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1.  Post-traumatic stress disorder associated with life-threatening motor vehicle collisions in the WHO World Mental Health Surveys 
BMC Psychiatry  2016;16:257.
Motor vehicle collisions (MVCs) are a substantial contributor to the global burden of disease and lead to subsequent post-traumatic stress disorder (PTSD). However, the relevant literature originates in only a few countries, and much remains unknown about MVC-related PTSD prevalence and predictors.
Data come from the World Mental Health Survey Initiative, a coordinated series of community epidemiological surveys of mental disorders throughout the world. The subset of 13 surveys (5 in high income countries, 8 in middle or low income countries) with respondents reporting PTSD after life-threatening MVCs are considered here. Six classes of predictors were assessed: socio-demographics, characteristics of the MVC, childhood family adversities, MVCs, other traumatic experiences, and respondent history of prior mental disorders. Logistic regression was used to examine predictors of PTSD. Mental disorders were assessed with the fully-structured Composite International Diagnostic Interview using DSM-IV criteria.
Prevalence of PTSD associated with MVCs perceived to be life-threatening was 2.5 % overall and did not vary significantly across countries. PTSD was significantly associated with low respondent education, someone dying in the MVC, the respondent or someone else being seriously injured, childhood family adversities, prior MVCs (but not other traumatic experiences), and number of prior anxiety disorders. The final model was significantly predictive of PTSD, with 32 % of all PTSD occurring among the 5 % of respondents classified by the model as having highest PTSD risk.
Although PTSD is a relatively rare outcome of life-threatening MVCs, a substantial minority of PTSD cases occur among the relatively small proportion of people with highest predicted risk. This raises the question whether MVC-related PTSD could be reduced with preventive interventions targeted to high-risk survivors using models based on predictors assessed in the immediate aftermath of the MVCs.
Electronic supplementary material
The online version of this article (doi:10.1186/s12888-016-0957-8) contains supplementary material, which is available to authorized users.
PMCID: PMC4957291  PMID: 27449995
Posttraumatic stress disorder; PTSD; Motor vehicle collision
2.  Association of DSM-IV Posttraumatic Stress Disorder With Traumatic Experience Type and History in the World Health Organization World Mental Health Surveys 
JAMA psychiatry  2017;74(3):270-281.
Previous research has documented significant variation in the prevalence of posttraumatic stress disorder (PTSD) depending on the type of traumatic experience (TE) and history of TE exposure, but the relatively small sample sizes in these studies resulted in a number of unresolved basic questions.
To examine disaggregated associations of type of TE history with PTSD in a large cross-national community epidemiologic data set.
The World Health Organization World Mental Health surveys assessed 29 TE types (lifetime exposure, age at first exposure) with DSM-IV PTSD that was associated with 1 randomly selected TE exposure (the random TE) for each respondent. Surveys were administered in 20 countries (n = 34 676 respondents) from 2001 to 2012. Data were analyzed from October 1, 2015, to September 1, 2016.
Prevalence of PTSD assessed with the Composite International Diagnostic Interview.
Among the 34 676 respondents (55.4% [SE, 0.6%] men and 44.6% [SE, 0.6%] women; mean [SE] age, 43.7 [0.2] years), lifetime TE exposure was reported by a weighted 70.3% of respondents (mean [SE] number of exposures, 4.5 [0.04] among respondents with any TE). Weighted (by TE frequency) prevalence of PTSD associated with random TEs was 4.0%. Odds ratios (ORs) of PTSD were elevated for TEs involving sexual violence (2.7; 95% CI, 2.0–3.8) and witnessing atrocities (4.2; 95% CI, 1.0–17.8). Prior exposure to some, but not all, same-type TEs was associated with increased vulnerability (eg, physical assault; OR, 3.2; 95% CI, 1.3–7.9) or resilience (eg, participation in sectarian violence; OR, 0.3; 95% CI, 0.1–0.9) to PTSD after the random TE. The finding of earlier studies that more general history of TE exposure was associated with increased vulnerability to PTSD across the full range of random TE types was replicated, but this generalized vulnerability was limited to prior TEs involving violence, including participation in organized violence (OR, 1.3; 95% CI, 1.0–1.6), experience of physical violence (OR, 1.4; 95% CI, 1.2–1.7), rape (OR, 2.5; 95% CI, 1.7–3.8), and other sexual assault (OR, 1.6; 95% CI, 1.1–2.3).
The World Mental Health survey findings advance understanding of the extent to which PTSD risk varies with the type of TE and history of TE exposure. Previous findings about the elevated PTSD risk associated with TEs involving assaultive violence was refined by showing agreement only for repeated occurrences. Some types of prior TE exposures are associated with increased resilience rather than increased vulnerability, connecting the literature on TE history with the literature on resilience after adversity. These results are valuable in providing an empirical rationale for more focused investigations of these specifications in future studies.
PMCID: PMC5441566  PMID: 28055082
3.  Genomewide Association Studies of Posttraumatic Stress Disorder in Two Cohorts of US Army Soldiers 
JAMA psychiatry  2016;73(7):695-704.
Posttraumatic stress disorder (PTSD) is a prevalent, serious public health concern, particularly in the military. The identification of genetic risk factors for PTSD may provide important insights into the biological basis of vulnerability and comorbidity.
To discover genetic loci associated with lifetime PTSD risk in two cohorts from the Army Study To Assess Risk and Resilience in Servicemembers (Army STARRS).
Design, Setting and Participants
Two coordinated genomewide association studies of mental health in the US military: New Soldier Study (NSS, N=3167 cases and 4607 trauma-exposed controls) and Pre/Post Deployment Study (PPDS, N=947 cases and 4969 trauma-exposed controls). The primary analysis compared lifetime DSM-IV PTSD cases to trauma-exposed controls without lifetime PTSD.
Main Outcomes and Measures
Association analyses were conducted for PTSD using logistic regression models within each of 3 ancestral groups (European, African, Latino) by study and then meta-analyzed. Heritability and genetic correlation and pleiotropy with other psychiatric and immune-related disorders were estimated.
We observed a genomewide significant locus in ANKRD55 on chromosome 5 (rs159572; odds ratio [OR] = 1.62, p-value =2.43×10−8; adjusted for cumulative trauma exposure [AOR] = 1.68, p-value = 1.18×10−8) in the African American samples from NSS. We also observed a genomewide significant locus in or near ZNF626 on chromosome 19 (rs11085374; OR = 0.77, p-value = 4.59 ×10−8) in the European American samples from NSS. We did not find similar results for either SNP in the corresponding ancestry group from the PPDS sample, or in other ancestral groups or trans-ancestral meta-analyses. SNP-based heritability was non-significant, and no significant genetic correlations were observed between PTSD and six mental disorders and nine immune-related disorders. Significant evidence of pleiotropy was observed between PTSD and rheumatoid arthritis and, to a lesser extent, psoriasis.
Conclusions and Relevance
In the largest GWAS of PTSD to date, involving a US military sample, we found limited evidence of association for specific loci. Further efforts are needed to replicate the genomewide significant association with ANKRD55 – associated in prior research with several autoimmune and inflammatory disorders – and to clarify the nature of the genetic overlap observed between PTSD and rheumatoid arthritis and psoriasis.
PMCID: PMC4936936  PMID: 27167565
genomewide association; genetic; immune; inflammatory; military; posttraumatic stress disorder; pleiotropy; risk; trauma
4.  A genome-wide gene-by-trauma interaction study of alcohol misuse in two independent cohorts identifies PRKG1 as a risk locus 
Molecular psychiatry  2017;10.1038/mp.2017.24.
Traumatic life experiences are associated with alcohol use problems, an association that is likely to be moderated by genetic predisposition. To understand these interactions, we conducted a gene-by-environment genome-wide interaction study (GEWIS) of alcohol use problems in two independent samples, the Army STARRS (ASTARRS, N=16,361) and the Yale-Penn (N=8,084) cohorts. Because the two cohorts were assessed using different instruments, we derived separate dimensional alcohol misuse scales and applied a proxy-phenotype study design. In African-American subjects, we identified an interaction of PRKG1 rs1729578 with trauma exposure in the ASTARRS cohort and replicated its interaction with trauma exposure in the Yale-Penn cohort (discovery-replication meta-analysis: z=5.64, p=1.69*10−8). PRKG1 encodes cGMP-dependent protein kinase 1, which is involved in learning, memory, and circadian rhythm regulation. Considering the loci identified in stage-1 that showed same effect directions in stage-2, the gene ontology (GO) enrichment analysis showed several significant results, including calcium-activated potassium channels (GO:0016286; p=2.30*10−5), cognition (GO:0050890; p=1.90*10−6), locomotion (GO:0040011; p=6.70*10−5), and Stat3 protein regulation (GO:0042517; p=6.4*10−5). To our knowledge, this is the largest GEWIS performed in psychiatric genetics, and the first GEWIS examining risk for alcohol misuse. Our results add to a growing body of literature highlighting the dynamic impact of experience on individual genetic risk.
PMCID: PMC5589475  PMID: 28265120
5.  Mental disorders among college students in the WHO World Mental Health Surveys 
Psychological medicine  2016;46(14):2955-2970.
Although mental disorders are significant predictors of educational attainment throughout the entire educational career, most research on mental disorders among students has focused on the primary and secondary school years.
The World Health Organization World Mental Health Surveys were used to examine the associations of mental disorders with college entry and attrition by comparing college students (n = 1,572) and nonstudents in the same age range (18–22; n = 4,178), including nonstudents who recently left college without graduating (n = 702) based on surveys in 21 countries (4 low/lower-middle income, 5 upper middle-income, 1 lower-middle or upper-middle at the times of two different surveys, and 11 high income). Lifetime and 12-month prevalence and age-of-onset of DSM-IV anxiety, mood, behavioural and substance disorders were assessed with the Composite International Diagnostic Interview.
One-fifth (20.3%) of college students had 12-month DSM-IV/CIDI disorders. 83.1% of these cases had pre-matriculation onsets. Disorders with pre-matriculation onsets were more important than those with post-matriculation onsets in predicting subsequent college attrition, with substance disorders and, among women, major depression the most important such disorders. Only 16.4% of students with 12-month disorders received any 12-month healthcare treatment for their mental disorders.
Mental disorders are common among college students, have onsets that mostly occur prior to college entry, in the case of pre-matriculation disorders are associated with college attrition, and are typically untreated. Detection and effective treatment of these disorders early in the college career might reduce attrition and improve educational and psychosocial functioning.
PMCID: PMC5129654  PMID: 27484622
Mental Illness; College; Education; College Dropout; College attrition; Epidemiology
6.  The cross-national epidemiology of social anxiety disorder: Data from the World Mental Health Survey Initiative 
BMC Medicine  2017;15:143.
There is evidence that social anxiety disorder (SAD) is a prevalent and disabling disorder. However, most of the available data on the epidemiology of this condition originate from high income countries in the West. The World Mental Health (WMH) Survey Initiative provides an opportunity to investigate the prevalence, course, impairment, socio-demographic correlates, comorbidity, and treatment of this condition across a range of high, middle, and low income countries in different geographic regions of the world, and to address the question of whether differences in SAD merely reflect differences in threshold for diagnosis.
Data from 28 community surveys in the WMH Survey Initiative, with 142,405 respondents, were analyzed. We assessed the 30-day, 12-month, and lifetime prevalence of SAD, age of onset, and severity of role impairment associated with SAD, across countries. In addition, we investigated socio-demographic correlates of SAD, comorbidity of SAD with other mental disorders, and treatment of SAD in the combined sample. Cross-tabulations were used to calculate prevalence, impairment, comorbidity, and treatment. Survival analysis was used to estimate age of onset, and logistic regression and survival analyses were used to examine socio-demographic correlates.
SAD 30-day, 12-month, and lifetime prevalence estimates are 1.3, 2.4, and 4.0% across all countries. SAD prevalence rates are lowest in low/lower-middle income countries and in the African and Eastern Mediterranean regions, and highest in high income countries and in the Americas and the Western Pacific regions. Age of onset is early across the globe, and persistence is highest in upper-middle income countries, Africa, and the Eastern Mediterranean. There are some differences in domains of severe role impairment by country income level and geographic region, but there are no significant differences across different income level and geographic region in the proportion of respondents with any severe role impairment. Also, across countries SAD is associated with specific socio-demographic features (younger age, female gender, unmarried status, lower education, and lower income) and with similar patterns of comorbidity. Treatment rates for those with any impairment are lowest in low/lower-middle income countries and highest in high income countries.
While differences in SAD prevalence across countries are apparent, we found a number of consistent patterns across the globe, including early age of onset, persistence, impairment in multiple domains, as well as characteristic socio-demographic correlates and associated psychiatric comorbidities. In addition, while there are some differences in the patterns of impairment associated with SAD across the globe, key similarities suggest that the threshold for diagnosis is similar regardless of country income levels or geographic location. Taken together, these cross-national data emphasize the international clinical and public health significance of SAD.
PMCID: PMC5535284  PMID: 28756776
Social anxiety disorder; Social phobia; Cross-national epidemiology; World Mental Health Survey Initiative
7.  Associations between DSM-IV mental disorders and subsequent onset of arthritis 
We investigated the associations between DSM-IV mental disorders and subsequent arthritis onset, with and without mental disorder comorbidity adjustment. We aimed to determine whether specific types of mental disorders and increasing numbers of mental disorders were associated with the onset of arthritis later in life.
Data were collected using face-to-face household surveys, conducted in 19 countries from different regions of the world (n = 52,095). Lifetime prevalence and age at onset of 16 DSM-IV mental disorders were assessed retrospectively with the World Health Organization (WHO) Composite International Diagnostic Interview (WHO-CIDI). Arthritis was assessed by self-report of lifetime history of arthritis and age at onset. Survival analyses estimated the association of initial onset of mental disorders with subsequent onset of arthritis.
After adjusting for comorbidity, the number of mood, anxiety, impulse-control, and substance disorders remained significantly associated with arthritis onset showing odds ratios (ORs) ranging from 1.2 to 1.4. Additionally, the risk of developing arthritis increased as the number of mental disorders increased from one to five or more disorders.
This study suggests links between mental disorders and subsequent arthritis onset using a large, multi-country dataset. These associations lend support to the idea that it may be possible to reduce the severity of mental disorder-arthritis comorbidity through early identification and effective treatment of mental disorders.
PMCID: PMC4884652  PMID: 26944393
arthritis; comorbidity; mental disorders; substance abuse
8.  Post-Traumatic Stress Disorder and other mental disorders in the general population after Lorca’s earthquakes, 2011 (Murcia, Spain): A cross-sectional study 
PLoS ONE  2017;12(7):e0179690.
To describe the prevalence and severity of mental disorders and to examine differences in risk among those with and without a lifetime history prior to a moderate magnitude earthquake that took place in Lorca (Murcia, Spain) at roughly the mid-point (on May 11, 2011) of the time interval in which a regional epidemiological survey was already being carried out (June 2010 –May 2012).
The PEGASUS-Murcia project is a cross-sectional face-to-face interview survey of a representative sample of non-institutionalized adults in Murcia. Main outcome measures are prevalence and severity of anxiety, mood, impulse and substance disorders in the 12 months previous to the survey, assessed using the Composite International Diagnostic Interview (CIDI 3.0). Sociodemographic variables, prior history of any mental disorder and earthquake-related stressors were entered as independent variables in a logistic regression analysis.
A total number of 412 participants (response rate: 71%) were interviewed. Significant differences in 12-month prevalence of mental disorders were found in Lorca compared to the rest of Murcia for any (12.8% vs 16.8%), PTSD (3.6% vs 0.5%) and other anxiety disorders (5.3% vs 9.2%) (p≤ 0.05 for all). No differences were found for 12-month prevalence of any mood or any substance disorder. The two major predictors for developing a 12-month post-earthquake mental disorder were a prior mental disorder and the level of exposure. Other risk factors included female sex and low-average income.
PTSD and other mental disorders are commonly associated with earthquake disasters. Prior mental disorders and the level of exposure to the earthquakes are the most important for the development of a consequent mental disorder and this recognition may help to identify those individuals that may most benefit from specific therapeutic intervention.
PMCID: PMC5516965  PMID: 28723949
9.  Days out of role due to common physical and mental conditions in Portugal: results from the WHO World Mental Health Survey 
BJPsych Open  2017;3(1):15-21.
One important aspect of the societal burden of mental disorders is the extent to which these problems cause disability.
To assess days out of role associated with commonly occurring mental disorders in comparison with physical disorders in Portugal.
National cross-sectional survey, with home interviews carried out with 3849 adult (aged 18+) respondents (57.3% response rate).
Twelve-month prevalence for any mental disorder was 21.8%, any physical disorder 55.1% and any disorder 63.1%, with an average of 2.3 disorders per respondent with a disorder. Close to one out of every 10 respondents (9.2%) reported at least one day totally out of role in the past month (median of 6.4 days/any). The 18 conditions accounted for 78.2% of all days out of role, with 20.2% because of mental disorders and 59.2% because of physical disorders.
Mental disorders account for a substantial proportion of all role disability in the Portuguese population. Early detection and intervention would have a positive societal effect. Owing to highly frequent comorbidity, simultaneous management of mental and physical disorder comorbidities is advised for greater effect.
Declaration of interest
R.C.K. in the past 3 years has been a consultant for Hoffmann-La Roche Inc., Johnson & Johnson’s Wellness and Prevention, Inc. and Sanofi-Aventis Groupe. He has served on advisory boards for Mensante Corporation, Johnson & Johnson Services, Inc., Lake Nona Life Project and U.S. Preventive Medicine, Inc. He is a co-owner of DataStat, Inc.
Copyright and usage
© The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.
PMCID: PMC5295249
10.  Age of Onset and Lifetime Projected Risk of Psychotic Experiences: Cross-National Data From the World Mental Health Survey 
Schizophrenia Bulletin  2016;42(4):933-941.
Given the early age of onset (AOO) of psychotic disorders, it has been assumed that psychotic experiences (PEs) would have a similar early AOO. The aims of this study were to describe (a) the AOO distribution of PEs, (b) the projected lifetime risk of PEs, and (c) the associations of PE AOO with selected PE features.
Data came from the WHO World Mental Health (WMH) surveys. A total of 31 261 adult respondents across 18 countries were assessed for lifetime prevalence of PE. Projected lifetime risk (at age 75 years) was estimated using a 2-part actuarial method. AOO distributions were described for the observed and projected estimates. We examined associations of AOO with PE type metric and annualized PE frequency.
Projected lifetime risk for PEs was 7.8% (SE = 0.3), slightly higher than lifetime prevalence (5.8%, SE = 0.2). The median (interquartile range; IQR) AOO based on projected lifetime estimates was 26 (17–41) years, indicating that PEs commence across a wide age range. The AOO distributions for PEs did not differ by sex. Early AOO was positively associated with number of PE types (F = 14.1, P < .001) but negatively associated with annualized PE frequency rates (F = 8.0, P < .001).
While most people with lifetime PEs have first onsets in adolescence or young adulthood, projected estimates indicate that nearly a quarter of first onsets occur after age 40 years. The extent to which late onset PEs are associated with (a) late onset mental disorders or (b) declining cognitive and/or sensory function need further research.
PMCID: PMC4903064  PMID: 27038468
epidemiology; psychotic experiences; age of onset; lifetime prevalence; World Mental Health Survey
11.  Risk Factors, Methods, and Timing of Suicide Attempts Among US Army Soldiers 
JAMA psychiatry  2016;73(7):741-749.
Suicide attempts in the US Army have risen in the past decade. Understanding the association between suicide attempts and deployment, as well as method and timing of suicide attempts, can assist in developing interventions.
To examine suicide attempt risk factors, methods, and timing among soldiers currently deployed, previously deployed, and never deployed at the time this study was conducted.
This longitudinal, retrospective cohort study of Regular Army–enlisted soldiers on active duty from 2004 through 2009 used individual-level person-month records to examine risk factors (sociodemographic, service related, and mental health), method, and time of suicide attempt by deployment status (never, currently, and previously deployed). Administrative data for the month before each of 9650 incident suicide attempts and an equal-probability sample of 153 528 control person-months for other soldiers were analyzed using a discrete-time survival framework.
Suicide attempts and career, mental health, and demographic predictors were obtained from administrative and medical records.
Of the 9650 enlisted soldiers who attempted suicide, 86.3% were male, 68.4% were younger than 30 years, 59.8% were non-Hispanic white, 76.5%were high school educated, and 54.7% were currently married. The 40.4% of enlisted soldiers who had never been deployed (n = 12 421 294 person-months) accounted for 61.1% of enlisted soldiers who attempted suicide (n = 5894 cases). Risk among those never deployed was highest in the second month of service (103 per 100 000 person-months). Risk among soldiers on their first deployment was highest in the sixth month of deployment (25 per 100 000 person-months). For those previously deployed, risk was highest at 5 months after return (40 per 100 000 person-months). Currently and previously deployed soldiers were more likely to attempt suicide with a firearm than those never deployed (currently deployed: OR, 4.0; 95% CI, 2.9–5.6; previously deployed: OR, 2.7; 95% CI, 1.8–3.9). Across deployment status, suicide attempts were more likely among soldiers who were women (currently deployed: OR, 3.4; 95% CI, 3.0–4.0; previously deployed: OR, 1.5; 95% CI, 1.4–1.7; and never deployed: OR, 2.4; 95% CI, 2.3–2.6), in their first 2 years of service (currently deployed: OR, 1.9; 95% CI, 1.5–2.3; previously deployed: OR, 2.2; 95% CI, 1.9–2.7; and never deployed: OR, 3.1; 95% CI, 2.7–3.6), and had a recently received a mental health diagnosis in the previous month (currently deployed: OR, 29.8; 95% CI, 25.0–35.5; previously deployed: OR, 22.2; 95% CI, 20.1–24.4; and never deployed: OR, 15.0; 95% CI, 14.2–16.0). Among soldiers with 1 previous deployment, odds of a suicide attempt were higher for those who screened positive for depression or posttraumatic stress disorder after return from deployment and particularly at follow-up screening, about 4 to 6 months after deployment (depression: OR, 1.4; 95% CI, 1.1–1.9; posttraumatic stress disorder: OR, 2.4; 95% CI, 2.1–2.8).
Identifying the timing and risk factors for suicide attempt in soldiers requires consideration of environmental context, individual characteristics, and mental health. These factors can inform prevention efforts.
PMCID: PMC4937827  PMID: 27224848
12.  Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) 
Molecular psychiatry  2016;10.1038/mp.2016.110.
The 2013 U.S. Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are known not to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male non-deployed Regular U.S. Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naïve Bayes, random forests, support vector regression, elastic net penalized regression) were explored. 41.5% of Army suicides in 2004-2009 occurred among the 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100,000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded.
PMCID: PMC5247428  PMID: 27431294
Army; machine learning; military; predictive modeling; risk assessment; suicide
13.  Major depressive disorder subtypes to predict long-term course 
Depression and anxiety  2014;31(9):765-777.
Variation in course of major depressive disorder (MDD) is not strongly predicted by existing subtype distinctions. A new subtyping approach is considered here.
Two data mining techniques, ensemble recursive partitioning and Lasso generalized linear models (GLMs) followed by k-means cluster analysis, are used to search for subtypes based on index episode symptoms predicting subsequent MDD course in the World Mental Health (WMH) Surveys. The WMH surveys are community surveys in 16 countries. Lifetime DSM-IV MDD was reported by 8,261 respondents. Retrospectively reported outcomes included measures of persistence (number of years with an episode; number of with an episode lasting most of the year) and severity (hospitalization for MDD; disability due to MDD).
Recursive partitioning found significant clusters defined by the conjunctions of early onset, suicidality, and anxiety (irritability, panic, nervousness-worry-anxiety) during the index episode. GLMs found additional associations involving a number of individual symptoms. Predicted values of the four outcomes were strongly correlated. Cluster analysis of these predicted values found three clusters having consistently high, intermediate, or low predicted scores across all outcomes. The high-risk cluster (30.0% of respondents) accounted for 52.9-69.7% of high persistence and severity and was most strongly predicted by index episode severe dysphoria, suicidality, anxiety, and early onset. A total symptom count, in comparison, was not a significant predictor.
Despite being based on retrospective reports, results suggest that useful MDD subtyping distinctions can be made using data mining methods. Further studies are needed to test and expand these results with prospective data.
PMCID: PMC5125445  PMID: 24425049
Epidemiology; Depression; Anxiety/Anxiety Disorders; Suicide/Self Harm; Panic Attacks
14.  Epidemiology of anxiety disorders: from surveys to nosology and back 
On the basis of epidemiological survey findings, anxiety disorders are the most prevalent mental disorders around the world and are associated with significant comorbidity and morbidity. Such surveys rely on advances in psychiatric nosology and may also contribute usefully to revisions of the nosology. There are a number of questions at the intersection of psychiatric epidemiology and nosology. This review addresses the following: What is the prevalence of anxiety disorders and how do we best explain cross-national differences in prevalence estimates? What are the optimal diagnostic criteria for anxiety disorders, and how can epidemiological data shed light on this question? What are the comorbidities of anxiety disorders, and how do we best understand the high comorbidities seen in these conditions? What is the current treatment gap for anxiety disorders, and what are the implications of current understandings of psychiatric epidemiology and nosology for policy-making relevant to anxiety disorders? Here, we emphasize that anxiety disorders are the most prevalent of the psychiatric conditions, and that rather than merely contrasting cross-national prevalence in anxiety disorders, it is more productive to delineate cross-national themes that emerge about the epidemiology of these conditions. We discuss that optimizing diagnostic criteria for anxiety disorders is an iterative process to which epidemiological data can make a crucial contribution. Additionally, high comorbidity in anxiety disorders is not merely artefactual; it provides key opportunities to explore pathways to mental disorders and to intervene accordingly. Finally, work on the epidemiology and nosology of anxiety disorders has provided a number of important targets for mental health policy and for future integrative work to move between bench and bedside, as well as between clinic and community.
PMCID: PMC5573557
anxiety disorder; classification; comorbidity; epidemiology; generalized anxiety disorder; nosology
Depression and anxiety  2014;32(1):3-12.
The prevalence of suicide among U.S. Army soldiers has risen dramatically in recent years. Prior studies suggest that most soldiers with suicidal behaviors (i.e., ideation, plans, and attempts) had first onsets prior to enlistment. However, those data are based on retrospective self-reports of soldiers later in their Army careers. Unbiased examination of this issue requires investigation of suicidality among new soldiers.
The New Soldier Study (NSS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) used fully structured self-administered measures to estimate preenlistment histories of suicide ideation, plans, and attempts among new soldiers reporting for Basic Combat Training in 2011–2012. Survival models examined sociodemographic correlates of each suicidal outcome.
Lifetime prevalence estimates of preenlistment suicide ideation, plans, and attempts were 14.1, 2.3, and 1.9%, respectively. Most reported onsets of suicide plans and attempts (73.3–81.5%) occurred within the first year after onset of ideation. Odds of these lifetime suicidal behaviors among new soldiers were positively, but weakly associated with being female, unmarried, religion other than Protestant or Catholic, and a race/ethnicity other than non-Hispanic White, non-Hispanic Black, or Hispanic.
Lifetime prevalence estimates of suicidal behaviors among new soldiers are consistent with retrospective reports of preenlistment prevalence obtained from soldiers later in their Army careers. Given that prior suicidal behaviors are among the strongest predictors of later suicides, consideration should be given to developing methods of obtaining valid reports of preenlistment suicidality from new soldiers to facilitate targeting of preventive interventions.
PMCID: PMC5113817  PMID: 25338964
military personnel; prevalence; suicide; suicide ideation; suicide attempt
16.  Predicting non-familial major physical violent crime perpetration in the U.S. Army from administrative data 
Psychological medicine  2015;46(2):303-316.
Although interventions exist to reduce violent crime, optimal implementation requires accurate targeting. We report the results of an attempt to develop an actuarial model using machine learning methods to predict future violent crimes among U.S. Army soldiers.
A consolidated administrative database for all 975,057 soldiers in the U.S. Army in 2004-2009 was created in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). 5,771 of these soldiers committed a first founded major physical violent crime (murder-manslaughter, kidnapping, aggravated arson, aggravated assault, robbery) over that time period. Temporally prior administrative records measuring socio-demographic, Army career, criminal justice, medical/pharmacy, and contextual variables were used to build an actuarial model for these crimes separately among men and women using machine learning methods (cross-validated stepwise regression; random forests; penalized regressions). The model was then validated in an independent 2011-2013 sample.
Key predictors were indicators of disadvantaged social/socio-economic status, early career stage, prior crime, and mental disorder treatment. Area under the receiver operating characteristic curve was .80-.82 in 2004-2009 and .77 in a 2011-2013 validation sample. 36.2-33.1% (male-female) of all administratively-recorded crimes were committed by the 5% of soldiers having highest predicted risk in 2004-2009 and an even higher proportion (50.5%) in the 2011-2013 validation sample.
Although these results suggest that the models could be used to target soldiers at high risk of violent crime perpetration for preventive interventions, final implementation decisions would require further validation and weighing of predicted effectiveness against intervention costs and competing risks.
PMCID: PMC5111361  PMID: 26436603
crime perpetration; physical violence; military violence; risk model; actuarial model; machine learning
17.  Lifetime Prevalence of DSM-IV Mental Disorders Among New Soldiers in the U.S. Army: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) 
Depression and anxiety  2014;32(1):13-24.
The prevalence of 30-day mental disorders with retrospectively-reported early onsets is significantly higher in the U.S. Army than among socio-demographically matched civilians. This difference could reflect high prevalence of pre-enlistment disorders and/or high persistence of these disorders in the context of the stresses associated with military service. These alternatives can to some extent be distinguished by estimating lifetime disorder prevalence among new Army recruits.
The New Soldier Study (NSS) in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) used fully-structured measures to estimate lifetime prevalence of 10 DSM-IV disorders in new soldiers reporting for Basic Combat Training in 2011-2012 (n=38,507). Prevalence was compared to estimates from a matched civilian sample. Multivariate regression models examined socio-demographic correlates of disorder prevalence and persistence among new soldiers.
Lifetime prevalence of having at least one internalizing, externalizing, or either type of disorder did not differ significantly between new soldiers and civilians, although three specific disorders (generalized anxiety, posttraumatic stress, and conduct disorders) and multi-morbidity were significantly more common among new soldiers than civilians. Although several socio-demographic characteristics were significantly associated with disorder prevalence and persistence, these associations were uniformly weak.
New soldiers differ somewhat, but not consistently, from civilians in lifetime pre-enlistment mental disorders. This suggests that prior findings of higher prevalence of current disorders with pre-enlistment onsets among soldiers than civilians are likely due primarily to a more persistent course of early-onset disorders in the context of the special stresses experienced by Army personnel.
PMCID: PMC5111824  PMID: 25338841
military personnel; mental disorders; prevalence; epidemiology; demographics
18.  Suicide attempts in U.S. Army combat arms, special forces and combat medics 
BMC Psychiatry  2017;17:194.
The U.S. Army suicide attempt rate increased sharply during the wars in Iraq and Afghanistan. Risk may vary according to occupation, which significantly influences the stressors that soldiers experience.
Using administrative data from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS), we identified person-month records for all active duty Regular Army enlisted soldiers who had a medically documented suicide attempt from 2004 through 2009 (n = 9650) and an equal-probability sample of control person-months (n = 153,528). Logistic regression analyses examined the association of combat occupation (combat arms [CA], special forces [SF], combat medic [CM]) with suicide attempt, adjusting for socio-demographics, service-related characteristics, and prior mental health diagnosis.
In adjusted models, the odds of attempting suicide were higher in CA (OR = 1.2 [95% CI: 1.1–1.2]) and CM (OR = 1.4 [95% CI: 1.3–1.5]), but lower in SF (OR = 0.3 [95% CI: 0.2–0.5]) compared to all other occupations. CA and CM had higher odds of suicide attempt than other occupations if never deployed (ORs = 1.1–1.5) or previously deployed (ORs = 1.2–1.3), but not when currently deployed. Occupation was associated with suicide attempt in the first ten years of service, but not beyond. In the first year of service, primarily a time of training, CM had higher odds of suicide attempt than both CA (OR = 1.4 [95% CI: 1.2–1.6]) and other occupations (OR = 1.5 [95% CI: 1.3–1.7]). Discrete-time hazard functions revealed that these occupations had distinct patterns of monthly risk during the first year of service.
Military occupation can inform the understanding suicide attempt risk among soldiers.
Electronic supplementary material
The online version of this article (doi:10.1186/s12888-017-1350-y) contains supplementary material, which is available to authorized users.
PMCID: PMC5445296  PMID: 28545424
Suicide attempt; Military; Occupation
19.  Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports 
Molecular psychiatry  2016;21(10):1366-1371.
Heterogeneity of major depressive disorder (MDD) illness course complicates clinical decision-making. While efforts to use symptom profiles or biomarkers to develop clinically useful prognostic subtypes have had limited success, a recent report showed that machine learning (ML) models developed from self-reports about incident episode characteristics and comorbidities among respondents with lifetime MDD in the World Health Organization World Mental Health (WMH) Surveys predicted MDD persistence, chronicity, and severity with good accuracy. We report results of model validation in an independent prospective national household sample of 1,056 respondents with lifetime MDD at baseline. The WMH ML models were applied to these baseline data to generate predicted outcome scores that were compared to observed scores assessed 10–12 years after baseline. ML model prediction accuracy was also compared to that of conventional logistic regression models. Area under the receiver operating characteristic curve (AUC) based on ML (.63 for high chronicity and .71–.76 for the other prospective outcomes) was consistently higher than for the logistic models (.62–.70) despite the latter models including more predictors. 34.6–38.1% of respondents with subsequent high persistence-chronicity and 40.8–55.8% with the severity indicators were in the top 20% of the baseline ML predicted risk distribution, while only 0.9% of respondents with subsequent hospitalizations and 1.5% with suicide attempts were in the lowest 20% of the ML predicted risk distribution. These results confirm that clinically useful MDD risk stratification models can be generated from baseline patient self-reports and that ML methods improve on conventional methods in developing such models.
PMCID: PMC4935654  PMID: 26728563
20.  Thirty-Day Prevalence of DSM-IV Mental Disorders Among Nondeployed Soldiers in the US Army 
JAMA psychiatry  2014;71(5):504-513.
Although high rates of current mental disorder are known to exist in the US Army, little is known about the proportions of these disorders that had onsets prior to enlistment.
To estimate the proportions of 30-day DSM-IV mental disorders among nondeployed US Army personnel with first onsets prior to enlistment and the extent which role impairments associated with 30-day disorders differ depending on whether the disorders had pre-vs post-enlistment onsets.
A representative sample of 5428 soldiers participating in the Army Study to Assess Risk and Resilience in Servicemembers completed self-administered questionnaires and consented to linkage of questionnaire responses with administrative records.
Thirty-day DSM-IV internalizing (major depressive, bipolar, generalized anxiety, panic, and posttraumatic stress) and externalizing (attention-deficit/ hyperactivity, intermittent explosive, alcohol/drug) disorders were assessed with validated self-report scales. Age at onset was assessed retrospectively. Role impairment was assessed with a modified Sheehan Disability Scale.
A total of 25.1% of respondents met criteria for any 30-day disorder (15.0% internalizing; 18.4% externalizing) and 11.1% for multiple disorders. A total of 76.6% of cases reported pre-enlistment age at onset of at least one 30-day disorder (49.6% internalizing; 81.7% externalizing). Also, 12.8% of respondents reported severe role impairment. Controlling for sociodemographic and Army career correlates, which were broadly consistent with other studies, 30-day disorders with pre-enlistment (χ82=131.8, P < .001) and post-enlistment (χ72=123.8, P < .001) ages at onset both significantly predicted severe role impairment, although pre-enlistment disorders were more consistent powerful predictors (7 of 8 disorders significant; odds ratios, 1.6–11.4) than post-enlistment disorders (5 of 7 disorders significant; odds ratios, 1.5–7.7). Population-attributable risk proportions of severe role impairment were 21.7% for pre-enlistment disorders, 24.3% for post-enlistment disorders, and 43.4% for all disorders.
Interventions to limit accession or increase resilience of new soldiers with pre-enlistment mental disorders might reduce prevalence and impairments of mental disorders in the US Army.
PMCID: PMC4057988  PMID: 24590120
21.  Approximating a DSM-5 Diagnosis of PTSD Using DSM-IV Criteria 
Depression and anxiety  2015;32(7):493-501.
Diagnostic criteria for DSM-5 posttraumatic stress disorder (PTSD) are in many ways similar to DSM-IV criteria, raising the possibility that it might be possible to closely approximate DSM-5 diagnoses using DSM-IV symptoms. If so, the resulting transformation rules could be used to pool research data based on the two criteria sets.
The Pre-Post Deployment Study (PPDS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) administered a blended 30-day DSM-IV and DSM-5 PTSD symptom assessment based on the civilian PTSD Checklist for DSM-IV (PCL-C) and the PTSD Checklist for DSM-5 (PCL-5). This assessment was completed by 9,193 soldiers from three US Army Brigade Combat Teams approximately three months after returning from Afghanistan. PCL-C items were used to operationalize conservative and broad approximations of DSM-5 PTSD diagnoses. The operating characteristics of these approximations were examined compared to diagnoses based on actual DSM-5 criteria.
The estimated 30-day prevalence of DSM-5 PTSD based on conservative (4.3%) and broad (4.7%) approximations of DSM-5 criteria using DSM-IV symptom assessments were similar to estimates based on actual DSM-5 criteria (4.6%). Both approximations had excellent sensitivity (92.6-95.5%), specificity (99.6-99.9%), total classification accuracy (99.4-99.6%), and area under the receiver operating characteristic curve (0.96-0.98).
DSM-IV symptoms can be used to approximate DSM-5 diagnoses of PTSD among recently-deployed soldiers, making it possible to recode symptom-level data from earlier DSM-IV studies to draw inferences about DSM-5 PTSD. However, replication is needed in broader trauma-exposed samples to evaluate the external validity of this finding.
PMCID: PMC4490033  PMID: 25845710
PTSD/posttraumatic stress disorder; Assessment/Diagnosis; Anxiety/Anxiety disorders; measurement/psychometrics; trauma
22.  Association of Mental Disorders With Subsequent Chronic Physical Conditions 
JAMA psychiatry  2016;73(2):150-158.
It is clear that mental disorders in treatment settings are associated with a higher incidence of chronic physical conditions, but whether this is true of mental disorders in the community, and how generalized (across a range of physical health outcomes) these associations are, is less clear. This information has important implications for mental health care and the primary prevention of chronic physical disease.
To investigate associations of 16 temporally prior DSM-IV mental disorders with the subsequent onset or diagnosis of 10 chronic physical conditions.
Eighteen face-to-face, cross-sectional household surveys of community-dwelling adults were conducted in 17 countries (47 609 individuals; 2 032 942 person-years) from January 1, 2001, to December 31, 2011. The Composite International Diagnostic Interview was used to retrospectively assess the lifetime prevalence and age at onset of DSM-IV–identified mental disorders. Data analysis was performed from January 3, 2012, to September 30, 2015.
Lifetime history of physical conditions was ascertained via self-report of physician’s diagnosis and year of onset or diagnosis. Survival analyses estimated the associations of temporally prior first onset of mental disorders with subsequent onset or diagnosis of physical conditions.
Most associations between 16 mental disorders and subsequent onset or diagnosis of 10 physical conditions were statistically significant, with odds ratios (ORs) (95% CIs) ranging from 1.2 (1.0–1.5) to 3.6 (2.0–6.6). The associations were attenuated after adjustment for mental disorder comorbidity, but mood, anxiety, substance use, and impulse control disorders remained significantly associated with onset of between 7 and all 10 of the physical conditions (ORs [95% CIs] from 1.2 [1.1–1.3] to 2.0 [1.4–2.8]). An increasing number of mental disorders experienced over the life course was significantly associated with increasing odds of onset or diagnosis of all 10 types of physical conditions, with ORs (95% CIs) for 1 mental disorder ranging from 1.3 (1.1–1.6) to 1.8 (1.4–2.2) and ORs (95% CIs) for 5 or more mental disorders ranging from 1.9 (1.4–2.7) to 4.0 (2.5–6.5). In population-attributable risk estimates, specific mental disorders were associated with 1.5% to 13.3% of physical condition onsets.
These findings suggest that mental disorders of all kinds are associated with an increased risk of onset of a wide range of chronic physical conditions. Current efforts to improve the physical health of individuals with mental disorders may be too narrowly focused on the small group with the most severe mental disorders. Interventions aimed at the primary prevention of chronic physical diseases should optimally be integrated into treatment of all mental disorders in primary and secondary care from early in the disorder course.
PMCID: PMC5333921  PMID: 26719969
23.  Barriers to initiating and continuing mental health treatment among soldiers in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) 
Military medicine  2016;181(9):1021-1032.
U.S. Army soldiers with mental disorders report a variety of barriers to initiating and continuing treatment. Improved understanding of these barriers can help direct mental health services to soldiers in need. A representative sample of 5,428 nondeployed Regular Army soldiers participating in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) completed a self-administered questionnaire (SAQ) and consented to linking SAQ data with administrative records. We examined reported treatment barriers (perceived need, structural reasons, attitudinal reasons) among respondents with current DSM-IV mental disorders who either did not seek treatment in the past year (n=744) or discontinued treatment (n=145). 82.4% of soldiers who did not initiate treatment and 69.5% of those who discontinued treatment endorsed at least two barriers. 69.8% of never-treated soldiers reported no perceived need. Attitudinal reasons were cited more frequently than structural reasons among never-treated soldiers with perceived need (80.7% vs. 62.7%) and those who discontinued treatment (71.0% vs. 37.8%). Multivariate associations with socio-demographic, Army career, and mental health predictors varied across barrier categories. These findings suggest most soldiers with mental disorders do not believe they need treatment, and those who do typically face multiple attitudinal and, to a lesser extent, structural barriers.
PMCID: PMC5120390  PMID: 27612348
military; mental health; treatment; barriers
24.  Associations between subjective social status and DSM-IV mental disorders: Results from the World Mental Health Surveys 
JAMA psychiatry  2014;71(12):1400-1408.
The inverse social gradient in mental disorders is a well-established research finding with important implications for causal models and policy. This research has used traditional objective social status (OSS) measures such as education, income and occupation. Recently, subjective social status (SSS) measurement has been advocated to capture perception of relative social status, but to date there are no studies of associations between SSS and mental disorders.
To estimate associations of SSS with DSM-IV mental disorders in multiple countries and to investigate whether the associations persist after comprehensive adjustment of OSS.
Design; Setting; Participants
Face-to-face cross-sectional household surveys of community-dwelling adults in 18 countries in Asia, South Pacific, the Americas, Europe, the Middle East (n= 56,085). SSS was assessed with a self-anchoring scale reflecting respondent evaluations of their place in the social hierarchies of their countries in terms of income, education and occupation. Scores on the 1–10 SSS scale were categorised into four categories: low (scores 1–3); low-mid (scores 4 and 5); high-mid (scores 6 and 7); high (scores 8–10). OSS was assessed with a wide range of fine-grained objective indicators of income, education and occupation.
Main Outcome Measures
The Composite International Diagnostic Interview assessed 12-month prevalence of 16 DSM-IV mood, anxiety and impulse control disorders.
Graded, inverse associations were found between SSS and all 16 mental disorders. Gross odds-ratios (lowest versus highest SSS categories) in the range 1.8–9.0 were attenuated but remained significant for all 16 disorders (ORs: 1.4–4.9) after adjusting for OSS indicators. The pattern of inverse association between SSS and mental disorders was significant in 14/18 individual countries, and in low, middle and high income country groups, but was significantly stronger in higher versus lower income countries.
Significant inverse associations between SSS and numerous DSM-IV mental disorders exist across a wide range of countries even after comprehensive adjustment for OSS. Although unclear whether these associations are due to social selection, social causation, or both, these results document clearly that research relying exclusively on standard OSS measures underestimates the steepness of the social gradient in mental disorders.
PMCID: PMC5315238  PMID: 25354080
25.  Response bias, weighting adjustments, and design effects in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) 
The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) is a multi-component epidemiological and neurobiological study designed to generate actionable recommendations to reduce U.S. Army suicides and increase knowledge about determinants of suicidality. Three Army STARRS component studies are large-scale surveys: one of new soldiers prior to beginning Basic Combat Training (BCT; n=50,765 completed self-administered questionnaires); another of other soldiers exclusive of those in BCT (n=35,372); and a third of three Brigade Combat Teams about to deploy to Afghanistan who are being followed multiple times after returning from deployment (n= 9,421). Although the response rates in these surveys are quite good (72.0-90.8%), questions can be raised about sample biases in estimating prevalence of mental disorders and suicidality, the main outcomes of the surveys based on evidence that people in the general population with mental disorders are under-represented in community surveys. This paper presents the results of analyses designed to determine whether such bias exists in the Army STARRS surveys and, if so, to develop weights to correct for these biases. Data are also presented on sample inefficiencies introduced by weighting and sample clustering and on analyses of the trade-off between bias and efficiency in weight trimming.
PMCID: PMC3992816  PMID: 24318218
Suicide; mental disorders; U.S. Army; epidemiologic research design; design effects; sample bias; sample weights; survey design efficiency; survey sampling

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