaction of the other partner’s
FOA and avoidance (Hypothesis 2B), though we do not predict a direction of this effect. As
gender differences in HPA reactivity are commonly observed (e.g., Brooks et al., 2011; Kudielka
& Kirschbaum, 2005), all hypotheses will explore differences between male and female partners.
Methods
Participants
Participants included 112 opposite-sex couples (224 individuals) who completed
interaction procedures, reported on FOA and avoidance, and provided saliva samples for cortisol
assay; of these participants, 29 young adults had participated as children or adolescents in a
longitudinal study assessing family aggression and adjustment. To be eligible for the present
study, these returning participants had to be in a dating relationship for at least 2 months with a
partner who was willing to complete procedures. The remaining 83 couples were recruited from
the community to match returning participants; newly recruited participants had to be aged 18-
25, in a relationship for at least 2 months, and able to complete all study procedures in English.
Participants were typically in their early twenties (Mmen = 23.1, Mwomen = 22.1) and together for
an average of 30 months (range = 2-109 months), with 44% of participants cohabiting.
Participants were diverse in terms of race/ethnicity (13% Asian, 15% African American/Black,
27% Non-Hispanic White/Caucasian, 25% Hispanic/Latino, 16% Multi-racial, and 4% other).
Most participants worked (40% employed), attended school (19% students), or both worked and
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 31
attended school (34% employed students).
Procedures
All study procedures were approved by USC’s IRB. Before the lab visits, participants
completed a series of questionnaires from home, administered online via Qualtrics. Participants
were instructed not to eat, drink, or chew gum for one hour prior to the visit, nor to brush their
teeth for three hours prior, nor to consume alcohol or use tobacco for 24 hours prior. To reduce
variability due to cortisol’s diurnal pattern, all visits were scheduled to begin between 10 A.M.
and 1 P.M. In lab, participants consented to study procedures, engaged in a series of interactions
with concurrent physiological assessments and questionnaires. Specific procedures applicable
here include a 15-minute relaxation period, during which participants watched a nature video
followed by couple interactions, which include a series of discussions, described below. After the
discussions, participants engaged in a 20-minute recovery task, during which they were asked to
“unwind” by engaging in a creative project; participants were provided art supplies to jointly
build and decorate a construction paper tower (J. Gottman, personal communication, September
9, 2002). Participants then completed additional questionnaires.
Discussion procedures. Participants completed four discussions: date planning (5 min),
desired areas of relationship change (10 min), and loss (2 discussions, 10 min each).
Date planning. Participants completed a baseline discussion, during which they were
asked to plan an enjoyable date together.
Change. To identify topics for the change discussion, each participant completed a
questionnaire assessing common areas of desired relationship change. Each partner then met
separately with an experimenter for a 5-minute interview to identify the most emotionally salient
topics and elicit what participants would like to tell their partners about the topic. Experimenters
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 32
jointly selected 2-4 topics, reflecting each partner’s desired areas of change for the conversation.
Participants were asked to talk about any combination of these topics in any order.
Loss. Each participant completed a questionnaire assessing common forms of loss (e.g.,
death, illness). Participants then met separately with an experimenter for 5-min interviews to
identify the loss that elicited the most sadness and to help participants identify what they would
like to express to their partners about what made the loss meaningful (Margolin, et al., 2019).
Experimenters identified the most salient loss topic for each participant. Each partner’s loss was
discussed in a separate conversation, the order of which was randomized. One partner was
instructed to describe the meaning and impact of the loss; the other partner was instructed to try
to understand by listening, commenting, and asking questions in whatever ways felt natural.
Saliva collection procedures. Participants provided 0.4 mL of saliva via passive drool
following relaxation, the conflict discussion, the second loss discussion, and the recovery
interaction. Members of each couple provided samples simultaneously, though sampling
intervals varied between couples. Approximately 2 hours (M = 2.04, SD = 0.14, range = 1.75-
2.43) elapsed between the first and final sample. Samples were immediately stored in a -80° C
deep freezer for later cortisol assay by the Dresden LabService GmbH.
Measures
Family of origin aggression. FOA was measured before the lab visit using the parent-
child conflict scale, which includes 14 items adapted from the Conflict Tactics Scale (Straus,
Hamby, Finkelhor, Moore, & Runyan, 1998, alpha = .907). Participants report how often parents
engaged in any of 14 aggressive behaviors towards them out of anger at any point during
childhood, using a 5-point Likert scale (0 = Never, 4 = more than 6 times). Eight items measured
parent-to-child psychological aggression (e.g., “Insulted you or told you that you were not good
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 33
enough or that you are a failure,”) and six items measuring parent-to-child physical aggression
(e.g., “Pushed, grabbed, or shoved you,”). Scores are derived by summing across the 14 items.
Most participants (85.6%) reported having experienced at least some parent-to-child aggression.
Avoidance. Attachment avoidance was measured in-lab using the Experiences in Close
Relationships-Revised Questionnaire (ECR-R; Fraley, Waller, & Brennan, 2000, alpha = .902),
which includes 36 items that measure two dimensions of attachment security: anxiety and
avoidance. Avoidance was calculated as the mean of 18 items measuring discomfort with
emotional intimacy and reliance on others (e.g., “I don't feel comfortable opening up to romantic
partners,” and “I find it difficult to allow myself to depend on romantic partners,”), using a 7-
point Likert scale (1 = Strongly disagree, 7= Strongly agree).
HPA reactivity. Cortisol levels were assayed from saliva samples, using high-sensitivity
immunoassay. To establish reliability, 31% of samples were assayed in duplicate (inter-assay
correlation r = .99, p <.001); the initial assay was used for all analyses. Cortisol values > 3 SD
above the mean for each sampling point (2.5% of samples) were winsorized to values 3 SD
above the mean. Sampling time was recorded as minutes elapsed since initial sample provision
(time of initial sample was centered at 0). HPA reactivity was modeled as cortisol slope (effect
of time on cortisol) and cortisol intercept (predicted cortisol value at time 0).
Covariates for cortisol analyses. As smoking tobacco influences salivary cortisol
(Granger et al., 2007), the initial sample provided by each participant was assayed for cotinine, a
biproduct of nicotine. Twenty-seven participants had sufficiently elevated levels of cotinine to
suggest recent nicotine use (>10 ng/ml; Caraballo, Giovino, & Pechacek, 2004) and at least trace
levels of cotinine were detectible for 92% of participants. To adjust for cortisol’s diurnal pattern,
participants reported their time of awakening, and the number of hours elapsed between
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 34
awakening and the initial saliva sample was calculated for each participant. Participants reported
whether they took a number of medications known to affect HPA activity (contraceptive, steroid,
and stimulant ADHD medications); 37% of participants reported using at least one of these
medications. Medication use was dummy-coded (0 = no medication, 1 = medication).
Demographic information. During the laboratory visit, participants reported personal
demographics (age, gender, self-identified racial/ethnic background, employment/student status)
and relationship demographics (number of months together as a couple, cohabitation).
Analytic Plan
We tested each hypothesis using a multi-level structural equation model, to account for
the nested structure of dyadic data. Data were structured in a two-level format, with repeated
cortisol measurements and sampling times for each partner in tall format and partners within
each dating couple in a wide format (Laurenceau & Bolger, 2012). Preliminary analyses did not
indicate that time exerted a curvilinear effect on cortisol reactivity. Rather, consistent with
findings that not all couples mount a cortisol increase to conflict discussions (Robles & Kiecolt-
Glaser, 2003), 77% of women and 79% of men in our sample showed no increase from pre- to
post- interaction samples. Therefore, model assumptions include linearity of effects, as well as a
multi-level data structure, independence of predictor variables, within-person heteroscedasticity
of residual variance, within-person auto-correlated residuals, and multivariate normal
distribution of residuals.
In the multi-level portion of our model, we tested the effect of time on cortisol (cortisol
slope) at level 1. Individual-specific intercepts and slopes were estimated simultaneously for men
and women. At level 2, we modeled random slopes and intercepts for variables that vary between
but not within participants (e.g., FOA). Level 2 equations estimated the effects of predictors and
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 35
covariates on cortisol intercepts and slopes, separately for men and women. All level 2
predictors were grand mean centered. Level 2 interaction scores were calculated as the product
of centered FOA and avoidance values. The following equations represent the multi-level
component of our model used to test Hypotheses 2A and 2B (the model testing Hypotheses 1A
and 1B excludes avoidance and interaction terms but is otherwise identical):
Maleit = α0i + α1i(timeit) + eit (1)
Femaleit = β0i + β1i(timeit) + fit (2)
α0i = γ00 + γ 01 (men’s FOAi) + γ02 (women’s FOAi) + γ03 (men’s avoidancei) + γ04
(women’s avoidancei) + γ05 (men’s FOA x avoidancei) + γ06 (women’s FOA x avoidancei)… +
γ0n (covariate ni) + u0i (3)
α1i = γ10 + γ 11 (men’s FOAi) + γ12 (women’s FOAi) + γ13 (men’s avoidancei) + γ14
(women’s avoidancei) + γ15 (men’s FOA x avoidancei) + γ16 (women’s FOA x avoidancei)… +
γ1n (covariate ni) + u1i (4)
β0i = δ 00 + δ01 (women’s FOAi) + δ 02 (men’s FOAi) + δ03 (women’s avoidancei) + δ04
(men’s avoidancei) + δ05 (women’s FOA x avoidancei) + δ 06 (men’s FOA x avoidancei) + δ0n
(covariate ni) + v0i (5)
β1i = δ10 + δ 11 (women’s FOAi) + δ 12 (men’s FOAi) + δ13 (women’s avoidancei) + δ14
(men’s avoidancei) + δ15 (women’s FOA x avoidancei) + δ 16 (men’s FOA x avoidancei) + δ1n
(covariate ni) + v1i (6)
In level 1 equations (1-2), Maleit and Femaleit represent partner i's cortisol value at time t, which
is a function of an individual-specific intercept (α0i and β0i for men and women, respectively),
individual-specific slope (α1i, β0i), and a residual score (eit, fit). Level 2 equations (3-6) model the
individual-specific intercepts and slopes as outcomes (α0i and α1i for men, β0i and β1i for women).
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 36
The intercepts and slopes of these equations are modeled as a function of level 2 predictors to
test our substantive hypotheses regarding the effects of FOA and avoidance. Level 2 covariates
in each model include relationship duration, time since awakening, cotinine value, and
medication use for each individual. Figure 1 represents the structural equation portion of our
model, which tests hypothesized actor and partner parameter effects specified in equations 3-6.
Analyses were conducted in Mplus 8.0 (Muthén & Muthén, 1998-2017), using maximum
likelihood estimation to compute parameter estimates. Full information maximum likelihood
estimation was used to handle missing data under the missing at random assumption. The
modeling sequence is described in Appendix Table 1. The Satorra-Bentler chi-square difference
test of nested models was used to select the best fitting model. Akaike Information Criterion
(AIC) and Bayesian Information Criterion (BIC) were used as additional indexes of model fit.
When significant interactions were found, the region of significance was calculated to determine
levels of the moderator at which effects are observed (Johnson & Neyman, 1936), using R scripts
for extracting and plotting Mplus data (http://www.statmodel.com/mplus-R/).
Results
Descriptive Statistics and Correlations
Table 1 presents the means, standard deviations, and correlations among all variables. t-
tests did not support that men and women differed significantly on any of the study variables or
covariates. Male and female partners exhibited positively correlated levels of FOA, avoidance,
and cortisol. Women’s cortisol was negatively associated with their partners’ FOA, such that
when men had more aggressive families, women had lower mean cortisol levels. Modeling the
effect of time on cortisol at level 1, both men and women exhibited negative cortisol slopes
(men’s slope b = -1.55, SE = 0.16, p <.001; women’s slope b = -0.71, SE = 0.16, p < .001) and
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 37
positive cortisol intercepts (men’s intercept b = 6.63, SE = 0.44, p <.001; women’s intercept b =
5.32, SE = 0.30, p <.001).
Hypothesis 1
Neither Hypothesis 1A nor 1B were supported. As shown in Table 2, Model 1, there were
no actor effects of FOA on HPA reactivity for men (intercept b = 0.04 SE = 0.04, p = .355; slope
b <.01, SE = .02, p = .878) or women (intercept b = -.01, SE = .02, p = .755; slope b = -.01, SE
= .01, p = .172). There were no statistically significant partner effects of women’s FOA on men’s
HPA (intercept b = -.03, SE = .03, p = .399; slope b = .01, SE = .01, p = .451) nor of men’s FOA
on women’s HPA (intercept b = -.03, SE = .02, p = .129; slope b = -.01, SE = .01, p = .548).
Hypothesis 2
Hypothesis 2A. In partial support of Hypothesis 2A, actor effects were observed, such
that FOA and avoidance interacted to predict HPA reactivity for men but not for women. For
men, the effect of FOA depended on avoidance (intercept b = .09, SE = .04, p = .022; slope b =
-.03, SE = .01, p = .005, see Table 2 Model 2). For men who were high in avoidance (≥ +1.4
SD), greater FOA predicted higher intercepts (simple slope b = .13, SE = .06, p = .049). For low
avoidant men (< 1.4 SD), FOA did not have a significant association with initial cortisol levels
(see Figure 2A). When men’s avoidance was high (≥ +2.0 SD), greater FOA predicted steeper
negative slopes (b = -.04, SE = .02, p = .049), whereas when men’s avoidance was low (≤ 0.9
SD), greater FOA predicted flatter cortisol slopes (b = .02, SE = .01, p = .049, see Figure 2B).
In contrast, women’s FOA and avoidance did not significantly interact to influence
women’s cortisol reactivity (intercept b = -.01, SE = .02, p = .512; slope b = .01, SE = .01, p
= .324, see Table 2).
Hypothesis 2B. In support of Hypothesis 2B, partner effects were observed for both men
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 38
and women (see Table 2). Men’s HPA reactivity depended on the interaction of women’s FOA
and avoidance (intercept b = .08, SE = .04, p = .022; slope b = -.03, SE = .01, p = .016). As
shown in Figures 3A and 3B, when women’s avoidance was below the mean (≤ -0.1 SD), men
showed lower intercepts (b = -.05, SE = .03, p = .049) and flatter slopes (b = .02, SE = .01, p
= .049) associated with greater women’s FOA. In contrast, when women’s avoidance was
moderate or high, women’s FOA history had no statistically significant effect on men’s cortisol
intercept or slope.
Men’s avoidance and FOA did not interact to affect women’s intercepts (b = .03, SE
= .02, p = .14). Women’s cortisol slope, however, depended on the interaction of men’s FOA and
avoidance (b = -.02, SE = .01, p = .050). Men’s greater FOA was associated with women’s
steeper negative slopes when men’s avoidance was high (≥ +2.2 SD, b = -.05, SE = .03, p = .049,
see Figure 3C); at mean and low levels of men’s avoidance, effects of men’s FOA on women’s
cortisol slope were not statistically significant.
Discussion
The present study assessed how FOA and attachment avoidance interact to influence
HPA reactivity to emotionally vulnerable dyadic interactions between young adult dating
partners. Contrary to Hypotheses 1A and 1B, no direct actor or partner effects of FOA on HPA
reactivity were observed. In partial support of Hypothesis 2A, attachment avoidance accounted
for divergence in the direction of effect of FOA on HPA reactivity for men only, such that FOA
was associated with dampened reactivity (flatter slope) when avoidance was low but heightened
reactivity (higher initial levels of cortisol and steeper rates of decline) when avoidance was high.
In support of Hypothesis 2B, women’s FOA dampened men’s HPA reactivity (lower intercept
and flatter slope) only when women’s avoidance was low. Men’s FOA heightened women’s
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 39
HPA reactivity (steeper downward slope) only when men’s avoidance was high.
Results support that current interpersonal characteristics, such as attachment, modify the
effect of past interpersonal adversity, such as FOA, on physiological reactivity to social stress for
men; indeed, the effect of FOA was only detectable when considered in the context of
attachment avoidance. Consistent with allostatic models, when avoidance is low, FOA dampens
HPA reactivity; consistent with conflict sensitization models, when avoidance is high, FOA
heightens HPA reactivity. For high-avoidance men who have been exposed to greater FOA,
making personal disclosures and providing support may be sufficiently stressful to surpass even
elevated HPA response thresholds endowed by allostatic adaptation to FOA; once mounted,
HPA response is elevated due to conflict sensitization. In contrast, for low avoidance men who
have been exposed to greater FOA, turning to others to give and receive support is non-
threatening; therefore, an HPA response is not mounted and FOA-induced hypo-reactivity is
observed.
FOA and avoidance also interacted to influence HPA reactivity across partners, such that
similar patterns of FOA and avoidance predicted heightened or blunted HPA responses, both
within-person and across partners. For instance, the interaction of men’s greater avoidance and
greater FOA predicted a steeper slope for both themselves and their female partners. This finding
is consistent with models of physiological linkage (e.g., Timmons et al., 2015). However,
women’s FOA and avoidance interacted to influence men’s level and slope of HPA reactivity,
even though these same factors did not have a detectable effect on women’s own physiology.
Therefore, physiological linkage is unlikely to wholly account for partner effects. Future studies
should comprehensively assess variables that might account for partner effects by coding dyadic
behaviors that might transmit the effect of FOA across partners and by measuring each partner’s
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 40
knowledge of the other’s FOA history. Identifying how one partner’s early social stress exposure
influences the other’s physiology may enhance understanding of mechanisms contributing to
linkage in health outcomes for members of romantic couples (e.g., Meyler, Stimpson, & Peek,
2007).
Gender differences were observed, such that men’s physiology appeared to be more
responsive to both actor and partner effects of FOA and avoidance. As women generally “take
the lead” in dyadic discussions (e.g., Christensen & Heavey, 1990), navigating emotional
conversations may be more novel and stressful for men, eliciting HPA response. Additionally,
menstrual phase and use of hormonal birth control can confound HPA measurement in women
(Kudielka & Kirschbaum, 2005); though the present study accounted for medication use, we
were unable to measure menstrual phase. Finally, different factors may govern women’s HPA
reactivity to dyadic interactions; for instance, aggression in the present relationship, rather than
FOA, may be a primary determinant of HPA reactivity for women, who are more likely to
experience severe forms of partner aggression (Coker et al., 2002).
Though avoidance contributes to different trajectories of HPA reactivity following FOA,
it remains unclear whether either of these trajectories is health-protective, as both up- and down-
regulation have been implicated in disease processes (e.g., McEwen, 1998). However, downward
recalibration of the HPA axis may protect against the burden of chronic stress exposure by
limiting encoding of adverse environmental stimuli, reducing glucocorticoid-induced immune
alterations, and conserving energy during threats that do not respond to active coping efforts (Del
Giudice, Ellis, & Shirtcliff, 2011; Fries, Hesse, Hellhammer, & Hellhammer, 2004). In line with
the above, FOA-induced increases in HPA reactivity are more common in clinical samples (e.g.,
Heim et al., 2000) and have been posited as a mechanism linking early stress exposure to the
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 41
development of depression (Mello, Mello, Carpenter, & Price, 2003). Hypo-reactivity may be a
relatively adaptive response to an aggressive environment (e.g., Saxbe, Margolin, Shapiro, &
Baucom, 2012) that has the potential to reduce allostatic load (Hellhammer, Schlotz, Pirke, &
Stone, 2004). Downward recalibration may be especially protective for FOA-exposed young
adults, as younger adults are more likely to still be in regular contact with families of origin.
Therefore, in contrast to buffering models that conceptualize protective relationship factors as
those that appear to erase the effects of early life stress on adult physiology, protective
relationship factors may be those that promote adaptation in the optimal direction following
FOA. Future longitudinal research is needed to measure how FOA and avoidance interact to
predict mental and physical health outcomes and to assess whether HPA reactivity is a
mechanism linking FOA and avoidance to clinical endpoints.
Participants did not generally produce increased cortisol in reaction to emotionally
vulnerable interactions; rather, the highest cortisol values were observed at baseline. Although
this pattern of HPA reactivity is not unusual in response to discussion tasks (e.g., Kiecolt-Glaser
et al., 1997; Robles & Kiecolt-Glaser, 2003), it introduces several important limitations to our
study interpretations. High baseline values may indicate anticipatory stress, as participants were
aware that they would be completing a series of dyadic interactions; however, high baseline
values may also denote an “arrival effect” (Shirtcliff et al., 2014), indicating that coming to the
lab is more taxing than engaging in dyadic interactions. Additionally, declining cortisol values
across the day confound typical definitions of heightened or blunted cortisol reactivity. Though
we conceptualized increased reactivity as higher initial levels and steeper rates of change, sharp
decreases may instead indicate early termination of the HPA axis, which is a form of cortisol
blunting (Fries et al., 2005) that may represent disengagement from the task, insensitivity to
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 42
social cues, and passive coping (Shirtcliff et al., 2014). This alternative interpretation suggests
that the rapid reductions in cortisol observed in avoidant, FOA-exposed men might demonstrate
the regulatory strategy of avoidance in action, as participants turn attention away from
emotionally vulnerable stimuli to modulate physiology and emotion. Similarly, relatively low
and flat cortisol values were conceptualized as indicating blunted reactivity. However, minimal
declines may also represent continued HPA output to meet the demands of the task, supporting
the effortful, attuned engagement (Shirtcliff et al., 2014) that marks low-avoidance coping.
Importantly, the degree of cortisol slope may be limited by floor and ceiling effects introduced
by cortisol intercept, such that there is more opportunity for decline when cortisol starting values
are higher. Finally, the implications of dyadic physiological reactivity may depend on the context
(e.g., Timmons et al., 2015), such that the functions of HPA response during emotionally
vulnerable dyadic interactions may differ from the functions of HPA response to conflict
discussions, which are more commonly described in the literature.
The present study has several limitations. First, we cannot assess when in development
avoidance moderated the effect of FOA. Though avoidance is measured in the context of
romantic relationships, attachment styles may be long-standing (Bowlby, 1969/1982). If so, use
of avoidant emotion regulation strategies may have interfered with HPA habituation to FOA as it
occurred in childhood. Additionally, other interpersonal characteristics that may moderate the
effect of FOA are beyond the scope of the present study. For instance, aggression in the current
relationship may interact with FOA and avoidance to influence HPA reactivity. Notably,
romantic attachment has two orthogonal components: avoidance and anxiety (Brennan et al.,
1998). As tasks requiring emotional vulnerability are more likely to activate avoidant, rather than
anxious, mental models of attachment (Simpson & Rholes, 1994), we did not hypothesize effects
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 43
of attachment anxiety; however, it is possible that anxiety and avoidance jointly interact with
FOA to influence HPA reactivity. Finally, the present study treats avoidance as a moderator of
FOA, rather than as a mechanism linking FOA to HPA reactivity. Although early family
experiences are thought to contribute to attachment throughout the lifespan, determining causal
sequences from FOA to attachment was not possible in the present study, nor were FOA and
avoidance correlated in our sample. Moreover, young adult attachment is not determined by
experiences with parents alone but is also the result of interactions with peers and romantic
partners (Allen, Grande, Tan, & Loeb, 2018).
Despite these limitations, the present study identifies avoidance as an interpersonal
quality that may account for discrepancies in FOA’s effect on HPA reactivity. Additional
research is needed to extend findings from surrogate endpoints, such as HPA reactivity, to
clinical endpoints, such mental and physical disorders. FOA is a widespread social determinant
of disease that contributes to health disparities throughout the lifespan (e.g., Repetti et al., 2011),
but FOA exposure cannot be directly altered once incurred. In contrast, romantic attachment is
amenable to change (e.g., Taylor, Rietzschel, Danquah, & Berry, 2015). Romantic attachments
are established in young adulthood, which precedes the onset of FOA-linked adverse health
outcomes. Therefore, attachment avoidance may provide a promising target for future
interventions to protect the health of FOA-exposed young adults.
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 44
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CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 51
Table 1.

Means, standard deviations, and correlations among study variables.

Mean (SD) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.
1. W Cortisol
1
4.48 (2.85) -
2. M Cortisol
1
5.06 (3.84) .18* -
3. W FOA 14.94 (13.01) -.17† -.03 -
4. M FOA 12.11 (13.23) -.22* .15 .19* -
5. W Avoidance 2.67 (0.75) <.01 .03 .15 .06 -
6. M Avoidance 2.71 (0.79) .11 .07 .14 .09 .20* -
7. Time
2
12:35 (1:15) -.18† .04 .08 .08 -.04 .14 -
8. W Hours Awake 4.79 (1.32) -.35*** -.17† .22* .11 -.07 .16 .56*** -
9. M Hours Awake 4.95 (1.52) -.13 -.01 .08 .05 -.01 -.01 .63*** .59*** -
10. W Cotinine 5.38 (18.25) -.01 .28** .03 .05 <.01 .12 -.06 -.03 .10 -
11. M Cotinine 15.11 (68.06) .03 .04 -.02 .17† .02 <.01 -.01 .03 .14 .21* -
12. Months Together 29.93 (23.91) -.16 -.15 .02 .01 -.15 -.13 -.05 .15 .02 -.12 .14 -

Notes:
† p < .10; * p < .05; ** p < .01; *** p < .001
M = men’s, W = women’s, FOA = family of origin aggression, SD = standard deviation
Table includes continuous variables. Medication status is a dichotomous variable and therefore was not included.
1
Cortisol is the mean value for each participant across the 4 sampling occasions.
2
Here, time refers to time of day when the initial saliva sample was collected in each dyad, presented in hours and minutes. In multi-level structural
equation models testing hypotheses, this initial value is centered to zero and subsequent values are calculated in minutes since the initial
sampling time.

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 52
Table 2.

Multi-level actor-partner interdependence models testing effect of FOA and FOA*avoidance on cortisol intercept and slope.

Model 1 Model 2
F Intercept
b (SE)
F Slope
b (SE)
M Intercept
b (SE)
M Slope
b (SE)
F Intercept
b (SE)
F Slope
b (SE)
M Intercept
b (SE)
M Slope
b (SE)
Covariates
Hours awake
1
-.61 (.19) .07 (.11) .25 (.38) -.22 (.15) -.69 (.21) .05 (.12) .29 (.31) -.25 (.12)
Cotinine
1
<.01 (.01) .01 (<.01)† <.01 (<.01) <.01 (<.01) -.01 (.01) -.01 (.0a) .01 (.01) .01 (.01)
Medication
1
1.54 (.57)** -.62 (.27)* 1.51 (1.23) -.43 (.46) 1.43 (.60)* -.53 (.29)† 2.10 (1.08)† -.65 (.44)
Months together -.01 (.01) -.01 (.01) -.02 (.02) <.01 (.01) -.01 (.01) -.01 (.01) -.02 (.02) .01 (.01)
F FOA -.01 (.02) -.01 (.01) -.03 (.03) .01 (.01) -.01 (.02) -.01 (.01) -.05 (.03) .02 (.01)
M FOA -.03 (.02) -.01 (.01) .04 (.04) <.01 (.02) -.03 (.02) -.01 (.01) .03 (.03) .01 (.01)
F Avoidance - - - - -.12 (.39) -.04 (.18) -.02 (.59) -.01 (.20)
M Avoidance - - - - .68 (.39) -.03 (.19) .22 (.54) -.04 (.17)
F FOA*Avoidance - - - - -.01 (.02) .01 (.01) .08 (.04)* -.03 (.01)*
M FOA*Avoidance - - - - .03 (.02) .02 (.01)* .09 (.04)* -.02 (.01)**

Notes:
Level-2 variables used to compute interactions are grand mean centered; F = Female, M = Male
† p < .10; * p < .05; ** p < .01; *** p < .001
1. Models predicting female intercept and slope use female covariates; models predicting male intercept and slope use male covariates

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 53

Figure 1A. Actor-partner effects of FOA and avoidance on cortisol intercept.
γ01
δ02

γ05

γ02

δ01
δ05

δ03

δ06

δ04

Men’s
Intercept
γ03

Men’s
FOA
Women’s
FOA
Women’s
Avoidance
Women’s
Intercept
γ04
Men’s
Avoidance
γ06
4γ0
Figure 1B. Actor-partner effects of FOA and avoidance on cortisol slope.
γ11
δ12

γ15

γ
12

δ11
γ16
4γ0
δ15

δ13

δ16

δ14

Men’s
Slope
γ13

Men’s
FOA
Women’s
FOA
Women’s
Avoidance
Women’s
Slope
γ14
Men’s
Avoidance
Figure 1. Structural equation model describing level-2 actor and partner- effects. Hypothesis 1A
tests actor effects of FOA on cortisol intercept (γ01, δ 01) and slope (γ 11, δ 11) for men and women,
respectively. Hypothesis 1B tests partner effects of FOA for both men and women (γ02, γ12, δ 02,
δ12). Hypothesis 2A tests actor effects of the interaction of FOA and avoidance on cortisol
intercept and slope, separately for men (γ05, γ15) and women (δ05, δ15). Hypothesis 2B tests the
partner effects of these interactions (γ06, γ 16, δ 06, δ 16). To account for interdependence between
members of the same couple, residual correlations among all cortisol intercepts and slopes for
men and women were estimated but are not presented here due to space constraints.
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 54

Figure 2. Actor effects of male’s cortisol intercept (Figure 2A) and slope (Figure 2B) as a function of the interaction of male’s family
of origin aggression (FOA) and avoidance. High and low values of avoidance are 1 standard deviation above and below the mean.
FOA scores are mean-centered.
0
1
2
3
4
5
6
7
8
9
10
-10 0 10 20 30
Men's Cortisol Intercept Predicted Value
Men's Family of Origin Aggression
Figure 2A. Actor Effects of Men's FOA and Avoidance
on Men's Cortisol Intercept
Low Men's Avoidance Mean Men's Avoidance
High Men's Avoidance
-2.5
-2
-1.5
-1
-0.5
0
0.5
-10 0 10 20 30
Men's Cortisol Slope Predicted Value
Men's Family of Origin Aggression
Figure 2B. Actor Effects of Men's FOA and Avoidance
on Men's Cortisol Slope
Low Men's Avoidance Mean Men's Avoidance
High Men's Avoidance
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 55

Figure 3. Partner effects, displaying the interaction of one partner’s family of origin aggression (FOA) and avoidance on the other
partner’s HPA reactivity. Graphs represent the effect of female’s FOA and avoidance on male’s cortisol intercept (Figure 3A) and
slope (Figure 3B) and the effect of male’s FOA and avoidance on female’s cortisol slope (Figure 3C). High and low values of
avoidance are 1 standard deviation above and below the mean. FOA scores are mean-centered.
-2.5
-2
-1.5
-1
-0.5
0
0.5
-10 0 10 20 30
Men's Cortisol Slope Predicted
Value
Women's Family of Origin Aggression
Figure 3B. Partner Effects of Women's FOA and
Avoidance on Men's Cortisol Slope
Low Women's Avoidance
Mean Women's Avoidance
High Women's Avoidance
-2.5
-2
-1.5
-1
-0.5
0
-10 0 10 20 30
Women's Cortisol Slope Predicted
Value
Men's Family of Origin Aggression
Figure 3C. Partner Effects of Men's FOA and
Avoidance on Women's Cortisol Slope
Low Men's Avoidance Mean Men's Avoidance
High Men's Avoidance
0
5
10
-10 0 10 20 30
Men's Cortisol Intercept Predicted
Value
Women's Family of Origin Aggression
Figure 3A. Partner Effects of Women's FOA and
Avoidance on Men's Cortisol Intercept
Low Women's Avoidance
Mean Women's Avoidance
High Women's Avoidance
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 56
Appendix Table 1.

Satorra-Bentler Chi-Square Statistics and Fit Indices for Nested Structural Equation Models.

Model -LL Parameters LRT Δdf p AIC BIC

0. Baseline Model
1
-5366.09 38 - - - 10808.18 10963.82
1. Main effects FOA -5358.91 46 18.57 8 0.017 10809.83 10998.24
2. Main effects of FOA
and avoidance
-5357.52 54 2.52 8 0.961 10823.04 11044.22
3. Main effects FOA,
avoidance; FOA x
avoidance interactions
-5348.47 62 22.78 16 0.120 10820.93 11074.87
4. Main effects,
interactions, and
covariates
-5328.70 78 66.73 32 <0.001 10813.41 11132.88

Notes:
-LL = Negative Log Likelihood, Parameters = Number of Parameters included in model, LRT = Likelihood ratio test, Δdf = difference in parameters
between models being compared, p = significance value, AIC = Akaike information criterion, BIC = Bayesian Information Criterion.
1. Preliminary modeling indicated that covariances of female cortisol slopes with all other intercepts and slopes could be set to zero in the baseline
model.

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 57

Paper 3
Family-of-origin Aggression, Romantic Relationships, and Inflammation in Young Adulthood
Kelly F. M. Kazmierski & Gayla Margolin
University of Southern California

Author Note:
Funding for this study was provided, in part, by NIH NICHD R21HD072170 awarded to
Margolin, NSF Graduate Research Fellowship DGE-0937362 awarded to Kazmierski, and SC
CTSI (NIH/NCATS) through Grant UL1TR001855 awarded to Margolin. The authors would
like to thank the research participants and our USC Family Studies Project colleagues,
particularly Corey Pettit, Stassja Sichko, Yehsong Kim, Olivia Shin, and Merai Estafanous.

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 58
Abstract
Growing up in an aggressive family confers health risk life-long. However, less is known about
how the romantic relationships young adults form may contribute to trajectories from family of
origin aggression (FOA) to disease. The present study assesses whether health effects of FOA
can be detected as early as young adulthood in a community sample, whether hypothalamic-
pituitary-adrenal (HPA) axis reactivity during interactions with romantic partners mediates these
associations, and whether this risk mechanism depends on young adults’ levels of romantic
attachment avoidance. Eighty-five opposite sex couples reported on FOA and attachment
avoidance, engaged in dyadic interaction tasks while providing saliva samples to index HPA
reactivity, and had at least one partner complete a follow-up health visit. Inflammation was
indexed by two pro-inflammatory cytokines: interleukin-1β (IL-1β) and interleukin-6 (IL-6).
Results indicate that FOA is associated with greater IL-1β and IL-6 for men. The indirect effect
of men’s FOA on IL-1β through HPA reactivity was conditional on men’s levels of attachment
avoidance, such that greater FOA only conferred heightened reactivity for more avoidant men;
heightened reactivity, in turn, predicted greater IL-1β. Low attachment avoidance buffered men
from the total effect of FOA on IL-1β. No indirect or conditional indirect effects were detected
for men’s IL-6. No predictors were associated with women’s inflammation. By identifying how
attachment amplifies or attenuates risky health trajectories, we take an exploratory step toward
identifying how young adults’ relationships can serve both as a disease mechanism and as a
natural point of intervention.
Keywords: family aggression, inflammation, couples, HPA reactivity, attachment avoidance,
emerging adulthood
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 59
Family-of-origin Aggression, Romantic Relationships, and Inflammation in Young Adulthood
Close relationships have far-reaching consequences for health, such that social support
and connection predict wellness and longevity, whereas isolation and maltreatment confer risk
for morbidity and mortality (e.g., Danese et al., 2009; Holt-Lunstad, Smith, & Layton, 2010;
Pietromonaco & Collins, 2017). Family of origin aggression (FOA) is among the most
widespread interpersonal sources of health risk, with over 90% of American parents reporting
perpetration of behaviors intended to cause children physical or psychological pain (Straus,
2001; Straus & Field, 2003). Although FOA is common, families vary greatly in the severity and
chronicity of their aggression perpetration, which can include verbalizations, such as yelling,
threatening, or swearing at children, and actions, such as spanking, slapping, or shaking children.
Individuals who grow up in highly aggressive families are at increased risk for developing a
wide range of serious and chronic illnesses, such as cardiovascular disease, diabetes, arthritis,
and cancer (Felitti & Anda, 2009; Moffitt, 2013; Wegman & Stetler, 2009; Widom, Czaja,
Bentley, & Johnson, 2012). However, questions remain regarding both how soon relationships
between FOA and health markers emerge in community samples and how adults’ subsequent
romantic relationships may contribute to or alter trajectories from FOA to disease (e.g.,
Fagundes, Bennett, Derry, & Kiecolt-Glaser, 2011).
The present study examines associations between FOA exposure and immune-mediated
inflammation, a health marker that has been linked to the development of a wide range of
diseases (e.g., Michaud et al., 2013). We assess these associations during young adulthood, a
developmental period in which divergence in health markers emerges but the full impact of
inflammation-related disease is not yet felt (Bonnie, Stroud, & Breiner, 2015). Next, we examine
whether physiological reactivity in the context of young adults’ romantic relationships mediates
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 60
associations between FOA and inflammation. We submit that childhood FOA exposure confers
sensitized physiological reactivity to interpersonal stress, and that romantic relationships provide
critical contexts in which these patterns of reactivity may be repeated, creating ongoing wear-
and-tear to bodily systems even after the stress of FOA has passed. However, romantic
relationships also provide opportunities to develop new patterns of interpersonal physiological
reactivity, based in part on mental representations of romantic relationships. Therefore, we
examine whether romantic attachment avoidance moderates paths from FOA to sensitized
reactivity during emotionally intimate interactions, to amplify or disrupt the proposed
mechanism of health risk.
Stress and Inflammation.
In response to stress, the body triggers the “fight or flight response,” which includes
activation of both the autonomic nervous system (ANS) and hypothalamic-pituitary adrenal
(HPA) axis. The sympathetic branch of the ANS produces rapid changes to physiology, which
include greater blood flow to essential organs and skeletal muscles, increased heart rate, dilation
of lung bronchioles, and activation of the inflammatory response (Steptoe, Hamer, & Chida,
2007). Inflammation is an adaptive response to acute stress, which helps the body heal wounds
and fight infections that may be incurred as a result of threatening stimuli. The release of
catecholamines (epinephrine and norepinephrine) trigger innate immune cells (e.g., lymphocytes
and macrophages) to increase production of pro-inflammatory cytokines, such as interleukin-1β
(IL-1β) and interlukin-6 (IL-6), which enhance inflammation by signaling the release of
additional immune cells. Concurrently, stress activates the HPA axis, triggering a cascade of
neuropeptides, the end result of which is cortisol. Cortisol binds to receptors on innate immune
cells to signal inhibition of their production of proinflammatory cytokines, providing a negative
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 61
feedback mechanism by which stress-induced inflammatory responses reduce or cease as the
stressor passes (Barnes, 1998; Brattsand & Linden, 1996). Although inflammation is an adaptive
response to stress in the short-term, chronic inflammation damages healthy tissue, contributing to
the development of a wide range of diseases, including heart disease, diabetes, dementia, and
cancer (e.g., Allin & Nordestgaard, 2011; Danesh et al., 2004; Engelhart et al., 2004; Pradhan,
Manson, Rifai, Buring, & Ridker, 2001), and incurring risk for earlier all-cause mortality
(Proctor et al., 2015).
Exposure to repeated stress, such as FOA, during childhood is thought to increase risk for
chronic inflammation in adulthood via allostatic adaptation, the process by which the body
modifies its basal functioning in response to environmental demand (McEwen, 1998). Each
stress-induced HPA activation exposes innate immune cells to a flood of glucocorticoids.
Repeated or prolonged cortisol exposure contributes to glucocorticoid insensitivity at immune
cell receptor sites, reducing the body’s ability to terminate the pro-inflammatory response and
initiate the anti-inflammatory response (Hänsel, Hong, Camara, & vok Känel, 2010; Miller,
Cohen, & Ritchey, 2002). Repeated stress responses also create wear-and-tear to the HPA axis,
reducing the body’s ability to flexibly calibrate cortisol levels to meet environmental demand,
leading to higher and less variable cortisol rhythms between acute stress exposures (Miller,
Chen, & Zhou, 2007). Therefore, ongoing stress likely contributes to chronic inflammation first
because stress-induced cortisol elevations lead to glucocorticoid resistance and then because
allostatic adaptation of the HPA axis extends risky patterns of glucocorticoid exposure between
episodes of acute stress. In line with this allostatic mechanism, individuals exposed to chronic
stress exhibit resistance to the anti-inflammatory properties of cortisol (Cohen et al., 2012),
which can be observed as early as adolescence (Ehrlich, Miller, Rohleder, & Adam, 2016).
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 62
Greater glucocorticoid resistance has been causally linked to adults’ greater production of IL-1β
and IL-6 (Cohen et al., 2012).
Family of Origin Aggression and Inflammatory Health
Stressful experiences in the family of origin incur risk for elevated inflammation, both
concurrently and longitudinally. Major adverse experiences and harsh family environments have
been linked to greater chronic systemic inflammation during childhood and adolescence (Miller
& Chen, 2010; Slopen & Kubzansky, 2012), particularly for those who also meet clinical
thresholds for depression (Danese et al., 2011). However, a systematic review noted that
inflammatory effects of early stress are not consistently detected among youth (Slopen, Koenen,
& Kubzansky, 2013).
Maltreated children continue to show elevated inflammation in adulthood. For instance,
adults who experienced multiple childhood adversities (Danese, Pariante, Caspi, Taylor, &
Poulton, 2007), who have been abused or neglected in childhood (Matthews, Chang, Thurston, &
Bromberger, 2014), or who report being raised in harsh family environments (Taylor, Lehman,
Kiefe, & Seeman, 2006) exhibit higher inflammation, as indexed by C-reactive protein (C-RP),
an acute-phase protein whose release is induced by IL-1β and IL-6 (Eklund, 2009). Associations
between childhood maltreatment and adult inflammation can persist for decades, with adversity
in the family of origin predicting higher levels of pro-inflammatory cytokines even among older
adults (Kiecolt-Glaser et al., 2011). However, effects of childhood maltreatment on inflammation
are also only inconsistently detected among adults (e.g., Coelho, Viola, Walss-Bass, Brietzke, &
Brassi-Oliveira, 2014; Palmos et al., 2019).
Notably, literature linking stress exposure in the family of origin to adults’ inflammatory
health typically assesses the impact of major childhood maltreatment, such as physical or sexual
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 63
abuse (e.g., Matthews et al., 2014). When less severe sources of family stress are assessed, they
are often collapsed into a single scale, alongside either more severe forms of adversity or
stressors that may have occurred outside of family relationships (e.g., Danese et al., 2007;
Matthews et al, 2014), leading a recent meta-analysis to note that collapsing myriad forms of
childhood adversity into combined measures rather than focusing on specific forms of
maltreatment poses a major limitation of the adversity-inflammation literature (Coelho et al.,
2014). Therefore, although the health impacts of major childhood interpersonal adversity, such
as overall violence exposure, are relatively well-established (e.g., Moffitt, 2013), the distinct
effects of more commonly-occurring interpersonal stressors, such as FOA, remain largely
untested. However, existing research suggests that more common forms of family adversity, such
as parental separation and low parent-child relationship quality, can yield risky inflammatory
profiles in adulthood (e.g., Lacey, Kumari, & McMunn, 2013). To our knowledge, no study has
assessed the discrete effect of FOA on inflammation.
Might Reactivity in Romantic Relationships Link FOA to Inflammation?
While early aggressive family relationships confer distal risks, physiological reactivity
within romantic relationships may be an important, albeit largely overlooked, proximal
mechanism linking FOA to disease. However, research rarely accounts for simultaneous effects
of proximal and distal relationship experiences on inflammatory health (Fagundes et al., 2011).
Childhood maltreatment is typically posited to lead to chronic inflammation insofar as it
evokes concurrent activation of the stress response system with each stress exposure. As
aggression is chronic within families (Straus & Field, 2003), FOA yields repeated physiological
activations that create allostatic adaptation during childhood, increasing inflammation by
reducing children’s sensitivity to glucocorticoids (e.g., Ehrlich et al., 2016) during sensitive early
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 64
periods of development (Miller, Chen, & Parker, 2011). However, FOA-exposed young adults
continue to face challenging interpersonal situations, even after the stress of childhood
aggression exposure has passed. How young adults physiologically respond to current
emotionally salient interpersonal interactions with dating partners may also play a role in linking
childhood FOA-exposure to adult health.
Conflict sensitization theories (Cummings & Davies, 1996; Davies & Woitach, 2008;
Grych & Fincham, 1990) submit that individuals who grow up in aggressive families are more
likely to perceive threat and respond with increased emotional and behavioral reactivity during
interpersonal interactions; we have recently proposed that this conflict sensitization extends to
altered physiological reactivity, which is domain-specific to interpersonal interactions (Margolin,
Ramos, Timmons, Miller, & Han, 2016), such that some individuals from aggressive families
display sensitized patterns of physiological response during emotionally vulnerable interactions
in adulthood (Kazmierski, Beam, & Margolin, 2019). Continuing to display patterns of
heightened interpersonal reactivity incurs ongoing, rather than merely distal, wear and tear on
bodily systems, which may partially account for links between FOA and health (Miller et al.,
2011). Therefore, we propose that physiological reactivity during interactions with dating
partners may act as a mediator, such that childhood FOA influences adult inflammation by
producing ongoing physiological hits in response to adults’ current relationships.
To our knowledge, no study has tested adults’ physiological reactivity to interpersonal
interactions as a mediator of early adversity’s effect on inflammation. However, young adults’
romantic relationship quality has been supported as a mechanism linking harsh parenting in
childhood to inflammation in adulthood (Beach et al., 2017), a finding that is consistent with
childhood adversity jeopardizing adult health in part by initiating cascades of social stress that
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 65
amplify chronic inflammation (Miller et al., 2011). Deleterious romantic relationship qualities
such as hostility, strain, low support, and low satisfaction, are well-established sources of risk for
increased acute and chronic inflammation (Donoho, Crimmins, & Seeman, 2013; Friedman et
al., 2005; Kiecolt-Glaser at al., 2005; Uchino et al., 2013; Whisman & Sbarra, 2012; Yang,
Schorpp, & Harris, 2014), presumably because these qualities elicit physiological stress
reactivity during interactions (Robles & Kiecolt-Glaser, 2003). Emerging research supports that
physiological reactivity within romantic relationships influences inflammatory health; for
instance, one recent study found direct effects of couple’s ANS synchrony on inflammation, such
that couples who show greater linkage in heart rate variability during conflict also exhibit higher
levels of pro-inflammatory cytokines (Wilson et al., 2018). The direct effects of HPA activity on
inflammation are less clear, however. Generally, lower or less variable diurnal patterns of HPA
activity are associated with greater inflammation (e.g., DeSantis et al., 2012; Edwards, Bosch,
Engeland, Cacioppo, & Marucha, 2010; Hostinar, Lachman, Mroczek, Seeman, & Miller, 2015;
Jaremka et al., 2013); however, the literature is inconsistent regarding what pattern of acute
cortisol stress reactivity is associated with inflammation (e.g., Bick et al., 2015; Edwards et al.,
2010; Hamer, O’Donnel, Lahiri, & Steptoe, 2009; Laurent, Lucas, Pierce, Goetz, & Granger,
2016). Mixed findings may be due to allostatic adaptation of the HPA axis, such that lower levels
of HPA activity endow risk insofar as they are the result of a history of acute HPA activations
(Miller et al., 2007). Notably, to our knowledge, no study linking HPA activity to chronic
inflammation has measured HPA response in the context of participants’ romantic relationships.
Attachment Avoidance as a Moderator of Risk Mechanisms
Although romantic relationships may provide opportunities for FOA to exert ongoing
stress on physiology, HPA reactivity is not determined by family history alone. Rather, distal and
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 66
proximal interpersonal characteristics interact to determine HPA response to social stress. For
instance, the effects of family adversity on HPA activity during married couples’ conflict
discussions depend on qualities of the current relationship, such as partner’s aggression (Arbel,
Rodriguez, & Margolin, 2016) or negative conflict behaviors (Winer, Powers, Pietromonaco, &
Schreck, 2018). Similarly, in an overlapping sample to that used in the present study, we recently
found that FOA only heightened HPA reactivity during dyadic interactions for young adults who
are higher in romantic attachment avoidance (Kazmierski et al., 2019). Building on these
findings, we propose that attachment avoidance may either amplify or disrupt trajectories from
FOA to inflammation by moderating associations between FOA and physiological reactivity.
Romantic attachment guides how adults think and behave in close relationships (Hazan &
Shaver, 1987). Adults hold experience-based mental models of attachment, which include
implicit expectations about how available and responsive relationship partners are likely to be;
these mental models guide how and whether adults turn to partners to regulate stress (Bowlby,
1969/1982). Individual differences in adult attachment are described along two orthogonal
dimensions: anxiety, fear of rejection and abandonment by partners, and avoidance, discomfort
with intimacy and inter-dependence in relationships (Brennan, Clark, & Shaver, 1998).
Attachment shapes how adults appraise social situations (e.g., Collins & Feeney, 2004), such that
more avoidant adults interpret intimate, emotionally vulnerable interactions as more threatening
(Simpson & Rholes, 1994) and use de-activating strategies to shift attention away from emotion
and relationship needs (Brennan et al., 1998).
Attachment avoidance may intensify the effects of FOA on physiology by heightening
the perceived stressfulness of emotionally intimate or vulnerable dyadic interactions. Vulnerable
interactions, such as disclosing painful emotions or experiences, are common and generally
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 67
salubrious in romantic relationships (Laurenceau, Barrett, & Rovine, 2005; Lippert & Prager,
2001). However, for high-avoidance young adults, interpreting emotionally vulnerable
interactions as threatening may activate FOA-induced sensitized physiological reactivity to
interpersonal conflict (Kazmierski et al., 2019; Margolin et al., 2016), inducing repeated HPA
activations in the context of present relationships and incurring greater wear to inflammatory
health. In contrast, low attachment avoidance may protect young adults from the effects of FOA
on inflammation by reducing HPA reactivity in present relationships. Less avoidant young adults
are comfortable turning to their relationship partners to regulate emotion (Brennan et al., 1998).
Through such interactions, less avoidant young adults may acquire new social learning that
reduces conflict sensitization and promotes more adaptive patterns of physiological response.
When current relationships do not evoke chronic HPA activations, not only are young adults
protected from the repeated blows of proximal allostatic wear-and-tear but also their immune
systems may be able to recover from allostatic load incurred in childhood. Research suggests that
stress-induced inflammation can abate once the stressor has passed; for instance, reductions in
depressive symptoms yield reductions in inflammation (Thornton, Anderson, Schuler, & Carson,
2009). Similarly, if current relationships do not evoke repeated glucocorticoid exposure, young
adults may recover sensitivity to cortisol’s inhibitory effect on inflammation, reducing chronic
inflammatory levels. Therefore, we propose that the indirect effect of FOA on inflammation
through HPA reactivity may be conditional on attachment avoidance, such that young adults who
form more secure relationships are protected from FOA-induced inflammation.
The Current Study
The present study examines the effect of FOA on young adults’ immune-mediated
inflammation; inflammation is indexed by circulating levels of two pro-inflammatory cytokines
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 68
that have previously been associated with childhood maltreatment: IL-1β and IL-6 (Coelho et al.,
2014; Miller et al., 2011). We predict that greater childhood FOA will be associated with greater
systemic inflammation in young adulthood (Hypothesis 1). We then examine HPA response
during dyadic interactions as a mediator of FOA’s effect on inflammation, predicting that
ongoing physiological reactivity to proximal interpersonal stimuli is a mechanism by which FOA
influences health (Hypothesis 2). HPA reactivity is indexed by participants’ change in cortisol
over time (cortisol slope) during a series of dyadic interaction tasks that elicit interpersonal
emotional vulnerability, with flatter slopes indicating less HPA response to interaction tasks and
steeper slopes indicating greater HPA response to interaction tasks. Finally, we assess whether
indirect effects of FOA on inflammation through HPA reactivity are conditional on young
adults’ attachment avoidance. We predict that for highly avoidant adults, FOA will confer
sensitized HPA reactivity that in turn increases risk for systemic inflammation, but that these
effects will be buffered for less avoidant adults (Hypothesis 3). As gender differences are
commonly observed in pathways from relationships to health (Kielcolt-Glaser & Wilson, 2017),
all hypotheses will explore differences between male and female partners.
Methods
Participants
Participants were opposite-sex couples who completed a lab visit that included reporting
on childhood FOA, completing dyadic interaction procedures, and providing saliva samples for
cortisol assay. To be included in the present study, at least one member of the couple also had to
return to the lab for a follow-up visit, which included provision of a dried blood spot (DBS)
sample for assay of pro-inflammatory cytokines. Of the 112 couples (224 individuals) who
completed in-lab procedures, 129 individuals (69 women, 60 men) from 85 couples completed
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 69
the follow up visit; both partners completed the follow-up assessment in 52% of couples.
Comparisons did not reveal significant differences in demographic or study variables between
participants who completed the follow-up visit and those who did not, with one exception: men
who completed the follow-up health visit were older than those who did not, t(105.509) = -1.187,
p = .025.
Participants included young adults drawn from a longitudinal study of the
intergenerational transmission of family aggression, who were in a dating relationship for at least
2 months at the time of lab visit (N = 24 couples). Additional couples (N = 61 couples) were
recruited from the community to demographically match returning participants; newly recruited
participants had to be 18-25 years old, in a relationship for 2 months or longer, and able to
complete procedures in English. At lab visit, participants were in their early twenties (Mmen =
23.3; M women = 22.3) and together for an average of 31 months (range = 2-109 months), with 43%
of participants cohabiting. Participants were diverse in terms of race/ethnicity (12.5% Asian,
14.8% African American/Black, 28.4% Non-Hispanic White, 25.0% Hispanic/Latino, 16.5%
Multi-Racial, and 2.8% Other). Most participants worked (41.5% employed), went to school
(17.0% students), or both worked and went to school (40.3% working students).
Procedures
All procedures were approved by the University of Southern California University Park
Institutional Review Board. Data were collected in two waves: an initial lab visit and a follow-up
health visit.
Initial visit procedures. Both members of each couple attended the initial lab visit.
Participants completed a series of questionnaires prior to the visit, administered online via
Qualtrics. To reduce variability in salivary cortisol, all initial lab visits were scheduled to begin
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 70
between 10 A.M. and 1 P.M., and participants were instructed not to eat, drink, or chew gum for
one hour prior to the visit, nor to brush their teeth for three hours prior, nor to consume alcohol
or use tobacco for 24 hours prior. In lab, participants provided informed consent regarding all
study procedures, completed interactions with concurrent physiological assessments, and
answered questionnaires.
Interaction procedures. During the visit, participants completed a series of dyadic
interaction tasks, which included a relaxation period, a series of discussions, and a recovery task.
During the 15-minute relaxation period, participants watched a nature video. Participants then
completed a series of four discussions: date planning (5 min), desired areas of relationship
change (10 min), and loss (2 discussions, 10 min each). Discussions were designed to focus on
topics that elicit emotional vulnerability; participants met with experimenters separately before
change and loss discussions to select the most emotionally salient topics. Discussion procedures
are described in detail by Kazmierski et al. (2019). During the recovery period, participants were
asked to “unwind” by jointly building and decorating a construction paper tower, using provided
art supplies.
Saliva collection procedures. Participants in each couple simultaneously provided 0.4
mL of saliva via passive drool at four points during the interaction tasks: following relaxation,
the change discussion, the second loss discussion, and the recovery period. Study procedures
were timed such that approximately 2 hours passed between the initial and final saliva sample
collection. Samples were immediately stored in a -80° C deep freezer for later cortisol assay by
the Dresden LabService GmbH.
Follow-up visit procedures. Participants could elect to complete the follow-up health
visit either at home or in-lab. Health visits followed lab visits by an average of 18.7 months (SD
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 71
= 7.59 months, range = 10.5-46.2 months). During health visits, participants provided a DBS
sample, which involved a finger prick to release 2-3 drops of blood onto filler paper. DBS
samples were stored in HemaSpot-HF protective cartridges. Initial samples were stored at room
temperature before being refrigerated at approximately 4° C; later samples were immediately
stored at 4° C. Samples were shipped at ambient temperature for assay at the Applied Physiology
Laboratory at the University of North Texas.
Measures
Family of origin aggression. Participants reported FOA before the initial lab visit, using
the parent-child conflict scale (modified from the Conflict Tactics Scale; Straus, Hamby,
Finkelhor, Moore, & Runyan, 1998, alpha = .91). Participants completed 14 items assessing how
often parents engaged in aggressive behaviors towards them out of anger at any point during
childhood, using a 5-point scale (0 = Never, 4 = more than 6 times). Eight items measured
psychological aggression (e.g., “Insulted you or told you that you were not good enough or that
you are a failure,”) and six items measuring physical aggression (e.g., “Pushed, grabbed, or
shoved you,”). FOA was computed by computing the sum of the 14 items. Most participants
(86%) reported having experienced at least some parent-to-child aggression.
Avoidance. Attachment avoidance was assessed in lab, via the Experiences in Close
Relationships-Revised Questionnaire (ECR-R; Fraley, Waller, & Brennan, 2000, alpha = .90).
Participants responded to 36 items measuring attachment anxiety and avoidance, using a 7-point
Likert scale (1 = Strongly disagree, 7= Strongly agree). Avoidance scores were computed as the
mean of 18 items measuring discomfort with emotional intimacy and reliance on others (e.g., “I
don't feel comfortable opening up to romantic partners,” and “I find it difficult to allow myself to
depend on romantic partners”).
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 72
HPA reactivity. To index HPA activity, salivary cortisol concentration was measured
using high-sensitivity immunoassay. Assay reliability was established by assaying 31% of
samples in duplicate (inter-assay correlation r = .99, p <.001); the initial assay value was used for
all analyses. Cortisol values greater than three standard deviations above the mean at each
sampling point (2.5% of all samples) were reduced to three standard deviations above the mean,
using the full sample of participants who completed initial in-lab procedures. Sampling time was
recorded as minutes elapsed since the first sampling point (time of first sample was centered at
0). HPA reactivity was modeled as the effect of time on cortisol (cortisol slope) across the four
cortisol sampling points, with steeper cortisol slopes indicating greater reactivity.
HPA-related covariates. Each participant’s initial saliva sample was assayed for
cotinine, a biproduct of nicotine; cotinine was entered as a continuous covariate to adjust for the
influence of tobacco use on salivary cortisol (Granger et al., 2007). As cortisol follows a diurnal
pattern which includes an increase upon awakening and decline throughout the day (Edwards,
Evans, Hucklebridge, & Clow, 2001), participants reported their time of awakening, and the
number of hours elapsed between awakening and the initial saliva sample was calculated for
each participant. Participants reported whether they used any contraceptive, steroid, and
stimulant ADHD medications, which influence HPA activity (Granger, Hibel, Fortunato, &
Kapelewski, 2009); 47% of women and 26% of men reported using at least one of these
medications. Medication use was dummy-coded (0 = no medication, 1 = medication).
Inflammation. Two pro-inflammatory cytokines were assayed from DBS samples: IL-1β
and IL-6. DBS samples were removed from the Hemaspot kit using aseptic technique, mixed
with an ammonium bicarbonate buffer (500 µL; 100 mM solution), vortexed, and placed on an
orbital shaker (1,000 RPM for 45 min) before the liquid was extracted by pipet for analysis. IL-
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 73
1b and IL-6 were measured in duplicate using a commercially available, high-sensitivity bead-
based kit (MilliporeSigma Catalog# HSTCMAG288PMX21) and the mean value was reported.
The intra-assay coefficient of variability was < 5% for both outcomes. After processing
according to assay guidelines, median fluorescent intensity of the known standards and unknown
DBS samples were measured using an automated analyzer (Luminex FlexMap 3D). A standard
curve was generated according to manufacturer guidelines and the concentrations in the
unknowns (i.e., DBS samples) were calculated. Cytokines were measured in picograms per
milliliter (pg/ml); values for each cytokine were log-transformed to address skewness.
Recovery and stability of cytokines in DBS samples. Spike recovery experiments were
used to test the ability to elute proteins from the DBS paper. Blood samples were spiked with
cytokine standards from the Luminex assay kit and then stored in the refrigerator. Spiked-DBS
samples were eluted using the same method described above and the expected cytokine
concentration (amount spiked into the sample) was compared to the recovered concentration.
Values were adjusted for relevant dilution factors and the recovery percentage was calculated by
comparing expected and measured cytokine concentrations. The calculated recovery was 92%
for 1b and 96% IL-6. In order to test the stability of DBS samples stored at room temperature
versus those that were immediately refrigerated, six samples were created in the laboratory, half
of which were stored in the refrigerator (4°C) for 14-days until analysis and half of which were
stored at room temperature (24°C). Samples were tested for analyte concentration using the
method described above. Stability was calculated by comparing the refrigerated samples to those
stored at ambient temperature. The calculated stability for the cytokine targets was 88-89%.
Demographic information. Participants reported their age, gender, self-identified
racial/ethnic background, employment and/or student status, current relationship duration, and
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 74
cohabitation status.
Analytic Plan
We tested hypotheses using multi-level structural equation models to account for
interdependence between dating partners and for the nested structure of repeated cortisol
measurements within person. Analyses were conducted in Mplus 8.0 (Muthén & Muthén, 1998-
2017), using Bayesian parameter estimates (Wang & Preacher, 2015), which utilize a full
information estimation approach to handle missing data under the missing at random assumption
(Schafer, 1997). We used a two-level data structure to organize repeated cortisol measurements
and sampling times for each partner in long format and partners within each dating couple in
wide format (Laurenceau & Bolger, 2012). Preliminary analyses did not support that time had a
curvilinear effect on cortisol reactivity; rather, most participants (75% of women and 80% of
men) showed decreases in cortisol across the interaction tasks.
In the multi-level portion of our model, we calculated the effect of time on cortisol
(cortisol slope) at level 1, in simultaneous equations for men and women. The following
equations represent level 1 of our model:
Maleit = α0i + α1i(timeit) + eit (1)
Femaleit = β0i + β1i(timeit) + fit (2)
In equations 1 and 2, Maleit and Femaleit model partner i's cortisol value at time t, which
is a function of an individual-specific intercept (α0i for men and β0i for women), slope (α1i, β0i),
and residual score (eit, fit). Level 1 equations were used to extract factor scores describing cortisol
slope, which were used in the level-2 structural equation portion of our models.
At level 2, we estimated the effects of variables that vary within but not between
participants (FOA, attachment avoidance, covariates) on inflammatory markers using structural
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 75
equation modeling. Level-2 covariates include participant age, relationships duration, and
variables that influence cortisol (medication use, salivary cotinine concentration, and hours since
awakening). Figure 1 represents the structural equation portion of our model. Separate models
were used to test effects of predictors on IL-1β and IL-6. Effects for males and females were
assessed simultaneously in each model, and residual correlations were estimated between men’s
and women’s variables in order to account for interdependence between members of the same
couple. Hypotheses were tested hierarchically, such that Hypothesis 1 tested the effects of FOA
on inflammation without simultaneously accounting for hypothesized indirect effects (Figure 1
paths cm and cf only). Hypothesis 2 was tested by adding indirect effects (Figure 1 paths a1m and
bm for men; paths a1f and bf for women) and testing the significance of the product of the a1 and
b pathways. Paths c’m and c’f display the direct effects of FOA on avoidance after accounting for
indirect effects. To test conditional indirect effects (Hypothesis 3), interaction scores were
calculated as the product of grand-mean centered FOA and avoidance values, and the effects of
FOA by avoidance interactions on cortisol slope were assessed (Figure 1 paths a3m and a3f). An
index of moderated mediation was computed as the interaction of a3 and b1 pathways (Hayes,
2015); when moderated mediation was supported, conditional indirect effects were assessed as
the sum of the product of the a1 and b1 pathways and the product of the a3 and b1 pathways at
high (1 SD above the mean), mean, and low (1 SD below the mean) levels of attachment
avoidance. Total effects of FOA on inflammation at high, mean, and low values of attachment
avoidance were calculated as the sum of each of these conditional indirect effects and the direct
effect. Conditional indirect effect size was calculated as the proportion mediated (ratio of
conditional indirect effect to conditional total effect) at a given level of the moderating variable.
Models were estimated using Bayesian methods, which treat parameters as random
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 76
values and data as fixed observations, in order to obtain posterior probability density
distributions of parameters using Markov chain Monte Carlo (MCMC) methods (Wang &
Preacher, 2015). Bayesian estimation yields point estimates of effects, posterior standard
deviations, and non-symmetric 95% credible intervals (CI) by iteratively drawing from the full
distribution of all parameters. When CIs do not contain 0, effects are considered statistically
significant. Bayesian mediation models have greater power to detect indirect effects than do
maximum likelihood methods; results are comparable to bootstrap CI methods for detecting
indirect effects (Preacher, Rucker, & Hayes, 2007; Wang & Preacher, 2015). Model fit was
assessed using the Deviance Information Criterion (DIC) statistic, with lower values representing
better model fit.
Results
Descriptive Statistics and Correlations
Table 1 presents the means, standard deviations, and correlations among all variables.
Differences between men and women were compared using t-tests, which support that male
participants have higher IL-1β, t(45) = -3.756, p <.001, and higher initial cortisol values, t(84) =
-2.385, p = .019. Correlations demonstrate positive associations between women’s IL-1β and IL-
6. Men’s FOA was marginally associated with their own greater IL-1β. Men’s and women’s
FOA and initial cortisol values were positively associated.
Hypothesis 1
In partial support of Hypothesis 1, effects of FOA on inflammation were observed in the
expected direction for both pro-inflammatory cytokines (IL-1β and IL-6) for men, but no effects
were observed for women. Step 1 of Table 2 presents main effects of FOA on IL-1β and IL-6 for
both men and women. Among men, growing up in an aggressive family was associated with
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 77
greater levels of IL-1β (path c, b = 0.025, SD = 0.013, CI = 0.002, 0.049) and IL-6 (path c, b =
0.006, SD = 0.003, CI = 0.001, 0.011). Among women, growing up in an aggressive family was
not associated with increased systemic inflammation as indexed by either cytokine (IL-1β: b =
0.010, SD = 0.012, CI = -0.014, 0.033; IL-6: b = -0.002, SD = 0.003, CI = -0.010, 0.004).
Hypothesis 2
Hypothesis 2 was not supported. As shown in Table 2, no significant indirect effects were
detected to support the hypothesis that cortisol reactivity mediates associations between FOA
and inflammation for men (IL-1β: b = 0.006, SD = 0.009, CI = -0.012, 0.028; IL-6: b = <0.001,
SD = 0.001, CI = -0.003, 0.002) or women (IL-1β: b = 0.007, SD = 0.029, CI = -0.028, 0.085; IL-
6: b = -0.001, SD = 0.005, CI = -0.013, 0.005). Notably, men’s FOA had a positive total effect on
IL-1β (b = 0.032, SD = 0.015, CI = 0.002, 0.060) and men’s steeper negative cortisol slopes were
associated with greater IL-1β (path b, b = -0.580, SD = 0.221, CI = -1.054, -0.156); however,
men’s FOA did not exert a statistically significant effect on cortisol slope (b = -0.011, SD =
0.015, CI = -0.042, 0.018).
Hypothesis 3
In partial support of Hypothesis 3, conditional indirect effects were observed for men’s
IL-1β (index of moderated mediation: b = 0.019, SD = 0.012, CI = 0.002, 0.045). As shown in
the left panel of Table 3, men’s FOA and attachment avoidance interacted to affect their cortisol
slopes (path a3: b = -0.033, SD = 0.015, CI = -0.061, -0.006), such that men’s FOA predicted
steeper negative cortisol slopes for those with high avoidance (+1 SD: b = -0.039, SD = 0.018, CI
= -0.078, -0.007) but not for those with moderate or low avoidance (mean: b = -0.013, SD =
0.013, CI = -0.040, 0.008; -1 SD: b = 0.011, SD = 0.017, CI = -0.020, 0.042). Steeper negative
cortisol slopes predicted greater IL-1β (path b: b = -0.646, SD = 0.229, CI = -1.078, -0.143).
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 78
Therefore, the conditional indirect effect of FOA on IL-1β through steeper negative cortisol
slope was observed for men who were high in avoidance (+1 SD: b = 0.025, SD = 0.04, CI =
0.001, 0.059) but not for men who endorsed moderate or low levels of avoidance (mean: b =
0.008, SD = 0.009, CI = -0.005, 0.029; -1 SD: b = -0.007, SD = 0.012, CI = -0.030, 0.017). Once
this conditional indirect effect was accounted for, the direct effect of FOA on IL-1β no longer
reached statistical significance (path c’: b = 0.024, SD = 0.013, CI = -0.002, 0.049). Total effects
of FOA on avoidance, which account for both direct and indirect effects, were significant at high
and moderate levels of avoidance (+1 SD: b = 0.050, SD = 0.019, CI = 0.015, 0.091; mean: b =
0.032, SD = 0.015, CI = 0.002, 0.064), but not at low levels of avoidance (-1 SD: b = 0.016, SD
= 0.140, CI = -0.019, 0.051). The detected indirect effect accounted for 51% of the total effect of
FOA on IL-1β for highly avoidant (+1 SD) men (PM = 0.509, SD = 0.273, CI = 0.078, 1.116).
Conditional indirect effects were not supported for men’s IL-6 (index of moderated
mediation: b = -0.001, SD = 0.002 CI = -0.006, 0.003) nor for either marker of women’s
inflammation (IL-1β index of moderated mediation: b = 0.002, SD = 0.010, CI = -0.015, 0.024;
IL-6 index of moderated mediation: b = <0.001, SD = 0.002, CI = -0.003, 0.005).
Discussion
The present study examined the effects of FOA on inflammation in young adulthood and
evaluated whether physiological reactivity within young adults’ romantic relationships links
FOA to inflammatory health. Findings support that for men, growing up in a more aggressive
family is associated with higher chronic inflammation, as indexed by two pro-inflammatory
cytokines (IL-1β and IL-6). HPA reactivity during dyadic interactions was then tested as a
mechanism underlying associations between childhood FOA and adult inflammation. This
mediation model was only supported when attachment avoidance was also accounted for: the
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 79
indirect effect of men’s FOA on IL-1β through HPA reactivity was conditional on men’s levels
of avoidance, such that reactivity linked FOA to greater inflammation for highly avoidant men,
but no statistically significant total effects of FOA on IL-1β were detected for men who are low
in avoidance. No mediation or moderated mediation models were supported for men’s IL-6, and
no hypothesized effects were observed for either marker of women’s inflammation.
Results provide initial evidence that levels of parent-to-child aggression observed in the
community influence inflammation during emerging adulthood. Although major forms of
maltreatment have been shown to exert effects on inflammatory health both concurrently (e.g.,
Miller & Chen, 2010; Slopen & Kubzansky, 2012) and decades later (e.g., Danese et al., 2007;
Kiecolt-Glaser et al., 2011; Matthews et al, 2014), the present study contributes to a growing
body of literature suggesting that even commonly-occurring forms of family adversity can
contribute to chronic inflammation (e.g., Beach et al., 2017; Lacey et al., 2014). FOA-linked
differences in inflammatory health were detectable among men even in our young and generally
physically healthy community sample. Given the high prevalences of aggression among
American parents (Straus & Field, 2003) and of inflammation-related diseases among American
adults (Merrill, Kessler, Udler, Rasband, & Feuer, 1999), reducing children’s FOA exposure may
belong in the canon of disease prevention targets, alongside diet, exercise, and stress reduction,
that protect health life-long.
Building on evidence that adult relationships contribute to trajectories from childhood
adversity to adult disease (e.g., Beach et al., 2017; Miller et al., 2011), the present study is the
first to test whether HPA reactivity within proximal relationships mediates associations between
FOA and inflammation. Findings provide tentative support for a nuanced view of this
mechanism, which requires accounting for both proximal interpersonal characteristics and distal
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 80
interpersonal experiences. For young men who are high in attachment avoidance, FOA confers
sensitized HPA reactivity during emotionally vulnerable dyadic interactions; this pattern of
reactivity, in turn, predicts greater levels of IL-1β approximately 1.5 years later. Once this
mechanism is accounted for, the direct effects of men’s FOA on IL-1β are no longer statistically
significant. For highly avoidant men, this indirect effect accounts for half of the total effect of
FOA on IL-1β, suggesting that the health consequences of FOA are incurred not only from the
direct physiological toll of childhood stress exposure, but also from FOA’s lingering effect on
young adults’ physiological responses to their current interpersonal worlds. Among men who are
not comfortable disclosing to or depending on romantic partners, HPA reactivity during
emotionally intimate interactions may act as a disease mechanism that contributes to the
development of inflammatory illness decades after FOA exposure. This proximal mechanism
helps account for the “surprisingly durable,” effects of childhood interpersonal stress on adult
health (Beach et al., 2017, p. 17).
Conditional indirect effects also shed light on how young adults’ romantic relationships
may provide contexts that promote recovery from the effects of FOA on health. While FOA
exerts a significant total effect on IL-1β for men who report high or moderate levels of
avoidance, men who are low in romantic attachment avoidance are buffered from the total effect
of FOA on IL-1β. Young men who are comfortable experiencing vulnerable emotions and
confident that partners will respond supportively display health-protective patterns of HPA
reactivity after FOA exposure. These patterns of reactivity may not only prevent further bodily
wear and tear but also create an environment that promotes recovery from FOA-induced chronic
inflammation. When current relationship interactions do not provoke heightened HPA reactivity,
FOA-exposed men may regain sensitivity to the inhibitory effect of cortisol on inflammation. In
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 81
support of the notion that improved psychosocial conditions can promote recovery from
psychosocially-induced inflammation, psychotherapy has been shown to decrease depression-
linked inflammation (see Lopresti, 2017 for review) and restore glucocorticoid sensitivity
(Bowie & Beaini, 1985), likely by reducing depressive symptoms (Thornton et al., 2009).
Similarly, forming secure romantic relationships may diminish the health effects of childhood
relationship stress. Intervention research further suggests that relationships play an important role
in recovery from stress-related inflammation, as psychotherapy-related reductions in
inflammation correspond with reductions in stress related to social roles (da Silva et al., 2016),
and therapies that specifically address relational aspects of depression have been shown to
reduce inflammation to non-clinical levels among depressed adults (Dahl et al., 2016). The
romantic relationships young adults form may provide naturally-occurring opportunities to
similarly leverage social connection to recover from stress-induced health risk.
However, several limitations of the present study underscore the need for more evidence
before concluding that the observed moderated mediation effect indicates that romantic
relationships provide contexts for physiological risk for and recovery from inflammatory effects
of FOA. First, we do not have a measure of participants’ attachment during childhood, which
limits our ability to attribute attachment avoidance to adult relationships alone. Attachment arises
during infancy in response to parent-child interactions (Bowlby, 1969/1982), and extends
throughout the lifespan, such that by young adulthood both experiences in the family of origin
and in romantic relationships shape attachment orientations (Cassidy, 2000; Dinero, Conger,
Shaver, Widaman, & Larsen-Rife, 2008), the security of which may differ between relationships
with parents and with romantic partners (Caron, Lafontaine, Bureau, Levesque, & Johnson,
2012). However, if our measure of romantic attachment avoidance represents a lifelong approach
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 82
to the social regulation of emotion, less avoidant men may have been protected from the effects
of FOA on HPA reactivity during childhood. In this case, results may indicate that less avoidant
men never acquired health-endangering patterns of physiological reactivity, rather than that adult
attachment helped ameliorate these effects. Future longitudinal research is needed to assess
possible changes in both attachment and physiology from childhood to adulthood, in order to
specify whether romantic relationships provide contexts that promote physiological recovery
from FOA.
Additionally, the nature of our dyadic interaction tasks introduces important limitations.
We assessed HPA reactivity during interactions that elicit emotional vulnerability. Highly
avoidant men show amplified effects of FOA on stress system response during such interactions,
but no effects of FOA on reactivity are present when avoidance is not accounted for. However, in
line with conflict sensitization theories (e.g. Cummings & Davies, 1996), FOA may exert main
effects on reactivity during conflictual, rather than vulnerable, interactions. Therefore, measuring
HPA reactivity during conflict discussions may allow for the detection of indirect effects that are
not conditional on attachment avoidance. Moreover, other aspects of romantic relationships may
moderate FOA’s effect on physiology during other types of interactions; for instance, attachment
anxiety is expected to be most influential during interactions that activate concerns about
abandonment, such as discussing the relationship’s future (Simpson & Rholes, 1994). Future
studies should assess interpersonal HPA reactivity during a wider variety of dyadic interactions
and with a wider variety of corresponding relationship-related moderators, in order to test the
proposed interpersonal mechanism of health risk and recovery more comprehensively.
In the present study, we conceptualize HPA reactivity in terms of cortisol slope across the
interaction tasks, and categorize individuals who showed greater change in cortisol over time as
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 83
exhibiting greater reactivity and individuals who show less change over time as exhibiting less
reactivity. Notably, however, in our sample, as in other couple interaction studies, most
participants did not exhibit increases in cortisol (Kiecolt-Glaser et al., 1997; Robles & Kiecolt-
Glaser, 2003). Rather, the highest cortisol values were exhibited at baseline. As participants were
aware that they would be asked to complete a series of emotionally-salient dyadic interactions
during the visit, this pattern may indicate that participants experienced significant anticipatory
stress in preparation for completing dyadic interactions, which raised cortisol values before the
initial sampling point; if so, our methods may have failed to capture initial cortisol increases that
occurred while mentally preparing for, rather than participating in, interaction tasks. Sharper
cortisol declines may therefore capture the termination of an evoked HPA activation, whereas
relatively flat cortisol slopes may indicate that the HPA axis was less activated by either
anticipating or completing the interactions. However, it is also possible that sharp cortisol
declines represent a form of HPA axis blunting (Fries, Hesse, & Hellhammer, 2005), which
underpins withdrawal from the demands of the task (Shirtcliff, Peres, Dismukes, Lee, & Phan,
2014). If so, sharper decreases in cortisol may multiply the risk of FOA on inflammation in so
far as these declines represent disengagement from one’s current interpersonal world (e.g.,
Eisenberger, Inagaki, Marhsal, & Irwin, 2010). Finally, observed declines in cortisol may
indicate either that interaction tasks were not sufficiently challenging to counteract the diurnal
decline in cortisol across the day or that the stress of arriving to the lab was more significant than
the stress of completing the interaction tasks (Shirtcliff et al., 2014). Additional research
employing multiple measures of physiological activation (e.g., both ANS and HPA response)
during dyadic interactions may help clarify the meaning of sharper versus flatter cortisol declines
during romantic partner interactions. Difficulty identifying which patterns of cortisol slope
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 84
indicate greater versus less physiological reactivity echo a larger problem in the literature: both
up- and down-regulation of the HPA axis has been implicated as a disease mechanism linking
stress to health (e.g., Miller et al., 2007), a paradox that may be due, in part, to the inherent
limitations of dichotomously categorizing a complex and dynamic stress response system into
“up” and “down” (e.g., Shirtcliff et al., 2014).
Across all hypotheses, effects of FOA on inflammation and on HPA reactivity were only
observed for men. Although gender differences are relatively common in the stress and
inflammation literature, when these differences emerge they often indicate that women are more
sensitive to the effects of psychosocial stress on inflammation (e.g., Kiecolt-Glaser & Newton,
2001; Kiecolt-Glaser & Wilson, 2017; Moieni et al., 2015). Women’s greater susceptibility is
particularly notable in links between romantic relationship-related stress and inflammation (e.g.,
Donoho et al., 2013; Whisman & Sbarra, 2012). Given women’s greater susceptibility to the
physiological and health effects of romantic relationships (Kiecolt-Glaser & Newton, 2001),
effects of distal FOA on women’s biology may be masked by the greater influence of proximal
relationships characteristics, such as current partner’s level of aggression or hostility, which were
not a focus of the present study. Finally, observed gender differences may be related to
biological differences between sexes that we were unable to adjust for in the present study; for
instance, menstrual phase may influence both HPA activity (Kirschbaum, Kudielka, Gaab,
Schommer, & Hellhammer, 1999) and inflammation (e.g., Evans & Salamonsen, 2012).
Several other limitations of our study should be noted. First, conditional indirect effects
were detected for IL-1β but not for IL-6. Although observing different effects across different
cytokines is a relatively common pattern in the stress and inflammation literature (e.g., Wilson et
al., 2018), the lack of consistency across inflammatory markers increases the caution with which
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 85
results should be interpreted. It is not clear why some cytokines might be more susceptible to the
effects of FOA or HPA reactivity than others. Additionally, the present study can only speculate
as to underlying mechanisms by which HPA activity influences inflammation. Although we posit
that alterations in immune cell’s sensitivity to glucocorticoids account for links between HPA
activity and inflammation, we did not assess participants’ levels of glucocorticoid resistance.
Prior studies have established that stress leads to glucocorticoid insensitivity (e.g., Cohen et al.,
2012), but to our knowledge no study has directly assessed whether naturally-occurring
protective relationship qualities, such as secure attachment, predict recovery of glucocorticoid
sensitivity following stress exposure. Importantly, the relationship between the HPA and
immune/inflammatory activity is complex and bidirectional (e.g., Miller, Maletic, & Raison,
2009), in part because stress exposure creates allostatic wear-and-tear on both response systems
(Hänsel et al., 2010). For example, if allostatic adaptation decreases the basal ability of the HPA
axis to flexibly produce glucocorticoids in response to variable environmental demands, chronic
inflammation may also be the result of insufficient cortisol to check the activity of immune cells,
rather than only the result of too much cortisol producing glucocorticoid resistance in immune
cells. Moreover, HPA activity is only one physiological pathway by which FOA might influence
inflammatory health; experiencing stress during sensitive periods in childhood may also shape
health via biologically embedded epigenetic changes and structural remodeling of the brain and
nervous system (Miller et al., 2011). Finally, the present study did not assess how FOA might
influence behaviors during dyadic interactions; it is likely that FOA influences inflammation via
complex cascades of behavioral and physiological risk, such that FOA-exposed children grow up
to form lower-quality relationships, and more conflictual or less supportive interactions evoke
greater HPA responses (Miller et al., 2011). Reciprocally, having an elevated fight-or-flight
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 86
response during emotionally vulnerable interactions may interfere with FOA-exposed youth’s
abilities to behave skillfully during dyadic interactions, further reinforcing cascades of risk.
However, testing these comprehensive mechanisms is beyond the scope of our current data set.
Despite these limitations, the present study provides initial evidence that FOA influences
young men’s inflammatory health even within community samples and that experiences within
romantic relationships link FOA exposure to inflammation. Findings not only underscore the
importance of preventing childhood FOA exposure in order to protect health but also introduce a
second potential disease-prevention window: emerging adulthood. Young adulthood marks the
emergence of disparities in surrogate disease markers, such as inflammation, but precedes the
onset of associated chronic illness (Bonnie et al., 2015). Establishing stable romantic
partnerships is a salient developmental task of young adulthood (Arnett, 2000) and the
relationships formed during this period may provide opportunities to acquire new physiological
reactions to interpersonal stress that mitigate the health effects of FOA-exposure. Intervening to
improve romantic relationship quality in emerging adulthood may therefore have unrealized
potential to prevent disease in later life. The present study suggests that enhancing attachment
security and regulating stress physiology in the context of close relationships may provide useful
targets for future interventions to protect FOA-exposed young adults from developing
inflammatory disease.
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 87
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rate variability during conflict predicts heightened inflammation throughout the day.
Psychoneuroendocrinology, 93, 107-116. doi: 10.1016/j.psyneuen.2018.04.017
Winer, J. P., Powers, S. I., Pietromonaco, P. R., & Schreck, M. C. (2018). Childhood family
adversity and adult cortisol response: The role of observed marital conflict behavior.
Journal of Family Psychology, 32, 793-803. doi: 10.1037/fam0000455
Yang, Y. C., Schorpp, K., & Harris, K. M. (2014). Social support, social strain and
inflammation: Evidence from a national longitudinal study of US adults. Social Science
& Medicine, 107, 124-135. doi: 10.1016/j.socscimed.2014.02.013
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 101
Table 1.

Means, standard deviations, and correlations among study variables.

Mean (SD) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.
1. W IL-1β 3.13 (1.21) -
2. M IL-1β 3.69 (1.11) .092 -
3. W IL-6 2.04 (0.32) .363** -.040 -
4. M IL-6 1.97 (0.25) .014 .039 .017 -
5. W FOA 14.64 (12.84) .147 .198 -.067 -.069 -
6. M FOA 11.66 (12.88) -.011 .227
†
-.103 .183 .237* -
7. W Avoid 2.70 (0.78) .293* .162 -.001 .087 .186
†
.094 -
8. M Avoid 2.69 (0.79) .024 .007 -.024 -.103 .088 .078 -
9. W Cortisol
1
5.63 (3.29) -.106 .121 -.095 -.213 -.133 -.133 -.007 .095 -
10. M Cortisol
1
7.14 (5.46) -.084 .228
†
-.131 -.168 .161 .161 .030 -.015 .214* -
11. Time
2
12:34 (1:15) -.052 .131 -.057 .084 .061 .061 -.033 .019 -.272* -.017 -
12. W Age 22.28 (1.81) .045 .031 .191 -.225
†
-.203
†
-.203
†
.125 .159 .032 -.078 -.135 -
13. M Age 23.31 (3.01) .018 .082 .081 .001 -.099 -.099 .099 -.004 .060 -.122 -.096 .588*** -
14. Months
Together
30.83 (24.60) -.134 .135 .017 -.152 .028 .028 -.197
†
-.064 -.042 -.164 -.003 .155 .227* -

Notes:
† p < .10; * p < .05; ** p < .01; *** p < .001
M = men’s, W = women’s, FOA = family of origin aggression, Avoid = attachment avoidance, SD = standard deviation
1
Cortisol is the initial value for each participant.
2
Here, time refers to time of day when the initial saliva sample was collected in each dyad, presented in hours and minutes. In multi-level structural
equation models testing hypotheses, this initial value is centered to zero and subsequent values are calculated in minutes since the initial
sampling time.

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 102
Table 2.
Bayesian multi-level structural equation models testing indirect effects of family of origin aggression on inflammatory markers (IL-1β,
IL-6) through cortisol slope.
IL-1β IL-6
Men Women Men Women
Est (LLCI, ULCI) Est (LLCI, ULCI) Est (LLCI, ULCI) Est (LLCI, ULCI)
Step 1: Effects of FOA on inflammation
FOA (path c) 0.025* (0.002, 0.049) 0.010 (-0.014, 0.033) 0.006* (0.001, 0.011) -0.002 (-0.010, 0.004)

Step 2: Effects of FOA on slope
1

FOA (path a) -0.011 (-0.042, 0.018) -0.019 (-0.042, 0.009) -0.008 (-0.040, 0.021) -0.017 (-0.044, 0.011)

Step 3: Effects of FOA and slope on inflammation
1

Slope (path b) -0.580* (-1.054, -0.156) -0.573 (-2.714, 1.522) 0.052 (-0.083, 0.163) 0.139 (-0.183, 0.575)
FOA (path c’) 0.025 (-0.002, 0.051) <0.001 (-0.079, 0.040) 0.004 (-0.002, 0.011) -0.001 (-0.010, 0.092)

Probing Moderated Mediation
Indirect Effect 0.006 (-0.012, 0.028) 0.007 (-0.028, 0.085) <0.001 (-0.003, 0.002) -0.001 (-0.013, 0.005)
Total Effect 0.032* (0.002, 0.060) 0.009 (-0.014, 0.034) 0.004 (-0.002, 0.011) -0.003 (-0.009, 0.004)

Model Fit
Step 1 Model DIC 9088.533 8735.709
Steps 2 and 3 Model DIC 8990.782 8519.109
Notes
* = statistically significant (95% credible interval does not include 0).
1. Steps 2 and 3 conducted in simultaneous multi-level structural equation model.
Covariates in all models include age, relationship duration, medication, salivary cotinine, and hours since awakening.
Est = estimate, LLCI = lower limit of 95% credible interval, ULCI = upper limit of 95% credible interval, FOA = family of origin aggression, slope = cortisol slope during dyadic
interactions, DIC = Deviance Information Criterion.
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 103
Table 3.
Bayesian multi-level structural equation models testing conditional indirect effects of family of origin aggression on inflammatory
markers (IL1β b, IL-6) through cortisol slope at high and low levels of attachment avoidance.
IL-1β IL-6
Men Women Men Women
Est (LLCI, ULCI) Est (LLCI, ULCI) Est (LLCI, ULCI) Est (LLCI, ULCI)
Step 1: Effects of FOA on inflammation
FOA (path c) 0.025* (0.002, 0.049) 0.010 (-0.014, 0.033) 0.006* (0.001, 0.011) -0.002 (-0.010, 0.004)

Step 2: Effects of FOA on slope
1

FOA (path a1) -0.013 (-0.040, 0.008) -0.010 (-0.038, 0.013) -0.014 (-0.039, 0.011) -0.013 (-0.042, 0.017)
Avoidance (path a2) 0.085 (-0.327, 0.512) -0.231 (-0.665, 0.210) 0.062 (-0.361, 0.454) -0.130 (-0.616, 0.281)
FOA*Avoidance (path a3) -0.033* (-0.061, -0.006) -0.003 (-0.037, 0.036) -0.037* (-0.066, -0.010) 0.004 (-0.022, 0.032)

Step 3: Effects of FOA and slope on inflammation
1

Slope (path b) -0.646* (-1.078, -0.143) -0.685 (-1.460, 0.167) 0.045 (-0.081, 0.142) 0.037 (-0.197, 0.394)
FOA (path c’) 0.024 (-0.002, 0.049) 0.002 (-0.032, 0.031) 0.004 (-0.002, 0.011) -0.001 (-0.008, 0.008)

Probing Moderated Mediation
Index of Moderated Mediation 0.019* (0.002, 0.045) 0.002 (-0.015, 0.024) -0.001 (-0.006, 0.003) <0.001 (-0.003, 0.005)
Conditional Indirect Effects
-1 SD -0.007 (-0.030, 0.017) 0.003 (-0.020, 0.027) <0.001 (-0.002, 0.004) <0.001 (-0.011, 0.005)
M 0.008 (-0.005, 0.029) 0.004 (-0.011, 0.032) <0.001 (-0.003, 0.002) <0.001 (-0.009, 0.003)
+1 SD 0.025* (0.001, 0.059) 0.004 (-0.011, 0.044) -0.002 (-0.007, 0.004) <0.001 (-0.009, 0.003)
Conditional Total Effects
-1 SD 0.016 (-0.019, 0.051) 0.005 (-0.032, 0.036) 0.005 (-0.002, 0.012) -0.002 (-0.010, 0.005)
M 0.032* (0.002, 0.064) 0.008 (-0.015, 0.032) 0.004 (-0.003, 0.011) -0.002 (-0.009, 0.004)
+1 SD 0.050* (0.015, 0.091) 0.011 (-0.015, 0.036) 0.003 (-0.006, 0.011) -0.002 (-0.009, 0.005)

Model Fit
Step 1 Model DIC 9088.533 8735.709
Steps 2 and 3 Model DIC 9009.060 8655.187
Notes
* = statistically significant (95% credible interval does not include 0).
1. Steps 2 and 3 conducted in simultaneous multi-level structural equation model.
Covariates in all models include age, relationship duration, medication, salivary cotinine, and hours since awakening. Conditional indirect and total effects are calculated at levels of
attachment avoidance that are one standard deviation below the mean (-1 SD), at the mean (M), and one standard deviation above the mean (+1 SD)
Est = estimate, LLCI = lower limit of 95% credible interval, ULCI = upper limit of 95% credible interval, FOA = family of origin aggression, slope = cortisol slope during dyadic
interactions, DIC = Deviance Information Criteri
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 104

Figure 1. Structural equation model describing total effects of family of origin aggression (FOA) on inflammation (path cm for men;
path cf for women), indirect effects of FOA on inflammation through cortisol slope (paths a1m and bm for men; paths a1f and bf for
women), and conditional indirect effects (paths a1m, a3m and bm for men; paths a1f, a3f and bf for women). Paths c’m and c’f represent
the direct effects of FOA after accounting for indirect effects. To account for interdependence between members of the same couple,
residual correlations among cortisol values and slopes for men and women were estimated but are not presented here due to space
constraints; covariates are not presented here due to space constraints. Markers of inflammation (IL-1β, IL-6) are tested in separate
models.
cm
c’f
a1m
bm
a3m
a2m
bf
Women’s
Inflammation
cf
a2f
a3f
a1f

Men’s
Inflammation
Men’s
FOA
Women’s
FOA
Women’s
Cortisol Slope
Men’s
Cortisol Slope
Men’s
Avoidance
Women’s
Avoidance
c’m
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 105

General Discussion
The three papers presented in this dissertation examine how childhood stressful
experiences become embedded in physiology to influence young adult health. Building on
allostatic load, conflict sensitization, and attachment theories, these studies demonstrate that
alterations to hypothalamic-pituitary-adrenal (HPA) axis activity link childhood stress to
indicators of adult health. Results then provide evidence that young adult romantic relationships
may present opportunities to either fortify or revise the impact of childhood stress on physiology
in ways that can endanger or protect health.
Paper one identifies attenuated cortisol awakening response as a mechanism linking
cross-domain adversity in childhood to greater body mass index (BMI) in emerging adulthood.
Paper two narrows in focus, to examine the effects of one salient form of childhood interpersonal
stress, family of origin aggression (FOA), on physiological reactivity during emotionally
vulnerable interactions between young adult dating partners; results indicate that the actor- and
partner- effects of FOA on HPA activity depend on romantic attachment avoidance, such that
greater FOA heightens HPA response when avoidance is elevated but lowers HPA response
when avoidance is low. Finally, paper three examines HPA reactivity to these interactions as a
mechanism linking FOA to immune-mediated inflammation, finding that young men’s FOA
history portends greater inflammation, and that reactivity only mediates this relationship for
those who are high in attachment avoidance; for less avoidant young men, there is no total effect
of FOA on inflammation.
These results both offer substantive contributions and point to areas for further inquiry.
First, associations between childhood stress and later health markers were detected in community
samples of generally healthy young adults. Children who were exposed to more forms of
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 106
adversity had higher BMIs in young adulthood, and young men who reported more childhood
FOA had greater levels of basal inflammation. Effects were detected longitudinally, such that in
study one, the effects of childhood stressors predicted HPA activity up to nine years later and
predicted BMI up to thirteen years later, with associations between cortisol awakening response
and BMI detectable across the approximately four years between measurements. Similarly, in
study three, FOA and HPA reactivity with dating partners predicted greater inflammation
approximately 18 months later. These findings join a growing literature indicating that stress in
childhood wears away at health over time, even in community samples (e.g., Lacey, Kumari, &
McMunn, 2013), in much the same way as is observed in samples that have experienced major
maltreatment, such as abuse or neglect (e.g., Matthews, Chang, Thurston, & Bromberger, 2014).
Given the high rates both of exposure to stress in childhood (Straus & Field, 2003) and of
chronic obesity- and inflammation-related illnesses in adulthood (e.g., Merrill, Kessler, Udler,
Rasband, & Feuer, 1999), findings in this dissertation may point to a common and costly
mechanism of disease. Although HPA alterations are frequently posited as a mechanism linking
childhood stress to adult health (e.g., Repetti, Robles, & Reynolds, 2011), the papers in this
dissertation are among the first to directly test this hypothesis in mediation models. Detecting
these associations during emerging adulthood is particularly significant, as young adulthood
precedes the onset of the chronic illnesses of aging but allows for the detection of individual
differences in disease-related surrogate endpoints, such as BMI and inflammation (e.g., Field et
al., 2001; Michaud et al., 2013). Young adulthood therefore may offer an effective prevention
window, as interventions can be targeted to those who exhibit health risk and implemented
before disease develops.
The papers in this dissertation build from testing a general allostatic model (i.e., that
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 107
reduced morning HPA activity mediates associations between stress and heath) to examining
allostatic processes within close relationships specifically (i.e., that in some cases FOA sensitizes
reactivity during romantic partners’ interactions). FOA may confer discrete patterns of
heightened reactivity that are only triggered by challenges within close relationships, even while
a history of childhood stress exposure otherwise reduces HPA activity throughout the day. In the
package of studies in this dissertation, less change in HPA activity during the day and greater
change in HPA activity during interactions predicted maladaptive health markers in emerging
adulthood. Interpreting these findings in conjunction, childhood stress may contribute to
allostatic wear-and-tear via a cascade of processes that unfold throughout development: first,
stress-induced HPA activations during childhood may dampen the ability of the HPA axis to
flexibly respond to day-to-day events during adulthood. Second, for some adults, childhood
stress exposure may confer a heightened stress response to stimuli that resemble sources of
childhood stress, creating additional “hits” to physiology that may recur long after sources of
childhood stress have passed. These acute activations in adulthood may further dull the flexible
responsivity of the HPA axis diurnally. Inflexible HPA activity, in which cortisol levels are
chronically too high or too low to meet environmental demand, may then take a toll on health.
Future studies should examine how childhood stress exposure influences the same individuals’
patterns of HPA activity both diurnally and within close relationships. Additionally, future
studies that measure HPA activity repeatedly across multiple contexts may help clarify the
discrete and cumulative health impacts of acute cortisol elevations, chronic cortisol attenuation,
or reduced diurnal variability in cortisol, which may co-occur in the same individuals.
Importantly, for young men, the impacts of FOA on reactivity during dyadic interactions
and on health-markers at follow-up depend on levels of attachment avoidance. This finding,
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 108
though preliminary, suggests that the romantic attachments young adults form can shape how
childhood stress influences adult health. However, future research is needed to confirm and
elucidate this mechanism. First, additional longitudinal research is needed to determine the
extent to which romantic attachment avoidance is the product of experiences in present
relationships versus a longstanding strategy for the social regulation of emotion (e.g., Allen,
Grande, Tan, & Loeb, 2018; Dinero, Conger, Shaver, Widaman, & Larsen-Rife, 2008). Building
on attachment and conflict sensitization theories, the present studies postulate that romantic
relationships provide opportunities to update social learning acquired in aggressive families;
however, changes in social learning are not directly assessed in this dissertation. Similarly,
measuring HPA reactivity at multiple points in development would help determine whether
romantic relationships might alter reactivity or merely provide contexts in which long-standing
individual differences in reactivity are made manifest. Given the cross-partner effects reported in
this dissertation and elsewhere (e.g., Winer, Powers, Pietromonaco, & Schreck, 2018), in future
studies, relationship-related changes in physiology should be measured dyadically; repeated
dyadic measures of physiology would help clarify how partners’ past interpersonal experiences
and current interpersonal attributes shape each other’s physiology and health over time. Finally,
if further evidence supports that relationships are contexts that can promote health-protective
HPA alterations, additional biomarkers should be assessed to determine how psychosocial
experiences might get under the skin to foster physiological recovery from stress. Candidate
processes include recovery from glucocorticoid resistance and epigenetic changes that promote
expression of genes governing sensitivity to cortisol (e.g., Liu & Nusslock, 2018; Miller, Chen,
& Parker, 2011). If young adult relationships can help repair the health-effects of childhood
stress, intervening to improve romantic relationship quality in emerging adulthood may have
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 109
untapped potential to prevent disease in later life. A multitude of evidence-based interventions
are available in communities to improve romantic relationship quality (e.g., Carr, 2014);
however, whether such interventions might also protect health remains unknown.
Notably, the gender differences observed in this dissertation suggest that young men may
be more sensitive to the effects of childhood stress on physiology and health. Whereas study one
found effects in a mixed-gender sample of young adults, studies two and three only detected
actor-effects of FOA on physiology and health among young men. Although gender differences
are commonly observed in the stress, HPA, and inflammation literatures (e.g., Chrousos, 2010;
Kudielka & Kirschbaum, 2005), the nature of these differences is inconsistent across studies.
Candidate processes to account for observed differences between men and women include both
sex differences, such as the influence of menstrual phase on HPA activity (e.g., Kirschbaum,
Kudielka, Gaab, Schommer, & Hellhammer, 1999) and hormone-related differences in the
impact of the cortisol stress responses on glucocorticoid sensitivity and inflammation (e.g.,
Rohleder, Schommer, Hellhammer, Engel, & Kirschbaum, 2001), and gender differences, such
as variability in the degree to which emotionally vulnerable interactions are novel (e.g.,
Christensen & Heavey, 1990) and variability in how early stressful experiences, such as FOA,
are reported (Chung & Monroe, 2003; Mayor, 2015). Unfortunately, the presented studies are not
able to account for the mechanisms that lead to the detection of some effects among men only.
Across studies, several important limitations must be noted. First, data sets do not include
baseline measures of BMI or inflammation during childhood. Additionally, included papers do
not comprehensively assess all variables that are likely to contribute to cascades from childhood
stress to adult health. For example, health behaviors, such as diet and exercise, can be shaped
both by stressful childhood experiences and by HPA activity (e.g., Adam & Epel, 2007); these
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 110
behaviors contribute substantially to obesity- and inflammation-related disease (Loef & Walach,
2012). Similarly, childhood stress, such as FOA, directly influences the quality of adult
relationships, and lower adult relationship quality can confer sensitized reactivity during dyadic
discussions (Robles & Kiecolt-Glaser, 2003); therefore, FOA may confer altered reactivity
because it reduces relationship quality (Doucet & Aseltine, 2003) and contributes to stress
proliferation within relationships (e.g., Pearlin, Schieman, Fazio, & Meersman, 2005). Finally,
though BMI and inflammatory markers are assessed as outcomes in separate studies, obesity and
inflammation are themselves linked, as adipose tissue produces pro-inflammatory mediators
(Tilg & Moschen, 2006). Future research should comprehensively measure the complex and
interconnected links in chains from stress to disease, in order to identify a wider range of
potential opportunities for intervention.
The strategies employed to index HPA reactivity introduce additional limitations. Paper
one measures cortisol awakening response as the difference between peak morning cortisol level
and level upon awakening; such a measure is advantageous insofar as it enhances interpretability
in terms of “greater” versus “lesser” HPA response. However, interpretability comes at the
expense of nuance, as this strategy precludes more detailed modeling of change in cortisol across
time. Conversely, papers two and three model the effect of time on cortisol across multiple
measurement points; although such a strategy takes advantage of the full available data set, the
resultant cortisol slope defies clean categorization as “greater” or “lesser” HPA response,
particularly because cortisol values do not rise in response to the interaction task for most
participants. This limitation is echoed in the larger cortisol literature, which is marked by
inconsistency in how HPA activity is indexed, in part because no one strategy is clearly
advantageous (e.g., Stalder et al., 2016). Therefore, interpretations that conceptualize dissertation
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 111
results within the larger HPA literature must remain tentative.
Despite these limitations, the papers in this dissertation demonstrate that physiological
pathways link childhood stress to young adult health, identify individual differences in how
stress becomes embedded in physiology, support that young adult romantic relationships may
provide contexts in which the physiological impacts of adversity may incur ongoing damage, and
introduce close relationships as opportunities to acquire health-protective physiological patterns
after stress exposure. Findings both shed light on mechanisms that may contribute to the
development of chronic disease and point to naturally-occurring opportunities to disrupt stress-
induced disease risk.

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 112
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CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 117

Supplemental Materials

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 118

Childhood Adversity

A Cumulative, Multi-Reporter Approach to Measuring Childhood Adversity
Kelly F. Miller, Reout Arbel; Sohyun C. Han, Hannah F. Rasmussen, Kristene Hossepian, and
Gayla Margolin
Created June 2014; updated April 2019

A version of this measure is available at:
https://dornsife.usc.edu/assets/sites/226/docs/New_A_Cumulative_Multi-Reporter_Approach_
to_Measuring_Childhood_Adversity.FINAL.pdf

Why Measure Childhood Adversity

Adverse childhood experiences (ACEs), such as physical abuse, sexual abuse, and
neglect, are commonly experienced, and these experiences confer risk for poorer physical health,
mental health, and well-being throughout the lifespan (CDC, 2010). A large and robust literature
linking these childhood adversities to adult maladaptation has utilized the Adverse Childhood
Experiences Scale (ACES; Felitti et al., 1998). This questionnaire asks adult respondents to
retrospectively rate whether or not 10 forms of adversity (emotional abuse, physical abuse,
sexual abuse, neglect, being unloved, parental separation/divorce, interparental physical
aggression, parental substance abuse, parental mental illness, and parental incarceration)
occurred at any point in the first eighteen years of life. Early versions of the ACES applied a cut-
off threshold to continuously-rated participant data to determine whether or not each type of
adversity had occurred; later versions asked participants to respond dichotomously. These data
support that diverse categories of adversity have a cumulative impact on well-being, such that
having experienced more forms of adversity exerts a linear detrimental impact.

Project Goals

Inspired by the ACES, we utilized the first 9 years of an existing longitudinal study of
families to create a multi-reporter, multi-timepoint measure of cumulative childhood adversity.
Our project mined the first 5 waves of a longitudinal data set (spanning middle childhood to
adolescence). Each wave included a range of self-report questionnaires from 3 reporters: youth,
mother-figures, and father-figures. As the original study was not originally intended to measure
adverse experiences, mothers, fathers, and youth were not presented with a dichotomous ACEs
scale at each wave. Rather, questions capturing each of these experiences were dispersed across a
wide range of self-report questionnaires administered to youth, mothers, and fathers. We
therefore utilized the entirety of our robust longitudinal data set to assess the presence of adverse
experiences in our participants’ lives. Pulling from converging literature on cumulative risk (e.g.,
The Risky Families Questionnaire, Taylor et al., 2004), in addition to the 10 ACEs, we included
data on interparental emotional abuse, family financial hardship, and youth social isolation. The
goal of the project was to create a measure of whether or not each of these 13 adversities were
reported by any informant, at any measurement point.
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 119

Anticipated Advantages

We anticipated that utilizing a multi-reporter, multi-timepoint, cumulative measure of
childhood adversity would provide several advantages. First, adverse experiences are sensitive
topics, and family members may be hesitant to disclose their occurrence. Utilizing multiple
reporters (mother, father, child) allows adversity scores to be calculated via maximum report
(i.e., adversities are counted if any informant reports that the event occurred). This methodology
provides the greatest likelihood of capturing under-reported events. Additionally, we assess
adverse experiences across multiple time points, as repeated, shorter-term recalls are more likely
to accurately reflect childhood experiences, as compared to one-time, long-term retrospective
reports. Finally, this methodology allows flexibility in creating total adversity scores, as
dichotomous scores can be selectively summed according to construct (type of adversity) and
wave. For instance, researchers may choose to sum all 13 constructs (for possible scores ranging
from 0 to 13) or focus only on the 10 original ACES (for possible scores ranging from 0 to 10).
Similarly, researchers may look across all 5 waves of data collection or select only a subset of
waves, depending on the outcome and developmental stage of interest. Therefore, the
developmental period and experiences included can be tailored to the desired research question.

Measurement Methodology

We assembled a team of researchers, including psychologists, clinical psychology
graduate students, and post-baccalaureate research assistants, to review each measure that had
been administered across the first five waves of our longitudinal study and identify items that
asked about each type of adverse experience. Although in many cases the same questions were
asked at each wave, questions were sometimes modified in order to be developmentally
appropriate for participants transitioning from childhood to adolescence. For instance, at wave 2
(youths’ mean age = 11 years), only parents reported whether children had experienced sexual
abuse, whereas in Wave 4 (youths’ mean age = 15 years), adolescents also reported about their
own experiences of sexual abuse.

In some instances, occurrence of adverse events was measured by a single dichotomous
measure at each wave (e.g., checking “Parents separated or divorced” on a past year Life Events
Checklist). More often, participants could be marked as having experienced a certain type of
adversity by endorsing any one of several items (e.g., for a child to be marked as experiencing
parental substance abuse, parents could score above a clinical cutoff on a questionnaire of
alcohol and substance use OR report that they have been so drunk or high that they were unable
to take care of their child OR describe their drinking as a “serious problem” or “extreme
problem” on a Likert scale, OR have one spouse describe the other in the above ways, etc.). In
total, items from 18 measures were used to assess the 13 constructs. We used items from
commonly administered psychological assessments and from measures we developed
specifically for our longitudinal study. Those measures are:
• Conflict Tactics Scale (CTS; Straus, 1979; Straus, Hamby, Boney-McCoy, & Sugarman,
1996)
• Domestic Conflict Inventory (DCI; Margolin, John, & Foo, 1998)
• Parent-Child Conflict (PCC; modified from Straus, Hamby, Finkelhor, Moore, &
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 120
Runyan, 1998)
• Child’s View Questionnaire (Margolin, 2000; developed for this project, with some items
modified from Greenberg, Seigel, & Leitch, 1983)
• Community Violence Questionnaire (modified from Ritchers & Martinez, 1993; Richters
& Saltzman, 1990)
• Youth Risky Behavior Survey (modified from YRBS; Eaton et al., 2004)
• How Friends Treat Each Other (Bennett, Guran, Ramos, &. Margolin, 2011)
• Life Events Scale (LES; modified from Holmes & Rabe, 1967)
• Life Events Checklist (LEC; modified from Johnson & McCutcheon, 1980)
• Drug Abuse Screening Test (DAST; Skinner, 1982)
• Michigan Alcoholism Screening Test (MAST; Selzer, 1971)
• Alcohol and Drug Questionnaire (modified from MAST [Selzer, 1971] and DAST
[Skinner, 1982; Skinner & Holt, 1987])
• Los Angeles Symptom Checklist (LASC; King, King, Leskin, & Foy, 1995)
• Symptom Checklist-90 (SCL-90; Derogatis, 1977)
• Child Depression Inventory (CDI; Kovaks, 1985)
• Youth Self Report (YSR; Achenbach, 1991)
• Economic Impact Questionnaire (Margolin, 2006; developed for this project)
• Alienation Inventory (modified from Lacourse, Villeneuve, & Claes, 2003;
Roberts,1987)

The attached table enumerates each item included in our cumulative adversity measure.
The table lists each adversity construct, the wave at which it was measured, the reporter, the
measure, the specific item used from the measure, and the level of item endorsement needed for
the type of adversity to be coded as present. If any reporter endorsed an item at or above the cut-
off threshold, that type of adversity was calculated as having occurred. Youth, mothers, and
fathers were invited to provide data at each wave; for constructs in which reporter is marked as
“parent,” items were administered to both mother and father.

Cumulative Adversity Publications and Presentations

To date, our measure has been used in the following academic journal articles, conference
presentations, and posters:

Publications:
Arbel, R., Schacter, H. L., Kazmierski, K. F. M., Daspe, M., & Margolin, G. (2018). Adverse
childhood experiences, daily worries, and positive thoughts: A daily diary multi-wave
study. British Journal of Clinical Psychology, 57, 514-519. doi: 10.1111/bjc.12200
Miller, K. F., Arbel, R., Shapiro, L. A. S., Han, S. C., & Margolin, G. (2018). Does the cortisol
awakening response link childhood adversity to adult BMI? Health Psychology, 37. doi:
10.1037/hea0000601

Presentations:
Arbel, R., Kazmierski, K.F.M., & Schacter, H.L. (March 2019). Adverse childhood experiences
and symptoms in early adulthood: The role of adolescents’ daily negative emotion
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 121
differentiation. Paper presented at the Society for Research in Child Development
Biennial Meeting, Baltimore, MD.
Arbel, R., Schacter, H.L., Miller, K.F., Margolin, G. (September 2018). A day-to- day
examination of friend victimization, prosocial behaviors, and the cortisol awakening
response: exploring the moderating role of adverse family environment. Paper presented
at the European Association for Research on Adolescence (EARA), Ghent, Belgium.
Arbel, R., Schacter, H. L., Miller, K. F., & Margolin, G. (May 2018). Adverse childhood
experiences as a moderator of relations between daily worries, positive thoughts, and
subsequent internalizing symptoms: A multi-wave study. Paper to be presented at the
48th Annual Meeting of the Jean Piaget Society, Amsterdam, Netherlands.
Shin, O., Pettit, C.A., Miller, K. F., & Margolin, G. (November 2017). Emotion regulation as a
moderator of the longitudinal relationship between childhood adversity and BMI in
young adulthood. Poster presentation at the International Society for Traumatic Stress
Studies 33rd Annual Meeting, Chicago, IL.
Arbel, R., Miller, K. F., & Margolin, G. (April 2017). Family adversity and late adolescents’
health: The moderating role of the cortisol Awakening Response and daily worrying.
Paper presentation at the Society for Research in Child Development Biennial Meeting,
Austin, TX.
Miller, K. F., Margolin, G., Han, S. G., Rasmussen, H. F., & Hossepian, K. (May 2016). Adverse
childhood experiences get under the skin to influence adolescent physiology and young
adulthood health. Paper presentation at the 28th Association for Psychological Science
Annual Convention, Chicago, IL.

References

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CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 122
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CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 123
Construct Wave Reporter Measure Item Level
Emotional abuse 1 child PCC
Shouted, yelled, or
screamed at you
11+
1 child PCC Swore or cursed at you 11+
1 child PCC
Said s/he would send you
away or kick you out of the
house
1+
1 child PCC
Called you dumb or lazy or
some other name like that
11+
1 parent PCC
Shouted, yelled, or
screamed at your child
11+
1 parent PCC
Swore or cursed at your
child
11+
1 parent PCC
Said you would send your
child away or kick your child
out of the house
1+
1 parent PCC
Called your child dumb or
lazy or some other name
like that
11+
2 child PCC
Shouted, yelled, or
screamed at you
11+
2 child PCC Swore or cursed at you 11+
2 child PCC
Said he would send you
away or kick you out of the
house
1+
2 child PCC
Called you dumb or lazy or
some other name like that
11+
2 parent PCC
Shouted, yelled, or
screamed at your child
11+
2 parent PCC
Swore or cursed at your
child
11+
2 parent PCC
Said you would send your
child away or kick your child
out of the house
1+
2 parent PCC
Called your child dumb or
lazy or some other name
like that
11+
3/3a child PCC
Shouted, yelled, or
screamed at you
11+
3/3a child PCC Swore or cursed at you 11+
3/3a child PCC
Said he would send you
away or kick you out of the
house
1+
3/3a child PCC
Called you dumb or lazy or
some other name like that
11+
3/3a parent PCC
shouted, yelled, or
screamed at your child
11+
3/3a parent PCC
Swore or cursed at your
child
11+
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 124
3/3a parent PCC
Said you would send your
child away or kick your child
out of the house
1+
4/4a parent PCC
Called your child dumb or
lazy or some other name
like that
11+
4/4a child PCC
Shouted, yelled, or
screamed at you
11+
4/4a child PCC Swore or cursed at you 11+
4/4a child PCC
Said he would send you
away or kick you out of the
house
1+
4/4a child PCC
Called you dumb or lazy or
some other name like that
11+
4/4a parent PCC
Swore or cursed at your
child
11+
4/4a parent PCC
Called your child dumb or
lazy or some other name
like that
11+
4/4a parent PCC
Said something hurtful (e.g.
about your child’s
appearance or friends)
11+
4/4a parent PCC
Insulted or shamed your
child in front of others
11+
4a parent PCC
Told your child that she/he
is a failure or will be a
failure or won’t succeed at
anything
11+
4a parent PCC
Told your child that she/he
is not at good as someone
else
11+
4a parent PCC
Told your child that she/he
would not be part of the
family anymore
1+
5/5a child PCC
Shouted, yelled, or
screamed at you
11+
5/5a child PCC Swore or cursed at you 11+
5/5a child PCC
Said he would send you
away or kick you out of the
house
1+
5/5a child PCC
Called you dumb or lazy or
some other name like that
11+
5/5a parent PCC
past year, shouted, yelled,
or screamed at your child
11+
5/5a parent PCC
Past year, swore or cursed
at your child
11+
5/5a parent PCC
past year, called your child
dumb or lazy or some other
name like that
11+
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 125
5/5a parent PCC
past year said something
hurtful (e.g. about your
child's appearance or
friends)
11+
5/5a parent PCC
past year, insulted or
shamed your child in front
of others
11+
5/5a parent PCC
past year, told your child
that she/he is a failure or
will be a failure or won't
succeed at anything
11+
5/5a parent PCC
past year, told your child
that she/he would not be
part of the family anymore
1+
Notes:
PCC has both a parent and a child version; child completes PCC once about mother and once about
father.
PCC has 7 response options which measure the frequency with which the events occur (never, once,
twice, 3 to 5 times, 6 to 10 times, 11 to 20 times, and more than 20 times). Responses of "11+" indicate
participants endorsed either "11 to 20 times" or "more than 20 times."

Physical abuse 1 child PCC Shook you 1+
1 child PCC
Slapped you on the hand,
arm, or leg
1+
1 parent PCC Shook child 1+
1 parent PCC
slapped you child on the
hand, arm, or leg
1+
2 child PCC Shook you 1+
2 child PCC
Slapped you on the hand,
arm, or leg
1+
2 parent PCC Shook your child 1+
2 parent PCC
Slapped your child on the
hand, arm, or leg
1+
3/3a child PCC
Shook you (reporting things
both mothers and fathers
do when they're in an
argument with or
disciplining you)
1+
3/3a child PCC
Slapped you on the hand,
arm, or leg
1+
3/3a parent PCC Shook your child 1+
3/3a parent PCC
Slapped your child on the
hand, arm, or leg
1+
3a parent PCC
Pushed, grabbed or shoved
your child
1+
3a parent PCC
Twisted your child’s arm
behind her/his back
1+
4/4a parent PCC Shook child 1+
4/4a parent PCC Slapped your child 1+
4/4a parent PCC
Spanked your child with an
object
1+
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 126
4/4a parent PCC
Twisted your child’s arm
behind her/his back
1+
4/4a parent PCC
Pushed, grabbed or shoved
your child
1+
4/4a child
Child Home
Data
My dad pushed, grabbed,
or shoved me
1+
4/4a child
Child Home
Data
My mom pushed, grabbed,
or shoved me
1+
5/5a child PCC
Shook you (reporting things
both mothers and fathers
do when they're in an
argument with or
disciplining you)
1+
5/5a child PCC
Slapped you on the hand,
arm, or leg
1+
5/5a parent PCC past year, shook child 1+
5/5a parent PCC
past year, slapped your
child
1+
5/5a parent PCC
past year, spanked child
with hand or object
1+
5/5a parent PCC
past year, twisted your
child's arm behind his/her
back
1+
5/5a parent PCC
past year, pushed, grabbed,
or shoved your child
1+
Notes:
PCC has both a parent and a child version; child completes PCC once about mother and once about
father

Neglect 1 child Child's View
My mom and dad care if I
bathe or shower regularly
Never/rarely
1 child Child's View
My mom or dad forget to
pick me up from school, an
activity, or a friend’s house
Usually/always
2 child Child's View
My mom and dad care if I
bathe or shower regularly
Never/rarely
2 child Child's View
My mom or dad know
where I am if I am not at
home
Never/rarely
2 child Child's View
My mom or dad forget to
pick me up from school, an
activity, or a friend’s house
Usually/always
2 parent PCC
Were not able to make sure
your child got the food
he/she needed
1+
2 parent PCC
Were not able to make sure
your child got to a doctor or
hospital when he/she
needed it
1+
2 parent PCC
Were so drunk or high that
you had a problem taking
care of your child
1+
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 127
3/3a child Child's View
My mom or dad have
forgotten to pick me up from
school, an activity, or a
friend’s house
Usually/always
3/3a child Child's View
My mom and dad care if I
bathe or shower regularly
Never/rarely
3/3a child Child's View
My mom or dad know
where I am if I am not at
home
Never/rarely
3/3a parent PCC
Were not able to make sure
your child got the food
he/she needed
1+
3/3a parent PCC
Were not able to make sure
your child got to a doctor or
hospital when he/she
needed it
1+
3/3a parent PCC
Were so drunk or high that
you had a problem taking
care of your child
1+
4 child Child's View
My mom or dad have
forgotten to pick me up from
school, an activity, or a
friend’s house
Usually/always
Notes:
Neglect not measured after wave 4 due to adolescent age (often >18)

Sexual abuse 2 parent
Community
Violence
Has your child been
sexually assaulted in the
past year?
any
endorsement
3/3a parent
Community
Violence
Has your child been
sexually assaulted in the
past year?
any
endorsement
4/4a child YRBS
During your life, how many
times has a person EVER
forced you to do anything
sexual you did not want to
do?
any
endorsement
4/4a child YRBS
If you answered more than
0 Times for the previous
question, during the last
year, how many times has a
person forced you to do
anything sexual you did not
want to do?
any
endorsement
4/4a parent
Community
Violence
Has your child been
sexually assaulted in the
past year?
any
endorsement
5/5a child
How
Friends
Treat each
other
Touched me sexually when
I didn't want it
any
endorsement
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 128
5/5a child
How
Friends
Treat each
other
Forced me to have sex
when I didn't want to
any
endorsement
5/5a parent
Community
Violence
Has your child been
sexually assaulted in the
past year?
any
endorsement
5/5a child
How
Friends
Treat each
other
Threatened me in an
attempt to have sex
any
endorsement
Notes:
No questions measuring sexual abuse were asked at wave 1

Parental
separation/divorce
1 child Life Events Parents divorced
any
endorsement
1 child Life Events Parents separated
any
endorsement
2 child Life Events Parents divorced
any
endorsement
2 child Life Events Parents separated
any
endorsement
3/3a child Life Events Parents divorced
any
endorsement
3/3a child Life Events Parents separated
any
endorsement
4/4a child
Life Events
Checklist
Parents separated or
divorced
any
endorsement
5/5a child
Life Events
Checklist
Parents separated or
divorced
any
endorsement

Parent-to-parent
emotional abuse
1 child CTS
Insulted or swore at the
other person (mother or
father)
3 (1-3 scale)
1 child CTS
Threatened to hit or throw
something at the other
person (mother or father)
3 (1-3 scale)
1 parent DCI
screamed or yelled at your
spouse
2-4/month or
1+/week
1 parent DCI
insulted or swore at your
spouse
2-4/month or
1+/week
1 parent DCI called your spouse names
2-4/month or
1+/week
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 129
1 parent DCI ridiculed your spouse
2-4/month or
1+/week
2 child CTS
Insulted or swore at the
other person
3 (1-3 scale)
2 child CTS
Threatened to hit or throw
something at the other
person
3 (1-3 scale)
2 parent DCI
Within the last year have
you or your spouse:
screamed or yelled at your
spouse
2-4/month or
1+/week
2 parent DCI
Within the last year have
you or your spouse:insulted
or swore at your spouse
2-4/month or
1+/week
2 parent DCI
Within the last year have
you or your spouse:insulted
or shamed your spouse in
front of others
2-4/month or
1+/week
2 parent DCI
Within the last year have
you or your spouse:blamed
your spouse for your
problems
2-4/month or
1+/week
2 parent DCI
Within the last year have
you or your spouse:treated
your spouse like he/she
was stupid
2-4/month or
1+/week
2 parent DCI
Within the last year have
you or your
spouse:criticized your
spouse
2-4/month or
1+/week
2 parent DCI
Within the last year have
you or your spouse:called
your spouse names
2-4/month or
1+/week
2 parent DCI
Within the last year have
you or your
spouse:ridiculed your
spouse
2-4/month or
1+/week
2 parent DCI
Within the last year have
you or your
spouse:threatened to hit
your spouse or throw
something at him/her in
anger
2-4/month or
1+/week
2 parent DCI
Within the last year have
you or your
spouse:threatened your
spouse with a knife or gun
2-4/month or
1+/week
3 child CTS
Insulted or swore at the
other person (child
reporting how often parents
did this when arguing in the
past year
3 (1-3 scale)
3 child CTS
Threatened to hit or throw
something at the other
person
3 (1-3 scale)
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 130
3a child DCI
parent screamed or yelled
at parent
3 (1-3 scale)
3a child DCI
parent insulted or swore at
other parent
3 (1-3 scale)
3a child DCI
parent insulted or shamed
other parent in front of
others
3 (1-3 scale)
3a child DCI parent called parent names 3 (1-3 scale)
3a child DCI parent ridiculted parent 3 (1-3 scale)
3/3a parent DCI
Within the last year have
you or your spouse:
screamed or yelled at your
spouse
2-4/month or
1+/week
3/3a parent DCI
Within the last year have
you or your spouse:insulted
or swore at your spouse
2-4/month or
1+/week
3/3a parent DCI
Within the last year have
you or your spouse:insulted
or shamed your spouse in
front of others
2-4/month or
1+/week
3/3a parent DCI
Within the last year have
you or your spouse:blamed
your spouse for your
problems
2-4/month or
1+/week
3/3a parent DCI
Within the last year have
you or your spouse:treated
your spouse like he/she
was stupid
2-4/month or
1+/week
3/3a parent DCI
Within the last year have
you or your
spouse:criticized your
spouse
2-4/month or
1+/week
3/3a parent DCI
Within the last year have
you or your spouse:called
your spouse names
2-4/month or
1+/week
3/3a parent DCI
Within the last year have
you or your
spouse:ridiculed your
spouse
2-4/month or
1+/week
3/3a parent DCI
Within the last year have
you or your
spouse:threatened to hit
your spouse or throw
something at him/her in
anger
2-4/month or
1+/week
3/3a parent DCI
Within the last year have
you or your
spouse:threatened your
spouse with a knife or gun
2-4/month or
1+/week
4/4a parent DCI
Within the past year has
(you or) your partner
screamed or yelled at you
2-4/month or
1+/week
4/4a parent DCI
Within the past year has
(you or) your partner
2-4/month or
1+/week
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 131
insulted or swore at you or
your partner
4/4a parent DCI
Within the past year has
(you or) your partner
insulted or shamed you or
partner in front of others
2-4/month or
1+/week
4/4a parent DCI
Within the past year has
(you or) your partner
blamed you or partner for
his/her problems
2-4/month or
1+/week
4/4a parent DCI
Within the past year has
(you or) your partner
ordered you around
2-4/month or
1+/week
4/4a parent DCI
Within the past year has
(you or) your partner
criticized you
2-4/month or
1+/week
4/4a parent DCI
Within the past year has
(you or) your partner called
you names
2-4/month or
1+/week
4/4a parent DCI
Within the past year has
(you or) your partner
ridiculed you
2-4/month or
1+/week
4/4a parent DCI
Within the past year has
(you or) your partner
threatened to hit you, or
throw something at you, in
anger
2-4/month or
1+/week
4/4a parent DCI
(Within past year have you
or your partner) damaged a
household item, or some
part of your home, out of
anger towards you
Once or more
4/4a parent DCI
deliberately disposed of or
hid an important item of
yours
Once or more
4/4a parent DCI
left you and (you) were
unsure whether he/she was
going to return
Once or more
4/4a parent DCI
been jealous and
suspicious of your friends
Once or more
4/4a parent DCI purposely hurt your pet Once or more
4/4a parent DCI
purposely damaged or
destroyed your clothes, car,
and/or other personal
possessions
Once or more
4/4a parent DCI locked you out of the house Once or more
4/4a parent DCI
tried to prevent you from
seeing/talking to family or
friends
Once or more
4/4a parent DCI
restricted your use of the
car or telephone
Once or more
4/4a parent DCI
driven recklessly when
she/he was angry at you
Once or more
4/4a parent DCI
Within the past year has
(you or) your partner used
Once or more
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 132
humiliation to make you
have sex
4/4a parent DCI
Within the past year has
(you or) your partner used
threats to make you have
sex
Once or more
4 child CTS
Insulted or swore at the
other person (mother or
father)
3 (1-3 scale)
4 child CTS
Threatened to hit or throw
something at the other
person (mother or father)
3 (1-3 scale)
4a child DCI
screamed or yelled at your
other parent
2-4/month or
1+/week
4a child DCI
insulted or swore at your
other parent
2-4/month or
1+/week
4a child DCI
insulted or shamed your
other parent in front of
others
2-4/month or
1+/week
4a child DCI
treated your other parent
like s/he was stupid
2-4/month or
1+/week
5/5a child DCI
Within the past year has
your mother called your
father names
2-4/month or
1+/week
5/5a child DCI
Within the past year has
your mother ridiculed your
father
2-4/month or
1+/week
5/5a child DCI
Within the past year has
your mother screamed or
yelled at your father
2-4/month or
1+/week
5/5a child DCI
Within the past year has
your mother insulted or
swore at your father
2-4/month or
1+/week
5/5a child DCI
Within the past year has
your mother insulted or
shamed your father in front
of others
2-4/month or
1+/week
5/5a child DCI
Within the past year has
your father screamed or
yelled at your mother
2-4/month or
1+/week
5/5a child DCI
Within the past year has
your father insulted or
swore at your mother
2-4/month or
1+/week
5/5a child DCI
Within the pst year has your
father insulted or shamed
your mother in front of
others
2-4/month or
1+/week
5/5a child DCI
Within the past year has
your father called your
mother names
2-4/month or
1+/week
5/5a child DCI
Within the past year has
your father ridiculed your
mother
2-4/month or
1+/week
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 133
5/5a parent DCI
Within the past year have
you screamed or yelled at
your partner
2-4/month or
1+/week
5/5a parent DCI
Within the past year have
you insulted or swore at
your partner
2-4/month or
1+/week
5/5a parent DCI
Within the past year have
you insulted or shamed
your partner in front of
others
2-4/month or
1+/week
5/5a parent DCI
Within the past year have
you criticized your partner
2-4/month or
1+/week
5/5a parent DCI
Within the past year have
you called your partner
names
2-4/month or
1+/week
5/5a parent DCI
Within the past year have
you ridiculed your partner
2-4/month or
1+/week
5/5a parent DCI
deliberately disposed of or
hid an important item of
yours
Once or more
5/5a parent DCI
left you and (you) were
unsure whether he/she was
going to return
Once or more
5/5a parent DCI
been jealous and
suspicious of your friends
Once or more
5/5a parent DCI purposely hurt your pet Once or more
5/5a parent DCI
purposely damaged or
destroyed your clothes, car,
and/or other personal
possessions
Once or more
5/5a parent DCI locked you out of the house Once or more
5/5a parent DCI
tried to prevent you from
seeing/talking to family or
friends
Once or more
5/5a parent DCI
restricted your use of the
car or telephone
Once or more
5/5a parent DCI
driven recklessly when
she/he was angry at you
Once or more
5/5a parent DCI
Within the past year has
(you or) your partner used
humiliation to make you
have sex
Once or more
5/5a parent DCI
Within the past year has
(you or) your partner used
threats to make you have
sex
Once or more
Notes:
Parent completes all parent-to-parent aggression items twice: once about having done these things
(own perpepetration against partner) and once about partner having done these things (own
victimization by partner); child completes items once about each parent

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 134

Parent to parent
physical abuse
1 child CTS
Threw, smashed, hit, or
kicked something (mother
or father)
Once or more
1 child CTS
Threw something at the
other person
Once or more
1 child CTS
Pushed, grabbed, or
shoved the other person
Once or more
1 child CTS Slapped the other person Once or more
1 child CTS Kicked, bit, or hit with a fist Once or more
1 child CTS
Hit, or tried to hit, with
something
Once or more
1 parent DCI
physically twisted your
spouse’s arm
Once or more
1 parent DCI
pushed, grabbed, or shoved
your spouse
Once or more
1 parent DCI slapped your spouse Once or more
1 parent DCI burned your spouse Once or more
1 parent DCI shaken your spouse Once or more
1 parent DCI
thrown or tried to throw your
spouse bodily
Once or more
1 parent DCI
choked or strangled your
spouse
Once or more
1 parent DCI
kicked, bit or hit your
spouse with a fist
Once or more
1 parent DCI
hit your spouse, or tried to
hit your spouse, with
something
Once or more
1 parent DCI
beat up your spouse
(multiple blows)
Once or more
1 parent DCI
used a knife or a gun on
your spouse
Once or more
1 parent DCI
slammed your spouse
against the wall
Once or more
2 child CTS
Threw, smashed, hit, or
kicked something (mother
or father)
Once or more
2 child CTS
Threw something at the
other person
Once or more
2 child CTS
Pushed, grabbed, or
shoved the other person
Once or more
2 child CTS Slapped the other person Once or more
2 child CTS Kicked, bit, or hit with a fist Once or more
2 child CTS
Hit, or tried to hit, with
something
Once or more
2 parent DCI
physically twisted your
spouse’s arm
Once or more
2 parent DCI
pushed, grabbed, or shoved
your spouse
Once or more
2 parent DCI slapped your spouse Once or more
2 parent DCI burned your spouse Once or more
2 parent DCI shaken your spouse Once or more
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 135
2 parent DCI
thrown or tried to throw your
spouse bodily
Once or more
2 parent DCI
choked or strangled your
spouse
Once or more
2 parent DCI
kicked, bit or hit your
spouse with a fist
Once or more
2 parent DCI
hit your spouse, or tried to
hit your spouse, with
something
Once or more
2 parent DCI
beat up your spouse
(multiple blows)
Once or more
2 parent DCI
used a knife or a gun on
your spouse
Once or more
2 parent DCI
slammed your spouse
against the wall
Once or more
3 child CTS
Threw, smashed, hit, or
kicked something (mother
or father)
Once or more
3 child CTS
Threw something at the
other person
Once or more
3 child CTS
Pushed, grabbed, or
shoved the other person
Once or more
3 child CTS Slapped the other person Once or more
3 child CTS Kicked, bit, or hit with a fist Once or more
3 child CTS
Hit, or tried to hit, with
something
Once or more
3a child DCI
parent physically twisted
other parent's arm (all of
the following separate for
mom and dad)
Once or more
3a child DCI
parent
pushed/grabbed/shoved
other parent
Once or more
3a child DCI parent slapped other parent Once or more
3a child DCI parent burned other parent Once or more
3a child DCI parent shaken other parent Once or more
3a child DCI parent thrown other parent Once or more
3a child DCI
parent thrown object at
other parent
Once or more
3a child DCI
parent choked/strangled
other parent
Once or more
3a child DCI
parent kicked/bit/hit other
parent
Once or more
3a child DCI
parent hit other parent with
object
Once or more
3a child DCI parent beat up other parent Once or more
3a child DCI
parent slammed parent
against wall
Once or more
3a child DCI
used a knife or gun on
parent
Once or more
3/3a parent DCI
pushed, grabbed, or shoved
your spouse
Once or more
3/3a parent DCI slapped your spouse Once or more
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 136
3/3a parent DCI
physically forced sex on
your spouse
Once or more
3/3a parent DCI burned your spouse Once or more
3/3a parent DCI shaken your spouse Once or more
3/3a parent DCI
thrown or tried to throw your
spouse bodily
Once or more
3/3a parent DCI
thrown an object at your
spouse
Once or more
3/3a parent DCI
choked or strangled your
spouse
Once or more
3/3a parent DCI
kicked, bit or hit your
spouse with a fist
Once or more
3/3a parent DCI
hit your spouse, or tried to
hit your spouse, with
something
Once or more
3/3a parent DCI
beat up your spouse
(multiple blows)
Once or more
3/3a parent DCI
used a knife or a gun on
your spouse
Once or more
3/3a parent DCI
slammed your spouse
against the wall
Once or more
3/3a parent DCI
physically twisted your
spouse’s arm
Once or more
4 child CTS
Threw, smashed, hit, or
kicked something (mother
or father)
Once or more
4 child CTS
Threw something at the
other person
Once or more
4 child CTS
Pushed, grabbed, or
shoved the other person
Once or more
4 child CTS Slapped the other person Once or more
4 child CTS Kicked, bit, or hit with a fist Once or more
4 child CTS
Hit, or tried to hit, with
something
Once or more
4a child DCI
pushed, grabbed, or shoved
your other parent
Once or more
4a child DCI slapped your other parent Once or more
4a child DCI
burned your other parent
(not accidentally)
Once or more
4a child DCI
thrown or tried to throw your
other parent bodily
Once or more
4a child DCI
choked or strangled your
other parent
Once or more
4a child DCI
kicked, bit or hit your other
parent with a fist
Once or more
4a child DCI
hit your other parent, or
tried to hit your other
parent, with something
Once or more
4a child DCI
beat up your other parent
(multiple blows)
Once or more
4a child DCI
used a knife or a gun on
your other parent
Once or more
4a child DCI
slammed your other parent
against the wall
Once or more
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 137
4/4a parent DCI
Within the past year (you or
partner) physically twisted
(you or) your partner’s arm
Once or more
4/4a parent DCI
Within the past year (you or
partner) pushed, grabbed,
or shoved (you or) your
partner
Once or more
4/4a parent DCI
Within the past year (you or
partner) slapped your
partner
Once or more
4/4a parent DCI
Within the past year (you or
partner) physically forced
sex on (you or) your partner
Once or more
4/4a parent DCI
Within the past year (you or
partner) burned (you or)
your partner
Once or more
4/4a parent DCI
Within the past year (you or
partner) shaken (you or)
your partner
Once or more
4/4a parent DCI
Within the past year (you or
partner) thrown or tried to
throw (you or) your partner
bodily
Once or more
4/4a parent DCI
thrown an object at your
spouse
Once or more
4/4a parent DCI
Within the past year (you or
partner) choked or
strangled (you or) your
partner
Once or more
4/4a parent DCI
Within the past year (you or
partner) kicked, bit or hit
(you or) your partner with a
fist
Once or more
4/4a parent DCI
Within the past year (you or
partner) hit (you or) your
partner, or tried to hit (you
or) your partner, with
something
Once or more
4/4a parent DCI
Within the past year (you or
partner) beat up (you or)
your partner (multiple
blows)
Once or more
4/4a parent DCI
Within the past year (you or
partner) used a knife or a
gun on (you or) your partner
Once or more
4/4a parent DCI
Within the past year (you or
partner) slammed (you or)
your partner against the
wall
Once or more
4/4a parent DCI
Within the past year (you or
partner) physically
prevented you (you or) from
leaving an argument or
blocked your exit
Once or more
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 138
5/5a child DCI
pushed, grabbed, or shoved
your other parent
Once or more
5/5a child DCI slapped your other parent Once or more
5/5a child DCI
burned your other parent
(not accidentally)
Once or more
5/5a child DCI
thrown or tried to throw your
other parent bodily
Once or more
5/5a child DCI
choked or strangled your
other parent
Once or more
5/5a child DCI
kicked, bit or hit your other
parent with a fist
Once or more
5/5a child DCI
hit your other parent, or
tried to hit your other
parent, with something
Once or more
5/5a child DCI
beat up your other parent
(multiple blows)
Once or more
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 139
5/5a child DCI
used a knife or a gun on
your other parent
Once or more
5/5a child DCI
slammed your other parent
against the wall
Once or more
5/5a parent DCI
Within the past year have
you physically twisted your
partner's arm
Once or more
5/5a parent DCI
Within the past year have
you pushed, grabbed, or
shoved your partner
Once or more
5/5a parent DCI
Within the past year have
you slapped your partner
Once or more
5/5a parent DCI
Within the past year have
you physically forced sex
on your partner
Once or more
5/5a parent DCI
Within the past year have
you burned your partner
Once or more
5/5a parent DCI
Within the past year have
you shaken your partner
Once or more
5/5a parent DCI
Within the past year have
you thrown or tried to throw
your partner bodily
Once or more
5/5a parent DCI
Within the past year have
you choked or strangled
your partner
Once or more
5/5a parent DCI
Within the past year have
you kicked, bit or hit your
partner with a fist
Once or more
5/5a parent DCI
Within the past year have
you beat your partner up
(multiple blows)
Once or more
5/5a parent DCI
Within the past year have
you threatened your partner
with a knife or gun
Once or more
5/5a parent DCI
Within the past year have
you used a knife or a gun
on your partner
Once or more
5/5a parent DCI
Within the past year have
you slammed your partner
against the wall
Once or more
5/5a parent DCI
In the past year, how often
has your partner done
something to you out of
Once or more
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 140
anger that caused you
physical pain, bruises, or
bodily injury?
5/5a parent DCI
Aside from your child's
other parent, has anyone
else done the following to
you in the past year:
physically twisted your arm,
slapped you, etc...
Once or more
Notes:
Parent completes all parent-to-parent aggression items twice: once about having done these things
(own perpetration against partner) and once about partner having done these things (own victimization
by partner); child completes items once about each parent

Parent
alcohol/substance
abuse
1 parent DAST (whole measure)
cutoff score =
6
1 parent MAST (whole measure)
cutoff score =
6
2 parent LASC abusive drinking
3 (serious
problem) or 4
(extreme
problem)
2 parent LASC drug abuse
3 (serious
problem) or 4
(extreme
problem)
2 parent PCC
Were so drunk or high that
you had trouble taking care
of your child
Once or more
2 parent
Alcohol &
Drug
In the past year, have you
had any problem with
alcohol?
large
2 parent
Alcohol &
Drug
Currently, do you have any
problem with alcohol?
large
2 parent
Alcohol &
Drug
In the past year, has
anyone told you that you
have a problem with
alcohol?
large
2 parent
Alcohol &
Drug
In the past year, has your
spouse had any problem
with alcohol?
large
2 parent
Alcohol &
Drug
Currently does your spouse
have any problem with
alcohol?
large
2 parent
Alcohol &
Drug
In the past year, has
anyone told your spouse
that he/she has a problem
with alcohol?
large
2 parent
Alcohol &
Drug
Have you had a drink first
thing in the morning to
steady your nerves or get
rid of a hangover?
yes
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 141
2 parent
Alcohol &
Drug
Has your spouse had a
drink first thing in the
morning to steady your
nerves or get rid of a
hangover?
yes
2 parent
Alcohol &
Drug
Have you abused
prescription drugs?
yes
2 parent
Alcohol &
Drug
Has your spouse abused
prescription drugs?
yes
3/3a parent
Alcohol &
Drug
In the past year, have you
had any problem with
alcohol?
large
3/3a parent
Alcohol &
Drug
Currently, do you have any
problem with alcohol?
large
3/3a parent
Alcohol &
Drug
In the past year, has
anyone told you that you
have a problem with
alcohol?
large
3/3a parent
Alcohol &
Drug
In the past year, has your
spouse had any problem
with alcohol?
large
3/3a parent
Alcohol &
Drug
Currently does your spouse
have any problem with
alcohol?
large
3/3a parent
Alcohol &
Drug
In the past year, has
anyone told your spouse
that he/she has a problem
with alcohol?
large
3/3a parent
Alcohol &
Drug
Have you had a drink first
thing in the morning to
steady your nerves or get
rid of a hangover?
yes
3/3a parent
Alcohol &
Drug
Has your spouse had a
drink first thing in the
morning to steady your
nerves or get rid of a
hangover?
yes
3/3a parent
Alcohol &
Drug
Have you abused
prescription drugs?
yes
3/3a parent
Alcohol &
Drug
Has your spouse abused
prescription drugs?
yes
3/3a parent LASC abusive drinking
3 (serious
problem) or 4
(extreme
problem)
3/3a parent LASC drug abuse
3 (serious
problem) or 4
(extreme
problem)
3/3a child
Life event
checklist
Parent abusing or using too
much alcohol
yes
4/4a parent LASC abusive drinking
3 (serious
problem) or 4
(extreme
problem)
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 142
4/4a parent LASC drug abuse
3 (serious
problem) or 4
(extreme
problem)
4/4a parent
Alcohol &
Drug
In the past year, have you
had any problem with
alcohol?
large
4/4a parent
Alcohol &
Drug
Currently, do you have any
problem with alcohol?
large
4/4a parent
Alcohol &
Drug
In the past year, has
anyone told you that you
have a problem with
alcohol?
large
4/4a parent
Alcohol &
Drug
In the past year, has your
spouse had any problem
with alcohol?
large
4/4a parent
Alcohol &
Drug
Currently does your spouse
have any problem with
alcohol?
large
4/4a parent
Alcohol &
Drug
In the past year, has
anyone told your spouse
that he/she has a problem
with alcohol?
large
4/4a parent
Alcohol &
Drug
Have you had a drink first
thing in the morning to
steady your nerves or get
rid of a hangover?
yes
4/4a parent
Alcohol &
Drug
Has your spouse had a
drink first thing in the
morning to steady your
nerves or get rid of a
hangover?
yes
4/4a parent
Alcohol &
Drug
Have you abused
prescription drugs?
yes
4/4a parent
Alcohol &
Drug
Has your spouse abused
prescription drugs?
yes
4/4a child
Life event
checklist
Parent abusing or using too
much alcohol
yes
5/5a child
Life event
checklist
Parent abusing or using too
much alcohol
yes
5/5a parent
Alcohol &
Drug
In the past year, have you
had any problem with
alcohol?
large
5/5a parent
Alcohol &
Drug
Currently, do you have any
problem with alcohol?
large
5/5a parent
Alcohol &
Drug
In the past year, has
anyone told you that you
have a problem with
alcohol?
large
5/5a parent
Alcohol &
Drug
In the past year, has your
spouse had any problem
with alcohol?
large
5/5a parent
Alcohol &
Drug
Currently does your spouse
have any problem with
alcohol?
large
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 143
5/5a parent
Alcohol &
Drug
In the past year, has
anyone told your spouse
that he/she has a problem
with alcohol?
large
5/5a parent
Alcohol &
Drug
Have you had a drink first
thing in the morning to
steady your nerves or get
rid of a hangover?
yes
5/5a parent
Alcohol &
Drug
Has your spouse had a
drink first thing in the
morning to steady your
nerves or get rid of a
hangover?
yes
5/5a parent
Alcohol &
Drug
Have you abused
prescription drugs?
yes
5/5a parent
Alcohol &
Drug
Has your spouse abused
prescription drugs?
yes
5/5a parent LASC abusive drinking
3 (serious
problem) or 4
(extreme
problem)
5/5a parent LASC drug abuse
3 (serious
problem) or 4
(extreme
problem)

Parent mental
illness
1 parent SCL-90 Whole measure
above clinical
cutoff for any
subscale
2 parent SCL-90 Whole measure
above clinical
cutoff for any
subscale
3/3a parent SCL-90 Whole measure
above clinical
cutoff for any
subscale
4/4a parent SCL-90 Whole measure
above clinical
cutoff for any
subscale
5/51 parent SCL-90 Whole measure
above clinical
cutoff for any
subscale
Notes:
Clinical cutoff scores used are: SOM > 0.99, OC > 1.065, INT >0.875, DEP > 1.02, ANX > 0.855,
HOS > 0.90, PHOB > 0.595, PAR > 1.0, PSYC >0.515

Parent in prison 1 child Life Events Parent going to jail yes
1 parent
Life
Experiences
Survey
Detention in jail or
comparable insttution
yes
2 parent
Life
Experiences
Survey
Detention in jail or
comparable insttution
yes
2 child Life Events Parent going to jail yes
3/3a child Life Events Parents going to jail yes
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 144
3/3a child
Community
Violence
Have you seen/heard about
the police arrest or take
someone away in the past
year (If so, child reports
who and whether that
person is a family member)
Yes- parent
selected for
who
3/3a parent
Life events
survey
Detention in jail or
comparable insttution
yes
4/4a child Life Events Parents going to jail yes
4/4a child
Community
Violence
Have you seen/heard about
the police arrest or take
someone away in the past
year (If so, child reports
who and whether that
person is a family member)
Yes- parent
selected for
who
4/4a parent LES
(experienced in past year)
Detention in jail or
comparable institution
yes
5/5a child Life Events Parents going to jail yes
5/5a parent LES
(experienced in past year)
Detention in jail or
comparable institution
yes
5/5a child
Community
Violence
Have you seen/heard about
the police arrest or take
someone away in the past
year (If so, child reports
who and whether that
person is a family member)
Yes- parent
selected for
who

Feels unloved 1 child CDI Nobody really loves me
Nobody really
loves me OR I
am not sure if
anyone loves
me
1 child YSR I feel that no one loves me 2 (0-2)
2 child CDI Nobody really loves me
Nobody really
loves me OR I
am not sure if
anyone loves
me
2 child YSR I feel that no one loves me 2 (0-2)
3/3a child CDI Nobody really loves me
Nobody really
loves me OR I
am not sure if
anyone loves
me
3/3a child YSR I feel that no one loves me 2 (0-2)
4/4a child CDI Nobody really loves me
Nobody really
loves me OR I
am not sure if
anyone loves
me
4/4a child YSR I feel that no one loves me 2 (0-2)
5/5a child CDI Nobody really loves me
Nobody really
loves me OR I
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 145
am not sure if
anyone loves
me
5/5a child YSR I feel that no one loves me 2 (0-2)

Family financial
difficulty
1 parent LES
Major change in financial
status
Marked as
"Bad" + Had
"Extremely
Negative"
Effect
2 parent LES
Major change in financial
status
Marked as
"Bad" + Had
"Extremely
Negative"
Effect
3/3a parent LES
Major change in financial
status
Marked as
"Bad" + Had
"Extremely
Negative"
Effect
4/4a parent LES
Major change in financial
status
Marked as
"Bad" + Had
"Extremely
Negative"
Effect
4a parent
Economic
impact
How much financial stress
are you under
"An extreme
amount"
4a child
Economic
impact
How much financial stresss
is your family experiencing
"An extreme
amount"
4a child
Economic
impact
How much financial stress
are you personally
experiencing
"An extreme
amount"
5/5a parent LES
Major change in financial
status
Marked as
"Bad" + Had
"Extremely
Negative"
Effect
5/5a parent
Economic
impact
How much financial stress
are you under
"An extreme
amount"
5/5a child
Economic
impact
How much financial stresss
is your family experiencing
"An extreme
amount"
5/5a child
Economic
impact
How much financial stress
are you personally
experiencing
"An extreme
amount"

Social Isolation 1 child CDI
I have plenty of friends/I
have some friends but I
wish I had more/I do not
have any friends
I do not have
any friends
1 child YSR I am not liked by other kids
2 (on 0-2
scale)
2 child CDI
I have plenty of friends/I
have some friends but I
wish I had more/I do not
have any friends
I do not have
any friends
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 146
2 child YSR I am not liked by other kids
2 (on 0-2
scale)
3/3a child CDI
I have plenty of friends/I
have some friends but I
wish I had more/I do not
have any friends
I do not have
any friends
3/3a child YSR I am not liked by other kids
2 (on 0-2
scale)
4/4a child CDI
I have plenty of friends/I
have some friends but I
wish I had more/I do not
have any friends
I do not have
any friends
4/4a child YSR I am not liked by other kids
2 (on 0-2
scale)
5/5a child CDI
I have plenty of friends/I
have some friends but I
wish I had more/I do not
have any friends
I do not have
any friends
5/5a child YSR I am not liked by other kids
2 (on 0-2
scale)
5/5a child Alienation
I feel isolated from or
unwanted by peers
Agree strongly

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 147
Adolescent Life Stress

Participant Instructions:
For each of the following events, please indicate if it happened to you in the last year. If not, mark no and go on to the next item. If
yes, mark yes and also indicate whether the event was good or bad, and how much of an impact the event had on your life.

Event Did it
happen?
(circle one)
Type of
event
(circle one)
Impact or effect of event
on your life

No
Yes
è
Good Bad
No
effect
Some
effect
Moderat
e effect
Large
effect
1. Moving to new home No Yes Good Bad
2. New brother or sister No Yes Good Bad
3. Brother or sister left home No Yes Good Bad
4. Changing to a new school No Yes Good Bad
5. Serious illness or injury or hospitalization of family member or
close family friend
No Yes Good Bad
6. Death of family member or close family friend No Yes Good Bad
7. Serious illness or injury of friend your own age No Yes Good Bad
8. Death of friend your own age No Yes Good Bad
9. Parents separated or divorced No Yes Good Bad
10. Your parents argue with each other more than last year No Yes Good Bad
11. Your parents argue with each other less than last year No Yes Good Bad
12. Mother or father lost job No Yes Good Bad
13. Mother or father gone from home more than they used to be No Yes Good Bad
14. Parent getting into trouble with law No Yes Good Bad
15. Parent going to jail No Yes Good Bad
16. Parent getting new job No Yes Good Bad
17. Parent abusing or using too much alcohol No Yes Good Bad
18. Family having money problems No Yes Good Bad
19. Brother or sister got into trouble No Yes Good Bad
20. You got good grades No Yes Good Bad
21. You got special recognition for good grades No Yes Good Bad
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 148
Event Did it
happen?
(circle one)
Type of
event
(circle one)
Impact or effect of event
on your life

No
Yes
è
Good Bad
No
effect
Some
effect
Moderat
e effect
Large
effect
22. Close friend moved away or moved to different school No Yes Good Bad
23. You and your parents argue less than last year No Yes Good Bad
24. You and your parents argue more than last year. No Yes Good Bad
25. Failing a class or getting a bad grade on report card No Yes Good Bad
26. Getting into trouble with teacher or at school No Yes Good Bad
27. Serious personal illness or injury No Yes Good Bad
28. Failing to make an athletic team No Yes Good Bad
29. Being suspended from school No Yes Good Bad
30. Getting on athletic team No Yes Good Bad
31. Joining a new club No Yes Good Bad
32. Special recognition for performance in athletics, music,
acting, etc.
No Yes Good Bad
33. Trouble with friends No Yes Good Bad
34. Addition of new adult (step-parent, grandparent) to your
home
No Yes Good Bad
35. You were hospitalized No Yes Good Bad
36. You were in an accident or had an injury or surgery that did
not require hospitalization
No Yes Good Bad
37. You had an accident or illness that changed the way your
body looks
No Yes Good Bad
38. Change in your popularity with other kids No Yes Good Bad
39. You tried or used drugs or alcohol No Yes Good Bad
40. Pet died No Yes Good Bad
41. You had a noticeable change in height No Yes Good Bad
42. You had a change in weight No Yes Good Bad
43. You had an unwanted change in appearance (e.g., acne) No Yes Good Bad
44. You had a desired change in appearance No Yes Good Bad
45. You need to take medication for a long time No Yes Good Bad
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 149
Event Did it
happen?
(circle one)
Type of
event
(circle one)
Impact or effect of event
on your life

No
Yes
è
Good Bad
No
effect
Some
effect
Moderat
e effect
Large
effect
46. Have or had “special relationship” with boyfriend or girlfriend No Yes Good Bad
47. Broke up with boyfriend/girlfriend No Yes Good Bad
48. Felt pressured regarding sex No Yes Good Bad
49. Found new group of friends No Yes Good Bad
50. Have time-consuming activity, hobby, etc. No Yes Good Bad
51. Earning own money No Yes Good Bad
52. Thinking about college No Yes Good Bad
53. Started driving No Yes Good Bad
54. Change in thoughts about religion or religious practices. No Yes Good Bad
55. Involved in community service, school service or volunteer
project
No Yes Good Bad
56. Parents rely on you for work around house, care of
brothers/sisters etc.
No Yes Good Bad

CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 150
Family of Origin Aggression
Participant Instructions:
At any time in your life, did a parent or stepparent do the following out of anger to you…

None Once Twice
3-5
times
More than
6 times
1. Swore or cursed at you 0 1 2 3 4
2. Kicked you out of the house or car 0 1 2 3 4
3. Insulted you or told you that you were
not good enough or that you are a failure
0 1 2 3 4
4. Insulted or shamed you in front of
others
0 1 2 3 4
5. Threatened to stop supporting you
financially
0 1 2 3 4
6. Sent you an insulting or threatening
text or email, tweet, etc.
0 1 2 3 4
7. Posted something embarrassing or
upsetting about you online
0 1 2 3 4
8. Stole money or took something of
value from you (not as a punishment)
0 1 2 3 4
9. Slapped or shook you 0 1 2 3 4
10. Pushed, grabbed, or shoved you 0 1 2 3 4
11. Hit you with a hand or object 0 1 2 3 4
12. Threw something at you out of anger 0 1 2 3 4
13. Twisted or yanked your arm out of
anger
0 1 2 3 4
14. Left bruise or visible injury 0 1 2 3 4
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 151
Romantic Attachment

Note: Items 1-18 measure attachment-related anxiety. Items 19-36 measure attachment-related avoidance. Item sequence is
randomized for participants.

Participant Instructions:
The statements below concern how you feel in emotionally intimate relationships. We are interested in how you generally experience
relationships, not just in what is happening in a current relationship. Respond to each statement by clicking a circle to indicate how
much you agree or disagree with the statement.

Strongly
disagree

Agree/
disagree

Strongly
agree
1. I'm afraid that I will lose my partner's love. 1 2 3 4 5 6 7
2. I often worry that my partner will not want to stay with me. 1 2 3 4 5 6 7
3. I often worry that my partner doesn't really love me. 1 2 3 4 5 6 7
4. I worry that romantic partners won’t care about me as much as I care about them. 1 2 3 4 5 6 7
5. I often wish that my partner's feelings for me were as strong as my feelings for him
or her.
1 2 3 4 5 6 7
6. I worry a lot about my relationships. 1 2 3 4 5 6 7
7. When my partner is out of sight, I worry that he or she might become interested in
someone else.
1 2 3 4 5 6 7
8. When I show my feelings for romantic partners, I'm afraid they will not feel the
same about me.
1 2 3 4 5 6 7
9. I rarely worry about my partner leaving me. 1 2 3 4 5 6 7
10. My romantic partner makes me doubt myself. 1 2 3 4 5 6 7
11. I do not often worry about being abandoned. 1 2 3 4 5 6 7
12. I find that my partner(s) don't want to get as close as I would like. 1 2 3 4 5 6 7
13. Sometimes romantic partners change their feelings about me for no apparent
reason.
1 2 3 4 5 6 7
14. My desire to be very close sometimes scares people away. 1 2 3 4 5 6 7
CHILDHOOD ADVERSITY, PHYSIOLOGY, AND HEALTH 152
15. I'm afraid that once a romantic partner gets to know me, he or she won't like who I
really am.
1 2 3 4 5 6 7
16. It makes me mad that I don't get the affection and support I need from my partner. 1 2 3 4 5 6 7
17. I worry that I won't measure up to other people. 1 2 3 4 5 6 7
18. My partner only seems to notice me when I’m angry. 1 2 3 4 5 6 7
19. I prefer not to show a partner how I feel deep down. 1 2 3 4 5 6 7
20. I feel comfortable sharing my private thoughts and feelings with my partner. 1 2 3 4 5 6 7
21. I find it difficult to allow myself to depend on romantic partners. 1 2 3 4 5 6 7
22. I am very comfortable being close to romantic partners. 1 2 3 4 5 6 7
23. I don't feel comfortable opening up to romantic partners. 1 2 3 4 5 6 7
24. I prefer not to be too close to romantic partners. 1 2 3 4 5 6 7
25. I get uncomfortable when a romantic partner wants to be very close. 1 2 3 4 5 6 7
26. I find it relatively easy to get close to my partner. 1 2 3 4 5 6 7
27. It's not difficult for me to get close to my partner. 1 2 3 4 5 6 7
28. I usually discuss my problems and concerns with my partner. 1 2 3 4 5 6 7
29. It helps to turn to my romantic partner in times of need. 1 2 3 4 5 6 7
30. I tell my partner just about everything. 1 2 3 4 5 6 7
31. I talk things over with my partner. 1 2 3 4 5 6 7
32. I am nervous when partners get too close to me. 1 2 3 4 5 6 7
33. I feel comfortable depending on romantic partners. 1 2 3 4 5 6 7
34. I find it easy to depend on romantic partners. 1 2 3 4 5 6 7
35. It's easy for me to be affectionate with my partner. 1 2 3 4 5 6 7
36. My partner really understands me and my needs. 1 2 3 4 5 6 7

Abstract (if available)

Abstract Paper 1 Abstract. Objectives: Childhood adversity is a risk factor for the development of obesity in adulthood. ❧ Dysregulated hypothalamic-pituitary-adrenal (HPA) activity, which has been associated separately with both adverse childhood experiences and obesity, has been posited as a mechanism by which stressful experiences influence body mass index (BMI)

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Asset Metadata

Creator Kazmierski, Kelly Frances Miller (author)

Core Title Effects of childhood adversity on physiology and health in emerging adulthood

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Psychology

Publication Date 06/17/2019

Defense Date 05/01/2019

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag attachment avoidance,body mass index,childhood adversity,cortisol awakening response,Couples,emerging adulthood,family aggression,HPA reactivity,Inflammation,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Margolin, Gayla (committee chair), Brekke, John (committee member), John, Richard (committee member), Saxbe, Darby (committee member)

Creator Email kazmierski.kelly@gmail.com,kfmiller@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-175270

Unique identifier UC11660521

Identifier etd-Kazmierski-7492.pdf (filename),usctheses-c89-175270 (legacy record id)

Legacy Identifier etd-Kazmierski-7492.pdf

Dmrecord 175270

Document Type Dissertation

Format application/pdf (imt)

Rights Kazmierski, Kelly Frances Miller

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA