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The impact of peer pressure on cigarette smoking among high school and university students in Ethiopia: A systemic review and meta-analysis

Roles Conceptualization, Data curation, Methodology, Software, Writing – review & editing

* E-mail: [email protected]

Affiliation College of Health Sciences, Debre Markos University, Debre Markos, Ethiopia

Roles Formal analysis, Resources, Supervision

Roles Data curation, Formal analysis, Investigation, Methodology, Validation

Roles Data curation, Formal analysis, Project administration, Software, Supervision

Roles Formal analysis, Visualization, Writing – original draft

Roles Data curation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Nursing, College of Nursing, University of Saskatchewan, Regina, Canada

Roles Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Validation, Visualization

Roles Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

Roles Data curation, Investigation, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing

Roles Investigation, Project administration, Software, Supervision, Validation, Writing – review & editing

Roles Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Roles Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Roles Methodology, Supervision, Writing – review & editing

Affiliations Colleges of Nursing, University of Saskatchewan, Saskatoon, Canada, School of Life Sciences and Bioengineering, Nelson Mandela African Institute of Science and Technology, Arusha City, Tanzania

Roles Methodology, Software, Supervision, Visualization, Writing – original draft, Writing – review & editing

Affiliations School of Science and Health, Western Sydney University, Penrith, NSW, Australia, Translational Health Research Institute, Western Sydney University, Penrith, NSW, Australia, Discipline of Child and Adolescent Health, Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia, Oral Health Services, Sydney Local Health District and Sydney Dental Hospital, NSW Health, Surry Hills, NSW, Australia

• Cheru Tesema Leshargie, 
• Animut Alebel, 
• Getiye Dejenu Kibret, 
• Molla Yigzaw Birhanu, 
• Henok Mulugeta, 
• Patricia Malloy, 
• Fasil Wagnew, 
• Atsede Alle Ewunetie, 
• Daniel Bekele Ketema, 

• Published: October 11, 2019
• https://doi.org/10.1371/journal.pone.0222572
• Reader Comments

Cigarettes and their by-products (i.e., smoke; ash) are a complex, dynamic, and reactive mixture of around 5,000 chemicals. Cigarette smoking potentially harms nearly every organ of the human body, causes innumerable diseases, and impacts the health of smokers and those interacting with the smokers. Smoking brings greater health problems in the long-term like increased risk of stroke and brain damage. For students, peer pressure is one of the key factors contributing to cigarette smoking. Therefore, this systematic review and meta-analysis assessed the impact of peer pressure on cigarette smoking among high school and university students in Ethiopia.

An extensive search of key databases including Cochrane Library, PubMed, Google Scholar, Hinari, Embase and Science Direct was conducted to identify and access articles published on the prevalence of cigarette smoking by high school and university students in Ethiopia. The search period for articles was conducted from 21 st September, 2018 to 25 th December 25, 2018. All necessary data were extracted using a standardized data extraction checklist. Quality and risk of bias of studies were assessed using standardized tools. Heterogeneity between the included studies was assessed using Cochrane Q-test statistic and I 2 test. To estimate the pooled prevalence of cigarette smoking, a random effects model was fitted. The impact of peer pressure on cigarette smoking was determined and was reported in Odds Ratio (OR) with 95% Confidence Interval (CI). Meta-analysis was conducted using Stata software.

From 175 searched articles, 19 studies fulfilled the eligibility criteria and were included in this study. The pooled prevalence of cigarette smoking among Ethiopian high school and university students was 15.9% (95% CI: 12.21, 19.63). Slightly higher prevalence of cigarette smoking was noted among university students [17.35% (95% CI: 13.21, 21.49)] as compared to high school students [12.77% (95% CI: 6.72%, 18.82%)]. The current aggregated meta-analysis revealed that peer pressure had a significant influence on cigarette smoking (OR: 2.68 (95% CI: 2.37, 3.03).

More than one sixth of the high school and university students in Ethiopia smoke cigarette. Students who had peer pressure from their friends were more likely to smoke cigarette. Therefore, school-based intervention programs are needed to reduce the high prevalence of cigarette smoking among students in Ethiopia.

Citation: Leshargie CT, Alebel A, Kibret GD, Birhanu MY, Mulugeta H, Malloy P, et al. (2019) The impact of peer pressure on cigarette smoking among high school and university students in Ethiopia: A systemic review and meta-analysis. PLoS ONE 14(10): e0222572. https://doi.org/10.1371/journal.pone.0222572

Editor: Wisit Cheungpasitporn, University of Mississippi Medical Center, UNITED STATES

Received: March 15, 2019; Accepted: September 3, 2019; Published: October 11, 2019

Copyright: © 2019 Leshargie et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: CI, Confidence Interval; HIV, Human Immune Deficiency Virus; OR, Odd Ration; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; SE, Standard Error; SNNPR, South Nation and Nationalities People of the Region; RR, Relative Risk; WHO, World Health Organization

Introduction

Smoking cigarettes yields a complex, dynamic and reactive mixture of around 5,000 chemicals [ 1 – 3 ]. Globally, it is one of the leading preventable causes of respiratory tract complications, disability, and early deaths related to complications [ 4 – 7 ]. It accounts for six of the eight leading causes of morbidity and mortality [ 5 ]. Essentially, it is a legal drug that kills many of its users when used exactly as intended by manufacturers. Currently, the World Health Organization (WHO) estimates that the use of both smoking and smokeless tobacco account for around 6 million deaths worldwide annually, of which 600,000 deaths were among non-smokers due to exposure to the smoke [ 8 ]. More than 30% of world’s adult population are consumers of tobacco, which leads to a warning that a billion people will die of adverse health effects related to the tobacco epidemic within the 21st century unless effective preventative measures are undertaken [ 3 ].

Smoking affects almost every organ in the human body (such as circulatory, respiratory, gastrointestinal and musculoskeletal systems), increases the risk for several diseases, and reduces the health of smokers in general [ 9 , 10 ]. The key effect of smoking cigarettes is primarily on the lungs with approximately 85% of chronic obstructive pulmonary disease (COPD) and lung cancer and about 33% of other cancers (i.e., esophagus, oral cavity, uterus, stomach, and pancreas) related to smoking [ 9 – 11 ].

Normal adolescent developmental stage is affected by high level of peer pressure that can influence risk-taking behaviors including substance use [ 12 ]. Globally, especially in low- and middle-income countries, an estimated 80% of the one billion adolescent smokers are suffering from tobacco-related morbidity and mortality [ 7 ]. Cigarette smoking negatively influences the physical and mental health of an individual [ 13 ]. This is particularly true for high school and university students who already face major health challenges such as stress [ 14 ]. Smoking is also associated with poor educational performance, high-risk drinking behavior, illegal drug use, and high-risk sexual behaviors [ 14 , 15 ]. Peer pressure is widely recognized as a crucial factor affecting young people's early experimentation with tobacco and their willingness to continue smoking [ 16 ]. Several students attending higher education institutions practice cigarette smoking for several reasons, such as a way to cope with stress [ 17 ]. Factors that contribute to the continued use of tobacco include being male, drinking alcohol, having a friend who drinks alcohol, having a friend who smokes, having family members who smoke and being older in age, to mention some [ 18 ].

In sub-Saharan Africa, the prevalence of smoking is increasing and is projected to continue to increase [ 19 , 20 ]. The current data in the region reveals substantial variation in smoking rates among countries ranging from 1.8% in Zambia to 25.8% in Sierra Leone [ 21 ]. In Ethiopia, cigarette smoking is among one of the most commonly used substances, which leads to addiction [ 22 ]. It has deleterious effects on the health of the young users, significantly reduces academic performance in students and increases risk of contracting HIV and other sexually transmitted diseases. Several primary studies on the prevalence and associated factors of cigarette smoking among high school and university students have been conducted in Ethiopia [ 23 – 37 ]. According to earlier reviews of the literature, prevalence of smoking in Ethiopia ranges from 2.99% in Addis Ababa [ 38 ] to 28.6% in Hawassa and Jima University [ 30 ]. Therefore, this systematic review and meta-analysis aimed to review the pooled prevalence of cigarette smoking among high school and university students in Ethiopia and the impact of peer pressure on cigarette smoking among high school and university students in Ethiopia.

Method and materials

This systematic review is based on the Preferred Reporting Items of Systematic Reviews and Meta-Analysis (PRISMA) checklist guidelines to ensure scientific rigor [ 39 ] ( S1 Table ). Prospective registration of systematic review and meta-analysis promotes transparency, helps reduce potential for bias, and improves review’s credibility. However, this meta-analysis and systematic review was not registered on the prosperous, and we have acknowledged this gap in the limitation section.

This systematic review and meta-analysis reports data from Ethiopia. Ethiopia is located in the north-eastern part of the African continent or what is known as the “Horn of Africa”. The country is divided into nine regional states and two administrative cities [ 40 ] containing a total of 108,386,391 million population with a national density of 94 people per square kilometer, 2019 [ 41 ]. Ethiopia shares land borders with five countries: Sudan , Somalia , Djibouti , Eritrea , and Kenya [ 42 ].

Inclusion and exclusion criteria

Eligibility criteria..

This systematic review and meta-analysis included studies only conducted in Ethiopia that assessed the prevalence of cigarette smoking. Published articles were reviewed and rated for inclusion. Full articles were retrieved if a specific outcome of interest (smoking status) was defined. This review included all observational study designs (cross-sectional studies, case-control studies, and cohort studies). However, case reports or case series, duplicate reports, and inconsistent outcome measures were excluded. Moreover, we excluded articles that were published in a language other than English. Documents that were not accessible after contacting the principal investigator three times by email were also excluded. Articles that reported measures other than Relative Risk (RR) or equivalent values, or from which an Odds Ratio (OR) could not be calculated were also excluded from consideration, The eligibility criteria for each individual article were checked by three authors independently (CT, AA1, and AA2). If there was a disagreement between the two authors, a third person (UGM) resolved the disagreement. All reviewers came together in person and discussed the assessment results.

Information sources

This systematic review and meta-analysis were conducted by considering all the available studies (both published and open grey reports), governmental and other stakeholder annual reports, and national surveys on children and adolescents which have data on cigarette smoking among high school and university students in Ethiopia. An extensive search was done from the following international databases, including Cochrane Library, PubMed, Google Scholar, Hinari , Embase, CINAHL, Web of Science, and Science Direct to access articles conducted on the prevalence of smoking cigarette. The following keywords “prevalence”, ("cigarette smoking" OR ("cigarette"[All Fields] AND "smoking"[All Fields]) OR "cigarette smoking"[All Fields]) AND substance[All Fields]) AND (high[All Fields] AND ("schools"[MeSH Terms] OR "schools"[All Fields] OR "school"[All Fields]) AND ("universities"[MeSH Terms] OR "universities"[All Fields] OR "university"[All Fields])) AND ("students"[MeSH Terms] OR "students"[All Fields]) AND ("Ethiopia"[MeSH Terms] OR "Ethiopia"[All Fields]) were used to obtain published articles. Boolean operators particularly pairing aspects of “OR” or “AND” were used as search terms to separate articles. The search for all articles was conducted from 21 st September, 2018 to 25 th December, 2018 ( S2 Table ).

This systematic review and meta-analysis had two outcomes. The first outcome was the pooled prevalence of cigarette smoking among high school and university students in Ethiopia, which was calculated by dividing the number of smokers to the total students (sample size) multiplied by 100. The second outcome was the impact of peer pressure on cigarette smoking practice. We adjusted the effect size into Odd Ratio (OR) since all the studies were cross sectional and the appropriate effect size estimate for cross sectional design is OR to estimate the impact of peer pressure on cigarette smoking.

Data extraction

The necessary data (primary author, publication year, region, study design, sample size, prevalence of cigarette smoking) were extracted from the eligible articles by two authors (CT, AA and AA1) independently using prepiloted data extraction format prepared in Microsoft ™ Excel spreadsheet ( S3 Table ). Any disagreements between the three reviewers in the review process were discussed with the three reviewer team members (GD, DB and PM) until consensus was reached. Moreover, the data of kappa of agreement during the systematic searches was also used to solve the disagreements among two independent reviewers (CT and AA4). The kappa agreement was interpreted as less than chance agreement if less than 0, slight agreement if 0.01–0.20, fair agreement if 0.21–0.40, moderate agreement if 0.41–0.60, substantial agreement if 0.61–0.80 and moderate agreement if the kappa was 0.81–0.99 [ 43 ].

The four authors (CT, FW, MA and AA1) also independently extracted data on the association of cigarette smoking and peer pressure. If studies did not report OR, RR, or equivalent measures, raw data were screened to determine whether OR could be calculated. When the studies reported both the crude OR/RRs and the adjusted OR/RRs, the adjusted figures were extracted.

Quality assessment of the included studies

We assessed the quality of the included studies according to the Newcastle-Ottawa Scale (NOS) [ 44 ] ( S4 Table ). The NOS has three main domains and uses a star-based grading system with each study scoring a maximum of 10 stars. The first domain focuses on the methodological quality of the study (sample size, response rate, and sampling technique) with the possibility of a five-star grading (1 = poor to 5 = excellent). The second domain of the tool deals with the comparability of the study cases or cohorts, with the possibility of two stars. The last domain deals with the outcomes and statistical analysis of the study with a possibility of three stars. Three authors (MA, UGM, and DB) independently assessed the quality of each included study using the NOS. Any disagreement between the three authors was resolved by requesting other two authors (MY and PP) to independently assess the methodological quality to reach a consensus. Finally, studies with stars of ≥ 7 out of 10 were considered to be of a high quality [ 45 ]. Moreover, we assessed the quality of each included articles using National Institutes of Health (NIH) ( S5 Table ) which is a more detail tool on quality assessment than NOS. The tool has 14 criteria to assess the article independently with a response of “Yes, No and Not Applicable”. Articles with NIH assessment result of 85% and more (that means number of articles with yes divided by total criteria minus not applicable) were considered as good quality.

Risk of bias

For each included study, the risk of bias was assessed independently by two authors (UGM and CT). Risk of bias assessment was carried out using Holly 2012 tool which contain 10 recommended criteria for the internal and external validity tool [ 46 ]. This tool includes: representation of the population, sampling frame, methods of participants’ selection, non-response bias, data collection directly from subjects, acceptability of case definition, reliability and validity of study tools, mode of data collection, length of prevalence period; and appropriateness of numerator and denominator. Each item was classified as low and high risk of bias. Unclear assessment was classified as high risk of bias. The overall score of the risk of bias was then categorized according to the number of high risk item scores for bias per study: low (≤ 2), moderate (3–4), and high (≥ 5) ( S6 Table ).

Statistical data analysis

Standard error for all included studies was computed using the binomial distribution formula. Heterogeneity across studies were assessed by determining the p-values of Cochrane Q-test and I 2 -test statistics [ 47 ]. For meta-analysis result with significant heterogeneity, univariate meta-regression was used to assess the source of heterogeneity across each study. A funnel plot was also used for visual assessment of the publication bias. Asymmetry of the funnel plot is an indicator of potential publication bias. Furthermore, Egger’s test was used to determine if there was significant publication bias, and a p -value less than 0.10 was considered to indicate the presence of significant publication bias [ 48 ]. We selected Egger`s test to assess the publication bias because, the value of Egger`s test is more specific than Begg`s test [ 49 , 50 ]. We conducted the log relative risk to assess the effect of peer pressure on students’ cigarette smoking status. Furthermore, sensitivity analysis using a random effects model was performed to assess the influence of a single study on the pooled prevalence estimates. Subgroup analysis was used to minimize the random variations between the point estimates of the primary study subgroup, and analysis was done based on study settings (i.e., institution). Univariable meta-regression analysis was also conducted with year of publication and the outcome variable. All data manipulation and statistical analysis were performed using Stata ™ software (Version 14; Stata Corp, College Station, TX).

The electronic database search identified a total of 179 published articles. Of these, 121 duplicate articles were removed. Furthermore, 28 articles were removed after reviewing the titles and the abstract as they were not relevant to the focus of the review. Finally, one article was excluded due to inaccessibility of the full text despite three requests to the primary author on data, and 10 articles were excluded after reviewing their full text. Finally, 19 articles met all the prior criteria and were included in this analysis ( Fig 1 ).

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0222572.g001

Overview of the original included articles

All of the 19 articles included in this study were published between 1999 to 2017 in peer-reviewed journals. A total of 16,486 study participants were included in this systematic review and meta-analysis. The smallest sample size was 155 from a study conducted at Bahir Dar University [ 36 ], and the largest sample size was 1,984 in a study conducted in Gondar Medical College, Amhara Region [ 34 ]. All included studies were cross-sectional in design. The characteristics of the studies included in this review are described in ( Table 1 ) .

https://doi.org/10.1371/journal.pone.0222572.t001

Quality assessment result of the included articles

The qualities of individual articles were assessed using different tools; namely NOS and NIH quality assessment tools. Accordingly, NOS assessment result all articles had good quality using the NOS criteria. However, when assessed using NIH quality assessment tool, 1 (5.3%) study [ 36 ] was categorized as poor and the rest [ 11 , 15 , 23 – 35 , 37 , 38 , 51 ] were categorized as good quality ( S5 Table ).

Kappa agreement

Disagreements between the two reviewers during data extraction process were assessed using the Kappa agreement. Therefore, a = 9 and b = 2 represent the number of times the two reviewers agreed while c = 1 and d = 7 represent the number of times the two reviewers disagree. If there are no disagreements, b and c would be zero, and the reviewers agreement (po) is 1, or 100%. If there are no agreements, a and d would be zero, and the reviewers agreement (po) is 0. Interobserver agreement was 68% that indicate a substantial agreement between the two main reviewers who extracted data.

Risk of bias was performed for each included study using the risk of bias assessment tool that includes ten different items [ 46 ]. From the 19 included studies, the risk of bias summary assessment revealed that 94.7% of the included studies had a low risk of bias [ 15 , 23 – 35 , 37 , 38 , 51 ] while only one (5.3%) of the included studies had a moderate risk of bias [ 36 ].

Prevalence of cigarette smoking

The overall pooled prevalence of cigarette smoking in Ethiopia using the 19 studies was 16.31% (95% CI: 12.17, 20.45). A random-effects model was used because of the significant heterogeneity ( I 2 = 98.1%, p-value <0.001) across the studies ( Fig 2 ). Additionally, univariate meta-regression analysis was conducted to identify possible sources of heterogeneity. The different covariates included in the analysis were publication year and sample size. However, none of these variables were found to be statistically significant.

https://doi.org/10.1371/journal.pone.0222572.g002

The existence of publication bias was assured by funnel plot asymmetry. The funnel plot graph indicates that there is a significant variability within the findings of the 19 individual primary articles included in this meta-analysis ( Fig 3 ). The publication bias checked by objective measurement namely Egger’s tests also showed a statistically significant publication bias ( Egger's test p-value = 0 . 001 ). To handle the observed publication bias, we performed the trim and fill analysis, which is a nonparametric methods for estimating the number of missing studies that might exist and helps in reducing and adjusting publication bias in meta-analysis.

https://doi.org/10.1371/journal.pone.0222572.g003

Assessment of heterogeneity

We used I 2 statistics to investigate the presence of variation across the included studies. Accordingly, the result of I 2 statistics using a random effects model revealed a significant heterogeneity across the included studies ((I 2 = 98.1%, p-value <0 . 001 ).

Subgroup analysis

The findings from the subgroup analysis showed that the highest and lowest cigarette smoking was observed among university students 17.35% (95% CI: 12.97, 22.16) and high school students 13.76% (95% CI: 7.24, 20.27), respectively ( Fig 4 ).

https://doi.org/10.1371/journal.pone.0222572.g004

Similarly, the regional subgroup analysis result revealed the pooled prevalence of smoking from highest to lowest was [20.11% (95% CI: 11.39, 28.84)] in Ethio-Somalia and Harari region, [18.96% (95% CI: -0.03, 38.01)] in Tigray region, [17.35% (95% CI: 13.21, 21.49)] in South Nation Nationality and People of Ethiopia (SNNPE), [15.34% (95% CI: 10.84, 19.83)] in Amhara region, [14.98% (95% CI: 7.37, 22.55)] in Oromia region, and [5.9% (95% CI: 0.02, 11.79)] in Addis Ababa region ( Fig 5 ).

https://doi.org/10.1371/journal.pone.0222572.g005

The linear trend of cigarette smoking status of students in Ethiopia

The cumulative univariate meta-analysis on cigarette smoking status among high school and university with the year of 1984–2017 was performed. The result from cumulative univariate meta-analysis showed the trend in prevalence estimates of cigarette smoking status among high school and university over time. The finding revealed that there is more or less constant trend ( Fig 6 ).

https://doi.org/10.1371/journal.pone.0222572.g006

The univariate meta-regression using bubble plot was also performed. The bubble plot figure indicates that the trend was slight increment ( Fig 7 ).

https://doi.org/10.1371/journal.pone.0222572.g007

The effect of peer pressure on cigarette smoking status

Five of the 19 included studies reported the effect of peer pressure on cigarette smoking. From this, three studies [ 11 , 30 , 37 ] showed a positive effect of peer pressure on cigarette smoking, while the other two studies [ 31 , 51 ] showed no relationship between peer pressure and cigarette smoking. However, the aggregated meta-analysis revealed a higher odds of cigarette smoking among students who experienced peer pressure than those who didn’t (OR: 2.68, 95% CI: 2.37, 3.03) ( Fig 8 ).

https://doi.org/10.1371/journal.pone.0222572.g008

Cigarette smoking has major health and social consequences, and it reduces the educational performance of students [ 52 , 53 ]. This systematic review and meta-analysis, therefore, was conducted to assess the pooled prevalence of cigarette smoking and its association with peer pressure among high school and university students in Ethiopia. Accordingly, the pooled prevalence of cigarette smoking among Ethiopian high school and university students was 15.92%. This finding is lower than a study conducted among students in South Africa which reported a prevalence of 16.9% [ 50 ]. Conversely, the current reported pooled prevalence of cigarette smoking was higher than a study conducted among government and private schools and college students in Bengaluru, India (12.8%) [ 54 ] and amongst university students in Iran (13.8%) [ 55 ].

In this review, the pooled prevalence of cigarette smoking was lower than a study finding observed among Kenyan secondary school students (38.6%) and Cameroon university students (93.1%) [ 56 , 57 ]. In addition, our finding was slightly lower than a study conducted among high school students in Shiraz- Iran (19.7%) [ 58 ]. This might be due to the difference between sample size and socio-demographic nature of the two study populations. There is also cultural variation among the study communities. Moreover, the higher prevalence of cigarette smoking in the current study could be due to the dominance of male participants as evidence suggests that males tend towards different types of substance abuse than females [ 59 , 60 ].

Similarly, the current pooled prevalence of cigarette smoking is also lower than a systematic review conducted in Africa [ 50 ] and the Middle East [ 61 ]. This variation might be due to the differences in the study period and sample size between these two studies. In addition, the previous review was conducted only among university students, while the current review included both high school and university students.

The current review also considered subgroup analysis to appreciate the variability or heterogenic characteristics of the included studies. Accordingly, a higher prevalence was observed among university students (17.35%) than high school students (12.77%). This could be because most high school students live with their families which may limit them from cigarette smoking because of parental control. Additionally, in most cases, students during their high school time live with families and that may not encourage smoking cigarette. On the contrary, when they join to the university, almost all students become independent of their family supervision. This independency and pressure from their friends increases the proportion of students who smokes cigarette [ 62 ]. Educational institutions can be a challenging environment and everyone copes with stress in different ways [ 17 ]. Moreover, as students enter to university, they start a new life away from their families in a different and strange environment which can contribute to their behavior or involvement in substance abuse like cigarette smoking [ 55 ]. Evidence also supports that as the level of education increase, the proportion of smoking increases [ 63 , 64 ].

A subgroup analysis by regions of the country also showed a higher prevalence of cigarette smoking among universities in other category (i.e., Harar region, Somalia region and Oromia region). This finding might be due to typical local practices of substances like cigarette and khat in these regions. Therefore, the government, school management, local communities and other concerned bodies need to implement school-based intervention programs in order to reduce the pooled prevalence of cigarette smoking.

Students who felt peer pressure were more likely to smoke cigarette than those who had no peer pressure. This finding was similar to a study conducted in Kenyan students and Shiraz- Iran [ 57 ] where peer pressure was found to have a significant (positive) effect on the likelihood of cigarette smoking [ 56 , 58 ]. Peer group pressure is widely known as a decisive factor which affects the early onset of experimentation with tobacco and the individual’s subsequent willingness to continue smoking [ 16 ]. Similarly, other systematic reviews state the most common factors influencing students’ smoking status was having smoker friends [ 55 , 65 ]. Therefore, the school management needs to implement youth association focusing on counseling and rehabilitation service for to seize students already practicing smoking and also those who are not practicing yet now.

Strengths and limitations of the study

This review has several strengths including: this review focus on the adolescent and young adult populations who are vulnerable to initiating substance use/abuse behaviors. In addition, this review rigorous adherence to the PRISMA checklist which improves its quality for the readers. Moreover, this finding will give an insight into developing a health promotion policy for the country. Whereas, on top of the above strength, this review has the following limitations: This review included studies that were published only in English language which may limit the number of studies that were reported in other languages. Moreover, the other limitation of this review was the risk of self-report bias introduced from the original studies included in the review. On top of these the protocol of this manuscript was not registered online before conducting it.

Conclusions

This systematic review and meta-analysis indicate that the prevalence of cigarette smoking among Ethiopian high school and university students was high. More than one sixth of the high school and university students smoke cigarettes. This higher cigarette smoking proportion of students was influenced by peer pressure. Variations were also observed in the prevalence of cigarette smoking by different regions in the country. Therefore, school-based intervention programs aimed at prevention of cigarette smoking is recommended. In particular, educational programs on how to resist and handle peer pressure are essential to prevent cigarette smoking among high school and university students in Ethiopia.

Supporting information

S1 table. prisma 2009 checklist..

https://doi.org/10.1371/journal.pone.0222572.s001

S2 Table. Searches for databases.

https://doi.org/10.1371/journal.pone.0222572.s002

S3 Table. Data extraction tools Smoke.

https://doi.org/10.1371/journal.pone.0222572.s003

S4 Table. Quality assessments.

https://doi.org/10.1371/journal.pone.0222572.s004

S5 Table. NIH quality assessments.

https://doi.org/10.1371/journal.pone.0222572.s005

S6 Table. Risk of bias for each study.

https://doi.org/10.1371/journal.pone.0222572.s006

Acknowledgments

The authors of this work would like to forward great and deepest gratitude for Debre Markos University for creating convenient environment and internet service. Furthermore, the authors would like also to forward special acknowledgement for authors of primary studies.

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• Published: 21 January 2021

The effects of tobacco control policies on global smoking prevalence

• Luisa S. Flor   ORCID: orcid.org/0000-0002-6888-512X 1 ,
• Marissa B. Reitsma 1 ,
• Vinay Gupta 1 ,
• Marie Ng   ORCID: orcid.org/0000-0001-8243-4096 2 &
• Emmanuela Gakidou   ORCID: orcid.org/0000-0002-8992-591X 1  

Nature Medicine volume  27 ,  pages 239–243 ( 2021 ) Cite this article

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Substantial global effort has been devoted to curtailing the tobacco epidemic over the past two decades, especially after the adoption of the Framework Convention on Tobacco Control 1 by the World Health Organization in 2003. In 2015, in recognition of the burden resulting from tobacco use, strengthened tobacco control was included as a global development target in the 2030 Agenda for Sustainable Development 2 . Here we show that comprehensive tobacco control policies—including smoking bans, health warnings, advertising bans and tobacco taxes—are effective in reducing smoking prevalence; amplified positive effects are seen when these policies are implemented simultaneously within a given country. We find that if all 155 countries included in our counterfactual analysis had adopted smoking bans, health warnings and advertising bans at the strictest level and raised cigarette prices to at least 7.73 international dollars in 2009, there would have been about 100 million fewer smokers in the world in 2017. These findings highlight the urgent need for countries to move toward an accelerated implementation of a set of strong tobacco control practices, thus curbing the burden of smoking-attributable diseases and deaths.

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Decades after its ill effects on human health were first documented, tobacco smoking remains one of the major global drivers of premature death and disability. In 2017, smoking was responsible for 7.1 (95% uncertainty interval (UI), 6.8–7.4) million deaths worldwide and 7.3% (95% UI, 6.8%–7.8%) of total disability-adjusted life years 3 . In addition to the health impacts, economic harms resulting from lost productivity and increased healthcare expenditures are also well-documented negative effects of tobacco use 4 , 5 . These consequences highlight the importance of strengthening tobacco control, a critical and timely step as countries work toward the 2030 Sustainable Development Goals 2 .

In 2003, the World Health Organization (WHO) led the development of the Framework Convention on Tobacco Control (FCTC), the first global health treaty intended to bolster tobacco use curtailment efforts among signatory member states 1 . Later, in 2008, to assist the implementation of tobacco control policies by countries, the WHO introduced the MPOWER package, an acronym representing six evidence-based control measures (Table 1 ) (ref. 6 ). While accelerated adoption of some of these demand reduction policies was observed among FCTC parties in the past decade 7 , many challenges remain to further decrease population-level tobacco use. Given the differing stages of the tobacco epidemic and tobacco control across countries, consolidating the evidence base on the effectiveness of policies in reducing smoking is necessary as countries plan on how to do better. In this study, we evaluated the association between varying levels of tobacco control measures and age- and sex-specific smoking prevalence using data from 175 countries and highlighted missed opportunities to decrease smoking rates by predicting the global smoking prevalence under alternative unrealized policy scenarios.

Despite the enhanced global commitment to control tobacco use, the pace of progress in reducing smoking prevalence has been heterogeneous across geographies, development status, sex and age 8 ; in 2017, there were still 1.1 billion smokers across the 195 countries and territories assessed by the Global Burden of Diseases, Injuries, and Risk Factors Study. Global smoking prevalence in 2017 among men and women aged 15 and older, 15–29 years, 30–49 years and 50 years and older are shown in Extended Data Figs. 1 , 2 , 3 and 4 , respectively. We found that, between 2009 and 2017, current smoking prevalence declined by 7.7% for men (36.3% (95% UI, 35.9–36.6%) to 33.5% (95% UI, 32.9–34.1%)) and by 15.2% for women globally (7.9% (95% UI, 7.8–8.1%) to 6.7% (95% UI, 6.5–6.9%)). The highest relative decreases were observed among men and women aged 15–29 years, at 10% and 20%, respectively. Conversely, prevalence decreased less intensively for those aged over 50, at 2% for men and 9.5% for women. While some countries have shown an important reduction in smoking prevalence between 2009 and 2017, such as Brazil, suggesting sustained progress in tobacco control, a handful of countries and territories have shown considerable increases in smoking rates among men (for example, Albania) and women (for example, Portugal) over this time period.

In an effort to counteract the harmful lifelong consequences of smoking, countries have, overall, implemented stronger demand reduction measures after the FCTC ratification. To assess national-level legislation quality, the WHO attributes a score to each of the MPOWER measures that ranges from 1 to 4 for the monitoring component (M) and 1–5 for the other components. A score of 1 represents no known data, while scores 2–5 characterize the overall strength of each measure, from the lowest level of achievement (weakest policy) to the highest level of achievement (strongest policy) 6 . Between 2008 and 2016, although very little progress was made in treatment provision (O) 7 , 9 , the share of the total population covered by best practice (score = 5) P, W and E measures increased (Fig. 1 ). Notably, however, a massive portion of the global population is still not covered by comprehensive laws. As an example, less than 15% of the global population is protected by strongly regulated tobacco advertising (E) and the number of people (2.1 billion) living in countries where none or very limited smoke-free policies (P) are in place (score = 2) is still nearly twice as high as the population (1.1 billion) living in locations with national bans on smoking in all public places (score = 5).

To assess national-level legislation quality, the WHO attributes a score to each MPOWER component that ranges from 1 to 5 for smoke-free (P), health warning (W) and advertising (E) policies. A score of 1 represents no known data or no recent data, while scores 2–5 characterize the overall strength of each policy, from 2 representing the lowest level of achievement (weakest policy), to 5 representing the highest level of achievement (strongest policy).

Source data

In terms of fiscal policies (R), the population-weighted average price, adjusted for inflation, of a pack of cigarettes across 175 countries with available data increased from I$3.10 (where I$ represents international dollars) in 2008 to I$5.38 in 2016. However, from an economic perspective, for prices to affect purchasing decisions, they need to be evaluated relative to income. The relative income price (RIP) of cigarettes is a measure of affordability that reflects, in this study, what proportion of the country-specific per capita gross domestic product (GDP) is needed to purchase half a pack of cigarettes a day for a year. Over time, cigarettes have become less affordable (RIP 2016 > RIP 2008) in about 75% of the analyzed countries, with relatively more affordable cigarettes concentrated across high-income countries.

Our adjusted analysis indicates that greater levels of achievement on key measures across the P, W and E policy categories and higher RIP values were significantly associated with reduced smoking prevalence from 2009 to 2017 (Table 2 ). Among men aged 15 and older, each 1-unit increment in achievement scores for smoking bans (P) was independently associated with a 1.1% (95% UI, −1.7 to −0.5, P  < 0.0001) decrease in smoking prevalence. Similarly, an increase of 1 point in W and E scores was associated with a decrease in prevalence of 2.1% (95% UI, −2.7 to −1.6, P  < 0.0001) and 1.9% (95% UI, −2.6 to −1.1, P  < 0.0001), respectively. Furthermore, a 10 percentage point increase in RIP was associated with a 9% (95% UI, −12.6 to −5.0, P  < 0.0001) decrease in overall smoking prevalence. Results were similar for men from other age ranges.

Among women, the magnitude of effect of different policy indicators varied across age groups. For those aged over 15, each 1-point increment in W and E scores was independently associated with an average reduction in prevalence of 3.6% (95% UI, −4.5 to −2.9, P  < 0.0001) and 1.9% (95% UI, −2.9 to −1.8, P  = 0.002), respectively, and these findings were similar across age groups. Smoking ban (P) scores were not associated with reduced prevalence among women aged 15–29 years or over 50 years. However, a 1-unit increase in P scores was associated with a 1.3% (95% UI, −2.3 to −0.2, P  = 0.016) decline in prevalence among women aged 30–49 years. Lastly, while a 10 percentage point increase in RIP lowered women smoking prevalence by 6% overall (95% UI, −10.0 to −2.0, P = 0.014), this finding was not statistically significant when examining reductions in prevalence among those aged 50 and older (Table 2 ).

If tobacco control had remained at the level it was in 2008 for all 155 countries (with non-missing policy indicators for both 2008 and 2016; Methods ) included in the counterfactual analysis, we estimate that smoking prevalence would have been even higher than the observed 2017 rates, with 23 million more male smokers and 8 million more female smokers (age ≥ 15) worldwide (Table 3 ). Out of the counterfactual scenarios explored, the greatest progress in reducing smoking prevalence would have been observed if a combination of higher prices—resulting in reduced affordability levels—and strictest P, W and E laws had been implemented by all countries, leading to lower smoking rates among men and women from all age groups and approximately 100 million fewer smokers across all countries (Table 3 ). Under this policy scenario, the greatest relative decrease in prevalence would have been seen among those aged 15–29 for both sexes, resulting in 26.6 and 6.5 million fewer young male and female smokers worldwide in 2017, respectively.

Our findings reaffirm that a wide spectrum of tobacco demand reduction policies has been effective in reducing smoking prevalence globally; however, it also indicates that even though much progress has been achieved, there is considerable room for improvement and efforts need to be strengthened and accelerated to achieve additional gains in global health. A growing body of research points to the effectiveness of tobacco control measures 10 , 11 , 12 ; however, this study covers the largest number of countries and years so far and reveals that the observed impact has varied by type of control policy and across sexes and age groups. In high-income countries, stronger tobacco control efforts are also associated with higher cessation ratios (that is, the ratio of former smokers divided by the number of ever-smokers (current and former smokers)) and decreases in cigarette consumption 13 , 14 .

Specifically, our results suggest that men are, in general, more responsive to tobacco control interventions compared to women. Notably, with prevalence rates for women being considerably low in many locations, variations over time are more difficult to detect; thus, attributing causes to changes in outcome can be challenging. Yet, there is already evidence that certain elements of tobacco control policies that play a role in reducing overall smoking can have limited impact among girls and women, particularly those of low socioeconomic status 15 . Possible explanations include the different value judgments attached to smoking among women with respect to maintaining social relationships, improving body image and hastening weight control 16 .

Tax and price increases are recognized as the most impactful tobacco control policy among the suite of options under the MPOWER framework 10 , 14 , 17 , particularly among adolescents and young adults 18 . Previous work has also demonstrated that women are less sensitive than men to cigarette tax increases in the USA 19 . Irrespective of these demographic differences, effective tax policy is underutilized and only six countries—Argentina, Chile, Cuba, Egypt, Palau and San Marino—had adopted cigarette taxes that corresponded to the WHO-prescribed level of 70% of the price of a full pack by 2017 (ref. 20 ). Cigarettes also remain highly affordable in many countries, particularly among high-income nations, an indication that affordability-based prescriptions to countries, instead of isolated taxes and prices reforms, are possibly more useful as a tobacco control target. In addition, banning sales of single cigarettes, restricting legal cross-border shopping and fighting illicit trade are required so that countries can fully experience the positive effect of strengthened fiscal policies.

Smoke-free policies, which restrict the opportunities to smoke and decrease the social acceptability of smoking 17 , also affect population groups differently. In general, women are less likely to smoke in public places, whereas men might be more frequently influenced by smoking bans in bars, restaurants, clubs and workplaces across the globe due to higher workforce participation rates 16 . In addition to leading to reduced overall smoking rates, as indicated in this study, implementing complete smoking bans (that is, all public places completely smoke-free) at a faster pace can also play an important role in minimizing the burden of smoking-attributable diseases and deaths among nonsmokers. In 2017 alone, 2.18% (95% UI, 1.8–2.7%) of all deaths were attributable to secondhand smoke globally, with the majority of the burden concentrated among women and children 21 .

Warning individuals about the harms of tobacco use increases knowledge about the health risks of smoking and promotes changes in smoking-related behaviors, while full advertising and promotion bans—implemented by less than 20% of countries in 2017 (ref. 20 )—are associated with decreased tobacco consumption and smoking initiation rates, particularly among youth 17 , 22 , 23 . Large and rotating pictorial graphic warnings are the most effective in attracting smokers’ attention but are lacking in countries with high numbers of smokers, such as China and the USA 20 . Adding best practice health warnings to unbranded packages seems to be an effective way of informing about the negative effects of smoking while also eliminating the tobacco industry’s marketing efforts of using cigarette packages to make these products more appealing, especially for women and young people who are now the prime targets of tobacco companies 24 , 25 .

While it is clear that strong implementation and enforcement are crucial to accelerating progress in reducing smoking and its burden globally, our heterogeneous results by type of policy and demographics highlight the challenges of a one-size-fits-all approach in terms of tobacco control. The differences identified illustrate the need to consider the stages 26 of the smoking epidemics among men and women and the state of tobacco control in each country to identify the most pressing needs and evaluate the way ahead. Smoking patterns are also influenced by economic, cultural and political determinants; thus, future efforts in assessing the effectiveness of tobacco control policies under these different circumstances are of value. As tobacco control measures have been more widely implemented, tobacco industry forces have expanded and threaten to delay or reverse global progress 27 . Therefore, closing loopholes through accelerated universal adoption of the comprehensive set of interventions included in MPOWER, guaranteeing that no one is left unprotected, is an urgent requirement as efforts toward achieving the Sustainable Development Goals by 2030 are intensified.

This was an ecological time series analysis that aimed to estimate the effect of four key demand reduction measures on smoking rates across 175 countries. Country-year-specific achievement scores for P, W and E measures and an affordability metric measured by RIP—to capture the impact of fiscal policy (R)—were included as predictors in the model. Although the WHO also calls for monitoring (M) and tobacco cessation (O) interventions, these were not evaluated. Monitoring tobacco use is not considered a demand reduction measure, while very little progress has been made in treatment provision over the last decade 7 , 9 . Further information on research design is available in the Life Sciences Reporting Summary linked to this paper.

Smoking outcome data

The dependent variable is represented by country-specific, age-standardized estimates of current tobacco smoking prevalence, defined as individuals who currently use any smoked tobacco product on a daily or occasional basis. Complete time series estimates of smoking prevalence from 2009 to 2017 for men and women aged 15–29, 30–49, 50 years and older and 15 years and older, were taken from the Global Burden of Disease (GBD) 2017 study.

The GBD is a scientific effort to quantify the comparative magnitude of health loss due to diseases, injuries and risk factors by age, sex and geography for specific points in time. While full details on the estimation process for smoking prevalence have been published elsewhere, we briefly describe the main analytical steps in this article 3 . First, 2,870 nationally representative surveys meeting the inclusion criteria were systematically identified and extracted. Since case definitions vary between surveys, for example, some surveys only ask about daily smoking as opposed to current smoking that includes both daily and occasional smokers, the extracted data were adjusted to the reference case definition using a linear regression fit on surveys reporting multiple case definitions. Next, for surveys with only tabulated data available, nonstandard age groups and data reported as both sexes combined were split using observed age and sex patterns. These preprocessing steps ensured that all data used in the modeling were comparable. Finally, spatiotemporal Gaussian process regression, a three-step modeling process used extensively in the GBD to estimate risk factor exposure, was used to estimate a complete time series for every country, age and sex. In the first step, estimates of tobacco consumption from supply-side data are incorporated to guide general levels and trends in prevalence estimates. In the second step, patterns observed in locations, age groups and years with smoking prevalence data are synthesized to improve the first-step estimates. This step is particularly important for countries and time periods with limited or no available prevalence data. The third step incorporates and quantifies uncertainty from sampling error, non-sampling error and the preprocessing data adjustments. For this analysis, the final age-specific estimates were age-standardized using the standard population based on GBD population estimates. Age standardization, while less important for the narrower age groups, ensured that the estimated effects of policies were not due to differences in population structure, either within or between countries.

Using GBD-modeled data is a strength of the study since nearly 3,000 surveys inform estimates and countries are not required to have complete survey coverage between 2009 and 2017 to be included in the analysis. Yet, it is important to note that these estimates have limitations. For example, in countries where a prevalence survey was not conducted after the enactment of a policy, modeled estimates may not reflect changes in prevalence resulting from that policy. Nonetheless, the prevalence estimates from the GBD used in this study are similar to those presented in the latest WHO report 28 , indicating the validity and consistency of said estimates.

MPOWER data

Summary indicators of country-specific achievements for each MPOWER measure are released by the WHO every two years and date back to 2007. Data from different iterations of the WHO Report on the Global Tobacco Epidemic (2008 6 , 2009 29 , 2011 30 , 2013 31 , 2015 32 and 2017 20 ) were downloaded from the WHO Tobacco Free Initiative website ( https://www.who.int/tobacco/about/en/ ). To assess the quality of national-level legislation, the WHO attributes a score to each MPOWER component that ranges from 1 to 4 for the monitoring (M) dimension and 1–5 for the other dimensions. A score of 1 represents no known data or no recent data, while scores 2–5 characterize the overall strength of each policy, from the lowest level of achievement (weakest policy) to the highest (strongest policy).

Specifically, smoke-free legislation (P) is assessed to determine whether smoke-free laws provide for a complete indoor smoke-free environment at all times in each of the respective places: healthcare facilities; educational facilities other than universities; universities; government facilities; indoor offices and workplaces not considered in any other category; restaurants or facilities that serve mostly food; cafes, pubs and bars or facilities that serve mostly beverages; and public transport. Achievement scores are then based on the number of places where indoor smoking is completely prohibited. Regarding health warning policies (W), the size of the warnings on both the front and back of the cigarette pack are averaged to calculate the percentage of the total pack surface area covered by the warning. This information is combined with seven best practice warning characteristics to construct policy scores for the W dimension. Finally, countries achievements in banning tobacco advertising, promotion and sponsorship (E) are assessed based on whether bans cover the following types of direct and indirect advertising: (1) direct: national television and radio; local magazines and newspapers; billboards and outdoor advertising; and point of sale (indoors); (2) indirect: free distribution of tobacco products in the mail or through other means; promotional discounts; nontobacco products identified with tobacco brand names; brand names of nontobacco products used or tobacco products; appearance of tobacco brands or products in television and/or films; and sponsorship.

P, W and E achievement scores, ranging from 2 to 5, were included as predictors into the model. The goal was to not only capture the effect of adopting policies at its highest levels but also assess the reduction in prevalence that could be achieved if countries moved into the expected direction in terms of implementing stronger measures over time. Additionally, having P, W and E scores separately, and not combined into a composite score, enabled us to capture the independent effect of different types of policies.

Although compliance is a critical factor in understanding policy effectiveness, the achievement scores incorporated in our main analysis reflect the adoption of legislation rather than degree of enforcement, representing a limitation of these indicators.

Prices in I$ for a 20-cigarette pack of the most sold brand in each of the 175 countries were also sourced from the WHO Tobacco Free Initiative website for all available years (2008, 2010, 2012, 2014 and 2016). I$ standardize prices across countries and also adjust for inflation across time. This information was used to construct an affordability metric that captures the impact of cigarette prices on smoking prevalence, considering the income level of each country.

More specifically, the RIP, calculated as the percentage of per capita GDP required to purchase one half pack of cigarettes a day over the course of a year, was computed for each available country and year. Per capita GDP estimates were drawn from the Institute for Health Metrics and Evaluation; the estimation process is detailed elsewhere 33 .

Given that the price data used in the analysis refer to the most sold brand of cigarettes only, it does not reflect the full range of prices of different types of tobacco products available in each location. This might particularly affect our power in detecting a strong effect in countries where other forms of tobacco are more popular.

Statistical analysis

Sex- and age-specific logit-transformed prevalence estimates from 2009 to 2017 were matched to one-year lagged achievement scores and RIP values using country and year identifiers 34 . The final sample consisted of 175 countries and was constrained to locations and years with non-missing indicators. A multiple linear mixed effects model fitted by restricted maximum likelihood was used to assess the independent effect of P, W and E scores and RIP values on the rates of current smoking. Specifically, a country random intercept and a country random slope on RIP were included to account for geographical heterogeneity and within-country correlation. The regression model takes the following general form:

where y c,t is the prevalence of current smoking in each country ( c ) and year ( t ), β 0 is the intercept for the model and β p , β w , β e and β r are the fixed effects for each of the policy predictors. \(\mathrm{P}_{c,\,t - 1},\,\mathrm{W}_{c,\,t - 1},\,\mathrm{E}_{c,\,t - 1}\) are the P, W and E scores and R c , t −1 is the RIP value for country c in year t  − 1. Finally, α c is the random intercept for country ( c ), while δ c represent the random slope for the country ( c ) to which the RIP value (R t − 1 ) belongs. Variance inflation factor values were calculated for all the predictor parameters to check for multicollinearity; the values found were low (<2) 35 . Bivariate models were also run and are shown in Extended Data Fig. 5 . The one-year lag introduced into the model may have led to an underestimation of effect sizes, particularly as many MPOWER policies require a greater period of time to be implemented effectively. However, due to the limited time range of our data (spanning eight years in total), introducing a longer lag period would have resulted in the loss of additional data points, thus further limiting our statistical power in detecting relevant associations between policies and smoking prevalence.

In addition to a joint model for smokers from both sexes, separate regressions were fitted for men and women and the four age groups (15–29, 30–49, ≥50 and ≥15 years old). To assess the validity of the mixed effects analyses, likelihood ratio tests comparing the models with random effects to the null models with only fixed effects were performed. Linear mixed models were fitted by maximum likelihood and t -tests used Satterthwaite approximations to degrees of freedom. P values were considered statistically significant if <0.05. All analyses were executed with RStudio v.1.1.383 using the lmer function in the R package lme4 v.1.1-21 (ref. 36 ).

A series of additional models to examine the impact of tobacco control policies were developed as part of this study. In each model, cigarette affordability (RIP) and a different set of policy metrics was used to capture the implementation, quality and compliance of tobacco control legislation. In models 1 and 2, we replaced the achievements scores by the proportion of P, W and E measures adopted by each country out of all possible measures reported by the WHO. In model 3, we used P and E (direct and indirect measures separately) compliance scores provided by the WHO to represent actual legislation implementation. Finally, an interaction term for compliance and achievement to capture the combined effect of legislation quality and performance was added to model 4. Results for men and women by age group for each of the additional models are presented in the Supplemental Information (Supplementary Tables 1–4 ).

The main model described in this study was chosen because it includes a larger number of country-year observations ( n  = 823) when compared to models including compliance scores and because it is more directly interpretable.

Counterfactual analysis

To further explore and quantify the impact of tobacco control policies on current smoking prevalence, we simulated what smoking prevalence across all countries would have been achieved in 2017 under 4 alternative policy scenarios: (1) if achievement scores and RIP remained at the level they were at in 2008; (2) if all countries had implemented each of P, W and E component at the highest level (score = 5); (3) if the price of a cigarette pack was I$7.73 or higher, a price that represents the 90th percentile of observed prices across all countries and years; and (4) if countries had implemented the P, W and E components at the highest level and higher cigarette prices. To keep our results consistent across scenarios, we restricted our analysis to 155 countries with non-missing policy-related indicators for both 2008 and 2016.

Random effects were used in model fitting but not in this prediction. Simulated prevalence rates were calculated by multiplying the estimated marginal effect of each policy by the alternative values proposed in each of the counterfactual scenarios for each country-year. The global population-weighted average was computed for status quo and counterfactual scenarios using population data sourced from the Institute for Health Metrics and Evaluation. Using the predicted prevalence rates and population data, the additional reduction in the number of current smokers in 2017 was also computed. Since models were ran using age-standardized prevalence, the number of smokers was proportionally redistributed across age groups using the sex-specific numbers from the age group 15 and older as an envelope.

The UIs for predicted estimates were based on a computation of the results of each of the 1,000 draws (unbiased random samples) taken from the uncertainty distribution of each of the estimated coefficients; the lower bound of the 95% UI for the final quantity of interest is the 2.5 percentile of the distribution and the upper bound is the 97.5 percentile of the distribution.

Reporting Summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The dataset generated and analyzed during the current study is publicly available at http://ghdx.healthdata.org/record/ihme-data/global-tobacco-control-and-smoking-prevalence-scenarios-2017 ( https://doi.org/10.6069/QAZ7-6505 ). The dataset contains all data necessary to interpret, replicate and build on the methods or findings reported in the article. Tobacco control policy data that support the findings of this study are released every two years as part of the WHO’s Global Report on Tobacco Control; these data are also directly accessible at https://www.who.int/tobacco/global_report/en/ . Source data are provided with this paper.

Code availability

All code used for these analyses is available at http://ghdx.healthdata.org/record/ihme-data/global-tobacco-control-and-smoking-prevalence-scenarios-2017 and https://github.com/ihmeuw/team/tree/effects_tobacco_policies .

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Acknowledgements

The study was funded by Bloomberg Philanthropies (grant 47386, Initiative to Reduce Tobacco Use). We thank the support of the Tobacco Metrics Team Advisory Group, which provided valuable comments and suggestions over several iterations of this manuscript. We also thank the Tobacco Free Initiative team at the WHO and the Campaign for Tobacco-Free Kids for making the tobacco control legislation data available and providing clarifications when necessary. We thank A. Tapp, E. Mullany and J. Whisnant for assisting in the management and execution of this study. We thank the team who worked in a previous iteration of this project, especially A. Reynolds, C. Margono, E. Dansereau, K. Bolt, M. Subart and X. Dai. Lastly, we thank all GBD 2017 Tobacco collaborators for their valuable work in providing feedback to our smoking prevalence estimates throughout the GBD 2017 cycle.

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Luisa S. Flor, Marissa B. Reitsma, Vinay Gupta & Emmanuela Gakidou

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L.S.F., M.N. and E.G. conceptualized the study and designed the analytical framework. M.B.R. and V.G. provided input on data, results and interpretation. L.S.F. and E.G. wrote the first draft of the manuscript. All authors read and approved the final version of the manuscript.

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Correspondence to Emmanuela Gakidou .

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Extended data

Extended data fig. 1 prevalence of current smoking for men (a) and women (b) aged 15 years and older (age-standardized) in 2017..

Age-standardized smoking prevalence (%) estimates from the 2017 Global Burden of Disease Study for men (a) and women (b) aged 15 years and older for 195 countries. Smoking is defined as current use of any type of smoked tobacco product. Details on the estimation process can be found in the Methods section and elsewhere 3 .

Extended Data Fig. 2 Prevalence of current smoking for men (a) and women (b) aged 15 to 29 years old (age-standardized) in 2017.

Age-standardized smoking prevalence (%) estimates from the 2017 Global Burden of Disease Study for men (a) and women (b) aged 15–29 years old for 195 countries. Smoking is defined as current use of any type of smoked tobacco product. Details on the estimation process can be found in the Methods section and elsewhere 3 .

Extended Data Fig. 3 Prevalence of current smoking for men (a) and women (b) aged 30 to 49 years old (age-standardized) in 2017.

Age-standardized smoking prevalence (%) estimates from the 2017 Global Burden of Disease Study for men (a) and women (b) aged 30–49 years old for 195 countries. Smoking is defined as current use of any type of smoked tobacco product. Details on the estimation process can be found in the Methods section and elsewhere 3 .

Extended Data Fig. 4 Prevalence of current smoking for men (a) and women (b) aged 50 years and older (age-standardized) in 2017.

Age-standardized smoking prevalence (%) estimates from the 2017 Global Burden of Disease Study for men (a) and women (b) aged 50 years and older for 195 countries. Smoking is defined as current use of any type of smoked tobacco product. Details on the estimation process can be found in the Methods section and elsewhere 3 .

Extended Data Fig. 5 Percentage changes in current smoking prevalence based on fixed effect coefficients from bivariate mixed effect linear regression models, by policy component, sex and age group.

Bivariate models examined the unadjusted association between smoke-free (P), health warnings (W), and advertising (E) achievement scores, and cigarette’s affordability (RIP) and current smoking prevalence, from 2009 to 2017, across 175 countries (n = 823 country-years). Linear mixed models were fit by maximum likelihood and t-tests used Satterthwaite approximations to degrees of freedom. P values were considered statistically significant if lower than 0.05.

Supplementary information

Supplementary information.

Supplementary Tables 1–4: additional models results.

Source Data Fig. 1

Input data for Fig. 1 replication.

Source Data Extended Data Fig. 1

Input data for Extended Data 1 replication.

Source Data Extended Data Fig. 2

Input data for Extended Data 2 replication.

Source Data Extended Data Fig. 3

Input data for Extended Data 3 replication.

Source Data Extended Data Fig. 4

Input data for Extended Data 4 replication.

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Flor, L.S., Reitsma, M.B., Gupta, V. et al. The effects of tobacco control policies on global smoking prevalence. Nat Med 27 , 239–243 (2021). https://doi.org/10.1038/s41591-020-01210-8

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Impact of tobacco and/or nicotine products on health and functioning: a scoping review and findings from the preparatory phase of the development of a new self-report measure

• Esther F. Afolalu   ORCID: orcid.org/0000-0001-8866-4765 1 ,
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Measuring self-reported experience of health and functioning is important for understanding the changes in the health status of individuals switching from cigarettes to less harmful tobacco and/or nicotine products (TNP) or reduced-risk products (RRP) and for supporting tobacco harm reduction strategies.

This paper presents insights from three research activities from the preparatory phase of the development of a new self-report health and functioning measure. A scoping literature review was conducted to identify the positive and negative impact of TNP use on health and functioning. Focus groups ( n  = 29) on risk perception and individual interviews ( n  = 40) on perceived dependence in people who use TNPs were reanalyzed in the context of health and functioning, and expert opinion was gathered from five key opinion leaders and five technical consultants.

Triangulating the findings of the review of 97 articles, qualitative input from people who use TNPs, and expert feedback helped generate a preliminary conceptual framework including health and functioning and conceptually-related domains impacted by TNP use. Domains related to the future health and functioning measurement model include physical health signs and symptoms, general physical appearance, functioning (physical, sexual, cognitive, emotional, and social), and general health perceptions.

Conclusions

This preliminary conceptual framework can inform future research on development and validation of new measures for assessment of overall health and functioning impact of TNPs from the consumers’ perspective.

As a leading cause of preventable morbidity and mortality worldwide, smoking remains a major public health problem. Compared with those who do not smoke, people who smoke are significantly more likely to develop heart diseases, lung cancer, chronic obstructive pulmonary disease (COPD), and other diseases [ 1 , 2 ]. It is well established that the best way to avoid the health risks associated with smoking is for people to never start and for those who smoke to quit [ 1 , 3 ]. Tobacco harm reduction is one way to alleviate the health risk for individuals who choose not to quit smoking [ 4 ], by providing less harmful tobacco and/or nicotine products (TNP), such as reduced-risk products (RRP) (used here to refer to products that present, are likely to present, or have the potential to present, less risk of harm to people who smoke and switch to these products versus continued smoking) or modified risk tobacco products (MRTP).

Several smokeless tobacco products and a heated tobacco product were recently authorized for marketing with modified risk claims through the United States (US) Food and Drug Administration (FDA) MRTP pathway [ 5 ]. The guidance on MRTP applications [ 6 ] specifies that health outcomes should be assessed during premarket evaluation and postmarket surveillance of modified risk TNPs such as these. These health outcomes comprise not only objective clinical and biological measures but also self-reported outcomes [ 6 , 7 ]. Studies and reports have recently started providing evidence on the health impact of new TNPs [ 8 ]. For instance, recent papers have investigated the effects of e-cigarettes and heated tobacco products on cardiopulmonary outcomes [ 9 , 10 , 11 , 12 , 13 , 14 ]. However, the papers have mainly focused on clinical measurements, such as spirometry and other lung function tests; consumer perception is rarely explored or the focus of the research. Measuring self-reported experience is important for understanding the changes in the health status of individuals switching from cigarettes to RRPs and is a key component of tobacco harm reduction strategies [ 7 ]. Self-reported ratings of RRP effectiveness or adverse events might differ from clinical measures and provide another perspective as useful as the clinicians. In addition, consumer perception of positive changes in health status, functioning and other behavioral outcomes will also subsequently influence use behaviors and switching to RRPs rather than continuing smoking.

Self-perceived health status is a complex concept to define and measure, particularly within the context of TNP use [ 15 ]. While generic health status measures, such as the Medical Outcomes Study 36-item Short-Form Health Survey (SF-36), have been used to evaluate the health status of people who smoke [ 16 , 17 ], comparisons have mainly been made between those who currently smoke, those who used to smoke, and those who never smoked [ 18 , 19 ]. Results from these studies strongly suggest that, in healthy populations, existing generic measures are not sensitive enough to detect change over time when stopping or switching from cigarettes to other TNPs, owing to high ceiling effects [ 20 ]. While a few smoking-specific quality of life measures have been developed, these measures have not been widely implemented or standardized [ 15 , 17 , 21 , 22 ], and the application of these smoking-specific measures to different TNP use across the risk continuum is scarce [ 20 ].

As part of the A ssessment of B ehavioral OU tcomes related to T obacco and Nicotine Products (ABOUT™) Toolbox initiative [ 23 ], the present project aims at developing a new self-report measure (ABOUT™— Health and Functioning ) to address the current gap and assess the impact of TNPs on health and functioning (including health status, functional status and other health-related quality of life constructs). This paper presents insights from three research activities [ 24 , 25 ] from the preparatory phase of development of the measure—that is, a scoping literature review, reanalysis of consumer focus groups/interviews, and expert opinion. These three activities serve as background research to support the development of a preliminary conceptual framework of health and functioning associated with the use of TNPs.

Scoping literature review

The purpose of the review was to address two main questions among individuals who use TNPs:

What are the positive and negative health and functioning impacts of TNP use?

What concepts are evaluated by measures used to assess the positive and negative impacts of TNP use?

Given the nature and breadth of the research questions and the number of potentially relevant publications, a scoping literature review was used as it provides a means of identifying the literature and mapping the concepts and evidence on a topic by using an informative and iterative research process [ 26 ]. The scoping review involved a PubMed search (August 2018) and application of Sciome’s rapid Evidence Mapping (rEM) [ 27 ], followed by additional manual screening and review. rEM is a proprietary methodology developed by Sciome ( https://www.sciome.com/ ) to rapidly summarize and produce a quantitative representation of the available body of scientific evidence in a particular area. The study by Lam et al. demonstrated a proof-of-concept application of the rEM methodology [ 27 ]. The PubMed search terms targeted qualitative and quantitative research among people who use TNPs (Table 1 ). This was supplemented by a second, parallel step of manually identifying relevant literature through other known sources. Table 2 describes the general inclusion and exclusion criteria that were applied to the scoping literature review.

After the initial rEM exercise, two reviewers (EC, SG) further manually screened the titles and abstracts of the articles identified through the automated rEM exercise against the inclusion and exclusion criteria. Finally, the selected publications underwent a full screening by two reviewers (VL and DF) for determining their relevance to the research questions for data extraction and one of the co-authors (LA-W) cross-checked the screening and resolved differences in opinion among the reviewers.

The World Health Organization (WHO) International Classification of Functioning, Disability and Health (ICF) [ 28 ] framework and the revised Wilson and Cleary [ 29 , 30 ] model were used as a guide to broadly inform categories for data extraction from the literature on TNP use and health and functioning. These established models enable the conceptualization and description of health status and functioning (the combination of which is often referred to as health-related quality of life) [ 31 , 32 ], and related outcomes and determinants. To complement and refine this and to ensure relevance to those who use TNPs, the data extracted from the literature was also grouped and labeled based on the contents of the literature reviewed.

The elements extracted from the selected papers were as follows:

Author, citation details, and publication type

Objectives and/or research questions

Sample type, size, and principle demographics

Type(s) of TNP and definitions of levels of consumption

Methodology, questionnaires, and statistical methods used

Main results

Results grouped in broad categories: Health Signs and Symptoms; General Health Perceptions; Quality of Life, Health-Related Quality of Life, and Functional Status; Individual Characteristics; Environmental and Social Characteristics; Biomarkers and Biological Endpoints.

Reanalysis of focus groups/in-depth interviews

The objective of the secondary analyses of existing qualitative data in people who use TNPs was to inform the drafting of the initial conceptual framework, as well as interview guides for planned concept elicitation qualitative studies to identify concepts and develop items to detect what is relevant to measure in this context. Two sets of qualitative data containing information related to health and functioning were reanalyzed and participants had consented for their data to be used in future studies. The first was from 29 focus groups (total number of participants n  = 229) that were originally designed to discuss perceived risk, appeal, and intent to use TNPs [ 33 , 34 ]. The focus groups—stratified by smoking status—were conducted in the United States (US; n  = 12), Japan ( n  = 4), Italy ( n  = 4), and the United Kingdom (UK; n  = 9) between December 2012 and August 2013. The second dataset included 40 in-depth interviews conducted in North Carolina, USA, with people who use TNPs, to discuss issues centered on perceived dependence on TNPs [ 35 ]. While 21 interviewees were people who were poly-TNPs users, 19 were people who were exclusive users of one of the following types of TNPs: cigarettes ( n  = 5), smokeless tobacco ( n  = 5), e-cigarettes ( n  = 5), or another type of TNP (pipes, waterpipes, or nicotine replacement therapy [NRT] products; n  = 4). These interviews were conducted in August 2017. The demographics of both data sets are presented in Table 3 . For reanalyzing the data, an initial codebook guided by the literature review data extraction categories was developed; however, new codes were created to complement these categories based on the thematic content analysis of the transcripts. The qualitative analysis software Quirkos [ 36 ] was used for the reanalysis.

Expert panel review

An expert panel consisting of five key opinion leaders (KOL) and five technical consultants was convened in August 28, 2018, in Neuchâtel, Switzerland. The KOLs were subject matter experts in the fields of nicotine and smoking cessation ( n  = 1), Patients Reported Outcomes (PRO) evaluation and scale development ( n  = 3), and health economics ( n  = 1). The consultants were experts on nicotine dependence ( n  = 1), psychometric validation ( n  = 2), market research ( n  = 1), and PRO development and validation ( n  = 1). The meeting followed an agenda and semi-structured discussion guide to facilitate conversations. First, the panel was presented with the principles underlying the tobacco harm reduction assessment strategy [ 4 ]. This session was followed by an open elicitation phase, during which two experienced moderators asked the panel to identify and discuss concepts related to health and functioning in people who use TNPs that different stakeholders might find important. Then, the panel was asked to review and respond to the concepts identified in the literature review and in the qualitative research reanalysis. These findings were discussed in depth to arrive at a consolidated preliminary conceptual framework. Each concept was presented, and the experts were asked to rank and agree on concepts to be included and how the concepts should be grouped by domains in the framework. In generating the framework, the project team and expert panel considered the themes and concepts identified under each of the categories from the scoping literature review, specific concepts from the secondary analyses of the qualitative data, and the expert panel meeting. The authors then synthesized and re-organized concepts emerging from the different preparatory phase activities under main health and functioning and conceptually-related domains. The participants also provided their input on the best strategies for planned qualitative studies to inform and support the development and validity of the proposed health and functioning measure.

The literature search identified 4761 articles. Figure  1 (flow diagram) depicts the results of the search and screening process. Titles and abstracts were screened by the rEM exercise until the machine learning algorithms predicted 97.7% relevant references; thus, 707 abstracts were not screened. After applying the inclusion/exclusion criteria to the remaining 4,054 abstracts, 281 were identified as part of the rEM exercise. After additional manual screening and review of the abstracts and articles against the inclusion/exclusion criteria, 90 full-text articles were included for data extraction [ 20 , 37 – 125 ]. Seven additional full-text articles were also included on the basis of a manual search [ 126 , 127 , 128 , 129 , 130 , 131 , 132 ]. Findings are summarized in Table 4 and a detailed description and data extracted from all the articles from the literature review is presented in Additional File 1 .

Flow diagram Sciome’s rapid Evidence Mapping (rEM) and manual screening processes of the scoping literature review

Fifty-six publications (56/97; 58%) presented data related to health signs and symptoms . These are grouped under five core areas: mental health and cognitive functioning (28/97; 29%); pain and physical trauma (6/97; 6%); respiratory, cardiovascular and inflammatory conditions (5/97; 5%); “other” health conditions , which included insomnia, liver disease, eye health, and hearing loss (5/97; 5%); and oral health (4/97; 4%). There were also eight publications related to the effects of smoking cessation on health signs and symptoms, mostly benefits of cessation but also including perceived dependence, addiction, and withdrawal symptoms (8/97; 8%). Overall, the burden and impact of cigarette smoking on both physical and mental health symptoms was negative and generally worse among people who smoke relative to those who do not smoke. On the other hand, quitting smoking was accompanied by improvements in general physical health and psychological wellbeing. However, in spite of the positive impact of quitting smoking, loss of moments of pleasure, struggle to manage stress, the social aspects of smoking, and withdrawal symptoms were seen as barriers to quitting.

The general health perceptions of various adults who use TNPs were reported in 18 of the 97 articles (18%), with 9 of them detailing the general health perceptions related to cigarettes and 9 being related to e-cigarettes and other TNPs. Perceptions were determined by questionnaires and focus groups for evaluating the health impacts, fear of diseases, harm to others and self, social impacts (both positive [e.g., inclusion and looking “cool”] and negative [e.g., stigma and exclusion]), and other reasons for taking up or considering/attempting smoking cessation.

Quality of life, health-related quality of life, and functional status was studied in 9 of the 97 included articles (9%). These studies mostly demonstrated with generic and specific QoL, HRQoL, or functional status questionnaires that cigarette smoking was associated with a worse quality of life and that smoking cessation often resulted in an improved quality of life. However, in some cases, the use of TNPs also reportedly enabled individuals to manage their levels of anxiety and improve some aspects of social engagement and functional status.

Individual, environmental and social characteristics were found to influence the decision to smoke and/or consider or attempt to quit smoking or switching to other TNPs, as reported in 8 (8%) and 11 (11%) of 97 publications, respectively. Some key characteristics and determinants of smoking behavior included low socioeconomic status, male sex, living alone, family, and close social environment, societal stigma, and local regulations.

Finally, 12 of the 97 publications (12%) were related to studies on biomarkers and biological endpoints in people who use TNPs and showed that smoking cigarettes negatively influenced cardiovascular, respiratory, oral, renal, stress, metabolic, and inflammatory-related biomarkers and physiological assessments.

The themes from this reanalysis are summarized below and organized on the basis of the narrative of the participants of their experiences.

Perceived negative impact of smoking

Other than health, the biggest and most salient reported negative impact of smoking was the perceived lack of control related to addiction and emotional health and wellbeing. Participants reported feeling that cigarette smoking was running their lives or “holding them hostage.” They reported that this perceived lack of a sense of control or willpower often led to feelings of weakness or a feeling that they were a “slave” to cigarettes. Many respondents reported smoking even when they did not necessarily want to and experiencing feelings of obsession and craving.

Perceived lack of control and addiction were also related to the activities of the participants throughout the day. People who smoke often reported altering their activities to smoke because of patterns of behavior or routine and the experienced need for a smoke. They reported that the “need for a smoke” sensation would cause them to leave work or social events early, not attend events if smoking was not allowed, interrupt what they were doing to smoke, and get up in the middle of the night.

Fear of withdrawal symptoms, with a strong emphasis on mental/emotional health, was also prominent among reported negative impacts of smoking. This fear was often reported as limiting the willingness of individuals to try to quit smoking or facilitating a return to prior smoking behavior. Individuals reported fearing the following symptoms they associated with withdrawal: mood swings and irritability, violent or aggressive behavior, inability to concentrate, anxiety, anger, and weight gain.

Perceived benefits of smoking

Several perceived benefits were identified that keep individuals smoking or using cigarettes. These included perceptions of enhanced cognitive functioning, relaxation, a way to take a break, use as a coping strategy, a social function, a weight management tool, the perception that it feels good, and being part of one’s identity. It is also important to note that the perceived benefits of smoking often outweighed the risks and the feeling of lack of control in the participant discussions. Even people who used to smoke noted they missed the relaxation and breaks they associated with smoking.

Recognition of symptoms/diseases related to smoking

Table 5 summarizes the negative symptoms and diseases related to smoking recognized by participants in both the focus groups and interviews. These were mostly related to six main body systems (cardiovascular, digestive, oral, neurological, reproductive, and respiratory).

Impacts on physical functioning

The participants noted how smoking impacts their physical functioning. In particular, they noted how their exercise capacity during running, playing sports, walking upstairs, and general physical activity was diminished. They also reported reduced stamina and endurance, decreased physical strength, and feeling tired more easily.

Effects on emotional health

The participants also described how smoking impacts their emotional health and wellbeing. People who smoke reported feelings of shame, guilt, weakness, and a lack of control or powerlessness. They also reported feelings of depression and anxiety associated with worry about health risks. Furthermore, the participants indicated that they experienced a fear of going to places where they could not smoke, being a bad role model for their children, and (in case of people who used to smoke) going back to smoking.

Positive and negative social impacts

Smoking was perceived to have both negative and positive impacts on the social lives of participants. Smoking impacted life negatively when it was not allowed in certain environments, such as in homes, at work, and in cars and airplanes. Stigma was also associated with smoking in an environment where peers and family members do not smoke, but it was also seen as a source of group identity within social networks that had a higher prevalence of smoking behaviors. Participants reported that smoking had some positive impacts on their social interaction, because it facilitated work breaks and increased communication with peers.

Reasons people decided to try to quit

Throughout the focus groups and interviews, individuals identified several reasons why they tried to quit smoking. These included: health, diagnosis of cancer (self, family, or friend), gum disease, pregnancy, hospital stay, worry that it will “kill me,” dislike of taste or odor, social reasons, change in surroundings (fewer smoking spaces), and price.

Reasons people do not like alternatives to cigarettes

The participants’ reasons for not liking alternatives to cigarettes (i.e., less harmful TNPs/RRPs) included perceptions that the alternatives did not work (i.e., the participants still had cravings and experienced withdrawal symptoms), made them feel or get ill (nausea and vomiting), were not “the same” as cigarettes in terms of the ritual, taste, or “feeling,” or were inconvenient/too big to carry.

The conclusions of the expert panel widely supported the findings of the literature review and the input from the reanalyzed focus groups and interviews. Some of the experts working in field of tobacco and nicotine provided additional insights based on their extensive experience with people who use TNPs; they highlighted the importance of the enjoyment of smoking for people who find it difficult to quit, the positive immediate benefits of quitting, and the smoking-related biomarkers that might be on a causal pathway between switching and changes in health and functioning status.

The following main areas were discussed and agreed during the meeting: (1) utility of use, referring to the perceived satisfaction and enjoyment of smoking (e.g., craving relief, weight control, and social affiliation); (2) signs and symptoms of withdrawal (e.g., anxiety, depression, and anger) and the positive immediate physical health effects of quitting smoking (e.g., better general and oral hygiene, less coughing, and improved exercise capacity); (3) functioning, including cognitive, physical, sexual, social, emotional, and role functioning; (4) worry associated with smoking and smoking-related diseases; (5) general health perceptions and quality of life; (6) association with smoking-related biomarkers that could be on the causal pathway between switching and changes in health and functioning; and (7) TNP use patterns and maintenance of switching to RRPs.

Generation of the preliminary conceptual framework

Triangulation of the findings from the literature review, qualitative input from people who use TNPs, and expert panel feedback helped generate a preliminary descriptive conceptual framework that includes the health and functioning and conceptually-related domains impacted by TNP use (Fig.  2 ).

Health and functioning conceptual framework related to tobacco and/or nicotine product use from the preparatory phase research findings

Four domains related to the future health and functioning measurement model for TNP use are indicated in grey rectangular boxes and include (moving down from proximal to distal parameters) physical health symptoms (e.g., oral and respiratory symptoms), general physical condition (e.g., appearance and hygiene), functioning (physical, sexual, cognitive, emotional, and social functioning), and general health perceptions, which will be the most distal measure of health and functioning. The preparatory phase research also identified six conceptually-related domains (in dashed rectangular boxes), which are not direct indicators of health status but might influence the impact of TNP use on health and functioning. These include attitudinal variables (worry about the health risks of using TNPs and perceived dependence/fear of withdrawal symptoms associated with quitting smoking), and utilitarian ones (perceived appeal, satisfaction, and benefits of TNP use). In addition, personal factors (e.g., sociodemographic) and environmental factors (e.g., peer/family influence, policies and regulations and sociocultural context) are also reflected in the conceptual framework as indirect indicators of health and functioning.

The framework further indicates that specific behavioral indicators (i.e., TNP use patterns over time) might influence any impact of TNP use on health and functioning. Whilst other causal and reciprocal relationships and hierarchies might exist within the domains, these are not explicitly characterized in this initial draft of the framework and will have to be tested with further empirical data. Finally, identified biomarkers of potential harm (in italics and dashed box) are also integrated in this conceptual framework as part of the conceptually-related domains, because they are on a causal pathway between TNP use and changes in health and functioning [ 133 , 134 ]. Biomarkers are not part of the measurement model that will be considered for a new self-report measure; however, because they are the most proximal parameters to health and functioning, they will be assessed independently as appropriate endpoints by objective clinical or biological analyses.

Triangulation of published literature, reanalysis of qualitative data, and expert opinion helped develop the presented preliminary conceptual framework as the foundation for a new measure to assess the impact of TNPs on self-reported health and functioning. This is essential for identifying relevant concepts and understanding what is important to measure in people who use TNPs. The findings reveal the importance of not only the perceived impacts of TNP use on physical health and physical functioning, but also on aspects of mental health and social interactions and functioning, and general perceptions of health and health-related quality of life.

For the literature review, the WHO ICF [ 28 ] and Wilson and Cleary model [ 29 , 30 ] served as useful guides to develop categories for data abstraction. The scoping literature review yielded 97 articles on TNP use and the relationship to health, perceptions of health, social and individual functioning, and quality of life. Overall, most studies had focused on the known negative effects of cigarette smoking (e.g., mental, respiratory, and oral health) and the rationale and motivation to quit smoking. The WHO ICF and Wilson and Clearly models were not always sufficient for identifying the breadth of relevant concepts, especially from the perspective of TNP use. Development of new codes for the reanalysis of existing qualitative data allowed for the development, extension, and exploration of the topic and provided valuable insights reported in the qualitative data reanalysis, such as the perceived benefits/satisfaction from cigarette smoking, and the rationale for quitting smoking or switching to an RRP. The findings show how this manner of secondary analysis can be valuable in health-related fields where the topic is broad and an existing body of knowledge can contribute by offering a different perspective [ 135 ].

The presentation of the preliminary conceptual framework from this preparatory phase is specific to TNP use and marks a slight departure from the established norms and characterization of the variables typically observed in existing generic health and functioning and health-related quality of life models, such as the WHO ICF and Wilson and Clearly models. Notably, specific hypothesized relationships and the hierarchy between domains are not explicitly characterized in the current draft of the framework. The framework provided an exploratory representation of the current findings to reflect a measurement instrument in people who use TNPs that would ideally be able to assess and demonstrate improvements in self-reported health and functioning status, stability of perceived positive aspects of using TNPs, and no worsening in key areas of physical and emotional health and functioning upon switching to RRPs. Nevertheless, the framework could still undergo further refinement to support the development and validation of a new measure and to further characterize and test the relationships and hierarchies between domains.

This work is not without limitations. For the scoping literature review, among the reviewed articles, not many reported on the use of e-cigarettes and other alternative tobacco or nicotine-delivery devices, because most studies had focused exclusively on cigarettes. It is possible that concepts associated with health and functioning that are relevant to other TNPs were not identified. This is most likely the consequence of the large number of publications related to cigarette use. Some concepts might also have been missed, given the large evidence base on health and functioning-related themes and concepts. However, this was also not a systematic literature search; a scoping review is generally broader than a systematic review in terms of the former having a less-defined research question, broader inclusion and exclusion criteria, and no systematic appraisal of study quality [ 26 ]. Nevertheless, the present scoping review methodology provides a lens on the overall evidence base, and regular updates on the search—specifically related to RRPs and novel TNPs and their health and functioning impacts—could be considered for fully understanding the evolving state of the art in this context. The reanalysis of existing qualitative data also has limitations related to data fit and completeness of preexisting data [ 136 ]. The insights collected from these reanalyzed studies were originally for a different purpose several years prior to the present research, and this might not completely and accurately reflect the objectives of the new project.

Considering the findings of the current research, the development of a health and functioning measure can continue to follow the FDA’s Guidance on PRO measures. As specified within the guideline, gaining input directly from the intended use populations through concept elicitation is a critical activity for ensuring content validity during the development of any new self-reported measure [ 137 ]. Continuous engagement with an expert panel can also support the refinement of the conceptual framework as well as the development of the draft and final measure.

The goal of this research was to identify from varied research activities key concepts and aspects of health and functioning and related changes associated with the use of TNPs. The resulting preliminary conceptual framework provides the basis for informing future research to further understand health and functioning concepts important to measure in individual who switch to RRPs and to develop a new self-report measure to assess this from the consumers’ perspective.

Availability of data and materials

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Abbreviations

Assessment of Behavioral OUtcomes related to Tobacco and Nicotine Products Toolbox

Chronic obstructive pulmonary disease

Food and Drug Administration

Health-related quality of life

International Classification of Functioning, Disability and Health

• Modified risk tobacco products

Nicotine replacement therapy

Patient-Reported Outcomes

Quality of life

Reduced-risk products

Rapid Evidence Mapping

• Tobacco and/or nicotine products

United Kingdom

United States

36-Item Short-Form Health Survey

World Health Organization

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Acknowledgements

We thank the team at Sciome LLC for their assistance and contribution to the literature review. We thank Vivienne Law and David Floyd for their contributions to the literature review, reanalysis of qualitative data, and assistance with review of the draft manuscript. We thank Catherine Acquadro for her review of the draft manuscript. We also thank John Ware, Jed Rose, Ashley Slagle, Donald Patrick, Karl Fagerström, Stefan Cano, and Thomas Salzberger for their input and review.

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EA, ES and CC performed conceptualization. EA, ES and LA-W performed methodology. EA, ES, SG, EC and LA-W were involved in the investigation. EA and ES were involved in writing—original draft. EA, EC, LA-W and CC were involved in writing—review & editing. EA performed visualization. ES and CC performed supervision. AB, EC and SG were involved in data curation. AB and EC were involved in project administration. LA-W performed formal analysis. CC was involved in funding acquisition. All authors read and approved the final manuscript.

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Esther F. Afolalu, Emilie Clerc, and Christelle Chrea are employees of Philip Morris International. Agnes Bacso, Erica Spies, and Sophie Gallot completed the work during prior employment with Philip Morris International. Linda Abetz-Webb is a consultant for Philip Morris International.

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Afolalu, E.F., Spies, E., Bacso, A. et al. Impact of tobacco and/or nicotine products on health and functioning: a scoping review and findings from the preparatory phase of the development of a new self-report measure. Harm Reduct J 18 , 79 (2021). https://doi.org/10.1186/s12954-021-00526-z

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Tobacco, Nicotine, and E-Cigarettes Research Report Introduction

In 2014, the Nation marked the 50th anniversary of the first Surgeon General’s Report on Smoking and Health. In 1964, more than 40 percent of the adult population smoked. Once the link between smoking and its medical consequences—including cancers and heart and lung diseases—became a part of the public consciousness, education efforts and public policy changes were enacted to reduce the number of people who smoke. These efforts resulted in substantial declines in smoking rates in the United States—to half the 1964 level. 1

However, rates of cigarette smoking and other tobacco use are still too high, 2 and some populations are disproportionately affected by tobacco’s health consequences. Most notably, people with mental disorders—including substance use disorders—smoke at higher rates than the general population. 3–6 Additionally, people living below the poverty line and those with low educational attainment are more likely to smoke than those in the general population. As tobacco use is the leading preventable cause of mortality in the United States, 1 differential rates of smoking and use of other tobacco products is a significant contributor to health disparities among some of the most vulnerable people in our society.

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The effect of cigarette prices on youth smoking

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• 1 School of Public Health, University of Illinois at Chicago, USA. [email protected]
• PMID: 12605466
• DOI: 10.1002/hec.709

Prior economic research provides mixed evidence on the impact of cigarette prices on youth smoking. This paper empirically tests the effects of various price measures on youth demand for cigarettes using data collected in a recent nationally representative survey of 17 287 high school students. In addition to commonly used cigarette price measures, the study also examined the effect of price as perceived by the students. This unique information permits the study of the effect of teen-specific price on cigarette demand. The analysis employed a two-part model of cigarette demand based on a model developed by Cragg (1971) in which the propensity to smoke and the intensity of the smoking habit are modeled separately. The results confirm that higher cigarette prices, irrespective of the way they are measured, reduce probability of youth cigarette smoking. There is also some evidence of negative price effect on smoking intensity, but it is sensitive to the price measure used in the model. The largest impact on cigarette demand has the teen-specific, perceived price of cigarettes.

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National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. Preventing Tobacco Use Among Youth and Young Adults: A Report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention (US); 2012.

Preventing Tobacco Use Among Youth and Young Adults: A Report of the Surgeon General.

1 introduction, summary, and conclusions.

• Introduction

Tobacco use is a global epidemic among young people. As with adults, it poses a serious health threat to youth and young adults in the United States and has significant implications for this nation’s public and economic health in the future ( Perry et al. 1994 ; Kessler 1995 ). The impact of cigarette smoking and other tobacco use on chronic disease, which accounts for 75% of American spending on health care ( Anderson 2010 ), is well-documented and undeniable. Although progress has been made since the first Surgeon General’s report on smoking and health in 1964 ( U.S. Department of Health, Education, and Welfare [USDHEW] 1964 ), nearly one in four high school seniors is a current smoker. Most young smokers become adult smokers. One-half of adult smokers die prematurely from tobacco-related diseases ( Fagerström 2002 ; Doll et al. 2004 ). Despite thousands of programs to reduce youth smoking and hundreds of thousands of media stories on the dangers of tobacco use, generation after generation continues to use these deadly products, and family after family continues to suffer the devastating consequences. Yet a robust science base exists on social, biological, and environmental factors that influence young people to use tobacco, the physiology of progression from experimentation to addiction, other health effects of tobacco use, the epidemiology of youth and young adult tobacco use, and evidence-based interventions that have proven effective at reducing both initiation and prevalence of tobacco use among young people. Those are precisely the issues examined in this report, which aims to support the application of this robust science base.

Nearly all tobacco use begins in childhood and adolescence ( U.S. Department of Health and Human Services [USDHHS] 1994 ). In all, 88% of adult smokers who smoke daily report that they started smoking by the age of 18 years (see Chapter 3 , “The Epidemiology of Tobacco Use Among Young People in the United States and Worldwide”). This is a time in life of great vulnerability to social influences ( Steinberg 2004 ), such as those offered through the marketing of tobacco products and the modeling of smoking by attractive role models, as in movies ( Dalton et al. 2009 ), which have especially strong effects on the young. This is also a time in life of heightened sensitivity to normative influences: as tobacco use is less tolerated in public areas and there are fewer social or regular users of tobacco, use decreases among youth ( Alesci et al. 2003 ). And so, as we adults quit, we help protect our children.

Cigarettes are the only legal consumer products in the world that cause one-half of their long-term users to die prematurely ( Fagerström 2002 ; Doll et al. 2004 ). As this epidemic continues to take its toll in the United States, it is also increasing in low- and middle-income countries that are least able to afford the resulting health and economic consequences ( Peto and Lopez 2001 ; Reddy et al. 2006 ). It is past time to end this epidemic. To do so, primary prevention is required, for which our focus must be on youth and young adults. As noted in this report, we now have a set of proven tools and policies that can drastically lower youth initiation and use of tobacco products. Fully committing to using these tools and executing these policies consistently and aggressively is the most straight forward and effective to making future generations tobacco-free.

The 1994 Surgeon General’s Report

This Surgeon General’s report on tobacco is the second to focus solely on young people since these reports began in 1964. Its main purpose is to update the science of smoking among youth since the first comprehensive Surgeon General’s report on tobacco use by youth, Preventing Tobacco Use Among Young People , was published in 1994 ( USDHHS 1994 ). That report concluded that if young people can remain free of tobacco until 18 years of age, most will never start to smoke. The report documented the addiction process for young people and how the symptoms of addiction in youth are similar to those in adults. Tobacco was also presented as a gateway drug among young people, because its use generally precedes and increases the risk of using illicit drugs. Cigarette advertising and promotional activities were seen as a potent way to increase the risk of cigarette smoking among young people, while community-wide efforts were shown to have been successful in reducing tobacco use among youth. All of these conclusions remain important, relevant, and accurate, as documented in the current report, but there has been considerable research since 1994 that greatly expands our knowledge about tobacco use among youth, its prevention, and the dynamics of cessation among young people. Thus, there is a compelling need for the current report.

Tobacco Control Developments

Since 1994, multiple legal and scientific developments have altered the tobacco control environment and thus have affected smoking among youth. The states and the U.S. Department of Justice brought lawsuits against cigarette companies, with the result that many internal documents of the tobacco industry have been made public and have been analyzed and introduced into the science of tobacco control. Also, the 1998 Master Settlement Agreement with the tobacco companies resulted in the elimination of billboard and transit advertising as well as print advertising that directly targeted underage youth and limitations on the use of brand sponsorships ( National Association of Attorneys General [NAAG] 1998 ). This settlement also created the American Legacy Foundation, which implemented a nationwide antismoking campaign targeting youth. In 2009, the U.S. Congress passed a law that gave the U.S. Food and Drug Administration authority to regulate tobacco products in order to promote the public’s health ( Family Smoking Prevention and Tobacco Control Act 2009 ). Certain tobacco companies are now subject to regulations limiting their ability to market to young people. In addition, they have had to reimburse state governments (through agreements made with some states and the Master Settlement Agreement) for some health care costs. Due in part to these changes, there was a decrease in tobacco use among adults and among youth following the Master Settlement Agreement, which is documented in this current report.

Recent Surgeon General Reports Addressing Youth Issues

Other reports of the Surgeon General since 1994 have also included major conclusions that relate to tobacco use among youth ( Office of the Surgeon General 2010 ). In 1998, the report focused on tobacco use among U.S. racial/ethnic minority groups ( USDHHS 1998 ) and noted that cigarette smoking among Black and Hispanic youth increased in the 1990s following declines among all racial/ethnic groups in the 1980s; this was particularly notable among Black youth, and culturally appropriate interventions were suggested. In 2000, the report focused on reducing tobacco use ( USDHHS 2000b ). A major conclusion of that report was that school-based interventions, when implemented with community- and media-based activities, could reduce or postpone the onset of smoking among adolescents by 20–40%. That report also noted that effective regulation of tobacco advertising and promotional activities directed at young people would very likely reduce the prevalence and onset of smoking. In 2001, the Surgeon General’s report focused on women and smoking ( USDHHS 2001 ). Besides reinforcing much of what was discussed in earlier reports, this report documented that girls were more affected than boys by the desire to smoke for the purpose of weight control. Given the ongoing obesity epidemic ( Bonnie et al. 2007 ), the current report includes a more extensive review of research in this area.

The 2004 Surgeon General’s report on the health consequences of smoking ( USDHHS 2004 ) concluded that there is sufficient evidence to infer that a causal relationship exists between active smoking and (a) impaired lung growth during childhood and adolescence; (b) early onset of decline in lung function during late adolescence and early adulthood; (c) respiratory signs and symptoms in children and adolescents, including coughing, phlegm, wheezing, and dyspnea; and (d) asthma-related symptoms (e.g., wheezing) in childhood and adolescence. The 2004 Surgeon General’s report further provided evidence that cigarette smoking in young people is associated with the development of atherosclerosis.

The 2010 Surgeon General’s report on the biology of tobacco focused on the understanding of biological and behavioral mechanisms that might underlie the pathogenicity of tobacco smoke ( USDHHS 2010 ). Although there are no specific conclusions in that report regarding adolescent addiction, it does describe evidence indicating that adolescents can become dependent at even low levels of consumption. Two studies ( Adriani et al. 2003 ; Schochet et al. 2005 ) referenced in that report suggest that because the adolescent brain is still developing, it may be more susceptible and receptive to nicotine than the adult brain.

Scientific Reviews

Since 1994, several scientific reviews related to one or more aspects of tobacco use among youth have been undertaken that also serve as a foundation for the current report. The Institute of Medicine (IOM) ( Lynch and Bonnie 1994 ) released Growing Up Tobacco Free: Preventing Nicotine Addiction in Children and Youths, a report that provided policy recommendations based on research to that date. In 1998, IOM provided a white paper, Taking Action to Reduce Tobacco Use, on strategies to reduce the increasing prevalence (at that time) of smoking among young people and adults. More recently, IOM ( Bonnie et al. 2007 ) released a comprehensive report entitled Ending the Tobacco Problem: A Blueprint for the Nation . Although that report covered multiple potential approaches to tobacco control, not just those focused on youth, it characterized the overarching goal of reducing smoking as involving three distinct steps: “reducing the rate of initiation of smoking among youth (IOM [ Lynch and Bonnie] 1994 ), reducing involuntary tobacco smoke exposure ( National Research Council 1986 ), and helping people quit smoking” (p. 3). Thus, reducing onset was seen as one of the primary goals of tobacco control.

As part of USDHHS continuing efforts to assess the health of the nation, prevent disease, and promote health, the department released, in 2000, Healthy People 2010 and, in 2010, Healthy People 2020 ( USDHHS 2000a , 2011 ). Healthy People provides science-based, 10-year national objectives for improving the health of all Americans. For 3 decades, Healthy People has established benchmarks and monitored progress over time in order to encourage collaborations across sectors, guide individuals toward making informed health decisions, and measure the impact of prevention activities. Each iteration of Healthy People serves as the nation’s disease prevention and health promotion roadmap for the decade. Both Healthy People 2010 and Healthy People 2020 highlight “Tobacco Use” as one of the nation’s “Leading Health Indicators,” feature “Tobacco Use” as one of its topic areas, and identify specific measurable tobacco-related objectives and targets for the nation to strive for. Healthy People 2010 and Healthy People 2020 provide tobacco objectives based on the most current science and detailed population-based data to drive action, assess tobacco use among young people, and identify racial and ethnic disparities. Additionally, many of the Healthy People 2010 and 2020 tobacco objectives address reductions of tobacco use among youth and target decreases in tobacco advertising in venues most often influencing young people. A complete list of the healthy people 2020 objectives can be found on their Web site ( USDHHS 2011 ).

In addition, the National Cancer Institute (NCI) of the National Institutes of Health has published monographs pertinent to the topic of tobacco use among youth. In 2001, NCI published Monograph 14, Changing Adolescent Smoking Prevalence , which reviewed data on smoking among youth in the 1990s, highlighted important statewide intervention programs, presented data on the influence of marketing by the tobacco industry and the pricing of cigarettes, and examined differences in smoking by racial/ethnic subgroup ( NCI 2001 ). In 2008, NCI published Monograph 19, The Role of the Media in Promoting and Reducing Tobacco Use ( NCI 2008 ). Although young people were not the sole focus of this Monograph, the causal relationship between tobacco advertising and promotion and increased tobacco use, the impact on youth of depictions of smoking in movies, and the success of media campaigns in reducing youth tobacco use were highlighted as major conclusions of the report.

The Community Preventive Services Task Force (2011) provides evidence-based recommendations about community preventive services, programs, and policies on a range of topics including tobacco use prevention and cessation ( Task Force on Community Preventive Services 2001 , 2005 ). Evidence reviews addressing interventions to reduce tobacco use initiation and restricting minors’ access to tobacco products were cited and used to inform the reviews in the current report. The Cochrane Collaboration (2010) has also substantially contributed to the review literature on youth and tobacco use by producing relevant systematic assessments of health-related programs and interventions. Relevant to this Surgeon General’s report are Cochrane reviews on interventions using mass media ( Sowden 1998 ), community interventions to prevent smoking ( Sowden and Stead 2003 ), the effects of advertising and promotional activities on smoking among youth ( Lovato et al. 2003 , 2011 ), preventing tobacco sales to minors ( Stead and Lancaster 2005 ), school-based programs ( Thomas and Perara 2006 ), programs for young people to quit using tobacco ( Grimshaw and Stanton 2006 ), and family programs for preventing smoking by youth ( Thomas et al. 2007 ). These reviews have been cited throughout the current report when appropriate.

In summary, substantial new research has added to our knowledge and understanding of tobacco use and control as it relates to youth since the 1994 Surgeon General’s report, including updates and new data in subsequent Surgeon General’s reports, in IOM reports, in NCI Monographs, and in Cochrane Collaboration reviews, in addition to hundreds of peer-reviewed publications, book chapters, policy reports, and systematic reviews. Although this report is a follow-up to the 1994 report, other important reviews have been undertaken in the past 18 years and have served to fill the gap during an especially active and important time in research on tobacco control among youth.

• Focus of the Report

Young People

This report focuses on “young people.” In general, work was reviewed on the health consequences, epidemiology, etiology, reduction, and prevention of tobacco use for those in the young adolescent (11–14 years of age), adolescent (15–17 years of age), and young adult (18–25 years of age) age groups. When possible, an effort was made to be specific about the age group to which a particular analysis, study, or conclusion applies. Because hundreds of articles, books, and reports were reviewed, however, there are, unavoidably, inconsistencies in the terminology used. “Adolescents,” “children,” and “youth” are used mostly interchangeably throughout this report. In general, this group encompasses those 11–17 years of age, although “children” is a more general term that will include those younger than 11 years of age. Generally, those who are 18–25 years old are considered young adults (even though, developmentally, the period between 18–20 years of age is often labeled late adolescence), and those 26 years of age or older are considered adults.

In addition, it is important to note that the report is concerned with active smoking or use of smokeless tobacco on the part of the young person. The report does not consider young people’s exposure to secondhand smoke, also referred to as involuntary or passive smoking, which was discussed in the 2006 report of the Surgeon General ( USDHHS 2006 ). Additionally, the report does not discuss research on children younger than 11 years old; there is very little evidence of tobacco use in the United States by children younger than 11 years of age, and although there may be some predictors of later tobacco use in those younger years, the research on active tobacco use among youth has been focused on those 11 years of age and older.

Tobacco Use

Although cigarette smoking is the most common form of tobacco use in the United States, this report focuses on other forms as well, such as using smokeless tobacco (including chew and snuff) and smoking a product other than a cigarette, such as a pipe, cigar, or bidi (tobacco wrapped in tendu leaves). Because for young people the use of one form of tobacco has been associated with use of other tobacco products, it is particularly important to monitor all forms of tobacco use in this age group. The term “tobacco use” in this report indicates use of any tobacco product. When the word “smoking” is used alone, it refers to cigarette smoking.

• Organization of the Report

This chapter begins by providing a short synopsis of other reports that have addressed smoking among youth and, after listing the major conclusions of this report, will end by presenting conclusions specific to each chapter. Chapter 2 of this report (“The Health Consequences of Tobacco Use Among Young People”) focuses on the diseases caused by early tobacco use, the addiction process, the relation of body weight to smoking, respiratory and pulmonary problems associated with tobacco use, and cardiovascular effects. Chapter 3 (“The Epidemiology of Tobacco Use Among Young People in the United States and Worldwide”) provides recent and long-term cross-sectional and longitudinal data on cigarette smoking, use of smokeless tobacco, and the use of other tobacco products by young people, by racial/ethnic group and gender, primarily in the United States, but including some worldwide data as well. Chapter 4 (“Social, Environmental, Cognitive, and Genetic Influences on the Use of Tobacco Among Youth”) identifies the primary risk factors associated with tobacco use among youth at four levels, including the larger social and physical environments, smaller social groups, cognitive factors, and genetics and neurobiology. Chapter 5 (“The Tobacco Industry’s Influences on the Use of Tobacco Among Youth”) includes data on marketing expenditures for the tobacco industry over time and by category, the effects of cigarette advertising and promotional activities on young people’s smoking, the effects of price and packaging on use, the use of the Internet and movies to market tobacco products, and an evaluation of efforts by the tobacco industry to prevent tobacco use among young people. Chapter 6 (“Efforts to Prevent and Reduce Tobacco Use Among Young People”) provides evidence on the effectiveness of family-based, clinic-based, and school-based programs, mass media campaigns, regulatory and legislative approaches, increased cigarette prices, and community and statewide efforts in the fight against tobacco use among youth. Chapter 7 (“A Vision for Ending the Tobacco Epidemic”) points to next steps in preventing and reducing tobacco use among young people.

• Preparation of the Report

This report of the Surgeon General was prepared by the Office on Smoking and Health (OSH), National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), USDHHS. In 2008, 18 external independent scientists reviewed the 1994 report and suggested areas to be added and updated. These scientists also suggested chapter editors and a senior scientific editor, who were contacted by OSH. Each chapter editor named external scientists who could contribute, and 33 content experts prepared draft sections. The draft sections were consolidated into chapters by the chapter editors and then reviewed by the senior scientific editor, with technical editing performed by CDC. The chapters were sent individually to 34 peer reviewers who are experts in the areas covered and who reviewed the chapters for scientific accuracy and comprehensiveness. The entire manuscript was then sent to more than 25 external senior scientists who reviewed the science of the entire document. After each review cycle, the drafts were revised by the chapter and senior scientific editor on the basis of the experts’ comments. Subsequently, the report was reviewed by various agencies within USDHHS. Publication lags prevent up-to-the-minute inclusion of all recently published articles and data, and so some more recent publications may not be cited in this report.

• Evaluation of the Evidence

Since the first Surgeon General’s report in 1964 on smoking and health ( USDHEW 1964 ), major conclusions concerning the conditions and diseases caused by cigarette smoking and the use of smokeless tobacco have been based on explicit criteria for causal inference ( USDHHS 2004 ). Although a number of different criteria have been proposed for causal inference since the 1960s, this report focuses on the five commonly accepted criteria that were used in the original 1964 report and that are discussed in greater detail in the 2004 report on the health consequences of smoking ( USDHHS 2004 ). The five criteria refer to the examination of the association between two variables, such as a risk factor (e.g., smoking) and an outcome (e.g., lung cancer). Causal inference between these variables is based on (1) the consistency of the association across multiple studies; this is the persistent finding of an association in different persons, places, circumstances, and times; (2) the degree of the strength of association, that is, the magnitude and statistical significance of the association in multiple studies; (3) the specificity of the association to clearly demonstrate that tobacco use is robustly associated with the condition, even if tobacco use has multiple effects and multiple causes exist for the condition; (4) the temporal relationship of the association so that tobacco use precedes disease onset; and (5) the coherence of the association, that is, the argument that the association makes scientific sense, given data from other sources and understanding of biological and psychosocial mechanisms ( USDHHS 2004 ). Since the 2004 Surgeon General’s report, The Health Consequences of Smoking , a four-level hierarchy ( Table 1.1 ) has been used to assess the research data on associations discussed in these reports ( USDHHS 2004 ). In general, this assessment was done by the chapter editors and then reviewed as appropriate by peer reviewers, senior scientists, and the scientific editors. For a relationship to be considered sufficient to be characterized as causal, multiple studies over time provided evidence in support of each criteria.

Four-level hierarchy for classifying the strength of causal inferences based on available evidence.

When a causal association is presented in the chapter conclusions in this report, these four levels are used to describe the strength of the evidence of the association, from causal (1) to not causal (4). Within the report, other terms are used to discuss the evidence to date (i.e., mixed, limited, and equivocal evidence), which generally represent an inadequacy of data to inform a conclusion.

However, an assessment of a casual relationship is not utilized in presenting all of the report’s conclusions. The major conclusions are written to be important summary statements that are easily understood by those reading the report. Some conclusions, particularly those found in Chapter 3 (epidemiology), provide observations and data related to tobacco use among young people, and are generally not examinations of causal relationships. For those conclusions that are written using the hierarchy above, a careful and extensive review of the literature has been undertaken for this report, based on the accepted causal criteria ( USDHHS 2004 ). Evidence that was characterized as Level 1 or Level 2 was prioritized for inclusion as chapter conclusions.

In additional to causal inferences, statistical estimation and hypothesis testing of associations are presented. For example, confidence intervals have been added to the tables in the chapter on the epidemiology of youth tobacco use (see Chapter 3 ), and statistical testing has been conducted for that chapter when appropriate. The chapter on efforts to prevent tobacco use discusses the relative improvement in tobacco use rates when implementing one type of program (or policy) versus a control program. Statistical methods, including meta-analytic methods and longitudinal trajectory analyses, are also presented to ensure that the methods of evaluating data are up to date with the current cutting-edge research that has been reviewed. Regardless of the methods used to assess significance, the five causal criteria discussed above were applied in developing the conclusions of each chapter and the report.

• Major Conclusions
• Cigarette smoking by youth and young adults has immediate adverse health consequences, including addiction, and accelerates the development of chronic diseases across the full life course.
• Prevention efforts must focus on both adolescents and young adults because among adults who become daily smokers, nearly all first use of cigarettes occurs by 18 years of age (88%), with 99% of first use by 26 years of age.
• Advertising and promotional activities by tobacco companies have been shown to cause the onset and continuation of smoking among adolescents and young adults.
• After years of steady progress, declines in the use of tobacco by youth and young adults have slowed for cigarette smoking and stalled for smokeless tobacco use.
• Coordinated, multicomponent interventions that combine mass media campaigns, price increases including those that result from tax increases, school-based policies and programs, and statewide or community-wide changes in smoke-free policies and norms are effective in reducing the initiation, prevalence, and intensity of smoking among youth and young adults.
• Chapter Conclusions

The following are the conclusions presented in the substantive chapters of this report.

Chapter 2. The Health Consequences of Tobacco Use Among Young People

• The evidence is sufficient to conclude that there is a causal relationship between smoking and addiction to nicotine, beginning in adolescence and young adulthood.
• The evidence is suggestive but not sufficient to conclude that smoking contributes to future use of marijuana and other illicit drugs.
• The evidence is suggestive but not sufficient to conclude that smoking by adolescents and young adults is not associated with significant weight loss, contrary to young people’s beliefs.
• The evidence is sufficient to conclude that there is a causal relationship between active smoking and both reduced lung function and impaired lung growth during childhood and adolescence.
• The evidence is sufficient to conclude that there is a causal relationship between active smoking and wheezing severe enough to be diagnosed as asthma in susceptible child and adolescent populations.
• The evidence is sufficient to conclude that there is a causal relationship between smoking in adolescence and young adulthood and early abdominal aortic atherosclerosis in young adults.
• The evidence is suggestive but not sufficient to conclude that there is a causal relationship between smoking in adolescence and young adulthood and coronary artery atherosclerosis in adulthood.

Chapter 3. The Epidemiology of Tobacco Use Among Young People in the United States and Worldwide

• Among adults who become daily smokers, nearly all first use of cigarettes occurs by 18 years of age (88%), with 99% of first use by 26 years of age.
• Almost one in four high school seniors is a current (in the past 30 days) cigarette smoker, compared with one in three young adults and one in five adults. About 1 in 10 high school senior males is a current smokeless tobacco user, and about 1 in 5 high school senior males is a current cigar smoker.
• Among adolescents and young adults, cigarette smoking declined from the late 1990s, particularly after the Master Settlement Agreement in 1998. This decline has slowed in recent years, however.
• Significant disparities in tobacco use remain among young people nationwide. The prevalence of cigarette smoking is highest among American Indians and Alaska Natives, followed by Whites and Hispanics, and then Asians and Blacks. The prevalence of cigarette smoking is also highest among lower socioeconomic status youth.
• Use of smokeless tobacco and cigars declined in the late 1990s, but the declines appear to have stalled in the last 5 years. The latest data show the use of smokeless tobacco is increasing among White high school males, and cigar smoking may be increasing among Black high school females.
• Concurrent use of multiple tobacco products is prevalent among youth. Among those who use tobacco, nearly one-third of high school females and more than one-half of high school males report using more than one tobacco product in the last 30 days.
• Rates of tobacco use remain low among girls relative to boys in many developing countries, however, the gender gap between adolescent females and males is narrow in many countries around the globe.

Chapter 4. Social, Environmental, Cognitive, and Genetic Influences on the Use of Tobacco Among Youth

• Given their developmental stage, adolescents and young adults are uniquely susceptible to social and environmental influences to use tobacco.
• Socioeconomic factors and educational attainment influence the development of youth smoking behavior. The adolescents most likely to begin to use tobacco and progress to regular use are those who have lower academic achievement.
• The evidence is sufficient to conclude that there is a causal relationship between peer group social influences and the initiation and maintenance of smoking behaviors during adolescence.
• Affective processes play an important role in youth smoking behavior, with a strong association between youth smoking and negative affect.
• The evidence is suggestive that tobacco use is a heritable trait, more so for regular use than for onset. The expression of genetic risk for smoking among young people may be moderated by small-group and larger social-environmental factors.

Chapter 5. The Tobacco Industry’s Influences on the Use of Tobacco Among Youth

• In 2008, tobacco companies spent $9.94 billion on the marketing of cigarettes and $547 million on the marketing of smokeless tobacco. Spending on cigarette marketing is 48% higher than in 1998, the year of the Master Settlement Agreement. Expenditures for marketing smokeless tobacco are 277% higher than in 1998.
• Tobacco company expenditures have become increasingly concentrated on marketing efforts that reduce the prices of targeted tobacco products. Such expenditures accounted for approximately 84% of cigarette marketing and more than 77% of the marketing of smokeless tobacco products in 2008.
• The evidence is sufficient to conclude that there is a causal relationship between advertising and promotional efforts of the tobacco companies and the initiation and progression of tobacco use among young people.
• The evidence is suggestive but not sufficient to conclude that tobacco companies have changed the packaging and design of their products in ways that have increased these products’ appeal to adolescents and young adults.
• The tobacco companies’ activities and programs for the prevention of youth smoking have not demonstrated an impact on the initiation or prevalence of smoking among young people.
• The evidence is sufficient to conclude that there is a causal relationship between depictions of smoking in the movies and the initiation of smoking among young people.

Chapter 6. Efforts to Prevent and Reduce Tobacco Use Among Young People

• The evidence is sufficient to conclude that mass media campaigns, comprehensive community programs, and comprehensive statewide tobacco control programs can prevent the initiation of tobacco use and reduce its prevalence among youth.
• The evidence is sufficient to conclude that increases in cigarette prices reduce the initiation, prevalence, and intensity of smoking among youth and young adults.
• The evidence is sufficient to conclude that school-based programs with evidence of effectiveness, containing specific components, can produce at least short-term effects and reduce the prevalence of tobacco use among school-aged youth.
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• Cite this Page National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. Preventing Tobacco Use Among Youth and Young Adults: A Report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention (US); 2012. 1, Introduction, Summary, and Conclusions.
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