Pre-deployment threat learning predicts increased risk for post-deployment insomnia: Evidence from the Marine Resiliency Study

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Highlights

  • Examined pre-deployment threat learning as a predictor of post-deployment insomnia.

  • Sample consisted of 814 active-duty servicemen.

  • Higher pre-deployment fear conditioning predicted greater post-deployment insomnia.

  • The effect was partially mediated by post-deployment nightmares.

  • The effect was observed for subjective but not physiological measures of fear.

Abstract

Insomnia is a common and impairing consequence of military deployment, but little is known about pre-deployment risk factors for post-deployment insomnia. Abnormal threat learning tendencies are commonly observed in individuals with insomnia and maladaptive responses to stress have been implicated in the development of insomnia, suggesting that threat learning could be an important risk factor for post-deployment insomnia. Here, we examined pre-deployment threat learning as a predictor of post-deployment insomnia and the potential mechanisms underlying this effect. Male servicemembers (N = 814) completed measures of insomnia, psychiatric symptoms, and a threat learning task before and after military deployment. Threat learning indices that differentiated participants with versus withoutinsomnia at post-deployment were tested as pre-deployment predictors of post-deployment insomnia. Post-deployment insomnia was linked to elevations on several threat learning indices at post-deployment, but only higher threat conditioning, as indexed by higher threat expectancy ratings to the danger cue, emerged as a pre-deployment predictor of post-deployment insomnia. This effect was independent of combat exposure levels and partially mediated by greater post-deployment nightmares. The tendency to acquire stronger expectations of aversive events following encounters with danger cues may increase risk for post-deployment insomnia, in part due to the development of more severe nightmares.

Introduction

Clinically significant insomnia, defined broadly as difficulties falling or staying asleep that interfere with daily functioning, is a common condition that can have serious adverse effects on physical and mental health (Roth, 2007; Cunnington et al., 2013). Among other consequences, insomnia has been linked to increased risk for new mental health conditions (Pigeon et al., 2017), exacerbation and/or poorer management of chronic medical conditions (Fernandez-Mendoza & Vgontzas, 2013), reduced quality of life (Olfson et al., 2018; Katz & McHorney, 2002), and premature death (Dew et al., 2003; Kripke et al., 2002). The burden of insomnia is particularly concerning among Veterans, where prevalence rates are as high as 50% and 2–3 times higher than the general population (Mysliwiec et al., 2013; Martin et al., 2017; Colvonen et al., 2020; Byrne et al., 2021). Moreover, rates of Veteran insomnia have been growing at an alarming rate in recent decades (Campbell & Riggs, 2015; Mysliwiec et al., 2013), with Veterans deployed in post-9/11 conflicts appearing particularly prone to sleep problems (Colvonoen et al., 2020).

Not surprisingly, the vast majority of Veteran insomnia cases are thought to develop following military deployment (Bramoweth & Germain, 2013). While there has been a great deal of research into the consequences of post-deployment insomnia (e.g., Hermes & Rosenheck, 2014; Kartal et al., 2021; Pigeon et al., 2012; Pigeon et al., 2013), surprisingly little research has been devoted to identifying predictors of post-deployment insomnia (Hughes et al., 2018). Indeed, only one previous investigation to our knowledge has attempted to predict post-deployment insomnia from pre-deployment data (Miller et al., 2021). Identifying factors that predispose Veterans for post-deployment insomnia is the first step toward understanding its etiology and preventing its development, which is critical given the cascade of adverse mental and physical consequences that may arise from post-deployment sleep issues (Hermes & Rosenheck, 2014; Kartal et al., 2021; Pigeon et al., 2012, 2013).

One factor that may be particularly important for predicting post-deployment insomnia is threat learning. Broadly speaking, threat learning refers to the ability to flexibly form, maintain, and extinguish fear responses to a particular stimulus depending on whether the stimulus has, has not been, or is no longer paired with an intrinsically aversive event. Military deployment can involve numerous instances of new threat learning where previously neutral activities (e.g., driving) are paired with aversive consequences (e.g., an IED explosion). Soldiers with a propensity for acquiring excessive, inflexible, or unnecessary threat responses may be more chronically aroused following aversive deployment experiences and thus be at higher risk for developing the persistent sleep-related arousal that often contribute to sleep problems among Veterans (Capaldi et al., 2011; Wright et al., 2011; Wallace et al., 2011; Bramoweth & Germain, 2013). This proposition is also consistent with prevailing models of post-deployment insomnia, which suggest that individuals who react excessively to or cope poorly with deployment-related stressors are at elevated risk for developing insomnia (Bramoweth & Germain, 2013; Hughes et al., 2018).

Additionally, there is a well-established link between disruptions in sleep-related processes (e.g., less total sleep time, lower proportion of rapid eye movement [REM] sleep) and abnormal threat learning (Straus et al., 2017; Colvonen et al., 2019; Schenker et al., 2021). While most studies have examined the effect of sleep on subsequent threat learning, evidence of the opposite pattern has been found in the few laboratory studies that have examined it – namely, that differences in threat learning constructs (e.g., heightened fear conditioning) predict changes in sleep quality the following night (Marshall et al., 2014; Straus et al., 2018). Heightened stress reactivity more broadly has also been linked to the development of insomnia, as individuals who experience more frequent cognitive intrusions and utilize more maladaptive coping strategies following stressful events have been found to be at elevated risk for future sleep problems (Drake et al., 2014; Pillai et al., 2014). Together, these data offer preliminary evidence that individual differences in threat learning could bias individuals toward or away from disrupted sleep following the stressful, combat-related experiences that often occur during military deployment.

Given the potential involvement of threat learning in the development of deployment-related insomnia, we investigated whether pre-deployment levels of threat learning could predict the incidence of post-deployment insomnia in a large longitudinal dataset of active-duty military members (i.e., the Marine Resiliency Study; Baker et al., 2012). Our study had three aims. Our first aim was to identify cross-sectional differences between participants with versus without insomnia at post-deployment across three key areas of threat learning: Threat conditioning (i.e., higher responding to a cue associated with an aversive stimulus), safety learning (i.e., lower responding to a cue that is not associated with an aversive stimulus), and fear extinction (i.e., lower responding to a cue that was formerly associated with an aversive unconditioned stimulus [US]). Consistent with research linking elevated threat learning to insomnia, we predicted that participants with insomnia would show greater fear conditioning, less safety learning, and less fear extinction at post-deployment relative to participants without insomnia.

Our second aim was to investigate whether pre-deployment levels of each insomnia-related difference in threat learning could predict post-deployment insomnia. This was done to test whether threat learning variables that were linked to insomnia at post-deployment acted as risk factors for insomnia or were merely consequences of post-deployment insomnia. If post-deployment insomnia was linked to a threat learning variable both cross-sectionally (i.e., at post-deployment) and longitudinally (i.e., at pre-deployment), it would suggest that abnormalities in that threat learning variable preceded the development of insomnia, consistent with the abnormality acting as a risk factor for post-deployment insomnia. However, if a threat learning variable was only linked to post-deployment insomnia cross-sectionally, it would imply that abnormalities in that threat learning variable arose after the development of insomnia (i.e., post-deployment), consistent with the abnormality being a consequence of post-deployment insomnia. Given the theory that heightened stress reactivity confers increased vulnerability for deployment-related insomnia (Bramoweth & Germain, 2013; Hughes et al., 2018), we hypothesized that threat learning variables would act as risk factors for post-deployment insomnia, as observed by levels of threat responses (fear potentiated startle, self-reported US expectancy) at pre-deployment predicting greater risk for insomnia at post-deployment.

Finally, our third aim was to examine potential moderators and mediators of the longitudinal threat learning-insomnia relationship. The purpose of this aim was to better understand the mechanisms that contribute to post-deployment insomnia. We hypothesized that the effects of pre-deployment threat learning on post-deployment insomnia would be moderated by the degree of combat exposure (i.e., higher combat exposure would be associated with a stronger effect) and mediated by higher levels of three post-deployment arousal symptoms (hypervigilance, startle, and nightmares). These hypotheses are consistent with theoretical models of post-deployment insomnia, wherein the propensity for heightened stress reactivity interacts with combat-related stress to produce excessive arousal, which in turn interferes with sleep (Bramoweth & Germain, 2013; Hughes et al., 2018).

Section snippets

Participants

Three infantry battalions of Marines and Navy Corpsmen (N = 1387) stationed in Southern California were enrolled in a longitudinal study of mental and physical health changes related to military deployment. One battalion (n = 546) did not deploy during the course of the study and was not included in the present analyses. Additionally, 21 participants did not complete the fear conditioning task at post-deployment, three failed to provide expectancy rating data for the first phase of the task,

Demographics

Demographic and clinical differences between participants with versus without post-deployment insomnia are shown in Table 1. At post-deployment, 21.5% of participants met criteria for insomnia disorder while 15.3% met criteria for lifetime insomnia when assessed at pre-deployment. Regarding rates of PTSD, 5.9% met criteria for PTSD at pre-deployment while 20.3% met criteria for PTSD at post-deployment. Prior to deployment, 86.7% of the sample reported having experienced a criterion A trauma as

Discussion

The purpose of the present study was to examine pre-deployment threat learning as a predictor of post-deployment insomnia and to test potential moderators and mediators of this effect. Consistent with expectations, post-deployment insomnia was associated with increased self-reported threat expectancy and fear potentiated startle to the conditioned danger cue, both across acquisition and during early extinction. Unexpectedly, only self-reported threat expectancy during acquisition at

Conclusions

The purpose of the present study was to investigate the prospective value of pre-deployment threat learning in predicting post-deployment insomnia, as well as examine whether this effect was moderated by combat exposure and mediated by post-deployment arousal symptoms. Consistent with expectations, service members with versus without insomnia showed a number of differences in threat learning at post-deployment. Moreover, one of these threat learning differences – higher pre-deployment threat

CRediT authorship contribution statement

Christopher Hunt: Conceptualization, Formal analysis. Daniel M. Stout: Conceptualization, Formal analysis. Dean Acheson: Conceptualization, Formal analysis. Peter J. Colvonen: Conceptualization, Formal analysis. Caroline M.Nievergelt: Data collection and analysis. Kate A.Yurgil: Data collection and analysis. Dewleen G. Baker: Funding acquisition, Writing – review & editing. Victoria B. Risbrough: Conceptualization, Formal analysis.

Declaration of competing interest

None.

Acknowledgments

Support for this work includes NIMH P50MH096889 (DGB, VBR), DOD (VBR) VA Merit Awards and Research Scientist Award (VBR 5I01BX004312; 1I21BX005872; IK6BX006186), the Office of Academic Affiliations Advanced Fellowship Program in Mental Illness Research and Treatment (CH), and the Center of Excellence for Stress and Mental Health (CH, DA, DS, DGB, CMN, VBR). The Marine Resilience Study was originally funded by project No. SDR 09–0128 (Drs Baker and Risbrough) from the Veterans Administration

References (62)

  • P.M. Nicassio et al.

    The phenomenology of the pre-sleep state: The development of the pre-sleep arousal scale

    Behaviour Research and Therapy

    (1985)
  • T. Nielsen et al.

    Nightmares: A new neurocognitive model

    Sleep Medicine Reviews

    (2007)
  • M.L. Perlis et al.

    Etiology and pathophysiology of insomnia

    Principles and Practice of Sleep Medicine

    (2005)
  • W.R. Pigeon et al.

    Longitudinal relationships of insomnia, nightmares, and PTSD severity in recent combat veterans

    Journal of Psychosomatic Research

    (2013)
  • D. Riemann et al.

    The hyperarousal model of insomnia: A review of the concept and its evidence

    Sleep Medicine Reviews

    (2010)
  • M.T. Schenker et al.

    Sleep and fear conditioning, extinction learning and extinction recall: A systematic review and meta-analysis of polysomnographic findings

    Sleep Medicine Reviews

    (2021)
  • L.D. Straus et al.

    Sleep deprivation disrupts recall of conditioned fear extinction

    Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

    (2017)
  • L.D. Straus et al.

    REM sleep and safety signal learning in posttraumatic stress disorder: A preliminary study in military veterans

    Neurobiology of Stress

    (2018)
  • U. Voderholzer et al.

    The impact of increasing sleep restriction on cortisol and daytime sleepiness in adolescents

    Neuroscience Letters

    (2012)
  • D.M. Wallace et al.

    Insomnia characteristics and clinical correlates in operation enduring freedom/operation Iraqi freedom veterans with post-traumatic stress disorder and mild traumatic brain injury: An exploratory study

    Sleep Medicine

    (2011)
  • V.T. Warren et al.

    Human fear extinction and return of fear using reconsolidation update mechanisms: The contribution of on-line expectancy ratings

    Neurobiology of Learning and Memory

    (2014)
  • K.P. Wright et al.

    Influence of sleep deprivation and circadian misalignment on cortisol, inflammatory markers, and cytokine balance

    Brain, Behavior, and Immunity

    (2015)
  • D.G. Baker et al.

    Predictors of risk and resilience for posttraumatic stress disorder among ground combat Marines: Methods of the marine resiliency study

    (2012)
  • A.T. Beck et al.

    Beck anxiety inventory [database record]

    (1988)
  • I. Bjorøy et al.

    The prevalence of insomnia subtypes in relation to demographic characteristics, anxiety, depression, alcohol consumption and use of hypnotics

    Frontiers in Psychology

    (2020)
  • D.D. Blake et al.

    The development of a clinician-administered PTSD scale

    Journal of Traumatic Stress

    (1995)
  • A.D. Bramoweth et al.

    Deployment-related insomnia in military personnel and veterans

    Current Psychiatry Reports

    (2013)
  • S.P. Byrne et al.

    Prevalence, risk correlates, and health comorbidities of insomnia in US military veterans: Results from the 2019–2020 National Health and Resilience in Veterans Study

    Journal of Clinical Sleep Medicine

    (2021)
  • R. Campbell et al.

    The role of psychological symptomatology and social support in the academic adjustment of previously deployed student veterans

    Journal of American College Health

    (2015)
  • V.F. Capaldi et al.

    Sleep disruptions among returning combat veterans from Iraq and Afghanistan

    Military Medicine

    (2011)
  • P.J. Colvonen et al.

    Prevalence rates and correlates of insomnia disorder in post-9/11 veterans enrolling in VA healthcare

    Sleep

    (2020)
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