Prevalence and Predictors of Tobacco Use Among Adolescents in Ibadan, Nigeria

Ikenna Onoh, MBBS, MSc^1,2; Magbagbeola David Dairo, MBBS, MSc³; Muhammad Shakir Balogun, MBBS, MPH^1,4; Olufunmilayo Fawole, PhD, MBBS³ (View author affiliations)

Suggested citation for this article: Onoh I, Dairo MD, Balogun MS, Fawole O. Prevalence and Predictors of Tobacco Use Among Adolescents in Ibadan, Nigeria. Prev Chronic Dis 2023;20:220234. DOI: http://dx.doi.org/10.5888/pcd20.220234.

PEER REVIEWED

Abstract

Introduction

Most tobacco use begins in adolescence, causing dependence and prolonged use, and accounts for more than 8 million deaths worldwide annually. Monitoring adolescent tobacco use is critical to controlling it. Our study examined the prevalence and factors associated with tobacco use among adolescents in Nigeria.

Methods

We conducted a descriptive cross-sectional study among adolescent students in Ibadan, Nigeria, aged 11 to 18 years, from March through June 2021. We used a 2-stage cluster design to select 3,199 students from 23 schools. We adapted the Global Youth Tobacco Survey Core Questionnaire, version 1.2, for data collection and used logistic regression to assess factors associated with current tobacco use. We weighted all analyses for complex survey design and differential nonresponse at school, class, and student levels.

Results

Prevalence of current use of cigarettes, smokeless tobacco, or any tobacco were 1.4%, 1.1%, and 2.0%, respectively. Predictors of current tobacco use were male sex (adjusted odds ratio [aOR] = 3.13; 95% CI, 1.53–6.42); close friends as smokers (aOR = 3.10; 95% CI, 1.77–5.41); classmates as smokers (aOR = 3.12; 95% CI, 1.15–8.49); access to cigarette (aOR = 6.65; 95% CI, 2.55–17.33); perception that smoking is attractive (aOR = 3.15; 95% CI, 1.17–8.44); exposure to secondhand smoke (aOR = 2.93; 95% CI, 1.07–8.03); and internet awareness of tobacco use (aOR = 3.22; 95% CI, 1.48–7.04).

Conclusion

Prevalence of adolescent tobacco use was low in Ibadan. Predictors were peer influence, access to cigarettes, misperceptions about tobacco use, exposure to secondhand smoke, and tobacco advertising. We recommend an antitobacco campaign that uses a peer education strategy, a comprehensive enforcement of tobacco advertising, and a ban on public smoking.

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Introduction

Tobacco use is an important preventable cause of premature death and accounts for the deaths of up to half of its users (1). In 2017, about 8 million deaths worldwide were attributable to tobacco, mostly from smoked tobacco (2). If optimal control measures are not implemented, these deaths are projected to reach 10 million by 2030, mostly in low- and middle-income countries (3) where the high burden of tobacco use is due to an ongoing transition from tobacco production to tobacco consumption (4).

Africa has become attractive to multinational tobacco companies because of economic and personal income growth (5), an unsaturated market, weak tobacco-control policies, reduced awareness of the dangers of tobacco use, prioritization of control of infectious disease over noncommunicable diseases, and a young, growing population (4,6,7). Tobacco companies have adapted aggressive and uncontrolled marketing and promotional activities on the continent (6).

Worldwide, nearly all tobacco use begins in childhood and adolescence. Eighty-eight percent of adult daily smokers experiment with their first cigarette by age 18 years (8). Countries with the highest recent increases in tobacco use among their youth are generally lower human development index countries (a summary composite measure of a country’s average achievements in 3 basic aspects of human development: health, knowledge, and standard of living) (9). Globally, 43.8 million (12%) of adolescents aged 13 to 15 years use some form of tobacco (10). Adolescents in this age group in low- and middle-income countries have average tobacco use prevalence rates that range from 11% to 13% (10). The younger children are when they start smoking, the less likely they are to quit (11), with prolonged exposure leading to earlier and more pronounced health risks (12). The short-term health consequences of smoking include respiratory effects, such as exacerbation of severe asthma, pneumonia, ear infections, addiction to nicotine, and the risk of other drug use (13,14). In adults, the cumulative effects of tobacco use manifest as cardiovascular diseases, cancers, chronic respiratory diseases, type 2 diabetes, immune and autoimmune disorders, and eye disease (15). Early signs of these diseases occur in adolescents who smoke. Early abdominal aortic atherosclerosis, which affects the flow of blood to vital organs, has been found among young smokers. This leads to consequences such as hypertension, ischemic heart disease, and chronic obstructive pulmonary disease later in life (8).

A primary preventive approach that focuses on pre-adolescence and early adolescence is imperative. In response to the “tobacco epidemic,” the World Health Organization’s (WHO’s) Framework Convention on Tobacco Control (FCTC) (16) was adopted in 2003 and operationalized in 2005. WHO’s FCTC prioritizes the need for an effective surveillance system to monitor tobacco use. The Global Youth Tobacco Survey (GYTS), 1 of 4 surveys conducted within the Global Tobacco Surveillance System, is a school-based survey at a defined geographic site (17). GYTS collects data on students by using a standardized methodology (17). It includes questions on tobacco use and on knowledge and attitudes about tobacco, secondhand smoke (SHS) exposure, tobacco advertising exposure, tobacco cessation, access to tobacco products, and school teaching on tobacco use (18). The survey is repeated every 4 to 5 years, generating data that are comparable within and across countries (17).

Like other sub-Saharan African countries, Nigeria’s young and growing population (19) is attractive to the tobacco industry. Nigeria hosts transnational tobacco companies, including British America Tobacco Nigeria and Japan Tobacco International. Every year, more than 16,100 of Nigeria’s population die from tobacco-caused disease; 748,800 Nigerians aged 15 years or older and more than 25,000 aged 10 to 14 years use tobacco every day (20). Nigeria signed the WHO FCTC in 2004, ratified it in 2005 (21), and domesticated it through the National Tobacco Control Act of 2015 (22).

Two rounds of GYTS (2000 and 2008) were conducted in Nigeria, the last round in 1 state and 4 major cities, including Ibadan. At the time of the surveys, current cigarette use ranged from 2.6% to 6.2%, and current use of other tobacco products ranged from 13.1% to 23.3% (23). No follow-up survey has been done to date, and current levels of tobacco use among Nigerian adolescents is unknown. We addressed this information gap by determining the prevalence of tobacco use and its predictors among school-age adolescents in Ibadan, Nigeria.

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Methods

Study area

Ibadan, the capital of Oyo state, lies in southwestern Nigeria. Its urban area is divided into 5 local government areas: Ibadan North, Ibadan North East, Ibadan North West, Ibadan South East, and Ibadan South West. With an estimated population of 3,552,000 (24), Ibadan is the third most populous city in Nigeria and is home to several industries, including tobacco processing and cigarette manufacturing, and numerous bars, lounges, and night clubs where smoking is the cultural norm. Several public and private primary and secondary schools are in the city. The secondary school net attendance ratio — the proportion of official school age children participating in schooling — in Oyo State is 66.6% (25).

Study design and study population

Ours was a school-based, cross-sectional study among adolescents in grades 8 to 10 (Junior Secondary 2 and 3 or Senior Secondary 1), in public or private secondary schools in all 5 local government areas. These grades usually correspond to ages 13 to 15 years, the target age range for GYTS. Students were included in the study if they were in Junior Secondary 2 or 3 or in Senior Secondary 1 in selected schools. All students in selected classes were eligible to participate in the survey. Students in the selected classes who were absent on the day of data collection or who refused to participate were excluded from the survey.

Sample size and sampling technique

We computed the minimum sample size required for the study by using the formula for estimating a single proportion (26). After applying a cluster design effect factor of 1.5 and a 20% adjustment for nonresponse, the sample size was approximately 1,884 students. This corresponds with the minimum sample size of 1,875 students from 25 schools required for studies using the GYTS methodology (27).

We used a 2-stage cluster sample design. Schools were selected at the first stage by systematic selection with probability proportional to the enrollment size, followed by systematic random selection of classes in selected schools.

The sampling frame for the first stage included all private and public secondary schools in Ibadan containing any of the desired grades obtained from the most up-to-date school enrollment list from the Oyo State Ministry of Education. We listed the schools in the sampling frame from largest to smallest enrollment and assigned a continuous sequence of unique numeric identifiers. To maximize survey efficiency in line with GYTS methodology, we excluded schools with an enrolled eligible population of 40 or less. The cumulative population of eligible students in each school was then calculated.

To determine the sampling interval, we divided the total number of eligible students by 25, the target number of schools. A number-designated random start was then chosen randomly between 1 and the sampling interval. We first selected the school in which the cumulative population corresponding with the random start was located, after which subsequent schools were selected by adding sampling interval to random start until 25 schools were reached.

In the second stage, we selected classes by using systematic random sampling from a sequentially numbered list containing every eligible class in a selected school. Our calculated sampling interval for classes was based on the target student sample obtained from the enrollment list and assuming a fixed class size of 30. We specified the classes selected beforehand by their unique identifier. We surveyed all students in the selected classes who were present on the day of survey administration.

Data collection

We collected information about students’ sociodemographic characteristics, use of smoked and smokeless tobacco, tobacco use cessation, SHS exposure, access to cigarettes, antitobacco and protobacco message exposure, and attitudes and beliefs about using tobacco by using a self-administered, semistructured questionnaire adapted from the GYTS Core Questionnaire version 1.2 with optional questions (18). We pretested the study instrument in 2 nonstudy secondary schools in Ibadan on March 11, 2021, to test for clarity of questions. To increase the participation and availability of eligible students, we avoided the examination period and days close to holidays. A team of 10 trained research assistants led by a team supervisor collected data from March 30, 2021, through June 4, 2021.

Variable definition and measurement

Categories of variables of interest were tobacco use, SHS exposure, antitobacco advertising, protobacco advertising, attitudes and beliefs, and sociodemographics and background variables (eg, smoking by parents, peers) (Table 1).

Statistical analysis

We calculated weights for each student to account for the complex survey design and differential nonresponse at school, class, and student levels (27). The final weight for each student was a product of the school selection weight, class selection weight, and overall nonresponse adjustment factor. The school selection weight was the inverse probability of selecting a school. The class selection weight was the inverse probability of selecting a class in a school. The overall nonresponse adjustment factor was the product of school, class, and student nonresponse adjustment factors.

We used SPSS Statistics 23 (IBM Corp) to perform data analysis. The data collected were checked for errors and missing data, cleaned, and entered into the analysis software. Recoding of variables was done where appropriate. We summarized categorical variables with prevalence estimates and 95% CIs. We used the Pearson χ² test to assess bivariate associations between independent variables and current tobacco use. We modeled a binary logistic regression for predictors of current use of tobacco. The significance level for entering a variable into the model was set at 10% from bivariate analyses, in addition to variables found to be important in the literature. Level of significance from the logistic regression was set at P <.05.

Ethical considerations

We obtained ethical approval to conduct this study from the Oyo State Ministry of Health Ethical Review Committee. Before approaching the selected schools, we obtained approval from the Oyo State Ministry of Education. We then obtained approval from the heads of selected schools. We obtained written informed assent from each respondent after a detailed explanation of the study’s objectives, procedures, risks, and benefits and before starting the interview. The data were anonymized by using unique identifiers. Teachers were absent during survey administration to ensure privacy and to minimize reporting bias.

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Results

Participation rates and sociodemographic characteristics

A total of 3,199 students were surveyed from 23 selected schools. The school, class, student, and overall response rates were school, 92%; class, 100%; student, 93%; and overall, 85.6%. Mean age of all respondents was 14.1 years (SD, ±1.4 years), with ages ranging from 11 to 18 years. Although all participants were adolescents, most respondents (70.5%) were aged 13 to 15 years, with a slightly higher proportion of female students (54.4%) than male students (45.6%) (Table 2).

Prevalence and patterns of tobacco use

The prevalence of both ever and current use of all tobacco types was less than 5%. However, for all types, prevalence was higher in boys than girls. A very small proportion of respondents, 0.8%, were engaged in dual use of smoked and smokeless tobacco (Table 3).

Other tobacco use–related characteristics

Most respondents (97.6%) indicated that none of their parents smoked or that they were not aware of their parents’ smoking status. Similarly, most respondents indicated that none of their closest friends (93.4%) or classmates (89.1%) smoked tobacco. Few respondents (5.0%) had access to cigarettes near the school or perceived that cigarettes were easy to access (4.6%). Most (68.3%) perceived smoking to be harmful. A high proportion (40.3%) believed smokers had more friends (Table 4).

Fewer than half of respondents were aware of antitobacco messages in the media (43.3%) and at sporting or community events (31.9%). About 51.0% of students were exposed to tobacco use through television, videos, or movies. Much lower proportions were exposed to tobacco use or marketing at points of sale (12.5%) or on the internet (9.8%). The lowest level of exposure to SHS was at home (8.3%), and 46.1% of respondents overall were exposed (Table 4).

Predictors of current tobacco use

Boys were 3 times (aOR = 3.13; 95% CI, 1.53–6.42) more likely to use tobacco than girls (Table 5). Respondents, some of whose closest friends were smokers, were 3 times (aOR = 3.10; 95% CI, 1.77–5.41) more likely to use tobacco than those with no close friends who smoked. Those with access to cigarettes near their schools were twice (aOR = 1.97; 95% CI, 1.02–3.82) as likely to use tobacco as others, and those who perceived that cigarettes were easy to access were 7 times (aOR = 6.65; 95% CI, 2.55–17.33) likelier to use tobacco than other students. Additionally, those that felt adolescent smokers were attractive were 3 times likelier (aOR = 3.15; 95% CI, 1.17–8.44) to use tobacco than those who felt it was less attractive to smoke. Respondents who were not exposed to antitobacco messages at sporting or community events were less likely (aOR = 0.55; 95% CI, 0.39–0.76) to use tobacco than those who heard these messages. Finally, those who were aware of tobacco use on the internet were 3 times (aOR = 3.22; 95% CI, 1.48–7.04) likelier to use tobacco than other students.

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Discussion

The prevalence of tobacco use among adolescents in our study was low compared with recent global and African averages (10). It was also lower than findings from previous GYTSs across selected cities in Nigeria, including Ibadan (23), and another study done in Enugu, Nigeria (12). The low levels relative to global averages are likely due to the disproportionate burdens borne by Southeast Asia for smokeless tobacco and by the Americas and Europe for cigarettes (10). Similarly, the difference from the African average could reflect other countries in the region with higher prevalence (28). The difference as compared with the Enugu study is consistent with previous national findings showing higher prevalence of tobacco use in the southeastern part of Nigeria, where Enugu is located (29). These are all likely due to varying cultural and social norms.

The noted difference in tobacco use in Ibadan between the last round of GYTS in 2008 and our study may reflect tobacco control efforts in the intervening period. In the preceding decade, Nigeria signed on to and ratified the WHO FCTC and enacted the National Tobacco Control Act (22).

Levels of awareness of antitobacco messages in the media were lower than recent findings from different settings (28,30) as well as from the 2008 GYTS round in select Nigerian cities (23). It has been shown that sustained, well-designed, mass media campaigns can reduce tobacco use (31). It is therefore imperative that these campaigns form an important part of any comprehensive tobacco control program (31). However, global monitoring efforts have shown that low-income countries, including Nigeria, have not mounted an antitobacco media campaign in recent years (31).

Across all domains of protobacco advertising, the levels of exposure in our study were consistently lower than findings in most other studies (28,30). It is well documented that tobacco advertising, promotion, and sponsorship increase tobacco use and that comprehensive bans decrease tobacco use (32). Recent global monitoring reports recognize Nigeria as one of the best performing countries in adopting comprehensive advertising bans (31). The National Tobacco Control Act of 2015 (22) is exhaustive in articulating a ban on protobacco advertising, and country-specific monitoring has shown a high performance in this metric (20).

Despite the high performance of Nigeria with regards to bans on tobacco advertising, promotion, and sponsorship, more than half of respondents in our study were exposed to tobacco advertising through television, videos, or movies, suggesting a significant loophole in implementing the ban on these media. Additionally, awareness of tobacco use on the internet is noteworthy in our study. Despite the likely cross-border challenges that may be involved, policy makers are recognizing the need to ensure implementation of a ban on tobacco advertising, promotion, and sponsorship that use this channel of communication, considering the extensive exposure of children and adolescents to the internet’s various platforms (31).

Levels of exposure to SHS at home among our respondents were much lower than recent findings from countries across different continents (28,30), except for Finland where the values were slightly lower (33). Similar patterns were also found with levels of exposure in school. The 2 key factors that determine prevalence of SHS exposure are background prevalence of smoking in the population and variations in smoke-free laws and their enforcement (34). The low prevalence of SHS exposure in low-income settings such as Nigeria is mostly attributable to low smoking prevalence (34).

The effect on smoking of having close friends who smoke has also been shown in other studies (35–37). Adolescents are known to have strong social ties to friends (38), thus making them susceptible to peer pressure. The effect of peer pressure also explains the effect of having classmates who smoke. Similarly, perceived ease of getting cigarettes (37) supports the habit of smoking tobacco. Adolescents are exploratory and thrill-seeking in nature, and easy access to cigarettes only serves to feed these attributes. However, an added dimension is the effect on current tobacco use of access to cigarettes near school. This may play a role in the continued recruitment of children and young adolescents as lifelong tobacco users. Previous findings have shown that to introduce tobacco use to young people, tobacco companies strategically place youth-oriented brands in locations where young people congregate (39).

Our finding that the perception that smoking makes young people more attractive aligns with what was found in a Nigerian study conducted in 2013 (35). That study found that a positive attitude toward smoking was a significant determinant of smoking initiation among adolescent students. We also found that any exposure to SHS was a determinant of current tobacco use, as found in other studies (37,40). Witnessing tobacco use by peers, teachers, parents, siblings, or other adults sets an example for these very impressionable adolescents and normalizes tobacco use as something socially acceptable.

Finally, the effect of exposure to tobacco use on the internet is noteworthy because adolescents and children increasingly spend time on the internet and engage with different social media platforms. Highly engaging marketing and media advertising are effective at promoting tobacco use (41). Content on most internet and social media platforms is engaging and interactive.

Our study used a large sample size, which ensured the validity of various analyses and subgroup analyses. Respondents were selected by using standardized, systematic, and rigorous methods that provided representation of the in-school adolescent population in the study location. The approach of using application of weights and complex samples was an added strength. Both factors ensured generalizability and comparability to previous similar studies (12,28).

Our study had some limitations. First, the cross-sectional study design made it impossible to establish causality between independent and dependent variables through the demonstration of the time-sequence criterion. Second, all data were based on self-reports, possibly leading to under- or overreporting of behaviors, experiences, and perceptions and to recall bias. Although the extent of this under- or overreporting of behavior could not be determined, some GYTS questions have been analyzed and have demonstrated good test–retest reliability and validity (42). Third, this was a school-based design and was limited to students. It may, therefore, not be representative of all adolescents in Ibadan. However, in many countries, most people in the age group studied attend public, private, or technical schools. This holds true for our study area given that the net attendance ratio for Oyo state is about 70% (25), a value likely to be higher for Ibadan, the major urban area and capital city. We found a differential nonresponse rate between public and private schools at the school level, 0% and 33%, respectively. Although this may have altered the sample representativeness, we believe that this effect was minimal because the population of public-school students normally far outweighs that of private schools.

Our study provides information about prevalence of tobacco use and associated factors among in-school adolescents in Ibadan, Nigeria, and confirms that tobacco use was low but was associated with peer influence, access to cigarettes, tobacco use misperceptions, exposure to SHS, and protobacco advertising. Policy makers need to consider implementing an antitobacco campaign that uses a peer education strategy among adolescents along with enforcement of comprehensive bans on protobacco advertising and public smoking. A more comprehensive nationwide survey and maintenance of continuous surveillance is needed.

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Acknowledgments

We acknowledge funding from the Centers for Disease Control and Prevention (CDC) through the African Field Epidemiology Network (AFENET) in support of the Advanced Nigeria Field Epidemiology Training Program (A-NFETP). This work was done in fulfilment of the requirements for the A-NFETP. We acknowledge the support of the Emerging Authors Program for Global Cardiovascular Disease Research, a mentorship collaboration consisting of the Lancet Commission on Hypertension Group, the CDC, Resolve to Save Lives (RTSL), the World Hypertension League, and the Training Programs in Epidemiology and Public Health Interventions Network. This initiative received support from Bloomberg Philanthropies and RTSL through a grant to the National Foundation for the Centers for Disease Control and Prevention. We also thank the participating schools, teachers, and students for their participation. We thank Cynthia H. Cassell, PhD, in the Division of Global Health Protection, Center for Global Health, CDC, for her thorough feedback on various drafts of this paper. The views expressed are the authors’ and do not reflect those of the CDC, AFENET, or Emerging Authors Program for Global Cardiovascular Disease Research. No copyrighted materials or tools were used in this article.

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Author Information

Corresponding Author: Ikenna Onoh, MBBS, MSc, Department of Emergency Preparedness and Response, Nigeria Centre for Disease Control, Plot 801, Ebitu Ukiwe Street, Jabi, Abuja, Nigeria (ikenna.onoh@ncdc.gov.ng).

Author Affiliations: ¹Nigeria Field Epidemiology and Laboratory Training Programme, Abuja, Nigeria. ²Nigeria Centre for Disease Control, Abuja, Nigeria. ³Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria. ⁴African Field Epidemiology Network, Abuja, Nigeria.

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References

1. Doll R, Peto R, Wheatley K, Gray R, Sutherland I. Mortality in relation to smoking: 40 years’ observations on male British doctors. BMJ 1994;309(6959):901–11. PubMed doi:10.1136/bmj.309.6959.901
2. Institute for Health Metrics and Evaluation. GBD Compare Tool: findings from the Global Burden of Disease Study, 2017; 2018. Accessed February 18, 2020. https://vizhub.healthdata.org/gbd-compare/
3. Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006;3(11):e442. PubMed doi:10.1371/journal.pmed.0030442
4. Drope J. Tobacco control in Africa: people, politics and policies. Anthem Press & International Development Research Centre; 2011.
5. Sala-i-martin X, Pinkovskiy M. African poverty is falling . . . much faster than you think. Published February 2010. Accessed February 18, 2020. https://www.nber.org/system/files/working_papers/w15775/w15775.pdf
6. Lee S, Ling PM, Glantz SA. The vector of the tobacco epidemic: tobacco industry practices in low and middle-income countries. Cancer Causes Control. 2012;23(0 1) (suppl 1):117–129. PubMed doi:10.1007/s10552-012-9914-0
7. Network of African Science Academies. Preventing a tobacco epidemic in Africa: a call for effective action to support health, social, and economic development; 2014.
8. U.S. Department of Health and Human Services. Preventing tobacco use among youth and young adults: a report of the Surgeon General; 2012. https://www.ncbi.nlm.nih.gov/books/NBK99237/
9. Drope J, Schluger N, Cahn Z, Drope J, Hamill S, Islami F, et al. . The tobacco atlas: youth. Last updated 2021. Accessed February 19, 2020. https://tobaccoatlas.org/topic/youth/
10. World Health Organisation (WHO). WHO Global Report on Trends in Prevalence of Tobacco Use 2000–2025, 3rd edition; Published December 18, 2019. Accessed March 15, 2023 https://www.who.int/publications/i/item/who-global-report-on-trends-in-prevalence-of-tobacco-use-2000-2025-third-edition
11. Breslau N, Peterson EL. Smoking cessation in young adults: age at initiation of cigarette smoking and other suspected influences. Am J Public Health 1996;86(2):214–20. PubMed doi:10.2105/AJPH.86.2.214
12. Itanyi IU, Onwasigwe CN, McIntosh S, Bruno T, Ossip D, Nwobi EA, et al. . Disparities in tobacco use by adolescents in southeast, Nigeria using Global Youth Tobacco Survey (GYTS) approach. BMC Public Health 2018;18(1):317. PubMed doi:10.1186/s12889-018-5231-1
13. World Health Organisation (WHO). World No Tobacco Day 2008 : Tobacco-Free Youth (Break the Tobacco Marketing Net); Published 2008. Updated 2023. Accessed March 15, 2023. https://www.emro.who.int/tfi-campaigns/2008/index.html
14. US Department of Health and Human Services. The health consequences of involuntary exposure to tobacco smoke: a report of the Surgeon General; 2006. Accessed February 18, 2020. https://www.ncbi.nlm.nih.gov/books/NBK44324/
15. US Department of Health and Human Services. The health consequences of smoking — 50 years of progress: a report of the Surgeon General; 2014. Accessed February 20, 2020. https://www.ncbi.nlm.nih.gov/books/NBK179276/
16. World Health Organisation (WHO). WHO framework convention on tobacco control; Published 2003; updated reprint 2004, 2005. Accessed January 08, 2020. https://apps.who.int/iris/rest/bitstreams/50793/retrieve
17. Global Youth Tobacco Survey Collaborative Group. Tobacco use among youth: a cross country comparison. Tob Control 2002;11(3):252–70. PubMed doi:10.1136/tc.11.3.252
18. Global Youth Tobacco Survey Collaborative Group. Global Youth Tobacco Survey (GYTS): Core Questionnaire with Optional Questions, Version 1.2. Published online 2014. Accessed March 11, 2020. https://www.paho.org/hq/dmdocuments/2017/1-GYTS-CoreQuestionnairewithOptionalQuestions-v1.2-Nov2014.pdf
19. National Bureau of Statistics. Demographic Statistics Bulletin Nigeria 2017. Accessed February 18, 2020. https://nigerianstat.gov.ng/elibrary/read/775
20. Drope J, Schluger NW, Cahn Z, et al. . Tobacco atlas factsheet: Nigeria. Accessed December 29, 2019. https://tobaccoatlas.org/country/nigeria/
21. Nwhator SO. Nigeria’s costly complacency and the global tobacco epidemic. J Public Health Policy 2012;33(1):16–33. PubMed doi:10.1057/jphp.2011.58
22. Federal Republic of Nigeria. National Tobacco Control Act, 2015. Accessed January 8, 2020. https://d3vqfzrrx1ccvd.cloudfront.net/uploads/legislation/Nigeria/Nigeria-TCA-national.pdf
23. Ekanem I-OA. Global Youth Tobacco Survey report for Nigeria; 2008. Accessed December 20, 2019. https://untobaccocontrol.org/impldb/wp-content/uploads/nigeria_2018_annex-3_GYTS_report_2008.pdf
24. Central Intelligence Agency. The world factbook: Nigeria. Published 2020. Accessed August 12, 2020. https://www.cia.gov/the-world-factbook/countries/nigeria/
25. National Population Commission. Nigeria Demographic and Health Survey, 2018. Accessed February 11, 2021. Published October 2019. https://www.dhsprogram.com/pubs/pdf/FR359/FR359.pdf
26. Kirkwood BR, Sterne JAC. Essential Medical Statistics. Second edition. Blackwell Science Ltd; 2003.
27. Global Youth Tobacco Survey Collaborative Group. Global Youth Tobacco Survey (GYTS): sample design and weights, version 1.1. 2014. Accessed March 11, 2020. https://www.paho.org/hq/dmdocuments/2017/2-GYTS-SampleDesignandWeights-v1.1-Aug2014.pdf
28. Ministry of Health Tobacco Control Unit. Global Youth Tobacco Survey (GYTS) factsheet: Kenya 2013. 2013. Accessed June 05, 2020. https://nccd.cdc.gov/gtssdatasurveyresources/Ancillary/DownloadAttachment.aspx?ID=1277
29. Federal Ministry of Health. GATS: Nigeria. Global Adult Tobacco Survey: Country Report 2012. Accessed July 15, 2019. https://www.nigerianstat.gov.ng/pdfuploads/GATS_Nigeria_Country_Rpt_2012.pdf
30. Department of Health Philippines. Global Youth Tobacco Survey (GYTS) Philippines, 2015: country report. 2015. Accessed June 05, 2020. https://doh.gov.ph/sites/default/files/publications/FinalGYTS_CountryReport.pdf
31. World Health Organization. WHO report on the global tobacco epidemic, 2019: offer help to quit tobacco use. 2019. Accessed June 13, 2020. https://apps.who.int/iris/rest/bitstreams/1239531/retrieve
32. World Health Organization. WHO Framework Convention on Tobacco Control. Protocol to eliminate illicit trade in tobacco products. 2013. Accessed June 13, 2020. https://apps.who.int/iris/rest/bitstreams/284810/retrieve
33. Ministry of Social Affairs and Health Finland. Global Youth Tobacco Survey: factsheet, Finland 2012. 2014. Last updated October 6, 2015. Accessed June 05, 2020 https://nccd.cdc.gov/GTSSDataSurveyResources/Ancillary/DownloadAttachment.aspx?ID=1301
34. American Cancer Society; Vital Strategies. The tobacco atlas, 6th edition. Drope J, Schluger NW, editors. 2018. Accessed March 15, 2023. http://www.biblioteca.cij.gob.mx/Archivos/Materiales_de_consulta/Drogas_de_Abuso/Articulos/TobaccoAtlas.pdf
35. Odukoya OO, Odeyemi KA, Oyeyemi AS, Upadhyay RP. Determinants of smoking initiation and susceptibility to future smoking among school-going adolescents in Lagos State, Nigeria. Asian Pac J Cancer Prev 2013;14(3):1747–53. PubMed doi:10.7314/APJCP.2013.14.3.1747
36. Rudatsikira E, Abdo A, Muula AS. Prevalence and determinants of adolescent tobacco smoking in Addis Ababa, Ethiopia. BMC Public Health 2007;7(176):176. PubMed doi:10.1186/1471-2458-7-176
37. Wellman RJ, Dugas EN, Dutczak H, O’Loughlin EK, Datta GD, Lauzon B, et al. . Predictors of the onset of cigarette smoking: a systematic review of longitudinal population-based studies in youth. Am J Prev Med 2016;51(5):767–78. PubMed doi:10.1016/j.amepre.2016.04.003
38. Zollo P. Wise up to teens: insights into marketing and advertising to teenagers. New Strategist Publications, Inc; 1995.
39. Cummings KM, Morley CP, Horan JK, Steger C, Leavell NR. Marketing to America’s youth: evidence from corporate documents. Tob Control 2002;11(Suppl 1):I5–17. PubMed doi:10.1136/tc.11.suppl_1.i5
40. Xi B, Liang Y, Liu Y, Yan Y, Zhao M, Ma C, et al. . Tobacco use and second-hand smoke exposure in young adolescents aged 12–15 years: data from 68 low-income and middle-income countries. Lancet Glob Health 2016;4(11):e795–e805. PubMed doi:10.1016/S2214-109X(16)30187-5
41. Wellman RJ, Sugarman DB, DiFranza JR, Winickoff JP. The extent to which tobacco marketing and tobacco use in films contribute to children’s use of tobacco: a meta-analysis. Arch Pediatr Adolesc Med 2006;160(12):1285–96. PubMed doi:10.1001/archpedi.160.12.1285
42. Brener ND, Kann L, McManus T, Kinchen SA, Sundberg EC, Ross JG. Reliability of the 1999 Youth Risk Behavior Survey Questionnaire. J Adolesc Health 2002;31(4):336–42. PubMed doi:10.1016/S1054-139X(02)00339-7

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Tables

Abbreviations: —, not applicable; JS, junior secondary school; SS, senior secondary school.
^a The lowest administrative level of government.

^a The lowest administrative level of government.

Abbreviations: —, not applicable; aOR, adjusted odds ratio.
^a P value calculated by adjusted logistic regression; significant at P <.05.

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