WORKING PAPER
Prevalence and Patterns of Health Risk Behaviors
of Palestinian Youth
Findings from a Representative Survey
Peter Glick, Umaiyeh Kammash, Mohammed Shaheen, Ryan Andrew Brown, Prodyumna Goutam,
Rita Karam, Sebastian Linnemayr, and Salwa Massad
RAND Labor & Population
WR-1119-1
July 2016
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PREVALENCE AND PATTERNS OF HEALTH
RISK BEHAVIORS OF PALESTINIAN YOUTH:
FINDINGS FROM A REPRESENTATIVE
SURVEY
PeterGlick1,UmaiyehKammash2,3,MohammedShaheen4,RyanBrown1,ProdyumnaGoutam1,
RitaKaram1,SebastianLinnemayr1,SalwaMassad3,5
1
RANDCorporation,Santa.Monica,California,USA.
JuzoorforHealthandSocialDevelopment,Ramallah,Palestine.
3
United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA),
Jerusalem,Palestine.
4
AlQudsUniversity,AbuͲDis,Palestine
5
PalestinianNationalInstituteofPublicHealth,Ramallah,Palestine.
2
1
SUMMARY
Verylittleisknownaboutyouthhealthriskbehaviorssuchasdrugandalcoholuseandsexual
activityintheMiddleEastandNorthAfrica,andintheOccupiedPalestinianTerritories(OPT)
specifically. This lack of information, together with a lack of open discussion of these topics,
leavespublichealthauthoritiesintheregionunpreparedtodealwithemergingpublichealth
threatsatatimewhenmajorsocialandeconomicchangesareincreasingtherisksthatyoung
menandwomenface.ThePalestinianYouthHealthRiskStudywasdesignedtoaddressthese
gapsinknowledge.Itisthefirstintheregiontocollectlargescale,representativesurveydata
fromyouthonkeyriskbehaviors(smoking,alcoholanddruguse,andsexualactivityaswellas
interpersonal violence). The study investigates the prevalence and patterns of these risk
behaviors as well as of mental health, perceptions of the risks of such behaviors, and the
factorsincreasingvulnerabilitytoaswellasprotectionfromengagementinthem.Thestudy,
conducted by researchers at the RAND Corporation, based in Santa Monica, CA, USA, and
Juzoor Foundation, based in Ramallah, West Bank, Occupied Palestinian Territories,
implementedarepresentativesurveyofabout2,500maleandfemaleyouthage15Ͳ24livingin
theWestBankandEastJerusalem.Themainconclusionswithrespecttoprevalenceare:
Withtheexceptionsoftobaccouseandinterpersonalviolence(fighting),youthengagement
inhealthriskactivitiesoverallisrelativelylow,butsubstantiallyhigherformaleyouththan
female youth. Consistent with earlier studies, tobacco use among Palestinian youth is very
high.Evenamongyoungeryouthinthesample(age15Ͳ19)45%ofmalesand22%offemales
report current smoking; for older youth (20Ͳ24) the shares are 72% and 31% for males and
females, respectively. As these shares indicate, prevalence is substantially higher for male
youththoughbynomeanstrivialforfemales.
With regard to alcohol use, slightly less than one quarter of older (19Ͳ24) male youth report
havingtriedalcohol.Ratesamongfemaleyouthinthisagegroupareabouthalfthatformale
youth(12%).Experienceofalcoholamongyoungeryouthage15Ͳ19islower(8%ofmalesand
3.6%offemales).
Relatively few youth report having tried any of a range of drugs asked about in the survey,
including marijuana or hashish, pills, inhalants, and cocaine or heroin. 10% of males 20Ͳ24
reporthavingtriedanykindofdrugscomparedwith4%foryoungermaleyouth.Only4%of
older female youth and 1.6% of younger female youth report ever using drugs. Less than a
thirdofthoseyouthwhosaytheyevertrieddrugssaytheycurrentlytakedrugs.
2
QuestionsonsexualactivitywereaskedonlyofnonͲminors(over17years)duetothecultural
sensitivityofthesubject.25%ofolder(19Ͳ24)unmarriedmaleyouthand22%ofyounger(17Ͳ
18) male youth report having had any sexual experience. Rates for females are generally
similar. Experience specifically of sexual intercourse among unmarried youth is substantially
lowerthanforexperienceofanysexualactivity:9.5%ofolderunmarriedmaleyouthand5.6%
ofyoungerunmarriedmaleyouthreporthavinghadsexualintercourse,comparedwith7%for
older females and 4% for younger females. Phone sex (sexting) and internet sex involving
anotherpersonarerelativelycommonamongunmarriedyouthofbothgenders:amongmale
youth, 38% of older and 33% of younger (age 18 and 19) report having ever engaged in this
activity;30%ofolderfemaleyouthand23%ofthose18and19reporthavingdoneso.
Finally, in line with what was suggested by earlier studies of the OPT, engaging in physical
fighting is relatively common, especially among younger male youth 15Ͳ19. 56% of males in
thisagegroupand29.3%offemalesreportedengaginginoneormorefightsintheyearprior
tothesurvey.
Forallyouth,thefindingspointtotobaccouse(especially)andengagementininterpersonal
violentbehavioraskeybehaviorsdeservingoffocusedattention.Smokinghasobviousdirect
healthimplications,especiallyinthelongterm.Levelsofinterpersonalviolencearequitehigh
thoughbroadlyinlinewithfindingsfromseveralothermiddleincomecountries.Fightingmay
have direct health implications through injury but also may lead to significant negative
emotional outcomes among young people. The causes and implications of violence among
Palestinian youth (including the role of conflict and economic stress) should be carefully
studiedtoformulateappropriateinterventions.Otherriskbehaviorssuchasalcoholanddrug
useandsexualactivityappearlowrelativetocountriesoutsidetheregion,butremainasource
ofconcern,especiallyforsomesubgroupsandlocations.
There are important patterns in behaviors by location that should inform outreach efforts.
For almost all health risk behaviors, there is a pattern of substantially higher prevalence in
urbanareasandrefugeecampscomparedwithruralareas.Forexample,inbothurbanareas
andcamps,26%ofmaleyouthage19Ͳ24saytheyhaveusedalcohol,doubletheshareinrural
areas (13.2%). For the same group of older male youth, 13% of urban residents and 16% of
camp residents say they have tried drugs, compared with 3% in rural areas. Similar patterns
across areas are found for females and for younger youth age 15Ͳ19. These differences may
reflect easier access to alcohol and drugs in urban areas andcamps (many of which are also
urban), different cultural attitudes in urban vs. rural areas, or a greater ability to engage in
these behaviors discretely in urban settings. SelfͲreported sexual activity exhibits a similar
patternbyarea.
3
Thesizeofsampledidnotpermitsystematiccomparisonsacrossgovernorates.However,the
data do show significantly elevated levels of risk behaviors in Jerusalem. Jerusalem
Governorate,whichismostlyurban,isdividedinto‘J1’and‘J2’areas,correspondingtoEastern
areasofthecitythatwereannexedbyIsraelandinsidetheSeparationWallontheonehand,
andotherareas,ontheother.Amongmaleyouth15Ͳ24inJerusalemGovernorate(J1plusJ2),
rates of current alcohol use, having tried drugs, and sexual activity outside of marriage (age
over 17) are 13.8%, 15.5%, and 27.5%, respectively. For urban areas in Jerusalem alone they
are16.1%,18.4%,and31.0%.Theseratesaresubstantiallyhigherthanforotherurbanareas
combined(5.1%,5.5%,and5.5%forcurrentalcoholuse,trieddrugs,andsexualactivity;p=0.00
forJerusalemvs.otherurbanforeachbehavior).Asimilarpatternprevailsforfemaleyouthin
Jerusalemvisavistheothergovernorates.
While refusals to participate in the survey and nonͲresponses to individual questions were
low, the accuracy of selfͲreports of behavior remains a concern. Great effort was made to
develop protocols to ensure that youth were comfortable discussing sensitive topics. Youth
werealsoaskedlessdirectlypersonalquestionsaboutengagementindifferentriskbehaviors
bytheirgeneralpeersinthecommunity(individualsofthesameageandgender)aswellasby
their close friends. Responses to questions about close friends (asked before any questions
about therespondent’sown behavior) suggest moderately higher levels of engagement than
the youths’ responses about their own behavior would suggest. On the other hand, the
perceivedengagementofpeersingeneralinthecommunityissubstantiallyhigherthanthat
reportedbytherespondentsaboutthemselvesonaverage.Whileitisoftenarguedthatyouth
tendtosignificantlyoverestimatepeernormsofengagementinriskbehaviors,thisdiscrepancy
mayalsopointtounderreportingofownriskbehaviors.Moreresearchneedstobedonein
theregion,usingalternativeinterviewapproaches,toexplorepotentialbiasesinresponsesto
questionsaboutsensitiveorstigmatizedbehaviors.
Withrespecttoanumberofpatterns,thestudyfindingsdisplayastrikingsimilaritytoyouth
or adolescent surveys carried out in other regions. The disparity noted above between selfͲ
reportedlevelsofyouths’ownparticipationinriskbehaviorsandtheirperceptionsofthelevel
ofengagementofotheryouthisobservedinmanystudiesofyouthintheU.S.andelsewhere;
as noted, it is typically thought to reflect a tendency of youth to overestimate the extent to
which others participate in such behaviors. Wealso find, similar to studies elsewhere, that a
youth’sselfͲreportedengagementinriskbehaviorsisstronglycorrelatedwithhisorperception
of the level of engagement of peers in their community. This suggests that youth are
influencedbyperceivednormsofbehavior,thoughthiscannotbeestablishedconclusivelywith
thedata.Finally,inkeepingwithstudiesofyouthoradolescentsinotherregions,youthwho
engage in one risk behavior (e.g., smoking) are more likely to engage in other risk behaviors
(e.g.,alcohol).
4
Interventions for Palestinian youth should be informed by these patterns. As indicated, the
findingsprovideguidanceastowhereandforwhompreventioneducationprogramsaremost
needed. Not surprisingly, young men, especially older male youth, are the most likely to
engage in health risk activities. Programs should therefore make particular efforts to engage
maleyouth,butalsoshouldnotignorefemaleyouth,whowhileapparentlylesspronetodoso,
also engage in these behaviors. With regard to location, urban areas and camps have the
highest prevalence and should also be targeted. In addition, the fact that behaviors are
‘clustered’—with youth who participating in risk behavior tending to participate in multiple
such behaviors—means that prevention education programs need to deal with a range of
connectedriskbehaviorsforwhichcertainyouthmaybeatrisk,notjustsinglebehaviorssuch
as drug use. Finally, the correlation of an individual’s behavior with perceived level of local
peers’ behaviors suggests that influencing what youth think about peers may reduce their
likelihood of engaging in risk behaviors, though additional work is needed to better assess
whetherthisrelationshipiscausalassuchinterventionswouldassume.
TheexperienceofthePalestinianYouthHealthRiskstudyshowsthatitispossibletocarry
out populationͲbased surveys of youth on highly sensitive behaviors in conservative social
contextsoftheMiddleEast.Giventhelackofinformationonthesebehaviorselsewhereinthe
region,itwouldbehighlybeneficialforpublichealthauthoritiesandresearcherstocarryout
similar surveys across the region, both to understand current prevalence and to be able to
monitorchangesovertime.
Futureworkisplannedwiththesurveydatatoexaminethecorrelatesanddeterminantsof
thesebehaviors,includingfamilysituation,exposuretoviolence,mentalhealth,expectations
forthefutureandassessmentofrisksofbehaviors,andpersonalitytraitssuchasimpulsiveness
and fatalism. These findings will provide more refined guidance to the development of
preventionprogramsforPalestinianyouth.
5
CONTENTS
SUMMARY............................................................................................................................... ..............2
INTRODUCTION............................................................................................................................... ......7
METHODS............................................................................................................................... .............10
Studypopulation,sampling,andsurveydevelopment...................................................................10
Dataanalysis............................................................................................................................... .....12
RESULTS............................................................................................................................... ................13
Samplecompositionandcharacteristics.........................................................................................13
Healthriskbehaviors....................................................................................................................... 14
Furtherpatternsbyarea.................................................................................................................18
Peers’andfriends’behavior............................................................................................................19
Covarianceofindividualriskbehaviors...........................................................................................21
DISCUSSION............................................................................................................................... ..........22
Levelsandvariationinriskbehaviors.............................................................................................22
RiskBehaviorslevelsinInternationalPerspective......................................................................22
Patternsacrosssubgroups..........................................................................................................24
PerceptionsofpeerbehaviorandtheaccuracyofselfͲreportedbehavior....................................25
Relationofownandperceivedbehaviorofpeers..........................................................................27
Covarianceamongmultipleriskbehaviors.....................................................................................27
Implicationsofthefindings.............................................................................................................28
REFERENCES............................................................................................................................... .........30
TABLES............................................................................................................................... ..................35
6
INTRODUCTION
Health risk behaviors among adolescents and youth, such as smoking, drug and alcohol use,
and sexual activity, are a global concern. Smoking, drug and alcohol use during adolescence
havelongbeenrecognizedashavingdirecthealthimplicationsandmayincreasetherisksof
developingchronicdependenceandillnessinadulthood(VinerandBarker2005;WHO1993).
Research in the U.S. and other contexts has also shown that young people’s likelihood to
engageinsuchbehaviorsispositivelyrelatedtotheirbeliefsregardingpeers’engagementin
them (Rimal and Real 2005; SimonsͲMorton and Farhat 2010; Perkins and Wechsler 1996).
Further, youth who engage in one risk behavior tends to engage in others, that is, the
behaviorsareclustered,withimplicationsforthedesignofpreventionprograms.
Thereislittlesystematicinformationaboutthelevelsorpatternsofmosthealthriskbehaviors
amongyouthintheMiddleEastandNorthAfricaincludingsexualactivityanddrugandalcohol
use. This lack of information, together with a lack of open discussion of these topics, leaves
publichealthauthoritiesintheregionunpreparedtodealwithemergingpublichealththreats
atatimewhenmajorsocialandeconomicchangesareincreasingtherisksthatyoungmenand
women face. For example, rates of preͲmarital sexual activity are apparently rising as young
menandwomenstayinschoollongerandmarryatolderages(Shepardetal2005).Illicitdrug
useamongyouth,includinginjectingdruguse,hasemergedasaseriouspublichealthissuein
several countries in the region (Shepard et al 2005; RoudiͲFahimi 2007). Tobacco use among
youngpeopleintheregion,aboutwhichmoreisknown,isveryhighinanumberofcountries
(UsmanovaandMokdad2013).
There is therefore a strong need, recognized by international agencies (UNAIDS 2008, World
Bank2005)andagrowingnumberofgovernmentsoftheregion,foranunderstandingofthe
patternsandcausesofyouthriskbehaviors,includingthoseassociatedwithincreasedHIVrisk.
Such information will both reveal the epidemiology of these behaviors and provide
policymakers with the ability to target appropriate prevention programs to those at highest
risk.
YouthintheOccupiedPalestinianTerritories(OPT)oftheWestBank,EastJerusalem,andGaza
areexperiencingthesamerisksandtrendsastheircounterpartselsewhereintheregion.Rates
of tobacco use are very high for both genders (Ghrayeb et al. 2013; Husseini et al. 2010;
Musmar 2012). Drug use is a growing concern, although systematic data have been lacking.
Therewereabout10,000and15,000registereddrugabusersintheWestBank/GazaandEast
Jerusalem,respectivelyin2008(INCB2008).Youthunemployment,consideredariskfactorfor
drug use (Morell et al. 1998, Peck and Plant 1986), is very high in the OPT (26% and 55% in
WestBankandGaza,respectively,forthoseage20Ͳ24)duetoconflict,Israelirestrictionson
travel from the West Bank to Israel, and embargo in Gaza (Palestinian Central Bureau of
7
Statistics 2010). A further risk factor that is very pronounced in the OPT is exposure to long
termconflictandhardship;inothercontextssuchastheU.S.,exposuretoviolence(thoughnot
political violence) is linked to youth engagement in unsafe sex or having multiple partners,
smokinganddruguseBenͲZurH,ZeidnerM.2009,PatͲHorenczyketal.2007)aswellasearly
pregnancy(WilsonandDaly1997).
ExistingstudiesoftheOPTandoftheregionhaveseriousdrawbacksthatlimittheconclusions
wecandrawfromthemabouttheactualprevalenceandpatternsofthesebehaviors,whichis
critical for effective policy responses. First, prior studies of youth risk behaviors as well as
mental health in the OPT and the region mostly use convenience samples of students in
classroomsratherthanrepresentative,randomsamplesthatincludeoutofschoolyouthwho
maybeatgreatestrisk.Second,giventheschoolsetting,theyfocusonyoungeradolescents,
notolderyouth,whoaremorelikelytoengageinriskbehaviors.Third,theydonotaskabout
mostriskbehaviorsoriftheydo,theydonotaskabouttherespondents’ownengagementin
thembutonlyabouttheirperceptionsregardingpeers.
In order to address these gaps in knowledge, we designed and implemented the Palestinian
Youth Health Risk Study, which is the first in the region to collect large scale, representative
survey data from youth on key risk behaviors (smoking, alcohol and drug use, and sexual
activity).Thestudywasdesignedtoinvestigate(1)theprevalenceandpatternsofhealthrisk
behaviorsaswellasmentalhealthamongPalestinianyouth,(2)youths’perceptionsoftherisks
and benefits of potentially harmful behaviors, and their subjective expectations about future
life chances; (3) the relationship of exposure to violence (a significant consequence of
occupation and political strife in the OPT) to mental health, future orientation, and
engagement in high risk behaviors; (4) the effects of other factors including education,
socioeconomicstatus,andlocationonriskbehaviors.
To achieve these aims the survey also gathered detailed information on mental health, risk
perceptions,exposuretoviolenceandotherfactorswhichmaybedriversofriskbehaviors.It
also collected information on youth’s perceptions about the extent of risk behaviors among
both general peers, defined as youth in the community the same age and sex as the
respondent, and proximate peers, defined as the three peers closest to the respondent. The
purpose of collecting this information was twoͲfold. First, because peer norms (perceived
behaviorofpeers)itselfmaybeanimportantdriverofayouth’sownengagementinbehaviors,
and second, because responses about peers may be less subject to bias from respondents’
concerns over stigma or inclination to provide socially desirable answers than responses to
questions about their own behavior. The study was conducted by researchers at the RAND
8
Corporation(basedinSantaMonica,CA,USA,andJuzoorFoundation,basedinRamallah,West
Bank,OPT.1
The objective of the present paper is to present findings on the prevalence of risk behaviors
among youth 15Ͳ24, considering variations by gender, age, and location. Location is a
potentiallyimportantfactorforriskbehaviorsgiventhedifferencesbetweenruralandurban
areasoftheOPT—andbetweenthemandrefugeecampsͲͲwithrespecttocommunitycultural
attitudes,accesstoalcoholanddrugs,andeconomicpressuresandpoliticaltensions(thelatter
being especially severe in camps and in East Jerusalem). The paper also provides the first
systematic investigation of whether patterns in risk behaviors found among youth in other
contextsarealsofoundintheenvironmentoftheMiddleEastandtheparticularenvironment
of the OPT. For example, we examine whether multiple risk behaviors occur together (for
example,ifayouth’suseoftobaccoisrelatedtohisorheralcoholuse),andwhetherperceived
peernormsofbehaviorarerelatedtoayouth’sownlikelihoodofengaginginthatbehavior.
Thefindingsofthisanalysiswillbeimportantinputsintothedevelopmentofpoliciestotarget
vulnerableyouth.
1
ThisresearchwasfundedbytheU.S.NationalInstitutesofHealthunderawardnumberR01HD067115.The
contentissolelytheresponsibilityoftheauthorsanddoesnotnecessarilyrepresenttheofficialviewsofthe
NationalInstitutesofHealth.
9
METHODS
Study population, sampling, and survey development
The survey aimed to achieve a representative sample of youth age 15Ͳ24 living in the West
Bank and East Jerusalem. Initially it was planned to include Gaza in the survey, but logistical
andcostconsiderationsmadethisinfeasible.Atargetsamplesizeof2,500youth,splitequally
between males and females, was selected to enable meaningful statistical comparisons by
gender for younger and older youth (15Ͳ19 and 20Ͳ24), by urban and rural areas, and for
Jerusalemvs.othergovernorates.2AstratifiedtwoͲstagerandomsamplewasdrawnbasedon
the 2007 Population Census, with the strata formed by crossing the 12 governorates with
urban, rural, and refugee camp location. Within each of these strata, survey clusters (census
enumerationareas)wererandomlysampledwithprobabilityproportionaltosizeforatotalof
208clusters.3
Withineachcluster(essentially,community),amodifiedrandomwalkprocedurewasfollowed
to locate 14 households with youth in the appropriate age range. Implicit stratification was
usedtoensureequalnumbersofmaleandfemaleyouths(duringtherandomwalk,theteams
first looked for a household with a male youth, then one with a female youth, and so on).
Wherehouseholdshadmorethanoneindividualage15Ͳ24ofthetargetedgender,Kishtables
were used to randomly select the youth for interview. Both the household head or a parent
and the youth were interviewed; the latter was the key respondent. In some urban areas, it
proveddifficulttofindhouseholdswithyouth.InRamallah,forexample,whichisthedefacto
Palestinian capital, many apartments are inhabited part time by families that usually reside
elsewhere.Thereforeinsomeclustersaconsiderablenumberofresidenceshadtobevisited
beforehouseholdswithyouthwereidentified.
Extensive formative research, including focus groups and interviews with youth followed by
repeated cognitive testing of survey questions, was carried out to determine the optimal
culturallyappropriateapproachestointerviewingaswellasquestionwording,sequence,and
responseformats.Thequestionnaireandfieldprocedureswerepilotedinoneurbanareaand
oneruralarea,afterwhichfinalrefinementsweremade.
2
JerusalemGovernorateisdividedinto‘J1’and‘J2’areas,correspondingtoEasternareasofthecitythat
wereannexedbyIsraelandinsidetheSeparationWallontheonehand,andotherareasofJerusalem
Governorate,ontheother.
3
ThesamplingandclusterselectionwascarriedoutforthestudybythePalestinianCentralBureauof
Statistics.WegreatlyappreciatetheworkofNayefAbedofPCBSonthesampling.
10
Consentand interviewing approach:For minors (under 18) parental consent was obtained to
interviewtheyouth.Parentswereinformedofthepurposeandnatureofthestudy.Separate
consent was obtained from all youth. In view of the highly sensitive nature of the subject
matter in this culturally conservative environment, interviewers were strictly instructed to
ensure that the youth interview was carried out in a private room or other private area (in
somecasesthiswasontheflatroofofthehome).Youthwerealsogiventheoptionofmeeting
separately at a local youth center or other location for the interview, though in practice
relatively few did so, and almost no girls did so, reflecting greater constraints on their
movement. Male youth were interviewed by male interviewers and female youth by female
interviewers. Also reflecting perceived sensitivities of parents and the youth, questions on
sexualactivity—consideredthemostsensitiveofthebehaviorsͲͲwerenotaskedofminors.The
studywasapprovedbyRAND’sHumansubjectsProtectionCommittee.Refusalratesbyyouth
werealmostuniformlylow—11%forthesurveyoverall—butsignificantlyhigher(about30%)in
theareaofEastJerusalem(discussedfurtherbelow).
InterviewswereconductedfaceͲtoͲface,withonepartialexception.Initiallyitwasplannedto
usecomputerassistedselfͲinterview(ACASI)forsensitivequestions,wherebytherespondent
indicates on a small notebook computer or other device (out of view of the interviewer) the
answertoquestionsreadaloudbytheinterviewer.StudieshaveshownthatACASIyieldsmore
honest responses about highly stigmatized behaviors in some settings (Hewett et al. 2004;
Mensch et al. 2008). However, extensive formative research revealed a strong general bias
amongyouthagainstusingcomputersforinterviewinginthisway,andapreferenceforbeing
asked(andrespondingto)thesequestionsinafacetofaceformat.
Nonetheless, youth respondents were given the option of using a selfͲadministered (paper)
questionnaire (SAQ) for questions on sexual activity, which were deemed to be the most
sensitive.Thisapproachretainsthefacetofaceformat,withthequestionsreadaloudbythe
interviewer, but the answers are written by the youth and placed in a sealed envelope that
couldnotbeopenedwithoutdetection,andwasdelivereddirectlytotheteamsupervisorby
theinterviewer.Norespondentorfamilynamesoraddressesappearedonanyquestionnaire
forms used by the survey; only ID numbers, which were linked to names on crosswalk lists
maintainedbythesupervisorsforthedurationofthesurvey,appearedonthequestionnaires
AfterinitialfieldworkrevealedthatveryfewyouthchosetheSAQ,possiblyreflectingalackof
understanding of the method, it was decided to randomly allocate youth to SAQ or FTF for
sexual activity questions to ascertain if the mode mattered for responses, an important
question for future surveys on these topics. This analysis will form the focus of a separate
study.
11
Data analysis
Theanalysisinthispaperisalargelydescriptiveportrayaloftheprevalenceandpatternsofa
range of health risk behaviors covered in the survey. Analysis of differences in behavior by
subgroupswasdoneprimarilyusingPearsonchiͲsquaretests.Toexaminetherelationshipof
friends’ and peers’ behaviors with own behavior, we conducted regressions of perceived
friends or peers shares engaging in the behavior on the respondent's own selfͲreported
engagement in the behavior, with controls for age and location (urban, rural, camp). To
examinetherelationshipsofindividualriskbehaviors,weuselogisticmodelstoestimateodds
ratios of engaging in one behavior conditional on engaging in another, with controls for age
andlocation.Giventhelargeanticipateddifferencesbygenderinhealthriskbehaviorsinthis
environment,separateanalysesareperformedforyoungmenandyoungwomen.Theanalysis
wasdoneusingSTATAversion13,applyingthe‘Survey’routine,whichincorporatesthesurvey
design,inparticularthecorrelationsofstandarderrorswithinsampleclusters.
12
RESULTS
Sample composition and characteristics
Reflecting the sampling approach, the overall sample of 2,481 youth is evenly split between
males and females (Table 1). There are more individuals in the younger age group (15Ͳ19):
1,419(57%ofthetotal)vs.1,062age20Ͳ24(43%),apatternthatfitstheoveralldemographic
profileofPalestiniansintheOPT.(belowweusetheterm‘olderyouth’torefertothe20Ͳ24
agegroupand‘youngeryouth’toreferto15Ͳ19yearolds).However,whilethestratificationby
gender assured equal shares of males and females, the balance between younger and older
youthdiffersbygender.Malesage20Ͳ24makeup40%ofallthemaleyouth,whiletheolder
female group accounts for 45.7% of all females.This is likelyexplainedby older maleyouths
being more likely to be living away from home, or if living at home, being unavailable for
interviewevenaftermultipleattemptsatcontact.4
About one quarter of the sample are refugees (Table 2). ‘Refugee’ is an official designation
referringtosomeonewholostlandorlivelihoodduringthe1948or1967conflictsorwhois
the descendent of such a person, and is eligible for services provided by the United Nations
ReliefandWorksAgency(UNRWA)andotheragencies.Itshouldbenotedthatmostrefugees
are not actually living in refugee camps, which account directly for only a small share of the
refugeepopulation.
As Table 2 indicates, the majority of younger youth 15Ͳ19 are still in school (79% males and
85%females)whiletheoppositeisthecasefortheoldergroup(33%malesand40%females).
Thesubstantiallyhighereducationalenrollmentoffemalerelativetomaleyouthisnoteworthy
(p=0.001 for age 15Ͳ19, p=0.011 for age 20Ͳ24) and consistent with other data sources; for
example, published data from the Palestine Central Bureau of Statistics indicates that some
60%ofuniversitystudentsarefemale(PCBS2014).
Differences in education by location are important, with youth in camps being markedly less
likely to still be in school and having lower grade attainment. Among male youth (all ages),
while60.4%ofurbanrespondentsand64%ofruralreportbeinginschool,only45%ofthosein
camps do (p=0.019 and 0.006 for comparison of camps with urban and rural areas,
respectively). For female youth, about 65% of both urban and rural youth are in school
comparedwith58%forcampsbutthedifferencesarenotstatisticallysignificant(p=0.253and
4
Incaseswherethetargetedyouth(selectedfromamongthoselivinginthehousehold)wasnotinitially
available,interviewerswereinstructedtomakeuptotwosubsequentvisitstotheresidencetoconnectwith
theindividual.
13
0.200). It should be kept in mind (for here and for findings below) that power for detecting
differences between camps and rural or urban areas is low because of the relatively small
numberofsampledyouthincamps.
Marital status differs very strongly by gender, with only 6.5% of older male youth married
comparedwith43%ofolderfemaleyouth(whoobviously,giventhisimbalance,tendtomarry
older males). Reflecting this, a substantial share (35%) of older female youth live away from
theirparentsintheirnewhouseholds,whilealmostallyoungmeninthatagegrouparestill
livingathomewiththeirparents.Thesharesoffemaleyouthwhoaremarrieddoesnotvary
greatlybylocation.Slightlylessthanathirdofallmaleyoutharecurrentlyworkingcompared
withonly6%offemales;forboth,ratesarehigherforolderthanyoungeryouth,asexpected.
Thesefiguresforlevelsofeconomicactivity,includinginparticularthedifferencesbygender,
are in line with other data from the OPT and are similar to findings from across the Middle
East.5
Differencesinfamilysocioeconomicstatusbyareaarenoteworthy.Informationonownership
ofvariousconsumerdurableslikecars,TVs,andmicrowaveswasusedinafactoranalysisto
create a household wealth index. By construction, the mean of the index for the overall
sampleiszerowithastandarddeviationof1.0.Ruralrespondentsarelesswelloffthanurban
residents: for both males and females, the difference is about 0.3 s.d. of the index (p=0.001
and0.00,formalesandfemales,respectively).Thepointestimatessuggestthatwealthamong
camp residents is even lower than for rural areas but these differences are not statistically
significantforeithergender.Valuesoftheassetindexforfemalesareconsistentlylowerthan
formales,likelyreflectingthatasignificantshareoffemaleslivewiththeirspousesinrecently
formedhouseholdsratherthanwithparentswhohavemoreaccumulatedwealth.Withregard
to parental schooling, mother’s education (share having attained secondary level) is also
highestinurbanareas,thougheducationoffathersseemshighestinruralareas.
Health risk behaviors
Before discussing prevalence findings we present the shares of respondents who did not
respondtoquestionsabouttheirengagementinhealthriskbehaviors.Togetherwithrefusalto
participate in the survey (which as discussed above was low) and underreporting (discussed
below),lowlevelsofresponsetospecificquestionsisapotentialsourceofbiasinprevalence
estimates of behaviors. For sensitive questions, there was a coded ‘No Answer’ response for
the interviewer to mark if the youth was not willing to respond; for some questions, for
5
The2013PalestineLaborForceSurvey(PCBS2014)indicatesalaborforceparticipationrateof49%for
males15Ͳ24and8.8%forfemales(figuresincludeGaza).Notethatparticipationincludesboththose
employedandthosesearchingforwork.
14
exampleonpeers’behavior,a‘Don’tKnow’wasalsoallowed.Formostquestionsaboutthe
respondent’sownhealthriskbehaviorsdiscussedinthispaper,nonͲresponserateswerevery
low—under1%oftherelevantsampleforthequestion(thatis,respondentswho,givenfilter
patterns in the questionnaire, were asked the question). NonͲresponse rates for these
questionsareshowninAppendixTable1.RatesofnonͲresponseor‘NoAnswer’aresomewhat
higher(thoughunder5%)forquestionsoncurrentdruguse,whichwereaskedofthosewho
indicatedintheprecedingquestionsthattheyhadevertrieddrugs.
WealsoreportinAppendixTable1thesharesofmissingvaluesforthesamequestions,where
noresponseatallwascodedbytheinterviewer.Byandlargethesealsoarenotsignificant—
under 1% of the relevant sample. One significant exception is the nonͲtrivial number of
missing values for thequestion about current drug use, which shouldhave been asked of all
respondentsreportingthattheyhadeveruseddrugs:thecurrentusequestionismissingfor
17% of thisgroup. Thisis, presumably, not a matter ofnonͲresponse since ‘No answer’ was
explicitlycodedasresponseaswiththeotherbehaviorquestions.Instead,itappearsthatthe
followͲupquestionwasinadvertentlyskippedinsomecasesofindividualshavingreportedever
usingdrugs.
Smoking:Turningtotheprevalencesofriskbehaviors,thesurveymoduleontherespondent’s
health behaviors asked first about smoking, as this is the least stigmatized of health risk
activities. Smoking (including both cigarettes and narghila or water pipe) is very common
amongPalestinianyouth,inlinewithotherstudiesofadolescentsoryouthintheOPT(Husseini
et. al. 2010, Ghrayeb et al. 2013). As shown in Table 3, almost threeͲfourths of older male
youth smoke while almost half of younger male youth do. Rates are substantially lower for
femalesbutstillsignificant:31%forolderfemaleyouthand22%foryoungerfemales(p=0.00
formaleͲfemaledifferenceforbotholderandyoungergroups,respectively).Reportedtobacco
use is lower in rural areas, especially for female youth: among older females, 37% of urban
respondentsreportsmokingcomparedwith16%ofruralrespondents(p=0.00).
Alcoholuse:Slightlylessthanonequarterofmaleyouthage20Ͳ24reporthavingtriedalcohol;
rates in urban areas and camps (26% in each case) are double that in rural areas (13.2%;
p=0.002and0.039,forcomparisonorruralwithurbanareasandcamps,respectively).Rates
among female youth 20Ͳ24 are substantially lower, but with a similar pattern by area: 12%
overall reported having tried alcohol (15% in urban areas, 12.8% in camps, and 3.5% in rural
areas). Among younger youth, 8% of males and 3.6% of females report ever trying alcohol,
againwithhighersharesinurbanareasandcamps(p<0.05forurbanͲruraldifferencesforboth
youngerandolderyouth;p=0.114fordifferencebetweencampsandruralareasforyounger
youthandp=0.021forcampsvs.ruralareasforolderyouth.)
15
Reportedcurrentalcoholconsumption(havinghadalcoholinthelast30days)islower.Slightly
less than 10% of older male youth, and 3.4% of younger male youth, say they currently
consumealcoholicdrinks;4%ofolderfemalesand1.2%ofyoungerfemalessaytheycurrently
drink.Differencesacrossareasarestatisticallysignificantforurbanvs.ruralareasforyounger
youth(p=0.001),urbanvs.ruralforolderyouth(p=0.005)andcampvs.ruralforolderyouth
(p=0.044).
Druguse:Relativelyfewyouthreporthavingtriedanyofarangeofdrugsaskedaboutinthe
survey, including marijuana or hashish, pills, inhalants, and cocaine or heroin (separate
questionswereaskedforeachtype).10%ofmales20Ͳ24reporthavingtriedanykindofdrugs
compared with 4% for younger male youth. Only 4% of older female youth and 1.6% of
younger female youth report ever using drugs. Patterns by location are similar to that for
alcoholinthatselfͲreporteddruguseismarkedlyhigherinurbanareasandcampsthaninrural
areas. For example, 16% of older male youth in camps and 13% in urban areas report ever
usingdrugscomparedwith3%forrural(pfordifferencewithruralareas=0.0074forcamps
and0.0048forurbanareasforoldermaleyouth).Amongyouthsayingtheyevertookdrugs,
the most common types are marijuana/hashish (tried by 57% of those ever using drugs),
inhalants(42%)andpills(14%).
Forthosewhosaytheyhadtrieddrugs,thesurveyaskedaboutcurrentdruguse(“Thesedays
doyoutakeanydrugs?”).Asindicatedabove,therewasanonͲtrivialnumberofmissingvalues
(17%ofthoseeligibleforthequestion).Amongthoseinthegroupwhohadevertrieddrugs
andwereaskedaboutcurrentuse,about1/3ofboththeyoungerandoldermaleyouthsaid
they currently used drugs of some kind; 29% of the older females and 9% of the younger
femalesevertryingdrugssaidtheycurrentlyusethem(Table3).Ifmissingsforthisquestion
amongthegroupofeverusersarerandom,thisimpliesthatabout3.6%ofoldermaleyouth
and 1.1% of younger male youth, and 1.2% of older females and 0.15% of younger females,
currentlyusedrugs.
Sexual activity: Youth were asked if they had ever had experience of sexual activity with a
member of the opposite sex, defined as “romantic kissing, touching private body parts, or
sexual intercourse”. The question was asked only of unmarried, nonͲminor (over 17 years)
youth.25%ofolderunmarriedmaleyouthand22%ofyoungermaleyouthreporthavinghad
sexual experience. Rates for females are generally similar, though unexpectedly, the point
estimateishigherforyoungerfemalesthanolderfemales(25%vs21%)butthedifferenceis
notsignificant(p=0.363).MaleͲfemaledifferencesarenotstatisticallysignificant(p=0.432for
younger males vs. younger females, 0.288 for older males vs. older females). RuralͲurban
differencesappearmorepronouncedformales:foroldermales,thesharesare28%inurban
areas,14.5%inruralareas,and38.2%incamps(p=0.0302forurbanvs.rural,p=0.2924for
urbanvscampsforthisgroup).
16
Thosereportinghavinghadanysexualactivitywerethenaskedspecificallyiftheyhadeverhad
sexualintercourse(SI),definingthetermexplicitlytoavoidambiguity(inwhatfollows,werefer
to‘SI’toindicatethisquestion,while‘hadsexualactivity’referstothebroaderquestionofany
such activity, potentially but not necessarily including intercourse). Experience of SI among
unmarriedyouthissubstantiallylowerthanforexperienceofanysexualactivity.Amongmales,
9.5% of older (20Ͳ24) unmarried male youth and 5.6% of younger (18Ͳ19) unmarried male
youthreporthavinghadsexualintercourse.Forfemales,correspondingsharesare7%forolder
femalesand4%foryoungerfemales(pͲvaluesformaleͲfemaledifferencesare0.200forolder
youthand0.511foryoungeryouth).Notethattheyoungergrouphereincludesonlythosewho
are age 18 and 19, that is, nonͲminors. For both genders and both age groups, rates of SI
experiencearemarkedlylowerinruralareasthanurbanareasandcamps.
ForunmarriedmalesreportinghavinghadSI,thepartnerinthemostrecentoccurrencewasa
‘casualacquaintance’in39%ofcases,followedbyagirlfriend(38%)andsexworker(21%).For
unmarriedfemalesreportinghavinghadSI,thepartnerinthemostrecentoccurrencewasa
boyfriend in 43% of the cases, followed by fiancée (30%) and casual acquaintance (13%).
Contraceptionusewasreportedin73%ofthesecasesforbothmalesandfemales;themost
common method was condoms (approximately three quarters of those who reported using
contraception).
Qualitative formative research suggested that sameͲsex relations were, if not very common,
notexceedinglyrare,andsothesurveyalsoaskedaboutexperienceofsexualactivity(andfor
males,SIaswell)withmembersofthesamesex.2.2%ofunmarriedmales18andolderand
1.7% of females reported such activity. Note that for males this is approximately 10% the
magnitudeofthosereportinganysexualactivitywiththeoppositesex,andsomewhatbelow
thatforfemales.
Finally, the survey gathered information on both phone sex (sexting) and internet sex; the
latter was defined in the question as interaction with another person, not merely viewing
sexual material online. These nonͲphysical forms of sexual interaction are relatively common
amongunmarriedyouthofbothgenders:amongmaleyouth,38%ofolderand33%ofyounger
(age18and19)reporthavingeverengagedineitheroftheseactivities;30%ofolderfemale
youthand23%ofthose18Ͳ19reporthavingdoneso.
InterpersonalViolence:Thesurveyaskedrespondentsiftheyhadbeeninvolvedinaphysical
fightinthelastyear(andhowmanytimes),aswellasaskingiftheywereeverhurtorinjured,
or ever hurt or injured someone, in a fight. The question is not intended to capture
participation in politically motivated violence or altercations with either Israeli or Palestinian
authorities(thequestionasks“Wereyouinvolvedinaphysicalfightwithsomeoneinthelast
year?”),thoughitispossiblethatsomesuchoccurrencesareincludedintheresponses.
17
Fightingisnotuncommon,especiallyamongmalesandamongyoungeryouth.Amongyouth
15Ͳ19,56%ofmalesand29.3%offemalesreportedengaginginoneormorephysicalfightsin
the year prior to the survey. Among older youth 20Ͳ24, 38% of males and 21% of females
reporthavebeeninafight(p=0.000formalesvs.femalesinbothagegroups).Ofthosewho
saidtheywereinvolvedinfighting,42%reportedjustoneincidentinthelastyear,42%report
2Ͳ5incidents,andtheremaining16%reportedahighernumber.Withrespecttoareapatterns,
for both younger and older age groups we find statistically higher prevalence in urban areas
than rural areas (p = 0.049 for urban vs. rural areas for younger youth, p = 0.000 for older
youth).Thereissomeevidenceofhigherprevalenceincampsthanruralareas(p=0.076and
0.053campvs.ruralareasforyoungerandolderyouth,respectively).
Responsesabouteverbeinghurtorinjuredorhurtingorinjuringsomeoneelseinafight,also
showninTable3,displaysimilarpatternsbygender.Theapparentlyhighersharesofyounger
youth relative to older youth reporting either event seems implausible, since the cumulative
likelihoodofeverhavehurtsomeoneorbeenhurtwillrisewithageevenifolderyouthfight
less.Olderyouthmayhavemoredifficultyrecallingsuchanoccurrencethathappenedsome
yearsearlier,orpossiblyaremoreembarrassedtoreportit.
Further patterns by area
Asseenabove,urbanareashavesubstantiallyhigherprevalencethanruralareasofmostyouth
riskbehaviors.Variationsacrossgovernoratesarealsoofsignificantinterest.Whilethesample
wasstratifiedongovernoratebyurban,rural,andcampareas,itwasnotpoweredtodetect
differencesacrossthegovernorates.Nonetheless,thedatasuggestsubstantialvariationacross
governoratesaswellasacrossurbanareas,andinparticular,ofsignificantlyelevatedlevelsof
riskbehaviorsinJerusalem.JerusalemGovernorate,whichismostlyurban,isdividedinto‘J1’
and ‘J2’ areas, corresponding to Eastern areas of the city that were annexed by Israel and
insidetheSeparationWallontheonehand,andotherareas,ontheother.Amongmaleyouth
15Ͳ24 in Jerusalem Governorate (J1 plus J2), rates of current alcohol use, having tried drugs,
andsexualactivityoutsideofmarriage(ageover17)are13.8%,15.5%,and27.5%,respectively.
For urban areas in Jerusalem alone they are 16.1%, 18.4%, and 31.0%. These rates are
substantially higher than for other urban areas combined (5.1%, 5.5%, and 5.5% for current
alcohol use, tried drugs, and sexual activity; p=0.00 for Jerusalem vs. other urban for each
behavior). For female youth age 15Ͳ24 in urban Jerusalem Governorate, rates of current
drinking, tried drugs, and (age over 17) having had any sexual activity are11.6%, 11.5%, and
22.2%, respectively, which similarly are substantially higher than for urban female youth
elsewhereintheOPT.
18
Peers’andfriends’behavior
As noted earlier, youth respondents were asked to indicate the share of peers, both general
and proximate, who engage in different behaviors. General peers were defined as youth of
their age and sex in their communities. Based on preͲtesting, we asked these questions in a
percentageformat.Thesurveyresponsessuggestthattheyouthwereabletogivemeaningful
responses in this format. For example, there was little clumping of responses at 50%,
indicating that youth report actual perceptions of the fractions instead of resorting to the
modalresponse.
However, for some questions there were nonͲtrivial fractions indicating ‘don’t know’ or ‘no
response’.Thissharewas1.5%forsmoking,6%foralcohol,9%fordrugsand12%forsexual
relations. Thus the degree of nonͲresponse appears to be related to the degree of
stigmatizationoftheactivityinquestion;theverysmallshareforsmokingsuggeststhatnonͲ
responseisnotcausedbyalackoffamiliaritywiththepercentageformat.Itisnotpossibleto
determine whether it is caused by a lack of comfort answering questions about more
stigmatizedbehaviorsorthatrespondentshavelessknowledgeofsuchbehaviorsamongtheir
peers,inpartbecausethesearemorelikelytobecarriedoutdiscreetly.However,sincealmost
allyouthwerewillingtoanswerquestionsabouttheirownparticipationinthesebehaviors(as
seen earlier, nonͲresponse rates to such questions were very low), lack of knowledge about
peersseemsthemorelikelyreason.
Questions on peers in general were followed by questions about proximate peers – defined
hereasthethreepeerswhoareclosesttotherespondent(individuals“yourownageandsex
who you spend your time with, such as your good friends”) and which we refer to here as
‘friends’. The respondent was asked how many of these three individuals engaged in a
behavior.Forcomparisonswithownandgeneralpeers’ratesofengagementinthebehavior,
thefriendsresponsesarealsoexpressedasshares—thatis,0,1,2,or3outof3total.
Means for shares of friends engaging in each behavior display the same patterns by age,
gender, and location as means for own engagement while generally being somewhat higher
(Table 4). For example, for male youth 20Ͳ24, the mean own smoking prevalence is 71.5%,
whileitis76%forfriends(p=0.030forthedifference);foryoungwomeninthisagegroupthe
sharesare31%and29%respectively(p=0.018).Forcurrentalcoholuseinthisagegroup,9%of
males say they currently drink, compared with 13% for friends (p=0.000); the corresponding
figuresforfemalesare4%and6%.(p=0.001)
In contrast, respondents perceive levels of general peers’ engagement in risk behaviors that
areusuallysubstantiallyhigherthanmeansfortheirownengagement(aswellasthatoftheir
friends). For smoking, perceived prevalence of peers is modestly higher than those for own
behavior orfriends’;peers’ prevalence is usuallyno more than 20% abovefriends’ rates. For
19
morestigmatizedbehaviors,however,thedifferenceswithownbehavioraswellasfriendsare
typicallylarge.Forexample,whereas9.1%ofoldermaleyouthsaytheycurrentlydrinkalcohol
and the mean proportion of friends reported to drink is 13%, the mean perceived rate of
drinkingamonggeneralageͲsexpeersis22%;forfemalesinthisagegrouptheratesare4.1%
and6.7%forowndrinkingandfriendsand9%forpeers.Asimilarpatternprevailsfordrinking
amongyoungeryouthofbothgenders.Fordruguse,evenlargerproportionaldifferencesare
seenbetweenownandfriends’use(bothofwhichareverylow)ontheonehand,andpeerson
theother.
Although perceived general peer engagement in risk behaviors is thus overall substantially
higher than that reported for friends and oneself, patterns by age, gender, and location are
similar:thatis,markedlylowerforfemalesthanmales,andlowerinruralareasthaninurban
areasandcamps.
Intraclusterconsistencyofownandperceivedpeerbehavior
We explore the reasons for differences in selfͲreported own risk behaviors and perceptions
aboutpeersintheDiscussionsectionbelow.Hereweconductapartialcheckonthevalidityof
the perceptions about peers, based on the idea that if youth were fairly well aware of how
their peers behave, responses within a community about these peers should be relatively
consistent.Thisisbecausethequestionsineffectaskallrespondentsinanage/sexcategoryto
estimate the same datumͲͲthe share of youth like them in the community who engage in a
behavior.Thereforetheseresponses,iftheyareaccuratelycapturingthelocalprevalenceofa
behavior,shouldberelativelyhighlycorrelatedwithinsampleclusters(ofwhichthereare208
inthesurvey),andshouldalsobemorehighlycorrelatedthantheintraͲclusterresponsesfor
ownengagementinthebehavior,asthesedotrulyvaryacrossindividualswithinacommunity.
Theassociationofresponseswithinaclustercanbemeasuredwiththeintraclustercorrelation
coefficient(ICC),theratioofbetweenͲclustervariationoverthesumofthetotal(withinͲcluster
andbetweenͲcluster)variation;ahigherICCindicatesstrongerconsistencyorrelatednessofan
outcomewithinclusters.
AsshowninTable5,formales,ICCsfor(own)smokinganddrinkingarelow(.031and.056)and
similar to schoolͲbased ICCs in studies of US students (Resnicow et al. 2010). Consistency
withinclustersofresponsesregardingbothoneselfandone’speersisstrongerforfemalethan
maleyouth.However,auniformfindingforbothgendersisthatICCsforresponsesaboutlocal
peer engagement in a behavior are substantially larger than for responses about the
individual’s own behavior; that is, responses within a cluster about average peer behavior in
thecommunityvarylessthanresponsesabouttheindividual’sownengagement.Althoughitis
not possible to state unambiguously what a ‘high’ value would be for ICCs (they cannot be
20
interpreted as simple Pearson correlation coefficients), the relative consistency in responses
aboutlocalpeerbehaviorsuggeststhatthepeerprevalenceresponsesaremeaningful.
Relationshipofownbehaviortothatoffriendsandgeneralpeers
InTable6weexaminetherelationshipoftherespondent’sownbehaviortothatoffriendsand
general peers as reported by the respondent. The table compares the mean of friends’ and
peers’prevalencesforrespondentswhoreportengaginginabehaviorwiththosewhoreport
not engaging in the behavior. In general the differences are very large and statistically
significant,withyouthwhoreportengaginginabehavioralsoreportinghigherfriends’aswell
as peers’ engagement in the behavior (p=0.00 in each case). In proportional terms, the
differencesarelargestfordruguse.Formales,individualswhosaytheyhavenevertrieddrugs
haveameanreportedfriends(current)usageof1%comparedwith17%forthosewhohave
trieddrugs(p=0.000),andmeanreportedpeersusageof8%comparedwith26%forthosewho
havetrieddrugs(p=0.000).Patternsforfemaleyouthareverysimilar.
Covariance of individual risk behaviors
Table7presentsoddsratiosofengaginginonehealthriskbehaviorconditionalonengagingin
another, based on logistic models for males and females with controls for age and location
(urban, rural, camp). For young men, the associations of risk behaviors are very large. For
example, if a male youth is a tobacco smoker, the odds of currently consuming alcohol are
about9timeshigherthanifhedoesnotsmoke(p=0.000);theoddsofhavingeveruseddrugs
are 3.8 times higher (p= 0.000); of having had sexual intercourse, about 11 times higher (p=
0.001).Lastly,thereisanassociationofsmokingandviolentbehaviorbutthisissomewhat
lower:maleyouthwhosmokeareabout1.6timesmorelikelytohavebeeninaphysicalfight
in the last year (p=0.001) and the associations of fighting with other risk behaviors are also
generallysmallerthanbetweentheotherriskbehaviors.However,alloddsdifferencesinthe
tableformaleyoutharesignificantatp<=.05.
For female youth, the correlations are similarly positive but more variable and less precisely
estimated.Allofthe(smallnumberof)femaleyouthreportingalcoholusealsosmoke,sono
odds ratio is estimated. The relationship of other behaviors to smoking is very strong for
females,withORsof8.01forevertrieddrugs(p=0.000),3.98foranysexualactivity(p=0.000)
and4.23forfighting(p=0.000).Alcoholuseappearstobesignificantlyassociatedwithahigher
likelihoodofsexualactivityandinternet/phonesex.
Totestwhethercovariancesofbehaviorschangesasyouthgetolder,thesamemodelswere
runaddinginteractionsofageinyears(andalternatively,anindicatorforbeingintheolder20Ͳ
24 group) with the given behavior indicator (results not shown). These interaction terms
generally were not statistically significant, suggestion no change in the relationships among
21
behaviors as young people transition to adulthood. One exception was that among females,
the relationship between smoking and having had sexual intercourse become stronger with
age,thoughthesmallnumberofunmarriedfemalesreportingsexualintercoursesuggeststhe
needforcautionininterpretationofthisestimate.
DISCUSSION
ThisstudyisthefirstofwhichweareawaretocollectpopulationͲbaseddataonPalestinian–
andperhapsanyMiddleEastern—youthonthemajorhealthriskbehaviors,includingsmoking,
alcohol,drugs,andsexualactivity.Wediscussfindingsbymajortopicbelow.
Levels and variation in risk behaviors
Risk Behaviors levels in International Perspective
Other than smoking and engagement in physical fighting, prevalence of selfͲreported risk
behaviors in our survey of youth are usually at the low end of the range of findings from
countriesinotherregions;lackofcomparabledatamakesitdifficulttoknowhowtheratesfor
PalestinianyouthcomparetothoseofotherMiddleEasterncontexts.Datafromotherregions
tendtobeforyoungeryouth.Belowwedrawcomparisonswhereavailablefromotherrecent
studies for similar behaviors and note the age ranges involved. Only samples with significant
overlapofagerangewithoursampleareconsidered.Wefocusonrepresentativesurveysof
youngpeople,hencedonotincludesurveysofuniversitystudentswhichatleastinmostlow
andmiddleincomecountrieswouldbeahighlyselectivesample.
Alcohol use: In the U.S., selfͲreported drinking (once or more in last month) in a nationwide
sample of youth 13Ͳ18 was 34% for boys and 36% for girls (CDC 2014). In South Africa the
equivalent figures were 41% and 30% (Reddy et al. 2010). Among secondary school youth in
Bangkok Thailand, 37% reported ever trying alcohol (Ruangkanchanasetr et al 2005); also in
Thailand, in a nationwide survey of youth age 13Ͳ24, 49% of males and 30% of females said
theyeverdrank,and38%ofmalesand15%offemalesreporteddrinkinginthelast30days
(SirirassameeandSirirassamee2015).Recallthatinoursample,only3.4%ofboysand1.2%of
girls15Ͳ19saytheycurrentlydrinkand8%and4%saytheyeverhadalcohol;amongyouth20Ͳ
24,9.1%ofmalesand4.1%offemalessaytheycurrentlydrinkand22%ofmalesand12%of
females say they ever drank. More in line with our sample, 17% of boys 13Ͳ18 surveyed in
Tehran,Iranreportedevertryingalcohol(Mohammadietal.2006).
Druguse:ExperiencewithdrugsissignificantamongUSadolescents,withapproximately40%
of both boys and girls 13Ͳ18 reporting ever trying marijuana, but lower elsewhere. For
example,inSouthAfrica18%ofboys14Ͳ18and8%ofgirlsreportedevertryingmarijuana,and
in the Thailand national sample of 13Ͳ24 year olds, 13.5% of males and 1.0% of females
22
reportedevertryingmarijuana.Amongyouth15Ͳ19inoursample,only3.8%ofboysand1.6%
of girls said they ever used drugs, which is comparable to rates found in the Tehran sample
(2.1%ofboys15Ͳ18reportingusinganydrugs).
Sexual activity: SelfͲreports of sexual experience among youth and adolescents varies
substantiallybycountryaswell,withPalestinianyouthagainatthelowerendoftherange(for
example, as noted, 10% of unmarried males and 7% of females 20Ͳ24 reporting have had
sexual intercourse). U.S. and South African adolescents report significantly more experience
(US: 48% of boys and 46% report having had SI; South Africa: 45% boys and 30% girls).
Similarly,amongThaiyouth14Ͳ24,49.8%ofmalesand31.5%offemalesreporthavinghadSI.
In the sample of younger (secondary students) youth in Bangkok, only 10% (boys and girls
combined)reporthavinghadSI.Closetoratesinoursample,inurbanChina,7.4%ofboysand
2.6% girls in grades 9Ͳ12, and 16.2% of male college students and 6.7% of female college
studentreporthavinghadSI(SongandJi2010).
Smoking:WherePalestinianyouthshowparticularlyelevatedlevelsofhealthriskbehaviorisin
smoking. Even among younger youth in our sample smoking is significant: 45% of males and
22%offemalesage15Ͳ19reportthattheycurrentlysmokecigarettesornarghila.Ourfindings
areinaccordwithothersurveysinOPT.Forexample,amongstudentsage13Ͳ17inTarkumia,
aruralareainthesouthoftheWestBank,47.4%ofboysand16.8%ofgirlsreportedsmoking
cigarettesinthelast30days(Ghrayebetal.2013).Inasampleofadolescentsingrades7Ͳ10
(ages 12Ͳ17) in Ramallah and Jenin Governorates, 39% of boys and 8% of girls said they
currently smoke cigarettes or narghila (Husseini et al. 2010); the authors of that study aptly
describetobaccouseamongyoungPalestiniansasanepidemic.
Incontrast,intheUS,only16%ofboys13Ͳ18and15%ofgirlsreportsmoking;inSouthAfrica,
26% of boys and 16% of girls smoke. 15.4% of secondary school students in Bangkok report
ever smoking, though a nationwide survey of Thailand for 13Ͳ24 year olds indicates higher
prevalence, with 52% of males reporting ever smoking (39% in the last 30 days) though just
6.3%ofgirlsreporteverysmoking(0.6%inthelast30days).13%ofboys15Ͳ18intheTehran
study report current smoking. However, in Jordan, smoking rates seem to approach those
amongPalestinianyouth:amongmalestudentsage15Ͳ19,66.4%reportedeversmokingand
46.7%saidtheysmokedinthelast30days;amongfemales,44.5%reportedeversmokingand
25.5%saidtheysmokedinthelast30days(Malak2015).
InterpersonalViolence:Wenotefirstthatourfindingswithrespecttoengaginginfightingare
broadly in line with those of a 2011 representative survey of violence carried out by the
PalestineBureauofStatistics(PCBS2011)coveringtheWestBankandGaza,thoughdefinitions
andquestionsdiffer.Forexample,amongmales18Ͳ29inthatsurvey,34%reportedsuffering
physicalabuse(notincludingsexualabuse)inthelastyear;forwomeninthatagerangethe
23
shareishigher(43.4%).ThequestionsposedinthePCBSsurveyreferredtobeingexposedto
violence or physical abuse which clearly in many cases will not be the same as engaging in
fighting. Still, for young men, these numbers are not very different for selfͲreported fighting
amongoldermaleyouth(20Ͳ24)inoursurvey,ofwhom38%reportedbeinginphysicalfights
in the last year. For women the differences are larger, as only 21% of females 20Ͳ24 in our
samplereportedbeinginafight.
Studies on the prevalence of adolescent violence from other countries tend to focus on
youngeradolescentpopulationsthatarenotcomparabletoouroldersample;forexample,the
GlobalSchoolͲBasedHealthSurvey,carriedoutinnumerouscountries,focusseson11Ͳ15year
olds.However,somestudiesconsiderolder,secondaryͲlevelstudents.Levelsofengagementin
fighting in our sample appear comparable to findings from other middle income countries.
AmongSouthAfricansecondarystudents(mostlyage14Ͳ18),ofwhom39%ofboysand25%of
girlsreportedbeinginafightinthelastsixmonths(Reddyetal.2010);ourfindingsformale
and female youth 15Ͳ19, over a reference period that is twice as long, are 56% and 29%,
respectively. With respect to youth elsewhere in the region, our results are quite similar to
findingsforsecondarystudentsinTurkey(meanage16.4years),ofwhom61%ofmalesand
22%offemalesreportedbeinginafightintheprevious12months(Alikasifogluetal.2004).In
asurveyofthreelowͲincomesuburbsofBeirut,Lebanon,20%ofmaleyouthage13Ͳ19were
involvedinfightingwithinashorterthreeͲmonthreferenceperiod(Hajjetal.2011).
IntheU.S.,youngpeople’sselfͲreportedparticipationinfightingislower:amongsecondary
studentsingrades9Ͳ12nationwide,30.2%ofmalesand19.2%offemalesreportedbeingina
physicalfightoneormoretimesduringthelast12months(CDC2013).Notethatthisisan
equivalentrecallperiodtooursurveyhencesuggestsasignificantlylowerlevelofinterpersonal
violencethaninoursampleofyouth.
Patterns across subgroups
Substantialvariationbyage,gender,andlocationarefoundintheselfͲreportedriskbehaviors
of youth in our sample. Engagement in these behaviors is consistently much higher for male
youththanfemaleyouth,higherforolderyouth,andhigherinurbanareasandrefugeecamps
thaninruralareas.Itshouldbenotedthecampsareoftenlocatedinurbanareas,andcanbe
describedaslowincomeneighborhoodswithinthesecities.Campsaregenerallyareasoflow
socioeconomicstatusandlowopportunity(asseveralvariablesinTable2indicate)whichmay
beafactorintherelativelyhighparticipationinriskbehavior.
Also with respect to location, Jerusalem Governorate stands out for its high prevalence of
alcoholuse,druguse,andsexualactivityamongyouth.Thismayreflectproximitytoandease
of access to Israel and hence easier access to drugs and alcohol. Further, J1, the portion of
24
JerusalemformallyannexedbyIsraelin1980,ismarkedbyeconomicdepression,poorsocial
services, and significant social and political tensions (UNCTAD 2013), conditions that may
contribute to the propensity to engage in risky behaviors. J2 in contrast is outside the
separationwallandremainspartoftheWestBank,butduetolegalambiguityoverIsraeliand
Palestinian authority in the area, there arevery few servicesand very little lawenforcement
eitherbyIsraelorthePalestinianAuthority.Consequently,athrivingdrugtradeisreportedto
havedevelopedinJ2(Monks2011;UNOCHA2011).
Strong variation in levels of behaviors by area may seem striking in view of the small
geographicalsizeoftheWestBank.However,travelwithintheWestBankisdifficultandcostly
duetorestrictionsimposedbycheckpoints,theseparationwall,andtheneedtoroutearound
Israeli settlements and roads to settlements. Further, with regard to ruralͲurban differences,
being in rural areas may inhibit engagement in risk behaviors because drugs and alcohol are
less available, stigma is higher (such areas being more conservative), and it is harder to be
discreteoranonymousinvillagesthaninurbanareas.Indeed,formativeinterviewsandfocus
groupswithyouthsuggestedthatmanyyouthvisitcitiestoengageinsuchbehaviorstobeable
toescapetheeyesoftheircommunitiesaswellasbecausethisiswhereillegalsubstancesand
alcoholcanbeeasilyobtained.
Perceptions of peer behavior and the accuracy of self-reported behavior
The survey was unusual in that it asked about both proximate peers (‘friends’) and general
peers’behavior,inadditiontoownbehavior.Theperceivedriskbehaviorofclosefriendsofthe
respondents is fairly closely aligned with the respondents’ own selfͲreported behavior.
However, for peers in general (youth of same age and gender in their community), youth
perceiveprevalencesofbehaviorsthataresubstantiallyhigherthantheirown(selfͲreported)
behavior. In a representative youth sample, sample means for reports of activity of local
age/sex peers, friends, and of the respondents themselves should all be similar provided
respondentshavecorrectknowledgeabouttheirpeersandfriendsanddonotmisstatewhat
they know about their own or others’ behavior. That the means of own and general peer
behaviorinparticulardivergesomuchisthereforedueeitherto(1)youthunderreportingtheir
own behaviors or (2) youth overestimating or overͲreporting peer engagement in the
behaviors,oracombinationofthetwo.
Regarding(2),largedisparitiesbetweendescriptivepeernormsandselfͲreportedalcoholand
drugusebehaviorhavebeennotedforyearsintheliteratureintheUSandelsewhere(Perkins
andBerkowitz1986;Perkins1997;BorsariandCarey2001).Mostauthorsconcludethatyouth
tendtooverestimatetheshareofotherswhoengageinhealthriskbehaviors(thoughnotall
agreeontheevidenceforthis,seePape2012).Itislikelythatthesametendencywouldexistin
oursample.Thefactthatestimatesoftheirclosefriends’engagementinriskbehaviors—which
25
respondents should know fairly accurately—are lower than estimates for general peers
suggeststhattheydooverestimatethelatter.
Atthesametime,(1)underͲreportingbyyouthoftheirownriskbehaviors,mostofwhichare
highly stigmatized in this context, is also certainly possible. In the US, where the degree of
stigmatization is presumably lower, studies of young people’s drug use (using biomarkers
among other means) suggest underreporting (DelaneyͲBlack et al. 2010). Great effort was
made to develop protocols to prevent this in our survey by ensuring that youth were
comfortablediscussingsensitivetopics.Also,thequestionsaboutbothfriendsandpeerscame
before questions about the respondent’s own behaviors (peers were asked about first, then
friends). This means that youth would not be tempted to calibrate their responses about
friends and peers to match what they had previously said about themselves. Youth also, as
noted,likelyhavegoodknowledgeaboutthebehaviorofclosefriends(moresothanpeersin
general).
Given these factors, we might accept the reports about friends as being accurate—that is,
neither misͲreported or misͲestimated to any significant degree. Further, respondents’ own
behavior is likely to be similar to that of their close friends on average, suggesting that the
reportsaboutfriendsaregenerallyindicativeoftherespondents’ownbehaviors.Finally,given
that own behavior reports are generally only moderately lower than for friends, we might
concludethatselfͲreportedbehaviorsarethemselvesalsoclosetothereality.
However,thismaybetoooptimistic,sinceyouthmaybereluctanttorevealwhattheyknow
about their friends’ engagement in risk behaviors as this may be perceived as a negative
reflection on them (although we suspect this reluctance would be less than for one’s own
behavior, and this seems to be borne out in the generally higher means of risk behaviors
reportedforfriends).Insum,theremaystillbeunderreportingofriskbehaviorsoftheyouth
themselvesaswellasoftheirfriends’behaviors.
Since we are fairly confident of the direction of the potential bias in selfͲreported behavior
(downward), and are similarly confident of the direction of any bias with respect to peers’
activities(upward),weinferthatthesetwoestimatesboundthetrueprevalenceofabehavior.
Thisrangesuggeststhatprevalenceofmosthealthriskbehaviorsarestillmodestbutnottrivial
(and for smoking and engaging in violent behavior, significantly higher). Therefore these
behaviorsshouldbeasourceofconcernforhealthpolicymakers.Evenwithuncertaintyover
exact levels, the resultsprovide an important view into patterns of riskbehaviors across age
groups,gender,andlocation.Thesepatternsareconsistentacrossbehaviors,andarereflected
bothinyouth’sselfͲreportedbehaviorsandtheirperceptionsofthebehaviorsofpeers.
26
Relation of own and perceived behavior of peers
Our finding that individuals’ selfͲreported risk behavior is strongly and positively correlated
with descriptive peer norms is consistent with studies from outside of the region (Rimal and
Real2005;SimonsͲMortonandFarhat2010;PerkinsandWechsler1996).Likethosestudies,
our results suggest a possible causal link from perceptions of peer engagement to an
individual’s own participation in health risk activities. Here the emphasis is less on whether
these perceptions are accurate than whether they influence one’s own behavior. If youth’s
own actions respond to what they believe their peers are doing, policies that are able to
‘correct’ overestimation of peers’ behaviors—or that actually change the behavior of peersͲͲ
can reduce individuals’ likelihood of engaging in risk activities, by changing descriptive social
norms.
However, as is well recognized, correlations of selfͲreported behavior and perceived peer
behavior may reflect selection issues or confounders rather than a causal relation. Those
participatinginastigmatizedactivitymaysimplyhavebetterinformationabouthowcommon
that activity is in the community; or respondents may assume that other youth are like
themselvesintermsofbehavior;oryouthwhoengageinabehaviormaytendtoexaggerate
theextentofthatbehavioramongothersasameansofselfͲjustification.Eachofthesefactors
canexplainthecorrelationofownbehaviorandperceivedpeerengagement,apartfromany
causalrelationship.Subsequentanalysisofthedatawillexplorethesepossibilitiesmoredeeply
with inclusion of confounding variables, though it will be difficult to arrive at a conclusive
determinationoncausality.
Covariance among multiple risk behaviors
Alsoasinstudiesinmanyothersettings(reviewedinMonahanandHawkins2010)wefindthat
youthwhoparticipatedinoneriskbehaviorhaveanelevatedchanceofparticipatinginother
risk behaviors. This pattern is often explained by problem behavior theory, introduced by
Jessor(Jessor&Jessor,1977;Jessoretal.,2003),wherebyanunderlyingbehavioralsyndrome
causesayouthtoadoptmultipleriskbehaviors.Wefindthat‘traditional’healthriskbehaviors
such as smoking and drinking are linked not only to each other but also to engagement in
interpersonalviolence(fighting),apatternthathasbeenobservedinsurveysofadolescentsin
Westerncountries(SmithͲKurietal.2004).Someresearchfromindustrializedcountriesthat
examineschangesinclusteringofriskbehaviorsasyoungpeopletransitiontoadulthoodfind
thatthecorrelationsdeclinewithage,suggestingaweakeningofunderlyingproblembehavior
syndrome (see Monahan and Hawkins 2010), though other studies find no change. In our
sample we find few differences in the correlations of behaviors between younger and older
youth.
27
Future analysis of the data will examine whether youth who participate in multiple risk
behaviors share important characteristics, namely a lack of protective factors such as family
supportandincomeoranexcessofriskfactorssuchasexposuretoviolenceordepression.
Implications of the findings
The experience of the Palestinian Youth Health Risk study shows, first, that it is possible to
carryoutpopulationͲbasedsurveysofyouthonhighlysensitivebehaviorsinconservativesocial
contextsoftheMiddleEast.Giventhelackofinformationonthesebehaviorselsewhereinthe
region,itwouldbehighlybeneficialforpublichealthauthoritiesandresearcherstocarryout
similar surveys across the region, both to understand current prevalence and to be able to
monitor changes over time. A great deal of effort went into the development of the
instrumentsandfieldproceduresforthisstudytodealwithculturalsensitivities,andthiswill
undoubtedlybenecessaryelsewhere.Responseratestothecurrentsurveywerehigh,butitis
expectedthatthereissomedegreeofunderreportingbyyouthoftheirengagementincertain
behaviors.Inothercontexts,alternativessuchasaudioassistedcomputerinterviewsmaybe
feasible to reduce bias, even if this approach was deemed not appropriate for the current
study.
The survey provides a first clear view of patterns by age, gender and location of health risk
behaviorsamongPalestinianyouth.Urbanareasandrefugeecampshavesubstantiallyhigher
prevalenceofriskbehaviors.Jerusalemappearstohaveparticularlyhighlevelsofsuchactivity.
OutreachandeducationprogramsforPalestinianyoutharerelativelyundeveloped,astheyare
for youth in the region generally. The current findings provide guidance as to where such
programsaremostneeded.Also,andnotsurprisingly,youngmen,especiallyoldermaleyouth,
are the most likely to engage in health risk activities. Programs should therefore make
particular efforts to engage male youth, but also should not ignore female youth, who while
apparently less prone to do so, also engage in these behaviors. Among younger youth,
programswilllikelyneedtoinvolveparents,andresearchisneededonthebestwaytodothis.
For all groups of youth, the findings point to tobacco use (especially) and engagement in
interpersonal violent behavior as key behaviors deserving of focused attention. Smoking has
obviousdirecthealthimplications,especiallyinthelongterm.Levelsofinterpersonalviolence
arequitehighthoughbroadlyinlinewithfindingsfromseveralothermiddleincomecountries.
Fighting may have direct health implications through injury but also may lead to significant
negative emotional outcomes among young people. The causes and implications of violence
amongPalestinianyouth(includingtheroleofconflictandeconomicstress)shouldbecarefully
studiedtoformulateappropriateinterventions.
28
With respect to sexual activity, experience with sexual intercourse among unmarried youth
seems rare among Palestinian youth, but reported sexual activity overall is not, though it is
higherformaleyouththanfemaleyouth.Inaddition,phoneandinternetsexisfairlycommon
among even younger youth and females. These forms of nonͲphysical interaction obviously
pose no direct health risk. The question is whether they are a substitute for actual sexual
contactwhichismorerisky(andharderforyoungpeopletoarrangeinthisenvironment)ora
complementtoit,ormayevenleadtoactualengagementintheseriskybehaviors.Forboth
youngmenandwomen,thereisapositiveassociationofsexting/internetsexwithhavinghad
intercourse(p=0.000inbothcases).Thisdoesnotmeanthatthetwoconstructsarecausally
related (for example we do not control for covariates that may affect both outcomes, which
will be investigated in future work with the data). More generally, the implications of the
internetandsextingforyouthriskbehaviorsshouldbesubjecttofurtherstudy.
Finally,withrespecttoanumberofkeypatterns,thestudyfindingsdisplayastrikingsimilarity
to youth or adolescent surveys carried out in other regions. These include perceived peer
normsforriskbehaviorsthataresubstantiallyhigherthanselfͲreportedengagementinthese
behaviors; a correlation of a youth’s own behavior with these perceived peer norms; and a
strong likelihood that youth who engage in one risk behavior also engage in others.
InterventionsforPalestinianyouthshouldbeinformedbythesepatterns.Withregardtothe
last finding, for example, prevention education programs need to deal with a range of
connectedriskbehaviorsforwhichcertainyouthmaybeatrisk,notjustsinglebehaviorssuch
as drug use. In addition, the correlation of an individual’s behavior with perceived peer
behaviorsuggeststhatinfluencingwhatyouththinkaboutpeersmayreducetheirlikelihoodof
engaging in risk behaviors, though additional work is needed to better assess whether this
relationshipiscausalassuchinterventionswouldassume.
ThispaperprovidesthefirstviewofPalestinianyouths’engagementinarangeofhealthrisk
behaviorsandhasbeenmostlydescriptive.Futureworkisplannedwiththesurveytoexamine
the correlates and determinants of these behaviors, including family situation, exposure to
violence,mentalhealth,expectationsforthefutureandassessmentofrisksofbehaviors,and
personalitytraitssuchasimpulsivenessandfatalism.Thesefindingswillprovidemorerefined
guidancetothedevelopmentofpreventionprogramsforPalestinianyouth.
29
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34
TABLES
Table1ͲͲCompositionofthesamplebygender,ageandlocation
male
all
15Ͳ19
20Ͳ24 all
female
15Ͳ19
20Ͳ24
urban Number
Share(column)
811
65.4%
490
65.7%
321
64.8%
810
65.3%
433
64.3%
377
66.5%
rural
Number
Share(column)
334
26.9%
198
26.5%
136
27.5%
334
26.9%
191
28.4%
143
25.2%
camp
Number
Share(column)
96
7.7%
58
7.8%
38
7.7%
96
7.7%
49
7.3%
47
8.3%
All
Number
Share(column)
Share(row)
1241
100.0%
50.0%
746
100.0%
30.1%
1240
100.0%
50.0%
673
100.0%
27.1%
567
100.0%
22.9%
35
495
100.0%
20.0% Table2ͲͲSocioͲdemographiccharacteristicsofthesample
all
1241
N
Refugee(%)
Currentlyinschool(%)
male
15Ͳ19
20Ͳ24
746
495
all
1240
female
15Ͳ19
20Ͳ24
673
567
Refugee
25.38%
23.06%
28.89%
26.37%
27.04%
25.57%
all
urban
rural
camp
60.19%
60.42%
64.07%
44.79%
78.69%
79.80%
81.31%
60.34%
32.32%
30.84%
38.97%
21.05%
64.76%
64.81%
66.47%
58.33%
85.29%
85.91%
84.29%
83.67%
40.39%
40.58%
42.66%
31.91%
11.29
10.54
12.42
11.93
10.89
13.24
Yearsofschooling
Married(%)
all
urban
rural
camp
2.58%
2.96%
1.50%
3.13%
0.00%
0.00%
0.00%
0.00%
6.46%
7.48%
3.68%
7.89%
22.34%
22.47%
21.86%
22.92%
4.61%
4.62%
4.19%
6.12%
43.39%
42.97%
45.45%
40.43%
Working(%)
yes
31.02%
16.09%
53.54%
6.05%
1.04%
11.99%
withparents
Withspouseinownhousehold
Other*
96.78%
2.10%
0.64%
98.93%
0.00%
0.67%
93.54%
5.25%
0.61%
78.71%
17.74%
3.06%
94.95%
3.57%
1.19%
59.44%
34.57%
5.29%
56.23%
59.58%
48.96%
58.16%
63.13%
50.00%
53.27%
54.41%
47.37%
47.65%
58.98%
43.75%
54.04%
62.30%
44.90%
40.32%
54.55%
42.55%
Mother'sEducationͲSecondaryorhigher
Urban
53.14%
Rural
47.60%
Camp
45.83%
59.18%
48.99%
51.72%
43.93%
45.59%
36.84%
45.56%
40.72%
40.63%
51.50%
47.64%
40.82%
38.73%
31.47%
40.43%
0.236
Ͳ0.074
Ͳ0.073
0.212
Ͳ0.032
Ͳ0.105
Ͳ0.013
Ͳ0.324
Ͳ0.398
Ͳ0.013
Ͳ0.275
Ͳ0.283
Ͳ0.012
Ͳ0.388
Ͳ0.517
Livingarrangement%
Father'sEducationͲSecondaryorhigher
Urban
Rural
Camp
AssetIndex
Urban
Rural
Camp
0.226
Ͳ0.057
Ͳ0.085
Note:*"Other"includes"Livingwithmyspouses'parent(s)","livewithotherrelatives"and"livewithfriends"
36
Table3ͲPrevalenceofhealthriskbehaviorsbyage,sexandlocation(%)
Males
all
urban
rural
camps
Currentsmoking
15Ͳ19
45.44% 46.53%
20Ͳ24
71.52% 77.57%
All
55.84% 58.82%
Everusealcohol
15Ͳ19
8.04%
9.80%
20Ͳ24
22.42% 25.86%
All
13.78% 16.15%
Currentalcoholuse
15Ͳ19
3.35%
4.49%
20Ͳ24
9.09% 11.21%
All
5.64%
7.15%
Everusedrugs
15Ͳ19
3.75%
4.29%
20Ͳ24
10.51% 13.08%
All
6.45%
7.77%
Currentdruguse(as%ofthoseeverusedrugs)
15Ͳ19
32.14% 33.33%
20Ͳ24
34.62% 38.10%
All
33.75% 36.51%
Hadanysexualactivity(unmarriedonlyand18orabove)
15Ͳ19
21.52% 23.90%
20Ͳ24
24.51% 27.36%
All
23.50% 26.15%
Hadsexualintercourse(unmarriedonlyand18orabove)
15Ͳ19
5.49%
6.92%
20Ͳ24
9.33% 12.16%
All
8.02% 10.33%
Currentinternetorphonesex(unmarriedonlyand18orabove)
15Ͳ19
33.33% 32.70%
20Ͳ24
37.96% 41.55%
All
36.39% 38.46%
Engagedinafightlastyear
15Ͳ19
56.03% 57.35%
20Ͳ24
38.38% 41.43%
All
48.99% 51.05%
Waseverhurtorinjuredinafight
15Ͳ19
30.97% 33.67%
20Ͳ24
26.67% 26.48%
All
29.25% 30.83%
Everhurtorinjuredsomeoneelse
15Ͳ19
40.75% 43.27%
20Ͳ24
36.57% 37.38%
All
39.08% 40.94%
37
all
urban
Females
rural
camps
41.92%
56.62%
47.90%
48.28%
73.68%
58.33%
21.55%
31.22%
25.97%
26.79%
36.60%
31.36%
9.95%
16.08%
12.57%
20.41%
34.04%
27.08%
4.04%
13.24%
7.78%
6.90%
26.32%
14.58%
3.57%
11.64%
7.26%
4.62%
14.59%
9.26%
1.05%
3.50%
2.10%
4.08%
12.77%
8.33%
0.51%
3.68%
1.80%
3.45%
10.53%
6.25%
1.19%
4.06%
2.50%
1.85%
5.04%
3.33%
0.00%
1.40%
0.60%
0.00%
4.26%
2.08%
2.02%
2.94%
2.40%
5.17%
15.79%
9.38%
1.63%
4.23%
2.82%
1.85%
5.31%
3.46%
0.52%
0.70%
0.60%
4.08%
6.38%
5.21%
50.00%
25.00%
37.50%
0.00%
16.67%
11.11%
9.09%
29.17%
22.86%
12.50%
35.00%
28.57%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
10.34%
14.50%
13.23%
35.00%
38.24%
37.04%
24.87%
20.87%
22.39%
27.61%
21.86%
24.07%
19.61%
21.79%
20.93%
16.67%
10.71%
12.50%
1.72%
2.29%
2.12%
5.00%
11.76%
9.26%
4.06%
6.85%
5.79%
4.48%
8.84%
7.16%
1.96%
2.56%
2.33%
8.33%
3.57%
5.00%
32.76%
27.48%
29.10%
40.00%
47.06%
44.44%
23.35%
29.60%
27.22%
26.12%
32.56%
30.09%
15.69%
20.51%
18.60%
25.00%
32.14%
30.00%
53.03%
30.15%
43.71%
55.17%
42.11%
50.00%
29.27%
20.99%
25.48%
30.48%
24.67%
27.78%
24.08%
10.49%
18.26%
38.78%
23.40%
31.25%
26.77%
24.26%
25.75%
22.41%
36.84%
28.13%
16.79%
13.58%
15.32%
17.78%
16.18%
17.04%
14.14%
7.69%
11.38%
18.37%
10.64%
14.58%
33.84%
30.88%
32.63%
43.10%
50.00%
45.83%
14.12%
11.82%
13.06%
14.78%
14.32%
14.57%
10.99%
4.90%
8.38%
20.41%
12.77%
16.67%
Table4ͲPerceptionsoffriends'andpeers'behavior(%engaginginriskactivities)
Males
all
urban
rural
camps
Currentsmoking
15Ͳ19
all
Females
urban
rural
camps
Friends
Peers
Friends
Peers
54.07
63.99
76.38
80.36
53.40
63.72
76.98
80.45
52.19
60.28
72.06
78.76
66.09
79.18
86.84
85.26
16.87
20.08
27.61
28.78
18.71
23.19
32.71
34.13
11.52
10.60
13.05
11.66
21.53
28.52
31.21
39.11
Friends
Peers
Friends
Peers
6.41
13.00
13.02
22.47
7.28
13.37
15.26
25.11
3.72
10.86
7.16
15.24
8.19
17.27
14.91
25.53
1.93
5.54
6.71
10.86
2.62
7.36
8.22
13.26
0.70
1.11
2.33
3.11
0.68
7.12
7.97
15.16
Friends
Peers
Friends
Peers
1.03
7.60
3.98
13.17
1.23
8.53
5.10
15.24
0.00
3.78
1.23
8.51
2.87
12.71
4.39
12.15
0.25
4.19
2.12
8.10
0.31
5.65
2.57
10.14
0.18
0.55
0.70
0.96
0.00
6.32
2.90
14.05
Currentsexualactivity,unmarried(intercourse)
Friends
4.20
3.99
15Ͳ19
Peers
7.68
7.74
20Ͳ24
Friends
11.80
13.58
Peers
14.15
15.37
4.73
7.03
7.45
11.74
4.17
9.31
13.06
11.82
9.79
10.64
20.81
15.21
8.94
12.38
22.18
18.41
10.67
5.32
16.11
5.10
14.07
17.30
25.98
20.00
20Ͳ24
Currentalcoholuse
15Ͳ19
20Ͳ24
Currentdruguse
15Ͳ19
20Ͳ24
Notes:'Friends'refertothreeclosestfriendsoftherespondent.%foreachrespondentiscalculatedasthenumberreportedto
engageinthebehaviordividedby3.'Peers'refertogeneralpeersinthecommunityofthesameageandsexoftherespondent.
38
Table5ͲIntraclusterCorrelationCoefficients(ICCs)forownandpeers'engagementinriskbehaviors
Behavior/Respondentengagement
Males
Own
engagement
Peer
engagement
Females
Own
Peer
engagement engagement
Smoking
0.031
0.179
0.343
0.447
Alcoholuse
0.056
0.269
0.127
0.575
Druguse
0.106
0.358
0.018
0.592
EverSexualintercourse(unmarried)
0.156
0.263
0.201
0.544
Notes:ICCistheratioofbetweenͲclustervariationdividedbythetotalvariation,thesumofthewithinͲclusterand
betweenͲclustervariation.Forsmoking,alcoholuse,andsexualintercourse,'ownengagement'referstocurrent
selfͲreportedparticipationoftherespondentand'peerengagement'referstotheperceivedshareoflocalage/sex
peersparticipating.Fordruguse,ownengagementreferstotherespondentreportingevertryingdrugsandpeer
engagementreferstotheperceivedshareofpeerscurrentlyengagedindruguse.Forownengagementinbehaviors,
whicharebinaryoutcomes,weusetheapproachofRodriguezandElo(2003)toderiveICCsandconfidenceintervals.
AllpeerandownbehaviorICCsaresignificantatthe1%level.
39
Table6ͲMeanofFriends'andpeers'engagementinriskbehaviorsbyrespondent'sownengagementinthebehavior(%)
Males
Females
Behavior/Respondentengagement
Friends
p
Peers
p
Friends
p
Peers
p
Currentsmoking
No
Yes
0.43 0.000
0.79
61.95 0.000
77.37
0.09 0.000
0.57
15.60
47.54
0.000
Currentalcoholuse
No
Yes
0.06 0.000
0.59
15.49 0.000
38.67
0.03 0.000
0.45
6.93
46.55
0.000
Evertrieddrugs
No
Yes
0.01 0.000
0.17
8.36 0.000
25.87
0.01 0.001
0.14
5.30
28.94
0.000
EverSexualintercourse(unmarried)
No
0.06 0.000
10.93 0.000
0.19 0.000
11.68
0.000
Yes
0.46
32.31
0.72
45.67
Notes:Fordrugsandsexualintercourse,questionsregardingfriendsandpeersaskabouttheircurrentengagement
behavior,notwhethertheyeverengagedinit.PͲvaluesarefromregressionsofperceivedfriendsorpeerssharesonthe
respondent'sownselfreportedengagementinthebehavior,withcontrolsforageandlocation(urban,rural,camp)
40
Table7ͲAssociationsofindividualriskbehaviors(oddsratios)
Males15Ͳ24
Currentsmoking
p
Currentalcoholuse
p
everuseddrugs
p
everhadsexualintercourse
p
everhadsexualactivity
p
Currentsmoking
ͲͲ
ͲͲ
9.486
0.000
3.843
0.000
10.988
0.001
3.916
0.000
Currentalcoholuse
9.486
0.000
ͲͲ
ͲͲ
9.453
0.000
19.974
0.000
9.145
0.000
everused
drugs
3.843
0.000
9.453
0.000
ͲͲ
ͲͲ
11.031
0.000
8.249
0.000
everhad
sexual everhadsexual
intercourse
activity
10.988
3.916
0.001
0.000
19.974
9.145
0.000
0.000
11.031
8.249
0.000
0.000
ͲͲ
ͲͲ
ͲͲ
ͲͲ
Females15Ͳ24
Currentsmoking
p
Currentalcoholuse
p
everuseddrugs
p
everhadsexualintercourse
p
everhadsexualactivity
p
Currentsmoking
ͲͲ
Currentalcoholuse
ͲͲ
ͲͲ
ͲͲ
8.017
0.000
22.499
0.000
3.984
0.000
ͲͲ
ͲͲ
3.646
0.062
3.394
0.075
2.670
0.041
everused
drugs
8.017
0.000
3.646
0.062
ͲͲ
ͲͲ
6.839
0.001
2.115
0.081
everhad
sexual everhadsexual
intercourse
activity
22.499
3.984
0.000
0.000
3.394
2.670
0.075
0.041
6.839
2.115
0.001
0.081
ͲͲ
ͲͲ
ͲͲ
ͲͲ
Notes:Basedonlogitregressions.Showstheincreaseinthelikelihoodofengaginginanactivity(showninfirstcolumn)
conditionalonengagingtheother(alongtoprow).Modelalsoincludescontrolsforageandlocation.(urban,rural,
camp).Amongfemales,allwhoreportedcurrentdrinkingalsoreportedcurrentysmokingsothisrelationshipisnot
estimated.
41
AppendixTable1ͲͲNonͲresponseratesforriskbehaviorquestions
Age15Ͳ19
all
urban
rural
camps
Currentsmoking
NoAnswer
0.07%
0.11%
0.00%
0.00%
Missing
0.14%
0.22%
0.00%
0.00%
0.09%
0.09%
0.14%
0.00%
0.00%
0.36%
0.00%
0.00%
Everusealcohol
NoAnswer
Missing
urban
Age20Ͳ24
rural
camps
0.33%
0.11%
0.00%
0.00%
0.00%
0.00%
0.00%
0.19%
0.00%
0.14%
0.00%
0.36%
0.00%
0.00%
Currentlyusealcohol(forthosewhoeverusedalcohol)
NoAnswer
0.00%
0.00%
Missing
5.95%
4.41%
0.00%
20.00%
0.00%
0.00%
0.56%
0.56%
0.00%
0.00%
0.00%
0.00%
6.25%
6.25%
Evertrieddrugs
MarijuanaorHasish
NoAnswer
Missing
AmphtamineorTripPills
NoAnswer
Missing
Substanceinhalation
NoAnswer
Missing
CocaineorHeroine
NoAnswer
Missing
0.21%
0.07%
all
0.00%
0.21%
0.00%
0.11%
0.00%
0.51%
0.00%
0.00%
0.09%
0.09%
0.14%
0.00%
0.00%
0.36%
0.00%
0.00%
0.00%
0.42%
0.00%
0.33%
0.00%
0.00%
0.00%
2.80%
0.00%
0.56%
0.00%
0.72%
0.00%
0.36%
0.00%
0.00%
0.00%
0.28%
0.00%
0.33%
0.00%
0.00%
0.00%
0.93%
0.00%
0.75%
0.00%
0.86%
0.00%
0.72%
0.00%
0.00%
0.00%
0.42%
0.00%
0.43%
0.00%
0.00%
0.00%
1.87%
0.00%
0.66%
0.00%
0.86%
0.00%
0.36%
0.00%
0.00%
Currentdruguse(forthosewhoeveruseddrugs)
NoAnswer
2.56%
3.45%
Missing
20.51% 24.14%
0.00%
0.00%
0.00%
20.00%
2.63%
11.84%
3.23%
11.29%
0.00%
20.00%
0.00%
11.11%
Hadanysexualactivity(unmarriedand18orabove)
NoAnswer
0.23%
0.34%
Missing
0.69%
0.00%
0.00%
1.83%
0.00%
3.13%
0.51%
1.53%
0.20%
1.76%
0.96%
0.96%
1.61%
1.61%
Hadsexualintercourse(unmarriedand18orabovewhohavehadanysexualactivity)
Missing
1.00%
1.33%
0.00%
0.00%
0.56%
0.00%
2.78%
0.00%
Continued
Note:showsthe%ofrespondentsforagivenquestionwithacodedresponseof'noanswer'or(dependingonthequestionresponses)
'donotknow'.Thetablealsoshowsthe%ofmissingvaluesforeachquestion,equaltotheshareofrespondentswithnocodedresponse
toaquestiontheyshouldhavebeenasked,givenfilterpatternsinthequestionnaire.
42
AppendixTable1(Continued)ͲͲNonͲresponseratesforriskbehaviorquestions
Age15Ͳ19
all
urban
rural
camps
all
urban
Age20Ͳ24
rural
camps
Currentinternetorphonesex(unmarriedand18orabove)
PhoneSex
NoAnswer
0.23%
0.34%
Missing
0.92%
0.34%
InternetSex
NoAnswer
0.00%
0.00%
Missing
0.92%
0.34%
0.00%
1.83%
0.00%
3.13%
0.13%
0.90%
0.20%
0.78%
0.00%
0.48%
0.00%
3.23%
0.00%
1.83%
0.00%
3.13%
0.26%
0.64%
0.20%
0.78%
0.48%
0.00%
0.00%
1.61%
Engagedinafightlastyear
NoAnswer
Don'tKnow
Missing
0.14%
0.28%
0.21%
0.00%
0.33%
0.22%
0.26%
0.00%
0.26%
0.93%
0.93%
0.00%
0.00%
0.00%
0.85%
0.00%
0.00%
0.86%
0.00%
0.00%
1.08%
0.00%
0.00%
0.00%
Selfhurtorinjuredinafight
Don'tKnow
Missing
0.21%
0.35%
0.33%
0.22%
0.00%
0.51%
0.00%
0.93%
0.09%
0.75%
0.14%
0.72%
0.00%
1.08%
0.00%
0.00%
Hurtorinjuredsomeoneelse
NoAnswer
Don'tKnow
Missing
0.07%
0.35%
0.78%
0.00%
0.43%
0.54%
0.26%
0.26%
1.54%
0.00%
0.00%
0.00%
0.19%
0.19%
1.41%
0.29%
0.29%
1.58%
0.00%
0.00%
1.43%
0.00%
0.00%
0.00%
Note:showsthe%ofrespondentsforagivenquestionwithacodedresponseof'noanswer'or(dependingonthequestionresponses)
'donotknow'.Thetablealsoshowsthe%ofmissingvaluesforeachquestion,equaltotheshareofrespondentswithnocodedresponse
toaquestiontheyshouldhavebeenasked,givenfilterpatternsinthequestionnaire.
43