Undergraduate student drinking and related harms at an Australian university: web-based survey of a large random sample.

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by  Hallett, Jonathan

Hallettetal.BMCPublicHealth2012,12:37
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RESEARCH ARTICLE Open Access
Undergraduate student drinking and related
harms at an Australian university: web-based
survey of a large random sample
Jonathan Hallett1,2,3*, Peter M Howat1,2,3, Bruce R Maycock1,2,3, Alexandra McManus4, Kypros Kypri5,6 and
Satvinder S Dhaliwal2,7
Abstract
Background: There is considerable interest in university student hazardous drinking among the media and policy
makers. However there have been no population-based studies in Australia to date. We sought to estimate the
prevalence and correlates of hazardous drinking and secondhand effects among undergraduates at a Western
Australian university.
Method: We invited 13,000 randomly selected undergraduate students from a commuter university in Australia to
participate in an online survey of university drinking. Responses were received from 7,237 students (56%), who
served as participants in this study.
Results: Ninety percent had consumed alcohol in the last 12 months and 34% met criteria for hazardous drinking
(AUDIT score ≥ 8 and greater than 6 standard drinks in one sitting in the previous month). Men and Australian/
New Zealand residents had significantly increased odds (OR: 2.1; 95% CI: 1.9-2.3; OR: 5.2; 95% CI: 4.4-6.2) of being
categorised as dependent (AUDIT score 20 or over) than women and non-residents. In the previous 4 weeks, 13%
of students had been insulted or humiliated and 6% had been pushed, hit or otherwise assaulted by others who
were drinking. One percent of respondents had experienced sexual assault in this time period.
Conclusions: Half of men and over a third of women were drinking at hazardous levels and a relatively large
proportion of students were negatively affected by their own and other students’ drinking. There is a need for
intervention to reduce hazardous drinking early in university participation.
Trial registration: ACTRN12608000104358
Background students, 37% have reported one or more binge episodes
A high prevalence of hazardous drinking by university in the previous week [13].
students has been reported in many countries [1-3] with Factors within the university environment contribute
this population group often drinking more than their to these high levels of consumption leading to a range
non-university/college student peers [4-7]. In large-scale of negative consequences [5,7,14]. These include: social,
national surveys in the United States, 37-44% of stu- physical and psychological harms to the student e.g. aca-
dents report binge drinking (more than five standard demic impairment, blackouts, injury, suicide, unintended
drinks per occasion; each containing 12 g ethanol) in sexual activity and sexual coercion; harm to other peo-
the previous two weeks [8-10] with men drinking more ple including interpersonal and sexual violence; and
than women, although this difference has narrowed over costs to the institution such as property damage and
time [10-12]. Among New Zealand (NZ) university student attrition [13,15-21]. The secondhand effects of
people’s drinking on others are also assuming greater
importance for advocacy in alcohol control policy, both
*Correspondence:[email protected]
1WesternAustralianCentreforHealthPromotionResearch,CurtinHealth for the victims experiencing assaults, sexual violence
InnovationResearchInstitute,CurtinUniversity,KentStreet,Bentley,Australia
Fulllistofauthorinformationisavailableattheendofthearticle
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and impacts on studying [18,22] and for the wider com- 52.4% of the sample and 20.6% were non-residents. The
munity experiencing litter, noise and vandalism [23]. term ‘non-resident’ refers to students enrolled at the
Australian studies report between 70-96% of university university that are not permanent residents of Australia
students regularly consume alcohol [24-29] with 50% or New Zealand and includes those on student visas and
drinking to intoxication at least weekly [30,31]. How- humanitarian visas.
ever, previous studies have relied on convenience sam-
ples [24-39] and most are at least a decade old Procedure
[24-33,38]. The one Australian study that used a ran- We adopted a survey recruitment procedure described
dom sample [40] surveyed only international students in detail elsewhere [59,65,67,70]. Four weeks after the
and therefore is not generalizable to all university stu- start of the first semester of 2007 the University Surveys
dents. This study found, that 66% consumed alcohol Office accessed the enrolment database to identify a
and 2% drank five standard drinks or more per occasion random sample of 13,000 full-time undergraduates aged
once or more a week. 17-25 years. A personally addressed letter from the
There is significant support for the use of the Internet research team was sent to each student, inviting them to
to collect epidemiological data particularly among uni- participate in the survey. The letter explained that they
versity populations [41-45]. Online surveys permit fast would soon receive a hyperlink to the questionnaire in
application and wide accessibility [46,47]. With their an email message, that responses would be confidential
capacity for interactivity, automaticity, respondent anon- and that the research team was independent of the uni-
ymity and cost effectiveness [48-50], ability to facilitate versity administration. Students were offered the oppor-
more honest and thoughtful responses [42,51] and good tunity to win one of 40 AU$100 gift vouchers for
validity and reliability [43,52-57], a carefully conducted participating. After 1 week, a reminder email was sent
online survey may help overcome many of the barriers encouraging completion of the questionnaire to those
associated with collecting epidemiological data [58-60]. who had not yet responded. A second reminder was
Unlike the proportionate cost to attain large sample sent 10 days later.
sizes using traditional modes of survey implementation,
marginal costs are low and therefore they are advanta- Measures
geous for large sample sizes [59,61]. In addition, unique The questionnaire included items on: past alcohol use
features such as complex logic and branching [62] and [71]; current alcohol use [Alcohol Use Disorders Identi-
real-time error checking and automated data entry [63] fication Test (AUDIT) [72]]; peak consumption in the
allow statistical processing to occur in real time [64]. previous 4 weeks [73]; height and weight (in order to
This enables web-survey technology to deliver concur- estimate Blood Alcohol Concentration); secondhand
rent feedback interventions [65]. It may be ethically effects of drinking [22]; attitudes toward nutrition/ingre-
obligatory when surveys identify harmful behaviours dient labelling on alcohol packaging [68]; and tobacco
among respondents to provide feedback. This may be an use [74]. The use of standardised instruments for mea-
efficient option given that provision of immediate feed- suring personal use [Alcohol Use Disorders Identifica-
back in this context has been shown to change beha- tion Test (AUDIT) [72]] and secondhand effects [22]
viour [65,66]. make it comparable to studies carried out in other
As part of a larger efficacy trial of a web-based alcohol countries. The complete wording and layout of all items
screening and brief intervention [65,67], this study esti- can be seen at: http://lamp.health.curtin.edu.au/thrive/
mated the frequency and quantity of alcohol consump- baselinetest.php.
tion, and prevalence of hazardous drinking and
secondhand effects among a large sample of undergrad- Data analysis plan
uate students attending a university in Perth, Western Descriptive statistics were computed for the following:
Australia. demographic data [age (17-19, 20-25 year olds), sex, and
citizenship (Australian and NZ residents, non-residents)]
Methods of respondents and the sample; early or late response to
Participants the survey; the quantity and frequency of alcohol use;
A random sample of 13,000 undergraduate students AUDIT scores; and the number of secondhand effects.
aged 17-25 years, enrolled full-time and studying on Three AUDIT subscale scores were calculated to mea-
campus at a Western Australian university, were invited sure alcohol consumption (AUDIT items 1-3), depen-
to complete a web survey on alcohol consumption, sec- dence (items 4-6) and problems (or adverse
ondhand effects, attitudes toward nutrition/ingredient consequences) (items 7-10) [72,75]. Total AUDIT scores
labeling [68] and tobacco use [69]. Women made up were divided into four ordinal categories: moderate (0-
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7), hazardous (8-15), harmful (16-19), and dependent Therewasahigherrepresentationofwomen,Australian/
(20-40) [72]; and binary categories of hazardous (≥ 8) NZresidentsandthoseaged17-19yearsamongthesur-
and non-hazardous (< 8). veyrespondentscomparedtothesample(p<0.001)(see
The representativeness of responders to the random Table 1). The small differences (less than 5%) between
sample was assessed using chi-squared tests. The asso- early(beforethesecondreminder)andlate(afterthesec-
ciation between participant demographics and being ondreminder)survey respondersinrelationto age, citi-
either early or late responder, or to having an AUDIT zenship andgender were not significant. There was also
score ≥ 8, was assessed using chi-squared tests. T-tests no significant difference in mean AUDIT score between
were used to compare the mean AUDIT measure for earlyandlatesurveyresponders.
the three subscales (alcohol consumption, dependence
and problems) against participant age, sex, and citizen- Consumption characteristics
ship and to compare total AUDIT score between early Ninety percent of respondents had consumed alcohol in
and late responders. the last 12 months, with a mean volume per typical
The association of secondhand effects experience to occasion of 5.1 (SD = 5.0) standard drinks for women
participant demographics and frequency of consuming and 8.7 (SD = 8.6) for men. The National Health and
six or more drinks on one occasion (item three in the Medical Research Council (Australia) thresholds for
AUDIT [72]) was also assessed using chi-squared tests. acute harm (40 g/60 g ethanol for women/men) [76]
The association between frequencies of consuming six were exceeded at least once in the last 4 weeks by 48%
or more drinks (60 g ethanol) on secondhand effects of respondents.
was assessed using multivariable logistic regression after A significantly higher mean AUDIT score (p <
adjusting for gender, age and citizenship. Results are 0.001) was observed for men (8.6; SD = 6.9) than
presented as odds-ratio and associated 99% confidence women (6.5; SD = 5.9); and for Australian/NZ resi-
intervals. dents (8.1; SD = 6.4) than non-residents (3.5; SD =
The associations between age, sex and citizenship and 4.6). There was not a significant difference (p = 0.730)
hazardous drinking were analysed using binary logistic between 17 and 19 year olds (7.7; SD = 6.4) and 20-25
regression. To protect against small effects being consid- year olds (7.0; SD = 6.5). There were significant differ-
ered as being statistically significant due to the large ences in the proportions scoring 8 or higher on the
sample size in the study, p-values of < 0.01 will be con- AUDIT (see Table 2) with 44.5% of 17-19 year olds
sidered as statistically significant. The assumptions versus 39.1% of 20-25 year olds (p < 0.001), 50.6% of
behind the statistical models fitted were assessed to men versus 35.7% of women (p < 0.001) and 47.0% of
ensure validity of results. residents versus 16.5% of non-residents (p < 0.001).
This study received ethical approval from Curtin Uni- Men and Australian/NZ residents had significantly
versity [HR 189/2005] and is registered with the Austra- increased odds (OR: 2.1; 95% CI: 1.9-2.3; OR: 5.2; 95%
lian and New Zealand Clinical Trial Register CI: 4.4-6.2) of being categorised as dependent (AUDIT
[ACTRN12608000104358]. score 20 or over) compared to women and non-
residents.
Results Men had higher odds of drinking at hazardous levels
Of the 13,000 students invited, 7,237 responded (56% compared to women (OR: 2.0; 95% CI: 1.8-2.2). Austra-
responserate)with57%ofthesebeingwomen(n=4123) lian/NZ residents had higher odds compared to non-
and 16.2% non-Australian/NZresidents(n=1172). The residents (OR: 5.1; 95% CI: 4.3-6.0) and the association
mean age of the respondents was 19.5 years (SD = 1.9). with age was non-significant (p = 0.113).
Table 1Demographic comparison ofrespondersvs. studysample andearly vs.late responders
Sample Responders p-value Earlyresponder Lateresponder p-value
N=13000 N=7237 N=4627 N=2610
Demographiccharacteristic %(N) %(N) %(N) %(N)
Age 17-19 48.6(6321) 54.7(3956) <0.001 53.3(2465) 57.1(1491) 0.020
20-25 51.4(6679) 45.3(3281) 46.7(2162) 42.9(1119)
Gender Female 52.4(6811) 57.0(4123) <0.001 57.5(2660) 56.1(1463) 0.024
Male 47.6(6189) 43.0(3114) 42.5(1967) 43.9(1147)
Citizenship Aust/NZ 79.4(10322) 83.8(6065) <0.001 84.5(3909) 82.6(2156) 0.370
Non-Aust/NZ 20.6(2678) 16.2(1172) 15.5(718) 17.4(454)
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Significantly higher mean AUDIT scores (p < 0.001) There was a significant difference based on citizenship
were observed for men and Australian/NZ residents for most secondhand effects with Australian/NZ resi-
compared to women and non-residents in all AUDIT dents more likely than non-residents to have had a ser-
subscales (shown in Table 2). There were significant dif- ious argument or quarrel (13.2% vs. 9.4%; p < 0.001);
ferences in relation to age in the AUDIT Consumption had to baby-sit another student (28.8% vs. 19.0%; p <
subscale with higher mean scores for 17-19 year olds 0.001) or to have experienced an unwanted sexual
compared to 20-24 year olds, but not the other advance (11.9% vs. 5.8%; p < 0.001). Non-residents on
subscales. the other hand were more likely to have had their study-
ing or sleep interrupted (25.0% vs. 20.1%; p < 0.001);
Secondhand effects been a victim of sexual assault (2.1% vs. 0.8%); been a
The 4-week prevalence of secondhand effects is shown victim of another crime on campus (2.2% vs. 0.6%; p <
in Table 3. The most commonly reported effects were 0.001) and were almost twice as likely to have found
having to ‘baby-sit’ inebriated students (27.2%); having vomit in the halls or bathroom of their residence (10.0%
studying or sleep interrupted (20.9%); being insulted or vs. 5.6%; p < 0.001). The odds of experiencing most sec-
humiliated (12.9%); having a serious argument (12.5%); ondhand effects increases with increasing frequency of
or experiencing an unwanted sexual advance (10.9%). consuming six or more drinks (60 g ethanol) on one
Menweremorelikelythanwomentoexperience being occasion, after adjusting for gender, age and citizenship.
‘pushed, hit or otherwise assaulted’ (8.7% vs. 4.8%; p < Being a victim of sexual assault, and being a victim of
0.001)andtohavebeenavictimofanothercrimeoffcam- another crime on and off campus are not significantly
pus (2.8% vs. 1.8%; p = 0.007) while women were more associated with the frequency of this level of alcohol
likelytoexperienceanunwantedsexualadvance(13.8%vs. consumption (see Table 4).
7.1%;p<0.001)andtohavehadto‘baby-sit’ortakecare
ofanotherstudentwhohadtoomuchtodrink(28.8%vs. Discussion
25.1%;p=0.001).Thoseaged17-19yearsweremorelikely This study is the first known prevalence study of stu-
than 20-25 year olds to have had a serious argument dent drinking completed in Australia with undergradu-
(13.7%vs.11.1%;p=0.001);beenassaulted(7.2%vs.5.6%; ate students. The vast majority of students were current
p = 0.005); had to ‘baby-sit’ another student (31.9% vs. drinkers (90%) and there was a high prevalence of
21.6%; p<0.001);had theirstudyingorsleepinterrupted hazardous drinking (48%), with a higher prevalence
(22.1% vs. 19.4%; p = 0.004) or to have experienced among men compared with women, and in Australian/
unwantedsexualadvances(12.1%vs.9.5%;p=0.001). NZ residents compared with non-residents. A relatively
Table 2AUDIT subscalescores andhazardous drinking (AUDIT Score ≥8) by demographic characteristics
AUDITSubscales AUDITScore≥8
%(N)
Demographiccharacteristic AUDITConsumptiona AUDITDependenceb AUDITProblemsc
Mean(SD) Mean(SD) Mean(SD)
Age 17-19 4.8(SD=3.3) 0.8(SD=1.4) 2.1(SD=2.8) 44.5(1762)
20-25 4.3(SD=3.2) 0.8(SD=1.4) 1.9(SD=2.8) 39.1(1284)
p-value <0.001 0.587 0.35 <0.001
Gender Female 4.0(SD=3.0) 0.7(SD=1.2) 1.8(SD=2.6) 35.7(1471)
Male 5.3(SD=3.5) 1.0(SD=1.6) 2.3(SD=3.0) 50.6(1575)
p-value <0.001 <0.001 <0.001 <0.001
Citizenship Aust/NZ 5.0(SD=3.2) 0.9(SD=1.4) 2.3(SD=2.9) 47.0(2853)
Non-Aust/NZ 2.3(SD=2.6) 0.4(SD=1.0) 0.8(SD=1.9) 16.5(193)
p-value <0.001 <0.001 <0.001 <0.001
aConsistsofAUDITitems1-3:Howoftendoyouhaveadrinkcontainingalcohol(0-4);Howmanydrinkscontainingalcoholdoyouhaveonatypicaldaywhen
youaredrinking(0-4);andHowoftendoyouhavesixormoredrinksnooneoccasion(0-4)[Totalrange0-12]
bConsistsofAUDITitems4-6:Howoftenduringthelastyearhaveyoufoundthatyouwerenotabletostopdrinkingonceyouhadstarted(0-4);Howoften
duringthelastyearhaveyoufailedtodowhatyounormallyexpectedfromyoubecauseofdrinking(0-4)andHowoftenduringthelastyearhaveyouneeded
afirstdrinkinthemorningtogetyourselfgoingafteraheavydrinkingsession(0-4)[Totalrange0-12]
cConsistsofAUDITitems7-10:Howoftenduringthelastyearhaveyouhadafeelingofguiltorremorseafterdrinking?(0-4);Howoftenduringthelastyear
haveyoubeenunabletorememberwhathappenedthenightbeforebecauseyouhadbeendrinking?(0-4);Haveyouorsomeoneelsebeeninjuredasaresult
ofyourdrinking?(0-4);Hasarelativeorfriendoradoctororanotherhealthworkerbeenconcernedaboutyourdrinkingorsuggestedyoucutdown?(0-4)
[Totalrange0-16]
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Table 3Secondhand effects experience by demographic characteristics
Secondhandeffects Age Gender Citizenship
17-19 20-25 p- Female Male P- Aust/NZ Non p-
value value value
%(N) %(N) %(N) %(N) %(N) %(N)
Beeninsultedorhumiliated 13.6 12.1 0.070 12.2 13.9 0.027 13.4 10.7 0.015
(535) (396) (500) (431) (207) (124)
Hadaseriousargumentorquarrel 13.7 11.1 0.001 12.6 12.4 0.808 13.2 9.4 <
(541) (362) (518) (385) (794) (109) 0.001
Beenpushed,hitorotherwiseassaulted 7.2(283) 5.6 0.005 4.8(195) 8.7 < 6.7(403) 5.3(61) 0.074
(181) (269) 0.001
Hadyourpropertydamaged 8.3(325) 7.0 0.039 7.2(296) 8.3 0.098 7.5(452) 8.6 0.185
(227) (256) (100)
Hadto‘baby-sit’ortakecareofanotherstudentwhohad 31.9 21.6 < 28.8 25.1 0.001 28.8 19.0 <
drunktoomuch (1256) (706) 0.001 (1184) (778) (1742) (220) 0.001
Foundvomitinthehallsorbathroomofyourresidence 6.5(257) 6.0 0.364 5.6(231) 7.2 0.008 5.6(337) 10.0 <
(196) (222) (116) 0.001
Hadyourstudyingorsleepinterrupted 22.1 19.4 0.004 21.5 20.1 0.128 20.1 25.0 <
(872) (633) (884) (621) (1215) (290) 0.001
Experiencedunwantedsexualadvances 12.1 9.5 0.001 13.8 7.1 < 11.9 5.8 <
(474) (310) (565) (219) 0.001 (717) (784) 0.001
Beenavictimofsexualassault 0.9(35) 1.1(36) 0.358 0.9(36) 1.1(35) 0.289 0.8(47) 2.1(24) <
0.001
Beenavictimofanothercrimeoncampus 0.8(30) 1.1(35) 0.165 0.8(34) 1.0(31) 0.448 0.6(39) 2.2(26) <
0.001
Beenavictimofanothercrimeoffcampus 2.4(93) 2.0(66) 0.328 1.8(74) 2.8(85) 0.007 2.1(125) 2.9(34) 0.067
large proportion of students’ experienced secondhand Zealand studies incorporated pre-notification, persona-
effects from other people’s drinking. lised emails and follow-up notices. However, the earlier
The survey had a response rate of 56%, which is New Zealand study used up to nine follow-up contacts
higher than large college surveys in the early 2000s in (compared to five in this study) including a telephone
the United States (52%) [10], but lower than online sur- reminder, which may explain some of the difference.
veys in New Zealand using similar procedures (63-82%) Follow-up notices are likely to increase response rates
[13,59]. Higher response rates for online surveys have though larger numbers of notices may not appreciably
been linked to pre-notification, personalised contacts affect response if the contact develops resistance to par-
and follow up reminders [77]. Both this and the New ticipation [78]. It is also possible that the novelty factor
Table 4Effects* offrequency ofconsuming six or more drinks(60 gethanol) onsecondhand effects
Frequencyofconsumingsixormoredrinks(cfNever)
Secondhandeffect Lessthanmonthly 2-4timesamonth >2timesaweek
OR(99%CI) OR(99%CI) OR(99%CI)
Beeninsultedorhumiliated 1.39(1.03-1.90) 1.88(1.35-2.62) 2.57(1.88-3.51)
Hadaseriousargumentorquarrel 1.95(1.36-2.79) 3.15(2.16-4.60) 5.97(4.19-8.52)
Beenpushed,hitorotherwiseassaulted 1.18(0.76-1.85) 1.54(0.95-2.49) 3.02(1.96-4.64)
Hadyourpropertydamaged 1.66(1.11-2.47) 2.23(1.45-3.44) 2.68(1.77-4.05)
Hadto‘baby-sit’ortakecareofanotherstudentwhohaddrunktoomuch 1.96(1.56-2.47) 2.81(2.18-3.62) 3.66(2.87-4.66)
Foundvomitinthehallsorbathroomofyourresidence 1.51(0.97-2.34) 2.50(1.56-4.01) 3.58(2.29-5.60)
Hadyourstudyingorsleepinterrupted 1.44(1.12-1.86) 2.32(1.77-3.06) 3.26(2.51-4.23)
Experiencedunwantedsexualadvances 2.11(1.46-3.05) 2.86(1.93-4.24) 5.38(3.72-7.79)
Beenavictimofsexualassault(thisincludesdaterape) 0.79(0.31-1.97) 0.88(0.29-2.69) 1.62(0.63-4.17)
Beenavictimofanothercrimeoncampus 0.65(0.24-1.76) 0.77(0.22-2.63) 1.56(0.57-4.26)
Beenavictimofanothercrimeoffcampus 0.96(0.48-1.89) 1.33(0.63-2.79) 1.74(0.88-3.45)
*Resultsarepresentedasodds-ratioandassociated99%confidenceintervalsafteradjustingforgender,ageandcitizenshipinmultivariablelogisticregression
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of online surveys may have reduced in the years since availability and promotion of alcohol on and around
the New Zealand studies and factors such as prolifera- campus [22,83].
tion of junk mail, bombardment with online question-
naires and demands on student time may also have Conclusions
impacted on response rates [47]. Hazardous alcohol use among undergraduate students
The level of alcohol consumption reported in this remains an issue of concern although there is a lack
study is less than that reported in New Zealand, for of prevalence data on this population’s alcohol con-
both men and women [13]. Although gender conver- sumption in Australia. Some alcohol related harms
gence in drinking has been reported elsewhere such as sexual assault are only detected with large
[10-12,79] and a similar trend appears to be occurring population samples. Web-based surveys are a cost-
in Australia [80], this study shows a large discrepancy effective approach for measuring health behaviours in
between men and women. However, there are no older student populations, with a relatively high response
prevalence studies from which to assess attenuation rate. It is suggested that this research is replicated in
trends. other Australian universities, particularly residential
Large numbers of people were affected by other stu- campuses. Such surveys are required to develop trend
dents’ drinking. Of particular note was the 0.9% (n = data which will facilitate intervention program
36) of women and 1.1% (n = 35) of men who reported development.
being a victim of sexual assault in the previous 4 weeks.
This is slightly higher than that found in a New Zealand
Acknowledgements
sample [81] though with overlapping confidence inter-
ThisworkwassupportedbytheWesternAustralianHealthPromotion
vals. While the New Zealand sample was limited to Foundation(Healthway)[15166].TheauthorsgratefullyacknowledgeDeputy
those who had consumed alcohol in the previous 4 ViceChancellorJanedenHollander,AliceTsangandNerissaWood,other
universityadministrationstaffandthestudyparticipantsfortheirsupportof
weeks, our sample included non-heavy drinkers and
theresearch.TheCentreforBehaviouralResearchinCancerControlis
may highlight the impact that hazardous alcohol con- supportedbyCancerCouncilWA.
sumption can have on all students. Extrapolated to the
Authordetails
entire student population this may mean approximately
1WesternAustralianCentreforHealthPromotionResearch,CurtinHealth
140 students at this university experience sexual assault InnovationResearchInstitute,CurtinUniversity,KentStreet,Bentley,Australia.
in this context each month. 2CentreforBehaviouralResearchinCancerControl,CurtinUniversity,10
SelbyStreet,ShentonPark,Subiaco,Australia.3NationalDrugInstitute,Curtin
A limitation of this study was the imprecision in the
University,10SelbyStreet,ShentonPark,Subiaco,Australia.4CurtinHealth
specificity of crimes listed in the secondhand effects InnovationResearchInstitute,CurtinUniversity,KentStreet,Bentley,Australia.
questions and the reliance on respondents to attribute 5SchoolofMedicineandPublicHealth,UniversityofNewcastle,University
Drive,Callaghan,Australia.6InjuryPreventionResearchUnit,Departmentof
responsibility for the effect. As only yes or no responses
PreventiveandSocialMedicine,UniversityofOtago,18FrederickStreet,
were available, multiple experiences of the same effect Dunedin,NewZealand.7SchoolofPublicHealth,CurtinUniversity,Kent
were not captured and therefore the prevalence of these Street,Bentley,Australia.
effects may be underestimated. Given the high preva- Authors’contributions
lence of some of these effects further research in this JHcarriedoutthestudyanddraftedthemanuscript.PH,AM,KKandBM
area is warranted. Our estimates may be biased by selec- conceivedofthestudyandparticipatedinitsdesignandcoordination.SD
participatedinthedesignofthestudyandperformedthestatisticalanalysis.
tive non-response but conversely computerised ques-
PH,BM,KKandAMhelpedtodraftthemanuscript.Allauthorsreadand
tionnaires are known to increase reporting of high-risk approvedthefinalmanuscript.
behaviour [42,51].
Competinginterests
Universities with large on-campus resident popula-
Theauthorsdeclarethattheyhavenocompetinginterests.
tions may have higher levels of drinking than commuter
universities due to students’ greater proximity to peers Received:13September2011 Accepted:16January2012
Published:16January2012
[82]. As this study is based on a single commuter uni-
versity and has a high proportion of students on tem-
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