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This study examines the prospective associations of alcohol and drug misuse with suicidal behaviors among service members who have left active duty. We also evaluate potential moderating effects of other risk factors and whether substance misuse signals increased risk of transitioning from thinking about to attempting suicide.
Method
US Army veterans and deactivated reservists (N = 6,811) completed surveys in 2016–2018 (T1) and 2018–2019 (T2). Weights-adjusted logistic regression was used to estimate the associations of binge drinking, smoking/vaping, cannabis use, prescription drug abuse, illicit drug use, alcohol use disorder (AUD), and drug use disorder (DUD) at T1 with suicide ideation, plan, and attempt at T2. Interaction models tested for moderation of these associations by sex, depression, and recency of separation/deactivation. Suicide attempt models were also fit in the subgroup with ideation at T1 (n = 1,527).
Results
In models controlling for socio-demographic characteristics and prior suicidality, binge drinking, cannabis use, prescription drug abuse, illicit drug use, and AUD were associated with subsequent suicidal ideation (AORs = 1.42–2.60, ps < .01). Binge drinking, AUD, and DUD were associated with subsequent suicide plan (AORs = 1.23–1.95, ps < .05). None of the substance use variables had a main effect on suicide attempt; however, interaction models suggested certain types of drug use predicted attempts among those without depression. Additionally, the effects of smoking/vaping and AUD differed by sex. Substance misuse did not predict the transition from ideation to attempt.
Conclusions
Alcohol and drug misuse are associated with subsequent suicidal behaviors in this population. Awareness of differences across sex and depression status may inform suicide risk assessment.
Identification of genetic risk factors may inform the prevention and treatment of posttraumatic stress disorder (PTSD). This study evaluates the associations of polygenic risk scores (PRS) with patterns of posttraumatic stress symptoms following combat deployment.
Method
US Army soldiers of European ancestry (n = 4900) provided genomic data and ratings of posttraumatic stress symptoms before and after deployment to Afghanistan in 2012. Latent growth mixture modeling was used to model posttraumatic stress symptom trajectories among participants who provided post-deployment data (n = 4353). Multinomial logistic regression models tested independent associations between trajectory membership and PRS for PTSD, major depressive disorder (MDD), schizophrenia, neuroticism, alcohol use disorder, and suicide attempt, controlling for age, sex, ancestry, and exposure to potentially traumatic events, and weighted to account for uncertainty in trajectory classification and missing data.
Results
Participants were classified into low-severity (77.2%), increasing-severity (10.5%), decreasing-severity (8.0%), and high-severity (4.3%) posttraumatic stress symptom trajectories. Standardized PTSD-PRS and MDD-PRS were associated with greater odds of membership in the high-severity v. low-severity trajectory [adjusted odds ratios and 95% confidence intervals, 1.23 (1.06–1.43) and 1.18 (1.02–1.37), respectively] and the increasing-severity v. low-severity trajectory [1.12 (1.01–1.25) and 1.16 (1.04–1.28), respectively]. Additionally, MDD-PRS was associated with greater odds of membership in the decreasing-severity v. low-severity trajectory [1.16 (1.03–1.31)]. No other associations were statistically significant.
Conclusions
Higher polygenic risk for PTSD or MDD is associated with more severe posttraumatic stress symptom trajectories following combat deployment. PRS may help stratify at-risk individuals, enabling more precise targeting of treatment and prevention programs.
Personality traits (e.g. neuroticism) and the social environment predict risk for internalizing disorders and suicidal behavior. Studying these characteristics together and prospectively within a population confronted with high stressor exposure (e.g. U.S. Army soldiers) has not been done, yet could uncover unique and interactive predictive effects that may inform prevention and early intervention efforts.
Methods
Five broad personality traits and social network size were assessed via self-administered questionnaires among experienced soldiers preparing for deployment (N = 4645) and new soldiers reporting for basic training (N = 6216). Predictive models examined associations of baseline personality and social network variables with recent distress disorders or suicidal behaviors assessed 3- and 9-months post-deployment and approximately 5 years following enlistment.
Results
Among the personality traits, elevated neuroticism was consistently associated with increased mental health risk following deployment. Small social networks were also associated with increased mental health risk following deployment, beyond the variance accounted for by personality. Limited support was found for social network size moderating the association between personality and mental health outcomes. Small social networks also predicted distress disorders and suicidal behavior 5 years following enlistment, whereas unique effects of personality traits on these more distal outcomes were rare.
Conclusions
Heightened neuroticism and small social networks predict a greater risk for negative mental health sequelae, especially following deployment. Social ties may mitigate adverse impacts of personality traits on psychopathology in some contexts. Early identification and targeted intervention for these distinct, modifiable factors may decrease the risk of distress disorders and suicidal behavior.
Problematic anger is frequently reported by soldiers who have deployed to combat zones. However, evidence is lacking with respect to how anger changes over a deployment cycle, and which factors prospectively influence change in anger among combat-deployed soldiers.
Methods
Reports of problematic anger were obtained from 7298 US Army soldiers who deployed to Afghanistan in 2012. A series of mixed-effects growth models estimated linear trajectories of anger over a period of 1–2 months before deployment to 9 months post-deployment, and evaluated the effects of pre-deployment factors (prior deployments and perceived resilience) on average levels and growth of problematic anger.
Results
A model with random intercepts and slopes provided the best fit, indicating heterogeneity in soldiers' levels and trajectories of anger. First-time deployers reported the lowest anger overall, but the most growth in anger over time. Soldiers with multiple prior deployments displayed the highest anger overall, which remained relatively stable over time. Higher pre-deployment resilience was associated with lower reports of anger, but its protective effect diminished over time. First- and second-time deployers reporting low resilience displayed different anger trajectories (stable v. decreasing, respectively).
Conclusions
Change in anger from pre- to post-deployment varies based on pre-deployment factors. The observed differences in anger trajectories suggest that efforts to detect and reduce problematic anger should be tailored for first-time v. repeat deployers. Ongoing screening is needed even for soldiers reporting high resilience before deployment, as the protective effect of pre-deployment resilience on anger erodes over time.
Definition of disorder subtypes may facilitate precision treatment for posttraumatic stress disorder (PTSD). We aimed to identify PTSD subtypes and evaluate their associations with genetic risk factors, types of stress exposures, comorbidity, and course of PTSD.
Methods
Data came from a prospective study of three U.S. Army Brigade Combat Teams that deployed to Afghanistan in 2012. Soldiers with probable PTSD (PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition ≥31) at three months postdeployment comprised the sample (N = 423) for latent profile analysis using Gaussian mixture modeling and PTSD symptom ratings as indicators. PTSD profiles were compared on polygenic risk scores (derived from external genomewide association study summary statistics), experiences during deployment, comorbidity at three months postdeployment, and persistence of PTSD at nine months postdeployment.
Results
Latent profile analysis revealed profiles characterized by prominent intrusions, avoidance, and hyperarousal (threat-reactivity profile; n = 129), anhedonia and negative affect (dysphoric profile; n = 195), and high levels of all PTSD symptoms (high-symptom profile; n = 99). The threat-reactivity profile had the most combat exposure and the least comorbidity. The dysphoric profile had the highest polygenic risk for major depression, and more personal life stress and co-occurring major depression than the threat-reactivity profile. The high-symptom profile had the highest rates of concurrent mental disorders and persistence of PTSD.
Conclusions
Genetic and trauma-related factors likely contribute to PTSD heterogeneity, which can be parsed into subtypes that differ in symptom expression, comorbidity, and course. Future studies should evaluate whether PTSD typology modifies treatment response and should clarify distinctions between the dysphoric profile and depressive disorders.
Unit cohesion may protect service member mental health by mitigating effects of combat exposure; however, questions remain about the origins of potential stress-buffering effects. We examined buffering effects associated with two forms of unit cohesion (peer-oriented horizontal cohesion and subordinate-leader vertical cohesion) defined as either individual-level or aggregated unit-level variables.
Methods
Longitudinal survey data from US Army soldiers who deployed to Afghanistan in 2012 were analyzed using mixed-effects regression. Models evaluated individual- and unit-level interaction effects of combat exposure and cohesion during deployment on symptoms of post-traumatic stress disorder (PTSD), depression, and suicidal ideation reported at 3 months post-deployment (model n's = 6684 to 6826). Given the small effective sample size (k = 89), the significance of unit-level interactions was evaluated at a 90% confidence level.
Results
At the individual-level, buffering effects of horizontal cohesion were found for PTSD symptoms [B = −0.11, 95% CI (−0.18 to −0.04), p < 0.01] and depressive symptoms [B = −0.06, 95% CI (−0.10 to −0.01), p < 0.05]; while a buffering effect of vertical cohesion was observed for PTSD symptoms only [B = −0.03, 95% CI (−0.06 to −0.0001), p < 0.05]. At the unit-level, buffering effects of horizontal (but not vertical) cohesion were observed for PTSD symptoms [B = −0.91, 90% CI (−1.70 to −0.11), p = 0.06], depressive symptoms [B = −0.83, 90% CI (−1.24 to −0.41), p < 0.01], and suicidal ideation [B = −0.32, 90% CI (−0.62 to −0.01), p = 0.08].
Conclusions
Policies and interventions that enhance horizontal cohesion may protect combat-exposed units against post-deployment mental health problems. Efforts to support individual soldiers who report low levels of horizontal or vertical cohesion may also yield mental health benefits.
Whereas genetic susceptibility increases the risk for major depressive disorder (MDD), non-genetic protective factors may mitigate this risk. In a large-scale prospective study of US Army soldiers, we examined whether trait resilience and/or unit cohesion could protect against the onset of MDD following combat deployment, even in soldiers at high polygenic risk.
Methods
Data were analyzed from 3079 soldiers of European ancestry assessed before and after their deployment to Afghanistan. Incident MDD was defined as no MDD episode at pre-deployment, followed by a MDD episode following deployment. Polygenic risk scores were constructed from a large-scale genome-wide association study of major depression. We first examined the main effects of the MDD PRS and each protective factor on incident MDD. We then tested the effects of each protective factor on incident MDD across strata of polygenic risk.
Results
Polygenic risk showed a dose–response relationship to depression, such that soldiers at high polygenic risk had greatest odds for incident MDD. Both unit cohesion and trait resilience were prospectively associated with reduced risk for incident MDD. Notably, the protective effect of unit cohesion persisted even in soldiers at highest polygenic risk.
Conclusions
Polygenic risk was associated with new-onset MDD in deployed soldiers. However, unit cohesion – an index of perceived support and morale – was protective against incident MDD even among those at highest genetic risk, and may represent a potent target for promoting resilience in vulnerable soldiers. Findings illustrate the value of combining genomic and environmental data in a prospective design to identify robust protective factors for mental health.
Investigations of drinking behavior across military deployment cycles are scarce, and few prospective studies have examined risk factors for post-deployment alcohol misuse.
Methods
Prevalence of alcohol misuse was estimated among 4645 US Army soldiers who participated in a longitudinal survey. Assessment occurred 1–2 months before soldiers deployed to Afghanistan in 2012 (T0), upon their return to the USA (T1), 3 months later (T2), and 9 months later (T3). Weights-adjusted logistic regression was used to evaluate associations of hypothesized risk factors with post-deployment incidence and persistence of heavy drinking (HD) (consuming 5 + alcoholic drinks at least 1–2×/week) and alcohol or substance use disorder (AUD/SUD).
Results
Prevalence of past-month HD at T0, T2, and T3 was 23.3% (s.e. = 0.7%), 26.1% (s.e. = 0.8%), and 22.3% (s.e. = 0.7%); corresponding estimates for any binge drinking (BD) were 52.5% (s.e. = 1.0%), 52.5% (s.e. = 1.0%), and 41.3% (s.e. = 0.9%). Greater personal life stress during deployment (e.g., relationship, family, or financial problems) – but not combat stress – was associated with new onset of HD at T2 [per standard score increase: adjusted odds ratio (AOR) = 1.20, 95% CI 1.06–1.35, p = 0.003]; incidence of AUD/SUD at T2 (AOR = 1.54, 95% CI 1.25–1.89, p < 0.0005); and persistence of AUD/SUD at T2 and T3 (AOR = 1.30, 95% CI 1.08–1.56, p = 0.005). Any BD pre-deployment was associated with post-deployment onset of HD (AOR = 3.21, 95% CI 2.57–4.02, p < 0.0005) and AUD/SUD (AOR = 1.85, 95% CI 1.27–2.70, p = 0.001).
Conclusions
Alcohol misuse is common during the months preceding and following deployment. Timely intervention aimed at alleviating/managing personal stressors or curbing risky drinking might reduce risk of alcohol-related problems post-deployment.
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