Prospective risk factors for post-deployment heavy drinking

and alcohol or substance usedisorder among US Army soldiers

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Citation Campbell-Sills, Laura, Robert J. Ursano, Ronald C. Kessler, XiaoyingSun, Steven G. Heeringa, Matthew K. Nock, Nancy A. Sampson,Sonia Jain, and Murray B. Stein. 2017. “Prospective Risk Factorsfor Post-Deployment Heavy Drinking and Alcohol or SubstanceUse Disorder Among US Army Soldiers.” Psychological Medicine(October 17): 1–12. doi:10.1017/s0033291717003105.

Published Version doi:10.1017/S0033291717003105

Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:34864121

Terms of Use This article was downloaded from Harvard University’s DASHrepository, and is made available under the terms and conditionsapplicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP

1

Wordcount(textonly):43911

NumberofTables:32

NumberofFigures:23

NumberofSupplementaryTables:44

5

Prospectiveriskfactorsforpost-deploymentheavydrinkingandAlcoholorSubstanceUseDisorder6

amongU.S.Armysoldiers7

8

LauraCampbell-Sills,PhD19

RobertJ.Ursano,MD210

RonaldC.Kessler,PhD311

XiaoyingSun,MS412

StevenG.Heeringa,PhD513

MatthewK.Nock,PhD614

NancyA.Sampson,BA315

SoniaJain,PhD416

MurrayB.Stein,MD,MPH1,4,717

18

1DepartmentofPsychiatry,UniversityofCaliforniaSanDiego,LaJolla,CA,USA19

2CenterfortheStudyofTraumaticStress,DepartmentofPsychiatry,UniformedServicesUniversityof20

theHealthSciences,Bethesda,MD,USA21

3DepartmentofHealthCarePolicy,HarvardMedicalSchool,Boston,MA,USA22

4DepartmentofFamilyMedicineandPublicHealth,UniversityofCaliforniaSanDiego,LaJolla,CA,USA23

5UniversityofMichigan,InstituteforSocialResearch,AnnArbor,MI,USA24

2

6DepartmentofPsychology,HarvardUniversity,Cambridge,MA,USA25

7VASanDiegoHealthcareSystem,SanDiego,CA,USA26

27

Pleaseaddresscorrespondenceto:28

LauraCampbell-Sills,PhD29

UCSDDepartmentofPsychiatry30

9500GilmanDrive,MailCode085531

LaJolla,CA9209332

Phone:(858)534-6448;Fax:(858)534-646033

Email:campbell-sills@ucsd.edu34

35

ArmySTARRSwassponsoredbytheDepartmentoftheArmyandfundedundercooperativeagreement36

numberU01MH087981(2009-2015)withtheU.S.DepartmentofHealthandHumanServices,National37

InstitutesofHealth,NationalInstituteofMentalHealth(NIH/NIMH).Subsequently,STARRS-LSwas38

sponsoredandfundedbytheDepartmentofDefense(USUHSgrantnumberHU0001-15-2-0004).The39

contentsaresolelytheresponsibilityoftheauthorsanddonotnecessarilyrepresenttheviewsofthe40

DepartmentofHealthandHumanServices,NIMH,DepartmentoftheArmy,orDepartmentofDefense. 41

3

Abstract42

Background:Investigationsofdrinkingbehavioracrossmilitarydeploymentcyclesarescarce,andfew43

prospectivestudieshaveexaminedriskfactorsforpost-deploymentalcoholmisuse.Methods:44

Prevalenceofalcoholmisusewasestimatedamong4,645U.S.Armysoldierswhoparticipatedina45

longitudinalsurvey.Assessmentoccurred1-2monthsbeforesoldiersdeployedtoAfghanistanin201246

(T0),upontheirreturntotheU.S.(T1),3monthslater(T2),and9monthslater(T3).Weights-adjusted47

logisticregressionwasusedtoevaluateassociationsofhypothesizedriskfactorswithpost-deployment48

incidenceandpersistenceofheavydrinking(consuming5+alcoholicdrinksatleast1-2x/week)and49

AlcoholorSubstanceUseDisorder(AUD/SUD).Results:Prevalenceofpast-monthheavydrinkingatT0,50

T2,andT3was23.3%(SE=0.7%),26.1%(SE=0.8%),and22.3%(SE=0.7%);correspondingestimatesfor51

anybingedrinkingwere52.5%(SE=1.0%),52.5%(SE=1.0%),and41.3%(SE=0.9%).Greaterpersonallife52

stressduringdeployment(e.g.,relationship,family,orfinancialproblems)–butnotcombatstress–was53

associatedwithnewonsetofheavydrinkingatT2[perstandardscoreincrease:AOR=1.20,95%CI1.06-54

1.35,p=.003];incidenceofAUD/SUDatT2(AOR=1.54,95%CI1.25-1.89,p<.0005);andpersistenceof55

AUD/SUDatT2andT3(AOR=1.30,95%CI1.08-1.56,p=.005).Anybingedrinkingpre-deploymentwas56

associatedwithpost-deploymentonsetofHD(AOR=3.21,95%CI2.57-4.02,p<.0005)andAUD/SUD57

(AOR=1.85,95%CI1.27-2.70,p=.001).Conclusions:Alcoholmisuseiscommonduringthemonths58

precedingandfollowingdeployment.Timelyinterventionaimedatalleviating/managingpersonal59

stressorsorcurbingriskydrinkingmightreduceriskofalcohol-relatedproblemspost-deployment.60

61

4

Introduction62

Theburdenofalcoholmisuseonournation’spublichealth(Grantetal.,2015,Okoroetal.,63

2004,Sacksetal.,2015)extendstotheU.S.ArmedForces,wherehazardousdrinkingposesthreatsto64

boththehealthofindividualservicemembersandtroopreadiness(Brayetal.,2013,Hurt,2015).65

Militarypersonnelwhodrinkheavilysuffermoreaccidents/injuries;occupational,relational,andlegal66

problems;andproductivitylossthanothers(Mattikoetal.,2011).Moreover,alcoholmisuseis67

associatedwithmentaldisorders(Sampsonetal.,2015,Steinetal.,2017),suicidalideation(Mashetal.,68

2014),andsuicide(LeardMannetal.,2013)amongservicemembers.Improvedunderstandingofscope69

andriskfactorsmayhelpreducealcoholmisuseanditssequelaewithinthemilitarypopulation.70

Deploymenttoacombatzoneincreasesriskofalcoholmisuseamongcertainsubgroups71

(Jacobsonetal.,2008).Yetsystematiccharacterizationsofdrinkingbehavioracrossmilitarydeployment72

cyclesarescarce(Harbertsonetal.,2016,Hurt,2015);andfewprospectivestudieshaveinvestigated73

riskfactorsforpost-deploymentalcoholmisuse.AnotableexceptionfromtheMillenniumCohortStudy74

examinedalcoholmisuseamong>48,000previouslynon-deployedU.S.servicememberssurveyedin75

2001-2003and2004-2006(Jacobsonetal.,2008).Deploymentwithcombatexposureduringthetime76

betweensurveyswasassociatedwithonsetofbingedrinkingamongactive-dutypersonnel;andwith77

onsetofbingedrinking,heavydrinking,andalcohol-relatedproblemsamongReserve/NationalGuard78

personnel.Riskswerenotelevatedamongpersonnelwhoweredeployedbutnotexposedtocombat.79

Non-combat-relatedstressalsomaycontributetoriskforalcoholmisuse.Independentof80

combatstressexposure,personallifestressorswereassociatedwithsubsequentAlcoholUseDisorder81

(AUD)amongOhioNationalGuardmemberswhohaddeployedtoIraqorAfghanistan(Cerdaetal.,82

2014).Similarly,changesinalcoholconsumptionwereassociatedwithpersonallifeeventsbutnot83

deploymenttoIraq/AfghanistanamongUKmilitarypersonnel(Thandietal.,2015).Vulnerabilityto84

post-deploymentalcoholmisusealsomaydependonsocio-demographicandmilitaryservice85

5

characteristics(BoulosandZamorski,2016,Jacobsonetal.,2008)ormentalhealthfactorssuchas86

posttraumaticstressdisorder(PTSD)andmajordepressivedisorder(MDD),whichareconsistently87

linkedtoalcoholmisuseinmilitarysamples(Jacobsonetal.,2008,Kehleetal.,2012,Thandietal.,2015,88

Thomasetal.,2010,Steinetal.,2017).89

TheArmyStudytoAssessRiskandResilienceinServicemembers(ArmySTARRS)Pre/Post90

DeploymentStudy(Kessleretal.,2013a,Ursanoetal.,2014)affordsopportunitiestoexaminedrinking91

behavioracrossthedeploymentcycleandprospectiveriskfactorsforpost-deploymentalcoholmisuse.92

Weestimatedprevalenceofbingedrinking,heavydrinking,andalcoholorsubstanceusedisorder93

(AUD/SUD)amongsoldiersshortlybeforetheirdeploymenttoAfghanistan,andapproximately3and994

monthsfollowingtheirreturntotheU.S.Additionally,weevaluatedassociationsofsocio-demographic95

characteristics,priordeploymenthistory,combat/deploymentstress,personallifestressduring96

deployment(e.g.,relationship,family,financialproblems),pre-andperi-deploymentmentalhealth,and97

pre-deploymentbingedrinkingwithriskofincidenceandpersistenceofbothheavydrinkingand98

AUD/SUDat3monthspost-deployment.Tofurtherextendtheliteratureonmilitarydeploymentand99

alcoholmisuse,weutilizedthemultiplepost-deploymentPPDSassessmentstodeterminewhichofthe100

pre-andperi-deploymentriskfactorscontributedtopredictionofchronicheavydrinkingandAUD/SUD101

(i.e.,alcoholmisusethatwaspresentatboth3and9monthspost-deployment).102

Method103

ParticipantsandProcedures104

ThePre/PostDeploymentStudy(PPDS)isamulti-wavepanelsurveyofU.S.Armysoldiersin3105

BrigadeCombatTeams(BCTs).Baseline(T0)assessmentwasconductedduringQ1of2012,1-2months106

beforedeploymentoftheBCTstoAfghanistan.Follow-upassessmentoccurredwithin1monthofre-107

deploymentoftheBCTstotheU.S.(T1)andatapproximately3monthspost-deployment(T2)and9108

monthspost-deployment(T3).Participantsgavewritten,informedconsentfortheself-administered109

6

questionnaires(SAQs).BaselineSAQrespondentsalsowereaskedforconsentforcollectionofblood110

samples,linkageofArmyandDepartmentofDefense(DoD)administrativerecordstotheirSAQ111

responses,andcontactforparticipationinfutureassessments.Procedureswereapprovedbythe112

HumanSubjectsCommitteesofallcollaboratingorganizations.113

AtT0,9949soldierswerepresentfordutyinthe3BCTsand9488(95.3%)consentedtotheSAQ.114

Ofthosewhoconsented,8558(86.0%)providedcompletedataandconsentforArmy/DoDrecord115

linkage.ThesubpopulationofinterestforthisinvestigationwasT0participantswithcompleteSAQdata116

whosubsequentlydeployedtoAfghanistan(n=7742).Becausetheanalysisuseddatafromallwaves,the117

samplewasrestrictedtothe60.0%ofdeployedsoldierswhocompletedallfollow-ups(n=4645).118

Tomitigateimpactsofselectionfactorsandenhancegeneralizabilityofresultstothebroader119

populationofdeployedsoldiers,weightsweredevelopedandappliedinallanalyses(Heeringaetal.,120

2010).Combinedanalysisweightsinclude:(1)apropensity-basedweightingadjustmentforbaseline121

attritionduetoincompletesurveysandinabilitytolinktoadministrativedata(e.g.,duetoabsenceof122

soldierconsent);(2)post-stratificationtomaptheobservedsampleof7742eligiblePPDSsoldierstokey123

demographicandArmyservicecharacteristicsofsoldiersinthethreecombinedBCTsthatdeployedto124

AfghanistanaftertheT0interviewdates;and(3)apropensity-basedattritionadjustmenttoaccountfor125

thefactthat3097ofthe7742T0deployedcohortdidnothavecompletedatainoneormoreofthe3126

follow-upwaves.MoreinformationaboutweightingofArmySTARRSdatacanbeobtainedelsewhere127

(Kessleretal.,2013b).128

Measures129

Alcoholuseoutcomes.TheT0,T2,andT3surveysassessedfrequencyofalcoholbinges(5or130

moredrinksofalcoholonthesameday)duringthepast30days(never,lessthan1dayaweek,1-2days131

aweek,3-4daysaweek,andeveryornearlyeveryday;coded0-4).FollowingtheSubstanceAbuseand132

MentalHealthServicesAdministrationdefinitionsofbingedrinking(5ormorealcoholicdrinksonthe133

7

sameoccasiononatleast1dayinthepast30days)andheavydrinking(5ormoredrinks…5ormore134

daysinthepast30days),ratings>1werecodedpositiveforpast-monthBingeDrinking(BD)andratings135

>2werecodedpositiveforpast-monthHeavyDrinking(HD).Missingalcoholbingefrequencydatawere136

rare(<0.5%ateachwave)andcoded“0”toyieldconservativeestimates.137

DiagnosesofAUD/SUDwerebasedonitemsfromtheself-administeredCompositeInternational138

DiagnosticInterviewScreeningScales(CIDI-SC;KesslerandUstun,2004),whichassessednegative139

consequencesofalcoholand/ordruguseandsymptomsofdependence.Analgorithmemploying140

respondents’ratingswasusedtodiagnoseAUD/SUDandresultswerevalidatedagainststructured141

clinicalinterviewsintheArmySTARRSclinicalreappraisalstudy(Kessleretal.,2013c).IntheT0survey,142

respondentsendorsinganylifetimealcoholordruguseratedAUD/SUDitemsinreferencetotheperiod143

whentheyusedthemostalcohol(forthosewithnolifetimeuseofotherdrugs),drugs(forthosewith144

nolifetimeuseofalcohol),oralcoholordrugs(forthosewithlifetimealcoholandotherdruguse);145

yieldinglifetimeAUD/SUDdiagnoses.ForT2andT3surveys,AUD/SUDitemswereratedinreferenceto146

thepast30days,yieldingpast-monthAUD/SUDdiagnoses.AUD/SUDwasnotassessedatT1.147

BecausethesurveysdidnotestablishwhetherAUD/SUDsymptomswereduetoalcoholordrug148

use(orboth),non-alcoholdrugusewasexaminedamongrespondentswithAUD/SUDatT2andatT3.149

TheT2andT3surveysassessedpast30-dayuseofmarijuana/hashish;spice/syntheticmarijuana;and150

anyotherillegaldrug;andpast30-daymisuseofprescriptionstimulants,tranquilizers/sedatives,and151

analgesics.AmongrespondentswithAUD/SUDatT2,10.0%endorseduseofanynon-alcoholdrug1-152

2x/weekormoreduringthemonthpriortoassessment.Thesameproportion(10.0%)ofthosewith153

AUD/SUDatT3endorsednon-alcoholdruguse1-2x/weekormoreinthemonthpriortotheT3154

assessment.ThesedatasuggestthatalargemajorityofAUD/SUDwasinfactAUD.155

8

Socio-demographicandArmyservicevariables.Age,sex,race,ethnicity,maritalstatus,highest156

educationaldegree,andnumberofpriordeploymentswereconsideredaspredictorsofalcoholmisuse.157

BCTwasadjustedforinallmodels.158

Combat/deploymentstressandlifestress.TheT1surveyinquiredhowmanytimessoldiers159

hadexperienced14highlystressful/traumaticeventsduringtheindexdeployment.Frequencyratings160

werediscretized(0/1or0/1/2)andsummedtocreateaDeploymentStressScale(DSS;range=0-16;161

SupplementaryTable1).TheT1surveyalsoassessedstressduringdeploymentthatarosefrom7162

domainsofsoldiers’lives(ratednone,mild,moderate,severe,orverysevere;coded0-4).Exploratory163

factoranalysisusingminimumresidualestimationandpromaxrotationindicatedthat2latentfactors164

bestexplainedthecovarianceoftheseratings(SupplementaryTable2).Twolifestressvariableswere165

thereforederived.ThefirstwasPersonalLifeStress(PLS),quantifiedasthesumofratingsofstressfrom166

finances,romanticrelationships,legalproblems,familyrelationships,andproblemsexperiencedby167

lovedones(range=0-20;Cronbach’sα=.76).ThesecondwasMilitaryLifeStress(MLS),orthesumof168

ratingsofstressfromproblemswithchainofcommandandfellowunitmembers(range=0-8;α=.73).For169

regressionanalysis,DSS,PLS,andMLSscoreswerestandardizedtofacilitateinterpretationofresults.170

Standardscoresof1.0and2.0wereconsidered“above-averagestress”and“highstress,”respectively.171

Pre-andperi-deploymentmentalhealth.Regressionmodelsincludedavariableindicating172

presenceversusabsenceofanypast-monthPTSD,majordepressiveepisode(MDE),generalizedanxiety173

disorder(GAD),orsuicidalideation(SI)atT0(Steinetal.,2015).PTSD,MDE,andGADdiagnoseswere174

basedonitemsfromtheCIDI-SC(KesslerandUstun,2004)andPTSDChecklist(Weathersetal.,1993).175

Validationofthesediagnoseswasthefocusofapriorreport(Kessleretal.,2013c).SIwasestablished176

withanexpandedself-reportversionoftheColumbiaSuicidalSeverityRatingScale(Posneretal.,2011).177

Modelsalsoincludedindicatorsofsoldiers’mentalhealthduringdeployment.TheT1survey178

contained5itemsassessingPTSDsymptomsduringdeployment;ratingsoftheseitemsweresummedto179

9

quantifyoverallseverityofPTSDsymptomsduringdeployment(range=0-20;α=.84).TheT1survey180

itemsassessingMDEandGADsymptoms(7itemstotal)hadexcellentinternalconsistency(α=.90)and181

weresummedtoquantifyoverallseverityofMDE/GADsymptomsduringdeployment(range=0-28).The182

peri-deploymentPTSDandMDE/GADsymptomseveritymeasureswerestandardizedpriortoregression183

analysistofacilitateinterpretationofresults.184

DataAnalysis185

Weightedprevalenceofthefollowingwascalculated:30-dayBDandHDatT0,T2,andT3;186

lifetimeAUD/SUDatT0;and30-dayAUD/SUDatT2andT3.Weights-adjustedlogisticregression187

modelswerefittoestimateassociationsofhypothesizedriskfactorswithonsetandpersistenceofHD188

andAUD/SUD.ModelsofonsetofHDwereestimatedforsoldierswhodeniedpast-monthHDatT0;189

modelsofonsetofAUD/SUDwereestimatedforsoldierswithoutlifetimeAUD/SUDatT0,and190

persistencemodelswereestimatedforsoldierswhoendorsedtheoutcomeunderconsiderationatT0.191

OnsetandpersistenceofHDandAUD/SUDatT2weretheprimaryoutcomes.Toascertainwhichrisk192

factorswereassociatedwithchronicpost-deploymentalcoholmisuse,HDandAUD/SUDthatwere193

presentatbothT2andT3wereconsideredsecondaryoutcomes.194

Thefollowingindependentvariableswereincludedinallmodels:sex,age,race,ethnicity,195

education,maritalstatus,BCT,numberofpriordeployments,andpre-deploymentemotionaldisorder196

(fromT0);andcombat/deploymentstress,personallifestress,militarylifestress,peri-deploymentPTSD197

symptomseverity,andperi-deploymentMDE/GADsymptomseverity(fromT1).Pre-deploymentpast-198

monthBDwasincludedinmodelsofnew-onsetHDandAUD/SUD.199

PPDSdataareclustered(byBCTandadministrationsession)andweighted;therefore,the200

design-basedTaylorserieslinearizationmethodwasusedtoestimatestandarderrors.Multivariable201

significancewasexaminedusingdesign-basedWaldΧ2tests.Two-tailedp<.05wasconsidered202

significant.AnalyseswereconductedusingRVersion3.3.2(RCoreTeam,2013).203

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Results204

Descriptivefindings205

Weightedprevalenceofpast-monthbingedrinking,heavydrinking,andAUD/SUDisshownin206

Table1.MorethanhalfofsoldiersendorsedBDatpre-deploymentand3monthspost-deployment;207

lowerprevalencewasobserved9monthspost-deployment.TherateofHDwasrelativelystable,with208

approximatelyone-quarterofsoldiersendorsingpast-monthHDateachwave.Past-monthAUD/SUD209

wasslightlymoreprevalentat9monthspost-deploymentthanat3monthspost-deployment.Past-210

monthAUD/SUDwasnotassessedatthepre-deploymentassessment;however,prevalenceoflifetime211

AUD/SUDatT0was20.4%(SE=0.7%).212

DemographicdifferencesinprevalenceofBD,HD,andAUD/SUDwereexaminedandfullresults213

appearinSupplementaryTables3and4.WomenexhibitedlowerprevalenceofBD,HD,andAUD/SUD214

thanmenatallwaves(seeFigure1forBDandHDresults).RelativetoWhitesoldiers,BlackandAsian215

soldiersdisplayedlowerprevalenceofBD(allwaves),HD(allwavesexceptT3),andlifetimeAUD/SUDat216

T0.WhereasotheragegroupsexhibitedstableordecliningratesofBDandHDfrompre-deploymentto217

9monthspost-deployment,theyoungestsoldiers(aged18-20)displayedsubstantialincreasesinBDand218

HDoverthesameperiod(seeFigure2forHDresults).219

Nearly1in10soldiers(9.6%,SE=0.4%)hadpast-monthPTSD,MDE,GAD,orSIatT0.On220

average,soldierswereexposedto4combat/deploymentstressorsduringtheirdeploymentto221

Afghanistan[meanDSS=3.98,SD=2.72,observedrange=0-15].Notethatthisvaluerepresentsdistinct222

typesofcombat/deploymentstressorsencountered–nottotalnumberofstressfulexperiences,which223

couldhavebeenhigherinnumber(seeSupplementaryTable1forDSSscoringdetails).Reportedlevels224

ofpersonallifestress,militarylifestress,PTSDsymptoms,andMDE/GADsymptomsduringdeployment225

weregenerallymild[meanPLS=2.68,SD=2.68,range=0-20;meanMLS=1.73,SD=1.89,range=0-8;mean226

T1PTSDscore=3.18,SD=3.63,range=0-20;meanT1MDE/GADscore=5.56,SD=5.20,range=0-28].227

228

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Riskfactorsforonsetandpersistenceofheavydrinking229

New-onsetofHDpost-deployment.Malesex,youngerage,never-marriedstatus,pre-230

deploymentBD,andgreaterpersonallifestressduringdeploymentwereassociatedwithincreasedodds231

ofonsetofHDatT2amongsoldierswhodeniedHDatT0(Table2).Theadjustedodds-ratio232

characterizingtheassociationofpersonallifestresswithHDonsetindicatesthatsoldierswithabove-233

average(z=1.00)andhighpersonalstress(z=2.00)duringdeploymentexhibited20%and44%increased234

riskofpost-deploymentHDonset,relativetothosewithaveragepersonalstressduringdeployment.235

Otherdemographiccharacteristics,priordeployments,combat/deploymentstress,militarylifestress,236

andpre-andperi-deploymentmentalhealthfactorswerenotsignificantlyrelatedtoonsetofHD.237

Most(62.0%)newHDobservedatT2hadremittedbyT3–i.e.,frequencyofalcoholbinges238

droppedbackbelowthethresholdforHD.WhenonsetofchronicHD(presentatT2andT3)was239

specifiedastheoutcome,similarriskfactorswereevident.Malesex,youngerage,nevermarried240

status,andpre-deploymentBDweresignificantlyassociatedwithonsetofchronicHD.However,the241

associationofpersonallifestressduringdeploymentwithonsetofchronicHDwasnotstatistically242

significant(p=.079;Table2).243

PersistenceofHDfrompre-to-postdeployment.Thehypothesizedriskfactorsgenerallylacked244

substantiveassociationswithpersistenceofHDfrompre-topost-deployment.Onlyperi-deployment245

MDE/GADsymptomswereassociatedwithpersistenceofHDatT2amongsoldierswhoendorsedHDat246

T0(Table2).Soldierswithabove-average(z=1.00)andhighMDE/GADsymptoms(z=2.00)during247

deploymentexhibited20%and43%increasedriskofHDpersistenceatT2,relativetothosewith248

averagedistressduringdeployment.MDE/GADsymptomswerenotassociatedwithchronicpersistence249

ofHDatT2andT3(p=.13;Table2).250

251

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RiskfactorsforincidenceandpersistenceofAUD/SUD252

IncidenceofAUD/SUDpost-deployment.Pre-deploymentBDandgreaterpersonallifestress253

duringdeploymentwereassociatedwithincreasedriskofAUD/SUDatT2amongsoldierswithout254

lifetimeAUD/SUDatT0(Table3).Relativetoaveragepersonalstressduringdeployment,above-255

averagepersonalstresswasassociatedwith54%increasedriskofincidenceofAUD/SUDandhigh256

personalstresswasassociatedwithmorethandoubled(AOR=2.36)oddsofincidenceofAUD/SUD.257

Nearlytwo-thirds(64.0%)ofnew-onsetAUD/SUDpersistedatT3.Thesamefactors–pre-258

deploymentBDandpersonalstressduringdeployment–wereassociatedwithincreasedriskof259

incidenceofchronicAUD/SUD(i.e.,atT2andT3;Table3).OddsofincidenceofchronicAUD/SUDwere260

72%higheramongsoldierswithabove-averagepersonalstressandnearlytripled(AOR=2.94)for261

soldierswithhighpersonalstress,relativetothosewithaveragepersonalstressduringdeployment.262

PersistenceofAUD/SUDfrompre-topost-deployment.Amongsoldierswithlifetime263

AUD/SUDatT0,onlygreatermilitarylifestressduringdeploymentwassignificantlyassociatedwith264

persistenceofthedisorderatT2(Table3).Comparedtosoldierswithaveragemilitarylifestress,odds265

ofpersistenceofAUD/SUDatT2were20%and45%higheramongsoldierswithabove-averageandhigh266

militarylifestress,respectively.Theassociationofpersonallifestressseveritywithpersistenceof267

AUD/SUDatT2wasnotstatisticallysignificant(p=.062);however,greaterpersonallifestressduring268

deploymentwassignificantlyassociatedwithchronicpersistenceofAUD/SUDatT2andT3(Table3).269

Relativetothosewithaveragepersonallifestressduringdeployment,oddsofpersistenceofAUD/SUD270

atbothT2andT3were30%and69%higheramongsoldierswithabove-averageandhighpersonal271

stress,respectively.272

Discussion273

Thisprospective,longitudinalstudyofU.S.ArmysoldiersfromthreeBrigadeCombatTeams274

revealsassociationsbetweenpersonallifestressduringdeploymentandarangeofpost-deployment275

13

alcoholmisuseoutcomes.AmongsoldierswithnolifetimeAUD/SUDpre-deployment,highlevelsof276

personallifestressduringdeployment(definedasstandardscoreof2.00orhigheronthePLSmeasure)277

wereassociatedwithdoubledriskofincidenceofAUD/SUDat3monthspost-deployment;andnearly278

tripledriskofincidenceofchronicAUD/SUDobservedat3and9monthspost-deployment.Inaddition,279

personallifestressduringdeploymentpredictedonsetofheavydrinkingamongsoldierswhodenied280

drinkingheavilypre-deploymentandchronicpersistenceofAUD/SUD(atboth3and9monthspost-281

deployment)amongsoldierswiththedisorderearlierinlife.Bingedrinkingshortlybeforedeployment282

alsoportendedonsetofmoreseriousalcoholmisusepost-deployment;reflectedintripledoddsofonset283

ofheavydrinkingandnearlydoubledoddsofincidenceofAUD/SUD.Inadditiontopredictingthese284

outcomesatasinglepost-deploymenttimepoint,pre-deploymentbingedrinkingpredictedonsetof285

chronicheavydrinkingandAUD/SUDthatwerepresentatboth3and9monthspost-deployment.286

ThePPDSsurveydidnotpermitdifferentialdiagnosisofAUDversusSUDduetonon-alcohol287

druguse.AvailableevidencesuggeststhelargemajorityofAUD/SUDinthissamplewasinfactAUD;288

only10%ofrespondentswithAUD/SUDateitherpost-deploymentassessmentendorsedregularuseof289

anynon-alcoholdrug.PriorworkalsoindicatesthatAUDismorecommonthandrugabuse/dependence290

amongservicemembers(Finketal.,2016).Chronicity(persistenceatT3)oftwo-thirdsofAUD/SUDwith291

post-deploymentonsetarguesagainstcharacterizationofthesenewdisordersastransientreactions;292

andmayreflectmoreenduringstress/adjustmentdemandsassociatedwithdeploymenttoacombat293

zoneandsubsequentre-deploymenttotheU.S.WhilechronicitywasthenormforAUD/SUDwithpost-294

deploymentonset,aminorityofnew-onsetheavydrinkingpersistedatT3.Consideredtogether,these295

findingssuggestthatpresenceofabuseordependencesymptomsshortlyfollowingreturnfrom296

deployment–asopposedtoincreasedalcoholconsumptionperse–meritgreatestconcern.297

Theabsenceofassociationsofcombatstressseveritywiththealcoholmisuseoutcomesis298

counterintuitive,butlargelyconvergeswithresultsoftwootherstudiesthatjointlyexaminedpredictive299

14

effectsofcombatandpersonalstress(Cerdaetal.,2014,Thandietal.,2015).Althoughunderlying300

explanationsforthegreaterapparentinfluenceofpersonal(versuscombat)stressorswerenotexplored301

inthecurrentanalysis,somepossibilitiesmeritingfuturestudyare:continuanceofpersonalstressors302

intothepost-deploymentperiod(versusoffsetofdeploymentstress);soldierperceptionofdrinkingasa303

moreeffectivecopingtoolforeverydaystressthanforcombatstress;concentrationofother304

vulnerabilitycharacteristics(e.g.,traitspredisposingindividualstoalcoholmisuse)amongsoldierswith305

greaterpersonalstress;andincreasedresilienceamongthosewithlowstressarisingfromtheirpersonal306

lives(e.g.,relationshipsarestable/supportive).307

Whileweconcludethatseverityofcombatstresswasnotindependentlyassociatedwithpost-308

deploymentalcoholmisuseinthiscohort,wemakenoinferenceregardingtheeffectsofdeployment309

(withorwithoutcombatexposure)perseonriskofalcoholmisuse.Apreviouslarge-scaleprospective310

analysisfromtheMillenniumCohortStudy(MCS)addressedthatquestionandfoundthat,relativeto311

notdeploying,deploymentwithcombatexposure(butnotdeployingwithoutcombatexposure)was312

associatedwithincreasedriskofonsetofbingedrinkingamongactive-dutypersonnel;andwithonsetof313

bingedrinking,heavydrinking,andalcohol-relatedproblemsamongReserve/NationalGuardpersonnel314

(e.g.,Jacobsonetal.,2008).Wecannotmakesimilarcomparisons,asallsoldiersinthecurrentstudy315

deployedtoAfghanistan–withmostreportingexposuretoseveralcombatstressors.Futureresearch316

shouldexaminetheeffectsofpersonallifestressandotherriskfactorsforalcoholmisuseinsamplesof317

servicemembersdeployedtonon-combatpositions.318

Contrarytoexpectation,pre-deploymentemotionaldisorderwasnotassociatedwithincreased319

riskofpost-deploymentheavydrinkingorAUD/SUD.Peri-deploymentPTSDsymptomsalsolacked320

associationswiththealcoholmisuseoutcomes;andperi-deploymentMDE/GADsymptomsonly321

exhibitedanassociationwithpersistenceofHDfrompre-deploymentto3monthspost-deployment.322

TheselargelynullfindingsdivergefromresultsofpriorstudiesthatfoundrelationshipsbetweenPTSD,323

15

MDE,andalcoholmisuse.Among358NationalGuardsoldiersdeployedtoIraq,PTSDsymptomseverity324

wasassociatedwithincreasedriskofnew-onsetAUD(Kehleetal.,2012).BaselinesymptomsofPTSD325

and/orMDEcontributedtopredictionofincidenceofalcohol-relatedproblems(endorsing1ormore326

indicatorsofalcoholabuse)–butnotincidenceofbingeorheavydrinking–intheaforementionedMCS327

investigationthatincludedbothdeployedandnon-deployedservicemembers(Jacobsonetal.,2008).328

Disparitiesinstudyresultsmayreflectdifferencesinsamplecharacteristicsorintheconsiderationor329

operationalizationofmentalhealthandotherpredictorvariables.Althoughrobustpredictiveeffectsof330

mentalhealthvariableswerenotfoundinthisanalysis,alcoholmisusedisplaysconsistentcross-331

sectionalassociationswithPTSD,MDE,andotherdisordersinmilitarysamples(Steinetal.,2017;332

Thomasetal.,2010);thus,co-occurringmentalhealthproblemsmustbeconsideredinclinical333

interventionsandothereffortstoreducehazardousdrinkingandAUD/SUD.334

Male,younger,andnever-marriedsoldiersdisplayedincreasedoddsofonsetofheavydrinking335

post-deployment,convergingwithpreviousfindingsofelevatedriskofhazardousdrinkinginthese336

subgroups(BoulosandZamorski,2016,Jacobsonetal.,2008).Themarkedincreaseinriskydrinking337

pre-topost-deploymentamongsoldiersaged18-20distinguishesthemfromothersandsignalsthat338

youngsoldierswhodeploy(particularlythosepossessingotherriskfactors)maybeasubgroupto339

considerfortargetedpreventionefforts,eveniftheriseispartlyattributabletosomeofthemattaining340

legaldrinkingagebetweenassessments.341

Moregenerally,thisstudyconveysinformationregardingthescopeofalcoholmisuseamong342

Armysoldiersshortlybeforeandatmultiplepointsaftertheirdeploymenttoacombatzone.343

Approximatelyhalfofrespondentsreportedbingedrinkingandnearlyone-quarterendorsedheavy344

drinkingduringthemonthbeforepre-deploymentassessment.Althoughdifferencesinstudydesign345

precludedefinitivecomparisons,pre-deploymentprevalenceofheavydrinkinginthissample(23%)346

16

appearssimilartoprevalenceofarelatedoutcome(regularbingedrinking;27%)amongNavy/Marine347

Corpspersonnelpreparingtodeploy(Harbertsonetal.,2016).348

TypicalschedulingoftheArmy’sPost-DeploymentHealthReassessment(PDHRA)placesitin349

closestproximitytothePPDST2assessment.Giventhatsoldiersendorsingheavydrinkingwouldlikely350

scoreinthehigh-riskrange,itisstrikingthatT2prevalenceofheavydrinkingwastwicethereported351

rateof“highriskforalcoholabuse”amongPDHRArespondentsduring2008-2014(Hurt,2015).This352

maysignalunder-estimationofthetruescopeofalcoholmisusewhennon-confidentialformsof353

assessmentsuchasthePDHRAareused(Warneretal.,2011).354

Finally,substantiallyhigherratesofpast-monthbingeandheavydrinkingwereobservedamong355

PPDSrespondents(atallwaves)comparedtoacohortofnewsoldiers(Steinetal.,2017).Higher356

prevalenceofhazardousdrinkingamongPPDSrespondentscouldreflectincreasedalcoholmisusewith357

longerArmytenure,selectionoflightdrinkers/abstainersoutofArmyservice,ordifferencesin358

demographiccompositionorothercharacteristicsofthetwosamples.Potentialcontributionsofthese359

factorsshouldbeexploredinfutureresearch.360

Novelaspectsofthecurrentinvestigationincludeavailabilityofoutcomedataatboth3and9361

monthspost-deployment;inclusionofnumberofpriordeploymentsasapotentialriskfactor;increased362

granularityinmeasurementofcombatstressexposure(0-16indexversusdichotomouscharacterization363

ofdeploymentstatusorcombatexposure);andjointconsiderationofarangeofperi-deployment364

stressorsandsymptomsinrelationtopost-deploymentheavydrinkingandAUD/SUD.365

Thestudyalsohasseverallimitations.ConclusivedifferentialdiagnosisofAUDversusSUDwas366

notpossible.Retrospectiveself-reportdataarevulnerabletorecallandresponsebiases;inthecaseof367

alcoholanddruguseassessment,under-reportingmayoccur.Estimatesofnon-alcoholdrugusemight368

bemoresusceptibletothisbiasthanestimatesofalcoholusegivenfearofrepercussionsforadmitting369

druguseinlightoftheArmy’szero-tolerancepolicy.Under-reportingofbothalcoholanddruguse370

17

couldhavebeenaccentuatedatthepre-deploymentassessment,duetoheighteneddesirestoappear371

“combat-ready”.372

Weightswereappliedtomitigateimpactsofattritionandtoenhancegeneralizabilitytothe373

broaderpopulationofdeployedsoldiers.Nevertheless,selectionfactorsmayhaveinfluencedthe374

results(i.e.,soldierswhocompletedallassessmentsmayhavedifferedfromthelargerpopulationof375

soldiersonvariablesnotadjustedforviaweightsorcovariates).TheT0surveydidnotassesslifetime376

HD;thus,new-onsetofHDcouldonlybedefinedinrelationtodrinkingduringthemonthbeforeT0377

assessment.Finally,lowrepresentationlimitedpowertodetectriskdifferencesforcertainsubgroups378

(e.g.,females).Moreresearchisneededtoinvestigatewhethersexdifferencesarepresentwithrespect379

toriskfactorsforpost-deploymentalcoholmisuse.380

Inconclusion,pre-andpost-deploymentalcoholmisusewascommonamongsoldiersfrom3381

U.S.ArmyBrigadeCombatTeamsthatdeployedtoAfghanistan.Severityofpersonallifestressduring382

deployment–butnotseverityofcombatstress–wasassociatedwithpost-deploymentonsetofheavy383

drinkingandincidenceandpersistenceofAUD/SUD.Pre-deploymentbingedrinkingalsopredicted384

onsetofheavydrinkingandAUD/SUDpost-deployment.Detectionofriskydrinkingoccurringshortly385

beforedeploymentwouldprovideanopportunityforearlyinterventiontopreventonsetofmoresevere386

alcohol-relatedproblems.Additionally,effortstoidentifyandassistsoldiersexperiencingsubstantial387

personallifestressduringdeploymentcouldprovebeneficialnotonlyforreductionofalcoholmisuse,388

butpossiblyforoverallmentalhealth.389

390

18

Acknowledgments391

TheArmySTARRSTeamconsistsofCo-PrincipalInvestigators:RobertJ.Ursano,MD(UniformedServices392

UniversityoftheHealthSciences)andMurrayB.Stein,MD,MPH(UniversityofCaliforniaSanDiegoand393

VASanDiegoHealthcareSystem)394

SitePrincipalInvestigators:StevenHeeringa,PhD(UniversityofMichigan),JamesWagner,PhD395

(UniversityofMichigan),andRonaldC.Kessler,PhD(HarvardMedicalSchool)396

Armyliaison/consultant:KennethCox,MD,MPH(USAPHC(Provisional))397

Otherteammembers:PabloA.Aliaga,MA(UniformedServicesUniversityoftheHealthSciences);COL398

DavidM.Benedek,MD(UniformedServicesUniversityoftheHealthSciences);LauraCampbell-Sills,PhD399

(UniversityofCaliforniaSanDiego);Chia-YenChenDSc(HarvardMedicalSchool);CarolS.Fullerton,PhD400

(UniformedServicesUniversityoftheHealthSciences);NancyGebler,MA(UniversityofMichigan);Joel401

Gelernter(YaleUniversity);RobertK.Gifford,PhD(UniformedServicesUniversityoftheHealth402

Sciences);PaulE.Hurwitz,MPH(UniformedServicesUniversityoftheHealthSciences);SoniaJain,PhD403

(UniversityofCaliforniaSanDiego);Tzu-ChegKao,PhD(UniformedServicesUniversityoftheHealth404

Sciences);LisaLewandowski-Romps,PhD(UniversityofMichigan);HollyHerbermanMash,PhD405

(UniformedServicesUniversityoftheHealthSciences);JamesE.McCarroll,PhD,MPH(Uniformed406

ServicesUniversityoftheHealthSciences);JamesA.Naifeh,PhD(UniformedServicesUniversityofthe407

HealthSciences);TszHinHinzNg,MPH(UniformedServicesUniversityoftheHealthSciences);Matthew408

K.Nock,PhD(HarvardUniversity);NancyA.Sampson,BA(HarvardMedicalSchool);CDRPatcho409

Santiago,MD,MPH(UniformedServicesUniversityoftheHealthSciences);JordanW.Smoller,MD,ScD410

(HarvardMedicalSchool);andAlanM.Zaslavsky,PhD(HarvardMedicalSchool).411

412

FinancialSupport:ArmySTARRSwassponsoredbytheDepartmentoftheArmyandfundedunder413

cooperativeagreementnumberU01MH087981(2009-2015)withtheU.S.DepartmentofHealthand414

19

HumanServices,NationalInstitutesofHealth,NationalInstituteofMentalHealth(NIH/NIMH).415

Subsequently,STARRS-LSwassponsoredandfundedbytheDepartmentofDefense(USUHSgrant416

numberHU0001-15-2-0004).Thecontentsaresolelytheresponsibilityoftheauthorsanddonot417

necessarilyrepresenttheviewsoftheDepartmentofHealthandHumanServices,NIMH,Departmentof418

theArmy,orDepartmentofDefense.419

420

ConflictofInterest:Dr.SteinhasinthepastthreeyearsbeenaconsultantforActelion,Dart421

Neuroscience,HealthcareManagementTechnologies,Janssen,OxeiaBiopharmaceuticals,Pfizer,422

ResilienceTherapeutics,andTonixPharmaceuticals.Inthepast3years,Dr.Kesslerreceivedsupportfor423

hisepidemiologicalstudiesfromSanofiAventis;wasaconsultantforJohnson&JohnsonWellnessand424

Prevention,Shire,Takeda;andservedonanadvisoryboardfortheJohnson&JohnsonServicesInc.Lake425

NonaLifeProject.Kesslerisaco-ownerofDataStat,Inc.,amarketresearchfirmthatcarriesout426

healthcareresearch.Theremainingauthorshavenofinancialdisclosures.427

428

Ethicalstandards:Theauthorsassertthatallprocedurescontributingtothisworkcomplywiththe429

ethicalstandardsoftherelevantnationalandinstitutionalcommitteesonhumanexperimentationand430

withtheHelsinkiDeclarationof1975,asrevisedin2008.431

432

20

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25

Table1

Weightedprevalenceofpast-monthbingedrinking,heavydrinking,andAUD/SUDamongU.S.Army

soldierspre-andpost-deployment(n=4645)

Pre-

deployment(T0)

3monthspost-

deployment(T2)

9monthspost-

deployment(T3)

BingeDrinking 52.5%(1.0%) 52.5%(1.0%) 41.3%(0.9%)

HeavyDrinking 23.3%(0.7%) 26.1%(0.8%) 22.3%(0.7%)

AUD/SUD - 6.8%(0.4%) 10.4%(0.5%)

Note.AUD/SUD=AlcoholorSubstanceUseDisorder.Valuesareweightedprevalence(standarderror).

AnalysissamplewascomprisedofPre/PostDeploymentStudyrespondentswhocompletedsurveysat

all4waves:pre-deployment(T0),within1monthofre-deploymenttotheU.S.(T1),3monthspost-

deployment(T2),and9monthspost-deployment(T3).NodataareshownforT1becauseneither

alcoholbingefrequencynorAUD/SUDwereassessedatthatwave.TheT0surveydidnotassesspast-

monthAUD/SUD;prevalenceoflifetimeAUD/SUDatT0was20.4%(0.7%).

26

Table2

Adjustedoddsofonsetandpersistenceofpost-deploymentHeavyDrinkingamongArmySTARRSPre/PostDeploymentSurveyrespondents

AdjustedOdds-Ratio(95%CI)

OnsetofHeavyDrinking

post-deployment(n=3575)

PersistenceofHeavyDrinking

frompre-topost-deployment(n=1070)

AnyHD ChronicHD1 AnyHD ChronicHD1

Soldiercharacteristics(assessedatT0)

Age,y 0.95(0.93-0.98) 0.94(0.91-0.98) 1.00(0.96-1.04) 1.01(0.98-1.05)

WaldΧ2(1) 10.82** 8.21** 0.00 0.49

Sex

Male 1.00 1.00 1.00 1.00

Female 0.62(0.41-0.94) 0.35(0.15-0.82) 1.57(0.76-3.23) 0.63(0.20-2.01)

WaldΧ2(1) 5.16* 5.76* 1.49 0.61

Race

White 1.00 1.00 1.00 1.00

Black 0.75(0.53-1.06) 0.84(0.51-1.40) 0.81(0.52-1.27) 0.76(0.47-1.23)

Asian 0.66(0.41-1.07) 0.90(0.47-1.73) 0.36(0.16-0.84) 0.49(0.23-1.01)

27

Other 1.21(0.84-1.73) 1.44(0.91-2.28) 0.93(0.57-1.53) 0.63(0.37-1.08)

WaldΧ2(3) 9.43* 3.74 6.13 7.96*

Ethnicity

Non-Hispanic 1.00 1.00 1.00 1.00

Hispanic 0.88(0.64-1.22) 0.86(0.55-1.37) 0.70(0.45-1.08) 0.92(0.56-1.51)

WaldΧ2(1) 0.56 0.40 2.59 0.12

Education

Highschooldegree 1.00 1.00 1.00 1.00

Generalequivalencydiploma 0.69(0.42-1.15) 0.98(0.46-2.09) 0.82(0.50-1.37) 0.81(0.49-1.35)

Collegedegree 0.85(0.63-1.15) 1.10(0.79-1.53) 1.10(0.80-1.52) 0.78(0.50-1.22)

WaldΧ2(2) 2.51 0.41 1.05 2.17

Maritalstatus

Married 1.00 1.00 1.00 1.00

Divorced/separated/widowed 1.21(0.85-1.70) 1.02(0.53-1.96) 1.24(0.77-1.98) 0.92(0.61-1.39)

Nevermarried 1.44(1.12-1.85) 1.79(1.28-2.50) 1.51(1.07-2.12) 1.23(0.91-1.66)

WaldΧ2(2) 8.84* 12.42** 5.42 2.55

Pre-deploymentfactors(assessedatT0)

28

PriorDeployments

Zero 1.00 1.00 1.00 1.00

One 0.85(0.67-1.08) 0.77(0.49-1.20) 0.97(0.70-1.35) 1.12(0.75-1.68)

Twoormore 0.80(0.58-1.09) 1.00(0.59-1.68) 1.19(0.83-1.70) 1.08(0.64-1.80)

WaldΧ2(2) 2.56 1.75 1.24 0.33

Past-monthBingeDrinking 3.21(2.57-4.02) 2.69(1.89-3.82) - -

WaldΧ2(1) 104.68*** 30.52*** - -

Past-monthPTSD,MDE,GAD,orSI 0.78(0.52-1.17) 0.76(0.43-1.35) 0.97(0.58-1.63) 0.77(0.46-1.29)

WaldΧ2(1) 1.48 0.87 0.01 0.99

Peri-deploymentfactors(assessedatT1)

Combat/deploymentstress(standardized) 1.03(0.91-1.16) 1.03(0.89-1.20) 1.00(0.85-1.18) 1.11(0.95-1.30)

WaldΧ2(1) 0.16 0.14 0.00 1.73

Personallifestress(standardized) 1.20(1.06-1.35) 1.21(0.98-1.49) 0.99(0.86-1.14) 1.03(0.88-1.21)

WaldΧ2(1) 8.64** 3.08 0.04 0.14

Militarylifestress(standardized) 1.01(0.89-1.15) 0.94(0.77-1.13) 0.97(0.84-1.10) 0.94(0.81-1.10)

WaldΧ2(1) 0.01 0.48 0.28 0.60

PTSDsymptomseverity(standardized) 1.14(0.99-1.30) 1.10(0.91-1.33) 1.06(0.87-1.29) 0.95(0.79-1.16)

29

WaldΧ2(1) 3.43 0.96 0.36 0.22

MDE/GADsymptomseverity(standardized) 1.02(0.87-1.20) 1.03(0.81-1.32) 1.20(1.02-1.40) 1.21(0.95-1.55)

WaldΧ2(1) 0.08 0.07 5.09* 2.33

Note.CI=confidenceinterval;HD=heavydrinking;PTSD=posttraumaticstressdisorder;MDE=majordepressiveepisode;GAD=generalized

anxietydisorder;SI=suicidalideation.Eachcolumndisplaystheresultsforaseparateweights-adjustedlogisticregressionmodel.Modelsalso

adjustedforBrigadeCombatTeam.Significantadjustedoddsratios(wheretheoverallWaldΧ2testisalsostatisticallysignificant)arebolded.

*p<.05;**p<.005;***p<.0005.

1ChronicHDwasdefinedasheavydrinkingthatwaspresentatboth3monthsand9monthspost-deployment(i.e.,atbothT2andT3).

30

Table3

Adjustedoddsofonsetandpersistenceofpost-deploymentAUD/SUDamongArmySTARRSPre/PostDeploymentSurveyrespondents

AdjustedOddsRatio(95%CI)

IncidenceofAUD/SUD

post-deployment(n=3729)

PersistenceofAUD/SUD

frompre-topost-deployment(n=916)

AnyAUD/SUD ChronicAUD/SUD1 AnyAUD/SUD ChronicAUD/SUD1

Pre-deploymentfactors(assessedatT0)

Numberofpriordeployments

Zero 1.00 1.00 1.00 1.00

One 0.57(0.30-1.05) 0.52(0.27-1.01) 0.94(0.64-1.40) 1.05(0.63-1.73)

Twoormore 0.81(0.40-1.65) 0.58(0.27-1.25) 0.72(0.50-1.04) 0.84(0.55-1.28)

WaldΧ2(2) 3.40 4.47 3.02 0.86

Past-monthbingedrinking 1.84(1.27-2.70) 1.93(1.26-2.95) - -

WaldΧ2(1) 10.30** 9.09** - -

Past-monthPTSD,MDE,GAD,orSI 0.77(0.38-1.58) 0.54(0.24-1.22) 0.84(0.44-1.62) 1.06(0.52-2.13)

WaldΧ2(1) 0.50 2.22 0.27 0.02

Peri-deploymentfactors(assessedatT1)

31

Combat/deploymentstress(standardized) 1.22(0.96-1.55) 1.29(0.97-1.70) 1.05(0.90-1.23) 1.12(0.96-1.30)

WaldΧ2(1) 2.61 3.07 0.34 1.96

Personallifestress(standardized) 1.54(1.25-1.89) 1.72(1.41-2.09) 1.19(0.99-1.44) 1.30(1.08-1.56)

WaldΧ2(1) 16.99*** 28.48*** 3.49 7.80**

Militarylifestress(standardized) 1.02(0.89-1.16) 1.06(0.83-1.35) 1.20(1.02-1.41) 1.07(0.89-1.27)

WaldΧ2(1) 0.08 0.22 5.04* 0.49

PTSDsymptoms(standardized) 1.04(0.77-1.40) 0.94(0.64-1.37) 0.93(0.72-1.20) 0.87(0.65-1.16)

WaldΧ2(1) 0.07 0.11 0.35 0.88

MDE/GADsymptoms(standardized) 1.01(0.72-1.42) 0.99(0.69-1.44) 1.23(0.90-1.70) 1.24(0.92-1.68)

WaldΧ2(1) 0.00 0.00 1.69 1.97

Note.AUD/SUD=AlcoholorSubstanceUseDisorder;CI=confidenceinterval;PTSD=posttraumaticstressdisorder;MDE=majordepressive

episode;GAD=generalizedanxietydisorder;SI=suicidalideation.Eachcolumndisplaystheresultsforaseparateweights-adjustedlogistic

regressionmodel.Tostreamlinethetable,soldiercharacteristicsincludedinthemodels(age,sex,race,ethnicity,education,andmaritalstatus)

areomitted;nonedisplayedsignificantassociationswithincidenceorpersistenceofAUD/SUD(ps>.10).ModelsalsoadjustedforBrigade

CombatTeam.Significantadjustedoddsratios(wheretheoverallWaldΧ2testisalsostatisticallysignificant)appearinbold.

*p<.05;**p<.005;***p<.0005.

1ChronicAUD/SUDwasdefinedasthedisorderbeingpresentatboth3monthsand9monthspost-deployment(i.e.,atbothT2andT3).

32

FigureCaptions

Figure1.Weightedprevalencebygenderofbingedrinkingandheavydrinkingatpre-deployment(T0),

3monthspost-deployment(T2),and9monthspost-deployment.Groupn’stotalslightlylessthan4645

duetoraremissinggenderdata.Prevalenceofbingedrinkingandheavydrinkingwasloweramong

womenthanmenatallwaves[Χ2(1)=21.98to63.42,ps<.001].

Figure2.Weightedprevalencebyagegroupofheavydrinkingatpre-deployment(T0),3monthspost-

deployment(T2),and9monthspost-deployment.Groupn’stotalslightlylessthan4645duetorare

missingagedata.Prevalenceofheavydrinkingdifferedbyagegroupatallwaves[Χ2(3)=85.01to92.02,

ps<.001].

33

0%

10%

20%

30%

40%

50%

60%

Males (n=4358) Females (n=276) Males (n=4358) Females (n=276)

Binge Drinking Heavy Drinking

Wei

ghte

d pr

eval

ence

Pre-deployment 3 months post-deployment 9 months post-deployment

34

0%

5%

10%

15%

20%

25%

30%

35%

40%

Pre-deployment 3 months post-deployment 9 months post-deployment

Weightedprevalen

ceofH

eavy

Drinking

18 to 20 (n=731) 21 to 25 (n=1796) 26 to 30 (n=1114) 31 and older (n=989)

35

SupplementaryTable1

Item-levelcodingforDeploymentStressScale

Combatpatrol/dangerousduty <10times=0points;10ormoretimes=1point

Firedroundsatenemy/Tookenemyfire <10times=0points;10ormoretimes=1point

Wounded 0times=0points;1ormoretimes=1point

Hadclosecall(e.g.,equipmentshotoff) 0or1time=0points;2ormoretimes=1point

Unitmemberseriouslywounded/killed 0=0points;1to4times=1point;5ormoretimes=2points

Responsibleforenemycombatantdeath 0times=0points;1ormoretimes=1point

Responsiblefornon-combatantdeath 0times=0points;1ormoretimes=1point

ResponsibleforU.S.orallydeath 0times=0points;1ormoretimes=1point

Witnessedhomes/villagesdestroyed 0times=0points;1ormoretimes=1point

Directlyexposedtodeath/violence 0to4times=0;5ormoretimes=1point

Seriousphysicalassaultorfight1,2 0times=0points;1ormoretimes=1point

Sexualassault2 0times=0points;1ormoretimes=1point

Bullied/hazedbyunitmembers2 0times=0points;1ormoretimes=1point

Anyotherhighlystressfulexperience2 0=0points;1time=1point;2ormoretimes=2points

Note.Codingschemawasderivedduringpreliminaryanalysisofdatafromarestrictedsampleof1,145

respondentswhocompletedthePPDST0,T1,andT2surveys.Scoringwasinformedbyexaminationof

thefunctionalformofrelationshipsofeachratingtoaclinicallysalientoutcome(new-onsetofPTSDor

majordepressionatT2).TheDeploymentStressScalescorewascomputedbysummingpointsassigned

foreachitem(theoreticalrange=0-16).

1Separateitemsassessedphysicalassaultandgettingintoafight,buttheywerecollapsedforscoring.

36

2Toisolatecombatstress,ashorterformoftheDeploymentStressScalewasderivedafterexcluding4

items.Noneofthereportedresultschangedwhentheshortformwasusedinplaceofthefull

DeploymentStressScale.

37

SupplementaryTable2

Latentstructureof7surveyitemsassessingstressindifferentlifedomains:2-factormodel

Promax-rotatedfactorloadings

Personallifestress Armylifestress

Financialsituation 0.51 0.05

Lovelife 0.70 -0.02

Legalproblems 0.36 0.05

Relationshipwithfamily 0.76 -0.03

Problemsexperiencedbylovedones 0.75 -0.01

Problemswithchainofcommand -0.06 0.82

Problemswithunitmembers 0.02 0.73

Note.Exploratoryfactoranalysiswasconductedwithminimumresidualestimationandpromax

rotation.Arangeof1-to3-factorsolutionswasattempted;however,aninvalidsolutionwasobtained

when3factorswerespecified.The1-factormodelwasrejectedduetopooroverallfit(RMR=.10;

TLI=.68;RMSEA=.16).Theoverallfitofthe2-factorsolutionwasgood(RMR=.03;TLI=.95;RMSEA=.06);

eachitemdisplayedasalient(>.32)loadingononeofthetwofactors;cross-loadingswereabsent,and

thetwofactorswerereadilyinterpretable.

38

SupplementaryTable3

Prevalenceofpast-monthHeavyDrinkingandBingeDrinkingamongU.S.Armysoldierspre-andpost-deployment

n1 BingeDrinking(5+alcoholicdrinksatleastonce) HeavyDrinking(5+alcoholicdrinksatleastweekly)

T0 T2 T3 T0 T2 T3

Overall 4645 52.5%(1.0%) 52.5%(1.0%) 41.3%(0.9%) 23.3%(0.7%) 26.1%(0.8%) 22.3%(0.7%)

Sex:Male 4358 53.8%(1.0%) 53.3%(1.0%) 42.6%(0.9%) 24.1%(0.7%) 26.6%(0.8%) 23.1%(0.7%)

Sex:Female 276 28.8%(3.1%) 36.7%(3.5%) 17.6%(3.4%) 8.3%(2.7%) 14.7%(2.3%) 6.9%(1.8%)

Race:White 3358 54.7%(1.1%) 56.0%(1.0%) 43.4%(0.9%) 24.2%(0.9%) 27.6%(1.0%) 22.8%(0.8%)

Race:Black 507 38.0%(2.9%) 34.5%(2.6%) 28.1%(2.3%) 18.5%(1.9%) 18.3%(1.9%) 18.8%(1.8%)

Race:Asian 195 43.9%(3.4%) 45.6%(3.0%) 38.1%(3.5%) 18.0%(2.5%) 17.3%(3.1%) 20.7%(3.3%)

Race:Other 569 55.5%(2.3%) 51.2%(2.2%) 43.3%(2.4%) 23.7%(1.9%) 27.1%(1.8%) 23.5%(1.4%)

Ethnicity:Non-Hispanic 3865 52.4%(1.0%) 53.1%(1.0%) 41.1%(0.9%) 23.4%(0.9%) 26.4%(1.0%) 22.2%(0.8%)

Ethnicity:Hispanic 762 52.7%(2.0%) 49.6%(2.0%) 42.7%(2.2%) 22.4%(1.7%) 24.2%(1.5%) 22.8%(1.6%)

Age:18to20 731 36.4%(1.8%) 49.0%(2.1%) 48.2%(1.9%) 18.2%(1.7%) 30.7%(1.8%) 33.3%(1.9%)

Age:21to25 1796 63.2%(1.4%) 61.1%(1.3%) 46.1%(1.2%) 30.0%(1.0%) 32.6%(1.3%) 24.1%(0.9%)

Age:26to30 1114 56.0%(1.4%) 54.4%(1.5%) 39.8%(1.4%) 24.4%(1.2%) 23.9%(1.1%) 21.1%(1.3%)

Age:31andolder 989 41.6%(1.6%) 39.6%(1.7%) 32.3%(1.4%) 14.9%(1.4%) 16.1%(1.2%) 14.9%(1.0%)

39

Note.Valuesareweightedprevalence(standarderror).Atallwaves,prevalenceofBDandHDdifferedsignificantlybysex[Χ2(1)=21.98to63.42,

allps<.001]andagegroup[Χ2(3)=63.19to193.46,allps<.001].PrevalenceofBDdifferedbyraceatallwaves[Χ2(3)=42.63to88.40,ps<.001],

andprevalenceofHDdifferedbyraceatT0[Χ2(3)=13.99,p=.003]andT2[Χ2(3)=28.62,p<.001].Nodifferenceswereobservedbasedon

ethnicity(ps>.14).1Somesubgroupsamplesizestotalslightly<4645duetorarecasesofmissingdemographicdata.

40

SupplementaryTable4

PrevalenceofAlcoholorSubstanceUseDisorder(AUD/SUD)amongsoldierspre-andpost-deployment

n1 LifetimeAUD/SUD

atT0

Past-month

AUD/SUDatT2

Past-month

AUD/SUDatT3

Overall 4645 20.4%(0.7%) 6.8%(0.4%) 10.4%(0.5%)

Sex:Male 4358 20.7%(0.7%) 6.9%(0.4%) 10.6%(0.5%)

Sex:Female 276 13.2%(2.1%) 4.2%(1.8%) 5.7%(2.1%)

Race:White 3358 21.1%(0.8%) 6.8%(0.4%) 10.4%(0.5%)

Race:Black 507 16.5%(2.0%) 5.5%(0.9%) 7.1%(1.1%)

Race:Asian 195 14.3%(2.7%) 7.2%(1.8%) 13.2%(3.2%)

Race:Other 569 21.8%(1.5%) 7.9%(1.0%) 12.7%(1.3%)

Ethnicity:Non-Hispanic 3865 20.8%(0.8%) 6.8%(0.4%) 10.5%(0.6%)

Ethnicity:Hispanic 762 18.2%(1.6%) 7.2%(1.0%) 10.1%(1.2%)

Age:18to20 731 9.5%(1.5%) 7.0%(1.0%) 10.7%(1.2%)

Age:21to25 1796 21.8%(1.1%) 7.6%(0.6%) 11.7%(0.9%)

Age:26to30 1114 24.1%(1.5%) 7.0%(0.8%) 10.0%(0.9%)

Age:31andolder 989 20.2%(1.2%) 5.4%(0.8%) 9.0%(1.0%)

Note.Valuesareweightedprevalence(standarderror).AllestimatesofAUD/SUDprevalencediffered

significantlybysex[Χ2(1)=4.25to11.60,ps<.05].PrevalenceoflifetimeAUD/SUDatT0[Χ2(3)=13.75,

p=0.003]andofpast-monthAUD/SUDatT3[Χ2(3)=11.94,p=0.008]differedbyrace.Prevalenceof

lifetimeAUD/SUDatT0[Χ2(3)=60.88,p<0.001]differedbyagegroup.Nodifferenceswereobserved

basedonethnicity(ps>.13).1Somesubgroupsamplesizestotalslightly<4645duetorarecasesof

missingdemographicdata.