Skip to main content
Download PDF

Clustering of smoking, alcohol drinking and cannabis use in adolescents in a rapidly developing country

BMC Public Health volume 6, Article number: 169 (2006) Cite this article

Abstract

Background

Smoking, alcohol drinking and cannabis use ("risk behaviors") are often initiated at a young age but few epidemiological studies have assessed their joined prevalence in children in developing countries. This study aims at examining the joint prevalence of these behaviors in adolescents in the Seychelles, a rapidly developing country in the Indian Ocean.

Methods

Cross-sectional survey in a representative sample of secondary school students using an anonymous self-administered questionnaire (Global Youth Tobacco Survey). The questionnaire was completed by 1,321 (92%) of 1,442 eligible students aged 11 to 17 years. Main variables of interest included smoking cigarettes on ≥1 day in the past 30 days; drinking any alcohol beverage on ≥1 day in the past 30 days and using cannabis at least once in the past 12 months.

Results

In boys and girls, respectively, prevalence (95% CI) was 30% (26–34)/21% (18–25) for smoking, 49% (45–54)/48% (43–52) for drinking, and 17% (15–20)/8% (6–10) for cannabis use. The prevalence of all these behaviors increased with age. Smokers were two times more likely than non-smokers to drink and nine times more likely to use cannabis. Drinkers were three times more likely than non-drinkers to smoke or to use cannabis. Comparison of observed versus expected frequencies of combination categories demonstrated clustering of these risk behaviors in students (P < 0.001).

Conclusion

Smoking, drinking and cannabis use were common and clustered among adolescents of a rapidly developing country. These findings stress the need for early and integrated prevention programs.

Peer Review reports

Background

In addition to the increased risk of chronic diseases at an older age, smoking, drinking and use of illegal substances in adolescents are associated with more immediate health hazards such as depression, interpersonal violence, motor vehicle crashes and drowning, risky sexual behaviors, and suicidal behavior [1–3]. Furthermore, behaviors initiated during adolescence tend to track into adulthood [4]. Early experience with smoking and drinking increases the risk of subsequent tobacco [5] and alcohol [6] dependences. In addition, cross-sectional [7–9] and longitudinal [10–12] studies in western countries have shown that these behaviors tended to cluster in adolescence and perhaps even at an earlier age [13]. Also of importance, these behaviors increase the likelihood to adopt other risk behaviors at a later age, such as multiple substance use, violence and delinquency [14, 15].

The Republic of Seychelles comprises over 115 islands lying in the Indian Ocean, approximately 1,000 km east to Kenya and the country is part of the African region. Almost all of the population lives on three main islands and 90% reside on the largest one, Mahé. The large majority is of African descent. The country has experienced rapid socio-economic development due to booming tourism and fishing industries. The gross domestic product per capita has increased, in real terms, from US$ 2,927 in 1980 to US$ 5,239 in 2004.

Surveys among adults have shown high prevalence of both smoking and drinking in men but not in women [16–18]. In 1994, 51% of men and 6% of women reported drinking at least once per week [17] while 31% of men and 4% of women reported smoking daily in 2004 [18]. Until 2004, drugs such as heroin or cocaine were virtually unseen in the country, which was reflected by only very few police cases or hospital admissions related to illegal substance abuse.

In Seychelles, the law prohibits the sale of alcohol and cigarettes to children aged less than 18 years. Use and possession of cannabis and other illegal drugs is prohibited and liable to severe penalties. Both alcohol and cigarettes are heavily taxed and expensive. Advertising for cigarettes is banned while advertising for alcohol beverages is limited. Use of tobacco or alcohol in the premises of all schools is prohibited and severely sanctioned by school policies. Over the past decade, the ministry of health and some other organizations have been conducting high-profile awareness campaigns related to smoking, illegal drugs and responsible drinking. However, alcohol drinking is common at the occasion of social events and there has been a long standing social tolerance, at least among men [17].

The prevalence, age of onset and clustering of smoking, drinking and substance use in adolescents has been well described in western countries but few data on the joint prevalence of these behaviors are available from developing countries. In this study, we examined the prevalence and clustering patterns of smoking, drinking and cannabis use among a representative sample of school students aged 11–17 years of the Seychelles, a middle-income country experiencing rapid epidemiological transition.

Methods

This study is part of the Global Youth Tobacco Survey (GYTS), an international school-based survey of tobacco use that focuses on adolescents aged 13–15. The survey, which is sponsored by the World Health Organization (WHO) and the Centers for Disease Control (CDC), has been conducted once or several times in more than a hundred countries worldwide [19–22].

The GYTS is intended to be performed in students aged 13–15 years. In Seychelles this includes the four secondary grades S1–S4 (school is compulsory through the S4 level). There are 12 secondary schools (10 public, 2 private) on the three main islands that teach grades S1–S4. The total enrolment of Grades S1–S4 for these 12 schools was 6,161. A two-stage cluster sample design was used to produce a representative sample of all students in grades S1–S4 from all public and private schools in Seychelles. The first-stage sampling frame consisted of all schools containing the grades S1, S2, S3, and S4. Schools were selected with probability proportional to school enrolment size. The second-stage sampling frame consisted of an equal-probability sampling (with a random start) of all S1–S4 classes from the selected schools. Sample size estimation showed that 1,224 completed interviews were needed from an enrolment of 6,161 for a ± 5% margin of error.

Eight percent of students did not participate in the study, because they were absent on the day the study took place for benign reasons (e.g. illness) or because they were suspended for disciplinary reasons (i.e. major misbehaviors) [23].

The questionnaire was anonymous, self-administered, and written in English (English is the main language used at school). The questionnaire included 56 core questions on tobacco and other variables (for example age, sex) used in all GYTS worldwide. Fifteen additional questions were included in order to assess alcohol drinking and the use of illegal drugs [see Additional file 1]. Most students could complete the questionnaire within 35–45 minutes. The survey took place at the same time in all selected classes. The students and parents were not informed prior to the survey in view of the non-sensitive nature of the survey, the absence of invasive investigations or physical measurements, the allowance for declining participation given to all children, and the anonymous nature of the questionnaire ensuring confidentiality of all answers by all students. The research committee of the Ministry of Health and the Ministry of Education approved the study including the questionnaire and the fact that informed consent by parents was not necessary.

Some questions of particular relevance for this study read as follows: "During the past 30 days, on how many days did you smoke cigarettes?". Consistent with the GYTS methodology, "smoking in the past month" was defined as smoking on one day per month or more. "Have you ever tried cigarette smoking, even one or two puffs?". "Ever smoking" was defined as having ever smoked a cigarette, even a puff, at least once. "During the past 30 days, on how many days did you drink alcohol?". "Drinking in the past month" was defined as any alcohol consumption on at least one day during the past 30 days. "Have you ever had so much alcohol that you were drunk?". "Ever drunkenness" was defined as having ever been drunk at least once. "Did you ever take a joint, marijuana, or hashish in your life?". "Ever cannabis" was defined as having ever used cannabis at least once. "During the past 12 months, how many times did you take a joint, marijuana, or hashish?". "Cannabis in the past year" was defined as having smoked cannabis at least once during the past 12 months [see Additional file 1].

Overall prevalence estimates and 95% confidence intervals were weighted consistent with the survey design. We selected age categories (11–13, 14 and 15–17) so that numbers of students were balanced across all categories in order to maximize the power of statistical analyses. Differences in prevalence estimates were tested using the chi-square test. To analyze clustering patterns, we calculated the expected frequencies of the 4 different possible combinations of the three risk factors (i.e. 0, 1, 2, or 3) given the observed prevalence of each risk factor and assuming independency in associations. Difference between observed versus expected prevalences of combinations was tested with a goodness-of-fit chi square with 3 degrees of freedom. Analyses were conducted with Stata 8.2. P-values less than 0.05 were considered significant.

Results

All schools agreed to participate (100% school response rate) and 1,321 (92%) of 1,442 eligible students aged 11 to 17 years completed the questionnaire. Forty-two percent of all participants were aged 11–13, 28% aged 14, and 30% aged 15–17. The proportions of respondents did not differ significantly by age and age category. The answers not completed in the questionnaire were coded as missing values and their proportions varied between 0.9% and 5.6% depending on the questions.

Table 1 presents the proportions of boys and girls reporting risk behaviors. The prevalence of risk behaviors was markedly higher in the older than younger age categories. This suggests an important uptake of these risk behaviors over the considered age categories. The prevalence of risk behaviors was higher in boys than girls. However, at age 15–17, the difference between boys and girls was only minimal for monthly smoking and for monthly drinking, suggesting convergence in the prevalence in late adolescence. The prevalence of cannabis use in the past year was larger in boys than in girls in all age categories.

Table 1 Prevalence (percent with their 95% confidence intervals) of students reporting risk behaviors, by sex and age
Full size table

Table 2 shows the proportions of combinations of risk behaviors by sex and age categories. The proportions of students reporting none of the three risk behaviors tended to be lower in boys than in girls and in younger than older students (e.g. 41% at age 11–13 and 24% at age 15–17 among boys, respectively 50% and 35% among girls of same age categories). Inversely, the proportions of students reporting the three risk behaviors tended to be higher in boys than in girls and in the older than younger age categories (e.g. 7% at age 11–13 and 14% at age 15–17 among boys, respectively 3% and 8% among girls in the same age categories).

Table 2 Prevalence (percent with their 95% confidence intervals) of students reporting various combinations of smoking in the past month (S), drinking in the past month (D) and cannabis use in the past year (C) by sex and age. Y: Yes, N: No
Full size table

The figure shows the prevalence of combinations of 0, 1, 2 and 3 risk behaviors among all students. The prevalence of expected and observed combinations categories differed significantly (P < 0.001), which demonstrates a clustering pattern of the considered risk behaviors. Observed prevalences were higher than expected prevalences in the extreme combination categories (respectively 0 and 3 risk behaviors) while the reverse was found in the intermediate combination categories (respectively 1 and 2 risk behaviors). Compared to the expected prevalence, the observed prevalence was +33% (45% vs. 34%), -30% (34% vs. 48%), -15% (14% vs. 17%) and +380% (7% vs. 2%) in the combination categories of 0, 1, 2 and 3 risk behaviors, respectively. Results did not differ significantly by sex or age (data not shown).

Table 3 shows the joint prevalence of risk behaviors among smokers (n = 294), drinkers (n = 613) and cannabis users (n = 154). Compared to non-smokers, smokers were two times more likely to drink (76% vs. 38%), and more than nine times more likely to use cannabis (35% vs. 4%). Compared to non-drinkers, drinkers were three times more likely to smoke (39% vs. 11%) or to use cannabis (20% vs. 6%). Compared to non-users, cannabis users were four time more likely to smoke (75% vs. 18%) and two times more likely to drink (77% vs. 44%). Among drinkers, there were twice as many smokers as cannabis users (39% vs. 20%) and cannabis use was more common among smokers than among drinkers (35% vs. 20%). The 95% confidence intervals of prevalence estimates by "yes" and "no" status fell largely apart of each other in all situations shown in the table, which translates into significant differences in all instances.

Table 3 Joint prevalence of risk behaviors by sex
Full size table

Table 4 presents selected recently published estimates of the gender-specific prevalence of smoking, drinking and cannabis use among youth the United States [24], England [25], Switzerland [26], and South Africa [20, 27], in addition to our findings in Seychelles. We did not find publications on the joint prevalence of the considered behaviors in representative samples in African countries except for one in South Africa. Although the mean age of the study populations and the criteria used to define risk behaviors differ across countries, – and the figures must therefore be interpreted with great caution -, the table may be useful to set the prevalence of risk behaviors among Seychelles youth in an international context. The data suggest that the prevalence and gender patterns for smoking and drinking are not largely different in Seychelles as compared to the considered western countries. However fewer youths seemed to use cannabis in the former than in the latter.

Figure 1. Prevalence of expected and observed combinations of risk behaviors (smoking, drinking and cannabis use) in students aged 11–17
figure 1

Prevalence of expected and observed combinations of risk behaviors (smoking, drinking and cannabis use) in students aged 11–17

Full size image
Table 4 Prevalence of risk behaviors in adolescents in Seychelles and in selected countries
Full size table

Discussion

We found high prevalences of smoking, drinking and cannabis use among adolescents in the Seychelles. These risk behaviors tended to cluster, particularly smoking and drinking and smoking and cannabis.

Comparisons between countries must be interpreted cautiously in view of different methodology used across countries. However, the prevalence of smoking seemed higher in Seychelles than in several low-income developing countries in the African region [20], but similar as compared to western countries such as Switzerland [28], the US [24] or the UK [25]. Higher prevalence in Seychelles as compared to Africa may reflect a larger purchasing power of youth in Seychelles than in many other African countries [29]. While smoking is much less common in female than in male adults in Seychelles (respectively 4% and 31% in 2004 [30]), the much smaller difference by gender among youth may predict a marked increase in the prevalence of smoking in future generations of adult women [17, 31]. A lack of gender differences in adolescent smoking has been consistently found in developed and developing countries (Table 4) [24, 25, 28, 32].

Drinking in adolescents was as frequent in Seychelles as in South Africa [27] or in selected western countries [24, 25, 28]. The lack of a gender difference in drinking prevalence in Seychellois adolescents, consistent with findings in industrialized countries (Table 4) [24, 25, 28, 32], may announce a convergence by gender among younger cohorts, in contrast to the currently much higher prevalence of drinking in male than female adults [16–18].

Fewer adolescents in Seychelles reported cannabis use during the past year compared to youths in South Africa or in some western countries (Table 4). A higher prevalence in boys than in girls in Seychelles contrasts with the lack of a gender difference observed in selected other countries. The situation may be consistent with the indirect evidence of a low use of other illegal drugs in Seychelles at the time of the survey.

We found that smoking, drinking and cannabis use tended to cluster. The association was particularly strong between smoking and cannabis use, which is consistent with a clustering pattern often found in developed countries [1, 33]. The cross-sectional nature of our data precludes concluding on the direction of these associations (whether a certain behavior precedes or follows another behavior). Studies investigating temporal relationships of substance use suggest that smoking often precedes alcohol drinking and cannabis use and that smoking may represent a "gateway" to other substance use [14, 15, 34–37]. On the other hand, a "problem behaviors theory" postulates that there is no clear temporal sequence in the use of different substances. Along this theory, adoption of risk behaviors such as smoking, drinking, cannabis use and the use of other drugs is the consequence of a single underlying characteristic [38], e.g. an affinity to sensation-seeking and risky behaviors [39]. The associations between risk behaviors may also reflect social circumstances such as use of substances by peers and a perception by children that use of substances is encouraged among adults [40]. Pharmacologic factors may also play a role: tobacco, alcohol, cannabis and other drugs impact on several common neurotransmitters [41]. Moreover, early onset of smoking, drinking or cannabis use has been associated with higher nicotine addiction [4], higher alcohol dependence [6] and increased problem behaviors [42] during later adolescence, which may underlie other mechanisms for the association of these behaviors.

Mirroring a higher than expected prevalence of adolescents with all three behaviors, we also found a larger than expected proportion of adolescents indulging in none of the three risk behaviors. One could speculate that abstainers might include adolescents who socialize less and are therefore less exposed to peer pressure from experimenters or who are submitted to more parental or other social or cultural forms of control. Alternatively, abstainers might have developed particularly strong resilience skills, in relation to personal characteristics or to an enabling familial or social milieu.

Our study has some limitations. The sample size of the survey limits the precision of the prevalence estimates in some categories with subsequent large confidence intervals (e.g. cannabis use among girls). The size of the samples if further limited by missing data in some students (typically up to 5%), a factor that cannot be avoided from self-reported questionnaires. There are also several sources of bias in prevalence estimates. First, students could exaggerate or underestimate their answers in a systematic manner. Although the extent of this potential bias cannot be determined, questions on tobacco were shown to have good test-retest reliability in a another study [20]. Second, the prevalence of risk behaviors may be underestimated since non-participants typically indulge in more detrimental behaviors as compared to participants, as we have also shown on this sample of students [23]. On the other hand, strong points of the study include the large participation, the population-based design, and the anonymous nature of the data collected.

Our findings have several public health implications. First, the early onset of the considered behaviors emphasizes the importance of implementing school-based surveillance systems for guiding and evaluating policy and prevention programs.

Second, given the much lower prevalence of smoking and drinking in women compared to men in Seychelles (as found in many other developing countries), the only small gender difference found in boys and girls may predict a convergence by sex of these behaviors over the next decades. However, further appropriately powered studies (i.e. studies with larger sample sizes and extended age categories) should examine trends and significance of such gender patterns over age in adolescence before conclusions can be drawn. These issues are important as they underlie specific target groups for prevention.

Third, given tracking into adulthood [4, 6], the fairly high prevalence of the considered risk behaviors in adolescents emphasizes the need to strengthen school-based programs and policies aimed at promoting healthy behaviors as a main strategy to tackle non-communicable diseases in the general population. It has been shown that delaying smoking onset until after the age of 13 can reduce the prevalence of adult smoking [43] and that delaying drinking onset after the age of 14 can reduce the risk of alcohol dependence [6]. More generally, it is believed that adoption of healthy behaviors early in life has the potential to reduce CVD in adulthood [44]. Furthermore, programs to prevent substance use should therefore not be restricted to adolescents only but also extend to pupils in elementary school.

Fourth, the trend towards clustering of smoking, drinking and use of cannabis, as found in this report and in other studies, emphasizes the need to address these behaviors within comprehensive and integrated programs [43]. Similarly, comprehensive benefits can be expected from various policy measures: high cigarette prices can reduce the prevalence of both drinking and cannabis use in adolescents [45].

Conclusion

We found that smoking, drinking and cannabis use are common among adolescents of a rapidly developing country and that these risk behaviors are adopted at an early age and tend to cluster. These findings stress the need to initiate prevention interventions at an early age and using integrated approaches.

Abbreviations

GYTS:

Global Youth Tobacco Survey

WHO:

World Health Organization

CDC:

Centers for Disease Control

References

  1. Hanna EZ, Yi HY, Dufour MC, Whitmore CC: The relationship of early-onset regular smoking to alcohol use, depression, illicit drug use, and other risky behaviors during early adolescence: results from the youth supplement to the third national health and nutrition examination survey. J Subst Abuse. 2001, 13: 265-282. 10.1016/S0899-3289(01)00077-3.

    CAS  Article  PubMed  Google Scholar 

  2. Miller TR, Lestina DC, Smith GS: Injury risk among medically identified alcohol and drug abusers. Alcohol Clin Exp Res. 2001, 25: 54-59. 10.1111/j.1530-0277.2001.tb02127.x.

    CAS  Article  PubMed  Google Scholar 

  3. Breslau N: Daily cigarette consumption in early adulthood: age of smoking initiation and duration of smoking. Drug Alcohol Depend. 1993, 33: 287-291. 10.1016/0376-8716(93)90114-6.

    CAS  Article  PubMed  Google Scholar 

  4. Escobedo LG, Marcus SE, Holtzman D, Giovino GA: Sports participation, age at smoking initiation, and the risk of smoking among US high school students. JAMA. 1993, 269: 1391-1395. 10.1001/jama.269.11.1391.

    CAS  Article  PubMed  Google Scholar 

  5. Breslau N, Fenn N, Peterson EL: Early smoking initiation and nicotine dependence in a cohort of young adults. Drug Alcohol Depend. 1993, 33: 129-137. 10.1016/0376-8716(93)90054-T.

    CAS  Article  PubMed  Google Scholar 

  6. Grant BF, Stinson FS, Harford TC: Age at onset of alcohol use and DSM-IV alcohol abuse and dependence: a 12-year follow-up. J Subst Abuse. 2001, 13: 493-504. 10.1016/S0899-3289(01)00096-7.

    CAS  Article  PubMed  Google Scholar 

  7. Patton GC, Hibbert M, Rosier MJ, Carlin JB, Caust J, Bowes G: Patterns of common drug use in teenagers. Aust J Public Health. 1995, 19: 393-399.

    CAS  Article  PubMed  Google Scholar 

  8. Bailey SL: Adolescents' multisubstance use patterns: the role of heavy alcohol and cigarette use. Am J Public Health. 1992, 82: 1220-1224.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  9. Everett SA, Giovino GA, Warren CW, Crossett L, Kann L: Other substance use among high school students who use tobacco. J Adolesc Health. 1998, 23: 289-296. 10.1016/S1054-139X(98)00023-8.

    CAS  Article  PubMed  Google Scholar 

  10. Mills CJ, Noyes HL: Patterns and correlates of initial and subsequent drug use among adolescents. J Consult Clin Psychol. 1984, 52: 231-243. 10.1037/0022-006X.52.2.231.

    CAS  Article  PubMed  Google Scholar 

  11. Lai S, Lai H, Page JB, McCoy CB: The association between cigarette smoking and drug abuse in the United States. J Addict Dis. 2000, 19: 11-24. 10.1300/J069v19n02_02.

    CAS  Article  PubMed  Google Scholar 

  12. Yamaguchi K, Kandel DB: Patterns of drug use from adolescence to young adulthood: III. Predictors of progression. Am J Public Health. 1984, 74: 673-681.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. Gorin S, Arnold J: Health promotion handbook. 1998, St. Louis, Mosby

    Google Scholar 

  14. DuRant RH, Smith JA, Kreiter SR, Krowchuk DP: The relationship between early age of onset of initial substance use and engaging in multiple health risk behaviors among young adolescents. Arch Pediatr Adolesc Med. 1999, 153: 286-291.

    CAS  PubMed  Google Scholar 

  15. Ellickson PL, Tucker JS, Klein DJ: High-risk behaviors associated with early smoking: results from a 5-year follow-up. J Adolesc Health. 2001, 28: 465-473. 10.1016/S1054-139X(00)00202-0.

    CAS  Article  PubMed  Google Scholar 

  16. Bovet P, Perdrix J, Larue D, Yersin B, Paccaud F: Poor performance of the CAGE questionnaire in screening for heavy drinking in men in the Seychelles Islands (Indian Ocean). Afr J Drug Alcohol Stud. 2000, 1: 3-20.

    Google Scholar 

  17. Bovet P, Shamlaye C, Kitua A, Riesen WF, Paccaud F, Darioli R: High prevalence of cardiovascular risk factors in the Seychelles (Indian Ocean). Arterioscler Thromb. 1991, 11: 1730-1736.

    CAS  Article  PubMed  Google Scholar 

  18. Perdrix J, Bovet P, Larue D, Yersin B, Burnand B, Paccaud F: Patterns of alcohol consumption in the Seychelles Islands (Indian Ocean). Alcohol Alcohol. 1999, 34: 773-785.

    CAS  Article  PubMed  Google Scholar 

  19. Global Tobacco Surveillance System Collaborating Group. Global Tobacco Surveillance System (GTSS): Purpose, Production, and Potential. Journal of School Health. 2005, 75: 15-24. 10.1111/j.1746-1561.2005.tb00004.x.

  20. Tobacco use among youth: a cross country comparison. Tob Control. 2002, 11: 252-270. 10.1136/tc.11.3.252.

  21. Global Tobacco Surveillance System Collaborating Group. Differences in worldwide tobacco use by gender: findings from the Global Youth Tobacco Survey. J Sch Health. 2003, 73: 207-215.

  22. Warren CW, Riley L, Asma S, Eriksen MP, Green L, Blanton C, Loo C, Batchelor S, Yach D: Tobacco use by youth: a surveillance report from the Global Youth Tobacco Survey project. Bull World Health Organ. 2000, 78: 868-876.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Bovet P, Viswanathan B, Faeh D, Warren W: Comparison of smoking, drinking, and marijuana use between students present or absent on the day of a school-based survey. J Sch Health. 2006, 76: 133-137. 10.1111/j.1746-1561.2006.00081.x.

    Article  PubMed  Google Scholar 

  24. Grunbaum JA, Kann L, Kinchen S, Ross J, Hawkins J, Lowry R, Harris WA, McManus T, Chyen D, Collins J: Youth risk behavior surveillance--United States, 2003. MMWR Surveill Summ. 2004, 53: 1-96.

    PubMed  Google Scholar 

  25. National Centre for Social Research/National Foundation for Educational Research. Smoking, drinking and drug use among young people in England in 2004. 2004

  26. Hibell B, Andersson B, Bjarnason T, Ahlström S, Balakireva O, Kokkevi A, Morgan M: Alcohol and Other Drug Use Among Students in 35 European Countries. The Swedish Council for Information on Alcohol and Other Drugs (CAN) and the Pompidou Group at the Council of Europe. The ESPAD Report 2003. 2004, Stockholm, Sweden, , 436-

    Google Scholar 

  27. Parry CD, Myers B, Morojele NK, Flisher AJ, Bhana A, Donson H, Pluddemann A: Trends in adolescent alcohol and other drug use: findings from three sentinel sites in South Africa (1997-2001). J Adolesc. 2004, 27: 429-440. 10.1016/j.adolescence.2003.11.013.

    Article  PubMed  Google Scholar 

  28. sfa/ispa: Zahlen und Fakten zu Alkohol und anderen Drogen. 2004

    Google Scholar 

  29. World Bank Development Indicators, accessed on 17 Aug 2005. [http://www.worldbank.org/data/databytopic/GDP_PPP.pdf]

  30. Bovet P, Shamlaye C, Gabriel A, Riesen W, Paccaud F: Prevalence of cardiovascular risk factors in a middle-income country and estimated cost of a treatment strategy. BMC Public Health. 2006, 6: 9-10.1186/1471-2458-6-9.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Paccaud F, Schluter-Fasmeyer V, Wietlisbach V, Bovet P: Dyslipidemia and abdominal obesity: an assessment in three general populations. J Clin Epidemiol. 2000, 53: 393-400. 10.1016/S0895-4356(99)00184-5.

    CAS  Article  PubMed  Google Scholar 

  32. Warren CW, Jones NR, Eriksen MP, Asma S: Global Tobacco Surveillance System (GTSS) collaborative group. Patterns of global tobacco use in young people and implications for future chronic disease burden in adults. Lancet. 2006, 4: 749-753. 10.1016/S0140-6736(06)68192-0.

    Article  Google Scholar 

  33. Coogan PF, Adams M, Geller AC, Brooks D, Miller DR, Lew RA, Koh HK: Factors associated with smoking among children and adolescents in Connecticut. Am J Prev Med. 1998, 15: 17-24. 10.1016/S0749-3797(98)00022-1.

    CAS  Article  PubMed  Google Scholar 

  34. Siqueira LM, Brook JS: Tobacco use as a predictor of illicit drug use and drug-related problems in Colombian youth. J Adolesc Health. 2003, 32: 50-57. 10.1016/S1054-139X(02)00534-7.

    Article  PubMed  Google Scholar 

  35. Escobedo LG, Reddy M, DuRant RH: Relationship between cigarette smoking and health risk and problem behaviors among US adolescents. Arch Pediatr Adolesc Med. 1997, 151: 66-71.

    CAS  Article  PubMed  Google Scholar 

  36. Parra-Medina DM, Talavera G, Elder JP, Woodruff SI: Role of cigarette smoking as a gateway drug to alcohol use in Hispanic junior high school students. J Natl Cancer Inst Monogr. 1995, 83-86.

    Google Scholar 

  37. Wetzels JJ, Kremers SP, Vitoria PD, de Vries H: The alcohol-tobacco relationship: a prospective study among adolescents in six European countries. Addiction. 2003, 98: 1755-1763. 10.1111/j.1360-0443.2003.00553.x.

    CAS  Article  PubMed  Google Scholar 

  38. Donovan JE, Jessor R: Structure of problem behavior in adolescence and young adulthood. J Consult Clin Psychol. 1985, 53: 890-904. 10.1037/0022-006X.53.6.890.

    CAS  Article  PubMed  Google Scholar 

  39. Van Kammern WB, Loeber R, Stouthhamer-Loeber M: Substance use and its relationship to conduct problems and delinquiency in young boys. Journal of Youth and Adolescence. 1991, 20: 399-413. 10.1007/BF01537182.

    Article  Google Scholar 

  40. Lindsay GB, Rainey J: Psychosocial and pharmacologic explanations of nicotine's "gateway drug" function. J Sch Health. 1997, 67: 123-126.

    CAS  Article  PubMed  Google Scholar 

  41. Picciotto MR: Common aspects of the action of nicotine and other drugs of abuse. Drug Alcohol Depend. 1998, 51: 165-172. 10.1016/S0376-8716(98)00074-X.

    CAS  Article  PubMed  Google Scholar 

  42. Brook JS, Brook DW, Rosen Z, Rabbitt CR: Earlier marijuana use and later problem behavior in Colombian youths. J Am Acad Child Adolesc Psychiatry. 2003, 42: 485-492.

    Article  PubMed  Google Scholar 

  43. Centers for Disease Control & Prevention. Guidelines for school health programs to prevent tobacco use and addiction. Recomm Rep. Edited by: MMWR . 1994, 43: 1-18.

  44. Washington RL: Interventions to reduce cardiovascular risk factors in children and adolescents. Am Fam Physician. 1999, 59: 2211-2218.

    CAS  PubMed  Google Scholar 

  45. Farrelly MC, J.W. B, Zarkin GA, Wendling BW, R.L. P: The Effects of Prices and Policies on the Demand for Marijuana: Evidence from the National Household Surveys on Drug Abuse. National Bureau of Economic Research. 1999, Cambridge, MA,

    Google Scholar 

Pre-publication history

Download references

Acknowledgements

We are grateful to the survey officers and the head teachers and teachers of the participating schools for their collaboration with the survey; to the Ministry of Health and Social Services and to the Ministry of Education for their support; and to C. Ruffieux (PhD) for helpful statistical advice. Partial funding and assistance in the logistics of the study were obtained from the Centers for Disease Control and Prevention, Atlanta, USA and the World Health Organization.

Author information

Authors and Affiliations

  1. University Institute for Social and Preventive Medicine, Lausanne, Switzerland

    David Faeh, Arnaud Chiolero & Pascal Bovet

  2. Ministry of Health and Social Services, Victoria, Seychelles

    Bharathi Viswanathan & Pascal Bovet

  3. Office on Smoking and Health, National Centre for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, USA

    Wick Warren

Authors
  1. David Faeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bharathi Viswanathan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Arnaud Chiolero
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wick Warren
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Pascal Bovet
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pascal Bovet.

Additional information

Competing interests

The author(s) declare that they have no competing interests.

Authors' contributions

DF carried out literature research, statistical analysis, assisted in interpretation of the data, and was the main writer of the manuscript. BV participated in the study design and collected the data. AC and WW assisted in statistical analysis and reviewed the manuscript. PB designed the study, carried out analysis and interpretation of the data, and wrote partially the report.

Electronic supplementary material

12889_2006_466_MOESM1_ESM.pdf

Additional file 1: Final-GYTS-questionnaire(17sep02). Global Youth Tobacco Survey (GYTS) questionnaire with additional questions on alcohol consumption and use of illegal substances. (PDF 53 KB)

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Faeh, D., Viswanathan, B., Chiolero, A. et al. Clustering of smoking, alcohol drinking and cannabis use in adolescents in a rapidly developing country. BMC Public Health 6, 169 (2006). https://doi.org/10.1186/1471-2458-6-169

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/1471-2458-6-169

Keywords

  • Risk Behavior
  • Alcohol Drinking
  • Illegal Drug
  • Cannabis User
  • Cigarette Price

BMC Public Health

ISSN: 1471-2458

Contact us