The European Journal of Public Health Advance Access originally published online on July 12, 2006
The European Journal of Public Health 2007 17(1):27-32; doi:10.1093/eurpub/ckl071
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Child and adolescent health |
School-related risk factors for drunkenness among adolescents: risk factors differ between socio-economic groups
Anette Andersen, Bjørn E. Holstein and Pernille DueInstitute of Public Health, University of Copenhagen Denmark
Correspondence: Anette Andersen, Institute of Public Health, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen, Denmark, tel: +45 35 32 79 62; fax: +45 35 35 11 81; e-mail: anette.andersen{at}socmed.ku.dk
Received July 3, 2005, accepted March 13, 2006
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Abstract |
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Purpose: To examine, separately for boys and girls, whether socio-economic differences in drunkenness exist in adolescence, whether the level of exposure to school-related risk factors differ between socio-economic groups, and whether the relative contribution of school-related risk factors to drunkenness differ between socio-economic groups. Methods: The study population was a random sample of 1453 Danish 15-year-old students. The outcome measure was drunkenness 10 times or more, as a lifetime measure. Predictor variables comprised five aspects of well-being at school. Socio-economic position (SEP) was measured by parental occupation. Results: Among girls, exposures to school-related risk factors were more prevalent in lower socio-economic groups. Poor school satisfaction was associated with drunkenness among girls from high SEP, odds ratio (OR) = 2.98 (0.73–12.16). Among boys from high SEP autonomy in decision-making was associated with drunkenness, OR = 2.74 (1.06–7.08), whereas poor school satisfaction was associated with drunkenness among boys from intermediate SEP, OR = 2.26 (0.98–5.22). Weak Parental Support in school-related matters, OR = 3.92 (1.16–13.24), and disliking school, OR = 9.12 (1.77–47.09), were associated with drunkenness among boys from low SEP. These associations were also seen among girls although not significant. Conclusion: We found that well-being at school had socially differential impact on drunkenness in adolescence.
Keywords: adolescence, alcohol drinking, socio-economic position, well-being at school
Excess alcohol use in adolescence is a public health challenge in Denmark for several reasons. In international comparisons the youth in Denmark had the highest alcohol intake on the last drinking occasion and more young Danes had been drunk when compared to 28 other nations.1,2 High alcohol intake in adolescence has several adverse consequences such as poor academics performance, often feeling tired when going to school, fighting, injuries, and engaging in unplanned sex,3–5 and early alcohol drinking may be a strong predictor of later excess alcohol consumption.6
Social variation in risk behaviours in childhood and adolescence has been suggested as one of the mechanisms behind social inequalities in health in adulthood.7
Most studies on adults show that excessive drinking based on a quantity-frequency measure is more common among people in lower socio-economic groups, especially among men.8–12 Marmot (1997) found only little differences in drinking behaviour between men from different occupational groups, but among women he found the prevalence of heavy drinking to be higher in socially advantaged occupational groups.13
In youth the socio-economic differences in excessive alcohol drinking is sparsely investigated, and the results are contradictory. Lowry et al. (1996)14 found binge-drinking related to family income—drinking was less likely as family income increased. While others have found that high social class increases the risk of weekly drinking15 and monthly drinking,5 most studies have found only weak or no associations between socio-economic status and frequency of consumption,16 or between parental education and binge-drinking.17
As research suggest that excessive drinking track in youth,6 and from youth into early adulthood,18 a possible social inequality in alcohol consumption among adolescents may contribute to the development of social inequality in health over the life course. A range of different mechanisms may contribute to the development of socio-economic differences in behavioural patterns. Two suggested main mechanisms are as follows: (i) differential exposure to risk factors for alcohol consumption between socio-economic groups (lower socio-economic groups more exposed) and (ii) differential effects of risk factors on alcohol use (higher effect in lower socio-economic groups).19 As school environment has been related to alcohol drinking in several studies,20–22 we wanted to examine whether school-related risk factors may be part of these mechanisms.
The purposes of this study was to examine (i) whether socio-economic differences in excessive drinking existed in adolescence; (ii) whether the level of exposure to school-related risk factors differed between socio-economic groups; and (iii) whether the relative contribution of these risk factors to excessive drinking differed between socio-economic groups.
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Methods |
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We used the Danish 2002 data from the international research project Health Behaviour in School-Aged Children (HBSC), a WHO collaborative study. The design is repeated cross-sectional surveys in many countries, primarily in Europe. In Denmark the survey was carried out six times between 1984/85 and 2002. The data collection comprised all students aged 11, 13, and 15 in a random sample of schools. The 2002 survey comprised 68 schools with 5400 students in 297 classes. Of these, 4981 students (92.2%) were present on the day of data collection, and 4824 students (96.8% of the students present) returned a completed questionnaire. The analyses in this paper used 15-year-old students, i.e. students from grade 9. Of these 1453 students 681 girls and 621 boys had answered the questions about alcohol use and were included in the analyses.
The dependent variable in these analyses was drunkenness. The question was: ‘Have you ever been really drunk?’ response code: no, never; yes, once; yes, 2–3 times; yes, 4–10 times; yes, more than 10 times. The variable was dichotomised at drunkenness 10 times or more as an appropriate indicator of binge-drinking, which defines a large minority of the participants in the risk group (24% of the girls and 32% of the boys).
The independent variables were family socio-economic position (SEP) and school-related factors. In the multivariate analyses we controlled for confounding from social relations with parents, social relations with friends, and early drunkenness.
Predictor variables, which covered the same conceptual content, were combined into indexes. The coherence and reliability of the indexes were checked by correlation analyses and calculation of Cronbach's coefficient alpha.
Family SEP was measured by two items about father's and mother's occupation and coded according to the standards of the Danish National Institute of Social Research23 into six groups as follows: social class I (high) to V (low) and a group VI covering parents who were living from social welfare benefits. The participants were categorised according to the highest ranking parent into three groups, family SEP I–II, III–IV, and V–VI.
School-related factors were measured by 14 items, dichotomised into poor and good. The items had similar response codes and were dichotomised into ‘strongly disagree’ + ‘disagree’ versus ‘agree’ + ‘strongly agree’, with neither agree nor disagree coded in the reference group.
(1) ‘If I have a problem at school, my parents are ready to help’, (2) ‘My parents are willing to come to school to talk to teachers’, (3) ‘My parents encourage me to do well at school’. Items 1–3 concerned parental school support and were combined into an index which counted 1 point for each indicator of Weak Parental School Support, range 0–3 and dichotomised into 0 versus 1–3. The Pearson's correlation coefficients between the items varied between 0.57 and 0.65 for girls and between 0.55 and 0.57 for boys. Cronbach's coefficient alpha was 0.83 for girls and 0.78 for boys.
Items 4–8 concerned school satisfaction: (4) ‘I look forward to go to school’, (5) ‘I like being in school’, (6) ‘There are many things about school I do not like’, (7) ‘I wish I didn't have to go school’, (8) ‘I enjoy school activities’. These items were combined into an index which counted 1 point for each indicator of Poor School Satisfaction, range 0–5 and dichotomised into 0–2 versus 3–5. The Pearson's correlation coefficients between the items varied between 0.25 and 0.81 for girls and between 0.29 and 0.76 for boys. Cronbach's coefficient alpha was 0.81 for both girls and boys.
Items 9–11 concerned local identity: (9) ‘Our school is a nice place to be’, (10) ‘I feel I belong at this school’, (11) ‘I feel safe at this school’. These items were combined into an index which counted 1 point for each indicator of Poor Local Identity, range 0–3 and dichotomised into 0 versus 1–3. The Pearson's correlation coefficients between the items varied between 0.64 and 0.71 for girls and between 0.56 and 0.66 for boys. Cronbach's coefficient alpha was 0.85 for girls and 0.82 for boys.
Items 12–14 concerned autonomy at school: (12) ‘In our school the students take part in making rules’, (13) ‘The students are treated too severely/strictly in this school’, (14) ‘The rules in this school are fair’. These items were combined into an index which counted 1 point for each indicator of Poor Student Autonomy, range 0–3 and dichotomised into 0–1 versus 2–3. The Pearson's correlation coefficients between the items varied between 0.26 and 0.47 for girls and between 0.16 and 0.42 for boys. Cronbach's coefficient alpha was 0.65 for girls and 0.59 for boys.
Finally, item 15 was a global item and therefore treated separately: (15) ‘How do you feel about school at present?’ (don't like it very much + don't like it at all versus like a lot + like a bit).
Statistical procedures
We conducted analyses of sensitivity. These analyses demonstrated that choice of cut-off point did not change the direction of the association between the predictor variable and the outcome variable. The analyses of associations between predictor variables and the outcome variable were made separately for boys and girls. The first step was contingency tables to show the crude association (not shown). The second step was univariate and multivariate logistic regression analyses to examine the importance of the predictor variables on drunkenness. We chose logistic rather than linear regression modelling because the main interest was excessive drinking, i.e. drinking above a certain level. The third step was similar to step two but stratified for parental SEP.
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Results |
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The prevalence of the predictor and outcome variables is shown in table 1. In table 2, the prevalence of these variables are shown by SEP. Although non-significantly, the prevalence of the outcome variable drunkenness 10 times or more was higher among participants from higher SEP among both genders.
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Weak Parental School Support index was significantly higher among girls from SEP V–VI than from higher SEP (P-value = 0.001). More girls from lower SEP were found to have Poor School Satisfaction (index P-value = 0.034), Poor Local Identity (index P-value = 0.020), and Poor Student Autonomy (index P-value = 0.103). The same associations were seen among boys, but non-significant.
Family SEP was not associated with drunkenness 10 times or more either in the univariate or in the multivariate analyses (table 3). The univariate analyses showed that all aspects of well-being at school were associated with drunkenness, except for girls feeling poor local identity with their school. The multivariate associations showed some gender differences (table 3). Weak Parental School Support was associated with drunkenness among boys, odds ratio (OR) = 1.65 (1.02–2.69), but non-significant among girls, OR = 1.38 (0.82–2.30), whereas Poor Student Autonomy was associated with drunkenness among girls, OR = 1.83 (1.03–3.28), but non-significant among boys, OR = 1.45 (0.88–2.38). Poor Local Identity was positively associated with drunkenness among boys, OR = 1.27 (0.72–2.24), but was negatively associated among girls, OR = 0.25 (0.12–0.52).
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The stratified multivariate analyses showed predictors of drunkenness to be different among children from the various socio-economic strata (table 4).
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Weak Parental School Support was associated with drunkenness among girls with background in SEP V–VI, OR = 2.20 (0.55–8.72), Poor School Satisfaction and Poor Student Autonomy at school were associated with drunkenness among girls from SEP I–II, OR = 2.98 (0.73–12.16) and OR = 2.42 (0.83–7.07), respectively, but both factors were negatively associated with drunkenness among girls from SEP V–VI, OR = 0.40 (0.04–3.99) and OR = 0.65 (0.11–3.79). Disliking school was associated with drunkenness among girls from lower SEP, OR = 2.40 (1.11–5.19) for girls from SEP III–IV and OR = 3.12 (0.51–19.18) for girls from SEP V–VI.
Among boys with background in SEP I–II Poor Student Autonomy was positively associated with drunkenness, OR = 2.74 (1.06–7.08), but negatively associated with drunkenness among boys with background in SEP V–VI, OR = 0.60 (0.14–2.53). Poor School Satisfaction was predictive among boys background in SEP III–IV, OR = 2.26 (0.98–5.22), and among boys from SEP V–VI both Weak Parental School Support and disliking school were strongly associated with drunkenness, OR = 3.92 (1.16–13.24) and OR = 9.12 (1.77–47.09), respectively.
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Discussion |
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The literature on socio-economic pattering of excessive drinking is unequivocal,16,24,25 and our results show no significant socio-economic differences in drunkenness in adolescence. We did, however, find social differences in exposure levels for school-related risk factors of alcohol use in youth. We also found differences in risk factors for drunkenness between different socio-economic groups.
Almost all school-related risk factors were more prevalent among students from lower socio-economic groups. Among girls, three of four indicators of poor school connections were more prevalent in the lowest socio-economic groups: feeling that their parents are not engaged in school-related matters (especially if the parents were not ready to help with school-related problems or did not encourage to do well at school), low satisfaction with their school (especially if the girls did not look forward to go to school or disliked many things about school), and finally, poor affiliation at their school (especially girls who did not feel connected to their school). Among boys from lower SEPs higher prevalence of school-related risk factors were seen especially for boys whose parents were not ready to help with school problems, for boys who did not feel safe at school and for boys who felt treated too hard at school.
Different aspects of poor well-being at school were important for drunkenness in the different socio-economic groups. Experiencing low influence on their school environment was the most important predictor among both boys and girls with background in socio-economic group I–II. This was also the strongest predictor among girls from the intermediate socio-economic groups, but low satisfaction with school had the strongest impact on drunkenness among boys from the intermediate socio-economic groups. Among students from poorer social circumstances low parental engagement in school-related matters had the strongest impact on drunkenness.
Hemmingsson et al. (1998)26 found that manual workers had higher prevalence than non-manual employees of almost all risk factors for alcoholism. Furthermore, they found that unskilled workers seemed to receive an alcoholism diagnosis later in life more easily if they in adolescence stated risk use of alcohol, limited social network, low emotional control, smoking, contact with police or child care authorities, and origin from social class of manual workers. Our results also suggest that differences in exposure levels between socio-economic groups and socially differentiated effects of risk factors between socio-economic groups are possible mechanisms for the development of social inequalities in alcohol use. Young people from disaffected, peer-orientated groups, characterised by negative attitudes to school, extended peer-based social network, less positive parental relationships, who spend less time with the family, and reject adult authority, are more likely to be regular drinkers.27 Although Glendinning et al. (1995) found this to be independent of social class, young people who belonged to the disaffected, peer-orientated group are more likely to come from manual home backgrounds. Young people with these social strains may be more likely to develop into problem drinkers over time due to the absence of supportive networks. With lack of connectedness to school and family, adults may overlook the behavioural indicators leading to later alcohol abuse, and may therefore not be able to change the drinking patterns and avoid tracking of the behaviour into adulthood.
We have shown that the associations between drunkenness and different aspects of well-being at school vary between students from higher and lower SEPs. This is important when understanding the development of the social inequality in alcohol consumption over the life course. Other studies have found that low school connectedness is associated with increasing alcohol consumption,28,29 and that parental education is positively associated with school connectedness,29 or that adolescents from homes of lower SEP were more than twice as likely to report poorer connectedness to their schools.30
As this is a cross-sectional study, the direction of the association between risk factor and drunkenness is not unequivocal. However, these associations have previously been found in longitudinal studies.31,32 It is likely that the parents' occupational status was established before the children report drunkenness and risk factors, and unlikely that these variables would affect parental occupation. The strength of this study is the large representative sample and the low rate of non-respondents (2%). Students' reports of parents occupational status has been shown to be fairly valid,33,34 and only 7% of the data on parental occupational status were missing or not possible to code, which is much lower than found in other studies.35
The effectiveness of health education and information about alcohol may have an influence on knowledge and attitudes, but the effects on actual consumption levels are scarcely identifiable.36,37 A more promising strategy may be school-based interventions. School-based education provides opportunities for creating a safe and health enhancing social and physical environment. Links to families have, in this and other studies, shown to be of great importance in enhancing a healthy behavioural pattern among adolescents.37 Future studies should examine whether the parent–school interaction and school well-being in general, especially among children from poorer socio-economic backgrounds, have a strong influence on the actual binge-drinking behaviour.
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Acknowledgments |
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The study was financed by The Danish Cancer Society (no. 93-504) and by the National Board of Health (no. 407-19-1999). Funding to pay the Open Access publication charges for this article was provided by xxxxx.
Conflict of Interest: none declared.
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References |
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1 Hibell B, Andersson B, Ahlström S, et al. (2000) The 1999 ESPAD Report. The European School Survey Project on alcohol and other drugs(Council of Europe, Pompidou Group, Stockholm).
2 Currie C, Roberts C, Morgan A, et al. (2004) Young people's health in context. Health Behaviour in School-aged Children (HBSC) study: international report from the 2001/2002 survey. Health Policy for Children and Adolescents, No. 4. Denmark: World Health Organization.
3 Wechsler H, Davenport A, Dowdall G, et al. (1994) Health and behavioral consequences of binge drinking in college. A national survey of students at 140 campuses. J Am Med Assoc 272:1672–7.[Abstract]
4 Perkins HW. (1992) Gender patterns in consequences of collegiate alcohol abuse: A 10-year study of trends in an undergraduate population. J Stud Alcohol 53:458–62.[ISI][Medline]
5 Due P and Holstein BE. (1991) Alkoholforbrug og sociale faktorer blandt 11-15 årige (Alcohol consumption and social factors among 11–15-year olds). Nord Psykol 43:313–25.
6 Andersen A, Due P, Holstein BE, Iversen L. (2003) Tracking drinking behaviour from age 15–19 years. Addiction 98:1505–11.[CrossRef][ISI][Medline]
7 Kuh D, Power C, Blane D, Bartly M. (1997) Social pathways between childhood and adult health. In Kuh D and Ben –Shlomo Y (Eds.). A life course approach to chronic disease epidemiology(Oxford University Press, Oxford) pp. 169–98.
8 Osler M, Jørgensen T, Davidsen M, et al. (2001) Socioeconomic status and trends in alcohol drinking in the Danish MONICA population, 1982–92. Scand J Public Health 29:40–3.[ISI][Medline]
9 Droomers M, Schrijvers CTM, Stronks K, et al. (1999) Educational differences in excessive alcohol consumption: The role of psychosocial and material stressors. Prev Med 29:1–10.[CrossRef][ISI][Medline]
10 van Oers JAM, Bongers IBM, van de Goor LAM, Garretsen HFL. (1999) Alcohol consumption, alcohol-related problems, problem drinking, and socioeconomic status. Alcohol Alcohol 34:78–88.
11 Romelsjö A and Lundberg M. (1996) The changes in the social class distribution of moderate and high alcohol consumption and alcohol-related disabilities over time in Stockholm County and in Sweden. Addiction 91:1307–23.[CrossRef][ISI][Medline]
12 Knupfer G. (1989) The prevalence in various social groups of eight different drinking patterns, from abstaining to frequent drunkenness: analysis of 10 U.S. surveys combined. Br J Addict 84:1305–18.[CrossRef][ISI][Medline]
13 Marmot M. (1997) Inequality, deprivation and alcohol use. Addiction 92:Suppl 1, S13–20.
14 Lowry R, Kann L, Collins JL, Kolbe LJ. (1996) The effect of socioeconomic status on chronic disease risk behaviors among US adolescents. JAMA 276:792–7.[Abstract]
15 Pietilä A, Hentinen M, Myrhman A. (1995) The health behaviour of Northern Finnish men in adolescence and adulthood. Int J Nurs Stud 32:325–38.[CrossRef][ISI][Medline]
16 Tuinstra J, Groothoff JW, van den Heuvel WJA, Post D. (1998) Socio-economic differences in health risk behavior in adolescence: do they exist? Soc Sci Med 47:67–74.[CrossRef][ISI][Medline]
17 O'Malley PM, Johnston LD, Bachman JG. (1995) Adolescent substance use. Epidemiology and implications for public policy. Pediatr Clin North Am 42:241–60.[ISI][Medline]
18 Schulenberg J, O'Malley PM, Bachman JG, et al. (1996) Getting drunk and growing up: Trajectories of frequent binge drinking during the transition to young adulthood. J Stud Alcohol 57:289–304.[ISI][Medline]
19 Diderichsen F, Evans T, Whitehead M. (2001) The social basis of disparities in health. In Evans T, Whitehead M, Diderichsen F, Bhuiya A, Wirth M (Eds.). Challenging inequalities in health. From ethics to action(Oxford University Press, Oxford) pp. 13–23.
20 Nutbeam D, Smith C, Moore L, Bauman A. (1993) Warning! Schools can damage your health: Alienation from school and its impact on health behaviour. J Paediatr Child Health 29:Suppl 1, S25–30.
21 Samdal O. (1998) The school environment as a risk or resource for students' health-related behaviours and subjective well-being(Research Centre for Health Promotion, Faculty of Psychology, University of Bergen, Norway).
22 McLellan L, Rissel C, Donnelly N, Bauman A. (1999) Health behaviour and the school environment in New South Wales, Australia. Soc Sci Med 49:611–19.[CrossRef][ISI][Medline]
23 Hansen EJ. (1978) Fordelingen af levekårene. Bind 1 (The distribution of the living conditions. Part 1)(Socialforskningsinstituttet (The Danish National Institute of Social Research), Copenhagen).
24 Karvonen S and Rimpelä A. (1996) Socio-regional context as a determinant of adolescents' health behaviour in Finland. Soc Sci Med 43:1467–74.[CrossRef][ISI][Medline]
25 Lundborg P. (2002) Young people and alcohol: an econometric analysis. Addiction 97:1573–82.[CrossRef][ISI][Medline]
26 Hemmingsson T, Lundberg I, Diderichsen F, Allebeck P. (1998) Explanations of social class differences in alcoholism among young men. Soc Sci Med 47:1399–405.[CrossRef][ISI][Medline]
27 Glendinning A, Hendryp L, Shucksmith J. (1995) Lifestyle, health and social class in adolescence. Soc Sci Med 41:235–48.[CrossRef][ISI][Medline]
28 Resnick MD, Bearman PS, Blum RW, et al. (1997) Protecting adolescents from harm. Findings from the national longitudinal study on adolescent health. JAMA 278:823–32.[Abstract]
29 Bonny AE, Britto MT, Klosterman BK, et al. (2000) School disconnectedness: Identifying adolescents at risk. Pediatrics 106:1017–21.
30 Due P, Lynch J, Holstein B, Modvig J. (2003) Socioeconomic health inequalities among a nationally representative sample of Danish adolescents: the role of different types of social relations. J Epidemiol Community Health 57:692–8.
31 Bergmark KH and Andersson T. (1999) The development of advanced drinking habits in adolescence—a longitudinal study. Subst Use Misuse 34:171–94.[ISI][Medline]
32 Mason WA and Windle M. (2001) Family, religious, school and peer influences on adolescent alcohol use: a longitudinal study. J Stud Alcohol 62:44–53.[ISI][Medline]
33 Lien N, Friestad C, Klepp K-I. (2001) Adolescents' proxy reports of parents' socioeconomic status: How valid are they? J Epidemiol Community Health 55:731–7.
34 Holstein BE, Ito H, Due P. (1990) Sociale forskelle i børns helbred (Social inequalities in child health status). Ugeskr Laeger 151:2910–3.
35 Goodman E. (1999) The role of socioeconomic status gradients in explaining differences in US adolescents' health. Am J Public Health 89:1522–8.
36 Reelick F. (1990) The effectiveness of alcohol education. In Liedekerken PC, Jonkers R, de Haes WFM, Kok GJ, Saan JAM (Eds.). Effectiveness of health education(Dutch Health Education Centre, The Netherlands, Utrecht) pp. 71–3.
37 Anderson P. (2000) Health Challenges 2. The evidence of health promotion effectiveness. A report for the European Commission by the International Union for Health Promotion and Education(Jouve Composition & Impression, Paris, France) pp. 69–79.
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