Alcohol and Alcoholism Advance Access originally published online on March 14, 2007
Alcohol and Alcoholism 2007 42(5):448-455; doi:10.1093/alcalc/agm008
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Alcohol involvement in Swedish University freshmen related to gender, age, serious relationship and family history of alcohol problems
1 Clinical Alcohol Research, Lund University, Malmö University Hospital
2 Department of Clinical Sciences—Division of Psychiatry, Lund University, Lund University Hospital, Sweden
* Author to whom correspondence should be addressed at: Clinical Alcohol Research, University Hospital MAS, SE-205 02 Malmö, Sweden. Tel: +46 40 33 60 74; Fax: +46 40 33 62 03; E-mail: claes.andersson{at}med.lu.se
Received 26 July 2006; first review notified 7 October 2006; in revised form 30 January 2007; accepted 1 February 2007
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ABSTRACT |
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Aim: The primary aim of this study was to describe alcohol involvement in relation to gender and different age cohorts among freshmen at two Swedish universities. The secondary aim was to investigate whether the results were related to a likelihood of students being in serious relationships and/or had a first-degree relative with alcohol problems. Methods: Two complete cohorts of university freshmen at two homogeneous universities were asked to participate in an intervention study, and the results of the basic assessments are presented in this article. The following instruments were used: the Alcohol Use Disorders Identification Test (AUDIT), the Estimated Blood Alcohol Concentration (eBAC) and a shortened version of the Alcohol Expectancy Questionnaire (AEQ). Results: A total of 2032 (72%) freshmen agreed to participate. The mean AUDIT score was 8.8 (±4.9) for men and 6.0 (+4.0) for women, and there were high correlations between the AUDIT and other instruments. There were significant differences between different age groups for both men and women. Both genders were more likely to have AUDIT scores higher than the usual cut-off levels for high-risk interventions among those with first-degree heredity of alcohol problems, while those students in serious relationships were less likely to have AUDIT scores above the usual cut-off levels for high-risk interventions. Conclusions: This study reveals a high level of alcohol involvement among Swedish university freshmen. This is affected by age, gender, heredity of alcohol problems and serious relationships.
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Introduction |
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TOPABSTRACTIntroductionMaterials and MethodsResultsDiscussionReferences |
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In young adulthood, i.e. between adolescence and adulthood, alcohol involvement is found t be higher thn during any other period over the life-span course (Grant and Dawson, 1997
; Jackson, 1998). Among young adults there are large variations and only a subset exhibits heavy drinking consistently across this time period (Schulenberg et al., 1996). For most people, heavy drinking peaks around age 21, and then gradually falls to a more moderate level (Johnston et al., 2002; Muthén and Muthén, 2000). While these individuals mature out from heavy consumption, others continue to drink at moderate to heavy levels (Fillmore, 1988, Zucker, 1987). There are consistent findings that drinking in young adulthood is a decisive factor in adult drinking behaviour (O'Neill et al., 2001), so it is valuable to analyse how alcohol involvement interacts with individual and environmental factors in order to predict drinking patterns in young adults.
Definitions of alcohol involvement are mainly divided into three broad domains. (i) Alcohol consumption refers to the frequency at which alcohol is consumed and/or the quantity consumed over a given time. (ii) Alcohol-related consequences refer to a variety of negative life events and consequences that arise from drinking. (iii) Alcohol dependence refers to signs and symptoms signifying the importance of alcohol consumption in the life of the drinker (Babor et al., 2001; Brennan et al., 1986).
Although there are multiple determinants of alcohol involvement in young adults, this article focuses on four broad areas in relation to university freshmen: gender, alcohol expectancies, family history of alcoholism, and serious relationships.
The alcohol patterns of young adults vary according to gender in the same way as in the general population (O'Malley and Johnston, 2002). In general, men drink more alcohol and experience more and different kinds of alcohol-related problems, while a given dose of ethanol produces a higher blood-alcohol concentration (BAC) in women (Plant, 1990). To our knowledge, gender divergences while in the age of peak alcohol involvement, have not been reported previously.
Alcohol expectancies are an individual factor that have an impact on both initiation and maintenance of drinking (Cox and Klinger, 1988). Regardless of the nature of expected outcome, positive expectancies are more predictive of drinking and problematic alcohol use than negative expectancies (Leigh and Stacy, 2004).
A positive family history of alcohol problems has been shown to be a risk factor for problem drinking and the development of future alcohol problems in individuals (Hawkins et al., 1992; Sher et al., 1991). However, results for young adults are mixed (George et al., 1999; Sher et al., 1991). These differences are mainly attributed to study design and whether a broad or narrow definition of heredity has been used (Jackson et al., 2006). The most convincing data relates to settings where a family history of alcohol problems has been monitored prospectively. The main finding from these studies is that individuals with a family history of alcohol problems are less likely to mature out from heavy consumption in young adulthood (Chassin et al., 2002; Jackson et al., 2001). Approximately 20% of US college students have a positive family history of alcohol problems (Perkins, 2002).
Social influences are probably one of the strongest correlates of drinking (Borsari and Carey, 2001). The establishment of serious relationships is particularly important, and the transition into marriage is associated with a reduction in alcohol involvement (Curran et al., 1998; Leonard and Mudar, 2003). Previous studies in college settings have not reported on the significance of a broader definition of serious relationships. This is important since only a few college students are married.
Besides the individual factors given above, the university is considered to be an important environmental factor influencing alcohol involvement in young adults. US studies have identified college students as a population at high risk for heavy consumption and negative consequences (Wechsler et al., 1994; Task Force on College Drinking, 2002) and this also applies in Sweden (Bullock, 2004). Today, about half of all young adults enter university (Swedish National Agency for Higher Education, 2005), which makes students an important sub-population. College students are more likely to have higher prevalence rates of alcohol use and higher rates of heavy use, but lower rates of daily drinking when compared to their non-student peers (Johnston et al., 2002; O'Malley and Johnston, 2002; Slutske et al., 2004) However, a recent Swedish study comparing students and non-students reported no differences in total consumption or in drinking pattern between the two groups (Eriksson and Olsson, 2004).
The primary aim of this study is to describe alcohol involvement in relation to gender and different age cohorts among freshmen at two Swedish universities. The secondary aim is to investigate whether findings are related to serious relationships and/or having a first-degree relative with alcohol problems.
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Materials and Methods |
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Design of the study
Out of fourteen Swedish universities, two universities that were homogeneous (given below, is a study sample) were selected for participation in a 4-year research project. The aim was to compare one cohort of freshmen that underwent extensive, annual alcohol and stress interventions with the development in these areas at the other university, where the students were only offered minimal interventions (i.e. normative feedback). In this study, the basic assessments will be presented.
Sample
Luleå Technical University in the north and Växjö University in the south of Sweden represent two recently founded institutions of higher education that have similar characteristics and curriculum. Both universities are about the same size and are situated outside the city centres, where halls of residence, university departments and social facilities for students are concentrated into a compact area. Educational programmes are offered in a variety of disciplines ranging from technology, economics and health, social sciences to education and the humanities.
In autumn 2002, all freshmen that had been accepted onto a university course exceeding 3 years in length were invited to participate in the research project. Written information was sent when they had been accepted into the university. During the first weeks at university, all educational programmes were scheduled for baseline assessments. Prior to the assessment, all freshmen were given both oral and written information about the study and acceptance was confirmed by their signature in the questionnaire.
The Research Ethics Committees of Lund University (for Växjö University) and Umeå University (for Luleå Technical University) approved the study.
Instruments
Alcohol Use Disorders Identification Test (AUDIT) is a screening questionnaire that consists of 10 items, each giving 0–4 points so the maximum score is 40. The items cover the three domains: ‘alcohol consumption’ (items 1–3), ‘signs of alcohol dependence’ (items 4–6) and ‘alcohol-related harm’ (items 7–10). A ‘standard drink’ is defined as 12 g of 100% alcohol/day (+20 (Babor et al., 2001). In the psychometric evaluation of the Swedish translation of the instrument, the Cronbach alpha coefficient of the total AUDIT score has been calculated to 0.82 (Bergman and Källmen, 2002), and in this study this internal consistency score was 0.80.
When the AUDIT was designed, 
8 points was considered as the standard cut-off point for positive screens in both men and women (Babor et al., 1989; Saunders et al., 1993). Due to lower sensitivity and higher specificity in women compared with men, the recommended cut-off point was later lowered to 6 in women. Usually, 8 for men and 6 for women are considered as positive screens (Reinert and Allen, 2002). Recently NIAAA (2005) lowered their recommendations to 4 for women. In clinical management, persons who score in the low positive range (8–15) are recommended a brief intervention. In addition, individuals in the intermediate range (16–19) should receive regular monitoring, while those in the high range (20–40) should be given diagnostic assessment and treatment (Room et al., 2005).
In this article, the AUDIT scores are presented as summarized total mean scores and by domains (i.e. subscales).
Alcohol Expectancy Questionnaire (AEQ) (Brown et al., 1987) is an empirically derived self-reporting form assessing various anticipated experiences associated with alcohol use. AEQ originally consisted of 90 items with six subscales, but in this study is reduced to 18 items, three items each of the six dimensions, assessing the same domains of alcohol reinforcement expectancies. This version has been translated and developed for educational purposes at our department. In this study, the Cronbach alpha coefficient of the shortened AEQ was calculated at 0.75. In the results, AEQs are presented as summarized total mean scores.
Estimated Blood Alcohol Concentration (eBAC) is a self-assessment questionnaire in which the individuals are asked to record their last pleasant drinking occasion (number of standard drinks and the time interval over which they were consumed, as well as their gender and weight). On the basis of this data, the eBAC was calculated, in milligrams of alcohol per 100 ml of blood (%). This method for estimating BAC was obtained from the National Highway Traffic Safety Administration, US Department of Transportation (1994). In this study, the students were asked to remember their last pleasant drinking occasion and record their alcohol consumption at that occasion. This approach was considered to measure a typical optimal drinking occasion, rather than one of peak consumption.
The results of the above instruments are analysed in relation to gender and age. The latter is further divided into seven 2-year age categories (18–19, 20–21, 22–23, 24–25, 26–27, 28–29 and above 30 years of age).
The freshmen were also asked whether they were in a serious relationship (i.e. ‘going steady’ or married), and whether they had a positive family history of alcohol problems (defined here as first-degree relatives—parents and/or siblings). The last question was derived from the Brief Drinker Profile (Miller and Marlatt, 1987)
Statistics
The software used for statistical analysis was SPSS 11.5 for Windows. Scale reliability analyses were performed with Cronbach alpha. Spearman rank correlations were used to calculate the interaction between results of different instruments. A Chi-square test was used to analyse differences in proportions. Comparisons of ratings between subgroups were carried out with Mann–Whitney and Kruskal–Wallis non-parametric tests. ANOVA analyses of variance were used to adjust for age differences when analysing the effects of heredity and serious relationship. A statistical multivariate analysis was performed to gain more understanding of the associations between usual cut-off levels in the AUDIT (men 8, women 6) and age, alcohol expectancies, eBAC, heredity and serious relationships. Effect measure modification by gender was tested by using the likelihood ratio test when two-way interaction terms were included in the logistic regression model. A P-value of <0.05 was regarded as statistically significant.
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Results |
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A total of 2032 out of 2840 freshmen (72 %) responded to the baseline assessment. More women participated than men (75% vs 68%, P = 0.000). The mean age of all freshmen entering university education was 23.6 ± 5.5 years. Participants were younger than non-participants (23.5 ± 5.4 vs 24.6 ± 6.3, P = 0.000). The women that took part in the study were older than the men (Table 1).
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There were some differences between the freshmen at the two universities. Both men and women at Växjö University reported higher Alcohol expectancies compared with freshmen at Luleå Technical University (men 8.0 ± 3.3 vs 7.3 ± 3.3, P = 0.001 and women 6.6 ± 3.3 vs 5.8 ± 3.0, P = 0.000). Men at Växjö University also had higher AUDIT scores than men in Luleå (9.5 ± 5.1 vs 8.2 ± 4.7, P = 0.000). These differences do not affect the results of the present study and will not be discussed further in this article.
Men have higher total AUDIT scores than women, and in all domains. Gender differences were also noted in alcohol expectancies and estimated blood alcohol concentration (Table 1).
Seventy-five percent of the males and 66% of the women drink on a monthly basis, and 13% of the men and 8% of the women drink more than twice a week. Sixteen percent of the men and 4% of the women consume more than six drinks at least once a week. Three percent of the males and four percent of the females describe themselves as non-drinkers as defined by AUDIT item number one (not tabulated).
AUDIT scores in relation to usual cut-off levels (men 8, women 6) reveal a considerable risk concerning alcohol habits in both men and women. Fifty-six percent of males and 49% of females scored above the usual cut-off levels and 73% of the women are considered positive screens when using 4 as the cut-off level. Forty-six percent of the men and 26% of the women scored between 8 and 15. Seven percent of the men and 2% of the women scored between 16 and 19 and 3% of the men and 1% of the women have an AUDIT score above twenty.
Total AUDIT and eBAC showed significant correlation (r = 0.570) and this correlation is significant both for men (r = 0.547) and women (r = 0.605). There is also a strong correlation between AUDIT and alcohol expectancies (r = 0.549) for men (r = 0.521) and for women (r = 0.513). The correlation between eBAC and alcohol expectancies is slightly lower (r = 0.357), and this applies to both men (r = 0.360) and women (r = 0.344) (not tabulated).
AUDIT in different age groups
Dividing the population into 2-year age categories, men have higher total AUDIT scores than women, regardless of age, and also in the single domains with the exception of early ages in scores of dependency (18–21 years of age) and harmful alcohol use (18–19 years of age). As illustrated in Fig. 1 there is also a gender difference regarding the age groups that have the highest score. In men, the highest mean score is in the 24–25 age group for total AUDIT (10.5 ± 5.4), as well as for the dependency domain (1.1 ± 1.2) and harmful alcohol use (3.1 ± 3.1), while the highest mean score for the consumption domain is found among men 22–23 years of age (6.5 ± 2.2). In women, the total AUDIT (7.1 ± 4.3) as well as the single domains (consumption 4.7 ± 2.0, dependency 0.6 ± 1.0, and harm 1.8 ± 2.3) is greatest at 20–21 years of age. In both men and women there are significant differences between age categories in the total AUDIT as well as in the single domains.
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Alcohol expectancies in different age groups
In alcohol expectancies, in all age categories, men score significantly higher compared with women with the exception of the 18–19, 24–25 and 28–29–year-old groups. Among men, the highest alcohol expectancies are found in the 24–25 age group (8.0 ± 3.4), while the highest score for women is among freshmen aged 18–19 (6.4 ± 7.3). Both men and women show significant differences between different age categories.
Estimated blood alcohol concentration in different age groups
Even though men have higher total scores than women for eBAC, there are no significant differences between men and women in different age group categories. The highest mean eBAC is found at 22–23 years for men and at 20–21 years for women. In both men and women, there are significant differences between the age categories (P = 0.000).
Serious relationship
Thirty-eight percent of the men and 61 percent of the women were in a serious relationship (Table 1). These students are older compared with the others (Table 2), and since there are considerable age differences in measurements used, analyses of the effects of a serious relationship were adjusted for age. Doing so, it was observed that those in a serious relationship were found to score lower in the AUDIT compared with others. This difference is valid for all domains except consumption among women. However, being in a serious relationship has no impact on alcohol expectancies or eBAC (Table 2).
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Heredity
Nine percent of male and 14% of female freshmen are first-degree relatives to parents or siblings with alcohol problems (Table 1). These students are older compared with the others. Only five of the first-degree relatives were abstainers. Analyses adjusted for age differences reveal that male first-degree relatives score higher on alcohol expectancies and the AUDIT, including domains for dependency and harmful alcohol use, while female first-degree relatives score higher only on harm compared with others. A first-degree relationship was not associated with eBAC (Table 3).
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Multiple logistic regression analyses
Multiple logistic regression analyses were performed to investigate the associations between scoring above the usual AUDIT cut-off levels (men
8, women 6) as a dependent variable, and the following independent variables: gender, in young adulthood (18–25 years), high alcohol expectancies and eBAC, being a first-degree relative to someone with alcohol problems and not in a serious relationship (Table 4). This was calculated for the total cohort and for men and women separately. All independent variables were associated with an increased risk of scoring above the usual AUDIT cut-off levels. Not being in a serious relationship seemed to be a stronger effect among women (OR 2.2; 95% CI 1.6–3.1) than among men (OR 1.4; 95% CI 1.0–1.9). Interaction between not in a serious relationship and gender is significant (P-value = 0.04). No other interaction with gender was found significant (P-value 0.13). In women, the greatest probability was found among those not in a serious relationship and in 18- to 25-year-olds (2.2 and 2.0 respectively). In men, the greatest probability was found among those having first-degree relatives and in 18–25-year-olds (1.7 and 1.6 respectively).
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Discussion |
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TOPABSTRACTIntroductionMaterials and MethodsResultsDiscussionReferences |
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This study reports a generally high level of alcohol involvement among participating freshmen. The prevalence of previous monthly alcohol consumption corresponds to US data where about 70% of full-time college students reported to be drinking (O'Malley and Johnston, 2002
), but is somewhat lower than a previous Swedish study, where about 90% reported to be drinking in the previous month (Bullock, 2004). In relation to the usual cut-off levels, this study also corresponds to previous studies where about half of the young adults screen positive (Fleming et al., 1991; Granville-Chapman et al., 2001). According to given recommendations, about half of all college freshmen should be given a brief intervention for harmful or hazardous alcohol use (Room et al., 2005).
Besides the high prevalence of alcohol involvement, the first main finding is that there are large variations between freshmen of different ages and variations according to gender, as to the age category at which the mean alcohol involvement peaks. Younger students score higher than older students, and women peak earlier when compared with men. Differences by age have been reported previously (Grant and Dawson, 1997; Jackson, 1998; Johnston et al., 2002; Muthén and Muthén, 2000; Schulenberg et al., 1996), but this study analyses by gender in smaller age categories, thereby contributing by describing gender divergences in peak alcohol involvement. To our knowledge, this has not previously been reported.
Another important finding is regarding heredity. First-degree history of alcohol problems increases the probability of scoring above the usual cut-off levels of traditional high-risk interventions in both genders (Reinert and Allen, 2002). The association to a family history of alcohol problems is more pronounced in men compared to women and is mainly related to higher scores in alcohol-related harm and signs of alcohol dependency rather than consumption, compared to those subjects with no relatives with alcohol problems. Females with alcoholic parents also report more alcohol-related impairment without scoring higher on consumption.
The third finding is that serious relationships have an impact on alcohol involvement for both men and women regardless of age. The total AUDIT score for women, including all domain scores, is lower for those in a serious relationship. The results for men are not that pronounced, and the influence is only reflected in the total AUDIT score and the domain of alcohol dependence, even though slight indications of an association are found in all levels. These findings are new since lower alcohol involvement previously has been found to be associated with marriage (Curran et al., 1998; Leonard and Mudar, 2003). The term ‘serious relationship’ covers both relationships and marriage, and is used because the mean age among freshmen in Sweden is 22.5 while the mean age of first marriage is 30.9 in women and 33.5 in men (Statistics Sweden, 2005). It is noteworthy that more female freshmen report a serious relationship compared with men. Probably, female freshmen that are older compared with male freshmen have a relationship outside the university. An additional possibility is that there is a gender difference regarding attitudes towards the definition of a serious relationship.
A major strength of this study is the size of the cohort, as it represents two complete populations. Gender distribution and mean age is representative of Swedish university freshmen and differences regarding drinking patterns between the two universities are previously confirmed as regional variations between different parts of the country (Bullock, 2004; Swedish National Agency for Higher Education, 2005). Women and older individuals are known to be more willing to participate in research studies. This also applied in this study, except regarding the age of participants, where younger freshmen were more willing to be enrolled than older students. This is probably explained by the fact that the intervention study was primarily addressed to 19- to 25-year-old freshmen.
Another strength is the use of the AUDIT questionnaire as the main instrument, which has been used in several other studies in university settings (Fleming et al., 1991; Granville-Chapman et al., 2001; Kypri et al., 2002; McShane and Cunningham, 2003; O'Hare and Sherrer, 1999; Shields et al., 2004). The high correlation between the AUDIT and eBAC and the short version of AEQ in this study confirms the use of the AUDIT as a screening instrument in young adults.
The study has several limitations. The response rate (72%) is not very high and was calculated by comparing the number of freshmen answering the questionnaire in relation to the total number of freshmen registered in the official university record. This calculation is not precise for several reasons. For example, the twelve-month drop-out rate from Swedish university education is 33% and many freshmen register without actually starting their courses (Swedish National Agency for Higher Education, 2005). Even though the response rate in this study is acceptable, the actual response rate might be higher then the 72% reported using this method of calculation, because several individuals that have been included as missing subjects have probably not been taken into account.
Another limitation is that the results are based on one single assessment and so do not capture longitudinal variations in the same individuals as when using repeated measures. This limitation mainly affects results regarding age differences and has only a limited consequence on other results.
Furthermore, it is suggested that individuals with a family history of alcohol problems are less likely to mature out from heavy consumption (Jackson et al., 2001). The mean age of university freshmen in Sweden is somewhat higher compared with US freshmen, so it could be argued that the higher scores for students with a family history of alcohol problems capture this developmental process. These differences indicate that heredity may influence alcohol involvement during early young adulthood. In this study, it is also notable that individuals with a family history of alcohol problems enter university later than those with no family history of alcohol problems. This result corresponds to previous research that reported that a family history of alcohol problems interferes with an individual's ability to pursue a higher education (Sher et al., 1991). In comparison to US data, it is also notable that a lower percentage of Swedish university freshmen report a positive family history of alcohol problems (Perkins, 2002).
To conclude, there is a generally high level of alcohol involvement among Swedish university freshmen that is related to age, heredity of alcohol problems, and serious relationships. It is difficult to define half of the population as problem drinkers and, when following recommendations regarding interventions, it is important to remember that alcohol involvement in young adults has been associated with increasing and long-lasting alcohol-related problems (O'Neill et al., 2001). Moreover, research has shown that there are several prevention methods that are effective for young adults (Saltz, 2006).
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ACKNOWLEDGEMENTS |
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The Swedish Ministry of Health and Social Affairs, the Swedish Research Council, the AFA Insurance Company, the Swedish Retailing Company Research Foundation and the Swedish Council for Working Life and Social Research financially supported the research and preparation of this article. We also acknowledge Kerstin Thornqvist for taking part in data collection.
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