Health Education Research Advance Access originally published online on July 14, 2004
Health Education Research 2005 20(1):92-100; doi:10.1093/her/cyg102
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Health Education Research Vol.20 no.1, © Oxford University Press 2005; All rights reserved
Covariates of current cigarette smoking among secondary school students in Budapest, Hungary, 1999
1 Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 4770 Buford Highway, NE, Mailstop K-50, Atlanta, GA 30341, USA and 2 Division of Health Promotion and Protection, Department of Child and Youth Health, Metropolitan Institute of State Public Health and Public Health Officer Service, Budapest, Republic of Hungary
3 Correspondence to: A. Easton; E-mail: ace7{at}cdc.gov
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Abstract |
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To date, few studies have examined the relationship between health behavior risk factors and cigarette smoking in Hungary. From 1995 to 1999, the prevalence of current smoking increased from 35.9 to 46.0% among secondary students in Budapest, Hungary. The objective of the present study was to examine the association between smoking and other health behavior risk factors among secondary school students in Budapest. Surveys were administered during regular classes in 21 traditional and nine vocational/technical schools containing Grades 9–12; 2410 students aged 15–18 years were included in the analysis. Overall, 44.9% of males and 46.9% of females were current smokers. Smoking increased with age and was significantly higher among vocational/technical (60.2%) than traditional (43.1%) students. The likelihood of smoking was significantly higher among students who rarely or never used a seatbelt when riding in a car driven by someone else, currently used alcohol, had engaged in episodic heavy drinking, had had four or more sex partners during their lifetime or did not participate in vigorous physical activity. Health-risk behaviors are frequently interrelated. Findings suggest that programs designed to prevent smoking should consider related health-risk behaviors as part of a comprehensive program.
To date, few studies have examined the relationship between health behavior risk factors and cigarette smoking in Hungary. From 1995 to 1999, the prevalence of current smoking increased from 35.9 to 46.0% among secondary students in Budapest, Hungary. The objective of the present study was to examine the association between smoking and other health behavior risk factors among secondary school students in Budapest. Surveys were administered during regular classes in 21 traditional and nine vocational/technical schools containing Grades 9–12; 2410 students aged 15–18 years were included in the analysis. Overall, 44.9% of males and 46.9% of females were current smokers. Smoking increased with age and was significantly higher among vocational/technical (60.2%) than traditional (43.1%) students. The likelihood of smoking was significantly higher among students who rarely or never used a seatbelt when riding in a car driven by someone else, currently used alcohol, had engaged in episodic heavy drinking, had had four or more sex partners during their lifetime or did not participate in vigorous physical activity. Health-risk behaviors are frequently interrelated. Findings suggest that programs designed to prevent smoking should consider related health-risk behaviors as part of a comprehensive program.
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Introduction |
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To date, studies of smoking-related health behavior risk factors have rarely been undertaken in Hungary. Numerous studies of American youth have found that youth who smoke are more likely to engage in other health-risk behaviors, such as behaviors linked to unintentional and intentional injuries, alcohol and other drug use, physical inactivity, unhealthy dietary behaviors, and sexual behaviors that contribute to unintended pregnancy and sexually transmitted diseases (including HIV infection) (Torabi et al., 1993
; US Department of Health and Human Services, 1994; Willard and Schoenborn, 1995; Escobedo et al., 1997; Everett et al., 2000). These behaviors, which are often interrelated, begin in early adolescence. Problem Behavior Theory (PBT) proposes that problem behaviors constitute a ‘syndrome’ or clustering of problem behaviors that center around a common underlying factor of ‘unconventionality’ in both personality and social environment (Donovan and Jessor, 1985). In the Adverse Childhood Experiences (ACE) Study, however, Anda suggested a different interpretation of problem behavior—that youth and adults may use tobacco and other substances to self-medicate underlying pain associated with adverse childhood experiences or depression, and that such substance use may lead to or occur concurrently with other health-risk behaviors such as alcohol use and attempted suicide (Anda et al., 1999).
In Budapest, the capital city of Hungary, rates of smoking among youth have increased substantially. From 1995 to 1999, the prevalence of current smoking increased from 35.9 to 46.0% among secondary students in that city overall, with increases seen regardless of sex, age, grade or school type (i.e. vocational/technical or traditional) (Centers for Disease Control and Prevention, 2000). Delaying or preventing smoking initiation may reduce the occurrence of related health-risk behaviors, and reduce morbidity and mortality in adulthood (US Department of Health and Human Services, 1994).
The objective of the present study was to determine the relationship between cigarette use and other health-risk behaviors among secondary school students in Budapest. The current study examined behaviors related to tobacco use, including behaviors linked to unintentional injuries, attempted suicide, alcohol use, sexual risk behaviors and physical activity. In Hungary, these behaviors, all of which are preventable, contribute to some of the highest rates of death of any Central or Eastern European country from malignant neoplasms, acute myocardial infarction, chronic liver disease and cirrhosis, motor vehicle traffic accidents, and suicide and self-inflicted injury (WHO, 1998; Bray et al., 2000; Proceedings of the 2nd Conference on Health Status of Central and Eastern European Populations After Transition, 2000).
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Methods |
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Study design
The 1999 Budapest Student Health Behavior Survey used a two-stage cluster sampling design to produce a representative sample of secondary students in Grades 9–12 in Budapest (National Center for Chronic Disease Prevention and Health Promotion, 1992
). Among the 80 352 secondary school students in that city in 1999, 67 253 (84%) attended traditional high schools and 13 099 (16%) went to vocational/technical schools. The first stage of sampling consisted of randomly selecting 30 schools (21 traditional and nine vocational/technical) from the 222 secondary schools in Budapest. Schools were selected with a probability proportional to their enrollment. In the second sampling stage, three to four intact classes were randomly selected in Grades 9–12 at each of the 30 schools. All students in the selected classrooms were eligible for the survey, and all selected schools and classrooms agreed to participate.
From March through May of 1999, 2615 (85%) of the 3092 eligible students completed a pre-tested, standardized questionnaire translated from the US Youth Risk Behavior Survey (YRBS) that included questions on demographics, behaviors related to unintentional injuries, suicide attempts, smoking, alcohol use, sexual activity and physical activity (Centers for Disease Control and Prevention, 1998). Questions on depression were adapted from the US Teenage Attitudes and Practices Survey (Allen et al., 1992; Centers for Disease Control and Prevention, 2003). The questionnaire contained 61 multiple-choice questions and one open-ended question. The survey was developed in English, translated into Hungarian and then translated back into English to ensure clarity. Before survey administration, the questionnaire was pilot tested on a volunteer sample of 20 secondary students in Budapest to revise wording of the items. Psychometric review of the instrument has been presented elsewhere; the reliability of survey items has been found to be good in test–re-test procedures (Kolbe et al., 1993; Brener et al., 1995; Centers for Disease Control and Prevention, 1998). In Budapest, YRBS survey administration procedures were carefully followed to ensure anonymity and validity of responses (Kolbe et al., 1993; Brener et al., 1995; Centers for Disease Control and Prevention, 1998). Participation was voluntary and all information was collected anonymously. Students completed the self-administered questionnaire during a regular class period, recording their responses directly on the survey. Active, informed parental consent was required of all participants before administration.
Data analysis
Students were asked on how many days of the preceding 30 days they had smoked cigarettes; current smokers were those who reported smoking on 1 or more days of the preceding 30 days. Five independent variables were examined in relation to current smoking:
- Alcohol use. Current alcohol use was defined as drinking alcohol on at least 1 of the 30 days preceding the survey, episodic heavy drinking as drinking 5 or more drinks of alcohol on 1 or more of the preceding 30 days.
- Behaviors related to unintentional injury. Three behaviors were included: rarely/never use a seatbelt when riding in a car driven by someone else, riding with a driver who had been drinking alcohol (on at least 1 day of the 30 days preceding the survey) and driving after drinking (on at least 1 day of the preceding 30 days).
- Attempted suicide. Respondents who had ever attempted suicide were considered positive for this behavior.
- Sexual risk behaviors. Students were asked whether they had ever had sexual intercourse. Those who answered affirmatively were asked whether they (1) had had four or more lifetime sex partners, (2) were current sexually active, i.e. had had intercourse in the preceding 3 months (among those who have ever had sexual intercourse) and (c) had used a condom during last sexual intercourse.
- Physical activity. Students were asked whether during the preceding 7 days they had engaged in vigorous physical activity (activities that made them sweat and breathe hard) for 20 min or more on 3 or more days or moderate physical activity (activities that did not make them sweat and breathe hard) for 30 or more min on 5 or more days.
The prevalence of current smoking and factors associated with current smoking were estimated through weighted frequencies, 
2 and logistic regression analyses. In total, 2410 students aged 15–18 years were included in the analysis. A weighting factor was applied to each student record to adjust for non-response and for varying probabilities of selection. SUDAAN was used to compute 95% confidence intervals and account for clustering by schools (Shah, 1997). The intraclass correlation coefficient was 0.00116, with a design effect of 1.1. Differences between estimates were considered significant at the P < 0.05 level. Independent variables significantly associated with current smoking in the univariate analysis were entered into an initial logistic regression model. These significant variables included various behaviors classified under alcohol use, unintentional injury, intentional injury, sexual risk behaviors and physical activity (Table II). Least significant variables were dropped one at a time using backward elimination. School type, age, grade and sex were included as potential confounders, and remained in the final model (Table IV), which had a good fit (Hosmer and Lemeshow goodness-of-fit statistic, 0.9149 with 1 d.f.; P = 0.3388).
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Results |
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An estimated 46% of students were current smokers, with prevalence varying little by sex (male 44.9%, female 46.9%). Students aged 18 years (51.8%) were significantly more likely than younger students (15 years, 37.2%) to be current smokers. Vocational/technical students (60.2%) were significantly more likely than traditional high school students (43.1%) to be current smokers (Table I).
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Current smokers were significantly more likely than those not currently smoking to be users of alcohol (86.5 versus 51.6%) and to have engaged in episodic heavy drinking (36.8 versus 8.8%), to rarely or never use a seatbelt when riding in a car driven by someone else (37.8 versus 21.5%), to have ridden with a driver who had been drinking alcohol (26.6 versus 11.8%), to drive after drinking (7.2 versus 2.3%), to have attempted suicide (6.9 versus 2.6%), and to have ever had intercourse (60.7 versus 26.8%) (Table II). Among those who had ever had sex, current smokers were significantly more likely to have had four or more partners (33.9 versus 16.3%) and to be currently sexually active (73.8 versus 67.4%). Current smokers were significantly less likely than non-current smokers to participate in vigorous physical activity (55.4 versus 61.5%).
The full logistic regression model is presented in Table III. Riding with a driver who had been drinking alcohol, driving after drinking, having attempted suicide, ever having sexual intercourse and being currently sexually active were dropped from the final model because they did not reach statistical significance. After adjustment for school type, age, grade and sex in the final model (Table IV), factors associated with current smoking included rarely/never using a seatbelt when riding in a car driven by someone else [odds ratios (OR) = 1.47, 95% confidence interval (CI) = 1.18–1.84, P = 0.0007], current alcohol use (OR = 4.10, 95% CI = 3.25–5.19, P < 0.0001), episodic heavy drinking (OR = 2.90, 95% CI = 2.19–3.83, P < 0.0001) and having had four or more sex partners lifetime (OR = 2.24, 95% CI = 1.53–3.30, P < 0.0001). Students who smoked were significantly more likely than students who did not smoke to have not participated in vigorous physical activity (OR = 1.36, 95% CI = 1.11–1.67, P = 0.0030) (Table IV).
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Discussion |
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The findings of this study, which were based on Hungary's largest city, are the first of their kind, and underscore a central principle of adolescent behavior seen throughout Central and Eastern Europe and the US—smoking is a strong marker for engaging in other important health-risk behaviors. Of particular concern is that from 1995 to 1999 smoking prevalence among secondary school students in Budapest increased by more than 10 percentage points (Centers for Disease Control and Prevention, 2000
). Although the Hungarian Parliament passed stronger legislation in 1999 to enforce restrictions on smoking in the workplace and other public places, no regulation of the sale of cigarettes to minors occurred until 1999 and beginning in 1997 there were fewer advertising restrictions. Other factors that may have contributed to this substantial increase in smoking uptake, including free distribution of cigarette samples, weak health warnings, availability of contraband cigarettes, low fines for advertising violations and lack of enforcement of existing regulations (World Tobacco Marketfile, 2000).
The rising popularity of American brands in Hungary may also have contributed to the substantial increase in smoking uptake among Budapest youth. In 1996, Philip Morris increased its overall market shares in Hungary by 5%, placing it in second place in the country; the increase in shares was attributed to gains by both of its leading international brands, Multifilter and Marlboro (World Tobacco Marketfile, 2000). Among Budapest youth, however, American brands are by far the most popular brands smoked. Among secondary students surveyed who were current smokers, 36% smoked Multifilter and 31.3% smoked Marlboro. Less than 7% smoked Sopiane, one of the most popular Hungarian brands (unpublished data from the 1999 Budapest Student Health Behavior Survey). The great popularity of American cigarettes may have spurred many young people to become smokers as a way, perhaps, of embracing the popular culture of the US.
Our findings of a linkage between health-risk behaviors and smoking are consistent with previous research. For example, the US Surgeon General's Report Preventing Tobacco Use Among Young People found that youth who smoke are more likely to drink alcohol, get into fights, carry weapons, attempt suicide and engage in high-risk sexual behaviors, and they are less likely to wear seatbelts (US Department of Health and Human Services, 1994). Willard and Schoenborn found a consistent association between smoking and other health-risk behaviors (Willard and Schoenborn, 1995), and Everett et al. found that, in general, tobacco-using students are more likely to engage in other substance use, intentional injury risk behaviors and sexual risk behaviors (Everett et al., 2000). Additionally, Escobedo et al. found an association between smoking and binge drinking, as was found in the current study (Escobedo et al., 1997).
The present study has several limitations. First, as it was cross-sectional the authors could not identify temporal relationships between smoking and other health-risk behaviors. Second, the authors were not able to query students about other substance use because of concerns related to legislation on illicit drug use that was passed in Hungary several weeks before the survey (É. Kiss, personal observation, 2001). Third, these data apply only to youth who attended secondary school and thus are not representative of all persons in this age group [e.g. secondary school students who dropped out and the approximate 80% of gypsy children who do not attend secondary school; 4% of Hungary's population is Roma (gypsy)] (Kézdi, 1999; Central Intelligence Agency, 2000). Lastly, information on smoking relied on self-reported data.
Explanations vary as to why youth who smoke are more likely to engage in other health-risk behaviors. As per the PBT proposed by Jessor and Jessor (Jessor and Jessor, 1977), involvement in one behavior increases the likelihood of involvement in others. This activity occurs during a period in adolescence when youth are learning about themselves and others, and engage in risk behaviors together. Michaud et al., however, have argued that this approach, which commonly uses recognized models of explaining health-risk behaviors, while useful for population studies, may not translate to the individual level (Michaud et al., 1998). Youth are in great transition such that what might be true at one moment may be different at another and thus a model might not be useful. In addition, youth have different experiences and skills in addressing experimentation that so often comes with adolescence. These experiences and skills, particularly the ones which are protective against health-risk behaviors, are often overlooked in behavioral models.
As noted earlier, the ACE Study represents another possible explanation. Anda and colleagues found a dose–response relationship between the number of adverse childhood experiences (e.g. physical, mental, emotional abuse) and the prevalence of smoking. Early smoking initiation was reported by just 8.7% of persons who had one adverse childhood experience compared to 21.1% who had five or more. These findings suggest that tobacco and other substances are a mechanism of self-medicating for various reasons, including adverse childhood experiences or depression (Anda et al., 1999).
The observed increase in smoking among youth in Budapest may lead to increases in other heath-risk behaviors, eventually further increasing Hungary's existing high rates of malignant neoplasms, acute myocardial infarction, and chronic liver disease and cirrhosis. In the US as well as many European countries, motor vehicle crashes, suicide and interpersonal violence are leading causes of death among adolescents (Kaminsky et al., 1991; Guyer et al., 1995). To have a beneficial impact on present and future smoking-related morbidity and mortality, underlying social issues such as unemployment and education need to be addressed when working to prevent youth from initiating smoking or to get youth and adults already smoking to quit. Additionally, programs shown to be effective in keeping youth smoke-free that also address accompanying health-risk behaviors should be implemented as part of a comprehensive program (Centers for Disease Control and Prevention, 1994). Such efforts are further advanced when targeted community programs that address the role of families, community organizations, tobacco-related policies, anti-tobacco advertising and other elements of adolescents' social environments are added (US Department of Health and Human Services, 1994).
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Acknowledgments |
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At the time of this study A. E. was a fellow in the Epidemic Intelligence Service (EIS) Program, Epidemiology Program Office, Centers for Disease Control and Prevention, Atlanta, GA.
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Received on June 10, 2003; accepted on February 17, 2004
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