Abstract
-
Background
Indonesia has one of the highest smoking prevalence rates worldwide; smoking initiation often occurs during adolescence or childhood. This study aimed to identify factors associated with loss of autonomy among adolescent smokers in Indonesia.
-
Methods
This cross-sectional study analyzed data from the 2019 Indonesia Global Youth Tobacco Survey (GYTS). The sample comprised students who reported smoking within the past 30 days. The primary outcome variable was loss of autonomy. Multivariate analysis utilized modified Poisson regression with backward elimination. Results are presented as adjusted prevalence ratios (APRs) with a significance level of P<0.05.
-
Results
Among 1,129 student smokers, only 27.44% retained their autonomy. A total of 61.20% reported a strong urge to smoke and an inability to resist doing so. Factors significantly associated with loss of autonomy included electronic cigarette use (APR, 1.08; 95% confidence interval [CI], 1.01–1.17), cigarette accessibility near schools (APR, 1.11; 95% CI, 1.04–1.19), and peer cigarette offers (APR, 1.39; 95% CI, 1.23–1.57). Higher daily cigarette consumption was also associated with a greater likelihood of loss of autonomy.
-
Conclusion
Loss of autonomy among adolescent smokers indicates nicotine dependence and difficulty quitting. Daily cigarette consumption, peer influence, cigarette accessibility near schools, and electronic cigarette use are key contributing factors. Essential policy recommendations include strengthening youth-focused tobacco regulations and incorporating smoking prevention and cessation programs into school curricula.
-
Keywords: Nicotine Dependence; Youth; Nicotine Addiction; Tobacco Use Disorder
Graphical Abstract
Introduction
In low- and middle-income countries, smoking remains a leading cause of premature death. In the Southeast Asian region, although age-standardized smoking rates are declining in most countries, they remain high in Lao People’s Democratic Republic, Indonesia, and Timor-Leste [
1]. Nearly 80% of adolescents who have ever smoked initiated the habit before age 13 years [
2]. Adolescents who initiate smoking early face a substantially higher risk of developing severe nicotine addiction and are more likely to continue smoking into adulthood.
Even infrequent cigarette use can lead to addiction symptoms, such as failed cessation attempts [
3]. This difficulty in cessation is referred to as loss of autonomy (LOA), which occurs when individuals can no longer control their smoking behavior, making abstinence unpleasant or unsustainable [
4]. Among adolescents, LOA is a critical milestone in the progression toward nicotine dependence [
3,
4].
Adolescents who lose autonomy over their smoking behavior are less likely to successfully quit and are more likely to transition to daily smoking [
3]. This creates a reinforcing cycle: the more autonomy adolescents lose, the more frequently they smoke, thereby deepening their addiction [
5]. Once autonomy is lost, the likelihood of lifelong smoking increases, contributing to long-term health risks such as lung disease, cardiovascular diseases, and cancer [
6-
8].
Despite having one of the highest smoking prevalence rates and a continuing upward trend in tobacco use, Indonesia lacks sufficient data regarding LOA among adolescent smokers. Understanding the factors that contribute to LOA is essential for developing targeted and effective smoking prevention and cessation interventions. Therefore, this study aimed to identify the determinants of LOA among adolescent smokers in Indonesia.
Methods
Study design
This cross-sectional study utilized secondary data from the 2019 Indonesia Global Youth Tobacco Survey (GYTS). The GYTS is a standardized, school-based international survey developed collaboratively by the World Health Organization (WHO), the U.S. Centers for Disease Control and Prevention, and the Indonesian Ministry of Health that collects data on adolescent tobacco use and related factors. It employs a standardized methodology, rigorous sampling techniques, and a validated questionnaire, ensuring that the data are representative and comparable across countries. GYTS data are used to inform public health policies and programs aimed at reducing adolescent tobacco use.
Population and sample
A total of 9,992 students from grades 7 to 12, representing 148 schools across nearly all provinces in Indonesia, participated in the survey. The study achieved a 91.0% response rate, ensuring national representativeness. From this overall sample, a subset of 1,714 students who reported smoking within the past 30 days was identified.
Outcome variable
LOA in student smokers manifests as an inability to quit despite a conscious desire to do so, driven by nicotine dependence, psychological cravings, and peer influences. Key indicators include failed cessation attempts, withdrawal symptoms, and persistent smoking despite awareness of adverse effects [
3,
9]. LOA was measured using five questions from the Indonesian GYTS questionnaire. These questions assessed the following [
10]: (1) feeling the urge to smoke first thing in the morning; (2) experiencing a strong craving to smoke after a cigarette; (3) wanting to stop smoking immediately; (4) attempting to quit smoking in the past 12 months; and (5) believing in the ability to stop smoking. Respondents answering “yes” to questions 1 and 2, and “no” to questions 3, 4, and 5, were classified as experiencing LOA.
The independent variables were categorized into three groups: sociodemographic characteristics, internal factors, and external factors. Sociodemographic characteristics included age, gender, school grade, and disposable income. Internal factors included age of smoking initiation, days smoked per month, cigarettes smoked per day, perception of smoking harm, and e-cigarette use. E-cigarette use was derived from the question: “During the past 30 days, where did you usually get your e-cigarettes?” Response options included “I have not used e-cigarettes in the past 30 days” and several categories indicating sources of acquisition (e.g., store, online shop, street vendor, or from someone else). For analysis, respondents who selected any source of acquisition were classified as current e-cigarette users (“yes”), while those who reported no use in the past 30 days were classified as non-users (“no”). Because the survey lacked a direct question regarding frequency of use, this acquisition-based item served as the most appropriate proxy.
External factors included parental smoking status, peer cigarette offers, cigarette accessibility near schools, advice to quit smoking, and observation of teachers smoking on school grounds. The variable “observation of teachers smoking on school grounds” was derived from the question: “During school hours, how often do you see teachers smoking in the school?” For analytical purposes, the variable was dichotomized into “yes” (everyday/sometimes) and “no” (never/don’t know). Detailed operational definitions are provided in the
Supplement 1.
Data selection focused on current smokers. Of all 2019 Indonesian GYTS respondents, 1,714 students (17.15%) reported smoking within the past 30 days. Subsequently, 585 respondents with missing data were excluded. After final selection, 1,129 eligible students were retained for analysis (
Figure 1).
Univariate analysis evaluated the frequency and proportion of each variable, accounting for data weighting. Bivariate analysis assessed the associations between LOA and independent variables. Associations were measured using prevalence ratios (PRs) and 95% confidence intervals (CIs) Variables showing statistical significance (P<0.05) in the bivariate analysis were included in a multivariate modified Poisson regression model. Backward elimination was applied to optimize model fit, systematically removing non-significant variables to yield a parsimonious model. Results of the multivariate analysis are presented as adjusted prevalence ratios (APRs). All statistical analyses were performed using Stata ver. 17.0 (Stata Corp.).
Ethical consideration
This study used publicly available de-identified data and therefore did not require Institutional Review Board approval.
Results
Table 1 presents the questions indicating the presence of LOA among student smokers. Regarding these indicators, 61.20% of students reported a strong desire to smoke again and an inability to resist doing so. Additionally, 32.62% of students reported smoking as their first activity in the morning. Only 12.23% of students were confident in their ability to quit smoking, reflecting low cessation self-efficacy.
Among the 1,129 students, only 27.44% retained their autonomy. Conversely, nearly one-third of the students (30.15%) exhibited LOA based on a single indicator. Notably, 2.48% of students exhibited LOA across all five indicators, suggesting severe nicotine dependence (
Figure 2).
As shown in
Table 2, 817 students (nearly three-quarters of the smoking cohort) experienced LOA. These respondents were predominantly boys (94.70%). Nearly half of the students had used electronic cigarettes in the past 30 days, and 17.09% reported smoking daily. The most common daily consumption rate was 2 to 5 cigarettes.
The most common age of smoking initiation was 12 to 13 years (31.15%), corresponding to the transition from elementary to junior high school. Nearly three-quarters of students initiated smoking due to peer influence. The school environment strongly facilitated smoking behavior; 61.58% of students reported observing teachers smoking on school grounds, and one-third reported easy cigarette accessibility near schools.
In the bivariate analysis, several independent variables were significantly associated with LOA, including age, school grade, e-cigarette use, days smoked per month, cigarettes smoked per day, peer cigarette offers, observation of teachers smoking on school grounds, and cigarette accessibility near schools.
In the multivariate analysis (
Table 3), four variables remained significantly associated with LOA. Students who used electronic cigarettes were 1.08 times more likely to experience LOA compared with those who did not. Beyond the magnitude of these associations, the findings suggest interrelated behavioral and environmental mechanisms underlying LOA among adolescents. Misperceptions regarding e-cigarettes among adolescents—particularly the belief that they pose minimal health risks—may lead to their use as an early source of nicotine exposure. Such exposure can facilitate neurobiological dependence and increase vulnerability to nicotine addiction.
Cigarette accessibility near schools increased the likelihood of LOA by 1.11 times, while peer cigarette offers increased the likelihood by 1.39 times. Easy access to cigarettes in the vicinity of schools likely reinforces this process by reducing structural barriers to continued use, thereby enabling more frequent smoking and further impairing self-regulation. Peer cigarette offers appear to exert the strongest influence, highlighting the central role of social normalization and peer reinforcement in shaping adolescent smoking behavior. Peer environments may simultaneously promote smoking initiation, sustain access to tobacco products, and normalize nicotine use, thereby interacting with both e-cigarette exposure and cigarette availability to accelerate the transition from experimentation to loss of control.
Additionally, higher daily cigarette consumption was associated with a greater likelihood of LOA. Consistent with this framework, the observed dose-response relationship between daily cigarette consumption and LOA supports the notion that repeated nicotine exposure progressively undermines adolescents’ capacity to regulate smoking behavior.
Discussion
This study provides robust evidence that LOA is highly prevalent among adolescent smokers and emerges early in the smoking trajectory. Nearly three-quarters of student smokers experienced at least one indicator of LOA, whereas a small but concerning proportion exhibited LOA across all five indicators, reflecting severe nicotine dependence. The most frequent indicators were strong cravings and difficulty resisting the urge to smoke, underscoring that impaired control over smoking behavior can develop rapidly during adolescence. These findings reinforce the conceptualization of LOA as an early and sensitive marker of nicotine addiction among youth.
Adolescent LOA is commonly assessed using the Hooked on Nicotine Checklist (HONC) [
11,
12]. The HONC consists of 10 items designed to comprehensively assess LOA. Even a single dependence symptom is sufficient to indicate the onset of LOA [
11]. Early LOA can be identified using modified or shortened HONC items that capture key symptoms such as cravings, inability to resist smoking, and smoking upon waking [
10,
13,
14].
In this study, 72.55% of adolescent smokers in Indonesia experienced LOA, indicating severe early nicotine dependence. This finding is consistent with evidence from other settings showing that LOA is common among young smokers and increases with smoking intensity and early initiation. In Greece, 88.8% of current smokers aged 13 to 15 years reported at least one symptom of LOA, with prevalence rising alongside smoking frequency [
3]. Similarly, among young adult smokers in India, 85% experienced at least one LOA symptom, particularly those who smoked more frequently and initiated smoking at younger ages [
9]. In contrast, studies from New Zealand reported substantially lower LOA prevalence rates, with 46% of adolescents who smoked less than monthly and 25% to 30% of those who had smoked only one cigarette experiencing diminished autonomy, although LOA could still emerge after minimal exposure [
15]. The relatively high prevalence of LOA among adolescent smokers in Indonesia suggests that they may transition more rapidly from experimentation to nicotine dependence. This underscores the importance of early preventive interventions and strengthened tobacco control policies.
One of the most common prohibitory policies to control adolescent tobacco use is banning tobacco sales to minors [
16]. This strategy is also employed by Indonesia’s current tobacco control law, which prohibits the sale of tobacco products within 500 meters of playgrounds, schools, and other places where children are frequently present. The purpose of this strategy is to make it more difficult for minors to obtain cigarettes and to reduce the visibility of tobacco products in places frequented by youth. Additionally, the law establishes an 18-year minimum age requirement for buying and using cigarettes [
17].
Theoretically, restricting access to commercial cigarettes reduces consumption [
18]. However, adolescents often utilize social networks and alternative methods to circumvent these bans, as demonstrated by previous policy evaluations [
16]. Strict implementation of prohibitions is also expected to establish anti-smoking norms, thereby reducing adolescent smoking rates . Nonetheless, evaluations show that although sales bans decrease the social appeal of smoking, they do not alter adolescents’ risk perceptions [
16]. Additionally, some theories suggest that smoking may become more appealing to adolescents when it is prohibited [
18].
Accordingly, implementing the sales ban in Indonesia requires accounting for these diverse environmental and personal factors to ensure effectiveness [
18]. Strict enforcement of other current legal provisions—including prohibiting online sales, restricting tobacco promotion, and mandating stringent packaging [
17]—may enhance the sales ban’s effectiveness by raising risk awareness, shaping public anti-smoking norms, and minimizing adolescents’ ability to obtain cigarettes from alternative sources.
Adolescent smoking initiation frequently occurs through peer offers and is sustained by curiosity [
19,
20]. By conforming to peer behavior, adolescents seek social acceptance and validation [
20]. The resulting comfort, acceptance, and peer validation make it difficult for them to refuse subsequent cigarette offers. Furthermore, adolescents often struggle to quit smoking due to an inability to assert their cessation goals or reject peer invitations [
21]. This inability to refuse cigarette offers directly indicates LOA among addicted adolescent smokers.
Conversely, positive peer support is strongly associated with the intention to quit smoking [
22]. Multidimensional social support—including emotional, esteem, instrumental, and informational support—is critical for successful cessation [
23]. Such peer support heavily influences an adolescent’s decision to initiate quit attempts [
20]. Additionally, the efficacy of peer support in fostering cessation intentions is mediated by psychological mechanisms such as imitation, suggestion, identification, and sympathy. Ultimately, peers play a crucial role in shaping adolescent identity, which inherently dictates their smoking behaviors [
24].
Adolescent smokers exhibit increasing nicotine dependence as their daily cigarette consumption rises; studies demonstrate that the number of cigarettes per day is significantly correlated with higher addiction scores on validated instruments such as the Modified Fagerstrom Tolerance Questionnaire and the HONC [
4]. Research on heavy smokers in clinical settings demonstrates that lighter daily cigarette consumption predicts greater cessation success over 6 months, establishing consumption volume as a significant predictor of quitting [
25]. A 2020 systematic review found that combining behavioral counseling with pharmacotherapy substantially improves cessation outcomes for heavy smokers, yielding significantly higher abstinence rates than unassisted cessation attempts [
26]. In adolescents, trajectory studies suggest that dependence symptoms develop in tandem with smoking behavior; specifically, increased frequency of use—not just total quantity—drives nicotine dependence early in the smoking trajectory [
27]. Taken together, these findings affirm that daily cigarette consumption is a reliable indicator of nicotine addiction in student populations, and that cessation efforts are most effective when tailored to baseline dependence levels and smoking intensity.
This study’s primary strength is its national representativeness for examining adolescent nicotine dependence, utilizing a rigorous survey methodology overseen by the WHO. However, the analysis is limited by the available variables and the pre-defined items within the secondary dataset. Furthermore, the cross-sectional design precludes establishing causal relationships between the identified factors and LOA. Therefore, longitudinal studies are required to elucidate the causal mechanisms driving adolescent nicotine addiction and LOA.
Conclusion
LOA among adolescent smokers reflects an inability to quit due to nicotine addiction. Daily cigarette consumption demonstrates a clear dose-response relationship with the likelihood of losing behavioral control. LOA also contributes to an inability to refuse peer cigarette offers, often driven by distorted perceptions of social acceptance and masculinity. Additionally, easy cigarette accessibility near schools—particularly single-cigarette sales—and the increasing prevalence of adolescent e-cigarette use warrant stringent government intervention.
Indonesian Government Regulation No. 28 (2024) on Health stipulates that schools are designated as smoke-free areas; smoking by any individual, alongside the sale and promotion of all tobacco products (including e-cigarettes), is strictly prohibited [
17]. The regulation also bans single-cigarette sales and prohibits tobacco retail near school premises. The present findings provide empirical support for these regulatory provisions and underscore the need for strict and consistent enforcement within educational environments. Integrating comprehensive education regarding the health risks of tobacco and e-cigarettes into school curricula is crucial for reshaping adolescent risk perceptions and preventing initiation.
Notes
Supplementary materials
Figure. 1.Sample selection flowchart. GYTS, Global Youth Tobacco Survey.
Figure. 2.Prevalence of loss of autonomy indicators among adolescent smokers.
Table 1.Questions indicating loss of autonomy among adolescent smokers
|
No. |
Indicator (answer) |
% (95% CI) |
|
1 |
Do you want to stop smoking now? (No) |
19.06 (16.67–21.70) |
|
2 |
During the past 12 months, didn’t you ever try to stop smoking? (No) |
20.03 (17.58–22.71) |
|
3 |
Do you think you would be able to stop smoking if you wanted to? (No) |
12.23 (10.29–14.46) |
|
4 |
Do you ever smoke tobacco or feel like smoking tobacco first thing in the morning? (Yes) |
32.62 (29.72–35.64) |
|
5 |
After you smoke tobacco do you start to feel a strong desire to smoke again that is hard to ignore? (Yes) |
61.20 (58.07–64.24) |
Table 2.Bivariate analysis of factors associated with loss of autonomy among adolescent smokers in Indonesia
|
Variable |
Total |
Loss of autonomy
|
PR (95% CI) |
P-value |
|
Yes |
No |
|
Total no. |
1,129 (100.00) |
817 (72.55) |
312 (27.45) |
|
|
|
Age (y) |
|
|
|
|
|
|
≤13 |
325 (29.78) |
207 (64.43) |
118 (35.57) |
Ref |
|
|
14–15 |
383 (37.46) |
284 (74.62) |
99 (25.38) |
1.15 (1.03–1.28) |
0.008*
|
|
≥16 |
421 (32.76) |
326 (77.57) |
95 (22.43) |
1.20 (1.08–1.33) |
0.001*
|
|
Gender |
|
|
|
|
|
|
Girls |
63 (5.30) |
38 (66.39) |
25 (33.61) |
Ref |
|
|
Boys |
1,066 (94.70) |
779 (72.90) |
287 (27.10) |
1.09 (0.90–1.33) |
0.340 |
|
Grade |
|
|
|
|
|
|
Junior high school |
649 (63.36) |
450 (70.19) |
199 (29.81) |
Ref |
|
|
Senior high school |
480 (36.64) |
367 (76.64) |
113 (23.36) |
1.09 (1.01–1.17) |
0.021*
|
|
Adolescent disposable income (IDR) |
|
|
|
|
|
|
<11.000 |
312 (26.76) |
212 (68.41) |
100 (31.59) |
Ref |
|
|
11.000–30.000 |
361 (31.99) |
264 (73.10) |
97 (26.90) |
1.06 (0.96–1.18) |
0.218 |
|
31.000–50.000 |
193 (17.61) |
143 (74.79) |
50 (25.21) |
1.09 (0.97–1.23) |
0.144 |
|
>50.000 |
263 (23.64) |
198 (74.84) |
65 (25.16) |
1.09 (0.92–1.22) |
0.115 |
|
E-cigarette smoking status |
|
|
|
|
|
|
No |
592 (52.16) |
382 (64.36) |
210 (35.64) |
Ref |
|
|
Yes |
537 (47.84) |
435 (81.49) |
102 (18.51) |
1.26 (1.17–1.36) |
0.001*
|
|
Days smoked per month |
|
|
|
|
|
|
1–2 |
425 (38.34) |
232 (55.69) |
193 (44.31) |
Ref |
|
|
3–5 |
189 (17.65) |
131 (71.60) |
58 (28.40) |
1.28 (1.12–1.46) |
0.001*
|
|
6–9 |
127 (11.48) |
105 (82.58) |
22 (17.42) |
1.48 (1.30–1.68) |
0.001*
|
|
10–19 |
125 (10.68) |
104 (82.20) |
21 (17.80) |
1.47 (1.29–1.67) |
0.001*
|
|
20–29 |
57 (4.75) |
51 (88.96) |
6 (11.04) |
1.59 (1.39–1.82) |
0.001*
|
|
Everyday |
206 (17.09) |
194 (94.04) |
12 (5.96) |
1.68 (1.52–1.86) |
0.001*
|
|
Cigarettes smoked per day |
|
|
|
|
|
|
Less 1 cigarette |
244 (22.40) |
110 (48.58) |
134 (51.42) |
Ref |
|
|
1 cigarette |
359 (33.07) |
229 (63.52) |
130 (36.48) |
1.30 (1.10–1.54) |
0.001*
|
|
2–5 cigarettes |
385 (33.23) |
342 (89.61) |
43 (10.39) |
1.84 (1.59–2.13) |
0.001*
|
|
6–10 cigarettes |
94 (7.71) |
91 (97.64) |
3 (2.36) |
2.00 (1.74–2.31) |
0.001*
|
|
More 10 cigarettes |
47 (3.60) |
45 (93.45) |
2 (6.55) |
1.92 (1.61–2.28) |
0.001*
|
|
First age smoked (y) |
|
|
|
|
|
|
≥16 |
79 (6.07) |
58 (71.67) |
21 (28.33) |
Ref |
|
|
14–15 |
250 (20.88) |
186 (75.50) |
64 (24.50) |
1.05 (0.89–1.24) |
0.540 |
|
12–13 |
338 (31.15) |
232 (69.12) |
106 (30.88) |
0.96 (0.81–1.14) |
0.672 |
|
10–11 |
229 (21.15) |
160 (69.61) |
69 (30.39) |
0.97 (0.81–1.15) |
0.744 |
|
8–9 |
117 (10.69) |
91 (78.75) |
26 (21.25) |
1.09 (0.91–1.31) |
0.304 |
|
≤7 |
116 (10.07) |
90 (77.18) |
26 (22.82) |
1.07 (0.89–1.29) |
0.429 |
|
Perception smoking harmful |
|
|
|
|
|
|
No |
984 (86.99) |
710 (71.88) |
274 (28.12) |
Ref |
|
|
Yes |
145 (13.01) |
107 (77.03) |
38 (22.97) |
1.07 (0.96–1.18) |
0.174 |
|
Parent smoking |
|
|
|
|
|
|
No |
618 (53.67) |
435 (70.44) |
183 (29.56) |
Ref |
|
|
Yes |
511 (46.33) |
382 (75.00) |
129 (25.00) |
1.06 (0.98–1.15) |
0.112 |
|
Offering cigarette from friend |
|
|
|
|
|
|
No |
305 (27.09) |
151 (49.99) |
154 (50.01) |
Ref |
|
|
Yes |
824 (72.91) |
666 (80.94) |
158 (19.06) |
1.61 (1.42–1.83) |
0.001*
|
|
Observed teacher smoking at school |
|
|
|
|
|
|
No |
426 (38.42) |
289 (67.82) |
137 (32.18) |
Ref |
|
|
Yes |
703 (61.58) |
528 (75.51) |
175 (24.49) |
1.11 (1.02–1.21) |
0.012*
|
|
Access to cigarettes near schools |
|
|
|
|
|
|
No |
728 (66.14) |
477 (66.08) |
252 (33.92) |
Ref |
|
|
Yes |
398 (33.86) |
339 (85.31) |
59 (14.69) |
1.29 (1.20–1.38) |
0.001*
|
|
Advice to stop smoking |
|
|
|
|
|
|
Yes |
964 (85.61) |
703 (73.41) |
261 (26.59) |
Ref |
|
|
No |
165 (14.39) |
114 (67.46) |
51 (32.54) |
0.91 (0.81–1.03) |
0.178 |
Table 3.Multivariate modified Poisson regression analysis of factors associated with loss of autonomy among adolescent smokers in Indonesia
|
Variable |
APR (95% CI) |
P-value |
|
E-cigarette smoking status |
|
|
|
No |
Ref |
|
|
Yes |
1.08 (1.01–1.17) |
0.024*
|
|
Grade |
|
|
|
Junior high school |
Ref |
|
|
Senior high school |
0.91 (0.85–0.98) |
0.015*
|
|
Cigarettes smoked per day |
|
|
|
Less 1 cigarette |
Ref |
|
|
1 cigarette |
1.28 (1.09–1.50) |
0.002*
|
|
2–5 cigarettes |
1.65 (1.43–1.90) |
0.001*
|
|
6–10 cigarettes |
1.75 (1.51–2.02) |
0.001*
|
|
More 10 cigarettes |
1.68 (1.40–2.01) |
0.001*
|
|
Offering cigarette from friend |
|
|
|
No |
Ref |
|
|
Yes |
1.39 (1.23–1.57) |
0.001*
|
|
Access to cigarettes near schools |
|
|
|
No |
Ref |
|
|
Yes |
1.11 (1.04–1.19) |
0.001*
|
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