binge drinking

Binge Drinking, Cognitive Performance and Mood in aPopulation of Young Social Drinkers

Julia M. Townshend and Theodora Duka

Background: Binge drinking may lead to brain damage and have implications for the development ofalcohol dependence. The aims of the present study were to determine individual characteristics as well asto compare mood states and cognitive function between binge and nonbinge drinkers and thus furthervalidate the new tool used to identify these populations among social drinkers.

Methods: The lowest and the highest 33.3% from a database of 245 social drinkers binge scores derivedfrom the Alcohol Use Questionnaire (AUQ) were used as cutoff points to identify nonbinge drinkers andbinge drinkers in a further population of 100 young healthy volunteers. Personality characteristics, expec-tations of the effects of alcohol and current mood were evaluated. Cognitive performance was tested withaMatching to Sample Visual Search task (MTS) and a SpatialWorkingMemory task (SWM) both from theCANTAB battery, and a Vigilance task from the Gordon Diagnostic System.

Results: The binge drinkers had less positive mood than the nonbinge drinkers. In the MTS choice time onan 8-pattern condition and movement time on an 8- and 4-pattern condition was found to be faster in the bingedrinkers compared to nonbinge drinkers. A gender by binge drinking interaction in the SWM and the GordonDiagnostic System task revealed that female binge drinkers were worse on both these tasks than the femalenonbinge drinkers.

Conclusions: These results confirm previous findings in binge drinkers and suggest that in a nondepen-dent alcohol-drinking group, differences can be seen in mood and cognitive performance between thosethat binge drink and those that do not.

Key Words: Alcohol Use Questionnaire (AUQ), Impulsivity, Repeated Withdrawal, Gender, FrontalLobe.

BINGE DRINKING IN young people is on the increasein Britain (Morgan et al., 1999), the United States(Naimi et al., 2003) and increasingly in developing coun-tries throughout the world (Parry et al., 2002). In a studentpopulation, binge drinking has been shown to predict thefrequency with which alcohol related problems are experi-enced (Wechsler et al., 1994) and Hunt (1993) has sug-gested that binge drinkers may be more at risk of develop-ing brain damage. Binge ethanol exposure in adult rats hasbeen shown to cause necrotic neurodegeneration after aslittle as 2 days of exposure (Obernier et al., 2002a). Inaddition Crews and colleagues (Crews et al., 2000) havefound that young adolescent rats show differential patternsof brain damage after binge ethanol treatment compared toadult rats. The associated frontal cortical olfactory regionswere damaged only in the adolescent rats. Further animalstudies have provided evidence of increased brain damage

after multiple withdrawals from alcohol or when repeatedlyhigh amounts of alcohol in the brain are followed by peri-ods of abstinence (i.e., binge drinking; Crews et al., 2001;Veatch and Gonzalez, 1999). Imaging studies on adoles-cents with alcohol use disorders have also provided evi-dence for brain abnormalities associated with the age atonset of the alcohol use disorder (De Bellis et al., 2000).It has been proposed that number of drinks in a row

differentiates binge drinkers from nonbinge drinkers(Wechsler and Austin, 1998), and while this may be thecase it also means that binge drinkers and nonbinge drink-ers will almost certainly consume different quantities ofalcohol. We have used a score (binge drinking score)derived from items from an Alcohol Use Questionnaire(Mehrabian and Russell, 1978) referring to drinking behav-ior and not to consumption and have compared it with themeasurement drinks in a row as described by Wechslerand Austin (Wechsler and Austin, 1998). We have shownthat, unlike the measurement drinks in a row, the bingedrinking score was unrelated to weekly alcohol consump-tion (Townshend and Duka, 2002). Based on the proposalthat repeated withdrawal from alcohol may contribute tothe development of addiction (withdrawal sensitizationtheory of addiction, Stephens, 1995) a binge scorefounded on patterns of drinking rather than quantities of

From Laboratory of Experimental Psychology, University of Sussex,Falmer, Brighton.

Received for publication March 15, 2004; accepted December 13, 2004.This work was supported by MRC Grant No. G9806260.Reprint requests: Dr. Theodora Duka, Psychology, University of Sussex,

Falmer, Brighton BN1 9QG; Fax: 44 1273 678058; E-mail: [email protected]

Copyright 2005 by the Research Society on Alcoholism.

DOI: 10.1097/01.ALC.0000156453.05028.F5

0145-6008/05/2903-0317$03.00/0ALCOHOLISM: CLINICAL AND EXPERIMENTAL RESEARCH

Vol. 29, No. 3March 2005

Alcohol Clin Exp Res, Vol 29, No 3, 2005: pp 317325 317

alcohol consumed may be a better predictor of futurealcohol dependency problems.A characteristic marker of binge drinking behavior is the

consumption of large amounts of alcohol within a limitedtime period followed by a period of abstinence, as opposedto regular drinking in which a person might consume sim-ilar weekly amounts of alcohol but without the extremes ofalcohol intoxication. Thus binge drinking can be consideredanalogous to repeated withdrawal from alcohol, a behaviorthat has been shown to affect both cognitive and emotionalresponding in alcoholic inpatients (Duka et al., 2004; Dukaet al., 2002, 2003; Townshend and Duka, 2003). Such anidea is based on extrapolation from animal studies thathave shown clearly binges of alcohol, like multiple with-drawals from alcohol, produce brain damage and cognitiveimpairments (Duka et al., 2004; Obernier et al., 2002b;Ripley et al., 2003; Stephens et al., 2001).In alcoholics several morphological abnormalities in the

frontal lobe system have been reported (for a review, seeMoselhy et al., 2001), and we have recently found thatalcoholic patients with two or more previous experiences ofmedically supervised detoxifications from alcohol weremore impaired than patients with a single, or no previousexperience of detoxification in tasks measuring frontal lobefunction. Given these results it is possible that binge drink-ing behavior in young healthy adults might also affectperformance on such tasks. We have therefore included atask that measures the ability to disinhibit a prepotentresponse (the Vigilance task in the Gordon DiagnosticSystem). In a previous study that looked at the effects ofalcohol on frontal lobe tasks we have found in a posthocanalysis that binge drinkers made more between searcherrors and had a worse strategy in a task that measuresspatial working memory compared to nonbinge drinkers.To replicate these findings in a prospective study we havealso added the Spatial Working Memory task from theCANTAB battery in the present study. In addition we haveincluded a measure of visual search speed that can revealimpulsivity, a behavioral trait often cited as an importantbehavioral predictor of excessive alcohol consumption.Such a measure will provide information about a cognitiveimpairment that might have preceded the binge drinkingbehavior. However, we are aware that unless a prospectivestudy is carried out with adolescents before and after theyhave indulged into binge drinking behavior, a clear distinc-tion of what cognitive impairment preceded and what fol-lowed as a result of binge drinking is not possible.Traditionally more of a male activity, binge drinking is

now increasing in females. In a recent study, reported casesof blackouts were as high in females as in males leading toincreasingly risky behavior in terms of personal safety(White et al., 2002). However whether the consequences ofbinge drinking behavior are different between males andfemales is not yet known. Consequently, in this study, wewill be looking at gender differences in performance onimpulsivity and frontal lobe tasks.

The grouping of binge drinkers in this study was based ona database of 245 Alcohol Use Questionnaires (AUQ;Mehrabian and Russell, 1978) completed by volunteers. Abinge drinking score was calculated for each individualusing the three questions from the AUQ evaluating drink-ing patterns (drinks per hour; times drunk within the last 6months; % of being drunk when drinking) and excludingweekly alcohol consumption. The lowest and the highest33.3% were grouped as nonbinge drinkers and binge drink-ers respectively. The maximum score of the nonbingedrinking group and the minimum score of the binge-drinking group from the 245 social drinkers were used ascutoff points to identify binge drinkers and nonbinge drink-ers in this current study population. As the binge drinkingscore is based on patterns of drinking rather than quantityconsumed, we did not find differences between the bingedrinking scores of males and females in our sample of socialdrinkers. Consequently, the same cutoff points were usedfor male and female volunteers.There is evidence that greater positive alcohol expectan-

cies are associated with binge drinking episodes (Blume etal., 2003). Also peer influence can have a strong impact ondrinking behavior. It has previously been shown that siblingsmoking was one of the strongest predictors of smokingbehavior in adolescents (Wilkinson and Abraham, 2004).Personality (temperament) traits like high Harm Avoid-ance, as measured by the Temperament and CharacterInventory (TCI; Cloninger et al., 1994) have been associ-ated with binge drinking (Gilligan et al., 1987). On theother hand aspects of impulsivity and an early age of start-ing drinking have been associated with high Novelty Seek-ing also measured by the TCI. We have therefore includedan Alcohol Outcome Expectancy Questionnaire and theTCI in the present study. These latter measures thereforewill provide information about trait characteristics whichmay predispose to binge drinking. In a previous study wehave also found that alcoholic patients who have experi-enced two or more detoxifications presented with highratings of feelings of anger compared with their counter-parts with no previous detoxifications (Duka et al., 2002).Thus the present study was designed to look at the rela-tionship between patterns of drinking behavior, cognitiveperformance, mood, expectancies from alcohol, and per-sonality characteristics. The role of gender was alsoexamined.

MATERIALS AND METHODS

Participants

One hundred young, healthy volunteers (50 male and 50 female)moderate to heavy social drinkers between the ages of 18 and 30 (mean20.9, SD 2.6) answered an advertisement for social drinkers to take part ina study looking at the relationship between performance on cognitive tasksand drinking patterns. Volunteers with current symptoms or a history ofmental illness, neurological diseases, drug or alcohol dependence were notincluded in the study. Participants had been instructed to abstain from theuse of illicit recreational drugs for at least 1 week prior to the experiment,

318 TOWNSHEND AND DUKA

from the use of sleeping tablets or hay fever medication for at least 48 hr,and from the use of alcohol for at least 12 hr prior to the experiment. Itwas discovered at the data input stage that one female had participatedtwice in the study so her second data set was discarded leaving 99 partic-ipants. Those who drank 6 units or less per week [3 glasses of wine or 2.5pints lager (3 drinks)] were excluded, as by any definition they could nothave been binge drinkers (i.e., even if they had the drinks in a row therewould have been less than 4 drinks in a row). Two females were lost by thisexclusion leaving 50 male participants and 47 female participants in total.All except 4 spoke English as their first language. The National AdultReading Test (NART) scores from these 4, and 1 dyslexic volunteer werediscarded. The study was approved by the University of Sussex EthicalCommittee and all volunteers gave their informed consent and were paidfor their time at a rate of approximately 5 per hour.

Demographics

Population characteristics were based on information obtained fromthe participants and included smoking information and the quantity andtime of their most recent alcoholic drink and caffeinated product.

Questionnaires

I. Alcohol and Drug UseAlcohol Use Questionnaire (AUQ). A quantity-frequency, beverage-

specific index of alcohol consumption for the previous 6 months wasobtained using a revised version of the Alcohol Use Questionnaire (AUQ;Mehrabian and Russell, 1978). The revised questions, by determiningbrands of liquor, allow for actual alcoholic content (percentage volume) ofdrinks to be assessed. Participants were asked to estimate the number ofdrinking days, the usual quantity consumed and the pattern of drinking.We have previously demonstrated that the AUQ is a reliable measure ofdrinking quantity and drinking pattern (Townshend and Duka, 2000).

Binge drinking score. A binge drinking score was calculated for allparticipants on the basis of the information given in items 10, 11, and 12 of theAUQ [Speed of drinking (average drinks per hour); number of times beingdrunk in the previous 6 months; percentage of times getting drunk whendrinking (average)]. The binge score is calculated in the same way as theAUQ score is derived but without the items 1 9 that refer to quantity andtype of alcohol intake: [4 (Item 10) Item 11 0.2 (Item 12);Mehrabian and Russell, 1978]. This score gives a picture of the drinkingpatterns of the participants rather than just a measure of alcohol intake.Participants who have a high binge score and drink frequently but irregu-larly may have a similar intake of alcohol to those with a lower binge scorewho drink on a regular basis. The cutoff points of the binge score forseparating binge drinkers from nonbinge drinkers was binge score 16 fornon binge drinkers and binge score 24 for binge drinkers. Subjects withscores in between were considered not classifiable.

Alcohol Expectancy Questionnaire (AEQ). Based on the ComprehensiveEffects of Alcohol Questionnaire (CEOA; Fromme et al., 1993), the AEQis a 38-item questionnaire, which assesses positive and negative expectedeffects of alcohol consumption. There are seven expectancy factors, fourpositive (sociability, tension reduction, liquid courage and sexuality), andthree negative (cognitive and behavioral impairments, risk and aggression,and negative self perception).

Structured Interview Questionnaire revised (SIQ-R). The StructuredInterview Questionnaire has previously been used to evaluate the drinkinghabits of an alcoholic population (Duka et al., 2002). A revised version wasconstructed for the healthy volunteers in the current study that askedabout age of starting drinking, family history of alcoholism and siblingalcohol / drug use. A family history score was derived by giving a score of2 points for each first degree relative and 1 point for each second degreerelative. Participants were asked to estimate as best they could theirsiblings weekly alcohol and/or drug use. For the analysis the amount ofalcohol or drug use was taken for the sibling (same or opposite sex) ofnearest age to the participant provided they were more than 16 years old.

Drug Use Questionnaire. This questionnaire asks for duration of use,time since last use, how often used and dose per session for all the main

drug categories. For the purposes of this study as a rough guide to druguse, participants were given a score in which 0 no drug use; 1 occasional use of cannabis/hash or marijuana; 2 regular use of cannabis/hash or marijuana (at least once a week); 3 use of ecstasy and/or otherdrugs.

II. Trait MeasurementsThe Temperament and Character Inventory (TCI) (Cloninger et al.,

1994) is a 240-item personality questionnaire designed to assess individualdifferences on 4 measures of temperament and 3 measures of character.The temperament measures, which represent hereditary traits, are noveltyseeking, harm avoidance, reward dependence, and persistence. The char-acter measures, which represent acquired traits, are self-directedness,cooperativeness, and self-transcendence. The TCI was always given at theend of the testing session.

III. Current Mood MeasuresProfile of Mood States (POMS;McNair et al., 1971). The POMS consists

of 72 mood related adjectives which participants are instructed to rate ona 5-point scale ranging from not at all (0) to extremely (4). Throughthe process of factor analysis 8-factors have been established: Anxiety,Fatigue, Depression, Anger, Vigor, Confusion, Friendliness, and Elation.In addition, two further composite factors can be derived as follows:Arousal (Anxiety Vigor) (Fatigue Confusion), and PositiveMood Elation Depression (de Wit and Doty, 1994). All 10 factorswere evaluated for this study.

The questionnaires and the Vigilance task for adults from the GordonDiagnostic System (see below) were given in random order before theother cognitive measures.

Cognitive MeasuresNational Adult Reading Test (NART: Nelson, 1991). The participants

were given the NART to provide an estimate of the participants verbal IQperformance.

Matching to Sample Visual Search task. CANTAB (Cambridge CognitionLtd). This sub test of the CANTAB is a speed/accuracy trade off task thattests the subjects ability to match visual samples and measures their choiceand movement time. The sample stimulus appears in the center of the screenand is an abstract pattern composed of 4 colored elements. After a brief delay1, 2, 4, or 8 similar patterns appear around the edge of the screen. Theincorrect patterns are composed of juggled elements of the sample patternand only one of themmatches the one in the center of the screen. The subjectmust hold down a press pad to obtain the sample pattern and the matchingstimuli. When a choice has been made the subject releases the pad andidentifies the matching pattern by touching it. The matching to sample visualsearch task resembles the Matching Familiar Figures test first developed byKagan (1965) who used it to measure reflection the amount of time spentthinking about a response before making a decision, later developed furtherby Cairns and Cammock (1978); it has been used to measure impulsivitytaking into account both time of response and number of errors made(Messer and Brodzinsky, 1981). The Matching to Sample Visual Search taskgives two reaction time measures, choice time on the basis of the release ofthe press pad, and movement time from the release of the pad to the touchof the screen. Errors are also recorded. Results are given only for the 4 and8-pattern condition (conditions 1 and 2 are very easy and performance runsat ceiling with young adults).

Spatial Working Memory. CANTAB (Cambridge Cognition Ltd). Thissubtest of CANTAB is a self ordered search task that requires participantsto search through a spatial array of boxes to collect tokens hidden inside.At any one time there will be one single token hidden. The key instructionis that once a blue token has been found inside a box, then that box willnever be used again to hide a token. There are trials of 3, 4, 6, and 8 boxes.There are two types of errors in this task, within- and between-searcherrors. A between-search error occurs when a participant returns to abox in which a token has previously been found and a within searcherror occurs when a participant returns to a box within the same search.Results refer to between-search errors and are given only for the 6 and8 boxes condition as in the 3 and 4 box conditions error rates are very low.A further variable was the strategy score, which indicates the particularsequence that participants follow in each session. A high score indicates

BINGE DRINKING, MOOD AND COGNITION 319

poor strategy. The two CANTAB tasks were presented in counter bal-anced order.

The Vigilance Task for Adults from the Gordon Diagnostic System (Gor-don et al., 1986). In this task participants are required to press a button ona purpose-built electronic machine, which briefly displays 3 digits in fast,random succession on a 3 column, LED display. Participants are requiredto concentrate only on the digit in the middle column of the display, andare instructed to press the blue button every time a 1 is followed by 9(1 being the alerting stimulus and 9 being the target stimulus). The taskmeasures the subjects ability to inhibit responding under conditions thatmake demands for sustained attention and impulse control. The mainvariable in this task is errors of commission. Errors of commission aretargetrelated errors recorded when a response is made to the targetstimulus 9 or to the alerting stimulus 1 when they are not in thesequence 1 / 9/.

Target VariablesFor the purpose of this paper, the target variables are the reaction time,

movement time and number of errors made in the Matching to SampleVisual Search task; the between search errors and strategy score in theSpatial Working Memory task; errors of commission in the Vigilance taskfor adults from the Gordon Diagnostic System; self-reported currentmood, alcohol expectancies and personality. All other measures representcorrelates.

Statistical MethodsFor the cognitive tasks and the POMS composite factors arousal and

positive mood, initial analyses were performed using Univariate analysisor mixed ANOVAs (task condition was the within factor) with group (2levels: binge drinkers and nonbinge drinkers) and gender (2 levels) as thebetween subject factors. For the Alcohol Expectancy and the TCI ques-tionnaire ratings Multivariate analyses were performed with the factorsfrom the questionnaires as the dependent variables and with group (2levels: binge drinkers and nonbinge drinkers) and gender (2 levels) asfixed factors. Where an interaction was found between binge drinkinggroup and gender, further analysis was performed on males and femalesseparately. Where there was no interaction gender was not exploredfurther, as binge drinking was the behavior of interest in this study.Independent t-tests were performed to analyze differences in demo-graphic characteristics between nonbinge and binge drinkers and betweenmales and females within binge or nonbinge drinkers group. Betweengroup differences (units per week, age of starting to drink and drug usescore) were entered as covariates where binge drinkers performed differ-

ently on cognitive tasks. All procedures were carried out using SPSSsoftware version 11.5.

RESULTS

Group Demographics

Table 1 shows the demographic data for the drinkingpattern groups and for males and females within thegroups. There are an unequal number of males and femalesin the binge drinking and nonbinge drinking groups, whichmay reflect real world population ratios. Alcohol units andage of starting drinking were different between the groupswith the binge drinkers drinking more alcohol units perweek [t(70) 3.5; p 0.01) and starting earlier regulardrinking [t(70) 2.84; p 0.05]. There was also a differ-ence between bingers and nonbingers with respect to druguse score with binge drinkers having higher drug use scorethan nonbinge drinkers [t(70) 2.358; p 0.021). Therewere no differences between males and females for any ofthe demographic characteristics in the nonbinge drinkergroup [ts(32) 1.8]. Only a marginal difference betweenmales and females in the binge group was found with malesconsuming more units per week [t(36) 2.01; p 0.052].

SIQ

There were 22 nonbinge drinkers and 24 binge drinkerswho had siblings over the age of 16 years. There weredifferences between groups [t(44) 2.1; p 0.05) in theamount of reported alcohol use by their nearest aged sib-lings [(mean SD), nonbinge drinkers: 11.7 10.0; bingedrinkers: 19.5 13.9] but not in drug use or in familyhistory of alcoholism (data not shown). A Pearson corre-lation using the population with siblings (n 60) from thetotal pool (n 97) found that the amount of sibling alcohol

Table 1. Demographic Data for Non-Binge and Binge Drinkers and for Males and Females

Group characteristics

Non-binge drinkers Binge drinkers

Total Males Females Total Males Females

Number 34 13 21 38 23 15Age 20.9 20.4 21.2 20.9 20.9 21.1

(2.5) (1.9) (2.8) (2.6) (2.9) (2.1)Alcohol units per weeka 20.5 22.2 18.7 33.3 38.2 26.0

(11.9)b (11.7) (12.1) (19.0) (21.3) (11.9)Binge drinking score 10.6 11.2 10.3 40.4 37.1 45.5

(3.4)b (2.8) (3.8) (16.1) (13.8) (18.4)Estimated IQ (NART) 107.9 108.5 107.6 107.6 108.6 106.1

(7.9) (7.2) (8.4) (5.7) (5.1) (6.4)Age of starting drinking 15.3 16.0 14.9 14.4 14.8 14.0

(1.6)c (1.9) (1.3) (1.3) (1.3) (1.4)Drug use score 0.94 0.62 1.14 1.53 1.48 1.60

(1.04)c (0.87) (1.1) (1.06) (1.17) (0.91)Cigarette smokers (n) 10 4 6 11 5 6Occasional use of cannabis (n) 13 5 8 13 6 7Regular use of cannabis (n) 2 0 2 9 5 4XTC and/or other drug use (n) 5 1 4 9 6 3

Data are presented as mean (SD).a One unit is 8 g of alcohol.b p 0.005 compared to binge drinkers.c p 0.05.


use was most closely related to the participants bingedrinking score (Fig. 1; Pearson R 0.358, p 0.01). APearson correlation using only the population with siblingsamong the binge drinkers and nonbinge drinkers group (n 46) found also that the amount of sibling alcohol use wasmost closely related to the participants binge drinkingscore (Pearson R 0.422; p 0.01).

Alcohol Expectancy Questionnaire and TCI

The 7 factor ratings from the Alcohol Expectancy Ques-tionnaire and from the TCI are presented in table 2. Mul-tivariate analysis on the 7 factors of each questionnaireseparately and with the fixed factors group and genderfound no significant interactions or main effects (F7,62 2.0).

Profile of Mood States

Table 3 shows means and SEM of arousal and posi-tive mood scores in binge and nonbinge drinkers. Univar-iate analysis for positive mood found a significant groupeffect (F1,71 4.2; p 0.045) with binge drinkers beinglower on positive mood. No other effects or interactions

were found. There was no relationship between currentpositive mood and time of last drink indicating that theirlow current mood was not due to withdrawal from alcoholin the binge drinkers.

Cognitive Measures

CANTAB; Matching to Sample Visual Search. Due totechnical reasons values from 3 participants in the non-binge drinkers and 4 participants in the binge drinkersgroup were missing. A mixed ANOVA on choice time (4and 8 pattern choice) in the MTS task found no effect ofgender but a group (2 levels; binge drinkers and nonbingedrinkers) pattern (2 levels: 4 and 8 pattern condition)interaction (F1, 61 4.4, p 0.05). Further investigationshowed that the binge drinkers were faster in their choicetime in the 8 pattern, but not in the 4-pattern condition(Fig. 2a). Mixed ANOVA on movement time (4 and 8pattern condition) revealed a main effect of group (F1,615.3; p 0.05) with binge drinkers being overall faster inmovement time than nonbinge drinkers (Fig. 2b). Therewere no differences in the number of errors made. None ofthe covariates entered (units per week, age of starting todrink and drug use score) affected the group results.CANTAB; Spatial Working Memory. Due to technical

reasons values from 2 participants in the nonbinge drinkersgroup were missing. A mixed ANOVA on between trialerrors (6 and 8 boxes condition) found a gender by bingedrinking group interaction (F1,66 10.26; p 0.005).Consequently the population was split by gender and malesand females examined separately. A further mixedANOVA on errors for males and females separately, founda group effect (F1,32 6.3; p 0.05) only in femalesindicating that female binge drinkers (n 15) made moreerrors than female nonbinge drinkers (n 19; Fig. 3). AUnivariate analysis on strategy scores showed no interac-tions or main effects. None of the covariates entered (unitsper week, age of starting to drink and drug use score)affected the group results.Gordon Diagnostic System; Vigilance task for adults. Due

to technical reasons values from 2 participants in the non-binge drinkers and 1 subject in the binge drinkers groupwere missing. A Univariate Analysis with errors of commis-sion as the dependent variable found a group by genderinteraction (F1, 68 5.3; p 0.05) so the population wassplit by gender for further analysis. A further UnivariateAnalysis on errors of commission for males and femalesseparately, found a group effect (F 1,33 4.6; p 0.05)only in females indicating that female binge drinkers (n

Fig. 1. The relationship between binge drinking score of all participants withnearest age siblings (over 16 years old) and estimated quantity of sibling alcoholconsumption.

Table 2. Scores on the Alcohol Expectancy Questionnaire and the TCI forNon-Binge Drinkers and Binge Drinkers, Mean (SEM)

Non-binge drinkers(n 34)

Binge drinkers(n 38)

Alcohol expectancy factorsSociability 26.1 (.52); range 2031 26.6 (.56); range 1832Tension reduction 7.4 (.25); range 410 7.5 (.28); range 411Liquid courage 12.5 (.38); range 917 13.1 (.38); range 818Sexuality 9.7 (.34); range 514 9.9 (.39); range 514Cognitive and behavioral

impairment23.7 (.87); range 1436 24.7 (.56); range 1731

Risk and aggression 12.0 (.50); range 719 12.8 (.43); range 618Negative self perception 7.2 (.43); range 415 7.9 (.40); range 415

TCI factorsNovelty seeking 21.5 (1.03); range 834 24.0 (1.07); range 935Harm avoidance 15.7 (1.23); range 530 14.3 (1.44); range 130Reward dependence 16.6 (.67); range 924 15.6 (.66); range 822Persistence 5.26 (.35); range 18 4.5 (.38); range 18Self directedness 26.6 (1.36); range 740 24.2 (1.47); range 540Co-cooperativeness 33.0 (1.16); range 941 31.0 (1.18); range 1341Self-transcendence 15.5 (1.22); range 030 13.6 (1.06); range 529

Table 3. Profile of Mood States, Arousal and Positive Mood Composite Scorein the Non-Binge and Binge Drinkers

POMS factors Non-binge drinkers (n 34) Binge drinkers (n 38)

Arousal 0.05 (1.53); range 2.402.69 0.55 (1.53); range 3.012.34Positive Mooda 1.00 (0.81); range 0.632.33 0.54 (1.17); range 2.472.33

Mean (SEM).a p 0.045 (univariate analysis of variance, group effect).


15) made more errors than female nonbinge drinkers (n 19; Fig. 4). When age of starting drinking was entered as acovariate the group difference became marginal (F 1,33 4.0; p 0.06). No effect of the other covariates (units perweek and drug use score) was found.

DISCUSSION

The present study set out to examine the validity of a newmethod of identifying binge drinking in young, healthysocial drinkers, and to look at differences in cognitiveperformance and mood between groups with differentdrinking patterns. Using a questionnaire method that asksabout drinking behavior rather then quantity of alcoholconsumed, we have been able to show differences in cog-

nitive performance between groups of young healthy adultswho are similar in aspects other than their drinking behav-ior. However it should be noted that there is an importantlimitation to the study as the differentiation of binge drink-ers and nonbinge drinkers was based on information pro-vided by the participants themselves rather than objectivemeasures, although we have previously found that informa-tion about drinking behavior collected from the AUQ anddrinking behavior recorded daily in a diary were veryclosely related (Townshend and Duka, 2002).The groups were well matched for age and IQ but the

binge drinkers started drinking earlier than the nonbingedrinkers. They also consumed more alcohol and used moredrugs than the nonbinge drinkers, and drug use and bingedrinking scores were positively related in the whole popu-

Fig. 3. Between search errors (total errors 6 and 8 boxes, mean SEM)in the CANTAB Spatial Working Memory task, for male and female bingeand nonbinge drinkers. *p 0.05 compared to female nonbinge drinkersand male binge drinkers.

Fig. 2. Choice time (a) and movement time (b) for the 4- and 8-pattern condition (ms; mean SEM) in the CANTAB Matching to Sample Visual Search task for bingeand nonbinge drinkers. *p 0.05 compared to nonbinge drinkers.


lation (data not shown). The concurrent use of alcohol anddrugs has been previously reported in several studies [e.g.,(Sutherland and Willner, 1998)] and has been suggested tobe due to one of two hypotheses, either to alcohol acting asa gateway to illicit drugs (Kandel et al., 1992), or as part ofa general behavior pattern in which alcohol use has a lowerthreshold to other drugs and is easier to obtain (Jessor,1987). The results from this current study do not distinguishbetween these two hypotheses but provide further evidenceof a relationship between increased frequency of drug useand increased frequency of drunkenness.Although neither the units of alcohol drunk per week nor

the higher incidence of drug use found in binge drinkerscompared to nonbinge drinkers was found to relate to theimpairments seen in performance on cognitive tasks amongbinge drinkers, a contribution of these factors cannot beexcluded from the present data.Participants were asked to estimate the alcohol and drug

use of their siblings. The alcohol use of the nearest agedsibling was strongly related to the participants binge drink-ing score. Peer influence would appear to have a strongimpact on drinking behavior and a similar result has pre-viously been shown in a smoking study in which siblingsmoking was the one of the strongest predictors of smokingbehavior (Wilkinson and Abraham, 2004). However it can-not be ruled out that similarities between sibling drinking inthis current study may simply be due to biased reporting bythe participants [see Weitzman et al. (2003) for similar dataon peers] Conversely, family history of alcohol use was notrelated to binge drinking behavior or to sibling alcohol use,although only about 40% of participants had any familymembers with alcohol dependency problems, the majorityof whom were second degree relatives. Although these datasuggest that binge drinking in the population of socialdrinkers in the present study was less the result of a geneticpredisposition and more of a cultural influence or peerpressure, future studies are needed to examine a possiblegenetic predisposition of binge drinking by using morerobust measures of family history of alcoholism than selfreports as we used in the present study.Current mood states in the binge drinkers group were less

positive than their nonbinge drinking counterparts and thiswas not related to alcohol withdrawal as measured by time oflast drink. Increased anxiety and negative emotional sensitivity

has been reported previously in alcohol dependent partici-pants with multiple alcohol withdrawals (Adinoff et al., 1994;Duka et al., 2002). Although alcohol abuse is often comorbidwith low mood states, whether it is a cause or effect relation-ship is not clear. Increased anxiety could advance the progres-sion to alcohol dependence particularly when coupled to abinge drinking induced loss of executive protective inhibitoryfunctions.The finding of faster reaction times on the Matching to

Sample Visual Search task in the binge drinkers group is ofinterest. Such a finding suggests that binge drinkers requireless time to reflect and make their choice, although choicetime was found to be faster only in the 8, whereas move-ment time both in the 6 and 8 pattern condition. Such anincrease in the speed of response may suggest that bingedrinkers are more efficient in response execution with re-gard to a visuospatial task. As the task was quite easy andthere were very few errors made overall, we cannot suggestthat binge drinkers, as predicted, might be more impulsive;further studies are required to address this question.The Vigilance task from the Gordon Diagnostic System

is similar to a go / no go paradigm, in which participantshave to inhibit their responding following the alerting stim-ulus, until the target stimulus appears. The task measuresboth sustained attention and impulse control and the fe-male binge drinkers were particularly impaired in this taskbeing unable to inhibit their response to the alerting stim-ulus suggesting a lack of inhibitory control from the frontallobes. Interestingly when age of starting drinking was en-tered as a covariate the significant impairment found in thefemales became marginal indicating the importance ofstarting drinking early as a contributing factor to theseeffects of binge drinking. Previous studies have also shownimpairments in cognitive function associated with heavydrinking during early adolescence (Brown et al., 2000). Wefound also group differences in females in the SpatialWorking Memory task in which the binge-drinking femalesmade more errors than their nonbinge-drinking counter-parts. No other factor was found to contribute to this effect.We have also previously shown that binge drinkers mademore between search errors in the Spatial Working Mem-ory task compared to nonbinge drinkers (Weissenborn andDuka, 2003), however, there was not gender differencefound. One reason for this discrepancy could be that the

Fig. 4. Errors of commission in the Gordon Diagnostic System Vigilancetask for male and female binge and nonbinge drinkers; *p 0.05 comparedto female nonbinge drinkers and male binge drinkers.


female binge drinkers in the current study had a higherbinge score (45.5 4.7) than the female binge drinkers inthe previous study (28.0 2.6). Additionally in the previousstudy participants were tested under alcohol or placebo andthe grouping of binge and nonbinge drinkers was based ona posthoc median split. Further research on the relation-ship between gender and binge drinking is needed to clarifythe discrepancy between the two studies. Interestingly malebinge drinkers drank more alcohol than female bingedrinkers although their binge scores were lower. This find-ing might indicate that female drinkers, although they con-sume less, may become drunk more often when drinking,giving them a higher binge score for the amount of alcoholdrunk compared to males. Thus it is perhaps not surprisingthat female binge drinkers were more impaired than malebinge drinkers.Previous studies examining drinking habits (Deckel et al.,

1995) or the adverse consequences of drinking (Giancola etal., 1996) in young adult social drinkers, have shown arelationship between impaired executive function and boththe frequency of drinking to get high and get drunk(Deckel et al., 1995) or the severity of drinking conse-quences (Giancola et al., 1996). Although impairment incertain cognitive tasks, also shown in the present study,might be the cause of extreme drinking patterns (includingbinge drinking) as the above studies indicate, data fromanimals suggest that binge drinking can induce corticaldamage and lead to cognitive deficits like perseverativeresponding in a spatial learning task (Obernier et al.,2002b). It is acknowledged however that only a prospectivestudy looking at cognitive performance in adolescents be-fore and after starting binge drinking would clarify thesequestions.In summary, these results suggest that a binge drinking

score can be used to show differences in cognition andmood in nondependent healthy social drinkers. Patterns ofdrinking may reveal differences that quantity of alcoholconsumed does not, and may be more analogous to theeffects of repeated detoxification seen in alcoholic patients.In particular the results have revealed that binge drinking isassociated with impaired performance in cognitive tasks infemales more than males. The importance of the age ofstarting drinking as a contributing factor to the findingspresented here has also been highlighted. These findingsfurthermore indicate the possibility that low mood statesand loss of executive function due to binge drinking maycombine to contribute to the progression of dangerousdrinking levels and alcohol dependence.

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