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and its major subfractions: the Caerphillyand Speedwell Collaborative Heart Dis-ease Studies. J Epidemiol CommunityHealth. 1988;42:220-225.

2. Kivela S-L, Nissinen A, Punsar S, Puska P,Karvonen MJ. Determinants and predic-tors of heavy alcohol consumption amongaging Finnish men. Compr Gerontol [B].1988;2:103-109.

3. Johnson CC, Hunter SM, Amos CI, ElderST, Berenson GS. Cigarette smoking,alcohol, and oral contraceptive use by typeA adolescent[s}-the Bogalusa Heart Study.JBehav Med. 1989;12:13-24.

4. The 1988 Joint National Committee. The1988 Report of the Joint National Commit-tee on Detection, Evaluation, and Treat-ment of High Blood Pressure. Arch IntemMed. 1988;148:1023-1038.

5. LaPorte R, Valvo-Gerard L, Kuller L, etal. The relationship between alcohol con-sumption, liver enzymes, and high densitylipoprotein cholesterol. Circulation. 1981;64(III):67-72.

6. Prevention ofCardiovascularDiseaseRecom-mendationsforNational Governments. Tech-nical reports of the World Health Organiza-tion, Coronary Prevention Group. London,England: World Health Organization; 1992.

7. Schoenbom CA, Cohen BH. Trends insmoking, alcohol consumption, and otherhealth practices among US adults, 1977and 1983. Adv Data Vital Health Stat. June30, 1986; no. 118. DHHS publication PHS86-1250.

8. Healthy People 2000: NationalHealth Promo-tion and Disease Prevention Objectives, Con-ference Edition. Washington, DC: US Deptof Health and Human Services; 1990.

9. Berenson GS, McMahan CA, Voors AW,et al. Cardiovascular Risk Factors in Chil-dren: The EarlyNatural History ofAtheroscle-rosis and Essential Hypertension. New York,NY: Oxford University Press; 1980.

10. Croft JB, Freedman DS, Cresanta JL, et al.Adverse influences of alcohol, tobacco, andoral contraceptive use on cardiovascularrisk factors during transition to adulthood.Am JEpidemiot 1987;126:202-213.

11. Hunter SM, Webber LS, Berenson GS.Cigarette smoking and tobacco usage be-havior in children and adolescents: Boga-lusa Heart Study. Prev Med. 1980;9:701-712.

12. Bresnahan JL, Shapiro MM. A generalequation and technique for the exactpartitioning of chi-square contingencytables. Psychol Bull. 1966;66:252-262.

13. Johnston LD, O'Malley PM, Bachman JG.National Survey Results on Drug Use fromMonitoring the Future Study, 1975-1992:Volume I. Secondary School Students. Rock-ville, Md: National Institutes of Health,National Institute on Drug Abuse; 1993.

14. Brooks SD, Williams GD, Stinson FS,Noble J. Apparent per Capita AlcoholConsumption: National, State and RegionalTrends, 1977-1987. Rockville, Md: Na-tional Institute on Alcohol Abuse andAlcoholism; 1989. Surveillance Report 13.

15. Barber JG, Bradshaw R, Walsh C. Reduc-ing alcohol consumption through televisionadvertising. J Consult Cin Psychol. 1989;57:613-618.

A Gender-Specific Measure of BingeDrinking among College StudentsHenry Wechsler, PhD, George W Dowdall, PhD, Andrea Davenport, MPH, andEric B. Rimm, ScD

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IntroductionBinge drinking, or the consumption

of large amounts of alcohol on a singleoccasion, has been linked to an increasedrisk of negative health outcomes.1 It hasbecome common practice in research onalcohol to define heavy or binge drinkingin terms of episodes involving five or moredrinks in a row for both men andwomen.2-7 Yet blood alcohol level tablesthat determine the legal definition ofdriving while intoxicated8 are based on sexas well as on weight. Recent researchsuggests that the gender differences areowing to women's lower rates of gastricmetabolism of alcohol (initially only 80%of men's) and, therefore, to their higherblood alcohol levels for a fixed amount ofalcohol, even after accounting for differ-ences in body weight or lean body mass.9Psychiatric epidemiologists have sug-gested that clinical criteria should there-fore be defined differently for men andwomen in the diagnosis of alcohol depen-dency and alcoholism.10

This paper contrasts the use of thecurrently accepted definition of bingedrinking to the use of a gender-specificstandard among college students.

Methods and StatisicalAnalysisThe data for this research were

gathered as part of a representativesurvey of 17 592 students at 140 colleges.A self-administered 20-page question-naire received by 25 627 students in early1993 yielded an overall response rate of

Henry Wechsler, George W. Dowdall, andAndrea Davenport are with the Department ofHealth and Social Behavior, and Eric B. Rimmis with the Department of Epidemiology andNutrition, Harvard School of Public Health,Boston, Mass. Dr Dowdall is also with St.Joseph's University, Philadelphia, Pa.

Requests for reprints should be sent toHenry Wechsler, PhD, Department of Healthand Social Behavior, Harvard School of PublicHealth, 677 Huntington Ave, Boston, MA02115.

This paper was accepted January 11,1995.

July 1995, Vol. 85, No. 7

Public Health Briefs

69%. Details of the study design havebeen published elsewhere.'

This analysis is based on the 12 243respondents who reported drinking alco-hol in the 30 days prior to the survey andcould be classified as current drinkers,nonbinge or binge. To quantify differ-ences by sex and to control for otherpotential confounders, multiple logisticregression was used to compare thelikelihood of an alcohol-related problemamong men with that among women for atypical drinking level (i.e., the usualnumber of drinks per occasion in the past30 days). The dependent variable waswhether a student reported experiencing1 of 12 outcomes as a result of drinking.Each student was asked: "Since thebeginning of the school year, how often hasyour drinking caused you to [experienceeach of twelve problems]." The ninealcohol-related problems that were expe-rienced by at least 5% of students of eachsex are presented in Table 1. The threeproblems that fell below this cutoff-vandalism, trouble with the police, andalcohol overdose-were excluded fromthe rest of the analysis.

The logistic model was as follows:

In1 P= 1O + P1 Xgender

n

+ E r3iXi + i3intrxXXgenderqi=2

where Xgender is 1 if male and 0 if femaleand the xi are a series of indicatorvariables specifying the level of a student'stypical drinking during the previous month.For example, X3 takes on the value 1 forstudents who reported typically drinkingthree drinks per occasion andx3 is 0 for allother students. Students typically drinkingone drink were considered the referencecategory. The antilogs of the beta coeffi-cients can be directly interpreted as theodds of a particular outcome between the"exposed" and the referent populations.The P,I is the estimate for the effect of sex,the P3i's are the estimates of effect for eachindividual level of alcohol consumption,and the 3inx's are the estimates for theinteraction between sex and level ofdrinking.

To determine if female and malestudents had similar odds of an alcohol-related outcome for a given level ofalcohol consumption, the odds ratio (OR)

drinks five drinks can be estimated fromthe ratio of fitted logits:

OR

between the sexes was calculated. Forexample, the odds ratio for a woman whodrinks four drinks versus a man who

Odds of woman who drinks 4

Odds of man who drinks 5

=

el+culaende9+55+ inoi,

= eN-3gender-P - intS .

We calculated 95% confidence inter-

vals (CIs) using the variance estimates ofeach coefficient plus two times the covari-ance of each possible pair of terms."Self-reported items on height and weightwere transformed into metric measure-ments. The body-mass index was createdusing the conventional definition ofweight(in kilograms) divided by the square ofheight (in meters). In this sample, bodymass index averaged 24 for males and 22for females.

American Journal of Public Health 983July 1995, Vol. 85, No. 7

TABLE 1-Odds Ratios (95% Confidence Intervals) for Risk of Alcohol-RelatedProblems with Gender-Neutral and Gender-Specific Definitionsamong 12 243 US College Students

Gender-Neutral Gender-SpecificDefinition: OR of Definition: OR of

Women Consuming Women ConsumingAlcohol-Related % Reporting 5 Drinks vs Men 4 Drinks vs Men

Problem Problem Consuming 5 Drinks Consuming 5 Drinks

Hangover 64 1.78*** (1.36-2.34) 1.30* (1.02-1.67)Miss a class 30 1.47*** (1.19-1.81) 0.99 (0.81-1.21)Fall behind 23 1.33* (1.06-1.66) 1.04 (0.83-1.29)Cause regret 36 1.41** (1.15-1.73) 1.17(0.96-1.43)Forget 27 1.31* (1.06-1.62) 0.92 (0.74-1.13)Argument 22 1.08(0.86-1.35) 0.90 (0.72-1.12)Unplanned sex 21 0.89 (0.71-1.12) 0.89 (0.72-1.11)Unsafe sex 11 0.94 (0.70-1.26) 0.87 (0.66-1.16)Injury 10 1.23 (0.92-1.65) 0.81 (0.60-1.09)

*P < .05; **P < .01; ***P < .001.

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FIUR 1-umlaive prcentag f1 24 ;studnt wh8o i.reported misin a

clssa aRresult ofsdrJinkn lchl by usual nube of drink pr;occasionin the past month~~~~~~~~~~~~~~11k

>~~~~~~~~~~~~~~ - iX_it';jj ' si l 0

ffi:.;i <it > 3 @_2 gs <J 2r}8 |

. w g+ ; ,. r, -te, 9! | i W ~~~~~~~~~~~~~~~~~~~~~~7i

FIGURE 1 -umulative percentage of 12 243 students who reported missing aclass as a result of drinking alcohol, by usual number of drinks peroccasion in the past month.

Public Health Briefs

ResultsThe overall sample is representative

of full-time undergraduates currentlystudying at 4-year American colleges anduniversities. The proportions of men andwomen were similar in such variables asage, race, marital status, self-rating ofhealth, having a parent who was a collegegraduate, and living with a roommate.

Figure 1 illustrates the differencesbetween the sexes for one drinking-related problem. Plotted along the verti-cal axis are the usual numbers of drinksconsumed per occasion during the previ-ous 30 days. The horizontal axis presentsthe cumulative percentage of studentswho reported missing a class since thebeginning of the school year as the resultof drinking. Other figures (not presentedfor reasons of space) illustrating indi-vidual alcohol-related problems show simi-lar results.

If men and women missed a classbecause of drinking and this outcome wasdue to the same usual number of drinksper episode for both sexes, Figure 1 wouldshow two overlapping lines, with the samecumulative proportion ofmen and womenat each level of usual drinking. Instead,Figure 1 shows a clear difference, with agap between the two sexes indicating thatwomen reported missing a class at asignificantly lower level of usual drinkingthan men.

Table 1 gives the odds of each of ninedrinking-related problems for a womanwho usually drinks four or five drinkscompared with a man who usually drinksfive drinks. The problems are presented inthe same order as in the original question-naire. The crucial numbers in this tableare not the odds ratios of the risk ofdisease; rather, they are the comparisons.For example, the second row reports onthe results from one question, "Since thebeginning of the school year, how oftenhas your drinking caused you to miss aclass?" Thirty percent of the students whodrank during the last year reportedmissing a class because of drinking.Women who usually consumed five drinkswere 1.47 times (95% CI = 1.19, 1.81)more likely to miss a class than were menwho consumed five drinks, strong andstatistically significant evidence that usingthe same cutoff for binge drinking for menand women is misleading. By contrast,women who usually consumed four drinkswere almost equally likely to miss a classcompared with men who usually con-sumed five drinks (OR = 0.99; 95%CI = 0.81, 1.21). The important compari-

sons are not across the two sets of oddsratios (1.47 and 0.99) but are embeddedwithin the confidence limits of each. Theonly meaningful comparison across col-umns may be that one odds ratio issignificantly different from 1.00 while theother is not. For most of the problemsexamined, the evidence (presented in thecolumn labeled "Gender-Neutral Defini-tion") suggests that women who drankfive drinks were significantly more likelyto experience an adverse outcome thanmen who drank at a similar level. Bycontrast, for eight of the nine problemsreported (the column labeled "Gender-Specific Definition"), women who typi-cally drank four drinks had a similarlikelihood of each alcohol-related prob-lem as men who had five drinks.

At least some of the associationbetween usual drinking and the occur-rence of alcohol-related problems mightbe owing not to sex but to differences inbody mass. However, controlling for bodymass index only somewhat attenuated theodds ratios. For example, the odds of anyof the alcohol-related problems (exclud-ing unplanned or unsafe sex) for a womanconsuming five drinks versus a manconsuming five drinks dropped from 1.66(95% CI = 1.18, 2.34) to 1.53 (95%CI = 1.08, 2.16) after controlling for bodymass index. When women who consumedfour drinks were compared with men whoconsumed five drinks, the odds alsodiminished from 1.36 (95% CI = 1.00,1.87) to 1.25 (95% CI = 0.90, 1.71). Thissupports the argument that women havelower rates of gastric metabolism ofalcohol and therefore higher blood alco-hol levels than men for a fixed amount ofalcohol, even after accounting for differ-ences in body weight and lean body mass.9Further control for year in school, type ofschool, or living arrangements did notappreciably alter these results.

DiscussionThe methodological implications of

this research are clear: a lower standarddefining heavy or binge drinking needs tobe used for women than for men. Foreight of the alcohol-related problemsexamined in this study of college students,women who typically drank four drinkshad a similar likelihood of experiencingthat problem as men who usually drankfive drinks. The findings did not apply,however, to the most frequently experi-enced problem, hangover.

The study relies on self-reports,which introduce the possibility of error

due to under- or overreporting or untruth-fulness. However, investigators have stud-ied the validity of self-reported question-naires and have used this method withsuccess.1',2"-7 There is also no evidence ofdifferences between men and women inself-report inconsistencies or inaccura-cies.

What are the practical consequencesof using this cutoff to understandingcollege binge drinking? Using the olddefinition of binge drinking (five or moredrinks) would identify 33% of the womenas binge drinkers; using the new definitionincreases that figure to 39%. This increaseof 6% (a relative increase of 18%) in thenumber ofwomen binge drinkers is in linewith the growing emphasis on alcoholproblems in women.1820 Clinicians andadministrators might draw additional im-plications from the findings. Womenshould be advised that they cannot drinkat the same level as men without riskinggreater health and behavioral conse-quences. College alcohol educators shouldconsider programs to alert women to theheightened risk they run in matching maledrinking patterns. While "blaming thevictim" is poor social policy, it is entirelyappropriate to educate women to protecttheir own health in an environment inwhich gender-neutral drinking norms ac-tually put them at higher risk than men.Clinicians should suspect the presence ofdrinking problems in their female patientsat lower levels of alcohol use than is seenin male patients.

Although many women drink asheavily as men, their recognition ofalcohol problems lags. Among drinkerswho binged three or more times in thepast 2 weeks, 22% of the men describedthemselves as heavy or problem drinkerscompared with only 8% of the women. Itis important to correct the underestima-tion of the extent and seriousness ofdrinking problems in women,20 contrib-uted to in part by the use of a singlestandard for heavy alcohol consumption.A gender-specific definition of bingedrinking should be used in future researchand clinical practice. O

AcknowledgmentsThis research was supported by the RobertWood Johnson Foundation.

We wish to thank the following personswho assisted with the project: Andrew Brodsky,BS; Sonia Castillo, PhD; Gary Gregg, PhD;Jeffrey Hansen, BS; Lloyd Johnston, PhD;Avtar Khalsa, MSW; Marianne Lee, MPA; andBarbara Moeykens, MS. We also wish to thankScott Chasan-Taber, PhD, for assistance indeveloping the statistical models.

984 American Journal of Public Health July 1995, Vol. 85, No. 7

References1. Wechsler H, Davenport A, Dowdall G,

Moeykens B, Castillo S. Health and behav-ioral consequences of binge drinking incollege: a national survey of students at 140campuses.JAMA. 1994;272:1672-1677.

2. Wechsler H, Isaac N. "Binge" drinkers atMassachusetts colleges: prevalence, drink-ing styles, time trends, and associatedproblems.JAMA. 1992;267:2929-2931.

3. Hanson DJ, Engs RC. College students'drinking problems: a national study, 1982-1991. Psychol Rep. 1992;71:39-42.

4. Presley CA, Meilman PW, Lyerla R.Alcohol and Drugs on American CollegeCampuses: Use, Consequence, and Percep-tions of the Campus Environment. Vol 1.1989-1991. Carbondale, Ill: Core Institute;1993.

5. Johnston LD, O'Malley PM, Bachman JG.National Survey Results on Drug Use fromthe Monitonng the Future Study, 1975-1993.Vol.1. Secondary School Students. Washing-ton, DC: US Government Printing Office;1994. NIH publication 94-3809.

6. National Household Survey on Drug Abuse:Population Estimates, 1992. Rockville, Md:

US Dept of Health and Human Services;1993.

7. Hingson RW, Strunin L, Berlin BM,Heeren T. Beliefs about AIDS, use ofalcohol and drugs, and unprotected sexamong Massachusetts adolescents. Am JPublic Health. 1990;80:295-299.

8. O'Brien R, Chafetz M. The Encyclopedia ofAkoholism. New York, NY: Facts on File;1982:49-51.

9. Frezza M, diPadova C, Pozzato G, TerpinM, Baraona E, Lieber CS. High bloodalcohol levels in women: the role ofdecreased gastric alcohol dehydrogenaseactivity and first-pass metabolism.N EnglJMed. 1990;322:95-99.

10. Hetzler JE, Burnham A. Alcohol abuseand dependency. In: Robins LN, RegierDA, eds. Psychiatnic Disorders in America.New York, NY: Free Press; 1991.

11. Hosmer DW, Lemeshow S. Applied Logis-tic Regression. New York, NY: John Wiley& Sons; 1989.

12. Freier MC, Bell RM, Ellickson PL. DoTeens Tell the Truth? The Validity ofSelf-Reported Tobacco Use by Adolescents.Santa Monica, Calif: RAND; 1991. RANDpublication N-3291-CHF.

Public Health Briefs

13. Midanik L. Validity of self-reported alco-hol use: a literature review and assessment.BntJAddict. 1988;83:1019-1030.

14. Reinisch OJ, Bell RM, Ellickson PL. HowAccurate Are Adolescent Repois of DrugUse? Santa Monica, Calif: RAND; 1991.RAND publication N-3189-CHF.

15. Kupetz K, Klagsbrun M, Wisoff D, LaRosaJ, Davis DI. The acceptance and validity ofthe Substance Use and Abuse Survey(SUAS).JDrugEduc. 1979;9:163-188.

16. Rachel JV, Guess LL, Hubbard RL, et al.Adolescent Drinking Behavior. Vol 1. Re-search Triangle Park, NC: Research Tri-angle Institute; 1980.

17. Room R. Survey vs sales data for the US.Drink DrugPract Sunr. 1971;3:15-16.

18. Celis W. Drinking by college women raisesnew concern. New York Times. February16, 1994:A18.

19. Ettore E. Women and Substance Use. NewBrunswick, NJ: Rutgers University Press;1992.

20. Rodin J, Ickovics JR. Womens' health:review and research agenda as we ap-proach the 21st century. Am Psychol.1990;45:1018-1034.

Tuberculosis Knowledge among NewYork City Injection Drug UsersHannah Wolfe, MS, Michael Marnor, PhD, Robert Maslansky, MD,Stuart Nichols, MD, Michael SimberkoffJ MD, Don Des Jarlais, PhD,andAndrew Moss, PhD, MPH

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IntrodutionIn the past decade, New York City

has witnessed a dramatic increase inpulmonary tuberculosis. Increases in hu-man immunodeficiency virus (HIV) infec-tion, homelessness, and poverty are re-sponsible for much of this resurgence; allof these are prevalent among New YorkCity injection drug users, who are amongthose at highest risk for tuberculosis.16The present study sought to assess tuber-culosis-related knowledge in this popula-tion.

Virtually no public health educationregarding tuberculosis has been done inthe past 3 decades. A recent survey ofinjection drug users in Brooklyn, NY,suggests the presence of a high level ofmisinformation and fear about tuberculo-SiS.7 The Centers for Disease Control andPrevention (CDC) recently called forpublic awareness campaigns to alert the

minority communities most affected bytuberculosis about its increasing inci-dence, and to provide knowledge andother resources needed to influence tuber-culosis programs directed toward thosecommunities.8 In 1994, the CDC addedquestions on tuberculosis transmission to

Hannah Wolfe and Michael Marmor are withthe Division of Epidemiology and Biostatistics,New York University Medical Center; RobertMaslansky is with the Department of Psychia-try, Bellevue Hospital; Stuart Nichols and DonDes Jarlais are with the Beth Israel MedicalCenter; and Michael Simberkoff is with theManhattan Veterans Affairs Medical Center,all in New York, NY. Andrew Moss is with theDepartment of Epidemiology and Biostatistics,University of California, San Francisco.

Requests for reprints should be sent toMichael Marmor, PhD, Department of Envi-ronmental Medicine, New York UniversityMedical Center, 341 E 25th St, New York, NY10010.

This paper was accepted on October 4,1994.

American Journal of Public Health 985