Multilevel analysis of situational drinking among Canadian undergraduates

Social Science & Medicine 55 (2002) 415–424

Multilevel analysis of situational drinking among Canadian undergraduates Andre! e Demersa,*, Sylvia Kairouza,b, Edward M. Adlaf b,c, Louis Gliksmanb,d, Brenda Newton-Taylorb, Alain Marchanda a

! ! Groupe de recherche sur les aspects sociaux de la sante! et de la prevention, 2801 Edouard Montpetit, Universite! de Montreal, ! (Quebec), ! C.P. 6128, succ. Centre-Ville, Montreal Canada H3C-3J7 b Centre for Addiction and Mental Health, Canada c University of Toronto, Canada d University of Western Ontario, Canada

Abstract Using a multi-level approach, we examined the contribution of drinking setting characteristics and of individual characteristics on the alcohol intake per drinking occasion. The data are drawn from the Canadian Campus Survey, a national mail survey conducted in 1998 with a random sample of 8,864 students in 18 universities. For each student, up to five drinking occasions were investigated, resulting in 26,348 drinking occasions among 6,850 drinkers. At the individual level this study focused on the university life experience. At the situational level, information about alcohol intake was recorded relative to why, when, where and with whom drinking occurred. Our results show that drinking setting is as important as the individual characteristics in explaining the alcohol intake per occasion. Policies aimed at reducing students alcohol intake may be more beneficial if they address both situational and individual factors. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: Alcohol consumption; Drinking occasion; University students; Multilevel models; Canada

‘‘The wise adapt themselves to circumstances, as water molds itself to the pitcher’’FChinese Proverb

Introduction Drinking is an integral part of campus social life, and the university milieu carries its own set of norms, opportunities and social influences regarding alcohol consumption. Consequently, the campus drinking culture is often described as a ‘‘wet’’ culture, and the university students’ drinking style is generally characterized as a heavy episodic or a binge drinking style (Gliksman, Demers, Adlaf, Newton-Taylor, & Schmidt, 2000; Wechsler, Lee, Kuo, & Lee, 2000).

*Corresponding author. Tel.: +1-514-343-6111, ext.n4267; fax: 1-514-343-2334. E-mail address: [email protected] (A. Demers).

By far, most studies have attempted to understand campus drinking based on individual-level variables. Student drinking patterns have been related to (1) sociodemographic characteristics such as gender, religiosity, ethnicity and marital status (Berkowitz & Perkins, 1986; Brennan, Walfish, & AuBuchon, 1986a; Prendergast, 1994; Saltz & Elandt, 1986), (2) psychological factors such as personnality, expectancies, attitudes, beliefs and motivation (Klein, 1994; O’Hare, 1998; Prendergast, 1994; Schall, Kemeny, & Maltzman, 1992), (3) child and youth development and family background (MacDonald, Fleming, & Barry, 1991), (4) peer-influence (Brennan, Walfish, & AuBuchon, 1986b; Martin & Hoffman, 1993), and (5) individual experiences of university life such as the perception of the campus drinking culture, involvement in social activities and living arrangement (Brennan, Walfish, & AuBuchon, 1986b; Gfroerer, Greenblatt, & Wright, 1997; Gliksman, Newton-Taylor, Adlaf, & Giesbrecht, 1997; Igra & Moos, 1979; O’Hare, 1990; Perkins & Berkowitz, 1986;

0277-9536/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved. PII: S 0 2 7 7 - 9 5 3 6 ( 0 1 ) 0 0 2 5 8 - 1

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Perkins & Wechsler, 1996; Wechsler, Dowdall, Davenport, & Castillo, 1995). Some have attempted to assess the impact of ecological campus factors on individual drinking despite inferential difficulties (Bell, Wechsler, & Johnston, 1997; Chaloupka & Wechsler, 1996). The statistical models employed by most studies investigating student drinking patterns implicitly assume that the sole influences on drinking behaviour are individual traits and that drinking occasions are fairly invariant within individuals. These assumptions are generally unfounded. Indeed, although heavy drinking episodes are prevalent among university students, not every episode is excessive. The issue of occasion and individual drinking heterogeneity is long-standing. As suggested by Harford (1979), ‘‘the consumption of alcoholic beverages is situationally specific, rather than a trans-situational property of specific individuals’’ (p. 289). Drinking occurs in a variety of situations that are normatively marked. Moreover, as noted by Bacon (1957), ‘‘the rules and procedures are on occasion rather specific, but also show enormous variability so that a given individual may follow one set of rules with his family, another with business or professional associates, and a third on holiday occasiony.’’ (p. 179–180). Hence, it might be expected that the variation in drinking is, at least in part, related to the drinking setting. The drinking situation Individuals do interact with the social environment in which they belong. Sociologically, the drinking setting can be seen as the environment in which the act of drinking occurs. Each setting carries its own set of rules and norms regarding drinking in terms of normaldeviant drinking (appropriateness of drinking) as well as in terms of beverage choice (form of drinking). These are reinforced through social interaction, and thereby normatively regulates the alcohol intake (Klein & Pittman, 1990; Simpura, 1991). Arguably, the apparent relationship between setting and alcohol intake is an artefact of a self-selection process, i.e., heavy drinkers are more likely to find themselves in heavy drinking situations. However, self-selection cannot be the sole determinant because the alcohol intake of any given individual is not invariant across drinking events. Thus the self-selection hypothesis cannot explain the variability in the individual drinking in different settings. Furthermore, it has been clearly established, particularly by research on the modelling of alcohol consumption, that a social influence process is at play in drinking (Quigley & Collins, 1999). Studies assessing situational influences related to student drinking remain rare and underdeveloped. Nevertheless, the results of these studies suggest that student drinking is related to the setting of the drinking

occasion, such as why, where, when and with whom students consume alcohol. Students drink more in bars, in group settings, particularly at large parties, and in same-sex groups (Harford, Wechsler, & Rohman, 1981; Perkins & Berkowitz, 1986; Rosenbluth, Nathan, & Lawson, 1978). Clapp, Shillington and Segars (2000) reported that binge drinking occasions occur mainly on Saturday, with friends, in the absence of partners or spouse, in bars as well as in private homes, on dates or socializing and in parties. Harford et al. (1981) suggested that the usual decline in student drinking during college may be related to changes in setting: as students move from group drinking to more intimate settings, they seem to reduce their consumption. Finally, contextual gender differences show that women are more likely than men to drink in family and in restaurant settings (O’Hare, 1990), whereas men drink in a wider range of activities and locations than do women (Biber, Hashway, & Annick, 1980). The relationship between drinking setting and situational consumption has also been shown among the general population. As for university students, research has stressed the importance of the symbolic meaning, physical, temporal and relational dimensions of the setting, on the situational alcohol intake (Clark, 1984; Demers, 1997; Harford, 1983; Hennessy & Saltz, 1993; Simpura, 1984, 1987; Single & Wortley, 1993; Sykes, Rowles, & Schaefer, 1993). Previous studies contributed substantially to our understanding of how people drink in settings in which alcohol is commonplace. They provided a thorough description of drinking patterns in various interpersonal environments such as the group size and the group composition (Hennessy & Saltz, 1993; Rosenbluth et al., 1978; Sykes et al., 1993). They also examined the role of individual characteristics in predicting the level of consumption in various settings (Harford, 1979; Simpura, 1984, 1987; Single et al., 1993). Even though they all acknowledge that drinking patterns are the results of interactions among setting and individual, they treated the drinking situations and the individuals at one single level of analysis. When treating individuals as the unit of analysis, they ignore the variation due to the occasion. This can be resolved crudely by studying a single occasion (most recent occasion approach), but again this assumes occasion factors to be invariant. On the other hand, when treating occasion as the unit of analysis, they ignore individual variation. This is indeed problematic given the socio-ecological conception of health behaviours, which argues that similar types of people may not behave in the same way under different settings. The major contribution of this study will be to simultaneously assess the predictive values of individual characteristics and setting characteristics on drinking in a multilevel approach. Using a multilevel modelling of the data to disentangle the contribution of the individual factors and of the

A. Demers et al. / Social Science & Medicine 55 (2002) 415–424

situational factors will represent more adequately the determinants of the drinking act (Hox, 1994). Bridging individual and situational factors: a multi-level model From our perspective, alcohol intake per occasion is best viewed as a function of both individual and situational characteristics. Therefore, alcohol intake on a given occasion might vary according to the setting in which drinking takes place as well as according to the individual’s characteristics. In this study, drinking situations and individuals are conceptualized as hierarchical relations in which drinking occasions are nested within the individual, and both the setting of the occasion and the individual characteristics determine the quantity of alcohol consumed. Although the most common application of multilevel models is with nested organizational or geographical structures, such as students within schools, multilevel models can also analyse data that are nested within individuals, such as repeated measures and multiple responses (Duncan, Jones, & Moon, 1996). Situational factors are conceptualized as the primary determinants of per occasion intake, that is, explaining variations between individuals as well as between various drinking settings (within individual or between occasions variation). Individual factors are conceptualized as secondary determinants of individual drinking patterns. Defined at a higher level, individual factors may only explain residual variance between individuals, as these factors remain constant for a given individual despite the setting in which he/she drinks. These factors may also modify the relationship between drinking setting characteristics and per occasion alcohol intake. A full theoretical model might include interaction effects to capture the complexity of the interwoven action of situational and individual factors. However, given the scarcity of previous research and the exploratory nature of this study, the main contribution of this paper will be firstly to disentangle and estimate the relative contribution of the setting and of the individual levels on drinking and, secondly, to determine the direct effect of situational and individual characteristics. However, as gender is a major determinant of drinking behaviour (Engs & Hanson, 1990; Wilsnack & Wilsnack, 1997), the interactions between gender and the other factors will be explored.

Method Sample The data analyzed in this paper are based on a hierarchical structure of drinking behaviour. From a

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sample of university undergraduate drinkers, 26,348 drinking occasions (level 1), nested within 6,850 individuals (level 2) were analysed. Each respondent provided information for up to five drinking occasions, defined as the five most recent occasions since the beginning of the academic year (i.e., over an 8 to 12 week period). These data were derived from the Canadian Campus Survey (CSS), a mail survey conducted between October 30 and December 15, 1998. In total, the data are based on undergraduate students enrolled in full-time studies at 18 of the 49 accredited Canadian universities (16 universities were derived from probability sampling and two universities were self-selected (buy-in)). One thousand students were randomly selected, from each university. Eighteen thousand questionnaires were mailed, of which 17,366 were deemed eligible mailings (ineligible mailings included incomplete and foreign addresses). Four mailings were employed during a fiveweek period, beginning October 30, 1998 (a questionnaire, a reminder card, a second questionnaire, and a second reminder card). Questionnaires were accepted until December 15, 1998. To enhance the response rate, lottery incentives were offered. A total of 8,864 eligible and useable completions were returned, for a 51% student completion rate. Of those, 83% (n ¼ 7360) reported drinking since the beginning of the academic year. After excluding cases with missing data and solitary drinking occasions, 6,850 drinkers and 26,348 drinking occasions (on average 3.85 occasions per drinker) remained in the analysis. To evaluate for potential non-response bias, we compared responses between early and late responders, based on the premise that non-respondents are more similar to late respondents than early respondents. These analyses indicated no differences between early and late responders for the major demographic factors. As well, comparisons between the CCS98 sample and a subsample of 1,000 undergraduates derived from the 1996 National Population Health Survey (Canada’s largest national health survey of 44,439 respondents) revealed no significant differences for sex, age and frequency of alcohol use. Measures The outcome variable is alcohol intake per occasion (level 1). For each occasion, respondents were asked ‘‘On this occasion, how many drinks of the following alcohol beverages (glasses of beer, wine, spirits) did you have?’’. Respondents were provided with information on the equivalence of one consumption for each beverage type (one beer of 341 ml; one glass of wine of 150 ml; 45 ml of spiritual; one cooler of 341 ml). For each beverage, the answers could range from 0 to 99. The total intake per occasion was obtained by summing beer,

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wine and spirit consumption. To reduce skewness, a ceiling of 12 was used for each beverage (which occurred in 4.1% of the occasions) and the total intake score was log-transformed. The situational characteristics (level 1) were measured by ten variables (22 regressors). For each drinking occasion, respondents were asked to specify the following: the circumstance in which drinking occurred (party, get together, non-specific, other); whether food (a meal) was consumed (yes, no); the location where most of the drinking took place (on or off campus; private location, restaurant, bar/disco/pub, other); the day of the week (6 dummy variables); the number of drinking partners (one, two or three, four to nine, ten or more); the gender composition of the group (gender-mixed, non-mixed); the student composition of the group (mainly student, not mainly student); whether the respondent’s partner or spouse was present (yes, no); the relationship of group members to the respondent (mainly family members, friends, acquaintances and others). The individual characteristics (level 2) were represented by seven variables (8 regressors): gender, average weekly drinking frequency, perceived campus drinking norms, importance of academic-oriented activities, importance of recreational-oriented activities, year of study (first year vs others) and living arrangement. *

*

*

The average weekly frequency is based on the question ‘‘How often, on average, did you consume alcoholic drinks since September (i.e., the beginning of the academic year)? The response categories (every day, 4–6 times a week, 2–3 times a week, once a week, 1-3 times a month, less than once a month) were transformed into number of drinking occasions per week (respectively, 7, 5, 2.5, 1, 0.5, 0.2). The campus drinking norms is a score derived from four five-point Likert items (strongly disagree (0) to strongly agree (4)). The items were: students here admire non-drinkers (the reversed score was used for this item); it’s important to show how much you can drink and still hold your liquor; you can’t make it socially in this university without drinking; drinking is an important part of the university experience. The mean score of these items was used, and the scores could range from 0 to 4, with zero indicating weak drinking norms and four indicating strong drinking norms. The importance of academic and recreationaloriented activities scores were derived from eight activities based on the following question ‘‘How important is it for you to participate in the following activities’’. Responses were based on a four-point Likert scale, from not very important (1) to very important (4). The eight items were subjected to a principal component analysis in order to establish a reduced number of underlying factors. The analysis

*

revealed two factors that explained 52.7% of the variance. Importance of academic-oriented activities was represented by five items (arts, academics, students associations, cultural/ethnic/religious and politics activities), whereas importance of recreational-oriented activities was represented by three items (parties, athletics and recreational activities). The mean score of the items was used, and the scores could range from 1 to 4, with 1 indicating low importance given to activities on campus and four indicating high importance. The internal consistency of the two composite measures, assessed with the Cronbach’s alpha, were 0.71 for the academicoriented activities and 0.64 for the recreationaloriented activities. The living arrangement is a three category variable: student residence (which in Canada is at 93% managed by universities and 7% are by fraternity or sorority); family housing; independent housing (which included students living by their own alone, with friends or with a partner).

Frequency distributions of the sample for the variables included in the analyses are presented in Table 1. Analyses The goal of our analysis is to decompose the variance in alcohol intake per occasion between drinking situation and individual characteristics. Because drinking occasions are nested within individual, we employed multilevel modelling to estimate firstly the variance deriving from the situational level (level 1) and the individual level (level 2), and secondly, to investigate characteristics of occasions and of individuals that may affect the alcohol intake (Bryk & Raudenbush, 1992; Goldstein, 1995; Snijders & Bosker, 1999) (Formalization is presented in Appendix A). We employed iterative generalized least squares (IGLS) (Goldstein, 1986, 1995) provided by MLwiN software (Rasbash et al., 1999) for parameter estimation. IGLS views the likelihood function as depending on random coefficients and fixed regression coefficients, in which the latter are treated as known quantities when computing the random parameters. Since data are weighted for sampling characteristics, robust sandwich estimators for standard errors are computed (Goldstein, 1995) for fixed (regression) coefficients. Fixed coefficients are tested with normal deviate two-tailed significance reported at po0:01: For variance parameters, likelihood ratio tests are applied with halved p-values (po0:01 reported) (Snijders & Bosker, 1999). Proportion of variance explained at each level (R21 ; R22 ) are computed using Snijders and Bosker (1994) formulas.

A. Demers et al. / Social Science & Medicine 55 (2002) 415–424 Table 1 Individual and contextual descriptors

to their respective levels. Model four (Eq. (4)) is a full conditional model, including both level 1 and level 2 variables. This model allows to observe how the effect of situational characteristics are modified by the inclusion of individual characteristics in the model and vice versa. Model five is a parsimonious model retaining only significant main effects of the variables and the significant interaction terms with gender (po0:01). This model was thoroughly evaluated with regards to statistical assumptions. No problem of multicollinearity was detected, nor were there found to be any departures from assumptions of normality, linearity and homoscedasticity of variances.

% (weighted) Situational characteristics Circumstance Party Get together Other circumstances No particular circumstance Drink with meal Location off campus Location Home Restaurant Disco/Bar Other Day of the week Sunday Monday Tuesday Wednesday Thursday Friday Saturday Group size 1 person 2–3 persons 4–9 persons 10 or more Mixed gender group Univ. students group Presence of partner Type of relationship Family Friends acquaintances/others Individual characteristics Males Living arrangement Student residence Off-campus/on one’s own Family housing First year students Academic-oriented activities Recreational-oriented activities Perception of campus drinking norms Weekly drinking frequency since Sept

N=26 348 33.8 32.1 18.2 16.0 55.7 83.8 42.1 8.9 39.2 9.8

Results

6.1 3.3 4.7 6.6 13.7 28.4 37.1 12.5 23.8 37.9 25.8 78.5 60.1 34.7 10.8 74.4 14.8 N=6850 42.8 19.2 39.0 41.7 24.9 MEAN 1.9 2.1 1.7 1.1

419

(s.d.) 0.6 0.7 0.7 1.2

Our analysis strategy consists of five regression models. The first one includes the constant only (Eq. (3)) to estimate the distribution of the variance between each level (null model). The second model estimates only level 1 independent variables (situational model), whereas model three estimates only level 2 independent variables (individual model). The situational and individual models allow us disentangling the effect of each level on the outcome variable, conditional

The results of the multilevel analyses are presented in Table 2. The null model (Model 1) indicates an overall mean alcohol intake per occasion (log) of 1.48 (s.e.=0.59), i.e. 4.4 drinks per occasion in original units, and finds sizeable variance for both setting and individual characteristics. The intraclass correlation is 0.49, indicating that 49% of the variance in alcohol intake per occasion is between individuals and 51% is between occasions. Model 2 evaluates the effects of the situational characteristics (level 1). Gender composition and spouse or partner presence had no significant effect on alcohol intake. All other situational variables are significant predictors of alcohol intake. The situational characteristics explain 15.6% of the variance at the situational level (level 1) and 15.4% at the individual level (level 2). Model 3 evaluates the effects of the individual characteristics (level 2). Living arrangement had no significant effect on alcohol intake. All other individual characteristics are significant predictors of alcohol intake, and explain 11.3% at the situational level and 18.1% of the variance at the individual level. Model 4 is the full conditional model, including both situational (level 1) and individual (level 2) variables. The inclusion of level 2 variables into the model does not modify the effect of the level 1 variables whereas the effects of the living arrangement and the year of study variables (level 2) have been modified by the inclusion of level 1 variables. This model explains 25.2% of the variance at the situational level and 30.7% at the individual level. A transitional step before estimating the final parsimonious model (model 5) consisted of testing the full model (model 4) including the significant interactions with gender (w2 (df=53)=6160.100). Model 5, is the final model that retains only variables significant at po0:01: As seen, the exclusion of the nonsignificant variables did not significantly change the fit of the model (w2 (df=18)=0.490, p ¼1.00). With respect

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Table 2 Multilevel estimates for alcohol intake per occasion (logarithmic). Regression coefficients and t-values Model 1

Model 2

Estim. t Fixed parameters Level 1 (situational) Constant

Estim. t

1.481 246.83

Circumstance (ref: party) Get together Other circumstances No particular circumstance Drink with meal (ref: no) Location on/off campus (ref: on) Location (ref: home) Restaurant Disco/Bar Other Day of the week (ref: Saturday) Sunday Monday Tuesday Wednesday Thursday Friday Group size (ref: 10+) 1 person 2–3 persons 4–9 persons Mixed gender gr. (ref: non-mixed) U students group (ref: no) Presence of partner (ref: no) Type of relationship (ref: family) Friends Acquaintances/others Level 2 (individual) Gender Academic-oriented activities Recreational-oriented activities Freq. of consumption since Sept. Percept. campus drinking norms Living arrang. (ref: family housing) Student residence Off-campus/on one’s own First year (ref: not first year) Random parameters s2m (individual) s2e (situational) Statistics Deviance Chi-square df p R21 ðsituationalÞ R22 ðindividualÞ

Model 3

Model 4

Estim. t

1.508 82.11

Estim. t

1.134 45.36

39533.150 F F F

Gender interaction

Estim

Estim

t

42.86

0.158 19.75 0.136 15.11 0.234 23.40 0.034 4.86 0.061 6.78

0.159 22.17 0.159 0.140 15.55 0.141 0.248 24.80 0.246 0.036 6.00 0.036 0.069 7.67 0.069

22.71 15.67 24.60 6.00 7.67

0.170 15.45 0.034 4.86 0.016 1.45

0.162 14.73 0.136 0.037 5.28 0.038 0.020 2.00 0.029

10.46 0.092 4.75 0.008 2.23 0.025

0.137 11.42 0.159 9.94 0.066 5.08 0.078 6.50 0.048 5.33 0.021 3.00

0.146 12.17 0.146 0.175 10.94 0.175 0.080 6.15 0.081 0.088 7.33 0.088 0.054 6.00 0.056 0.022 3.14 0.023

12.67 10.94 6.23 7.33 6.22 3.28

0.316 26.33 0.218 24.22 0.095 11.87 0.000 0.00 0.030 4.28 0.004 0.57

0.308 25.67 0.254 0.210 23.33 0.166 0.089 11.12 0.074 0.001 0.12 0.019 2.71 0.019 0.007 1.00

19.54 0.157 15.09 0.123 8.22 0.039

0.188 17.09 0.121 10.08 0.111 0.133 0.155 0.096 0.062

p¼ 0.00 0.00

0.144 0.148

34970.890 4562.260 22 0.00 0.156 0.154

p¼ 0.00 0.00

1.236 42.62

Main effects

1.243

0.194 17.64 0.122 9.38

0.169 0.177

Model 5

10.09 0.120 12.00 0.115 13.30 0.114 12.67 0.111 19.37 0.093 11.62 0.093 19.20 0.110 27.50 0.123 7.75 0.057 8.14 0.034

0.030 0.008 0.046

2.00 0.67 3.83

0.030 0.038 0.025

2.14 3.45 2.27

0.130 0.177

p¼ 0.00 0.00

0.111 0.148

p¼ 0.00 0.00

38174.910 1358.24 8 0.00 0.113 0.181

0.187 0.121

33542.290 5990.860 30 0.00 0.252 0.307

4.18 0.61 1.19

7.48 7.23 2.60

2.71

17.00 10.08 3.71 12.33 11.62 20.50 0.030 3.78 0.068

0.034 0.036

2.61 3.27

0.110 0.147

p¼ 0.00 0.00

33373.540 6159.610 35 0.00 0.257 0.312

t

3.33 4.53

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to the setting characteristics, this model finds that students consume more alcohol per occasion when they are at a party (as opposed to other drinking occasions), with meals, off campus, in a bar (or to a lesser extent at home than in a restaurant), with friends or acquaintances (as opposed to with family), on Saturday (followed by Friday and Thursday, while Sunday and Monday are the days when they drink the least), with larger groups. The effect of the group size is more marked for men than women. Regarding individual characteristics, as may be expected, men drink more than women. Alcohol intake per occasion is positively associated with the importance of involvement in recreational-oriented activities whereas it is negatively associated with the importance of involvement in academic-oriented activities. The more students perceive drinking to be the norm in university life, the more they drink per occasion. The effect of the university drinking norm is more noticeable for men than women. Students living in residence drink more compared to those living with their families. Finally, the more often students drink, the more they drink per occasion. The relationship between the frequency of drinking and the consumption per occasion is stronger for female than for male students.

Discussion This study examined the effects of individual factors, particularly the individual experience of university life, and of situational factors on alcohol intake per occasion. The hierarchical structure of our data, where drinking occasions are nested within individuals, allows us to conduct a multilevel analysis to disentangle the situational and individual effects. The drinking situation, why, where, when and with whom students drink, appears to have an important effect on situational alcohol intake. Some characteristics appear to act as predisposing factors for students to drink more. These include drinking at a party, in a bar/ disco, off campus, during the weekend, in a peer drinking-oriented environment such as in large group and with friends. As indicated by the interaction terms, the magnitude of the effect of the drinking locations and of the group size is greater for men than for women. These results are in line with previous studies (Harford et al., 1981; Perkins & Berkowitz, 1986; Rosenbluth et al., 1978). In this regard, our contribution is mainly to have shown that these characteristics are at play over and above the individual characteristics and the experience of university life. A few of our results regarding the characteristics of the drinking situation may seem counter intuitive. For instance, having a meal is generally associated with more moderate alcohol intake. However, our data revealed

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the opposite. This raises the possibility that eating and drinking in combination may have a different meaning for students. For the general adult population, the meal is probably the core of the drinking event, that is, drinking is done to accompany or enjoy a meal. For students, the meal may be part of a larger party setting where there is alcohol, music and dancing with friends. This may also explain in part why no relationship was found between the gender composition of the drinking group and the alcohol intake: drinking is probably largely a party-oriented activity (parties account for 34% of the drinking occasions), which usually is a mix of males and females. Another intriguing result is the absence of a relationship between the presence of the regular partner and alcohol intake, a relationship that many studies on students have found. These studies have shown that marital status is related to the drinking pattern (Saltz & Elandt, 1986; Wechsler et al., 1995). In addition, at least with respect to the general population, studies have highlighted the controlling role of the partner, particularly the wife’s control over her husband (Holmila, 1987; J.arvinen, 1991; Room, Greenfield & Weisner, 1991). There are three possible reasons for this different finding. First, our measure referred broadly to an intimate relationship that does not necessarily mean a marital relationship. Hence, the idea of responsibility that has been suggested to explain the lower consumption of married people is not necessarily involved in this intimate relationship. Second, the partner is likely to also be a student who drinks like a student, and who shares the same drinking sub-culture. It is unlikely that such a partner would try to control alcohol intake, and even if they were, the idea of ‘‘do as I say and not as I do’’ would probably not be a powerful message. Third, the influence of the partner is measured in a specific drinking setting and not, as in other studies, on the drinking pattern. Hence, it is possible that having a partner may impact on the alcohol intake by changing the circumstances in which students drink, or by reducing the frequency of drinking but not the amount consumed when they do. At the individual level, with respect to the individual experiences of university life, our results showed that the importance given to recreational-oriented activities, living in student residences or on your own are related to greater consumption. At the same time, those according more importance to academic-oriented activities drink less per occasion. Consistent with previous results (Brennan et al., 1986b; Chaloupka & Wechsler, 1996; Perkins & Berkowitz, 1986; Perkins & Wechsler, 1996), these findings suggest a pattern of social integration into university life, in which the university is invested with the properties of a milieu in which one lives and not just pursues intellectual activities, and is thus associated with heavier alcohol intake per occasion.

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Moreover, the more students perceive drinking to be the norm on campus, the more they drink, and the magnitude of this relationship is greater for men than for women. As suggested by Perkins and Wechsler (1996), perception of drinking norms may result in a self-fulfilling prophecy, in which students tend to act in accordance with their perceptions of the normative standards. A self-selection process may also be involved in which heavier drinkers are more likely to use the university as a living milieu, be integrated into the wet part of the university life and perceive drinking to be the norm on campus. Longitudinal data would be needed to clarify the nature of these relationships. With respect to the frequency of drinking, our results clearly indicate that those who drink more often also drink more when they do and this relationship is more marked for women than for men. This may reflect the impact of a greater integration into the non-intellectual part of the university life, or it may be due to a greater tolerance to alcohol, reflecting the start of a potential dependence process. Although it is hard to explain this result at this time, it does raise a further question that will need to be addressed: are people likely to drink more per occasion when they drink more often or is this relationship specific to students or young adults? Finally, although this study presents interesting findings that contribute to our understanding of why people drink more or less on a given occasion, its major contribution is to have shown that drinking behaviours may be conceptualized as sets of situated and interrelated events and to have assessed the relative weight of situational factors and of individual factors in this matter. The drinking setting appears to be as important as the individual characteristics in explaining how students drink: 51% of the variance in alcohol intake per occasion is at the situational level and 49% is at the individual level. The individual characteristics solely explained 11.3% of the variance at the situational level and 18.1% at the individual level whereas the situational characteristics solely explained 15.6% and 15.4% at the situational and individual levels, respectively. Together, they explained 25.2% of the variance at the situational level and 30.7% at the individual level, and the estimates at each level are not substantially changed by the inclusion of the other level. This clearly indicates the additive effects of the two levels. Despite the significance of our findings, drinking situations are complex events and this complexity is not fully captured in this study. More work need to be done to extend the understanding and improve the measurement of drinking situations. Moreover, the drinking setting may be seen as a whole, as a specific constellation of characteristics that appear together and contribute as a system to shape the individual’s drinking behaviour, rather than as the additive effect of a set of characteristics. Further analysis will be needed to explore this issue.

Finally, the cross-sectional nature of our design imposes severe limitations on inferences of causality. Do students adapt their drinking to the circumstances as water molds itself to the pitcher? Conversely, it may be argued that those who drink heavily are more likely to find themselves in settings that promote greater alcohol intake, to perceive the norms on campus as supportive of drinking and heavy drinking, and to participate more in recreational-oriented activities where they may find more opportunities to drink. The direction of this relationship can only be clarified through a longitudinal design. Nevertheless, the hierarchical design used in this study clearly shows that the alcohol intake of a given individual varies with the drinking situation, implying that students are not impermeable to their drinking environment.

Conclusion The analysis presented here indicates that the drinking situation has a substantial effect on alcohol intake. It is apparent from our findings that the individual cannot be conceptualized as an autonomous actor making selfgoverning decisions in a social vacuum. From a prevention perspective, the major implication of this study is that programs or policies aiming to reduce student drinking may be more beneficial if they address both individual and situational factors, concurrently or concomitantly. It is apparent from the data that programs exclusively focusing either on individual factors or on situational variables are doomed to have limited success because both sets of variables actively influence the amount that students drink on any given occasion. Finally, the multilevel modelling of student drinking may be improved by adding the academic milieu as a third level of analysis, which cannot be done in this study given the limited number of universities sampled (n ¼ 18). Recently, a few studies have used multilevel modelling to highlight the effect of the environment on drinking in the general population (Rice, Carr-Hill, Dixon, & Sutton, 1998; Twigg, Moon, & Jones, 2000). Each milieu may have its own set of rules, norms and culture regarding drinking. Some universities have developed strong alcohol policies to control drinking on campus whereas others are more tolerant in this regard; some departments or faculties are well known for their ‘‘wet culture’’ and others for their ‘‘dry culture’’. This may be captured in further surveys using a sample design by universities and departments. Adding this macro-level component will contribute to our understanding of drinking as a structurally determined social phenomenon and to break down the individualistic perspective that has dominated alcohol research and, more broadly, health-related behaviour research. It may

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allow us more easily moving forward in the emerging ‘‘health of populations’’ paradigm (Evans, Barer, & Marmor, 1994).

Appendix A Formally, we have a dependent variable Yij at level 1, with j ¼ 1yK level 2 (individual) and i ¼ 1ynj level 1 (drinking occasion). The equation for the situational level is written as: Yij ¼ b0j þ eij ;

ð1Þ

where b0j is the expected value (mean) for individual j and eij is the error term (residual) for situation i in individual j: b0j is treated as a random variable at individual level, so the individual equation level becomes: Y0j ¼ g00 þ m0j ;

ð2Þ

where g00 is the overall expected value (mean) and m0j is the error term (residual) for individual j: The substitution of (2) in (1) results in: Yij ¼ g00 þ m0j þ eij

ð3Þ

m0j and eij are assumed to be uncorrelated and follow a normal distribution with mean 0 and variances s2m ; s2e estimated by the data. The model described by Eq. (3) is called a variance component model and the residual variance provides the quantities to compute the intraclass correlation: ri ¼

s2m

s2m þ s2e

which measures the proportion of variance in alcohol intake attributable to individuals. Next, we add into Eq. (3) independent variables measured at the situation and individual levels. The general equation could be written as: Yij ¼ g00 þ g1p X1pij þ g2q Z1qjþ ðmj þ eij Þ;

ð4Þ

where X1 is a vector of p independent variables measured at the situation level and Z1 is a vector of q independent variables measured at the individual level. g1p and g2q are slopes for X1 and Z1 ; respectively. In Eq. (4), level 1 independent variables explain residual variance within and between individuals, while level 2 independent variables explain only residual variance between individuals.

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