DTIC ADA617718: Risk Factors for Relapse to Problem Drinking Among Current and Former US Military Personnel: A Prospective Study of the Millennium Cohort

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by  Defense Technical Information Center

94 E.C.Williamsetal./DrugandAlcoholDependence148(2015)93–101

1. Introduction completed a baseline questionnaire (Wave 1) and two consecutive follow-up

surveys(Wave2:2004–2006andWave3:2007–2008).ThebaselineMillennium

Alcoholuseisthethird-greatestcontributortomorbidityand Cohort survey instrument included a skip pattern such that participants who did
notendorsedrinkingmorethan12alcoholbeveragesinthelastyearwereasked
mortalityintheUnitedStates(Mokdadetal.,2004)andcomesat
enormous co stto societ y(Harw oodetal .,1 998 ,2009 ).Wh ilema ny tsou rsvkeipys thaes rwemelaliansinrge aplocrothoofl-rderliantkeidn gqumesotrieontsh. aTnhe1r2efoalrceo, hcoomlicplbeetvioenra ogfe aslli nthtrheee

peopledrinkalcoholathealthylevels,approximately9%drinkat lastyearwereconsideredinitialinclusioncriteria.Participantsadditionallyhad
levels t hat re sult in the develo pment of problems (e .g., famil ial to( 1)res pond toquestion sperta iningto“ problem drinking”a tbaseline,(2 )be
in rem ittancef rom problem drinkinga tW ave2and thusatr isk forrelaps e,a nd
orlegalproblems;Grantetal.,2004).Oncepeopledrinkatthese
(3)havecompletedataonexposuresandproblemdrinkingstatusinordertobe
levels,theyoftenhaveahardtimechangingdespiteexperiencing
eligibleforthisstudy(Fig.1).Therewere6909participantswhometthesecriteria.
resulta ntpr oblem s.Wh il esom epeo plewith problem drinkingcan

resolveproblemswithorwithoutstoppingalluse,manycannot 2.2. Problemdrinking

(Dawsonetal.,2007;NationalCenteronAddictionandSubstance
Abuse, 2 01 2) T herefo re, prob lem dr ink ing can be con sidered a Baseline problem drinking was assessed using the lifetime version of the CAGE
questionnaire(Ewing,1984;Haveyoueverfelttheneedtocutdownyourdrinking,
chroniccondition(McLellanetal.,2000)thatrelapsesandremits
suchtha tpeoplem oveinan d out ofpro blem drinking sep arated faelmt aonrnnionygedey bey ocprietniceisr?m) oafn ydotuhre dPriRnIkMinEg-,M hDadP gautiieltnyt feHeelainltghs Qabuoeustti dorninnakiirneg,( PtaHkQen),

byintervalsofabstinence,riskydrinking,oruseatrecommended whichassessesfivealcohol-relatedconsequencesoccurringmorethanoncedur-
lev els(Daws on etal.,2007 ;Vail lant,1983 ;V aill an tandMilofsky, ingthe last12m ont hs(Spitzeretal .,1999).PHQa lcohol-rela tedit emsi nclud e(1)

drinkingalcoholeventhoughadoctorsuggestedstoppingbecauseofhealthprob-
1982).
lems;(2)beinghighfromalcoholorhungoverwhileworking,beinginschool,or
Multiple studies have described high rates of problem drink-
takingcareofchildren;(3)missingorbeinglateforwork,school,orotheractivities
ingamongm ilitary servic emember s(Ar medF or cesSurve illance becaus eofd ri nking;(4) ha vingpro ble msge tting alo ngwi thpeop le while drinking;

Center,2013;Brayetal.,2013,2010;Clarke-Walperetal.,2013; and(5)drivingacarafterhavingseveraldrinksorafterdrinkingtoomuch.Baseline
Heltem eseta l.,201 3; Ins titute ofMed icine,2012;Jac ob son etal., prob lem drinki ng wa s defi ned as endorse ment of o ne o r more ite ms from e ither the
CAGEorPHQ.Remittentproblemdrinkingwasdefinedbasedonnon-endorsement
2008; Stahre et al., 2009). Problem drinking may be particularly
costly in this po pul ation d ue to ass ociated d ecrea se d work per- oinf ga,nwy aPsHdQe ifitnemed abta tsheed Wonaveen 2d soursrveemye. nThteo fstaundyyP oHuQtciotmeme, aretlWapasvee to3 .pTrhoeblCeAmG dEriwnkas-

formance(Blumeetal.,2010;Frone,2006;Harwoodetal.,2009), notusedtodefineproblemdrinkingatWaves2or3duetoitslifetimetimeframe.

impairedathleticperformance(O’BrienandLyons,2000),increased
riskofinj ury(Har risetal.,200 9;Willia mse tal.,20 12)an dcomor- 2.3. Exposures

bid mental health disorders (Bray et al., 2010; LeardMann et al.,
Demographic characteristics: Demographic characteristics included sex, age
2013),andmultipleotheradversehealthoutcomesincludingsleep (17–24, 25–34, 3 5–44, and >44 years), marita l status (never married, mar ried,
deprivatio n and fa tigue (Lamond and D awson, 1 999; Roth and divorced orwid owed),e duca tion (somec ollegeor less,ba chelor’ sdegreeo rhigher),

Roehrs,1996)thatmayleadtoperformanceimpairment(Harwood andself-reportedrace/ethnicity(whitenon-Hispanic,blacknon-Hispanic,Hispanic,
etal.,20 09;In stitu teof Med ici ne,2012).The costsofalco holuseto and other). Asian and Native Am erican participants, as we ll as those of unknown
race,wereincludedinthe“Other”groupduetosmallnumbers.Allcharacteristics
theDepartmentofDefense(DoD)wererecentlyestimatedat$425
mil lionperyear (D alletal., 2007; Instit uteofMe dicine,20 12 ). e2xbceecpatu msearititmal asytavtuarsy woevreer otbimtaein.ed at baseline; marital status was obtained at Wave

Militaryservicemembersmaybepronetorelapseafterprevious Militaryservicecharacteristics:Militarycharacteristicsincludedservicebranch
recoverype riods,g ivenacul ture of alcoho lu seasa copin gmech- (Army,Navy /Coast Guard,MarineC orps,Air Force),service compone nt(activ eduty,

Reserve/NationalGuard),occupation(combatspecialist,healthcare,other)andpay
anism for stressful or traumatic events associated with military
grade(juniorenlisted[E00–E05],seniorenlisted[E06–E09],officer[warrantand
dutiesorcombatexposure(AmesandCunradi,2004;Amesetal., enliste d]).De ploymen texperience waso btainedb etweenWa ves1an d2andc ate-
2007,2 00 9;Instit uteofMe dicine, 2012 ).Howev er,the preva len ce gorizedas nodeployme nt,deploym ent withoutc ombatex posure ,a ndd e ploy ment

anduniquepredictorsofrelapseareunknowninmilitaryperson- withcombatexposure.Combatexposurewasassessedusing5itemsthatasked
nelf orwhom theexpe rie nceswit hin themilitar ym aysign ificantly “over the pas t 3 years” w hether r esponden ts ha d persona lly: (1 ) w itnes sed a death
duetowar,disaster,ortragicevent;(2)witnessedinstancesofphysicalabuse;(3)
influencerelapse(Amesetal.,2007).
We so ught to descri be the prevalence of relapse to problem eiaxnpso;soerd( t5o) edxepados oerd dteocpormispoonseirnsgo bfowdaierso; r(4re) feuxgpeoesse.Edn tdoo mrsaeimmeendt soofldanieyrsit oerm ciwvials-

drinking,aswellastoidentifysociodemographic,military,behav- combinedwithdeploymentdatestoidentifydeploymentwithcombatexposure.
ioral, and h ealth ch ar acteristi cs associated with relapse, among Deployme ntto SouthwestA sia,Bo sn iaorKo sovobefore 2000 (yes/no) ,multiple

deployments(yes/no),andmilitaryseparationduring2001–2008wereevaluated
current and former military members with remittent problem
usingDMDCdata.
drinkinginalarge,prospectivestudyofUSmilitaryservicemem- Be haviora lfactors:ThreebehavioralfactorsweremeasuredatWave2.Smoking
berswho pa r ticipat edinTheM illenni um Co hortStu dy. statuswascat egorize dinto non-smok er,pas tsmo ker,orcu rre ntsm ok er.Non-

smokers reported never having smoked 100 cigarettes at Wave 1 and Wave 2

2. Methods surveys.Currentsmokersreportedsmoking100cigaretteseverandhadnottried

orhadbeenunsuccessfulatquittingatWave2.Pastsmokersreportedsmoking100

2.1. Studypopulationanddatasources cigaretteseverandhavingsuccessfullyquitatconsecutivewaves(1and2)orat

Wave2.DrinkingstatusatWave2wasdefinedbasedonpast-weekandpast-year

TheMillenniumCohortStudycommencedpriortoSeptember11,2001,and itemsmeasuringthequantityandfrequencyofaveragedrinkingandthefrequency

consistsoffourrecruitmentpanelsthataresurveyedapproximatelyevery3years. ofheavyepisodic(or“binge”)drinkingreportedatWave2.Abstinencewasdefined
Thepres en tstu dyutilizedda tafrom the firs trecruitm entpanel,awe ighted s ample as repor tingzero dr inksint helastw eekand ne verbi ng edrinking (≥5 and≥4

ofactivedutyandReserve/NationalGuardpersonnelservinginthemilitaryasof drinks/dayformenandwomen,respectively,onasingleoccasion)inthelastyear.

October2000.PersonneldeployedtoSouthwestAsia,Bosnia,andKosovofrom1998 Low-riskdrinkingwasdefinedasalcoholusewithinnationalrecommendedweekly
to2000, Reser vists,andw omenwe re oversampl ed.In formed con sentwa sobta ined limits(N ationalIn stitu teonA lc oholAb use andAl coholism ,2007;≤7dri nksfor
fro mall participan ts.D etailed descri ptionofthes amplinga ndmet hodo logyhas wome nand≤14 drinksf orm en)and nore port ofbingedrin king.R isk ydrink ing

beenpreviouslypublished(Ryanetal.,2007;Smithetal.,2007).Thisstudywas wasdefinedasexceedingtherecommendedweeklyordailylimits,oranybinge

reviewedandapprovedbyIRBsattheNavalHealthResearchCenterandVAPuget drinkinginthelastyear(Smithetal.,2009).Troublesleepingwasdefinedbasedon

Sound. aresponseof“moderately”or“greatly”tothequestion“Inthepastmonth,haveyou

Datasourcesincludedquestionnairesandofficialmilitaryrecords.Electronic hadtroublefallingasleeporstayingasleep?”onthePosttraumaticStressDisorder

militarypersonnelfilesprovidedbytheDefenseManpowerDataCenter(DMDC) (PTSD)Checklist-CivilianVersion(PCL-C);oraresponseof“severaldaysorlonger”

contained sociodemographic, military service, and employment characteristics. tothequestion“Overthelast4weeks,howoftenhaveyouexperiencedtrouble

Behavioralmetricsandmilitaryexposures,includingalcoholuseandcombatexpe- fallingasleeporstayingasleep?”onthePHQ.

rience,wereobtainedfromthequestionnaires. Mentalhealthconditions:Depression,anxiety,andpanicdisorderswereassessed

Inclusionandexclusioncriteria:Ofthe77,047participants(36%ofthoseinitially atWave2usingthePHQ,basedonDiagnosticandStatisticalManualofMentalDis-

contacted; Ryan et al., 2007) enrolled in the first panel, 46,437 participants orders,FourthEdition(DSM-IV)criteria(Kroenkeetal.,2001;Spitzeretal.,1999).
E.C.Williamsetal./DrugandAlcoholDependence148(2015)93–101 95

Problem drinkers at Wave 1 (N = 9951)

+Inclusion criteria: Panel 1 participants with follow-up surveys at both Wave 2

and Wave 3. Reported problem drinking at Wave 1.

Wave 2
n = 79 missing problem drinking status
n = 1989 continued problem drinking
Problem drinkers in remission at Wave 2 (N = 7883; 79%)

n =928missing study exposures

Problem drinkers in remission at Wave 2 with

complete data (N = 6955; 88%)

Wave 3
n = 46 missing problem drinking status

Relapse problem drinking No problem drinking relapse

(n = 1074; 15%) (n = 5835; 84%)
Fig.1. Flowchartforstudypopulation.

Bingeeatingwasdefinedasself-reportindicatingalossofcontrolovereatingand Threesetsofiterativelyadjustedlogisticregressionmodelswerefittoestimate

consumingunusuallylargeamountsoffood,orexcessiveexercisetoavoidgain- theoddsofrelapseassociatedwitheachexposure.Allmodelswereadjustedforprior

ingweight(Striegel-Mooreetal.,2010).PTSDsymptomsweremeasuredusingthe deployment,servicecomponent,andgendertoaccountforoversamplingofspecific

PCL-Candweredefinedbasedon(1)meetingDSM-IVcriteriaofreportingatleast militarysubpopulations(KornandGraubard,1999).Thefirstsetofmodelswas

threeavoidancesymptoms,twohyperarousalsymptoms,andoneintrusionsymp- additionallyadjustedforremainingdemographicsanddrinkingstatusatWave2due
toma t“modera te”orhighe rlev els,and(2)h avingatot alsc ore of≥50.T hePCL toknownst rongasso cia tionsbetw eenrelapsean dth esechar acteris ti cs(Da w son

hasbeenshowntocorrectlyidentifyindividualswithPTSDbasedonsymptom etal.,2007).Inordertounderstandtheextenttowhichmilitary-specificexposures

reporting(sensitivity100%,specificity92%)andthe50pointcut-off(sensitivity attenuatedobservedassociations,thesecondsetofmodelsadditionallyincludedall

60%,specificity99%)(Blanchardetal.,1996;Brewin,2005).Duetosmallnumbers, militarycharacteristics.Thefinalmodelwasconsideredtheprimaryanalyticmodel

asinglemeasureindicatinganymentalhealthconditionatWave2wascreated andincludedallexposurecharacteristics,thusobtainingestimatesforeachexposure

to represent screening positive for depression, binge eating, anxiety, panic, or characteristicadjustedforallotherexposures.Collinearitywasevaluatedwiththe

PTSD. varianceinflationfactor(VIF);noproblemswerelikely(VIF<4inallinstances).All

Physicalhealth:PhysicalhealthwasmeasuredatWave2bythephysicalcom- analyseswereperformedwithSASsoftware,version9.3(SASInstituteInc.,Cary,

ponentsummary(PCS)scorederivedfromtheMedicalOutcomesStudyShortForm NorthCarolina).

36-ItemHealthSurveyforVeterans(McHorneyetal.,1993;Wareetal.,1998).PCS

scoresrangefrom1to100,with100representingoptimalhealth,andarestan-
3. Results
dardized to the US population (mean score 50; SD = 10) (Ware et al., 1993). Because
militarypersonnelgenerallyhaveverygoodphysicalhealth,PCSscoresweredivided

intothreepercentilegroups(1–15,16–85,and86–100). Analysesassessingresponsebiasidentifiedsmallbutsignificant
L ifestr essors:Life stresso rs(0,1 ,>1)ass esse datWave2includeddivorce,major differences i n all char acteristic s, ex cept gend er, co mb at deploy-
financia lproblem s,s exualhar ass m ent, violenta ss ault,d ea thorilln essofa loved
ment,deploymenttoSouthwestAsia,BosniaorKosovobefore2000,
one, or personally experiencing a disabling illness or injury in the last 3 years, as andre portofbinge ea tingorsexu alas sault(S up plemen taryTa ble1).
wellasreportofforcedsexualrelationsorsexualassault(yes/no)(Holmesetal.,
1967 ). W eight ed distr ibution s of exp osure characteristics i n those

who relapsed to problem drinking, those who did not relapse,

2.4. Statisticalanalysis and for the total population, are presented in Table 1. Among

6909 participants with remittent problem drinking, 1074 (16%)
Inordertoassessdifferencesbylosstofollow-up,intitialanalysesdescribedand
relapsedduringthesubsequent3years.Weighteddistributionsof
comparedexposurecharacteristicsacrosstwogroups:(1)initialMillenniumCohort
all characterstics except gender, race, occupation, military sepa-
pWaartvieci3paanntds ,w(2it)ht hreemeiltigteibnlte psrtoubdlyempo dpruinlaktiinong a(it. eW.,athvoes 2e wwhitoh dreidm nitotte nretspproonbdle tmo rat ion, PCS scores , and r eport of sexua l assault we re statis tically

drinkingatWave2whorespondedtoWave(3).Subsequently,characteristicsof

theincludedsampleweredescribedandcomparedacrossproblemdrinkingrelapse

status.AllcomparisonswerecompletedwithChiSquaretestsofindependence,and
alldesc rip tiveanalyses were weightedt oacc oun tforsa mplin g strategy(Korn and 1 Supplementarymaterialcanbefoundbyaccessingtheonlineversionofthis
Gra ubard,199 9). paperathttp://dx.d oi.organd by ent eringd oi: ....
96 E.C.Williamsetal./DrugandAlcoholDependence148(2015)93–101

Table1
Chara cteristicsaofweightedbstudypopulation:overallandbyproblemdrinkingrelapsestatus.

Relapsedtoproblemdrinking*N(%) Remission**N(%) TotalN(%) p-Valuec

N 1074(16) 5835(84) 6,909

Demographics
Sex 0.10

Female 190(14) 1125(86) 1315

Male 884(16) 4710(84) 5594

Race/ethnicity 0.11

White,non-Hispanic 832(16) 4463(84) 5295

Black,non-Hispanic 71(13) 481(87) 552

Hispanic 74(20) 315(80) 389

other 97(15) 576(85) 673

Agecategory(years) <0.01

17–24 203(20) 856(80) 1059

25–34 386(16) 2102(84) 2488

35–44 357(16) 2003(84) 2360

>44 128(13) 874(87) 1002

Maritalstatus <0.01

Married 711(15) 4220(85) 4931

Nevermarried 260(20) 1103(80) 1363

Divorcedorwidowed 103(18) 512(82) 615

Education <0.01

Bachelor’sdegreeorhigher 267(13) 1854(87) 2121

Somecollegeorless 807(17) 3981(83) 4788

Militaryservice

Servicebranch <0.01

Army 577(18) 2683(82) 3260

Navy/CoastGuard 221(15) 1294(85) 1515

Marines 71(21) 294(79) 365

AirForce 205(11) 1564(89) 1769

Servicecomponent <0.01

Activeduty 527(14) 3293(86) 3820

Reserve/Guard 547(18) 2542(82) 3089

Occupation 0.19

Combatspecialist 264(16) 1386(84) 1650

Healthcare 93(13) 541(87) 634

Other 717(16) 3908(84) 4625

Paygrade <0.01

Juniorenlisted 485(19) 2219(81) 2704

Seniorenlisted 350(16) 1911(84) 2261

Officer 239(13) 1705(87) 1944

CombatdeploymentpriortoWave2 0.02

Notdeployed 756(16) 4128(84) 4884

Deployedwithoutcombatexposure 116(13) 827(87) 943

Deployedwithcombatexposure 202(19) 880(81) 1082

MultipledeploymentsbetweenWaves1–3 155(14) 1065(86) 1220 0.03

Militaryseparationoverfollow-up 0.09

No 754(15) 4367(85) 5121

PriortoWave2 193(17) 910(83) 1103

PriortoWave3 127(19) 558(81) 685

DeploymenttoSWAbefore2000 307(14) 1931(86) 2238 0.04

Behavioralfactors

Smokingstatus <0.01

Nonsmoker 415(14) 2638(86) 3053

Pastsmoker 409(16) 2160(84) 2569

Currentsmoker 250(20) 1037(80) 1287

Drinkingstatus <0.01

Abstinence 86(10) 867(90) 953

Lowrisk,noproblem 92(8) 1072(92) 1164

Riskydrinking 896(19) 3896(81) 4792

Troublesleeping 461(20) 1931(80) 2392 <0.01

Mentalhealthconditions

Depression 61(32) 152(68) 213 <0.01

Bingeeating 274(20) 1102(80) 1376 <0.01

Panic/anxietydisorder 63(26) 188(74) 251 <0.01
PTSD(DSM-IV &PCL-C ≥50) 60 (28) 153 (72) 213 <0.01

Physicalhealth

Physicalcomponentssummary 0.06

1–15Percentile 180(19) 839(81) 1019

16–85Percentile 751(15) 4280(85) 5031

86–100Percentile 143(17) 716(83) 859

Lifestressors

Lifestressorevents 0.01

None 516(15) 2930(85) 3446

1event 385(16) 2174(84) 2559
E.C.Williamsetal./DrugandAlcoholDependence148(2015)93–101 97

Table1(Continued)

Relapsedtoproblemdrinking*N(%) Remission**N(%) TotalN(%) p-Valuec

Morethan1event 173(21) 731(79) 904

Sexualassault 13(21) 39(79) 52 0.42

Abbreviations:DSM-IV,DiagnosticandStatisticalManualofMentalDisorders,FourthEdition;PCL-C,PTSDChecklist-CivilianVersion;PCS,physicalcomponentsummary;

PTSD,posttraumaticstressdisorder.

a Demographicsandmilitaryservicevariablesweretakenatbaselineunlessotherwisestated;maritalstatus,behavioralfactors,mentalhealthconditions,physicalhealth,

andlifestressorsweretakenatWave2survey.
b Wei ghtedto accou ntfor sam pling s trategy.PersonneldeployedtoSouthwestAsia,Bosnia,andKosovofrom1998to2000,Reservists,andwomenwereoversampled.
c Chi-square te stcomp arin gfrequen ciesacro ssrelapse status.
* Relapsewa sde finedasrep ortof≥1pas t-year alcohol -relatedproblemonthevalidatedPatientHealthQuestionnaireatthesecondfollow-up(2007–2008).
** Remissi onw asdefin ed asnon -en do rsemento fanypast-yeara lcohol-re lat edp roblemsa tthefir stand secondfollow- up .

significantly different between remittent problem drinkers who 4. Discussion

relapsed and those who did not (Table 1). Regarding military

characteristics, relapse was most common among members of Thisisthefirststudytodescribetheprevalenceandcorrelatesof

theArmyandMarines,Reservists/NationalGuard,juniorenlisted relapsetoproblemdrinkingovertimeamongaprospectivecohort

members, those deployed with combat exposure, and those ofmilitarypersonnel.Thisstudyindicatesthatonesixthofmilitary

deployed to Southwest Asia, Kosovo, or Bosnia before 2000 personnelwithremittentproblemdrinkingrelapsedwithin3years

(Table1). andidentifiesparticularmilitarysubpopulationsathigherriskof

Associationsbetweenexposuresandrelapseresultingfromeach relapse.Specifically,thoseservingintheReserves/NationalGuard,

iterativesetofmodelsarepresentedinTable2,columns2–4,cor- thosewhoseparatedfromthemilitary,andthosewhodeployed

respondingtoadjustmentforsamplingcharacteristics,additional withcombatexposurehadhigherriskofrelapse,asdidthosewith

demographicsandWave2drinkingstatus(column2),addingmil- otherriskyhealthbehaviorsandmentalhealthconditions.

itary characteristics (column 3); and mutual adjustment for all Theprevalenceofrelapseidentifiedinthepresentstudy–16%

exposures (column 4). Relative to their respective referent cate- –islowrelativetopreviousestimatesinthegeneralpopulation

gories,thefirstsetofmodelsidentifiedbeingnevermarried,having (26%;Dawsonetal.,2007)andsamplespreviouslytreatedforalco-

some college or less, being in the Reserve/National Guard, sepa- holusedisorders(McKay,1999;McKayetal.,2006;MoosandMoos,

rating from the military prior to Waves 2 or 3, being deployed 2006;WalitzerandDearing,2006;range,40–80%).However,prob-

with combat exposure, being a past or current smoker, report- lemdrinkingmaybeparticularlycostlyamongmilitarypersonnel

ingriskydrinkingandtroublesleeping,screeningpositiveforany via decreased performance (Frone, 2006; Harwood et al., 2009;

mentalhealthcondition,beinginthelowestcategoryofphysical Lamond and Dawson, 1999; O’Brien and Lyons, 2000), adverse

health, and report >1 life stressor or sexual assault to be associ- physicalhealthoutcomes(Harrisetal.,2009;Williamsetal.,2012),

atedwithsignificantlyhigheroddsofrelapseatWave3(Table2, comorbidmentalhealthdisorders(Millikenetal.,2007),andrisk

column2).ServingintheAirForce,havingmultipledeployments, ofsuicide(LeardMannetal.,2013).Remittingandrelapsingprob-

andbeingdeployedwithoutcombatexposureortoSoutwestAsia, lemdrinkingmaybeparticularlyriskyamongmilitarypersonnel

Bosnia, or Kosovo before 2000 were associated with lower odds because it may reflect disordered drinking, which is often diffi-

of relapse relative to the respective referent categories (Table 2, cult to control and change once developed (National Center on

column 2). After adjustment for military service characteristics, AddictionandSubstanceAbuse,2012).

education,deploymentwithoutcombatexposureortoSouthwest This study’s findings that risky health behaviors, particularly

Asia, Bosnia, or Kosovo before 2000, and report of past smok- risky drinking and smoking, and screening positive for mental

ingorsexualassaultwerenolongersignificantlyassociatedwith healthconditionsarecorrelatesofrelapseareconsistentwithstud-

relapse,andthelowerriskassociatedwithbeingintheAirForce ies in the general population and treatment samples (Dawson

wasslightlyattenuated(Table2,column3).Afteradjustmentfor et al., 2007; McKay, 1999; McKay et al., 2006; Moos and Moos,

all other exposures, associations between relapse and both life 2006; Walitzer and Dearing, 2006). However, among military

stressorsandphysicalhealthwerenolongersignificant,butmale personnel, several service characteristics were also predictive of

genderwasassociatedwithhigheroddsofrelapse(Table2,column relapse. The strongest predictor of relapse was membership in
3). theRese rves /NationalG uard,wit ha nestima ted∼ 67%higherr isk

Afterfulladjustment,risky(relativetolowrisk)drinkingwas ofrelapsecomparedwithactive-dutymembers.Thismayreflect

thestrongestpredictorofrelapsetoproblemdrinking(Table2,col- lower risk adversion among Reserve/Guard personnel who gen-

umn4).Malegender,current(relativetonever)smoking,report erally have other non-military occupations. Alternatively, due to

oftroublesleeping,andscreeningpositiveforanymentalhealth recentconflictsinIraqandAfghanistan,manyReserve/Guardper-

conditionwerealsoassociatedwithhigherriskofrelapse.Addi- sonnel may have returned to alcohol as a coping mechanism as

tionally,severalmilitaryservicecharacteristicsweresignificantly aresultofbeinglesspreparedfordeploymentthantheiractive-

associatedwithhigherriskofrelapse(Table2,column4).These duty counterparts (Jacobson et al., 2008; Milliken et al., 2007).

includedservicecomponent,withReservistsandNationalGuard Otherfactors,suchaslackofunitsupportduringdeploymentand

members having higher odds of relapsing compared with their lackofsupportfromfellowservicemembersafterreturninghome

active-dutycounterparts,separationfromthemilitaryatanytime fromdeployment,couldalsohavecontributedtotheincreasedrisk

duringfollow-up,anddeploymentwithcombatexposurerelative observedamongReserve/Guardpersonnel.

tonodeployment.Pointestimatesofhigherriskassociatedwith Militarypersonneldeployedwithcombatexposurewereesti-

thesecharacteristicsrangedfrom30%(deploymentwithcombat matedtobe30%morelikelytorelapsetoproblemdrinkingthan

exposure) to 67% (Reserve/National Guard member) (confidence thosenotdeployed.Thesefindingsaddtoanincreasingliterature

intervalspresentedinTable2,column4).However,severalmil- highlightingcombatexposureasariskfactorforproblemdrinking

itarycharacteristicswereassociatedwithalowerriskofrelapse, (Brayetal.,2013;Gallawayetal.,2013;Hogeetal.,2004;Jacobson

includingmultipledeployments(versusoneornone)andservice etal.,2008;Wilketal.,2010)andothermentalhealthconditions

intheAirForcerelativetotheArmy(Table2,column4). (Mitchelletal.,2012).Interestingly,however,participantsinthis
98 E.C.Williamsetal./DrugandAlcoholDependence148(2015)93–101

Table2
Assoc iationsbetweenproblemdrinkingrelapse*anddemographic,military,behavioral,andhealthfactors.

Adjustedfordemographics,Wave2drinking Adjustedfordemographics, Mutuallyadjusted

behavior,priordeployment,andservice Wave2drinkingbehavior, forallcovariates

component andmilitarycharacteristics

OR(95%CL) OR(95%CL) OR(95%CL)

Demographics
Sex
Female 1.00 1.00 1.00

Male 1.15(0.96–1.38) 1.10(0.91–1.33) 1.22(1.00–1.48)

Race/ethnicity
White,non-Hispanic 1.00 1.00 1.00

Black,non-Hispanic 0.88(0.67–1.14) 0.87(0.66–1.13) 0.87(0.67–1.15)

Hispanic 1.19(0.91–1.56) 1.21(0.92–1.58) 1.19(0.90–1.56)

Other 1.20(0.94–1.53) 1.17(0.91–1.52) 1.21(0.93–1.57)

Agecategory(years)

17–24 1.15(0.94–1.41) 1.08(0.87–1.34) 1.08(0.87–1.34)

25–34 1.00 1.00 1.00
35–44 1.01(0.86–1.19) 0.98(0.81–1.17) 0.95(0.79–1.15)

>44 0.82(0.65–1.03) 0.82(0.64–1.05) 0.80(0.62–1.02)

Maritalstatus

Married 1.00 1.00 1.00

Nevermarried 1.25(1.05–1.49) 1.20(1.01–1.44) 1.23(1.03–1.47)

Divorcedorwidowed 1.15(0.91–1.45) 1.12(0.87–1.42) 1.09(0.86–1.39)

Education
Bachelor’sdegreeorhigher 1.00 1.00 1.00

Somecollegeorless 1.30(1.10–1.53) 1.10(0.87–1.39) 1.07(0.85–1.35)

Militaryservice

Servicebranch

Army 1.00 1.00 1.00

Navy/CoastGuard 0.91(0.75–1.09) 0.97(0.80–1.17) 1.01(0.84–1.22)

Marines 1.18(0.89–1.57) 1.18(0.86–1.58) 1.20(0.90–1.61)

AirForce 0.66(0.55–0.79) 0.74(0.61–0.89) 0.78(0.64–0.94)

Servicecomponent

Activeduty 1.00 1.00 1.00

Reserve/Guard 1.40(1.21–1.62) 1.60(1.35–1.88) 1.67(1.41–1.97)

Occupation
Other 1.00 1.00 1.00

Combatspecialist 1.09(0.92–1.28) 1.06(0.90–1.26) 1.07(0.90–1.27)

Healthcare 1.01(0.79–1.29) 1.01(0.79–1.29) 1.01(0.79–1.29)

Paygrade
Juniorenlisted 1.00 1.00 1.00

Seniorenlisted 0.99(0.82–1.20) 1.01(0.83–1.23) 1.07(0.88–1.30)

Officer 0.81(0.62–1.07) 0.83(0.63–1.09) 0.92(0.69–1.22)

Militaryseparation

No 1.00 1.00 1.00

PriortoWave2 1.48(1.23–1.78) 1.38(1.14–1.68) 1.31(1.08–1.59)

PriortoWave3 1.62(1.30–2.03) 1.52(1.22–1.90) 1.47(1.17–1.84)

Multipledeployments

Yes 0.73(0.60–0.88) 0.74(0.59–0.93) 0.76(0.61–0.95)

CombatdeploymentatWave2

Notdeployed 1.00 1.00 1.00

Deployedwithoutcombatexposure 0.74(0.60–0.92) 0.95(0.75–1.20) 0.96(0.76–1.22)

Deployedwithcombatexposure 1.20(1.01–1.44) 1.39(1.14–1.71) 1.30(1.06–1.60)

DeploymenttoSWAbefore2000 0.85(0.72–0.99) 0.95(0.81–1.12) 0.95(0.80–1.12)

Behavioralfactors

Smokingstatus

Nonsmoker 1.00 1.00 1.00

Pastsmoker 1.16(1.00–1.35) 1.12(0.96–1.31) 1.12(0.96–1.30)

Currentsmoker 1.33(1.11–1.59) 1.27(1.05–1.52) 1.26(1.05–1.51)

Drinkingstatus

Lowrisk,noproblem 1.00 1.00 1.00

Abstinence 1.08(0.79–1.47) 1.03(0.76–1.41) 1.01(0.74–1.38)

Riskydrinking 2.49(1.98–3.13) 2.51(2.00–3.16) 2.47(1.96–3.12)

Troublesleeping 1.54(1.34–1.76) 1.46(1.27–1.67) 1.32(1.14–1.53)

Mentalhealthconditions

Anyreportofdepression,bingeeating, 1.61(1.39–1.86) 1.53(1.32–1.77) 1.40(1.20–1.63)

Panic/anxiety,orPTSD

Physicalhealth

Physicalcomponentssummary

1–15Percentile 1.32(1.10–1.59) 1.23(1.02–1.48) 1.05(0.87–1.28)

16–85Percentile 1.00 1.00 1.00

86–100Percentile 1.10(0.90–1.34) 1.12(0.92–1.37) 1.09(0.89–1.33)

Lifestressors

Lifestressorevents

None 1.00 1.00 1.00

1event 0.99(0.86–1.15) 0.97(0.84–1.12) 0.94(0.81–1.09)

Morethan1event 1.35(1.12–1.64) 1.27(1.04–1.55) 1.09(0.89–1.35)

Sexualassault 2.01(1.04–3.89) 1.85(0.95–3.59) 1.55(0.79–3.06)

* Problemdrinkingrelapsewasdefinedasreportof≥1past-yearalcohol-relatedproblemonthevalidatedPatientHealthQuestionnaireatthesecondfollow-up

(2007–2008).
E.C.Williamsetal./DrugandAlcoholDependence148(2015)93–101 99

study who reported multiple deployments were at lower risk of alcoholusedisorders(Buchsbaumetal.,1991;Ewing,1984;Fiellin

relapse compared to those without. It could be that participants et al., 2000; Spitzer et al., 1999). In addition, past-year problem

whoarequalifiedformultipledeploymentsareaselectpopulation drinking was assessed in approximately three year intervals.

ofparticularlyhealthyandresilientpersonnel(i.e.,thosewhoare Therefore, it is possible that participants who cycled through

high-functioning,abletopassdeploymentscreenings,anddonot relapse and remittance in the timeframe between responses

exhibitalcoholproblems).Thiswouldbeconsistentwithprevious were misclassified. However, the effect of the misclassification

studiesdescribinga“healthywarrioreffect”(Haley,1998;Larson biasislikelynon-differential,givennoindicationthatmilitaryor

et al., 2008). The lower odds of relapse observed in members of non-militarycharacteristicswererelatedtothetimingofsurveys.

theAirForcecomparedwithArmypersonnelareconsistentwith Lackoftreatmentdataforalcoholusedisordersisalsoalimitation,

previousstudiesdemonstratinglowerriskofmentalhealthout- sincethosewhoseektreatmentmaydifferinimportantwaysfrom

comesamongAirForcecomparedwithArmymembers(Milliken thosewhodonot,andresidualconfoundingmayexist.Further,it

etal.,2007;Riddleetal.,2007).Thesefindingsmaybeattributable ispossiblethatcorrelatesofrelapsemaybemodifiedbytreatment

tosocialandoccupationalfeaturesofthesebranches.Expectations status. However, the vast majority of people with alcohol use

ofAirForcepersonnelregardingproblemdrinkingmaybepartic- disorders,includingmilitarypersonnelforwhombarrierstocare

ularlyrigidduetotherigoroftheirjobsandtherequirementtobe such as stigma may be increased (Institute of Medicine, 2012;

readyforflightstatus. Milliken, 2011), never seek treatment. Thus, this is unlikely to

Theoverallrateofrelapseidentifiedinthisstudysuggeststhat, substantially impact findings. There are additionally limitations

asrecommendedbytheDoDandDepartmentofVeteransAffairs relatedtoseveralexposuremeasures.Wewerenotabletoidentify

(VA; VA Office of Quality and Performance, 2009), routine inter- mildtraumaticbraininjury,whichisassociatedwithhigherriskof

ventionswithandmonitoringofmilitarypersonnelwithproblem problemdrinking(Milleretal.,2013).Additionally,becausecom-

drinking are appropriate. Abstinence is generally recommended batexposurewasdefinedasendorsementofwitnessingtraumatic

for those with remittent problem drinking, because, consistent experiencesduringa3yearperiodandthencategorizedascombat

withfindingsfromthisstudy,continueduseincreasesrelapserisk exposure if it overlapped with deployment reported at Wave 2,

(Dawsonetal.,2007).Whileroutineinterventionandongoingmon- combat exposure was only assessed among those people who

itoringforthosewithriskyandproblemdrinkingarehistorically alsodeployedduringthesame3yearperiodandmayhavebeen

difficulttoimplementincare,theVAhashadsomeimplementation miscategorized. Also, while it has been used in previous studies

success(Laphametal.,2012;MoyerandFinney,2010;Williams (Boykoetal.,2013;Gehrmanetal.,2013),themeasureoftrouble

et al., 2011). However, availability of these services is variable sleepingusedhasnotbeenvalidated.Finally,similartootherlarge

across DoD settings, and, as highlighted in a 2012 IOM report longitudinalsurveys,generalizabilitymaybelimitedbyresponse

(Institute of Medicine, 2012), there is substantial fragmentation bias. A previous study in a similar subsample of Millennium

of care. In addition to the need for streamlining care, the report Cohortparticipantsassessednon-response(Jacobsonetal.,2008)

discussedtheneedforinterventionsthattemperstigmaformili- and identified older age, greater education, and being married

tarypersonnelwithremittentproblemdrinking(Amesetal.,2014; as predictors of response. Initial analyses in the present study

InstituteofMedicine,2012;Milliken,2011). demonstrated small but significant differences in many charac-

While efforts to prevent relapse are needed in the overall teriticsbyresponse.Therewasaslightlyhigherproportion(73%vs

military population with remittent problem drinking, this study 69%)ofpotentiallyeligibleparticipantsreportingriskydrinkingat

identified military and non-military service characteristics that Wave2whodidnotrespondtotheWave3survey,comparedwith

couldhelptargetpopulationsinmostneedofinterventionaimedat thoseincludedinthepresentstudy.Giventhestrongassociation

interruptingthepathwaytorelapse.Thisstudybuildsonaprevious betweenriskydrinkingatWave2andrelapse,wemaynothave

MillenniumCohortinvestigationthatassessedpredictorsofiniti- captured all cases who relapsed to problem drinking. While the

atingproblemdrinkingamongservicemembers(Jacobsonetal., overallinfluenceofresponsebiasonresultsofthecurrentstudyis

2008).Thesamepredictorsofinitiatingproblemdrinkingalsocon- unknown,thecharacteristicsofWave3non-respondersweresim-

tributetohigheroddsofproblemdrinkingrelapseinthissample, ilartoapreviousreportofnon-respondersinthefirstenrollment

thusstrengtheningtheargumentforinterventioninthesemilitary paneloftheMillenniumCohort,thefindingsofwhichsuggested

subpopulations, including members of the Reserve/Guard, those thatanalysesintherecruitedandretainedcohortareunlikelyto

who deploy and have combat exposure, and those with comor- besubstantiallybiasedbynon-response(Littmanetal.,2010).

bid mental health conditions. Because the prevalence of mental Thisstudydescribedrelapseamongmilitarypersonnelinremit-

healthconditions(Brayetal.,2010;Grossbardetal.,2013;Hawkins tanceofproblemdrinkingandprospectivelyevaluatescorrelates

etal.,2010;Millikenetal.,2007;Mitchelletal.,2012)issubstantial of relapse. Findings suggest that one sixth of military personnel

amongrecentlyreturnedsoldiersandveterans,interventionsmay withremittentproblemdrinkingexperiencerelapseapproximately

beparticularlyimportantinmentalhealthcaresettings. 3yearslaterandsupporttheimplementationofconductingrou-

This study has a number of limitations. First, full baseline tine monitoring of identified problem drinking among military

alcohol assessments were only completed among participants personnel and veterans. This practice is consistent with cur-

who reported drinking at least 12 drinks in the year prior to rentclinicalrecommendations.Militarypersonnelwithremittent

survey.Duetothis,andbecauseapproximatelyhalfofpeoplewho problem drinking who do not abstain from alcohol use during

meetCAGEcriteriaforproblemdrinkingarenon-drinkers(Samet remittance,ReservistsorNationalGuardmembers,thosewhoare

andO’Connor,1998),wewereunabletousetheCAGEtoidentify deployed with combat exposure, and those who have separated

remittent problem drinkers at baseline with precision. Thus, we fromthemilitarymaybenefitfromtargetedpreventionandtreat-

wereunabletomaximizetheutilityoftheselongitudinaldataby mentstrategies.

assessing relapse at Wave 2. Second, no diagnostic assessment

for alcohol use disorders was completed, which would have Authordisclosures
fac ilitateda mor efocuseds tudyo ftheprevale nceand correla tesof

relapsetoalcoholusedisorders.Thus,thepresentstudyassessed 4.1. Roleoffundingsource

problem drinking because it is associated with a high likelihood

of alcohol use disorders and the available validated measures ThisstudywasfundedbyaMeritReviewAwardDepartment

assess domains that overlap with those of diagnostic criteria for of Veterans Affairs Clinical Science Research and Development
100 E.C.Williamsetal./DrugandAlcoholDependence148(2015)93–101

Program. The Millennium Cohort Study is funded through the Walstrom; Martin White, M.P.H.; and James Whitmer; from the

MilitaryOperationalMedicineResearchProgramoftheUSArmy DeploymentHealthResearchDepartment,NavalHealthResearch

MedicalResearchandMaterielCommand(FortDetrick,Maryland). Center,SanDiego,California.

Dr. Williams is supported by a Career Development Award from We also thank Michael V. Nguyen from VA Puget Sound in

VAHealthServicesResearch&Development(CDA12-276)andis Seattle; Scott L. Seggerman, from the Management Information

an investigator with the Implementation Research Institute (IRI) Division, Defense Manpower Data Center, Seaside, California;

attheGeorgeWarrenBrownSchoolofSocialWorkatWashington MichelleLeWark,fromtheNavalHealthResearchCenter;andall

University in St. Louis. IRI is supported through an award from theprofessionalsfromtheUSArmyMedicalResearchandMateriel

the National Institute of Mental Health (R25 MH080916-01A2) Command,especiallythosefromtheMilitaryOperationalMedicine

andtheDepartmentofVeteransAffairs,HealthServicesResearch ResearchProgram,FortDetrick,Maryland.

&DevelopmentService,QualityEnhancementResearchInitiative

(QUERI).Dr.LittmanissupportedbyaCareerDevelopmentAward AppendixA. Supplementarydata
fromVA Reh abilitati on Research &D e velopm ent(CDA689 2).The

funding sources had no involvement in the study design, data Supplementarydataassociatedwiththisarticlecanbefound,
collectio n,analys is,in terp retationofda ta, writ ingof therepo rt,or in the online vers ion, at http://d x.doi. org/1 0.1016 /j.dr ug alcdep.
decisionto submitt hearticleforp ub licati on. 20 14.1 2.031.

This work represents report 13-47, supported by the Depart-

mentofDefense,underWorkUnitNo.60002.Theviewsexpressed
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