bmj openfor peer review only 25 1 16. filippidis ft, agaku it, vardavas ci. the association between...

For peer review only

Sport and scholastic factors in relation to smoking and smoking initiation in older adolescents: a prospective cohort

study in Bosnia and Herzegovina

Journal: BMJ Open

Manuscript ID bmjopen-2016-014066

Article Type: Research

Date Submitted by the Author: 29-Aug-2016

Complete List of Authors: Sekulic, Damir; University of Split, Faculty of Kinesiology; University of Split, University Department of Health Care Studies Sisic, Nedim; University of Split, Faculty of Kinesiology; University of

Zenica Terzic, Admir; University of Tuzla Jasarevic, Indira; University of Tuzla Ostojic, Ljerka; University of Mostar; University of Split, Faculty of Kinesiology Pojskic, Haris; Mid Sweden University, Department for Health Sciences Zenic, Natasa; University of Split, Faculty of Kinesiology

<b>Primary Subject Heading</b>:

Epidemiology

Secondary Subject Heading: Public health

Keywords: cigarettes, educational achievement, sports, puberty, association

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Sport and scholastic factors in relation to smoking and smoking initiation in older

adolescents: a prospective cohort study in Bosnia and Herzegovina

Damir Sekulic 1,2

, Nedim Sisic 1,3, Admir Terzic

4,5, Indira Jasarevic

5, Ljerka Ostojic

1,6,7,

Haris Pojskic 8,9, Natasa Zenic

1

1 Faculty of Kinesiology; University of Split, Teslina 6, Split – 21000, Croatia

2 University Department of Health Care Studies, Split- 21000, Croatia

3 University of Zenica, Fakultetska 3, Zenica – 23000, Bosnia and Herzegovina

4 High School Hasan Kikic, Sarajevska 1, Gradacac-76250, Bosnia and Herzegovina

5 Faculty of Physical Education and Sport, University of Tuzla, 2nd October 1, Tuzla-75000,

Bosnia and Herzegovina

6 University of Mostar, Matice Hrvatske bb, Mostar – 63000, Bosnia and Herzegovina

7 Academy of Medical Sciences of Bosnia and Herzegovina, Sarajevo, Bosnia and Herzegovina

8 Mid Sweden University, Department for Health Sciences, Östersund - 83125, Sweden

9 Mid Sweden University, Swedish Winter Sports Research Centre, Östersund - 83125, Sweden

Corresponding author: Natasa Zenic; Faculty of Kinesiology; University of Split, Teslina 6, Split

– 21000, Croatia; [email protected]

Key words: cigarettes, educational achievement, sports, puberty, association

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ABSTRACT

Objective

Sport- and scholastic-factors are known to be associated with cigarette-smoking in adolescence,

but little is known about the causality of this association. The aim of this study was to

prospectively explore the relationships of different sport- and scholastic-factors with smoking-

prevalence and smoking-initiation in older adolescents from Bosnia and Herzegovina.

Methods

In this 2-year prospective cohort study, the participants were 872 adolescents who were 16 years

of age at baseline (46% females). The study consisted of baseline tests at the beginning of the 3rd

year of high-school (September 2013) and follow-up testing at the end of the 4th year of high-

school (late May – early June 2015). The independent variables were scholastic- and sport-related

factors. The dependent variables were (i) smoking at baseline, (ii) smoking at follow-up, and (iii)

smoking-initiation over the course of the study. Logistic regressions controlled for age and

gender and were applied to define the relationships between independent and dependent

variables.

Results

School absence at baseline was a significant predictor of smoking initiation during the course of

the study (OR: 1.4, 95%CI: 1.1 – 1.8). Those who reported quitting sports at baseline showed an

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increased risk of smoking at the end of the study (OR: 1.4, 95%CI: 1.1 – 2.0) and of smoking

initiation (OR: 1.8, 95%CI: 1.3 – 2.0). Adolescents who reported lower competitive achievements

in sport were at a higher risk of (i) smoking at baseline (OR: 1.5, 95%CI: 1.1 – 2.1), (ii) smoking

at follow-up (OR: 1.5, 95%CI: 1.1 – 2.1), and (iii) smoking initiation (OR: 1.6, 95%CI: 1.1 –

2.6).

Conclusions

In developing accurate anti-smoking public health policies for older adolescents, the most

vulnerable groups should be targeted. The results showed that most participants initiated smoking

before 16 years of age. Therefore, further investigations should evaluate the predictors of

smoking in younger ages.

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Article focus

• A prospective examination of the associations of scholastic achievement and sport factors

with smoking in 16- to 18-year-old adolescents was conducted, specifically investigating

whether the observed scholastic and sports factors were related to smoking and smoking

initiation in the last two years of high school.

Key messages

• The smoking prevalence among adolescents continues to rise between 16 (28% smokers) and

18 years of age (36% smokers).

• Absence from school, withdrawal from sports, less than 5 years of involvement in a sport, and

low sport competitive achievement at baseline (beginning of the 3rd year of high school) are

associated with smoking initiation in the following two years.

• Most of the studied participants initiated smoking before the age of 16 years, and future

studies should explore the predictors of smoking during the first two years of high school.

Strengths and limitations of the study

• Data were self-reported, but as the study was strictly anonymous and conducted in a country

where smoking is socially accepted, the possibility that participants did not respond honestly

is lower.

• The study lacks qualitative data on the reasons for withdrawal from sports, which limits the

possibility of a more detailed interpretation of the obtained results.

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• The majority of participants initiated smoking before 16 years of age, and therefore the

generalizability of the results regarding the predictors of smoking initiation is limited solely

to adolescents who initiated smoking in late adolescence (16 to 18 years of age).

• This is one of the first studies to prospectively investigate the predictors of smoking in

southeastern Europe.

• The high retention rate (87% of the adolescents studied at baseline and follow-up) and low

rate of missing data are important strengths of the study.

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INTRODUCTION

Cigarette smoking is an important modifiable determinant of health, and preventing

smoking initiation among adolescents eliminates the numerous health risks they would face as

adult smokers [1 2]. With more than 20% of adolescents who smoke cigarettes daily, Bosnia and

Herzegovina is among the five European countries with the highest prevalence of smoking

among adolescents, together with Austria (>20%), Croatia (>20%), Belgium (<20%) and

Hungary (<20% daily smokers) [3-6]. This high prevalence is mostly explained by the low prices

of tobacco products, social acceptance of smoking in public, and the lack of effective public

health campaigns against smoking [7]. Consequently, in the last couple of years, several

investigations have explored the problem of adolescent smoking in Bosnia and Herzegovina and

found different sociodemographic, economic, community-specific, sport-related, and scholastic

factors to be associated with cigarette smoking [4 5 8]. Some factors including parental/familial

variables are confirmed to be strongly correlated to smoking, with a lower prevalence of smoking

in adolescents who reported stronger parental control and lower levels of conflict with

parents/family [7]. However, the relationships between the other potentially important covariates

such as scholastic and/or sport factors and smoking behaviour are not clear.

Poor performance in school is regularly observed in adolescents from Bosnia and

Herzegovina who smoke, and this is in accordance with findings of studies conducted in other

countries [7 9-11]. However, it remains unknown whether smoking results in poor scholastic

achievement or whether this relationship occurs in the opposite direction. The first explanation

implies that smoking is the cause of poor performance in school based on physiological

mechanisms and the negative effects of smoking on cognitive function [12]. In brief, smoking is

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known to be related to negative alterations in brain structure and could therefore result in reduced

memory and cognitive ability and poor performance in school [13-15]. Meanwhile, some

theoreticians are of the opinion that smoking should be observed as an effect, and not the cause,

of scholastic failure [8 16]. Namely, children who fail academically are frequently in out-of-

school situations where they are directly and/or indirectly exposed to individuals who smoke and

are therefore at higher risk of smoking themselves [5 7]. In most cases, the cross-sectional design

of the studies did not allow for the interpretation of the cause-effect relationship between

educational achievement in high school and smoking status [7 8 12].

Participation in sports promotes social well-being, improves physical and mental health

and increases self-discipline among young people [17]. Therefore, it is often hypothesized that

sport participation could be an effective way of reducing the tendency of adolescents to smoke

cigarettes [18-21]. Indeed, when investigators compared groups of adolescent athletes vs. non-

athletes and/or related participation in sports to smoking prevalence in this age group, the results

mostly showed a lower prevalence of smoking in those involved in sports [22-24]. However,

when sport participation was analysed more accurately and specifically (i.e., with regard to type

of sport, achievement, intensity, current – former involvement), there were some conflicting

findings on the association between sports and cigarette smoking [25-27]. For example, recent

studies specifically investigated three levels of sport involvement (never involved – quit –

currently involved) and found that adolescents who had stopped participating in a sport were at

high risk of misusing substances. Additionally, lower competitive achievement in sports was

found to be associated with a higher likelihood of cigarette smoking [4 7 26]. Again, because of

the cross-sectional study design, the causality is not clear. Indeed, smoking could impair physical

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capacity, thus leading to poor sport performance (low result) and consequent withdrawal from

sport. On the other hand, it is also possible that adolescents first stopped participating in sports

(possibly even because they were non-successful) and then started to smoke. Specifically,

children who quit participating in a sport could start smoking because they have more free time

and/or after because after quitting, they suddenly became part of a socio-cultural environment in

which smoking was more common [26 27].

Given the alarmingly high rates of adolescent smoking in adolescents from Bosnia and

Herzegovina, as well as the findings of recent studies that highlighted the need for prospective

designs to identify the predictors of smoking [5 8], this investigation aimed to prospectively

explore the potential relationships between scholastic and sport factors at the beginning of the 3rd

year of high school and smoking and smoking initiation in the following two years (from 16 to 18

years of age on average) in adolescents from Bosnia and Herzegovina. Understanding the

relationships studied here may help inform all responsible parties about the specific risks and

benefits related to the studied covariates of smoking. Although there are other potential predictors

of smoking, in this study, we were specifically focused on scholastic and sport factors, as both

groups of factors are regularly and independently monitored throughout the school system and a

better understanding of the associations could help develop cost-effective and targeted preventive

interventions.

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METHODS

Procedures and participants

To extend the findings of previous cross-sectional studies in Bosnia and Herzegovina and

the region [4 8 27 28], in this study, we aimed to prospectively investigate adolescents over their

last two years of high school (from 16 to 18 years of age). At baseline, the examinees were 16

years old on average and were in their 3rd year of high school. A multi-stage simple random

sampling method was used to select the participants. First, by lottery, we selected one-third of the

high schools in the territory of Zenica-Doboj Canton and Tuzla Canton, two typical regions in

Bosnia and Herzegovina. School size varied by just 10-15%, and therefore the schools were not

stratified by size. In the second stage of sampling, half of all 3rd year classes were selected via

lottery from the selected schools, resulting in a sample size of 44 classes and a cohort of 1213

participants. After obtaining the necessary ethics approvals (see later text), study personnel

explained the full procedure and study aims to potential participants and at least one

parent/guardian in a regular school meeting. Passive informed consent was obtained, and none of

the parents refused to let their child participate in the study. Finally, all children who were

present at school on the day of the testing were surveyed. This was one of the first studies to

prospectively investigate the correlates of smoking in adolescents in south-eastern Europe, and

we have tried to expand on previous findings of cross-sectional investigations performed in

similar samples [5 8]. Therefore, the authors are of the opinion that the sample included in this

study met the eligibility criteria necessary to objectively compare the results with those

previously reported.

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Two surveys were conducted, one (baseline) at the beginning of the 3rd year of high school

(September 2013), and the second (follow-up) at the end of high school (late May - early June

2015). Surveys were administered during school hours in groups of at least 15 examinees.

Examinees were assured that their participation was voluntary and that they could leave some of

the questions and/or the entire questionnaire blank. The study participants remained anonymous

(no personal data were collected), but the participants were asked to use self-selected confidential

codes for identification purposes in the repeated test. They were suggested to use the last three

digits of their e-mail password as their code for identification (i.e., these codes were easy to

remember between testing waves while being simultaneously confidential). After completing the

surveys, each participant placed the questionnaire in an envelope and then in a closed box. The

next day, an investigator who was not present during survey administration opened the boxes.

The study fulfilled all ethical guidelines and received the approval of the Ethical Boards from

University of Mostar, Bosnia and Herzegovina, and University of Split, Croatia, and was

officially authorised by the Ministry of Education, Science, Culture and Sports of Zenica-Doboj

Canton and Tuzla Canton. The study design and sampling is presented in Figure 1. Of the

theoretical sample of 1213 adolescents, 1164 responded to the first survey (96% response rate),

and of those, 1079 participated in the final survey (89% response rate). Additionally, 20

questionnaires were not included because of inconsistency in the identification code (87%

response rate). As a result, the drop-out rate was 13%. As 82% of the participants tested at both

waves were identified as Bosniaks, and as previous studies have frequently reported the influence

of ethnicity on tendency towards smoking [29-31], in this study, we included only participants

who were ethnic Bosniaks. Therefore, the sample of participants studied herein included 872

participants, of whom 404 were female (46%). It must be noted that 187 examinees who

responded to all surveys but were not identified as Bosniaks were not included as non-responders

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and were therefore not included in the drop-out rate. The analysis of attrition bias showed no

significant differences in initial smoking status between adolescents who dropped-out and those

who remained in the study (Chi square: 2.11, p > 0.05), but there were significantly more males

than females who dropped out (Chi square: 8.00, p < 0.01) (Table 1).

Table 1

Attrition bias analysis between responders and non-responders on a basis of smoking status and gender

Responders Non-responders Chi square (p)

Smokers Males 160 23

Females 156 14

Nonsmokers Males 252 53

Females 304 35

Subtotal smokers 316 37 2.11 (0.15)

Subtotal nonsmokers 556 88

Subtotal males 412 76 8.00 (0.01)

Subtotal females 460 49

Total 872 125

LEGEND: Note that group of non-responders does not include participants who were not present at the baseline testing (49 participants) but includes those who used inconsistent identification codes at testing waves (20 participants)

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Variables

The variables were collected using the Questionnaire of Substance Use, which was previously

reported to be a reliable and valid measuring tool in similar samples of participants.

Questionnaire was previously checked for reliability and validity, and results are presented in

details elsewhere [4 8]. In this study, we collected data on age (in years), gender, ethnicity

(Bosniak, Serbian, Croatian, other), sport factors, scholastic factors and consumption of

cigarettes.

Sports factors consisted of questions about subjects’ (i) involvement in sports (answers included:

never been involved, quit, currently involved); (ii) highest competitive achievement in sports

(never competed/did not participate in sports, local rank competitions, national and international

rank competitions); and (iii) time of involvement in sports (never involved, less than a year, 2-5

years, 5+ years). Scholastic variables represented participants’ academic achievement over the

last semester: (i) grade point average; (ii) behavioural grade (both on a five-point scale ranging

from excellent to poor); and (iii) school absences (number of absences in teaching hours).

Cigarette smoking was assessed on a six-point scale with the following responses: “No”, “From

time to time, but not daily”, “Less than 10 cigarettes daily”, and “More than 10 daily”.

Participants were later classified as non-smokers or smokers. Information on smoking initiation

during the course of the study was obtained from each participant. Specifically, if the participant

reported not smoking at baseline and responded differently when tested at follow-up, the

initiation of smoking was indicated.

Statistics

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For all variables, descriptive statistics (counts and percentages or means and standard

deviations) were calculated. Depending on the characteristic of the variable, the differences

between smokers and non-smokers were established by Mann-Whitney test (for ordinal

variables), or Chi square test (for categorical variables). Binary logistic regression was used to

estimate the Odds Ratio (OR) and corresponding 95% Confidence Interval (95%CI) of the

following: (i) smoking status at baseline, (ii) smoking status at the end of the study, and (iii)

smoking initiation occurring during the course of the study by scholastic and sport covariates.

The crude logistic regression models (Model 1) were additionally adjusted for gender and age

(Model 2).

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RESULTS

Table 2 presents the distribution of independent variables according to smoking status at

baseline and follow-up. Overall, 28% of adolescents were identified as smokers at the beginning

of their 3rd year of high school, and 36% were smokers at the end of high school 20 months later.

An evident increase in smoking prevalence over the observed period was evident in females

(from 27 to 38%, and 30 to 34.5% for females and males, respectively. At baseline and at follow-

up, non-smokers achieved better grade point averages (MW: 6.03 and 6.36, p < 0.01) and better

behavioural grades (MW: 7.76 and 7.71, p < 0.01) and were less absent from school (MW: 5.60

and 9.30, p < 0.01, for baseline and follow-up, respectively) than smokers. Non-smokers

achieved higher sport result than smokers at baseline (MW: 6.03, p < 0.01).

Table 2

Baseline and follow-up characteristics with differences on a basis of smoking status (MW – Mann Whitney Z values; Chi square test)

Baseline Follow-up

Smokers Nonsmokers MW Smokers Nonsmokers MW

f (%) f (%) Z (p) F (%) F (%) Z (p)

Experience in sport 1.54 (0.12) 0.93 (0.34)

Never been involved 180 (28.8) 56 (22.6) 174 (31.3) 62 (19.6)

Less than a year 132 (21.2) 56 (22.6) 104 (18.7) 84 (26.6)

2-5 years 164 (26.3) 72 (29) 136 (24.5) 100 (31.6)

>5 years 148 (23.7) 64 (25.8) 142 (25.5) 70 (22.2)

Sport success/result 2.34 (0.02) 0.96 (0.33)

Never competed 344 (55.1) 114 (46) 308 (55.4) 150 (47.5)

Local rank 230 (36.9) 116 (46.8) 204 (36.7) 142 (44.9)

National/International 44 (7.1) 18 (7.3) 40 (7.2) 22 (7)

Grade Point Average 6.03 (0.01) 6.36 (0.01)

Excellent 262 (42) 66 (26.6) 242 (43.5) 86 (27.2)

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Very good 246 (39.4) 96 (38.7) 222 (39.9) 120 (38)

Average 106 (17) 76 (30.6) 86 (15.5) 96 (30.4)

Under average 6 (1) 4 (1.6) 2 (0.4) 8 (2.5)

Poor 4 (0.6) 6 (2.4) 4 (0.7) 6 (1.9)

Behavioral Grade 7.76 (0.01) 7.71 (0.01)

Excellent 538 (86.2) 180 (72.6) 500 (89.9) 218 (69)

Very good 46 (7.4) 26 (10.5) 24 (4.3) 48 (15.2)

Average 30 (4.8) 28 (11.3) 24 (4.3) 34 (10.8)

Under average 6 (1) 8 (3.2) 6 (1.1) 8 (2.5)

Poor 4 (0.6) 6 (2.4) 2 (0.4) 8 (2.5)

School Absence 5.60 (0.01) 9.30 (0.01)

Almost never 244 (39.1) 52 (21) 246 (44.2) 50 (15.8)

Rarely 244 (39.1) 102 (41.1) 206 (37.1) 140 (44.3)

From time to time 108 (17.3) 78 (31.5) 90 (16.2) 96 (30.4)

Often 28 (4.5) 16 (6.5) 14 (2.5) 30 (9.5)

Chi Sq (p) Chi Sq (p)

Gender 0.82 (0.36) 1.32 (0.25)

Male 138 (29.7) 326 (70.3) 160 (34.5) 304 (65.5)

Female 110 (27.0) 298 (73.0) 156 (38.2) 252 (61.8)

Sport participation 0.46 (0.80) 3.79 (0.15)

Currently involved 128 (20.5) 56 (22.6) 118 (21.2) 66 (20.9)

Quit 206 (33) 80 (32.3) 170 (30.6) 116 (36.7)


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Increased odds of smoking were observed in adolescents with a lower grade point average

at baseline (Baseline: Model 1&2: OR 1.6, 95%CI 1.4-1.9; Follow-up: Model 1: 1.6, 1.4-1.9;

Model 2: 1.7, 1.5-2.0), poorer behavioural grades (Baseline: Model 1: 2.5, 1.9-3.3, Model 2: 2.6,

1.9-3.4; Follow-up: Model 1: 2.1, 1.6-2.7, Model 2: 2.3, 1.7-2.9) and more frequent absences

from school (Baseline: Model 1&2: 1.6, 1.4-2.0, Follow-up: Model 1: 1.8, 1.5-2.1, Model 2: 1.8,

1.5-2.2). School absence at baseline was a significant predictor of smoking initiation over the

course of the study (Model 1: 1.4, 1.1 – 1.8, Model 2: 1.4, 1.1.-1.8). Involvement in sports was

not associated with smoking status at baseline, but those who reported quitting sports showed an

increased risk of smoking at the end of the study (Model 1: 1.4, 1.0-1.9; Model 2: 1.4, 1.1-2.0)

and a higher risk of smoking initiation during the study course (Model 1: 1.7, 1.1—2.7; Model 2:

1.8, 1.2-3.0). Adolescents who were engaged in sports for less than 5 years showed a higher

prevalence of smoking at the end of the study and an increased risk of smoking initiation during

the course of the investigation (Model 1: ORs 2.1-2.8; Model 2: ORs 2.4-3.4). Finally, compared

with peers who were never involved in sports, those who reported involvement in sports

competitions but with lower competitive results were at a higher risk of the following: (i)

smoking at baseline (Model 1&2: 1.5, 1.1-2.1), (ii) smoking at the end of the study (Model 1: 1.4,

1.1-1.9; Model 2: 1.5, 1.1-2.1), and (iii) smoking initiation (Model 1: 1.5, 1.0-2.2; Model 2: 1.6,

1.1-2.6) (Table 3).

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Table 3

The ORs for smoking at baseline, smoking at follow up, and smoking initiation over the course of the study

Model 1 Model 2

Smoking at baseline

Smoking at follow up

Smoking initiation

Smoking at baseline


Smoking initiation

Age 0.9 (0.7-1.3) 0.9 (0.6-1.1) 1.0 (0.7-1.5)

Grade Point Average 1.6 (1.4-1.9) 1.6 (1.4-1.9) 1.1 (0.9-1.4) 1.6 (1.4-1.9) 1.7 (1.5-2.0) 1.2 (0.9-1.4)

School Absence 1.6 (1.4-2.0) 1.8 (1.5-2.1) 1.4 (1.1-1.7) 1.6 (1.4-2.0) 1.8 (1.5-2.2) 1.4 (1.1-1.8)

Behavioral Grade 2.5 (1.9-3.3) 2.1 (1.6-2.7) 0.9 (0.6-1.3) 2.6 (1.9-3.4) 2.3 (1.7-2.9) 0.9 (0.6-1.3)

Gender

Male 1.1 (0.8-1.5) 0.8 (0.6-1.1) 0.7 (0.5-1.1)

Female REF REF REF

Sport participation

Currently involved 1.1 (0.8-1.7) 1.2 (0.8-1.6) 1.2 (0.8-1.8) 1.1 (0.7-1.6) 1.2 (0.8-1.8) 0.9 (0.5-1.8)

Quit 1.0 (0.7-1.4) 1.4 (1.0-1.9) 1.7 (1.1-2.7) 0.9 (0.7-1.4) 1.4 (1.1-2.0) 1.8 (1.2-3.0)

Never been involved REF REF REF REF REF REF

Experience in sport


Less than a year 1.3 (0.9-2.1) 2.3 (1.5-3.4) 2.6 (1.4-4.9) 1.4 (0.9-2.1) 2.5 (1.6-3.8) 2.9 (1.5-5.5)

2-5 years 1.4 (0.9-2.1) 2.1 (1.4-3.0) 2.8 (1.5-5.2) 1.4 (0.9-2.1) 2.4 (1.6-3.6) 3.4 (1.8-6.4)

>5 years 1.4 (0.9-2.1) 1.4 (0.9-2.0) 1.1 (0.6-2.3) 1.4 (0.8-2.2) 1.5 (0.9-2.6) 1.4 (0.7-3.0)

Sport success/result

Never competed REF REF REF REF REF REF

Local rank 1.5 (1.1-2.1) 1.4 (1.1-1.9) 1.5 (1.0-2.2) 1.5 (1.1-2.1) 1.5 (1.1-2.1) 1.6 (1.1-2.6)

National/International 1.2 (0.7-2.2) 1.1 (0.6-1.9) 0.9 (0.4-2.4) 1.3 (0.7-2.2) 1.2 (0.7-2.1) 1.0 (0.4-2.5)

Model 1: Crude logistic regression model, Model 2: Adjusted for gender and age

DISCUSSION

This study aimed to prospectively investigate the potential relationships between

scholastic and sport factors with smoking in older adolescents. The analyses revealed several

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important findings that should be highlighted. First, baseline scholastic factors were

systematically associated with smoking, with poorer scholastic achievement in adolescents who

reported smoking at baseline and follow-up. The number of school absences at baseline was a

predictor of smoking initiation in the following period. Quitting sports, poor competitive

achievement, and less than 5 years of participation in sports were shown to be specific risks for

smoking and smoking initiation. Prior to discussing these findings, we will provide a brief

overview of the established prevalence and trends in smoking in the observed participants. The

smoking prevalence significantly increased from 28% to 36% during the course of the study.

Consequently, approximately 77% of adolescents who reported smoking at the end of high school

(i.e., 28/36) initiated smoking when they were younger than 16 years. Although participants self-

reported their smoking status, which should be observed as a limitation of the study, the reported

prevalence of smoking in this study is similar to previous reports of a 30-35% prevalence of

adolescent smokers in Bosnia and Herzegovina and the wider territory of former Yugoslavia [4

26 28]. Consequently, the self-reported data on smoking obtained here are plausible. This study is

unique, as it is one of the first to prospectively investigate the factors associated with smoking in

adolescents from southeastern Europe. Therefore, the data on the relationships between scholastic

and sport factors and smoking initiation are particularly interesting.

The associations between baseline scholastic factors and smoking at study baseline (i.e.,

when subjects were 16 years old) and the associations between baseline scholastic factors and

scholastic achievement at the end of the investigation (i.e., end of high school, 18 years of age)

are similar. In both waves, higher odds of smoking are observed in adolescents with lower

scholastic achievement at baseline. Our findings are therefore in accordance with the results of

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previous cross-sectional studies performed with adolescents of a similar age, which repeatedly

reported lower scholastic achievement among children who smoke [8 12 26]. Although there is a

general consensus on the negative associations between smoking and performance in school, the

mechanisms that lead to these associations are still controversial. Some authors highlight the

negative effects of smoking on cognitive capacities, and consequently poorer learning

capabilities, as a result of cigarette smoking [12]. This explanation is strongly supported by the

evident physiological mechanisms (i.e., alterations in brain structure as a result of smoking) [13-

15]. The main criticism of this theory arises from the relatively short period of smoking in

adolescents. Therefore, significant deterioration in cognitive capacities and the resulting low

academic achievement in adolescents is less probable. As a result, it is suggested that lower

academic achievement in adolescent smokers may actually be the cause, and not the effect, of

smoking. Indeed, children who fail at school are frequently in “out of school situations” and

therefore in unique socio-cultural environments in which they are more likely to initiate smoking

[4 5]. This theory thus focuses on social influence. In this study, we showed a negative

relationship between “school absence” at baseline (i.e., 16 years of age) and smoking initiation in

the following 2-year period. Therefore, our results actually support the theory of social influence

as a probable explanation of the cause-effect relationship between academic failure and smoking

in this age group. Briefly, although the general associations between scholastic variables and

smoking are clear, demonstrating that children who smoke perform poorly in school, more

frequent absences from school at the beginning of the 3rd year of high school is a clear predictor

of smoking initiation in the following two years. Of course, one can argue that scholastic

achievement was not entirely objectively evaluated because the data were self-reported. Although

this should be considered an important limitation of the study, we believe that the strict

anonymity of the testing decreased the possibility that the participants responded dishonestly.

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All three sport factors observed in this study were found to be significant predictors of

smoking initiation in older adolescents. First, those who reported at baseline (i.e., when they were

16 years of age) that they had once practiced sports and then quit were at a higher risk of starting

to smoke by the time they were 18. Additionally, a higher risk of initiating smoking was evident

in adolescents who were involved in sports for less than 5 years and in those who practiced sports

but did not achieve significant competitive results. Most probably, the association between these

sport factors and smoking initiation is generated by a unique mechanism. Namely, it is generally

well proven that time of involvement in sports is strongly correlated with sport achievement

(sport results), and better sport results are actually a direct or indirect consequence of a longer

involvement in sport [32 33]. At the same time, a lack of success is one of the most important

factors that result in withdrawing from a sport in adolescence [34]. Although sport pedagogues

have exerted special efforts to keep the majority of children involved in sports regardless of their

competitive results, this is hardly achievable in the later years of high school. The 16- to 18-year-

old adolescents who do not achieve competitive results regularly stop participating in sports at

this particular age, mostly because they became personally aware of their inferiority (i.e., lack of

ability and/or skills). This inferiority was not as obvious before because children’s capacity to

judge their own abilities develops very slowly, and thus at younger ages they do not have a clear

understanding of how successful they may be in competition. Additionally, at the age of 16-18

years, quitting sports is augmented by some real-life circumstances such as friends leaving the

sport, lower parental control and children’s other interests [34]. Very recent studies noted a

higher likelihood of smoking in adolescents who quit sports and those who achieved poorer

competitive results [8 27], but their cross-sectional study design did not allow for the

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interpretation of causality. It was hypothesized that (i) children could start smoking and then stop

practicing a sport, but it was also possible that the mechanism actually occurred in the opposite

direction and that (ii) children quit sports and then start to smoke. Both explanations are probable.

First, (i) it is known that smoking impairs physical capacities, and this could therefore result in

poor sport performance and a lack of success, which would consequently result in withdrawal

from sports [35]. However, (ii) it is also possible that children first stop practicing a sport and

then start to smoke, as a result of the (negative) influence of their new socio-cultural environment

in which smoking is more prevalent [7 8]. The results of our study support the latter explanation,

as all three sport factors were predictors of smoking initiation. In adolescence, individuals

identify with particular groups of peers, and being a member of a social network directly and

indirectly affects a person’s values. Being a member of a specific social network or group

influences individuals’ values as well as their attitudes and the norms to which they are exposed

[17]. Therefore, it is likely that adolescents who quit sports started smoking as a way of adopting

the norms of the “non-sporting” society and of finding a place in a new social-milieu in which

smoking was more prevalent. This study lacks qualitative data on the reasons for quitting sports

and an objective evaluation of lower competitive achievement in sports. This is a clear limitation

of the investigation, as we are not able to accurately explain the background of the relationship

within the sport factors observed herein.

Apart from the limitations discussed previously (i.e., self-reported data, lack of qualitative

evaluation of the reasons for withdrawal from sports), a significant limitation comes from the fact

that this study was conducted in a country in which smoking is socially accepted and where

tobacco products are relatively cheap. However, although the generalizability of the findings is

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somewhat limited, the following conclusions can be made. With 28% of adolescents who started

smoking before they were 16 and an additional 8% who initiated smoking between 16 and 18

years of age, the prevalence of smoking is high. As expected from previous investigations, the

smoking prevalence was higher in adolescents who achieved poor grades in school. This study

expands on previous knowledge by demonstrating that school absences at the age of 16 are a

predictor of smoking initiation over the next two years (i.e., by the end of high school).

Additionally, adolescents who reported quitting sports, those who were involved in sports for a

relatively short time (i.e., up to 5 years), and those who achieved low competitive success by the

age of 16 are found to be at risk of initiating smoking by the end of high school (i.e., 18 years of

age). Therefore, to develop accurate and problem-oriented public health policies against smoking

in older adolescents, public health authorities should cooperate with school and sport

organizations to target the most vulnerable groups of adolescents established in this study.

Although it was not among the primary aims of the study, this was the first investigation that

indirectly showed that the majority of adolescents from Bosnia and Herzegovina started smoking

cigarettes before 16 years of age. Therefore, further investigations should evaluate the predictors

of smoking in younger ages.

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Acknowledgements

Special thanks go to Cantonal Ministries of Education who supported and approved the

investigation. Authors are particularly grateful to all children who voluntarily participated in the

study.

Contributors

DS designed the study, performed statistical analysis and discussed data; NS, AT and IJ

collected the data, overviewed previous research and drafted the manuscript; LO collected the

data and discussed the public health issues of the investigation; HP overviewed the previous

research and discussed the sport factors in relation to smoking; NZ discussed the data and

participated in statistical analyses. All authors have read and approved the final version.

Ethics approval

The Ethical Boards of University of Split, Faculty of Kinesiology, Split, Croatia and

University of Mostar, School of Medicine, Mostar, Bosnia and Herzegovina approved the

Investigation. Additionally, the study was approved by Cantonal Ministries of Education.

Funding

This study and publication were partially financed by the University of Split, Faculty of

Kinesiology, Split, Croatia, and by the University of Mostar, Faculty of Medicine, Mostar,

Bosnia and Herzegovina.

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Conflict of interest

The authors report no conflicts of interest.

Data sharing statement:

Data files are freely available here: https://www.dropbox.com/s/tk2i841ayto8abn/data.sta?dl=0

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Figure legend:

Figure 1

Sampling procedure, participants and non-responders (i.e. absent from school on testing day,

inconsistency in identification codes)

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145x142mm (150 x 150 DPI)

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STROBE 2007 (v4) checklist of items to be included in reports of observational studies in epidemiology*

Checklist for cohort, case-control, and cross-sectional studies (combined)

Section/Topic Item # Recommendation Reported on page #

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract P2

(b) Provide in the abstract an informative and balanced summary of what was done and what was found P2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 6-8 (8)

Objectives 3 State specific objectives, including any pre-specified hypotheses P8; 2nd

para

Methods

Study design 4 Present key elements of study design early in the paper P9 (Figure 1)

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data

collection P9

Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of selection of participants. Describe

methods of follow-up

Case-control study—Give the eligibility criteria, and the sources and methods of case ascertainment and control

selection. Give the rationale for the choice of cases and controls

Cross-sectional study—Give the eligibility criteria, and the sources and methods of selection of participants

Cohort study: P9

(b) Cohort study—For matched studies, give matching criteria and number of exposed and unexposed

Case-control study—For matched studies, give matching criteria and the number of controls per case

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic

criteria, if applicable P12-13

Data sources/ measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe

comparability of assessment methods if there is more than one group P12-13

Bias 9 Describe any efforts to address potential sources of bias NA

Study size 10 Explain how the study size was arrived at Figure 1

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen

and why NA

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding P12-13

(b) Describe any methods used to examine subgroups and interactions P12-13

(c) Explain how missing data were addressed P10-11

(d) Cohort study—If applicable, explain how loss to follow-up was addressed

Case-control study—If applicable, explain how matching of cases and controls was addressed Table 1; P11

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Cross-sectional study—If applicable, describe analytical methods taking account of sampling strategy

(e) Describe any sensitivity analyses

Results

Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility,

confirmed eligible, included in the study, completing follow-up, and analysed Figure 1; P10

(b) Give reasons for non-participation at each stage P10

(c) Consider use of a flow diagram Figure 1

Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and

potential confounders P9, Table 2

(b) Indicate number of participants with missing data for each variable of interest Table 2

(c) Cohort study—Summarise follow-up time (eg, average and total amount)

Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time Tables

Case-control study—Report numbers in each exposure category, or summary measures of exposure

Cross-sectional study—Report numbers of outcome events or summary measures

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95%

confidence interval). Make clear which confounders were adjusted for and why they were included Table 3

(b) Report category boundaries when continuous variables were categorized NA

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses

Discussion

Key results 18 Summarise key results with reference to study objectives Table 18

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction

and magnitude of any potential bias Discussion, end of

each paragraph + P22

(beginning)

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results

from similar studies, and other relevant evidence Discussion

Generalisability 21 Discuss the generalisability (external validity) of the study results P22

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on

which the present article is based

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

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Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE

checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

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Journal: BMJ Open

Manuscript ID bmjopen-2016-014066.R1


Date Submitted by the Author: 05-Dec-2016




Epidemiology

Secondary Subject Heading: Public health, Addiction



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Sport and scholastic factors in relation to smoking and smoking initiation in older 1

adolescents: a prospective cohort study in Bosnia and Herzegovina 2

3

Damir Sekulic 1,2



5, Ljerka Ostojic

1,6,7, 4


1 5

6

1 Faculty of Kinesiology; University of Split, Teslina 6, Split – 21000, Croatia 7

2 University Department of Health Care Studies, Split- 21000, Croatia 8

3 University of Zenica, Fakultetska 3, Zenica – 23000, Bosnia and Herzegovina 9

4 High School Hasan Kikic, Sarajevska 1, Gradacac-76250, Bosnia and Herzegovina 10

5 Faculty of Physical Education and Sport, University of Tuzla, 2nd October 1, Tuzla-75000, 11

Bosnia and Herzegovina 12

6 University of Mostar, Matice Hrvatske bb, Mostar – 63000, Bosnia and Herzegovina 13

7 Academy of Medical Sciences of Bosnia and Herzegovina, Sarajevo, Bosnia and Herzegovina 14

8 Mid Sweden University, Department for Health Sciences, Östersund - 83125, Sweden 15

9 Mid Sweden University, Swedish Winter Sports Research Centre, Östersund - 83125, Sweden 16

17

18

Corresponding author: Natasa Zenic; Faculty of Kinesiology; University of Split, Teslina 6, Split 19

– 21000, Croatia; [email protected] 20

Key words: cigarettes, educational achievement, sports, puberty, association 21

Word Count: 4582 22

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ABSTRACT 1

2

Objective 3

Sport- and scholastic-factors are known to be associated with cigarette-smoking in adolescence, 4

but little is known about the causality of this association. The aim of this study was to 5

prospectively explore the relationships of different sport- and scholastic-factors with smoking-6

prevalence -initiation in older adolescents from Bosnia and Herzegovina. 7

8

Methods 9

In this two-year prospective cohort study, there were 872 adolescent participants (16 years at 10

baseline; 46% females). The study consisted of baseline tests at the beginning of the 3rd year 11

(September 2013) and follow-up at the end of the 4th year of high school (late May – early June 12

2015). The independent variables were scholastic- and sport-related factors. The dependent 13

variables were (i) smoking at baseline, (ii) smoking at follow-up, and (iii) smoking-initiation over 14

the course of the study. Logistic regressions controlled for age, gender, and socio-economic 15

status were applied to define the relationships between independent and dependent variables. 16

17

Results 18

School absence at the baseline study was a significant predictor of smoking initiation during the 19

course of the study (OR: 1.4, 95% CI: 1.1 – 1.8). Those who reported quitting sports at baseline 20

showed an increased risk of smoking at the end of the study (OR: 1.4, 95%CI: 1.1 – 2.0) and of 21

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smoking initiation (OR: 1.8, 95%CI: 1.3 – 2.0). Adolescents who reported lower competitive 1

achievements in sport were at a higher risk of (i) smoking at baseline (OR: 1.5, 95%CI: 1.1 – 2

2.1), (ii) smoking at follow-up (OR: 1.5, 95%CI: 1.1 – 2.1), and (iii) smoking initiation (OR: 1.6, 3

95%CI: 1.1 – 2.6). 4

5

Conclusions 6

In developing accurate anti-smoking public health policies for older adolescents, the most 7

vulnerable groups should be targeted. The results showed that most participants initiated smoking 8

before 16 years of age. Therefore, further investigations should evaluate the predictors of 9

smoking in younger ages. 10

11

12

13

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1

Strengths and limitations of the study 2

• The data was self-reported, but as the study was strictly anonymous and conducted in a 3

country where smoking is socially accepted, the possibility that participants did not respond 4

honestly is lower. 5

• The study lacks qualitative data on the reasons for withdrawal from sports, which limits the 6

possibility of a more detailed interpretation of the obtained results. 7

• The majority of participants started smoking before 16 years of age, and therefore the 8

generalizability of the results regarding the predictors of smoking initiation is limited solely 9

to adolescents who initiated smoking in late adolescence (16to18 years of age). 10

• This is one of the first studies to prospectively investigate the predictors of smoking in south-11

eastern Europe. 12

• The high retention rate (87% of the adolescents studied at baseline and follow-up) and low 13

rate of missing data are important strengths of the study. 14

15

16

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INTRODUCTION 1

Cigarette smoking is an important modifiable determinant of health, and preventing 2

smoking initiation among adolescents eliminates the numerous health risks they would face as 3

adult smokers [1 2]. With more than 20% of adolescents who smoke cigarettes daily, Bosnia and 4

Herzegovina is among the five European countries with the highest prevalence of smoking 5

among adolescents, together with Austria, Croatia, Belgium and Hungary ( all about 20% daily 6

smokers) [3 4]. This high prevalence is mostly explained by the low prices of tobacco products, 7

social acceptance of smoking in public, and the lack of effective public health campaigns against 8

smoking [5]. Consequently, in the last couple of years, several cross-sectional investigations have 9

explored the problem and found different socio-demographic, economic, community-specific, 10

sport-related, and scholastic factors to be associated with adolescent smoking in the country [6 7]. 11

12

Scholastic achievement (educational achievement) is one of the factors known to be 13

associated with smoking in adolescence, with poor performance in school regularly observed in 14

adolescents who smoke [5 8-10]. However, the causality remains unknown. One possible 15

explanation implies that smoking is the cause of poor performance in school because of the 16

physiological mechanisms and the negative effects of smoking on cognitive function and learning 17

capacities [11-13]. Meanwhile, some authors are of the opinion that smoking should be observed 18

as an effect, and not the cause, of educational failure [7 14]. For example, children who fail 19

academically are frequently in out-of-school situations where they are directly and/or indirectly 20

exposed to individuals who smoke and are therefore at higher risk of smoking themselves [5 6]. 21

Indeed, social influences are known to be important with respect to a wide range of health 22

behaviours, including smoking, and such peer influence on smoking is also logical [15 16]. 23

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However, it is also possible that other factors, such as parental conflict, and/or poor familiar 1

control, result in both educational failure and smoking. Additionally, the association is in some 2

cases explained by the “theory of problem behaviour” (i.e. that the problem behaviours such as 3

failure in school and smoking often appear in tandem because some people have a psychosocial 4

tendency for unconventionality) [17]. Regardless of the background, the cross-sectional design of 5

the studies did not allow for the interpretation of the cause-effect relationship between 6

educational achievement in high school and smoking status [5 7 18]. 7

8

Participation in sport is often considered as a potentially effective way of reducing the 9

tendency of adolescents to smoke cigarettes [19-22]. Indeed, when comparing groups of 10

adolescent athletes vs. non-athletes, there is a lower prevalence of smoking in those involved in 11

sports [23-25]. However, when sport participation was analysed more specifically there were 12

some conflicting findings with the association between sports and cigarette smoking [26-28]. For 13

example, in a recent study, authors found that adolescents who had stopped participating in a 14

sport were at high risk of misusing substances, while lower competitive achievement in sports 15

was found to be associated with a higher likelihood of cigarette smoking [3 5 27]. Again, because 16

of the cross-sectional study design, the causality is not clear. Indeed, smoking could impair 17

physical capacity, thus leading to poor sport performance (a low result) and consequent 18

withdrawal from sport. On the other hand, it is also possible that adolescents first stopped 19

participating in sports and then started to smoke [27 28]. 20

This investigation aimed to prospectively explore the potential relationships between 21

scholastic- and sport-factors at the beginning of the 3rd year of high school, and smoking and 22

smoking initiation in the following two years (from 16 to 18 years of age on average) in 23

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adolescents from Bosnia and Herzegovina. Understanding the relationships studied here may help 1

inform all responsible parties about the specific risks and benefits related to the studied covariates 2

of smoking. Although there are other potential predictors of smoking, in this study we were 3

specifically focused on scholastic and sport factors, as both groups of factors are regularly and 4

independently monitored throughout the school system and a better understanding of the 5

associations could help develop cost-effective and targeted preventive interventions. 6

7

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METHODS 1

2

Procedures and participants 3

In this study, we aimed to prospectively investigate adolescents over their last two years 4

of high school. At baseline, the examinees were 16 years old on average and were in their 3rd year 5

of high school. A multi-stage cluster sampling method was used to select the participants. First, 6

we randomly selected one-third of the high schools in the territory of Zenica-Doboj Canton and 7

Tuzla Canton, mostly because of their socio-cultural environments as described below. 8

Bosnia and Herzegovina is a multi-ethnic country, home to three constitutive ethnicities 9

(Bosniaks, Serbs and Croats). Devastating wars that occurred in early 90s resulted in massive 10

emigrations of minority ethnic groups (specifically for different parts of the country), and overall 11

material devastation [29]. For the two Cantons studied, pre-war ethnic figures did not change 12

drastically. Therefore, these two Cantons should be observed as two typical regions in Bosnia and 13

Herzegovina. 14

School size varied by just 10-15%, and therefore the schools were not stratified by size. In 15

the second stage of sampling, half of all 3rd year classes were selected by random from the 16

selected schools, resulting in a sample size of 44 classes and a cohort of 1213 participants. After 17

obtaining the necessary ethics approvals (see later text), study personnel explained the full 18

procedure and study aims to potential participants and at least one parent/guardian in a regular 19

school meeting. Consent was obtained from at least one parent, and none of the parents refused to 20

let their child participate in the study. 21

22

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Two surveys were conducted, one (baseline) at the beginning of the 3rd year of high 1

school (September 2013), and the second (follow-up) at the end of high school (late May - early 2

June 2015). Surveys were administered during school hours in groups of at least 15 examinees. 3

Examinees were assured that their participation was voluntary and that they could leave any of 4

the questions and/or the entire questionnaire blank. The study participants remained anonymous 5

(no personal data were collected), but the participants were asked to use self-selected confidential 6

codes for identification purposes in the repeated test. They were asked to use the last three digits 7

of their e-mail password as their code for identification (i.e., these codes were easy to remember 8

between testing waves while being simultaneously confidential). After completing the surveys, 9

each participant placed the questionnaire in an envelope and then in a closed box. The next day, 10

an investigator who was not present during the survey administration opened the boxes. The 11

study fulfilled all ethical guidelines and received the approval of the Ethical Boards from the 12

University of Mostar, Bosnia and Herzegovina, and the University of Split, Croatia. After 13

obtaining ethical approvals, the study was officially authorised by the Ministries of Education in 14

Zenica-Doboj Canton and Tuzla Canton, the two areas of Bosnia and Herzegovina where the 15

research was taking place. The study design and sampling is presented in Figure 1. 16

17

Figure 1 – about here 18

19

Of the 1213 eligible students, 1059 (87%) had complete data in both the baseline and the follow-20

up study. Of the latter, 872 who identified as Bosnians were included in the study (72% of the 21

total eligible). The analysis of attrition bias showed no significant differences in initial smoking 22

status between adolescents who dropped-out and those who remained in the study (Chi square: 23

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2.11, p > 0.05), but there were significantly more males than females who dropped out (Chi 1

square: 8.00, p < 0.01) (Supplementary Table). 2

3

4

Variables 5

6

To extend current knowledge and allow meaningful comparison with previous cross-sectional 7

reports from countries belonging to the former Yugoslavia, such as Bosnia and Herzegovina, the 8

variables were collected using the Questionnaire of Substance Use, which was previously 9

reported to be a reliable and valid measuring tool in similar samples of participants [6 7 27]. In 10

this study, we collected data on age (in years), gender, self-reported socio-economic status 11

(“Below average” – “Average” - “Above average”), ethnicity (Bosniak, Serbian, Croatian, other), 12

sport factors, scholastic factors and consumption of cigarettes. 13

Sports factors consisted of questions about the subjects’ (i) involvement in sports (answers 14

included: never been involved, quit, currently involved); (ii) highest competitive achievement in 15

sports (never competed/did not participate in sports, local ranked competitions, national and 16

international ranked competitions); and (iii) time of involvement in sports (never involved, less 17

than a year, 2-5 years, 5+ years). Scholastic variables represented participants’ academic 18

achievement over the last semester (end of the 2nd year of high school): (i) grade point average; 19

(ii) behavioural grade (both on a five-point scale ranging from excellent to poor); and (iii) school 20

absences (“Almost never”, “Rarely”, “From time to time”, “Often”). Cigarette smoking was 21

assessed on a four-point scale with the following responses: “No, I don’t smoke”, “From time to 22

time, but not daily”, “Less than 10 cigarettes daily”, and “More than 10 cigarettes daily”. 23

Participants were later classified as non-smokers (those who responded “No, I don’t smoke)”or 24

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smokers (the remaining three answers). Information on smoking initiation during the course of 1

the study was obtained from each participant. Specifically, if the participant reported not smoking 2

at baseline and responded differently when tested at follow-up, the initiation of smoking was 3

indicated. 4

As a methodological remark we must note that variables such as peer-smoking and parental-5

smoking were not included in the study due to their known association with smoking in 6

adolescents [16 27]. Also, there were no differences in anti-smoking regulations among schools, 7

while anti-smoking regulations (i.e. smoking allowance in public, selling tobacco to minors) are 8

equal across the two studied communities. 9

10

Statistics 11

For all variables, descriptive statistics (counts and percentages or means and standard 12

deviations) were calculated. Depending on the characteristic of the variable, the differences 13

between smokers and non-smokers were established by the Mann-Whitney test (for ordinal 14

variables), or Chi square test (for categorical variables). Binary logistic regression was used to 15

estimate the Odds Ratio (OR) and the corresponding 95% Confidence Interval (95%CI) of the 16

following: (i) smoking status at baseline, (ii) smoking status at the end of the study, and (iii) 17

smoking initiation occurring during the course of the study by scholastic and sport covariates. 18

The logistic analyses were additionally adjusted for gender, age, and socioeconomic status. 19

20

21

22

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RESULTS 1

2

Table 1 presents the distribution of independent variables according to smoking status at 3

baseline and follow-up. Overall, 28% of adolescents were identified as smokers at the beginning 4

of their 3rd year of high school, and 36% were smokers at the end of high school 20 months later. 5

An increase in smoking prevalence over the observed period was particularly evident in females 6

(from 27 to 38%, and 30 to 34.5% for females and males, respectively). At baseline and at 7

follow-up, non-smokers achieved better grade point averages (MW: 6.03 and 6.36, p < 0.01) and 8

better behavioural grades (MW: 7.76 and 7.71, p < 0.01) and were less absent from school (MW: 9

5.60 and 9.30, p < 0.01, for baseline and follow-up, respectively) than smokers. Non-smokers 10

achieved higher sports results than smokers at baseline (MW: 2.34, p < 0.01). 11

12

Table 1 13

Baseline and follow-up characteristics with differences on a basis of smoking status (MW – Mann 14

Whitney Z values; Chi square test) 15

16

Baseline Follow-up


f (%) f (%) Z (p) F (%) F (%) Z (p)



Less than a year 132 (21.2) 56 (22.6) 104 (18.7) 84 (26.6)

2-5 years 164 (26.3) 72 (29) 136 (24.5) 100 (31.6)

>5 years 148 (23.7) 64 (25.8) 142 (25.5) 70 (22.2)


Never competed 344 (55.1) 114 (46) 308 (55.4) 150 (47.5)

Local rank 230 (36.9) 116 (46.8) 204 (36.7) 142 (44.9)



Excellent 262 (42) 66 (26.6) 242 (43.5) 86 (27.2)

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Very good 246 (39.4) 96 (38.7) 222 (39.9) 120 (38)

Average 106 (17) 76 (30.6) 86 (15.5) 96 (30.4)

Under average 6 (1) 4 (1.6) 2 (0.4) 8 (2.5)

Poor 4 (0.6) 6 (2.4) 4 (0.7) 6 (1.9)


Excellent 538 (86.2) 180 (72.6) 500 (89.9) 218 (69)

Very good 46 (7.4) 26 (10.5) 24 (4.3) 48 (15.2)

Average 30 (4.8) 28 (11.3) 24 (4.3) 34 (10.8)

Under average 6 (1) 8 (3.2) 6 (1.1) 8 (2.5)

Poor 4 (0.6) 6 (2.4) 2 (0.4) 8 (2.5)

School Absence 5.60 (0.01) 9.30 (0.01)

Almost never 244 (39.1) 52 (21) 246 (44.2) 50 (15.8)

Rarely 244 (39.1) 102 (41.1) 206 (37.1) 140 (44.3)

From time to time 108 (17.3) 78 (31.5) 90 (16.2) 96 (30.4)

Often 28 (4.5) 16 (6.5) 14 (2.5) 30 (9.5)


Gender 0.82 (0.36) 1.32 (0.25)

Male 138 (29.7) 326 (70.3) 160 (34.5) 304 (65.5)

Female 110 (27.0) 298 (73.0) 156 (38.2) 252 (61.8)



Quit 206 (33) 80 (32.3) 170 (30.6) 116 (36.7)


Socioeconomic status 5.66 (0.06) 2.58 (0.27)

Under average 10 (1.6) 4 (1.6) 10 (1.8) 4 (1.3)

Average 574 (92.0) 238 (95.7) 512 (92.1) 300 (95.0)

Below average 40 (6.4) 6 (2.4) 34 (6.1) 12 (3.8)

1

2

3

Increased odds of smoking were observed in adolescents with a lower grade point average 4

at baseline (Baseline: OR 1.6, 95%CI 1.4-1.9; Follow-up: 1.7, 1.4-1.9), poorer behavioural grades 5

(Baseline: 2.6, 2.0-3.5; Follow-up: 2.3, 1.7-2.9) and more frequent absences from school, with 6

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the highest chances of being smokers for those children who reported that they were often absent 1

from school (Baseline: 4.4, 2.0-9.4; Follow-up: 4.5, 2.1-9.4). School absence at baseline was a 2

significant predictor of smoking initiation over the course of the study as children who reported 3

that they were absent from time to time having the highest chances of starting smoking during the 4

course of study (2.6, 1.5-4.8). Involvement in sports (sport participation) was not associated with 5

smoking status at baseline, but those who reported quitting sports showed an increased risk of 6

smoking at the end of the study (1.4, 1.0-1.9) and a higher risk of smoking initiation during the 7

study (1.7, 1.1-2.9). Adolescents who were engaged in sports for less than 5 years showed a 8

higher prevalence of smoking at the end of the study (less than a year: 2.7, 1.6-3.8; 2-5 years: 2.4, 9

1.6-3.6), and an increased risk of smoking initiation during the course of the investigation (less 10

than a year: 2.7, 1.4-5.2; 2-5 years: 3.3, 1.6-6.2) than those who were never involved in sports. 11

Finally, compared with peers who were never involved in sports, those who reported involvement 12

in sports competitions but with lower competitive results were at a higher risk of the following: 13

(i) smoking at baseline (1.5, 1.1-2.0), (ii) smoking at the end of the study (1.5, 1.1-2.0), and (iii) 14

smoking initiation (1.6, 1.1-2.5) (Table 2). 15

16

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Table 2 1

The ORs for smoking at baseline, smoking at follow up, and smoking initiation over the course of the 2

study 3

4

Bivariate analyses Model 1 **

Baseline characteristics

Smoking at baseline


Smoking initiation

Smoking at baseline


Smoking initiation

Grade Point Average (grade) *

1.6 (1.4-1.9) 1.6 (1.4-1.9) 1.1 (0.9-1.4) 1.6 (1.4-1.9) 1.7 (1.4-1.9) 1.2 (0.9-1.4)

Behavioral Grade (grade) * 2.5 (1.9-3.3) 2.1 (1.6-2.7) 0.9 (0.6-1.3) 2.6 (2.0-3.5) 2.3 (1.7-2.9) 0.9 (0.6-1.3)

School Absence

Almost never REF REF REF REF REF REF

Rarely 2.0 (1.4-2.8) 2.3 (1.7-3.2) 1.7 (1.0-2.8) 2.0 (1.4-2.7) 2.3 (1.7-3.2) 1.7 (1.1-2.8)

From time to time 2.7 (1.7-4.2) 3.5 (2.3-5.4) 2.5 (1.4-4.6) 2.7 (1.7-4.2) 3.6 (2.3-5.5) 2.6 (1.5-4.8)

Often 4.0 (1.9-8.6) 4.1 (2.0-8.6) 1.7 (0.5-5.0) 4.5 (2.1-95) 4.5 (2.1-9.4) 1.8 (0.6-5.5)

Sport participation


Quit 1.0 (0.7-1.4) 1.4 (1.0-1.9) 1.7 (1.1-2.7) 1.0 (0.7-1.4) 1.4 (1.0-1.9) 1.7 (1.1-2.9)


Experience in sport


Less than a year 1.3 (0.9-2.1) 2.3 (1.5-3.4) 2.6 (1.4-4.9) 1.4 (0.9-2.1) 2.7 (1.6-3.8) 2.7 (1.4-5.2)

2-5 years 1.4 (0.9-2.1) 2.1 (1.4-3.0) 2.8 (1.5-5.2) 1.4 (0.9-2.1) 2.4 (1.6-3.6) 3.3 (1.7-6.2)

>5 years 1.4 (0.9-2.1) 1.4 (0.9-2.0) 1.1 (0.6-2.3) 1.4 (0.8-2.2) 1.5 (0.9-2.5) 1.4 (0.7-2.9)



Local rank 1.5 (1.1-2.1) 1.4 (1.1-1.9) 1.5 (1.0-2.2) 1.5 (1.1-2.0) 1.5 (1.1-2.0) 1.6 (1.1-2.5)


*The higher value presents poorer scholastic achievement; ** Adjusted for age, gender and socioeconomic status 5

6

7

8

9

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DISCUSSION 1

This study aimed to prospectively investigate the potential relationships between 2

scholastic and sport factors with smoking in older adolescents. The analyses revealed several 3

important findings that should be highlighted. First, baseline scholastic factors were 4

systematically associated with smoking, with poorer scholastic achievement in adolescents who 5

reported smoking at baseline and follow-up. The absence from school at baseline was a predictor 6

of smoking initiation in the following period. Quitting sports, poor competitive achievement, and 7

less than 5 years of participation in sports were shown to be specific risks for smoking and 8

smoking initiation. Prior to discussing these findings, we will provide a brief overview of the 9

established prevalence and trends in smoking. Smoking prevalence significantly increased from 10

28% to 36% during the course of the study. Consequently, approximately 77% of adolescents 11

who reported smoking at the end of high school (i.e., 28/36) initiated smoking when they were 12

younger than 16 years. Although participants self-reported their smoking status, which should be 13

observed as a limitation of the study, the reported prevalence of smoking in this study is similar 14

to previous reports of a 30-35% prevalence of adolescent smokers in Bosnia and Herzegovina 15

and the wider territory of the former Yugoslavia [3 27 30]. Consequently, the self-reported data 16

on smoking obtained here are plausible. This study is unique, as it is one of the first to 17

prospectively investigate the factors associated with smoking in adolescents from south-eastern 18

Europe. Therefore, the data on the relationships between scholastic- and sport-factors and 19

smoking initiation are particularly interesting. 20

21

The associations between scholastic factors and smoking at study baseline (i.e., when 22

subjects were 16 years old) and the associations between scholastic factors and scholastic 23

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achievement at follow up (i.e., end of high school, 18 years of age) are similar. In both waves, 1

higher odds of smoking are observed in adolescents with lower scholastic achievement. Our 2

findings are therefore in accordance with the results of previous cross-sectional studies performed 3

with adolescents of a similar age, which repeatedly reported lower educational achievement 4

among children who smoke [7 18 27]. Although there is a general consensus on the negative 5

associations between smoking and performance in school, the mechanisms that lead to these 6

associations are still controversial. Some authors highlight the negative effects of smoking on 7

cognitive capacities, and consequently poorer learning capabilities, as a result of cigarette 8

smoking [18]. This explanation is strongly supported by the evident physiological mechanisms 9

(i.e., alterations in brain structure as a result of smoking) [11-13]. The main criticism of this 10

explanation arises from the relatively short period of smoking in adolescents. Therefore, 11

significant deterioration in cognitive capacities and the resulting low academic achievement in 12

adolescents is less probable. As a result, it is suggested that lower academic achievement in 13

adolescent smokers may actually be the cause, and not the effect, of smoking. Indeed, children 14

who fail at school are frequently in “out of school situations” and therefore in unique socio-15

cultural environments in which they are more likely to initiate smoking [3 6]. This theory thus 16

focuses on social influence. In this study, we showed a negative relationship between “school 17

absence” at baseline (i.e., 16 years of age) and smoking initiation in the following 2-year period. 18

Therefore, our results actually support the theory of social influence as a probable explanation of 19

the cause-effect relationship between academic failure and smoking in this age group. Briefly, the 20

general associations between scholastic variables and smoking are clear, demonstrating that 21

children who smoke perform poorly in school. However, it must be stressed that more frequent 22

absences from school at the beginning of the 3rd year of high school is a clear predictor of 23

smoking initiation in the following two years. Of course, one can argue that scholastic 24

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achievement was not entirely objectively evaluated because the data were self-reported. Although 1

this should be considered an important limitation of the study, we believe that the strict 2

anonymity of the testing decreased the possibility that the participants responded dishonestly. 3

4

Our study found a high risk for smoking initiation for those adolescents (i) who quit sport, 5

(ii) who reported low competitive success, and (iii) who had a relatively short period of 6

involvement in sport. Generally, this is in accordance with very recent studies which have noted a 7

higher prevalence of smoking in adolescents who quit sports and those who achieved poorer 8

competitive results [7 28]. Because of the cross-sectional nature of studies the cause-and-effect 9

relationship between quitting sports and smoking had not been clearly identified. There is a 10

possibility that smoking impairs physical capacities, and this could therefore result in poor sport 11

performance and a lack of success, which would consequently result in withdrawal from sports 12

[31]. However, it is also possible that children first stop practicing a sport and then start to 13

smoke, as a result of the (negative) influence of their new socio-cultural environment in which 14

smoking is more prevalent [5 7]. The results of our study support the latter explanation. Namely, 15

all three sport factors observed in this study were found to be significant predictors of smoking 16

initiation in older adolescents. First, those who reported at study-baseline that they had once 17

practiced sports and then quit were at a higher risk of starting to smoke during the course of the 18

study (i.e. between 16 and 18 years of age), than their peers who were never involved in sports. 19

Additionally, a higher risk of initiating smoking was evident in adolescents who were involved in 20

sports for less than 5 years and in those who practiced sports but did not achieve significant 21

competitive results. Most probably, the association of all three sport factors ( (i) quitting sport, 22

(ii) short time of involvement and (iii) low competitive result), with smoking initiation is 23

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generated by equal mechanism. Briefly, it is well known that better sport results are actually a 1

direct or indirect consequence of a longer involvement in sport [32 33]. At the same time, a lack 2

of good sports results (i.e. poor competitive achievement in sport) is one of the most important 3

factors which results in withdrawing from a sport in adolescence [34]. The 16-to18-year old 4

adolescents who do not achieve competitive results regularly stop participating in sports at this 5

particular age, mostly because they have become personally aware of their inferiority (i.e. their 6

lack of ability and/or skills)[34]. Meanwhile, it is known that individuals identify with particular 7

groups of peers, and being a member of a specific social network or group influences individuals’ 8

values as well as their attitudes and the norms to which they are exposed [35]. Therefore, it is 9

likely that adolescents who quit sports started smoking as a way of adopting the norms of the 10

“non-sporting” society and of finding a place in a new social-milieu. This study lacks qualitative 11

data on the reasons for quitting sports and an objective evaluation of lower competitive 12

achievement in sports. This is a clear limitation of the investigation, as we are not able to 13

accurately explain the background of the relationship within the sport factors observed herein. 14

15

This study evidenced specific associations between scholastic and sport factors with 16

smoking initiation in older adolescents, but we may not ignore the potential confounding effects 17

of some covariates that were not observed in this study, such as those concerned with the home 18

environment (i.e. familiar factors). For example, it could be expected that both quitting sports and 19

poor academic performance (i.e. significant predictors of smoking initiation in our participants), 20

might be a result of some family-related issues such as lack of parental monitoring and high 21

parental conflict. Consequently, the lack of information on these issues could be highlighted as a 22

study limitation. However, we were of the opinion that eventual knowledge of these confounding 23

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effects, although scientifically interesting, may not add much to our understanding of how to 1

intervene. This is because children who have problems in their home environment, such as being 2

in conflict with their parents and/or experiencing a lack of parental control could not be tracked 3

(i.e. information on that manner was not able to be obtained). Meanwhile, all variables included 4

in this study were easily obtainable throughout the education system, which allows identification 5

of those children who are at specific risk for smoking initiation in late adolescence. 6

7

Although some study limitations have been presented (e.g. self-reported data on scholastic 8

factors, the lack of qualitative data on reasons for quitting sports), the most important limitation 9

comes from the fact that this study observed adolescents from 16 years of age, when many 10

students had already started to smoke. Therefore the generalizability of the findings is limited to 11

older adolescents. Meanwhile, in order to objectively overview the findings, some specific 12

contextual information on the socio-cultural environments is necessary. Bosnia and Herzegovina 13

is a country which is traditionally oriented toward tobacco consumption since the country was 14

part of the former Ottoman Empire, and tobacco farming has been an important part of the 15

economy in some cantons for more than 300 years (e.g. particularly in the Herzegovina-Neretva 16

Canton, which is the Mediterranean part of the country) [6]. As a result, smoking is socially 17

accepted in public, and cigarettes are relatively cheap. Next, although smoking is prohibited in 18

schools, such regulations are really only imposed for closed high-school buildings. It is probably 19

even more important that smoking is not prohibited in places of social gatherings (e.g. pubs, cafe 20

bars, and disco clubs). Finally, although is formally allowed only for those over 18 years, there is 21

no ID control for purchasing cigarettes, while cigarette vending machines are also common. 22

Therefore, although the generalizability of the findings is somewhat limited (mostly for Bosnian 23

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and Herzegovinian adolescents 16-to-18 years of age), the authors are of the opinion that the 1

generalizability is to some extent possible for surrounding countries as well. This is because in 2

many of the countries of the former Yugoslavia, smoking is a socially accepted behaviour, there 3

are no strict regulations against smoking in public, and tobacco products are relatively cheap [28 4

30]. 5

6

The following conclusions can be made. With 28% of adolescents who started smoking 7

before they were 16 and an additional 8% who started smoking between 16 and 18 years of age, 8

the prevalence of smoking is high. As expected from previous investigations, the smoking 9

prevalence was higher in adolescents who achieved poor grades in school. This study expands on 10

previous knowledge by demonstrating that school absences at the age of 16 are a predictor of 11

smoking initiation over the next two years (i.e., by the end of high school). Additionally, 12

adolescents who reported quitting sports, those who were involved in sports for a relatively short 13

time (i.e., up to 5 years), and those who achieved low competitive success by the age of 16 were 14

found to be at risk of starting smoking by the end of high school (i.e., 18 years of age). Therefore, 15

to develop accurate and problem-oriented public health policies against smoking in older 16

adolescents, public health authorities should co-operate with school and sport organisations to 17

target the most vulnerable groups of adolescents established in this study. Although it was not 18

among the primary aims of the study, this was the first investigation which indirectly showed that 19

the majority of adolescents from Bosnia and Herzegovina started smoking cigarettes before 16 20

years of age. Therefore, further investigations should evaluate the predictors of smoking in 21

younger ages. 22

23

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Acknowledgements 1

Special thanks go to Cantonal Ministries of Education who supported and approved the 2

investigation. The authors are particularly grateful to all children who voluntarily participated in 3

the study. 4

5

Contributors 6

DS designed the study, performed the statistical analysis and discussed the data; NS, AT 7

and IJ collected the data, overviewed previous research and drafted the manuscript; LO collected 8

the data and discussed the public health issues of the investigation; HP overviewed the previous 9

research and discussed the sport factors in relation to smoking; NZ discussed the data and 10

participated in statistical analyses. All authors have read and approved the final version. 11

12

Ethics approval 13

The Ethical Boards of University of Split, Faculty of Kinesiology, Split, Croatia and 14

University of Mostar, School of Medicine, Mostar, Bosnia and Herzegovina approved the 15

Investigation. Additionally, the study was approved by Cantonal Ministries of Education. 16

17

Funding 18

This study and publication were partially financed by the University of Split, Faculty of 19

Kinesiology, Split, Croatia 20

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1

Conflict of interest 2

The authors report no conflicts of interest. 3

4

5

6

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22

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Data sharing statement: 1

Data files are freely available here: https://www.dropbox.com/s/n7opixov3hrglj8/data.xlsx?dl=0 2

3

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Figure legend: 1

2

Figure 1 3

Sampling procedure, participants and non-responders (i.e. absent from school on testing day, 4

inconsistency in identification codes) 5

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Figure 1 Sampling procedure, participants and non-responders (i.e. absent from school on testing day, inconsistency

in identification codes)

76x69mm (300 x 300 DPI)

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Supplementary Table




Females 156 14

Nonsmokers

Males 252 53 Females 304 35

Subtotal smokers 316 37

2.11 (0.15) Subtotal nonsmokers 556 88

Subtotal males 412 76

8.00 (0.01) Subtotal females 460 49

Total 872 125

LEGEND: Note that group of non-responders does not include participants who were not present at the

baseline testing (49 participants) but includes those who used inconsistent identification codes at testing

waves (20 participants)

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Introduction



para

Methods



collection P9






Cohort study: P9










and why NA






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Results

















Discussion





(beginning)




Other information




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Journal: BMJ Open

Manuscript ID bmjopen-2016-014066.R2


Date Submitted by the Author: 30-Jan-2017




Epidemiology

Secondary Subject Heading: Public health, Addiction



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1

Sport and scholastic factors in relation to smoking and smoking initiation in older 1

adolescents: a prospective cohort study in Bosnia and Herzegovina 2

3

Damir Sekulic 1,2



5, Ljerka Ostojic

1,6,7, 4


1 5

6

1 Faculty of Kinesiology; University of Split, Teslina 6, Split – 21000, Croatia 7

2 University Department of Health Care Studies, Split- 21000, Croatia 8

3 University of Zenica, Fakultetska 3, Zenica – 23000, Bosnia and Herzegovina 9

4 High School Hasan Kikic, Sarajevska 1, Gradacac-76250, Bosnia and Herzegovina 10

5 Faculty of Physical Education and Sport, University of Tuzla, 2nd October 1, Tuzla-75000, 11

Bosnia and Herzegovina 12

6 University of Mostar, Matice Hrvatske bb, Mostar – 63000, Bosnia and Herzegovina 13

7 Academy of Medical Sciences of Bosnia and Herzegovina, Sarajevo, Bosnia and Herzegovina 14

8 Mid Sweden University, Department for Health Sciences, Östersund - 83125, Sweden 15

9 Mid Sweden University, Swedish Winter Sports Research Centre, Östersund - 83125, Sweden 16

17

18

Corresponding author: Natasa Zenic; Faculty of Kinesiology; University of Split, Teslina 6, Split 19

– 21000, Croatia; [email protected] 20

Key words: cigarettes, educational achievement, sports, puberty, association 21

Word Count: 4582 22

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ABSTRACT 1

2

Objective 3

Sport- and scholastic-factors are known to be associated with cigarette-smoking in adolescence, 4

but little is known about the causality of this association. The aim of this study was to 5

prospectively explore the relationships of different sport- and scholastic-factors with smoking-6

prevalence -initiation in older adolescents from Bosnia and Herzegovina. 7

8

Methods 9

In this two-year prospective cohort study, there were 872 adolescent participants (16 years at 10

baseline; 46% females). The study consisted of baseline tests at the beginning of the 3rd year 11

(September 2013) and follow-up at the end of the 4th year of high school (late May – early June 12

2015). The independent variables were scholastic- and sport-related factors. The dependent 13

variables were (i) smoking at baseline, (ii) smoking at follow-up, and (iii) smoking-initiation over 14

the course of the study. Logistic regressions controlled for age, gender, and socio-economic 15

status were applied to define the relationships between independent and dependent variables. 16

17

Results 18

School absence at the baseline study was a significant predictor of smoking initiation during the 19

course of the study (OR: 1.4, 95% CI: 1.1 – 1.8). Those who reported quitting sports at baseline 20

showed an increased risk of smoking at the end of the study (OR: 1.4, 95%CI: 1.1 – 2.0) and of 21

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smoking initiation (OR: 1.8, 95%CI: 1.3 – 2.0). Adolescents who reported lower competitive 1

achievements in sport were at a higher risk of (i) smoking at baseline (OR: 1.5, 95%CI: 1.1 – 2

2.1), (ii) smoking at follow-up (OR: 1.5, 95%CI: 1.1 – 2.1), and (iii) smoking initiation (OR: 1.6, 3

95%CI: 1.1 – 2.6). 4

5

Conclusions 6

In developing accurate anti-smoking public health policies for older adolescents, the most 7

vulnerable groups should be targeted. The results showed that most participants initiated smoking 8

before 16 years of age. Therefore, further investigations should evaluate the predictors of 9

smoking in younger ages. 10

11

12

13

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1

Strengths and limitations of the study 2

• The data was self-reported, but as the study was strictly anonymous and conducted in a 3

country where smoking is socially accepted, the possibility that participants did not respond 4

honestly is lower. 5

• The study lacks data on peer-smoking and parental-smoking which both can be associated 6

both with sport-participation and educational-achievement. 7

• Studied sport factors consisted of questions on formal sport-participation, while some other 8

important determinants of involvement in sport (non-formal physical exercising in fitness 9

centres, self-exercising, etc.) were not evaluated. 10

• The majority of participants started smoking before 16 years of age, and therefore the 11

generalizability of the results regarding the predictors of smoking initiation is limited solely 12

to adolescents who initiated smoking in late adolescence (16 to18 years of age). 13

• This is one of the first studies to prospectively investigate the predictors of smoking in south-14

eastern Europe. 15

• The high retention rate (87% of the adolescents studied at baseline and follow-up) and low 16

rate of missing data are important strengths of the study. 17

18

19

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INTRODUCTION 1

Cigarette smoking is an important modifiable determinant of health, and preventing 2

smoking initiation among adolescents eliminates the numerous health risks they would face as 3

adult smokers 1 2. With more than 20% of adolescents who smoke cigarettes daily, Bosnia and 4

Herzegovina is among the five European countries with the highest prevalence of smoking 5

among adolescents, together with Austria, Croatia, Belgium and Hungary ( all about 20% daily 6

smokers) 3 4. This high prevalence is mostly explained by the low prices of tobacco products, 7

social acceptance of smoking in public, and the lack of effective public health campaigns against 8

smoking 5. Consequently, in the last couple of years, several cross-sectional investigations have 9

explored the problem and found different socio-demographic, economic, community-specific, 10

sport-related, and scholastic factors to be associated with adolescent smoking in the country 6 7. 11

12

Scholastic achievement (educational achievement) is one of the factors known to be 13

associated with smoking in adolescence, with poor performance in school regularly observed in 14

adolescents who smoke 5 8-10. However, the causality remains unknown. One possible explanation 15

implies that smoking is the cause of poor performance in school because of the physiological 16

mechanisms and the negative effects of smoking on cognitive function and learning capacities 11-17

13. Meanwhile, some authors are of the opinion that smoking should be observed as an effect, and 18

not the cause, of educational failure 7 14. For example, children who fail academically are 19

frequently in out-of-school situations where they are directly and/or indirectly exposed to 20

individuals who smoke and are therefore at higher risk of smoking themselves 5 6. Indeed, social 21

influences are known to be important with respect to a wide range of health behaviours, including 22

smoking, and such peer influence on smoking is also logical 15 16. However, it is also possible that 23

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other factors, such as parental conflict, and/or poor familiar control, result in both educational 1

failure and smoking. Additionally, “the theory of problem behaviour” (i.e. that the problem 2

behaviours such as failure in school and smoking often appear in tandem because some people 3

have a psychosocial tendency for unconventionality) has been used to explain the association 4

between educational failure and smoking in adolescence 17. Regardless of the background, the 5

cross-sectional design of the studies did not allow for the interpretation of the cause-effect 6

relationship between educational achievement in high school and smoking status 5 7 18. 7

8

Participation in sport is often considered as a potentially effective way of reducing the 9

tendency of adolescents to smoke cigarettes 19-22. Indeed, when comparing groups of adolescent 10

athletes vs. non-athletes, there is a lower prevalence of smoking in those involved in sports 23-25. 11

However, when sport participation was analysed more specifically there were some conflicting 12

findings with the association between sports and cigarette smoking 26-28. For example, in a recent 13

study, authors found that adolescents who had stopped participating in a sport were at high risk of 14

misusing substances, while lower competitive achievement in sports was found to be associated 15

with a higher likelihood of cigarette smoking 3 5 27. Again, because of the cross-sectional study 16

design, the causality is not clear. Indeed, smoking could impair physical capacity, thus leading to 17

poor sport performance (a low result) and consequent withdrawal from sport. On the other hand, 18

it is also possible that adolescents first stopped participating in sports and then started to smoke 27 19

28. 20

This investigation aimed to prospectively explore the potential relationships between 21

scholastic- and sport-factors at the beginning of the 3rd year of high school, and smoking and 22

smoking initiation in the following two years (from 16 to 18 years of age on average) in 23

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adolescents from Bosnia and Herzegovina. Understanding the relationships studied here may help 1

inform all responsible parties about the specific risks and benefits related to the studied covariates 2

of smoking. Although there are other potential predictors of smoking, in this study we were 3

specifically focused on scholastic and sport factors, as both groups of factors are regularly and 4

independently monitored throughout the school system and a better understanding of the 5

associations could help develop cost-effective and targeted preventive interventions. 6

7

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METHODS 1

2

Procedures and participants 3

In this study, we aimed to prospectively investigate adolescents over their last two years 4

of high school. At baseline, the examinees were 16 years old on average and were in their 3rd year 5

of high school. A multi-stage cluster sampling method was used to select the participants. First, 6

we randomly selected one-third of the high schools in the territory of Zenica-Doboj Canton and 7

Tuzla Canton, mostly because of their socio-cultural environments as described below. 8

Bosnia and Herzegovina is a multi-ethnic country, home to three constitutive ethnicities 9

(Bosniaks, Serbs and Croats). Devastating wars that occurred in early 90s resulted in massive 10

emigrations of minority ethnic groups (specifically for different parts of the country), and overall 11

material devastation 29. For the two Cantons studied, pre-war ethnic figures did not change 12

drastically. Therefore, these two Cantons should be observed as two typical regions in Bosnia and 13

Herzegovina. 14

School size varied by just 10-15%, and therefore the schools were not stratified by size. In 15

the second stage of sampling, half of all 3rd year classes were selected by random from the 16

selected schools, resulting in a sample size of 44 classes and a cohort of 1213 participants. After 17

obtaining the necessary ethics approvals (see later text), study personnel explained the full 18

procedure and study aims to potential participants and at least one parent/guardian in a regular 19

school meeting. Consent was obtained from at least one parent, and none of the parents refused to 20

let their child participate in the study. 21

22

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Two surveys were conducted, one (baseline) at the beginning of the 3rd year of high 1

school (September 2013), and the second (follow-up) at the end of high school (late May - early 2

June 2015). Surveys were administered during school hours in groups of at least 15 examinees. 3

Examinees were assured that their participation was voluntary and that they could leave any of 4

the questions and/or the entire questionnaire blank. The study participants remained anonymous 5

(no personal data were collected), but the participants were asked to use self-selected confidential 6

codes for identification purposes in the repeated test. They were asked to use the last three digits 7

of their e-mail password as their code for identification (i.e., these codes were easy to remember 8

between testing waves while being simultaneously confidential). After completing the surveys, 9

each participant placed the questionnaire in an envelope and then in a closed box. The next day, 10

an investigator who was not present during the survey administration opened the boxes. The 11

study fulfilled all ethical guidelines and received the approval of the Ethical Boards from the 12

University of Mostar, Bosnia and Herzegovina, and the University of Split, Croatia. After 13

obtaining ethical approvals, the study was officially authorised by the Ministries of Education in 14

Zenica-Doboj Canton and Tuzla Canton, the two areas of Bosnia and Herzegovina where the 15

research was taking place. The study design and sampling is presented in Figure 1. 16

17

Figure 1 – about here 18

19

Of the 1213 eligible students, 1059 (87%) had complete data in both the baseline and the follow-20

up study. Of the latter, 872 who identified as Bosnians were included in the study (72% of the 21

total eligible). The analysis of attrition bias showed no significant differences in initial smoking 22

status between adolescents who dropped-out and those who remained in the study (Chi square: 23

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2.11, p > 0.05), but there were significantly more males than females who dropped out (Chi 1

square: 8.00, p < 0.01) (Supplementary Table). 2

3

4

Variables 5

6

To extend current knowledge and allow meaningful comparison with previous cross-sectional 7

reports from countries belonging to the former Yugoslavia, such as Bosnia and Herzegovina, the 8

variables were collected using the Questionnaire of Substance Use, which was previously 9

reported to be a reliable and valid measuring tool in similar samples of participants 6 7 27. In this 10

study, we collected data on age (in years), gender, self-reported socio-economic status (“Below 11

average” – “Average” - “Above average”), ethnicity (Bosniak, Serbian, Croatian, other), sport 12

factors, scholastic factors and consumption of cigarettes. 13

Sports factors consisted of questions about the subjects’ (i) involvement in sports (answers 14

included: never been involved, quit, currently involved); (ii) highest competitive achievement in 15

sports (never competed/did not participate in sports, local ranked competitions, national and 16

international ranked competitions); and (iii) time of involvement in sports (never involved, less 17

than a year, 2-5 years, 5+ years). Scholastic variables represented participants’ academic 18

achievement over the last semester (end of the 2nd year of high school): (i) grade point average; 19

(ii) behavioural grade (both on a five-point scale ranging from excellent to poor); and (iii) school 20

absences (“Almost never”, “Rarely”, “From time to time”, “Often”). Cigarette smoking was 21

assessed on a four-point scale with the following responses: “No, I don’t smoke”, “From time to 22

time, but not daily”, “Less than 10 cigarettes daily”, and “More than 10 cigarettes daily”. 23

Participants were later classified as non-smokers (those who responded “No, I don’t smoke)”or 24

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smokers (the remaining three answers). Information on smoking initiation during the course of 1

the study was obtained from each participant. Specifically, if the participant reported not smoking 2

at baseline and responded differently when tested at follow-up, the initiation of smoking was 3

indicated. 4

5

Statistics 6

For all variables, descriptive statistics (counts and percentages or means and standard 7

deviations) were calculated. Depending on the characteristic of the variable, the differences 8

between smokers and non-smokers were established by the Mann-Whitney test (for ordinal 9

variables), or Chi square test (for categorical variables). Binary logistic regression was used to 10

estimate the Odds Ratio (OR) and the corresponding 95% Confidence Interval (95%CI) of the 11

following: (i) smoking status at baseline, (ii) smoking status at the end of the study, and (iii) 12

smoking initiation occurring during the course of the study by scholastic and sport covariates. 13

The logistic analyses were additionally adjusted for gender, age, and socioeconomic status. 14

15

16

17

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RESULTS 1

2

Table 1 presents the distribution of independent variables according to smoking status at 3

baseline and follow-up. Overall, 28% of adolescents were identified as smokers at the beginning 4

of their 3rd year of high school, and 36% were smokers at the end of high school 20 months later. 5

An increase in smoking prevalence over the observed period was particularly evident in females 6

(from 27 to 38%, and 30 to 34.5% for females and males, respectively). At baseline and at 7

follow-up, non-smokers achieved better grade point averages (MW: 6.03 and 6.36, p < 0.01) and 8

better behavioural grades (MW: 7.76 and 7.71, p < 0.01) and were less absent from school (MW: 9

5.60 and 9.30, p < 0.01, for baseline and follow-up, respectively) than smokers. Non-smokers 10

achieved higher sports results than smokers at baseline (MW: 2.34, p < 0.01). 11

12

Table 1 13

Baseline and follow-up characteristics with differences on a basis of smoking status (MW – Mann 14

Whitney Z values; Chi square test) 15

16

Baseline Follow-up


f (%) f (%) Z (p) F (%) F (%) Z (p)



Less than a year 132 (21.2) 56 (22.6) 104 (18.7) 84 (26.6)

2-5 years 164 (26.3) 72 (29) 136 (24.5) 100 (31.6)

>5 years 148 (23.7) 64 (25.8) 142 (25.5) 70 (22.2)


Never competed 344 (55.1) 114 (46) 308 (55.4) 150 (47.5)

Local rank 230 (36.9) 116 (46.8) 204 (36.7) 142 (44.9)



Excellent 262 (42) 66 (26.6) 242 (43.5) 86 (27.2)

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Very good 246 (39.4) 96 (38.7) 222 (39.9) 120 (38)

Average 106 (17) 76 (30.6) 86 (15.5) 96 (30.4)

Under average 6 (1) 4 (1.6) 2 (0.4) 8 (2.5)

Poor 4 (0.6) 6 (2.4) 4 (0.7) 6 (1.9)


Excellent 538 (86.2) 180 (72.6) 500 (89.9) 218 (69)

Very good 46 (7.4) 26 (10.5) 24 (4.3) 48 (15.2)

Average 30 (4.8) 28 (11.3) 24 (4.3) 34 (10.8)

Under average 6 (1) 8 (3.2) 6 (1.1) 8 (2.5)

Poor 4 (0.6) 6 (2.4) 2 (0.4) 8 (2.5)

School Absence 5.60 (0.01) 9.30 (0.01)

Almost never 244 (39.1) 52 (21) 246 (44.2) 50 (15.8)

Rarely 244 (39.1) 102 (41.1) 206 (37.1) 140 (44.3)

From time to time 108 (17.3) 78 (31.5) 90 (16.2) 96 (30.4)

Often 28 (4.5) 16 (6.5) 14 (2.5) 30 (9.5)


Gender 0.82 (0.36) 1.32 (0.25)

Male 138 (29.7) 326 (70.3) 160 (34.5) 304 (65.5)

Female 110 (27.0) 298 (73.0) 156 (38.2) 252 (61.8)



Quit 206 (33) 80 (32.3) 170 (30.6) 116 (36.7)


Socioeconomic status 5.66 (0.06) 2.58 (0.27)

Under average 10 (1.6) 4 (1.6) 10 (1.8) 4 (1.3)

Average 574 (92.0) 238 (95.7) 512 (92.1) 300 (95.0)

Below average 40 (6.4) 6 (2.4) 34 (6.1) 12 (3.8)

1

2

3

Increased odds of smoking were observed in adolescents with a lower grade point average 4

at baseline (Baseline: OR 1.6, 95%CI 1.4-1.9; Follow-up: 1.7, 1.4-1.9), poorer behavioural grades 5

(Baseline: 2.6, 2.0-3.5; Follow-up: 2.3, 1.7-2.9) and more frequent absences from school, with 6

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the highest chances of being smokers for those children who reported that they were often absent 1

from school (Baseline: 4.4, 2.0-9.4; Follow-up: 4.5, 2.1-9.4). School absence at baseline was a 2

significant predictor of smoking initiation over the course of the study as children who reported 3

that they were absent from time to time having the highest chances of starting smoking during the 4

course of study (2.6, 1.5-4.8). Involvement in sports (sport participation) was not associated with 5

smoking status at baseline, but those who reported quitting sports showed an increased risk of 6

smoking at the end of the study (1.4, 1.0-1.9) and a higher risk of smoking initiation during the 7

study (1.7, 1.1-2.9). Adolescents who were engaged in sports for less than 5 years showed a 8

higher prevalence of smoking at the end of the study (less than a year: 2.7, 1.6-3.8; 2-5 years: 2.4, 9

1.6-3.6), and an increased risk of smoking initiation during the course of the investigation (less 10

than a year: 2.7, 1.4-5.2; 2-5 years: 3.3, 1.6-6.2) than those who were never involved in sports. 11

Finally, compared with peers who were never involved in sports, those who reported involvement 12

in sports competitions but with lower competitive results were at a higher risk of the following: 13

(i) smoking at baseline (1.5, 1.1-2.0), (ii) smoking at the end of the study (1.5, 1.1-2.0), and (iii) 14

smoking initiation (1.6, 1.1-2.5) (Table 2). 15

16

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Table 2 1

The ORs for smoking at baseline, smoking at follow up, and smoking initiation over the course of the 2

study 3

4

Bivariate analyses Model 1 **

Baseline characteristics

Smoking at baseline


Smoking initiation

Smoking at baseline


Smoking initiation

Grade Point Average (grade) *

1.6 (1.4-1.9) 1.6 (1.4-1.9) 1.1 (0.9-1.4) 1.6 (1.4-1.9) 1.7 (1.4-1.9) 1.2 (0.9-1.4)

Behavioral Grade (grade) * 2.5 (1.9-3.3) 2.1 (1.6-2.7) 0.9 (0.6-1.3) 2.6 (2.0-3.5) 2.3 (1.7-2.9) 0.9 (0.6-1.3)

School Absence

Almost never REF REF REF REF REF REF

Rarely 2.0 (1.4-2.8) 2.3 (1.7-3.2) 1.7 (1.0-2.8) 2.0 (1.4-2.7) 2.3 (1.7-3.2) 1.7 (1.1-2.8)

From time to time 2.7 (1.7-4.2) 3.5 (2.3-5.4) 2.5 (1.4-4.6) 2.7 (1.7-4.2) 3.6 (2.3-5.5) 2.6 (1.5-4.8)

Often 4.0 (1.9-8.6) 4.1 (2.0-8.6) 1.7 (0.5-5.0) 4.5 (2.1-95) 4.5 (2.1-9.4) 1.8 (0.6-5.5)

Sport participation



Quit 1.0 (0.7-1.4) 1.4 (1.0-1.9) 1.7 (1.1-2.7) 1.0 (0.7-1.4) 1.4 (1.0-1.9) 1.7 (1.1-2.9)

Experience in sport


Less than a year 1.3 (0.9-2.1) 2.3 (1.5-3.4) 2.6 (1.4-4.9) 1.4 (0.9-2.1) 2.7 (1.6-3.8) 2.7 (1.4-5.2)

2-5 years 1.4 (0.9-2.1) 2.1 (1.4-3.0) 2.8 (1.5-5.2) 1.4 (0.9-2.1) 2.4 (1.6-3.6) 3.3 (1.7-6.2)

>5 years 1.4 (0.9-2.1) 1.4 (0.9-2.0) 1.1 (0.6-2.3) 1.4 (0.8-2.2) 1.5 (0.9-2.5) 1.4 (0.7-2.9)



Local rank 1.5 (1.1-2.1) 1.4 (1.1-1.9) 1.5 (1.0-2.2) 1.5 (1.1-2.0) 1.5 (1.1-2.0) 1.6 (1.1-2.5)


*The higher value presents poorer scholastic achievement; ** Adjusted for age, gender and socioeconomic status 5

6

7

8

9

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DISCUSSION 1

This study aimed to prospectively investigate the potential relationships between 2

scholastic and sport factors with smoking in older adolescents. The analyses revealed several 3

important findings that should be highlighted. First, baseline scholastic factors were 4

systematically associated with smoking, with poorer scholastic achievement in adolescents who 5

reported smoking at baseline and follow-up. The absence from school at baseline was a predictor 6

of smoking initiation in the following period. Quitting sports, poor competitive achievement, and 7

less than 5 years of participation in sports were shown to be specific risks for smoking and 8

smoking initiation. Prior to discussing these findings, we will provide a brief overview of the 9

established prevalence and trends in smoking. Smoking prevalence significantly increased from 10

28% to 36% during the course of the study. Consequently, approximately 77% of adolescents 11

who reported smoking at the end of high school (i.e., 28/36) initiated smoking when they were 12

younger than 16 years. Although participants self-reported their smoking status, which should be 13

observed as a limitation of the study, the reported prevalence of smoking in this study is similar 14

to previous reports of a 30-35% prevalence of adolescent smokers in Bosnia and Herzegovina 15

and the wider territory of the former Yugoslavia 3 27 30. Consequently, the self-reported data on 16

smoking obtained here are plausible. This study is unique, as it is one of the first to prospectively 17

investigate the factors associated with smoking in adolescents from south-eastern Europe. 18

Therefore, the data on the relationships between scholastic- and sport-factors and smoking 19

initiation are particularly interesting. 20

21

The associations between scholastic factors and smoking at study baseline (i.e., when 22

subjects were 16 years old) and the associations between scholastic factors and scholastic 23

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achievement at follow up (i.e., end of high school, 18 years of age) are similar. In both waves, 1

higher odds of smoking are observed in adolescents with lower scholastic achievement. Our 2

findings are therefore in accordance with the results of previous cross-sectional studies performed 3

with adolescents of a similar age, which repeatedly reported lower educational achievement 4

among children who smoke 7 18 27. Although there is a general consensus on the negative 5

associations between smoking and performance in school, the mechanisms that lead to these 6

associations are still controversial. Some authors highlight the negative effects of smoking on 7

cognitive capacities, and consequently poorer learning capabilities, as a result of cigarette 8

smoking 18. This explanation is strongly supported by the evident physiological mechanisms (i.e., 9

alterations in brain structure as a result of smoking) 11-13. The main criticism of this explanation 10

arises from the relatively short period of smoking in adolescents. Therefore, significant 11

deterioration in cognitive capacities and the resulting low academic achievement in adolescents is 12

less probable. As a result, it is suggested that lower academic achievement in adolescent smokers 13

may actually be the cause, and not the effect, of smoking. Indeed, children who fail at school are 14

frequently in “out of school situations” and therefore in unique socio-cultural environments in 15

which they are more likely to initiate smoking 3 6. This theory thus focuses on social influence. In 16

this study, we showed a negative relationship between “school absence” at baseline (i.e., 16 years 17

of age) and smoking initiation in the following 2-year period. Therefore, our results actually 18

support the theory of social influence as a probable explanation of the cause-effect relationship 19

between academic failure and smoking in this age group. Briefly, the general associations 20

between scholastic variables and smoking are clear, demonstrating that children who smoke 21

perform poorly in school. However, it must be stressed that more frequent absences from school 22

at the beginning of the 3rd year of high school is a clear predictor of smoking initiation in the 23

following two years. Of course, one can argue that scholastic achievement was not entirely 24

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objectively evaluated because the data were self-reported. Although this should be considered an 1

important limitation of the study, we believe that the strict anonymity of the testing decreased the 2

possibility that the participants responded dishonestly. 3

4

Our study found a high risk for smoking initiation for those adolescents (i) who quit sport, 5

(ii) who reported low competitive success, and (iii) who had a relatively short period of 6

involvement in sport. Generally, this is in accordance with very recent studies which have noted a 7

higher prevalence of smoking in adolescents who quit sports and those who achieved poorer 8

competitive results 7 28. Because of the cross-sectional nature of studies the cause-and-effect 9

relationship between quitting sports and smoking had not been clearly identified. There is a 10

possibility that smoking impairs physical capacities, and this could therefore result in poor sport 11

performance and a lack of success, which would consequently result in withdrawal from sports 31. 12

However, it is also possible that children first stop practicing a sport and then start to smoke, as a 13

result of the (negative) influence of their new socio-cultural environment in which smoking is 14

more prevalent 5 7. The results of our study support the latter explanation. Namely, all three sport 15

factors observed in this study were found to be significant predictors of smoking initiation in 16

older adolescents. First, those who reported at study-baseline that they had once practiced sports 17

and then quit were at a higher risk of starting to smoke during the course of the study (i.e. 18

between 16 and 18 years of age), than their peers who were never involved in sports. 19

Additionally, a higher risk of initiating smoking was evident in adolescents who were involved in 20

sports for less than 5 years and in those who practiced sports but did not achieve significant 21

competitive results. Most probably, the association of all three sport factors ( (i) quitting sport, 22

(ii) short time of involvement and (iii) low competitive result), with smoking initiation is 23

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generated by equal mechanism. Briefly, it is well known that better sport results are actually a 1

direct or indirect consequence of a longer involvement in sport 32 33. At the same time, a lack of 2

good sports results (i.e. poor competitive achievement in sport) is one of the most important 3

factors which results in withdrawing from a sport in adolescence 34. The 16-to18-year old 4

adolescents who do not achieve competitive results regularly stop participating in sports at this 5

particular age, mostly because they have become personally aware of their inferiority (i.e. their 6

lack of ability and/or skills)34. Meanwhile, it is known that individuals identify with particular 7

groups of peers, and being a member of a specific social network or group influences individuals’ 8

values as well as their attitudes and the norms to which they are exposed 35. Therefore, it is likely 9

that adolescents who quit sports started smoking as a way of adopting the norms of the “non-10

sporting” society and of finding a place in a new social-milieu. This study lacks qualitative data 11

on the reasons for quitting sports and an objective evaluation of lower competitive achievement 12

in sports. This is a clear limitation of the investigation, as we are not able to accurately explain 13

the background of the relationship within the sport factors observed herein. 14

15

This study evidenced specific associations between scholastic and sport factors with 16

smoking initiation in older adolescents, but we may not ignore the potential confounding effects 17

of some covariates that were not observed in this study, such as those concerned with the home 18

environment (i.e. familiar factors). For example, it could be expected that both quitting sports and 19

poor academic performance (i.e. significant predictors of smoking initiation in our participants), 20

might be a result of some family-related issues such as lack of parental monitoring and high 21

parental conflict. Consequently, the lack of information on these issues could be highlighted as a 22

study limitation. However, we were of the opinion that eventual knowledge of these confounding 23

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effects, although scientifically interesting, may not add much to our understanding of how to 1

intervene. This is because children who have problems in their home environment, such as being 2

in conflict with their parents and/or experiencing a lack of parental control could not be tracked 3

(i.e. information on that manner was not able to be obtained). Meanwhile, all variables included 4

in this study were easily obtainable throughout the education system, which allows identification 5

of those children who are at specific risk for smoking initiation in late adolescence. 6

7

The most important limitation comes from the fact that this study observed adolescents 8

from 16 years of age, when many students had already started to smoke. Therefore the 9

generalizability of the findings is limited to older adolescents. Next, data on peer-smoking and 10

parental-smoking were not collected. It is reasonable to expect that these two factors could be 11

determinants of sport- and educational-factors, and consequently directly and/or indirectly 12

influence the associations studied in this investigation. Also, we have evaluated “formal” sport-13

participation only, while some potentially important determinants of physical exercising (i.e. self-14

exercising, fitness centres) were not observed. Finally, students were asked on scholastic 15

achievement over the last semester, which is relatively crude indicator of overall school success. 16

Therefore, in future studies more precise evaluation of physical activity, and accurate depiction of 17

changes in scholastic achievement (i.e. positive or negative changes in scholastic success) are 18

necessary. 19

20

In order to objectively overview the findings, some specific contextual information on the 21

socio-cultural environments is necessary. Bosnia and Herzegovina is a country which is 22

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traditionally oriented toward tobacco consumption since the country was part of the former 1

Ottoman Empire, and tobacco farming has been an important part of the economy in some 2

cantons for more than 300 years (e.g. particularly in the Herzegovina-Neretva Canton, which is 3

the Mediterranean part of the country) 6. As a result, smoking is socially accepted in public, and 4

cigarettes are relatively cheap. Next, although smoking is prohibited in schools, such regulations 5

are really only imposed for closed high-school buildings. It is probably even more important that 6

smoking is not prohibited in places of social gatherings (e.g. pubs, cafe bars, and disco clubs). 7

Finally, although is formally allowed only for those over 18 years, there is no ID control for 8

purchasing cigarettes, while cigarette vending machines are also common. Therefore, although 9

the generalizability of the findings is somewhat limited (mostly for Bosnian and Herzegovinian 10

adolescents 16-to-18 years of age), the authors are of the opinion that the generalizability is to 11

some extent possible for surrounding countries as well. This is because in many of the countries 12

of the former Yugoslavia, smoking is a socially accepted behaviour, there are no strict regulations 13

against smoking in public, and tobacco products are relatively cheap 28 30. 14

15

The following conclusions can be made. With 28% of adolescents who started smoking 16

before they were 16 and an additional 8% who started smoking between 16 and 18 years of age, 17

the prevalence of smoking is high. As expected from previous investigations, the smoking 18

prevalence was higher in adolescents who achieved poor grades in school. This study expands on 19

previous knowledge by demonstrating that school absences at the age of 16 are a predictor of 20

smoking initiation over the next two years (i.e., by the end of high school). Additionally, 21

adolescents who reported quitting sports, those who were involved in sports for a relatively short 22

time (i.e., up to 5 years), and those who achieved low competitive success by the age of 16 were 23

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found to be at risk of starting smoking by the end of high school (i.e., 18 years of age). Therefore, 1

to develop accurate and problem-oriented public health policies against smoking in older 2

adolescents, public health authorities should co-operate with school and sport organisations to 3

target the most vulnerable groups of adolescents established in this study. Although it was not 4

among the primary aims of the study, this was the first investigation which indirectly showed that 5

the majority of adolescents from Bosnia and Herzegovina started smoking cigarettes before 16 6

years of age. Therefore, further investigations should evaluate the predictors of smoking in 7

younger ages. 8

9

Acknowledgements 10

Special thanks go to Cantonal Ministries of Education who supported and approved the 11

investigation. The authors are particularly grateful to all children who voluntarily participated in 12

the study. 13

14

Contributors 15

DS designed the study, performed the statistical analysis and discussed the data; NS, AT 16

and IJ collected the data, overviewed previous research and drafted the manuscript; LO collected 17

the data and discussed the public health issues of the investigation; HP overviewed the previous 18

research and discussed the sport factors in relation to smoking; NZ discussed the data and 19

participated in statistical analyses. All authors have read and approved the final version. 20

21

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Ethics approval 1

The Ethical Boards of University of Split, Faculty of Kinesiology, Split, Croatia and 2

University of Mostar, School of Medicine, Mostar, Bosnia and Herzegovina approved the 3

Investigation. Additionally, the study was approved by Cantonal Ministries of Education. 4

5

Funding 6

This study and publication were partially financed by the University of Split, Faculty of 7

Kinesiology, Split, Croatia 8

9

Conflict of interest 10

The authors report no conflicts of interest. 11

12

13

14

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1

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34. Lee M. Coaching Children in Sport: Principles and Practice: Taylor & Francis 2002. 1

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4

5

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Data sharing statement: 1

Data files are freely available here: https://www.dropbox.com/s/n7opixov3hrglj8/data.xlsx?dl=0 2

3

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Figure legend: 1

2

Figure 1 3

Sampling procedure, participants and non-responders (i.e. absent from school on testing day, 4

inconsistency in identification codes) 5

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Figure 1 Sampling procedure, participants and non-responders (i.e. absent from school on testing day, inconsistency

in identification codes)

76x69mm (300 x 300 DPI)

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Supplementary Table




Females 156 14

Nonsmokers

Males 252 53 Females 304 35

Subtotal smokers 316 37

2.11 (0.15) Subtotal nonsmokers 556 88

Subtotal males 412 76

8.00 (0.01) Subtotal females 460 49

Total 872 125

LEGEND: Note that group of non-responders does not include participants who were not present at the

baseline testing (49 participants) but includes those who used inconsistent identification codes at testing

waves (20 participants)

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Introduction



para

Methods



collection P9






Cohort study: P9










and why NA






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Results

















Discussion





(beginning)




Other information




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BMJ Open

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Page 33 of 33


BMJ Open

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bmj openfor peer review only 25 1 16. filippidis ft, agaku it, vardavas ci. the association between...

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