Ethnic Differences - Binge Drinking

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128 Bersamin, Paschall, and Flewelling

could have important implications for underage alco-hol abuse prevention programs.

Risk factors for alcohol and other substanceabuse are derived from established theories of delin-quency and problem behavior (e.g., Hirschi, 1969;Jessor, 1984, 1991). They also provide a foundationupon which interventions are designed, with risk fac-tors occupying a central role as the targeted inter-mediate outcomes through which the interventioneffects are to be achieved. However, the theoret-ical and empirical research underlying the identi-fication of risk factors has been based largely onpredominantly white populations without differen-tiation by race or ethnicity (Botvin, 2001; Turner,2000; Pollard et al., 1999; Wallace & Muroff, 2002).As a result, alcohol abuse prevention programs thatfocus on established risk factors may be less effec-tive in preventing binge drinking in ethnic minority

youth than white youth (Dent et al., 1996; Kumpferet al., 2002; Wallace & Muroff, 2002; Turner,2000).

Cross-sectional and longitudinal studies havefound significant ethnic differences in both the mag-nitude and direction of the relationships betweensome risk factors and adolescent alcohol use, sug-gesting that particular risk factors may be especiallyimportant for specific ethnic groups (Chen et al.,2002; Ellickson & Morton, 1999; Gillmore et al., 1990;Griffin et al., 2000; Moon et al., 2000; Wallace &Muroff, 2002; Williams et al., 1999). However, therelationships between many other risk factors have

not varied by ethnicity with respect to alcohol use.Very few studies have utilized both a nationally rep-resentative sample and a comprehensive set of mea-sures for established risk factors to assess ethnic dif-ferences in the associations between risk factors andbinge drinking.

A recent study by Wallace and Muroff (2002)examined differences in black and white high schoolseniors vulnerability to 55 risk factors for adoles-cent binge drinking in community, family, school,and peer-individual domains using MTF data. As in-dicated in Table 1, 18 (33%) of the 55 risk factors ex-

amined by Wallace and Muroff were differentially as-sociated (p < .01) with binge drinking among blackand white high school seniors who participated in theMTF study. The remaining 37 risk factors did not ex-hibit statistically significant racial differences in theirassociations with binge drinking. Several other stud-ies also have found relatively few or only small ethnicdifferences in the strength of relationships betweenestablished risk factors, alcohol and other substance

use behaviors (e.g., Costa et al., 1999; Felix-Ortiz &Newcomb, 1992; Newcomb, 1995).

In general, the 18 risk factors identified byWallace and Muroff as being differentially relatedto binge drinking were more strongly associatedwith binge drinking among white adolescents thanblacks. This was true for family, school, and peer-individual risk factors such as limited parental super-vision, poor school grades, truancy, early alcohol ex-perience, and peer alcohol use. The differences formost of these risk factors were seen only in the mag-nitude of the association, although four risk factorsexhibited a difference in the direction of associationas well. For example, attending summer school forbad grades appeared to be positively associated withbinge drinking among white adolescents (r= 0.13)but not black youth (r= 0.06). For all four risk fac-tors for which there was a difference in direction,

however, at least one of the two correlations beingcompared was relatively close to zero.

The findings from the Wallace and Muroff studysuggest that (1) the majority of known risk factorsare not differentially associated with binge drinkingfor white and black adolescents, and (2) of the riskfactors that are differentially associated, all are inthe family, school, and peer-individual domains (i.e.,none are in the community domain), and most areless strongly associated with binge drinking amongblacks. Whether and to what extent these conclu-sions apply to ethnic minority groups other thanblacks, however, warrants further study. In addition,

it would be informative to extend the Wallace andMuroff study by examining within-race correlationsfor all risk factors that are available, rather than onlythose that are differentially associated with bingedrinking, and by comparing an overall measure of as-sociation with binge drinking for the entire set of riskfactors across ethnic groups.

The methodological limitations of previous stud-ies point to the need for additional research with anationally representative and ethnically diverse ado-lescent sample, and with a comprehensive set of riskfactor measures, to better understand ethnic differ-

ences in the relationships between risk factors andbinge drinking. The present study uses data collectedfrom a large sample of adolescents in four ethnicgroups (white, black, Asian, Hispanic) who partic-ipated in the 1999 NHSDA, which included a setof 39 risk factors in the community, school, family,and peer-individual domains. Many of the risk con-structs in the NHSDA overlap with those includedin the Wallace and Muroff study, and have also been


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Table 1. Racial Differences in Risk Factor Associations with Binge Drinking, Adapted from Wallace and Muroff (2002)

Correlation with binge drinking

Risk factors White Black

Community domain

Population densityNeighborhood dissatisfaction

Family domainFamily structure (single parent)

Number of individuals in householdLow parental education

Parents disapprove of marijuana useParents disapprove of cocaine use

Limited parental supervision of social activities 0.16 0.01Limited parental supervision and help with homework

Argue with parentsFamily closeness not important

Parental dissatisfactionSchool domain

Poor grades 0.18 0.07Repeated a grade

Attended summer school for bad grades 0.13 0.06Truancy 0.27 0.17

No college plansDo not like school

Spend little time on homework

Not involved in extracurricular activities 0.17 0.05Negative attitude toward school 0.29 0.13

No school consequences for smokingNo school consequences for drinking

Limited staff effort to prevent smokingLimited staff effort to prevent alcohol use

Limited staff effort to prevent drug useEasy access to marijuana at school

Offered drugs at schoolPeer-individual domain

Radical political beliefs 0.08 0.09Religious attendance

Religious importanceEager to leave home

Good citizen regardless of obeying the law 0.18 0.03Fool around in school 5th and 6th grade 0.19 .03

Sent to the office in 5th or 6th grade 0.26 0.03Deviance 0.40 0.37

Like to get high on alcohol at partiesLike to get high on marijuana at parties

Intend to smoke cigarettes in the futureIntend to drink alcohol in the future

Intend to use marijuana in the futureNumber of friends who drink alcohol 0.41 0.25

Number of friends who get drunk weekly 0.47 0.36Been around people drinking alcohol 0.39 0.24

Been around people taking drugsPerceived alcohol intoxication at parties 0.33 0.23

Perceived use of marijuana at parties

Perceived cigarette use among friendsPerceived marijuana use among friendsEarly initiation of alcohol use 0.30 0.14

Early initiation of marijuana useEarly initiation of cigarette use

Early age of first alcohol intoxication 0.35 0.02Like to do risky things 0.21 0.16

Get a kick out of doing dangerous things

Note. Only correlations that were significantly different for black and white adolescents were reported by Wallace andMuroff (2002). Differences between correlations were significant at the .01 level. The statistical significance of each

within-race correlation coefficient was not reported.


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Ethnic Differences in Risk Factors for Adolescent Binge Drinking 131

Table 2. Ethnic Differences in Risk Factor Associations with Binge Drinking

Odds ratios

White Black Asian Hispanic

Risk factor (n = 8386) (n = 1677) (n = 428) (n = 1653)

Community domainAdults known who use drugs 5.11a 2.60a 12.32a 3.19a

Lack of neighborhood cohesiveness 1.16b 1.11 2.26c 0.94

Neighborhood indifference to drug use 1.85a 1.69a 1.70 1.42a

Neighborhood disorganization and crime 1.56a 1.23 1.25 1.18

Neighborhood mobility 1.00 1.11 1.00 1.03

Family domainFamily poverty 1.08 2.11b 1.69 1.08

Residential instability 1.07b 1.17 1.26 1.05

Number of moves in past 5 years 1.17a 1.26c 1.13 1.07

Conflict with parents 1.34a 1.08 1.08 1.34a

Family domain

Lack of communication with parents about drugs 1.13 1.58c 1.61 1.23

Poor family management 1.81a 1.40 0.59 1.84a

Parental indifference to substance use 3.44a 1.53b 2.32 1.93a

Lack of parental recognition for positive behaviors 1.38a

1.03

1.02 1.33School domainAcademic failure 1.40a 1.58c 3.00b 1.41b

No exposure to drug education at school 1.08c 1.10 1.18 1.02Perceived drug use at school 4.58a 2.50a 6.70a 2.58a

No perceived school sanctions for drug use 1.78a 1.88 7.13b 1.35School dropout 1.69a 0.97 d 0.88

Low school commitment 1.92a 1.14 3.12b 1.58b

Lack of teacher recognition for good behavior 1.25a 1.14 1.16 1.42b

Peer-individual domainAntisocial and delinquent behaviors 6.93a 3.70a 17.72a 3.05a

Indifference to drug use 3.44a 2.12a 2.08c 2.63a

Early initiation of cigarette use 1.64a 1.67c 3.03c 1.55c

Early initiation of alcohol use 1.58a 3.77a 3.25c 1.96a

Early initiation of marijuana use 4.02a 1.90c 2.13 2.67a

Low exposure to drug prevention messages outside school 1.

42

a

1.

28 5.

55

c

1.

28Perceived friends indifference to drug use 2.94a 1.81a 1.63 2.32a

Perceived drug use among friends 7.16a 3.33a 4.42a 3.42a

Low participation in organized activities 1.11a 1.04 1.47b 1.03

Perceived availability of drugs 1.59a 1.04 1.14 1.54a

Peer-individualLow perceived harm from drug use 3.57a 1.53b 1.10 2.04a

Low religiosity 1.67a 2.02a 1.33 1.21

Risk taking 2.52a 1.04 3.82a 1.92a

Low social support from adults in community 1.85a 2.00 5.55 1.81b

Low social support from adults at school 1.85a 2.08 1.96 1.69c

Low social support from family 1.31a 1.22 1.25 1.23b

Low social support from friends 1.08 1.06 1.13 1.11

Low overall social support 1.14a 1.11 1.16 1.11b

Work intensity levele

120 h/week 1.19 0.41 1.32 0.93

More than 20 h/week 1.37a 0.74 1.44 1.59

Note. All regression models controlled for age, gender, family income, and early alcohol use. Within-group maineffect: ap < .001, bp < .01, cp < .05.

Interaction effect (ethnic minority group main effect relative to main effect for whites): p < .001, p < .01,p < .05.dOnly six Asian respondents were not enrolled in school, and none of those youth reported past-30-day binge drink-ing.

eNon-working adolescents are the referent group.


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To determine whether relationships betweenrisk factors and past-30-day binge drinking differedacross racial/ethnic groups, a separate logistic regres-sion model for each risk factor was run on the fullsample. Each model included ethnic group, the riskfactor, the control variables, and the risk factor-by-ethnicity interaction terms. We examined the inter-action term odds ratios for each ethnic group todetermine which ethnic minority group(s) differedsignificantly from whites in the association betweenthe risk factor and binge drinking. A second set of lo-gistic regression analyses was then performed sepa-rately for each ethnic group, controlling for age, gen-der, income, and early alcohol use for the purpose ofobtaining a within-group main effect (odds ratio) foreach risk factor. Because of the large number of sta-tistical tests and increased probability of Type I er-rors, differences that were statistically significant at

the .05 but not the .01 level were interpreted as beingonly marginally significant.

To quantify the overall associations betweenrisk factors and binge drinking for each ethnicgroup, logistic regression models that included eachdomain-specific subset of risk factors, and then thecomplete set of all 39 factors, were run for each eth-nic group. The resulting pseudo R2 was used to assessand compare the overall relationships between riskfactors and binge drinking across the ethnic groups.

No restrictions were used to limit the samplebased on complete or incomplete data for all studyvariables. Therefore, the sample size for each regres-

sion model varies and is somewhat smaller than sam-ple sizes reported at the top of Table 2. Variablesthat had relatively high levels of missing data wereexamined to determine whether nonresponse was as-sociated with demographic characteristics and bingedrinking.

RESULTS

Non-Response Attrition Analysis

The highest level of non-response (24%) was ob-

served for the multi-item scale measure of perceiveddrug use at school. Adolescents who did and did notprovide complete data for this risk factor were simi-lar with respect to age and gender. However, adoles-cents who did not provide complete data were morelikely to be non-white and to report a lower familyincome level and a lower level of past-30-day bingedrinking. Other variables that had relatively high lev-els of missing data were also in the school domain,

and exhibited the same pattern of non-response biasas perceived drug use at school.

Sample Characteristics

White adolescents comprised the largest pro-portion of the sample (68%) followed by blacks(14%), Hispanics (14%), and Asians (4%). Theethnic groups were similar with respect to age (over-all mean = 15.47) and gender (51.6% of total sam-ple were males). The average estimated family in-come level for the group as a whole was between$40,000 and $49,000. However, family income levelvaried significantly by ethnicity, with black andHispanic youth reporting the lowest family incomelevels.

About 14% of the adolescents reported binge

drinking in the past 30 days. As expected, a largerpercentage of white adolescents reported any past-30-day binge drinking (16.2%) as compared to blacks(7.1%), Asians (6%) and Hispanics (14.6%), but theprevalence of past-30-day binge drinking was not sig-nificantly higher among whites than Hispanics.

Ethnic Differences in Relationships BetweenRisk Factors and Binge Drinking

Results in Table 2 include the within-group maineffect for each risk factor and the associated signifi-

cance level for the within-group main effect, and in-dicate whether the main effect for each ethnic mi-nority group differed significantly from that of whiteadolescents. Seventeen of the 39 risk factors (43%)were differentially associated with past-30-day bingedrinking (p < .01) in at least one ethnic minoritygroup relative to whites. Ethnic group differenceswere observed primarily through variation in themagnitude of associations between risk factors andpast-30-day binge drinking, rather than through dif-ferences in directionality. Consistent with our expec-tation, the majority of the 17 risk factors were more

strongly associated with past-30-day binge drinkingamong white adolescents than black and Hispanicyouth. For example, white adolescents who reportedearly initiation of marijuana use were 4.02 times aslikely as those not initiating marijuana use before age14 to report any past-30-day binge drinking. In con-trast, black adolescents who reported early initiationof marijuana use were 1.90 times as likely as othersto report past-30-day binge drinking.


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A total of 912 risk factors were differentiallyassociated with past-30-day binge drinking amongHispanic and black adolescents relative to whitesat the .01 significance level, while an additional 610 risk factors were differentially associated withbinge drinking at the .05 level. Comparisons betweenwhite and Hispanic youth revealed a significantlystronger relationship between all nine risk factorsand binge drinking among white youth. A similarpattern of association was evident when comparingblack and white youth. A total of 11 of the 12 signifi-cant interaction terms were indicative of a strongerrelationship between risk factors and binge drink-ing among whites relative to blacks. The one excep-tion was family poverty, which was more stronglyassociated with binge drinking among black youth(OR = 2.11) compared to white youth (OR = 1.08).

Fewer significant differences were detected be-

tween white and Asian adolescents, which may bedue to the smaller sample size for Asian youth rel-ative to the other groups. Specifically, two risk fac-tors (poor family management, low perceived harmfrom drug use) were differentially associated withbinge drinking among Asian relative to white ado-lescents (p < .01), while three other risk factor dif-ferences approached statistical significance (p < .05).Interestingly, poor family management was a riskfactor for binge drinking among white adolescents(OR = 1.81), while the opposite was true for Asianadolescents (OR = 0.59). Among whites, low per-ceived harm from drugs was positively associated

with binge drinking (OR = 3.57), but was not re-lated to binge drinking among Asian youth (OR =1.10). Among the marginally significant (p < .05) dif-ferences, residential instability, academic failure andlow exposure to drug prevention messages outsideschool were more strongly related to binge drinkingfor Asian youth. Several other risk factors (e.g., per-ceived drug use among adults, antisocial and delin-quent behavior) also appeared to be more stronglyassociated with past-30-day binge drinking for Asianadolescents than whites. For example, the odds ra-

tio for perceived drug use among adults was 12.32 forAsian youth versus 5.11 for whites. However, thesedifferences were not statistically significant at the .01level due to a relatively small sample size, low preva-lence of past-30-day binge drinking, and large stan-dard errors for odds ratios in the Asian group.

Overall Value of Risk Factors

Table 3 includes the Cox and Snell pseudo R2

values for domain-specific subsets, and for the com-plete set of variables for each ethnic group. Formost domains, the risk factors collectively explaineda larger proportion of variation in binge drinkingamong white adolescents than youth in ethnic mi-nority groups. However, R2 values for the peer-individual domain were comparable for white ado-

lescents (.245) and Asians (.255), and the R2 valuefor the school domain was highest for Asian youth(.133).

The complete set of risk factors explained 39%of the variation in binge drinking among Asianadolescents, compared to 27% for whites, 22% forHispanics, and only 10% for blacks.

DISCUSSION

This study is one of the first to examine differ-ences across multiple ethnic groups in the strengthof associations between risk factors and binge drink-ing based upon a comprehensive set of risk fac-tor measures and a nationally representative sam-ple of adolescents. The observed rates of past-30-daybinge drinking in the 1999 NHSDA sample of ado-lescents were lower than rates obtained by the MTF,for which surveys are administered in classroom set-tings (Johnston et al., 2002). Nevertheless, past-30-day binge drinking was evident among adolescentsin the 1999 NHSDA sample as 14% reported con-suming five or more consecutive drinks at least once

Table 3. R2 Values for Risk Factor Domains by Ethnicity

White Black Asian Hispanic

Domain (N= 8386) (N= 1677) (N= 428) (N= 1653)

Community 0.093 0.035 0.101 0.056Family 0.086 0.020 0.050 0.065

School 0.093 0.027 0.133 0.056Peer-individual 0.245 0.101 0.255 0.186

All domains 0.265 0.100 0.393 0.217


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in the past 30 days. Ethnic differences in rates of ado-lescent binge drinking in the 1999 NHSDA were con-sistent with differences found in other national stud-ies as the highest prevalence rate of binge drinkingwas observed among whites and the lowest preva-lence rates were observed in blacks and Asians.

Our findings are comparable to the study byWallace and Muroff (2002) in that the majority ofrisk factor measures in the 1999 NHSDA were notdifferentially associated with binge drinking for dif-ferent ethnic groups, and most of the differentialassociations were stronger for whites than youth inother ethnic groups. Results of both studies also sug-gest that in general, most risk factors for binge drink-ing operate in the same direction for black and whiteadolescents, even when the magnitude of relation-ships differ. Similar to the study by Wallace andMuroff, we found that perceived drug use of friends,

negative attitude towards school (or low schoolcommitment), and deviant/delinquent behavior weremore strongly associated with binge drinking amongwhite adolescents than blacks. These findings sug-gest that binge drinking is more likely to co-occurwith school problems and other risk behaviors amongwhite adolescents than blacks.

Within these overall similar patterns, however,a number of more specific findings that differedbetween the two studies are noteworthy. Limitedparental supervision for social activities was the onlyfamily domain risk factor in the Wallace and Muroffstudy that was differentially associated with binge

drinking between black and white adolescents. Incontrast, our study did not indicate a significantblackwhite difference in the relationship betweenpoor family management and binge drinking. Ad-ditionally, our study revealed a positive associationbetween family poverty and binge drinking amongblacks but no such relationship among whites, whileWallace and Muroff found no differences in rela-tionships between low parental education and bingedrinking between blacks and whites in the MTFsample. Wallace and Muroff also did not find adifferential association between parental attitudes

towards marijuana and cocaine use and binge drink-ing, while our study indicated that parental indiffer-ence to drug use was more strongly associated withbinge drinking for white adolescents than blacks.This difference may be attributable to the more com-prehensive multi-item measure of parental indiffer-ence to drug use in our study, which was based onparental attitudes toward tobacco, alcohol and mari-

juana use. This study also indicated that no racial dif-

ferences were observed for academic failure. In con-trast, Wallace and Muroff found that school gradeswas more strongly associated with binge drinkingamong white than black adolescents in the MTFsample.

Differences between our findings and the studyby Wallace and Muroff may be attributable to dis-similarities in the age of the study samples (1417 year olds versus high school seniors), differencesin measures of risk factors, and differences in surveymethodology (in-home computer assisted interviewsversus in-school written surveys). Another explana-tion may be the large sets of results being compared.The differences in findings regarding differential ef-fects of specific risk factors, despite similarities inthe overall patterns observed, are characteristic ofthe research in general on this topic, and illustratewhat appears to be a relatively high sensitivity of this

research topic to methodological differences acrossstudies.

Results from the current study have importantimplications for prevention research and practice.First, because a number of the established risk fac-tors for alcohol and other substance use are morestrongly associated with binge drinking among whitesthan blacks or Hispanics, prevention programs thatspecifically target one or more of these risk factorsare likely to be more effective, and possibly morerelevant, among white youth than black or Hispanicyouth. This does not appear to be the case for Asianyouth. Our findings suggest that risk factors included

in this study are generally just as relevant to preven-tive interventions with Asian youth as white youth.

Potency of the targeted risk factors is only one ofthe several considerations that can influence the ef-fectiveness of any given intervention. Other elementsalso are likely to influence the relative efficacy of pre-vention programs across racial/ethnic groups, includ-ing the relative level of specific risk factors in thetarget populations. Persons or groups with relativelyhigh risk factor levels may be amenable to greater re-ductions in these risk factors. Although our findingsindicated that many risk factors were not as strongly

associated with binge drinking among Hispanic andblack youth relative to whites, it was also the casethat Hispanic and black youth had higher levels ofrisk than white youth for most of the risk factors (re-sults not shown).

Second, our findings suggest that currently es-tablished risk factors do not adequately explain vari-ation in adolescent binge drinking, especially amongblack youth. Although the relationship between


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binge drinking and many of the risk factors exam-ined were not significantly different between whitesand minority ethnic groups, the collective explana-tory value of all 38 risk factors was notably strongeramong white youth (R2 = .265) in comparison toblack (.100) and Hispanic (.217) youth. These find-ings appear to be consistent with the study byWallace and Muroff and other studies (e.g., Parkeret al., 2000; Griffin et al., 2000), and point to the needfor additional research to better understand why ado-lescents in general, and black adolescents in particu-lar, engage in binge drinking. It is apparent that im-portant risk factors for alcohol misuse by youth ingeneral, and black and Hispanic youth in particular,either have not yet been identified, or if they havebeen identified, have not been included in large na-tional surveys such as the NHSDA and MTF.

Findings of this study and the study by Wallace

and Muroff suggest that there is still much to belearned about what types of alcohol abuse preven-tion strategies, as characterized by the risk factorsthey target, are likely to be effective for black andHispanic youth. This is reflected in the scarcity ofprevention programs that are specifically tailored forspecific racial/ethnic populations. Of the 44 modelsubstance abuse prevention programs identified bythe Center for Substance Abuse Prevention (Schinkeet al., 2002), 42 are designated as being suitable formixed racial/ethnic populations, whereas only oneis tailored specifically to black youth and only one istailored specifically to Hispanic youth.

Large scale national surveys are designed toinclude risk factor measures that are thought to berelevant to the general population, which is predom-inantly white. The same is true for much of the eti-ologic research that guides the identification of riskfactors that are most robust in explaining adolescentalcohol misuse. Results of this study appear to reflectthis process as a number of risk factors included inthe NHSDA were less associated with binge drink-ing among Hispanic and black adolescents relativeto whites. The alternative explanation that bingedrinking is simply less predictable among black and

Hispanic youth seems less tenable. Research hasidentified variables such as acculturation and ethnicidentity (e.g., Kulis et al., 2003) that help to explainvariation in substance use behaviors among ethnicminority youth, but which are not included in na-tional surveys such as the NHSDA. Also mostly ab-sent from the NHSDA are factors that reflect alco-hol use motivations and expectancies. Studies haveshown that these constructs are related to adolescent

drinking behavior, but that their relevance varies byrace/ethnicity (Strunin, 1999).

Findings of this study should be considered inlight of several limitations. First, the study is basedon cross-sectional data which limits our ability to in-fer causal associations between risk factors and ado-lescent binge drinking. Relatedly, some of the signif-icant associations for individual risk factors reportedin Table 2, and significant differences in these rela-tionships across racial/ethnic groups, may be due inpart to confounding effects among these variables.Thus, despite controlling for early initiation of al-cohol use, not all of the significant associations re-ported in Table 2 are necessarily causal in nature.Although multivariate models can be used to helpassess confounding, their results are best interpretedin light of strong conceptual models and/or assump-tions that distinguish between confounding and me-

diational effects. Additionally, the lower prevalenceof binge drinking among black and Asian adoles-cents, and the relatively small sample size for theAsian group, may have limited our ability to detectpotentially important ethnic differences in associa-tions between some risk factors and binge drinkingas well as within-group main effects. Another pos-sible limitation of the study is the reliance on self-report data. Although the NHSDA uses survey ad-ministration procedures designed to maximize ac-curacy and honesty in self-reporting (Lessler et al.,2000), and the validity of self-reported substance usebehaviors by adolescents has generally been sup-

ported in prior research, the possibility of differen-tial accuracy of self-report across ethnic groups can-not be dismissed (Bauman & Ennett, 1994). Lessaccurate reporting may have attenuated relationshipsamong the variables examined, and thus could bepartly responsible for the weaker associations be-tween some risks factors and binge drinking observedfor Hispanic and black youth relative to whites. Fi-nally, the four categories of race/ethnicity defined forthis study comprise multiple groups that may varyconsiderably with respect to ethnic origin, culture,and acculturation.

Although this study and the previous nationalstudy by Wallace and Muroff suggest that the ma-jority of established risk factors for adolescent sub-stance use are weakly associated with binge drinkingamong black and Hispanic adolescents, it is possiblethat some of the risk factors examined in this study(e.g., family poverty) have delayed or long-term ef-fects on binge drinking in adulthood in these minor-ity groups. Thus, longitudinal studies with data from


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representative samples of adolescents are needed tobetter understand ethnic differences in delayed orlong-term effects of risk factors on binge drinking.

ACKNOWLEDGMENTS

This study was supported by a grant from theNational Institute on Drug Abuse (NIDA Grant No.DA14993).

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Ethnic Differences - Binge Drinking