smoking cessation research studies

• Research article
• Open access
• Published: 29 September 2023

Non-pharmacological interventions for smoking cessation: analysis of systematic reviews and meta-analyses

• Tao Nian 1 , 2 ,
• Kangle Guo 1 , 2 ,
• Wendi Liu 1 , 2 ,
• Xinxin Deng 1 , 2 ,
• Xiaoye Hu 1 ,
• Meng Xu 1 , 2 ,
• Fenfen E 1 , 2 ,
• Ziyi Wang 1 , 2 ,
• Guihang Song 3 ,
• Kehu Yang 1 , 2 , 4 ,
• Xiuxia Li 1 , 2 &
• Wenru Shang 1 , 4 , 5  

BMC Medicine volume  21 , Article number:  378 ( 2023 ) Cite this article

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Although non-pharmacological smoking cessation measures have been widely used among smokers, current research evidence on the effects of smoking cessation is inconsistent and of mixed quality. Moreover, there is a lack of comprehensive evidence synthesis. This study seeks to systematically identify, describe, and evaluate the available evidence for non-pharmacological interventions in smoking populations through evidence mapping (EM), and to search for best-practice smoking cessation programs.

A comprehensive search for relevant studies published from the establishment of the library to January 8, 2023, was conducted in PubMed, Web of Science, Embase, the Cochrane Library, CNKI, CBM, Wan Fang, and VIP. Two authors independently assessed eligibility and extracted data. The PRISMA statement and AMSTAR 2 tool were used to evaluate the report quality and methodology quality of systematic reviews/meta-analyses (SRs/MAs), respectively. Bubble plots were utilized to display information, such as the study population, intervention type, evidence quality, and original study sample size.

A total of 145 SRs/MAs regarding non-pharmacological interventions for smoking cessation were investigated, with 20 types of interventions identified. The most commonly used interventions were cognitive behaviour education ( n  = 32, 22.07%), professional counselling ( n  = 20, 13.79%), and non-nicotine electronic cigarettes (e-cigarettes) ( n  = 13, 8.97%). Among them, counselling and behavioural support can improve smoking cessation rates, but the effect varies depending on the characteristics of the support provided. These findings are consistent with previous SRs/MAs. The general population ( n  = 108, 74.48%) was the main cohort included in the SRs/MAs. The total score of PRISMA for the quality of the reports ranged from 8 to 27, and 13 studies (8.97%) were rated as high confidence, and nine studies (6.21%) as moderate confidence, in the AMSTAR 2 confidence rating.

Conclusions

The abstinence effect of cognitive behaviour education and money incentive intervention has advantages, and non-nicotine e-cigarettes appear to help some smokers transition to less harmful replacement tools. However, the methodological shortcomings of SRs/MAs should be considered. Therefore, to better guide future practice in the field of non-pharmacological smoking cessation, it is essential to improve the methodological quality of SRs and carry out high-quality randomized controlled trials (RCTs).

Peer Review reports

At present, tobacco use remains a preventable factor in the occurrence and development of non-communicable diseases, including cardiovascular and respiratory diseases and cancer, and a leading cause of death. In recent years, there has been a relative decline in tobacco use among persons aged 15 years and older, and at the global level, countries are on track to achieve a 22% relative reduction in tobacco use by 2025 [ 1 ]. However, despite a steady decline in the number of smokers worldwide, tobacco still kills more than seven million people every year [ 1 ]. Smoking has become an increasingly prominent public health problem. Some studies have shown that quitting reduces the risk of major chronic diseases in smokers and can also slow the progression of chronic obstructive pulmonary disease and cancer and extend life expectancy [ 2 , 3 ]. Helping smokers quit is considered to be the most effective way to reduce the health burden in the short to medium term, while seeking best practice smoking cessation programs would be a cost-effective option, to some extent reducing the heavy economic burden caused by smoking globally [ 4 , 5 ].

Rigotti et al. classified smoking cessation interventions into psychological and behavioural interventions, drug treatment, and other interventions [ 6 ]. Among them, the significance of non-pharmacological smoking cessation has become increasingly evident. Siu et al. concluded that behavioural interventions alone, such as in-person behavioural support and counselling, telephone counselling, and self-help materials, can significantly improve the success rate of tobacco cessation [ 7 ]. Ussher et al. demonstrated that abstinence rates were significantly higher in the physically active group than in the control group, especially at the end of the exercise, showing significant benefits [ 8 ]. This study only included non-pharmacological intervention research. In addition, we also added an electronic cigarette (e-cigarette) (no nicotine, treatments with nicotine components are classified as drug therapy) intervention [ 6 ]. Although non-nicotine e-cigarettes have not been approved as a smoking cessation agent by the Center for Drug Evaluation and Research (CDER) of the US Food and Drug Administration (FDA), they have been promoted for smoking cessation and multiple studies have been published. Meanwhile, analysing the effects of non-nicotine e-cigarettes on withdrawal adds to the range of non-pharmacological smoking cessation studies.

Evidence mapping(EM) is a new comprehensive evidence research method that systematically collects existing evidence in relevant research fields, conducts comprehensive analysis and scientific evaluation, and integrates, condenses, and concisely and intuitively presents the research status, existing problems, development direction, and evidence gap [ 9 , 10 ]. Unlike umbrella reviews/systematic reviews, which typically involve narrow research questions, the EM describes the volume, design, and characteristics of studies in broad subject areas, and their breadth helps identify research hotspots and evidence gaps while identifying best practice plans [ 11 , 12 , 13 ]. Meanwhile, the EM should be included in the literature on high-quality research design. The strength of evidence from SRs/MAs is generally superior to that of single original studies, which is an important basis for the gold standard and practice guidelines for efficacy evaluation [ 14 ].

This study, which we plan to include in SRs/MAs, aims to systematically identify, describe, and evaluate available evidence for non-pharmacological interventions in smoking populations using an evidence atlas approach and to identify best practice smoking cessation programs, and research hotspots. To analyse trends in the risk of bias in the included SRs/MAs, we assessed the current state of knowledge and identified evidence gaps for further work.

The present study was performed according to the guidelines of Preferred Reporting Items for Overviews of Systematic Reviews including a harms checklist (PRIO-harms) [ 15 ]. This evidence map was registered at the OSF Registries (Registration DOI: https://doi.org/10.17605/OSF.IO/R4BZC ).

Data sources and search strategy

In this study, SRs/MAs of smoking cessation studies were comprehensively searched between January 1, 1951, and December 31, 2022 in databases Medline, Web of Science, Embase, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, China National Knowledge Infrastructure (CNKI), China Biology Medicine (CBM), Wan Fang, and VIP Database for Chinese Technical Periodicals (VIP). The search keywords included the following: (smok OR cigarette OR tobacco OR nicotine OR cessation OR quit OR Abstinence OR Stop) AND (systematic review OR Overview OR meta-analysis OR meta analyses). The complete search strategies are described in Additional File 1 : Table S1 [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ]. The most recent search was conducted on January 8, 2023, which was a catch-up search.

We also searched the Cochrane Tobacco Addiction Group Specialized Register, checked the list of references for eligible studies by hand-searching at the time of full-text reading, and consulted experts in the field to identify any relevant forthcoming or unpublished studies.

Eligibility criteria

Based on the principle of Participants, Interventions, Control, Outcomes, and Study Designs (PICOS), we developed the inclusion and exclusion criteria. The following inclusion criteria were applied. First, we included the study population according to the definition of smoking population by the World Health Organization (WHO) International Classification of Diseases 11 (ICD-11), which is not limited by age, sex, and occupation [ 16 ]. Second, we deemed the following intervention strategy eligible for inclusion: (a) psychology and behavioural intervention (e.g., cognitive behavioural education, exercise); (b) non-nicotine e-cigarettes; and (c) other interventions (e.g., acupuncture, meditation). Eligible controls were blank, usual care, or other interventions other than those described above. Third, the outcome was to assess the effectiveness or adverse events of non-pharmacological therapy for smoking cessation. Fourth, the included study design was SRs/MAs.

The following studies were excluded: (a) smoking cessation studies with pharmacotherapy-related interventions; (b) nicotine-containing e-cigarettes; (c) no smoking cessation effect was reported in the study outcomes; (d) case reports, review articles, protocols, letters, abstracts, comments, and studies that did not report data; and (e) duplicate reports of the same study.

Data extraction and management

All the retrieved articles were imported into EndNote X 9.0 software. After excluding duplicate publications, two authors (T.N. and KL.G.) independently screened and extracted data according to the inclusion and exclusion criteria. Disagreements were resolved through a discussion or by consulting a third member (M.X.) with vast experience in the field [ 17 ]. After the retrieved literature was deduplicated by EndnoteX9 software, the two authors first screened the studies that might meet the criteria by reading the titles and abstracts according to the inclusion and exclusion criteria and carried out full-text screening of the uncertain studies to determine the final inclusion of all the studies that met the criteria. Data extraction tables were designed using Microsoft Excel 2019 software, and the following information was extracted: first author name, publication year, country, number of RCTs included, interventions, study population, research design, and outcomes of each included study.

Quality assessment

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and A Measurement Tool to Assess Systematic Review 2 (AMSTAR 2) tool were used to evaluate the reporting quality and methodological quality included in SRs/MAs respectively [ 18 , 19 ]. It was included independently by two researchers (T.N. and KL.G.), and different opinions were resolved by a third researcher (M.X.).

The PRISMA statement consists of 7 parts and 27 items. Each item is judged according to whether the author reports it or not. A full report is worth one point, a partial report is worth 0.5 points, and no report is worth 0 points. The PRISMA criterion score ≤ 15 was considered to be relatively severe information deficiency, 15–21 was considered to be somewhat defective, and 21–27 was considered to be relatively complete.

AMSTAR 2 considers items 2, 4, 7, 9, 11, 13, and 15 as critical items affecting the preparation and validity of the system evaluation, and the remaining items as non-critical items. A total of 16 items are included, and different items can be judged as “Yes”, “Partial yes”, “No” and “Not applicable”. Finally, the quality levels of high (no or one non-critical area is defective), medium (defect in more than one non-critical area), low (one critical area with or without a non-critical area), and very low (more than one critical area with or without defects in non-critical areas) are calculated. The quality assessment process is conducted online, and the overall quality of the study (“Critical low”, “Low”, “Moderate” and “High”) is automatically generated after the completion of the assessment results [ 20 ].

Data synthesis and statistical analysis

Microsoft Excel 2019 was used to extract and manage the data. The frequency and percentage of descriptive statistics were used to analyse the data and generate numbers. A bar chart was utilized to show the reporting quality and methodological quality results of the included SRs. We used a bubble plot to bring the included SRs/MAs together and display information on four dimensions, including the smoking cessation effect of SR inclusion, quality of evidence, population, and intervention [ 21 ]. Details are as follows: (a) authors’ conclusions (“Effective”, “Likely effective”, “Uncertain” and “Ineffective”) on the x -axis; (b) score from AMSTAR 2 assessment on the y -axis; (c) each bubble represents one SR, the color represents the population, and the size represents the number of people; and (d) the letters on the bubbles represent interventions.

For descriptive purposes, we categorized conclusions reported by authors for each PICO question, into four categories: “Effective”, “Likely effective”, “Uncertain” and “Ineffective”, as in the categorization performed in previous EM [ 22 ]. See Table 1 .

Literature selection

We initially identified 30,228 relevant articles according to the search strategy. Of these, 8738 studies were excluded because of duplication, 21,490 studies were screened by the titles and abstracts, and 485 studies were assessed through the full texts. Finally, 145 SRs/MAs were included in this study [ 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 ]. The literature screening procedure is shown in Fig.  1 .

Study selection flowchart

Study characteristics

Among 145 SRs/MAs, a quantitative synthesis (meta-analysis) accounted for 71.72%. The years of publication of studies were distributed from 1996 to 2022, and a majority of the studies were published after 2015. The years with 10 or more articles were 2017 ( n  = 14, 9.66%), 2019 ( n  = 17, 11.72%), 2021 ( n  = 10, 6.90%), and 2022 ( n  = 15, 10.34%). According to the country of origin of the first author, there are 12 countries with two or more published studies, among which the top three countries are the United Kingdom (UK) ( n  = 47; 32.41%), the United States (US) ( n  = 35; 24.14%) and Australia ( n  = 19; 13.10%). A total of 2670 individual studies were analysed in the included SRs/MAs, and 93 SRs/MAs (64.14%) included more than ten individual studies. In terms of population characteristics, 108 studies (74.48%) included mixed populations (population characteristics were not divided, mixed with various characteristics of the population), special populations including pregnant women ( n  = 9, 6.21%), acquired immunodeficiency syndrome (AIDS) patients ( n  = 3, 2.07%) and other vulnerable groups (referring to those with weak social power and power and difficult living conditions) ( n  = 8, 5.52%). A total of 20 non-pharmacological smoking cessation methods were included in the study. The commonly used intervention measures were cognitive behaviour education ( n  = 32, 22.07%), professional counselling ( n  = 20, 13.79%), and non-nicotine e-cigarette use ( n  = 13, 8.97%). The details are listed in Table 2 .

Reporting quality of the included SRs/MAs

The quality evaluation results of the PRISMA report are shown in Fig.  2 . For the 27 PRISMA items, the theoretical basis (item 3) and research objective (item 4) were well reported, with more than 97% of the SRs/MAs describing these two items in the background introduction. Eight items had reporting rates of more than 80% (items 3, 4, 6, 7, 17, 18, 24, 26), and only three items were less than 50% (items 5, 16, 23). The total PRISMA score for the quality of the included studies ranged from 10 to 27. There were seven articles with a score of less than or equal to 15, 38 articles with a score of more than 15 and less than or equal to 21, and 59 articles with a score of more than 21 and less than or equal to 27. The PRISMA quality appraisal scores are presented in Additional File 1 : Table S2) [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ].

Methodological quality of the included SRs/MAs

The results of the AMSTAR 2 assessment are shown in Fig.  3 . For each AMSTAR 2 item, 5 of 16 items were rated as relatively complete, with reporting rates ≥ 70% (items 1, 5, 6, 11, and 16). A total of 53 studies (36.55%) reported the predefined protocol (item 2), 52 studies (35.86%) provided the reason for inclusion (item 3), 86 studies (59.31%) provided the comprehensive search strategy and supplementary search (item 4), 33 studies (22.76%) provided the reason for exclusion (item 7), 85 studies (58.62%) described the basic characteristics of the research (item 8), 93 studies (64.14%) provided the appropriate risk of bias tools for the reviews (item 9), 15 studies (10.34%) reported to research funding sources (item 10), 59 studies (40.69%) assessed the potential effect of the risk of bias of individual studies (item 12), 81 studies (55.86%) accounted for the risk of bias in individual studies when interpreting the results (item 13), and 80 studies (55.17) provided a satisfactory explanation for heterogeneity in the review results (item 14). Publication bias was explained in 45 studies (31.03%) (item 15). For overall methodological quality, 13 studies (8.97%) were rated as high confidence, ten studies (6.90%) were rated as moderate confidence, and 25 studies (17.24%) were rated as low confidence. Ninety-seven studies (66.90%) were assessed as having very low confidence. The AMSTAR 2 quality appraisal scores are presented in Additional File 1 : Table S3 [ 20 , 21 , 22 , 23 , 24 , 25 , 26 ].

Efficacy outcomes

According to the results of the integrated inclusion studies, 32 SRs/MAs have centered around cognitive behavioural education interventions. As shown in Fig.  4 , after psychological and behavioural intervention in the general population ( n  = 17), 21 of them were “Effective” outcomes, six were “Likely effective” and five were “Uncertain”. Of these studies, three possessed high to moderate evidence quality, while the remaining 14 featured low to very low quality. Moreover, three research results documented smoking cessation in pregnant women, of which two realized “Effective” effects. Studies aimed at elderly patients, AIDS sufferers, and chronic obstructive pulmonary disease (COPD) patients ( n  = 2, n  = 2, and n  = 1, respectively) all delivered “Effective” outcomes, whereas cardiovascular and inpatient cases ( n  = 2 and n  = 2, respectively) generated one “Effective” and one “Likely effective”.

Cognitive behavioural education intervention to quit smoking affects different people

As depicted in Fig.  5 , a total of 39 SRs/MAs were integrated. The results indicated that smoking cessation interventions (including motivational interviews, financial incentives, exercise, mixed psychological interventions, self-help material interventions, and group support) were “Effective” in 14 studies. Of note, vulnerable groups indicated significant effects due to group support and mixed psychological interventions. The smoking cessation effect of pregnant women through exercise and self-help material intervention was effective. Furthermore, nine studies with regard to smoking cessation interventions (including competition motivation, exercise, meditation, group support, mixed psychological intervention, and self-help material intervention) were “Likely effective”. Seven studies noted “Uncertain” outcomes regarding their smoking cessation interventions (involving exercise, group support, hypnosis, motivational interview, and mixed psychological intervention). Finally, nine studies (including disgusting therapy, competition motivation, meditation, exercise, and group support) yielded “Ineffective” results for smoking cessation. As far as methodological quality is concerned, eight studies were classified as being of high to medium quality, while the remaining featured low to very low quality.

Effect of relevant intervention on smoking cessation in different populations

As demonstrated in Fig.  6 , 38 SRs/MAs were incorporated. The results indicated that smoking cessation interventions (including acupuncture, smoking cessation App, professional guidance, and brain stimulation) yielded “Effective” outcomes in 19 studies, of which interventions involving professional consultation with cancer, AIDS, and other hospital patients yielded clear results. Ten studies displayed “Likely effective” results related to smoking cessation interventions (including acupuncture, smoking cessation App, professional consultation, and brain stimulation). Furthermore, three studies about interventions such as acupuncture and smoking cessation Apps were identified as “Uncertain”. Six studies showed that the respective interventions (including acupuncture, smoking cessation App, professional consultation, and smoking reduction) were “Ineffective”. In terms of methodological quality, six had high or medium quality, whereas the remaining had low or very low quality.

As demonstrated in Fig.  7 , a total of 36 SRs/MAs were included, concluding that smoking cessation interventions (including non-nicotine e-cigarettes, Internet consultation, SMS consultation, and smoke-free policies) effectuated an “Effective” outcome in 21 studies. Six studies revealed that such interventions (again, incorporating non-nicotine e-cigarettes, online consultancy, and smoke-free policies) constituted “Likely effective” results; six rendered an “Uncertain” verdict; and three studies concluded that they were “Ineffective”. Of these studies, four studies featured high to medium methodological quality, while the others were low to very low.

Summary of the main findings

The EM can amplify the comprehension of a specific field’s direction and trend. This study applied it to render the four-dimensional representation of included SRs/MAs (methodological quality, smoking cessation effects, interventions, and population), compare the variation in smoking cessation effects among different populations and interventions, and delve into treatment effects and study quality. The research publications in the past decade have been at a high level, mainly reviewed and analysed by British and American scholars, and it is a hot research topic in the treatment of persistent smokers. We collected data from 145 SRs/MAs studies distributed between 1996 and 2022, a large number of which reflect the growing therapeutic potential value and interest in non-pharmacotherapy interventions in smoking populations. Of the various interventions observed, results determined that 51.72% of studies regarded them as effective in facilitating persistent smokers quitting, 31.38% were likely to be effective, 14.48% were uncertain, and 12.41% were ineffective.

We ascertained that several abstinence measures, such as cognitive behavioural education, professional counselling advice, and motivational interviews, were efficacious in raising smokers’ cognizance of the connection between smoking and illness through various face-to-face avenues, thereby reducing smoking rates [ 129 , 168 , 169 ]. Cognitive behavioural education can provide the population with a well-developed smoking cessation program, a proper understanding of nicotine addiction, and skills to cope with cravings and negative emotions to maintain abstinence compared to conventional controls. The smoking cessation effect of behavioural interventions shown in our study is consistent with the outcomes of past network meta-analyses [ 170 ]. Notably, 88% of the studies on the effect of cognitive behavioural education on withdrawal in the general population were “Effective” or “Likely effective”. The impacts of professional counselling are likewise noteworthy, especially in the short to mid-term, echoing the findings of Lancaster et al. [ 171 ]. These observations imply that its efficiency may be mirrored in the readiness and powerful motivation of smokers themselves, compelling them to obtain information regarding smoking cessation through consulting professional doctors [ 172 ]. Conversely, Lindson et al. demonstrated that motivational interviews are more suitable for those with low motivation to quit smoking [ 169 ]. Moreover, the implementation of motivational interviews is also critical. The effect of motivational interviews conducted by nurses is not significant, and the motivational interviews provided by general practitioners will bring more benefits than those provided by nurses or consultants. This may be because general practitioners and smokers are already familiar with and have established a good personal relationship, and this state is more suitable for this approach [ 138 ]. However, this inference is based on a few relatively small studies and must not be exaggerated. Of course, in addition to smoking counselling, smoking cessation rates can be monitored for controllable smoking risk factors. As early as 2005, the Chinese government ratified the WHO Framework Convention on Tobacco Control, which was successfully implemented in major cities such as Shanghai and Beijing, significantly mitigating smoking rates in these areas. However, implementation capacity and supervision fluctuate substantially among provinces and regions (urban and rural), resulting in varying smoking cessation effects [ 173 ]. Furthermore, prohibiting tobacco sponsorship and advertising exposure, disallowing sales to minors, escalating taxes and prices, and being informed on the dangers of smoking have collectively contributed to diminishing smoking rates to some degree [ 174 ].

With the burgeoning prevalence of the Internet, smoking cessation techniques rooted online have aroused remarkable interest. Most of the relevant literature we searched and included was published in the past 10 years. Originally, interventions primarily entailed network consultations and SMS messaging. In agreement with previous MAs, the evidence indicates that the majority of these modalities demonstrate some degree of abstinence effect on smokers [ 170 ]. Notably, active telephone counselling has exhibited efficacy [ 88 ]. This bidirectional interactive intervention, such as text messaging and other up-to-date information and communication technologies, allows smokers to acquire smoking cessation information via the web or on the phone and text messages, and through asynchronous and real-time messaging with support networks, in addition to reducing barriers such as cost, location or time/schedule constraints, promoting the implementation of smoking cessation measures [ 175 ]. Furthermore, extended communication amplifies user participation in smoking cessation programs, can efficaciously boost the recognition of smoking cessation, and diminish smoking and corporeal and mental dependence on tobacco [ 176 , 177 ]. Currently, with the emerging trend of smoking cessation Apps, evidence of beneficial effects has been overwhelmingly restricted to follow-up of 6 months or less, yet there is scant proof of long-term abstinence through a smoking cessation App. Do et al. conjecture that web-based and structured text messaging aids may be more likely to increase long-term smoking cessation effects [ 163 ].

Non-nicotine e-cigarette interventions are similar to but do not fall under the category of alternative therapy, and aim to maintain smoking cessation habits, using the stimulation of smoking behaviour to reduce withdrawal symptoms when quitting [ 178 , 179 ]. Batra et al. indicated that nicotine addiction among smokers is a complex behaviour that depends not only on environmental and inherited components but also on psychological features and habits [ 180 ]. Non-nicotine e-cigarette intervention maintains the habit of smoking, is safer than cigarettes, and reduces irritability, depression, and withdrawal symptoms of craving [ 179 ]. However, in our findings, the smoking cessation effectiveness of non-nicotine e-cigarettes varied according to the characteristics of the population, which is consistent with the results of the review by Hartmann et al. [ 181 ]. The use of non-nicotine e-cigarettes has helped reduce the use of paper cigarettes to some extent, but reducing smoking may not increase the time it takes current smokers to quit, and most circumstantial evidence has found that reducing smoking is associated with the likelihood of quitting in the future [ 109 ].

We also grouped other non-pharmacological interventions. The results of the investigations into the influence of exercise on abstinence were contradictory and mostly indicated a temporary effect at the end of the exercise [ 182 , 183 ]. Although exercise does not generally increase the length of time for quitting smoking, it has the potential to offer benefits. Daley et al. uncovered that exercise can aid in lessening the development of many clinical disorders, abating the risk of future disease, and decreasing withdrawal symptoms, such as anxiety and mood swings resulting from giving up smoking [ 184 , 185 , 186 ]. The intervention of motivation mechanisms (monetary motivation or competition motivation) is generally arduous to effectuate due to the complexity of the original research design and appraisal. Moreover, confounding factors such as income, gender, and occupation contribute to a high risk of selective bias leading to conflicting research outcomes [ 42 , 187 ]. Smoke-free policies reduce the prevalence of tobacco use in the population by reducing smokers’ consumption and augmenting attempts to quit, thus increasing the number of successful quitters [ 72 ]. However, the potency of smoking cessation is usually undermined by the location in which it is conducted [ 37 ]. However, we note that although most of the conclusions extracted from SRs/MAs are classified as “Effective” or “Likely effective”, the evidence for non-pharmacological smoking cessation effects interventions is not entirely the same. The included SRs/MAs claimed inconsistent or even contradictory conclusions about some of the same interventions, such as match motivation, team support, aversion therapy, meditation, and acupuncture. Because the inclusion of SRs is limited, there is insufficient evidence that they are effective forms of treatment. In fact, for the effect of smoking cessation that we reflected in the EM, some studies could not draw firm conclusions despite randomized controlled trials.

Because of the particularity of the population, different populations have different sensitivities to the same interventions. Studies on inpatients, such as AIDS patients, cardiovascular patients, and COPD patients, indicate improved adherence to smoking cessation among those who partake in professional physician counselling and receive cognitive behavioural education from nursing staff [ 60 , 98 , 138 ]. A study performed by Stead et al. revealed that people suffering from co-morbidities have increased levels of anxiety and that advice provided by medical personnel may partially mitigate their apprehensive state [ 100 ]. Furthermore, medical providers should strive to establish a good connection with these smokers. Concerning vulnerable groups, evidence suggests that a team-based approach to smoking cessation produces more significant results, likely attributed to the social and psychological support provided in those circumstances and the resulting betterment of mental health [ 46 ]. de Kleijn et al. analysed the effect of school-centered intervention combined with mass media intervention by conducting experiments on 12- to 13-year-old female students and the results were significant [ 188 ]. The analysis may be that children in this age group, especially girls, are highly influenced by their peers [ 189 ].

Although the EM can only provide an overview of a wide range of research areas, the results suggest that there are more valid or potentially valid conclusions than there are uncertain or inefficient ones. However, the quality of the included systematic review studies was mostly low or very low. According to PRISMA, the reporting quality of the included quantitative SRs/MAs has several shortcomings. There were seven SRs with relatively serious insufficient information and 38 SRs with certain defects. The main defects were not clearly stated in the title that the research was a systematic review or meta-analysis; no registered research proposal or report in the paper; failure to describe possible bias in the method part and analysis in the results part; and heterogeneity arising from data consolidation was not analysed. The reported shortcomings of qualitative systematic reviews focused on registration protocols and possible bias in each study. In addition, attention should be given to several limitations related to the quality of the methodology included in the SR, particularly the seven important evaluation areas. Under AMSTAR, 2,97 SRs/MAs were assessed as having very low confidence and 25 were assessed as having low confidence, mainly due to the failure to provide content in the following key evaluation areas, prestudy protocols; no list of excluded studies, and reasons for exclusion. The possibility of publication bias was not adequately investigated after quantitative consolidation, and the effect of publication bias on the results was discussed. In addition, items 3, 10, and 12 also need to be improved. All of the above limitations affect confidence in SR inclusion.

Evidence gaps and future research directions

The results of the evidence atlas suggest that there may be gaps in non-pharmacological smoking cessation interventions in smokers (1). The methodological quality of the studies was generally low. The quality of research is important for the practice and promotion of intervention measures and scientific research results. The EM results showed that the included SRs/MAs were of low quality, with only 9.23% of the articles rated as high-quality studies. The new study should correct this to some extent. Depending on the quality of the evidence, future reviews should register research protocols in advance and take full account of heterogeneity and publication bias arising from data consolidation. (2) At present, most research on the effectiveness of the intervention of existing contradictions, mainly includes independent intervention, reducing smoking, money motivation, competition motivation, smoke-free policies, team support, mixed psychological intervention, motivated interviews, quit App consulting, exercise, aversion therapy intervention, non-nicotine e-cigarettes, acupuncture intervention, hypnosis, and meditation. This requires further high-quality original studies and SRs/MAs in the future to clarify their effects. (3) As the basis of clinical practice guidelines, systematic evaluation/meta-analysis is extremely important for the practice of intervention. However, the detailed implementation process of intervention, such as intervention time and intensity, is rarely involved in systematic evaluation/meta-analysis, which affects the promotion and implementation of the intervention. (4) Relapse often occurs in the process of quitting smoking, and there are many reasons for relapse. Currently, there is a lack of research, which needs to be further explored by high-quality research in the future.

Strengths and limitations

This study has several strengths. First, we conducted a comprehensive search from ten databases to identify SRs/MAs associated with non-pharmacological intervention for smoking cessation. Second, we assessed the reporting and methodological quality of the included SRs using PRISMA and AMSTAR 2 tools. Third, the EM, a visualization method, was utilized to present the trends and gaps in the risk of bias of SRs, as well as relationships between evidence outcomes and populations and interventions.

Our study has several limitations. First, this study only included a SRs/MAs, and excluded other study designs (such as randomized controlled trials, cohort studies, and case‒control studies. Second, there were some differences in the clinical trial inclusion criteria of each SR: some included retrospective studies instead of real prospective randomized controlled trials. Third, our results are based only on publications published before January 8, 2023, and need to be updated as new studies emerge. Fourth, the language was restricted to English or Chinese. Literature reviews in other languages were not included, causing a potential language bias.

In conclusion, the quality of non-pharmacological smoking cessation interventions for smokers is generally low. The same interventions have different effects on smoking cessation in different studies, and even opposite conclusions have been drawn. Future researchers still need to pay attention to differences in the effectiveness of different interventions, intensity and duration, adverse effects of interventions, and methodological quality of studies.

Availability of data and materials

Not applicable.

Abbreviations

Acquired immunodeficiency syndrome

A Measurement Tool to Assess Systematic Review-2

Application

China Biology Medicine

Center for Drug Evaluation and Research

Coronary heart disease

Cumulative Index to Nursing and Allied Health Literature

China National Knowledge Infrastructure

Chronic obstructive pulmonary disease

Electronic cigarette

Evidence mapping

Food and Drug Administration

International Classification of Diseases 11

Participants, Interventions, Control, Outcomes, and Study Designs

Preferred Reporting Items for Overviews

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Randomized controlled trials

Systematic Reviews/Meta-Analysis

United Kingdom

United States

VIP Database for Chinese Technical Periodicals

World Health Organization

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Acknowledgements

The authors would like to thank all members of the Evidence-Based Medicine Center at Lanzhou University for their help with this study.

This study was supported by the National Social Science Fund of China (No. 19ZDA142); Capital Medical University National Medical Security Research Institute Open Topic Project: Research on Medical Insurance Service Quality Evaluation System Based on DIP (No. YB2021B07); Fundamental Research Funds for the Central Universities (lzujbky-2021-ct06, lzujbky-2021-kb22).

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Additional file 1: table s1..

Search Strategy.  Table S2. PRISMA quality appraisal scores.  Table S3. AMSTAR 2 quality appraisal scores.

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Nian, T., Guo, K., Liu, W. et al. Non-pharmacological interventions for smoking cessation: analysis of systematic reviews and meta-analyses. BMC Med 21 , 378 (2023). https://doi.org/10.1186/s12916-023-03087-z

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• Non-pharmacological approaches
• Smoking cessation
• Evidence map
• Systematic reviews/meta-analyses

BMC Medicine

ISSN: 1741-7015

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• Introduction
• Evidence for Adults
• Evidence for Pregnant Women
• Conclusions
• Article Information

Evidence reviews for the US Preventive Services Task Force (USPSTF) use an analytic framework to visually display the key questions that the review will address to allow the USPSTF to evaluate the effectiveness and safety of a preventive service. The questions are depicted by linkages that relate interventions and outcomes. A dashed line indicates a health outcome that immediately follows an intermediate outcome. Additional Information available in the USPSTF Procedure Manual. 7

eMethods A. Literature Search Strategies for Overview of Reviews: Tobacco Cessation in Adults

eMethods B. Literature Search Strategies for Primary Literature: Tobacco Cessation in Adults: Electronic Cigarettes

eMethods C. Literature Search Strategies for Primary Literature: Tobacco Cessation in Adults: Pharmacologic Interventions in Pregnant Women

eFigure 1. Literature Flow Diagram, Tobacco Cessation in Adults: Overview of Reviews

eFigure 2. Literature flow diagram, Tobacco Cessation in adults: Electronic Cigarettes

eFigure 3. Literature Flow Diagram, Tobacco Cessation in Adults: Pharmacotherapy Interventions Among Pregnant Women

eFigure 4. NRT Interventions in Placebo-Controlled Trials for Smoking Cessation During Pregnancy, Smoking Cessation (KQ2)

eTable 1. Inclusion and Exclusion Criteria

eTable 2. Study-Design Quality Rating Criteria

eTable 3. Study and Population Characteristics for Evidence on the Use of Electronic Cigarettes for Tobacco Cessation, Sorted by KQ

eTable 4. Smoking Cessation Results at 6 or More Months (KQ2) for Electronic Cigarettes for Tobacco Cessation, by Author

eTable 5. Primary Evidence on Pharmacotherapy Among Pregnant Individuals: Study and Population Characteristics, by Study Design

eTable 6. Summary of Perinatal Health Outcome Results (KQ1) of Behavioral Tobacco Cessation Interventions Among Pregnant Women, Psychosocial Interventions Versus Any Control (Within Chamberlain, 2017 Review27)

eTable 7. Summary of Tobacco Cessation Outcomes (KQ2) of Behavioral Tobacco Cessation Interventions Among Pregnant Women (Within Chamberlain, 2017 Review27)

eReferences

• USPSTF Recommendation: Interventions for Tobacco Smoking Cessation in Adults JAMA US Preventive Services Task Force January 19, 2021 This 2021 US Preventive Services Task Force Recommendation Statement recommends that clinicians ask all adults about tobacco use, advise them to stop using tobacco, and provide behavioral interventions and pharmacotherapy for cessation (A recommendation) and concludes that evidence is insufficient to assess the benefits and harms of tobacco cessation pharmacotherapy in pregnant persons and e- cigarettes for tobacco cessation in any adult (I statement). US Preventive Services Task Force; Alex H. Krist, MD, MPH; Karina W. Davidson, PhD, MAS; Carol M. Mangione, MD, MSPH; Michael J. Barry, MD; Michael Cabana, MD, MA, MPH; Aaron B. Caughey, MD, PhD; Katrina Donahue, MD, MPH; Chyke A. Doubeni, MD, MPH; John W. Epling Jr, MD, MSEd; Martha Kubik, PhD, RN; Gbenga Ogedegbe, MD, MPH; Lori Pbert, PhD; Michael Silverstein, MD, MPH; Melissa A. Simon, MD, MPH; Chien-Wen Tseng, MD, MPH, MSEE; John B. Wong, MD
• A Comprehensive Approach to Increase Adult Tobacco Cessation JAMA Editorial January 19, 2021 Brenna VanFrank, MD, MSPH; Letitia Presley-Cantrell, PhD
• USPSTF Recommendation: Interventions to Promote Tobacco Cessation JAMA JAMA Patient Page January 19, 2021 This JAMA Patient Page summarizes the USPSTF 2020 guideline recommending that physicians ask all adults about tobacco use, advise them to stop using tobacco, and provide behavioral interventions and drugs shown effective for stopping cigarette and other tobacco use. Jill Jin, MD, MPH
• COVID-19 and the “Lost Year” for Smokers Trying to Quit JAMA Medical News & Perspectives May 18, 2021 This Medical News article describes a reduction in smoking cessation attempts during the COVID-19 pandemic. Mary Chris Jaklevic, MSJ

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Patnode CD , Henderson JT , Coppola EL , Melnikow J , Durbin S , Thomas RG. Interventions for Tobacco Cessation in Adults, Including Pregnant Persons : Updated Evidence Report and Systematic Review for the US Preventive Services Task Force . JAMA. 2021;325(3):280–298. doi:10.1001/jama.2020.23541

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Interventions for Tobacco Cessation in Adults, Including Pregnant Persons : Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

• 1 Kaiser Permanente Evidence-based Practice Center, Center for Health Research, Kaiser Permanente, Portland, Oregon
• 2 Center for Healthcare Policy and Research, University of California, Davis, Sacramento
• Editorial A Comprehensive Approach to Increase Adult Tobacco Cessation Brenna VanFrank, MD, MSPH; Letitia Presley-Cantrell, PhD JAMA
• US Preventive Services Task Force USPSTF Recommendation: Interventions for Tobacco Smoking Cessation in Adults US Preventive Services Task Force; Alex H. Krist, MD, MPH; Karina W. Davidson, PhD, MAS; Carol M. Mangione, MD, MSPH; Michael J. Barry, MD; Michael Cabana, MD, MA, MPH; Aaron B. Caughey, MD, PhD; Katrina Donahue, MD, MPH; Chyke A. Doubeni, MD, MPH; John W. Epling Jr, MD, MSEd; Martha Kubik, PhD, RN; Gbenga Ogedegbe, MD, MPH; Lori Pbert, PhD; Michael Silverstein, MD, MPH; Melissa A. Simon, MD, MPH; Chien-Wen Tseng, MD, MPH, MSEE; John B. Wong, MD JAMA
• JAMA Patient Page USPSTF Recommendation: Interventions to Promote Tobacco Cessation Jill Jin, MD, MPH JAMA
• Medical News & Perspectives COVID-19 and the “Lost Year” for Smokers Trying to Quit Mary Chris Jaklevic, MSJ JAMA

Importance   It has been estimated that in 2018 nearly 20% of adults in the US were currently using a tobacco product.

Objective   To systematically review the effectiveness and safety of pharmacotherapy, behavioral interventions, and electronic cigarettes for tobacco cessation among adults, including pregnant persons, to inform the US Preventive Services Task Force.

Data Sources   PubMed, PsycInfo, Database of Abstracts of Reviews of Effects, Cochrane Database of Systematic Reviews, Centre for Reviews and Dissemination of Health Technology Assessment; surveillance through September 25, 2020.

Study Selection   Systematic reviews of tobacco cessation interventions and randomized clinical trials that evaluated the effects of electronic cigarettes (e-cigarettes) or pharmacotherapy among pregnant persons.

Data Extraction and Synthesis   Independent critical appraisal and data abstraction; qualitative synthesis and random-effects meta-analyses.

Main Outcomes and Measures   Health outcomes, tobacco cessation at 6 months or more, and adverse events.

Results   Sixty-seven reviews addressing pharmacotherapy and behavioral interventions were included as well as 9 trials (N = 3942) addressing e-cigarettes for smoking cessation and 7 trials (N = 2285) of nicotine replacement therapy (NRT) use in pregnancy. Combined pharmacotherapy and behavioral interventions (pooled risk ratio [RR], 1.83 [95% CI, 1.68-1.98]), NRT (RR, 1.55 [95% CI, 1.49-1.61]), bupropion (RR, 1.64 [95% CI, 1.52-1.77]), varenicline (RR, 2.24 [95% CI, 2.06-2.43]), and behavioral interventions such as advice from clinicians (RR, 1.76 [95% CI, 1.58-1.96]) were all associated with increased quit rates compared with minimal support or placebo at 6 months or longer. None of the drugs were associated with serious adverse events. Five trials (n = 3117) reported inconsistent findings on the effectiveness of electronic cigarettes on smoking cessation at 6 to 12 months among smokers when compared with placebo or NRT, and none suggested higher rates of serious adverse events. Among pregnant persons, behavioral interventions were associated with greater smoking cessation during late pregnancy (RR, 1.35 [95% CI, 1.23-1.48]), compared with no intervention. Rates of validated cessation among pregnant women allocated to NRT compared with placebo were not significantly different (pooled RR, 1.11 [95% CI, 0.79-1.56], n = 2033).

Conclusions and Relevance   There is strong evidence that a range of pharmacologic and behavioral interventions, both individually and in combination, are effective in increasing smoking cessation in nonpregnant adults. In pregnancy, behavioral interventions are effective for smoking cessation, but data are limited on the use of pharmacotherapy for smoking cessation. Data on the effectiveness and safety of electronic cigarettes for smoking cessation among adults are also limited and results are inconsistent.

Despite progress in reducing the use of tobacco products by US adults, in 2019 an estimated 20.8% of adults in the US currently used any tobacco product and there are persistent differences in rates of smoking by age, sex, and race/ethnicity. 1 A large range of pharmacologic and behavioral methods are available to help adults quit tobacco use 2 ; however in a 2015 survey, among those who tried quitting in the previous year, only 31.2% reported using evidence-based cessation treatments and 7.4% were successful in quitting. 3

In 2015, the US Preventive Services Task Force (USPSTF) issued 4 recommendations related to tobacco cessation interventions among adults. Two A recommendations were given for behavioral and pharmacotherapy interventions for adults and for behavioral interventions for pregnant women, and 2 I statements were issued: one for pharmacotherapy interventions for pregnant women and one on the use of electronic cigarettes (e-cigarettes) for tobacco cessation among adults and pregnant women. 4 The objective of this review was to inform updated recommendations by the USPSTF.

This is an update of a 2015 overview of reviews that supported the 2015 USPSTF recommendation. 5 , 6 An analytic framework and 3 key questions (KQs) guided the review ( Figure ). Consistent with the 2015 review, an overview of reviews method was primarily used for this update. However, given the insufficient evidence found in 2015, original searches and syntheses of primary evidence were conducted for the benefits and harms of e-cigarettes for smoking cessation and for the benefits and harms of pharmacologic smoking cessation interventions among pregnant women. Details are available in the full report. 8 All main results presented in the full report are also presented in this article; more detailed methods, including review selection and determination of overall credibility and quality of individual reviews and studies, and additional effect estimates for specific types of interventions and comparative effectiveness outcomes, are provided in the full report.

Three separate literature searches were conducted (eMethods in the Supplement ). All searches were restricted to articles in the English language published since January 2014. For reviews, the following databases were searched through April 2019: PubMed, PsycINFO, the Database of Abstracts of Reviews of Effects, the Cochrane Database of Systematic Reviews (CDSR), and the Centre for Reviews and Dissemination Health Technology Assessment. For primary evidence on e-cigarettes, the CDSR, Cochrane Central Register of Controlled Clinical Trials (CENTRAL), PsycInfo, PubMed, and Scopus were searched through May 2020. For studies of pharmacotherapy tobacco cessation interventions among pregnant women, Medline, CENTRAL, PubMed, and PsycInfo were searched through May 2020. Ongoing surveillance for relevant primary literature and Cochrane systematic reviews was completed through September 25, 2020.

Two researchers independently reviewed all identified abstracts and full-text articles against prespecified eligibility criteria (eTable 1 in the Supplement ). Studies were included if they were systematic reviews, with or without meta-analysis, that examined the effectiveness of tobacco cessation interventions for adults. Interventions targeting cessation of any tobacco product, including e-cigarettes, were included and reviews that focused on specific interventions (eg, nicotine replacement therapy [NRT], group counseling) and specific subpopulations (eg, persons with serious mental illness) were eligible. Reviews published by Cochrane and non-Cochrane reviews were included. Narrative (nonsystematic) reviews and other overviews of reviews were excluded. Only the most recent version of updated reviews was included. Separate inclusion criteria were outlined when considering primary evidence related to e-cigarettes and pharmacotherapy interventions among pregnant women (eTable 1 in the Supplement ).

One reviewer completed the AMSTAR-2 (Assessment of Multiple Systematic Reviews 2) tool 9 to rate the credibility of the systematic reviews under consideration for inclusion, and a second reviewer provided an independent assessment using the same tool for all reviews rated critically low. For primary studies, 2 reviewers independently assessed the risk of bias of included evidence using study-design specific criteria. Each review and study were assigned a quality rating of “good,” fair,” or “poor” according to the USPSTF study design–specific criteria (eTable 2 in the Supplement ). 7 Reviews rated as having critically low credibility and primary studies rated as poor quality were excluded. Data from each included review and primary study were abstracted into detailed abstraction forms using DistillerSR. For all included evidence, one reviewer completed primary data abstraction and a second reviewer checked all data for accuracy and completeness.

Given the large number of reviews that met eligibility criteria and the overlapping scope and evidence between many of them, a method was developed to identify 1 or more reviews within each population and intervention group that represented the most current and applicable evidence. These reviews served as the basis for the main findings. All other reviews were examined for complementary or discordant findings. Pooled point estimates presented in the included reviews were reported when appropriate; none of the individual study evidence was reanalyzed. Data from trials of e-cigarette use were not meta-analyzed, given the few number of studies and data reporting. Methods for the meta-analyses of data from trials of pharmacotherapy among pregnant women are described in the full evidence report.

For the overview of reviews method, the strength of the overall body of evidence assigned within the primary systematic review was reported. In most cases, these grades were based on the Grading of Recommendations Assessment, Development and Evaluation working group definitions, which consider study limitations, consistency of effect, imprecision, indirectness, and publication bias. Where strength of evidence grades were not available, including for the primary evidence syntheses, an overall strength of evidence grade was assigned based on consensus discussions involving at least 2 reviewers. 10

This review addressed 2 populations of interest: the general adult population and pregnant women. Within each population, results are organized by KQ.

For the overview of reviews, investigators reviewed 1173 abstracts and 210 full-text articles for possible inclusion for all KQs (eFigure 1 in the Supplement ). Sixty-four reviews were identified that met eligibility criteria, including those among an unselected population of adults and those limited to a specific subgroup of adults ( Table 1 ). 11 - 53 , 57 - 77 Thirty-two reviews were designated as primary reviews. 11 - 16 , 18 - 20 , 22 , 24 - 30 , 32 - 34 , 38 , 41 , 43 , 45 , 46 , 48 - 53 , 78 Eleven additional reviews had overlapping evidence with the primary reviews. 17 , 21 , 23 , 31 , 35 , 37 , 39 , 40 , 42 , 44 , 47 Results of these reviews were consistent with the primary reviews in terms of effect magnitude and statistical significance and are not discussed further. Twenty-one reviews focused on specific subpopulations of adults (eg, people with severe mental illness, smokeless tobacco users). 57 - 77 These 21 reviews are not discussed here but are included in the full report. 8

The review of primary evidence on the use of e-cigarettes for smoking cessation resulted in 9 included randomized clinical trials (RCTs) reported in 16 publications; 5 of these RCTs addressed smoking cessation (KQ2) and all addressed potential harms (KQ3) (eFigure 2 in the Supplement ). 79 - 94 None of the e-cigarette trials reported results related to health outcomes (KQ1).

Key Question 1. Do tobacco cessation interventions improve mortality, morbidity, and other health outcomes in adults who currently use tobacco?

One RCT (n = 1445) reported the results of a behavioral tobacco cessation intervention on health outcomes. 95 This study reported no statistically significant differences between intervention and control groups in rates of total mortality (41.5% vs 44.%, P  = .93), coronary heart disease mortality (17.3% vs 19.9%, P  = .87), and lung cancer incidence (7.8% vs 8.8%, P  = .89) at 20-year follow-up among men at high risk for cardiorespiratory disease. 96

Key Question 2. Do tobacco cessation interventions increase tobacco abstinence in adults who currently use tobacco?

Among the general adult population, there was strong evidence from systematic reviews that the combination of pharmacotherapy and behavioral support, all 7 US Food and Drug Administration–approved medications (all forms of NRT, bupropion, varenicline), and a variety of behavioral interventions were statistically significantly associated with an increase in smokers’ relative likelihood to quit smoking at 6 or more months as compared with smokers receiving usual care or a minimal stop-smoking intervention ( Table 2 ).

The pooled risk ratio (RR) for smoking abstinence at 6 months or more for combined pharmacotherapy plus behavioral support vs usual care or minimal support control groups was 1.83 (95% CI, 1.68-1.98; 52 trials; n = 19 488). 11 Average quit rates in these trials ranged from 2% to 50% (mean, 15.2%) among participants receiving pharmacotherapy and behavioral support vs 0% to 36% (mean, 8.6%) among participants randomized to a control group.

There was also evidence of an association between the use of NRTs, bupropion, and varenicline and smoking abstinence at 6 months or more ( Table 2 ). The pooled RR for abstinence for NRT was 1.55 (95% CI, 1.49-1.61; 133 trials; n = 64 640) 12 ; for bupropion, 1.64 (95% CI, 1.52-1.77; 46 trials; n = 17 866) 15 ; and for varenicline, 2.24 (95% CI, 2.06-2.43; 27 trials; n = 12 625) 16 when compared with placebo or no drug. In all cases, behavioral support to quit smoking was provided to both intervention and control participants. There was also an association between combined NRT (typically a long- and short-acting therapy) and quitting at 6 months or more (RR, 1.25 [95% CI, 1.15-1.36]; 14 trials; n = 11 356) compared with a single form of NRT. 13 Pooled analysis of trials directly comparing NRT and bupropion did not suggest a difference between the 2 types of pharmacotherapy (RR, 0.99 [95% CI, 0.91-1.09]; 10 trials; n = 8230) 15 ; however, varenicline has been shown to be superior to both NRT (RR, 1.25 [95% CI, 1.14-1.37]; 8 trials; n = 6264) 16 and bupropion (RR [bupropion vs varenicline], 0.71 [95% CI, 0.64-0.79]; 6 trials; n = 6286) 15 in achieving abstinence at 6 months or more, although there are fewer trials testing these differences. There is limited evidence for the use of other antidepressants and nicotine receptor partial agonists for their effectiveness in helping people stop smoking. 15 , 16

Compared with various controls, behavioral interventions such as in-person advice and support from clinicians 26 , 27 ; individual-, 28 group-, 29 telephone-, 34 and mobile phone–based 38 support; interactive and tailored internet-based interventions 41 ; and the use of incentives 43 were associated with increased relative smoking cessation at 6 or more months (15% to 88% range of relative effects). Pooled results for all comparisons are reported in Table 2 . For example, smoking cessation advice from a physician or nurse was associated with pooled RRs of 1.76 (95% CI, 1.58-1.96; 28 trials; n = 22 239) 26 and 1.29 (95% CI, 1.21-1.38; 44 trials; n = 20 881), 27 respectively. Behavioral support, when added to pharmacotherapy, was also associated with increased rates of smoking cessation when compared with pharmacotherapy alone (RR, 1.15 [95% CI, 1.08-1.22]; 65 trials; n = 23 331). 25 There was a lack of clear benefit of motivational interviewing 30 ; decision aids 32 ; real-time video counseling 36 ; print-based, nontailored self-help materials 33 ; biomedical risk assessment 45 ; exercise 46 ; acupuncture 48 ; hypnotherapy 49 ; and systems-level interventions 50 , 51 compared with controls; however, there was substantially less evidence related to each of these interventions, and many individual trials of these interventions showed positive effects.

There was no evidence to suggest that the benefits and harms of pharmacotherapy and behavioral interventions, alone and combined, differed when offered to specific subpopulations of adults, including those with mental health conditions, ethnic minorities, or smokeless tobacco users. Where pooled results were presented, the direction and magnitude of effects were almost identical to those seen with the broader evidence base, although very few direct comparisons between subgroups were presented. While some reviews found evidence of potential effect modification by specific intervention, population, or study design characteristics, there was no individual factor that consistently predicted greater treatment effects across reviews.

Five trials (n = 3117) 80 , 81 , 90 , 91 , 93 were included that evaluated the effectiveness of using e-cigarettes to help current conventional smokers stop or reduce smoking compared with placebo or nicotine replacement therapy (eTable 3 in the Supplement ). The types of e-cigarettes, nicotine content, delivery of the intervention, and additional intervention components differed across all 5 trials, as did the comparisons (eTable 3 in the Supplement ). Mixed findings were reported on the effectiveness of e-cigarettes on smoking cessation at 6 to 12 months among adult smokers when compared with placebo devices or NRT (eTable 4 in the Supplement ). In 2 of the 5 trials (n = 2008), smokers randomized to e-cigarettes containing nicotine (with or without the co-use of NRT) were found to have statistically significantly greater rates of abstinence than those randomized to NRT alone 90 or NRT plus nonnicotine e-cigarettes 91 at 6- to 12-month follow-up. In both trials, continued use of e-cigarettes was high at 6- and 12-month follow-up (approximately 3-9 months after the treatment phase), with 45% to 80% of participants still using nicotine-based e-cigarettes as opposed to approximately 9% to 40% of participants still using NRT. Another trial (n = 300) compared the use of e-cigarettes (2 groups using different nicotine concentrations) with placebo at 12 months and found 11% abstinence in the nicotine-containing e-cigarette groups compared with 4% abstinence in the placebo group ( P  = .04), but 27% of those who quit smoking continued to use e-cigarettes at 1 year. 81 The remaining 2 trials (n = 807) reported no clear difference in the rates of smoking cessation among those randomized to nicotine e-cigarettes vs placebo e-cigarettes 80 or nicotine gum at 6 to 12 months’ follow-up. 93

Key Question 3. What harms are associated with tobacco cessation interventions in adults?

Nine primary reviews reported adverse events related to pharmacotherapy interventions for smoking cessation in general adult populations. 12 - 16 , 18 - 20 , 22 There was no association between the use of NRT, bupropion, or varenicline and serious adverse events, including major cardiovascular adverse events or serious neuropsychiatric events, as compared with placebo or nondrug control groups. Few reviews on behavioral interventions captured information on potential harms, and none suggested serious adverse events that arose. Nine trials reported on the potential short-term harms of e-cigarette use for cessation; none suggested relatively higher rates of serious adverse events. 80 - 84 , 86 , 90 , 91 , 93

Based on a primary literature review of 64 full-text articles, 7 RCTs (n = 2285) (reported in 12 publications) 98 - 109 that evaluated the use of NRT among pregnant women were included (eTable 5 in the Supplement ). Additionally, 5 large observational studies (n = 1 293 379) (reported in 6 publications) 110 - 115 were included that reported on the harms of NRT, bupropion, or varenicline use (eFigure 3 in the Supplement ).

Using the overview of reviews approach, 5 reviews were identified that addressed the benefits and harms of behavioral interventions for supporting women to stop smoking during pregnancy ( Table 1 ). 43 , 53 - 56 A 2017 Cochrane review included the most comprehensive evidence synthesis of tobacco cessation behavioral support interventions for pregnant women and was used as the basis for the findings presented here. 54 The other identified reviews were mostly duplicative and the results were entirely consistent with the Cochrane review.

No studies were identified that addressed the benefits or harms of the use of e-cigarettes to help pregnant women quit smoking.

Key Question 1. Do tobacco cessation interventions improve mortality, morbidity, and other health outcomes in pregnant women who currently use tobacco?

All 7 included RCTs (n = 2285) were designed to test the effectiveness of NRT on smoking cessation and reported infant, child, and maternal health. 98 , 99 , 102 , 105 - 107 , 109 Five placebo-controlled trials reported on preterm birth (delivery at <37 weeks’ gestation). 98 , 99 , 105 , 106 , 109 The most recent study, conducted in 2017, reported a statistically significant lower incidence of preterm delivery among those in the NRT inhaler group (3/67 [4.5%]) compared with the placebo group (10/67 [14.9%]) ( P  = .03) after controlling for history of preterm birth. 106 Within the other trials, 1 (n = 403) reported similar numbers of women with preterm birth in the NRT and placebo groups (14.0% vs 13.5%, respectively), 98 2 (n = 1301) reported only slightly fewer women with preterm birth in the NRT group, 99 , 109 and the study with the fewest patients (n = 194) reported reduced incidence of preterm birth with NRT compared with placebo (RR, 0.39 [95% CI, 0.17-0.91]). 105 The 3 placebo-controlled trials that did not report statistically significant differences had larger samples and estimated effects closer to null, with RRs ranging from 0.85 to 1.04. 98 , 99 , 109 Two trials without placebo controls were imprecise (very wide CIs) and estimated effects in opposite directions. 102 , 107

All 7 trials reported the association between NRT and mean birth weight. 98 , 99 , 102 , 105 - 107 , 109 Two placebo-controlled trials found significantly higher mean birth weights among women allocated to the NRT group, 105 , 109 and only one of these trials 105 reported similar effect for the proportion of infants categorized as having low birth weight. The 2 largest, good-quality, placebo-controlled trials of NRT patch interventions (n = 403 and n = 1051) did not find evidence of increased infant birth weight with NRT treatment. 98 , 99

One hundred two RCTs were included in a 2017 review that addressed the effects of behavioral smoking cessation interventions during pregnancy on smoking behavior and perinatal health outcomes. 54 Of the 102 included trials, 19 study groups reported rates of preterm birth (<37 weeks’ gestation), 26 study groups reported mean birth weight, and 17 groups reported rates of low-birth-weight infants (<2500 g). 54 Other, less commonly reported data included stillbirths (8 trials), perinatal deaths (4 trials), and neonatal deaths (5 trials) (results related to these outcomes are included in the full report).

Of the 19 trials reporting the effects of a behavioral intervention on preterm birth (less than 37 weeks’ gestation), results were mixed, although the majority reported a reduced risk of preterm birth among women within the behavioral interventions vs control groups. 54 The review’s meta-analysis of these trials found no significant association with behavioral interventions compared with controls on rates of preterm birth (RR, 0.93 [95% CI 0.77-1.11]; 19 trials; n = 9222) (eTable 6 in the Supplement ). When all 26 studies that reported mean birth weight were combined, there was evidence that behavioral smoking cessation interventions were associated with a higher mean birth weight (55.60 g, compared with usual care control interventions; mean difference, 55.60 g [95% CI, 29.82-81.38]; 26 trials; n = 11 338) (eTable 6 in the Supplement ). 54 A pooled analysis of 18 RCTs also found a 17% risk reduction for delivery of a low-birth-weight infant (<2500 g) (RR, 0.83 [95% CI, 072-0.94]; 18 trials; n = 9402) (eTable 6 in the Supplement ).

Key Question 2. Do tobacco cessation interventions increase tobacco abstinence in pregnant women who currently use tobacco?

There was no evidence of differences in rates of smoking cessation among pregnant women randomized to NRT vs placebo or no intervention within the included trials. Meta-analysis of 5 placebo-controlled trials found a pooled RR of 1.11 (95% CI, 0.79-1.56]; n = 2033) for NRT vs placebo (eFigure 4 in the Supplement ). 98 , 99 , 105 , 106 , 109 Quit rates in these trials ranged from 5% to 28% in the intervention groups and 5% to 25% in the control groups (mean, 11.8% vs 10.6%). The results of the 2 smaller trials with no treatment controls 102 , 107 were not statistically significant, and estimates of efficacy were greater than for the placebo-controlled trials.

Within the Cochrane review on behavioral interventions among pregnant women, of the 120 study groups included in the review, 97 groups reported the primary outcome measure of smoking abstinence in late pregnancy, up to and including the period of hospitalization for birth. 54 Pooled analyses of all behavioral interventions, regardless of type of behavioral support and including self-reported outcomes, indicated a statistically significant association with smoking cessation in late pregnancy when compared with usual care or a minimal intervention (RR, 1.35 [95% CI, 1.23-1.48]; 97 trials; n = 26 637) (eTable 7 in the Supplement ). The results were similarly associated with a beneficial effect when restricted to trials comparing counseling with usual care (RR, 1.44 [95% CI, 1.19-1.73]; 30 trials; n = 12 432). There was some evidence that the positive association of behavioral interventions on smoking cessation in late pregnancy continued into the postpartum period, up until approximately 18 months postpartum. For instance, in an examination of counseling interventions compared with usual care, the average RR was 1.59 (95% CI, 1.26-2.01; 11 trials) at 0 to 5 months postpartum, 1.33 (95% CI, 1.00-1.77; 6 trials) at 6 to 11 months postpartum, and 2.20 (95% CI, 1.23-3.96; 2 trials) at 12 to 17 months. 54

Key Question 3. What harms are associated with tobacco cessation interventions in pregnant women?

There was no evidence of perinatal harms related to NRT use among pregnant women, but data for assessing rare harms were very limited. 98 , 99 , 102 , 105 - 107 , 109 Two larger trials reported stillbirths and congenital malformations and reported few events and no differences in the outcome between study groups. 98 , 99 Trials reporting miscarriage 98 , 99 , 106 and neonatal deaths 98 , 99 , 105 reported few events and no difference between study groups. One trial provided extended follow-up and did not find differences in longer-term developmental or respiratory harms associated with NRT use during pregnancy. 101 Evidence from 5 large cohort studies did not find differences in stillbirth, birth outcomes, or any congenital anomaly for infants born to mothers with exposure to NRT, bupropion, or varenicline vs those unexposed to medications but whose mothers smoked. 110 - 115 Behavioral smoking cessation interventions were found to have minimal adverse effects. 54

This evidence review evaluated interventions for tobacco cessation in adults; the evidence is summarized in Table 3 . The results are generally consistent with the conclusions of the 2020 Surgeon General’s report on smoking cessation. 2 There is moderate- to high-certainty evidence that all 7 US Food and Drug Administration–approved medications for smoking cessation, a variety of behavioral support and counseling approaches, and the combination of pharmacotherapy plus behavioral support—all interventions that may be readily available to primary care patients and clinicians—can significantly increase the rate of smoking cessation among adults at 6 months and longer compared with usual care or brief self-help materials. Treatment effects appear to be comparable in a range of populations, settings, and types of behavioral support. Furthermore, despite adding nearly 5 more years of research since the previous review, 5 , 6 the effect estimates for each pooled comparison have been remarkably stable for at least the past 3 decades.

Nevertheless, various questions about tobacco cessation interventions have not yet been answered. Evidence is still needed to compare different forms, doses, and durations of drugs; to compare drugs with one another; to evaluate remotely delivered interventions vs minimal support; and to test interventions in special populations for which the effectiveness may differ from that in the general population (eg, pregnant women, persons with current severe mental illness, those with physical disabilities, nondaily and intermittent smokers), including direct subgroup comparisons.

Evidence on the potential benefits and harms of pharmacotherapy for smoking cessation during pregnancy is limited, with few placebo-controlled trials and limited power for detecting both potential benefits and harms ( Table 3 ). In contrast to the findings in this review, a recent Cochrane review concluded that there was low-quality evidence suggesting that NRT may be more effective than placebo and nonplacebo controls. 117 There was unclear evidence of an association when limited to only placebo-controlled trials, 117 however, a finding similar to this review. Careful collection of adverse events information, including long-term consequences of stop-smoking medications, is important in future trials, and data on adherence to medications and levels of nicotine exposure from NRT relative to what occurs with smoking would also be valuable.

In contrast to the robust evidence on pharmacotherapy and behavioral interventions for smoking cessation, evidence on the use of e-cigarettes as an intervention to quit conventional smoking is lacking ( Table 3 ). No studies on the use of e-cigarettes as tobacco cessation interventions reported health outcomes, and few trials reported on the potential adverse events of e-cigarette use when used in atttempts to quit smoking. This is particularly concerning given the apparent longer-term use of e-cigarettes for cessation compared to pharmacotherapy in addition to the recent outbreak of e-cigarette, or vaping, product use–associated lung injury. 118 Furthermore, there is lack of long-term epidemiologic studies and large clinical trials examining the associations between e-cigarette use and morbidity and mortality, especially in the long term. 119

Although this review was scoped to include interventions focused on quitting any tobacco product, most published trials have targeted (and reported) quitting combustible cigarette use. More research is needed on interventions to help people quit other tobacco products such as cigars, smokeless tobacco, and e-cigarettes. Given the high prevalence of dual use of combustible and electronic cigarettes, 120 there is a need for research on interventions to help dual users of conventional cigarettes and e-cigarettes quit both products, as well as research on potential relapse back to cigarette use among former smokers who use e-cigarettes.

The primary limitation of the evidence report relates to the overview of reviews approach. The comprehensiveness of the overview of reviews is inevitably limited by the recency and quality of the source reviews. Although most of the reviews included evidence at least through 2015, there may be evidence on specific population and intervention subsets that has been published after each review’s last search date. If this occurred, the respective bodies of evidence may not reflect these newer studies. Given the consistency of the effects within each group over time, however, it appears unlikely that any new trials, regardless of their sample size and effect estimates, would have substantial bearing on the overall results of this overview of reviews.

There is strong evidence that a range of pharmacologic and behavioral interventions, both individually and in combination, are effective in increasing smoking cessation in nonpregnant adults. In pregnancy, behavioral interventions are effective for smoking cessation, but data are limited on the use of pharmacotherapy for smoking cessation. Data on the effectiveness and safety of electronic cigarettes for smoking cessation among adults are also limited and results are inconsistent.

Corresponding Author: Carrie D. Patnode, PhD, MPH, Kaiser Permanente Evidence-based Practice Center, Center for Health Research, Kaiser Permanente Northwest, 3800 N Interstate Ave, Portland, OR 97227 ( [email protected] ).

Accepted for Publication: December 4, 2020.

Author Contributions: Dr Patnode had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Patnode, Henderson, Coppola, Melnikow.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Patnode, Coppola.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Patnode.

Administrative, technical, or material support: Henderson, Coppola, Melnikow, Durbin, Thomas.

Supervision: Patnode, Henderson, Melnikow.

Conflict of Interest Disclosures: None reported.

Funding/Support: This research was funded under contract HHSA-290-2015-00007-I-EPC5, Task Order 5, from the Agency for Healthcare Research and Quality (AHRQ), US Department of Health and Human Services, under a contract to support the US Preventive Services Task Force (USPSTF).

Role of the Funder/Sponsor: Investigators worked with USPSTF members and AHRQ staff to develop the scope, analytic framework, and key questions for this review. AHRQ had no role in study selection, quality assessment, or synthesis. AHRQ staff provided project oversight, reviewed the report to ensure that the analysis met methodological standards, and distributed the draft for peer review. Otherwise, AHRQ had no role in the conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript findings. The opinions expressed in this document are those of the authors and do not reflect the official position of AHRQ or the US Department of Health and Human Services.

Additional Contributions: We gratefully acknowledge the following individuals for their contributions to this project: Tina Fan, MD, MPH (AHRQ); current and former members of the US Preventive Services Task Force who contributed to topic deliberations; Evidence-based Practice Center staff members Todd Hannon, MLS, and Katherine Essick, BS (Kaiser Permanente Center for Health Research), for technical and editorial assistance. USPSTF members, peer reviewers, and those commenting on behalf of partner organizations did not receive financial compensation for their contributions.

Additional Information: A draft version of this evidence report underwent external peer review from 6 content experts (Brian King, PhD, MPH [Centers for Disease Control and Prevention], Janet Wright, MD [Office of the Surgeon General], Nicola Lindson, BSc, MSc, CPsychol, PhD [University of Oxford], Stephen Fortmann, MD [Kaiser Permanente Center for Health Research], Nancy Rigotti, MD [Harvard Medical School], and Michele Levine, PhD [University of Pittsburgh]) and 3 federal partners (Centers for Disease Control and Prevention, National Institutes of Health, and US Food and Drug Administration). Comments were presented to the USPSTF during its deliberation of the evidence and were considered in preparing the final evidence review.

Editorial Disclaimer: This evidence report is presented as a document in support of the accompanying USPSTF recommendation statement. It did not undergo additional peer review after submission to JAMA .

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• Correspondence
• Published: 13 August 2024

Smoking cessation as a recommended action for incident hypertension

• Tomoyuki Kawada   ORCID: orcid.org/0000-0002-4426-4644 1  

Journal of Human Hypertension volume  38 ,  page 624 ( 2024 ) Cite this article

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TO THE EDITOR:

I have read with interest a study by Talukder et al., presenting the prevalence and determinants of hypertension among urban residents in South Asian countries [ 1 ]. Low education, caffeine consumption, and obesity were significantly associated with higher prevalence of hypertension, and smokers also presented an increased risk of hypertension. Regarding the modifiable lifestyle factors, smoking cessation is urgently recommended, which is closely related to educational status, coffee intake and weight change. I present some comments with special reference to sex and age.

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Talukder A, Sara SS, Khan ZI, Yadav UN, Mistry SK, Biswas T, et al. Prevalence and determinants of hypertension in South-Asian Urban Communities: findings from Demographic and Health Surveys (DHS) data of South Asian countries. J Hum Hypertens. 2024;38:257–66.

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Greater Good Science Center • Magazine • In Action • In Education

Can Gratitude Help You Quit Smoking?

People who smoke often desire to quit. Yet smoking can be a hard habit to break, even knowing the clear link between smoking and cancer. While there are smoking cessation programs that can help, many smokers don’t sign up for them, leaving them vulnerable to increased health problems due to tobacco.

Now, findings from a new study suggest an unusual tool for encouraging people to quit smoking: practicing gratitude.

In this study, researchers analyzed large-scale surveys given at different points in time to over 30,000 Americans and others around the world. Whether looking at American teens, American adults, or people living elsewhere, those who reported feeling more gratitude had better outcomes around smoking.

For example, grateful teens were less likely to smoke or become smokers later on, even taking into account how sad they were (a known risk factor for smoking). The same was true of grateful American adults. Or, if they were already smokers, the adults were more likely to quit five to 10 years later.

Adults from 87 countries around the world who reported feeling more grateful had lower intentions to use drugs overall (including tobacco), no matter their age, gender, education, or the negative or other positive feelings they typically experienced—like love, hope, inspiration, and serenity. The higher average gratitude of people in a particular country, the lower the country-wide tobacco use, too.

Lead researcher Ke Wang of Harvard University says this suggests that something about feeling gratitude makes people want to smoke less, perhaps its more positive, other-oriented focus.

“If you feel negative and focus on yourself, you want to seek reward to compensate for that sense of loss and negativity. That’s one driver for smoking,” says Wang. “The opposite is true of gratitude: Feeling positive, having your attention on other people, and having already benefitted from other people, you don’t feel a strong desire to reward yourself by smoking.”

Gratitude reduces craving and encourages quitting

While these survey results were promising, Wang and his team wanted to go further and see if making smokers feel grateful might change their smoking behavior.

So, he and his colleagues recruited adult smokers and first asked them how much they were craving a cigarette. The participants then watched a video inducing them to feel either sadness, compassion, gratitude, or neutral (no particular feeling). For example, the gratitude video involved a scene from the movie Awakening in which the protagonist doctor receives unexpected help from his colleagues. Then, the participants wrote about a time something similar happened to them—when they received unexpected help. (The neutral group watched a furniture-making video and wrote about their day.)

Afterward, the smokers again reported how much they were craving a cigarette. Those in the gratitude group experienced significantly decreased cravings, while those feeling sad had increased cravings and those feeling compassion (or neutral) experienced no changes in cravings.

“This shows experimentally there’s a causal relationship between gratitude and smoking,” says Wang. “And the more gratitude participants felt, the more reduction in craving they experienced. So, that further confirms the role of gratitude.”

To further their findings, Wang and his team induced a different group of smokers to either feel grateful or neutral, and then gave them an opportunity to report on their intentions to quit, encourage other smokers to quit, and actually sign up for a smoking cessation program (offered by the Mayo Clinic). Interestingly, the grateful group were more likely to sign up for the program than the neutral group, even though they didn’t have stronger intentions to quit. There seemed to be no impact on the advice they gave to others, though.

This interests Wang, because often smokers have an intention to quit but don’t actually follow through. There’s always tension between what someone desires to do (for example, smoke) and what someone thinks they should do (stop smoking). The fact that the grateful participants were literally signing up for a program to quit was encouraging—and unexpected, he says.

“That was a super interesting pattern that we found; we did not originally expect that,” he says. “But it suggests [that] one way for gratitude to change behavior is not necessarily by changing intentions, but changing [people’s] follow-through of their intentions, which is a fascinating finding.”

He thinks that the reduced craving that gratitude brings may be very helpful for smokers who are on the fence.

“With gratitude, competing forces shift in balance, especially when craving decreases. Finally, [someone’s] intention to quit can manifest in their behavior,” he says.

To reduce smoking, increase people’s gratitude?

Does this mean we should encourage smokers to practice more gratitude in their lives? Wang thinks so.

“There are definitely lots of gratitude exercises for smokers to incorporate in their daily lives—writing gratitude journals , expressing gratitude more, or sharing gratitude with others —and those types of practice can be incorporated into their journey of quitting,” he says. “Many people set goals (like in New Year’s resolutions) to quit smoking, but they cannot follow through on their intentions. With more gratitude and better emotion regulation, they can achieve their goals better.”

Gratitude Journal

Count your blessings and enjoy better health and happiness

In addition, the last part of Wang’s study looked at public service announcements that aim to encourage people to stop smoking. When smokers rated how these ads made them feel, they felt sadness and sympathy more strongly than gratitude. Wang sees this as a missed opportunity—especially given how little money is available for these types of ads in comparison to the ad budgets of tobacco companies.

“We know sadness could backfire and compassion doesn’t seem to make any difference among smokers. So, we think to make the campaigns more effective, the CDC and others should consider using more gratitude, which could maximize the impact,” says Wang.

Wang hopes to do more research on gratitude, both to better understand why it affects smoking behavior and craving and how it might be useful for other unhealthy behaviors involving craving, such as overeating. He’d also like to study other positive emotions, alone and in combination, to see if there may be synergistic effects when we practice more positivity, in general.

Meanwhile, he sees practicing gratitude as having the potential to improve people’s lives significantly and has been in touch with the CDC about his findings, hoping they will take note.

“Gratitude is an underappreciated tool in reducing harmful health behavior,” he says. “Hopefully, the CDC will consider [promoting it] more now that we know the impact of this positive emotion on smoking.”

About the Author

Jill Suttie

Jill Suttie, Psy.D. , is Greater Good ’s former book review editor and now serves as a staff writer and contributing editor for the magazine. She received her doctorate of psychology from the University of San Francisco in 1998 and was a psychologist in private practice before coming to Greater Good .

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Experiences of smoking and tobacco use during pregnancy: A qualitative study protocol

Roles Data curation, Investigation, Methodology, Visualization, Writing – original draft

Affiliations Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain, Department of Primary Care Camp de Tarragona, Institut Català de la Salut, Primary Care Center Llibertat (Reus– 3), Reus, Spain, ISAC Research Group, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), Barcelona, Spain

Roles Conceptualization, Methodology, Writing – original draft

Affiliations Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain, ISAC Research Group, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), Barcelona, Spain, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Primary Healthcare Research Support Unit Camp de Tarragona, Reus, Spain, Universitat Oberta de Catalunya (UOC), Barcelona, Spain

Roles Conceptualization, Methodology, Writing – review & editing

Affiliations Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain, ISAC Research Group, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), Barcelona, Spain, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Primary Healthcare Research Support Unit Camp de Tarragona, Reus, Spain, School of Medicine and Health Sciences, Universitat Rovira i Virgili, Reus, Spain

Roles Methodology, Writing – review & editing

Affiliations Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain, ISAC Research Group, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), Barcelona, Spain, Department of Primary Care Camp de Tarragona, Institut Català de la Salut, Primary Care Center Horts de Miró (Reus– 4), Reus, Spain, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), TICS-AP Research Group, Barcelona, Spain

Roles Methodology, Software, Writing – review & editing

Roles Investigation, Writing – review & editing

Affiliations Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain, ISAC Research Group, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), Barcelona, Spain, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), TICS-AP Research Group, Barcelona, Spain, Department of Primary Care Camp de Tarragona, Institut Català de la Salut, Sexual and Reproductive Health Care Unit (ASSIR), Reus, Spain

Affiliations Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), TICS-AP Research Group, Barcelona, Spain, Department of Primary Care Camp de Tarragona, Institut Català de la Salut, Sexual and Reproductive Health Care Unit (ASSIR), Reus, Spain

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Writing – review & editing

* E-mail: [email protected]

Affiliations Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain, ISAC Research Group, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), Barcelona, Spain, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Primary Healthcare Research Support Unit Camp de Tarragona, Reus, Spain, School of Medicine and Health Sciences, Universitat Rovira i Virgili, Reus, Spain, Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP JGol), TICS-AP Research Group, Barcelona, Spain

Roles Conceptualization, Methodology, Resources, Writing – review & editing

• Maria Agràs-Guàrdia, 
• Sara Martínez-Torres, 
• Eva Satué, 
• Ester Granado-Font, 
• Meritxell Pallejà-Millán, 
• Demetria Patricio, 
• Miriam Leiva, 
• Cristina Rey-Reñones, 
• Francisco Martín-Luján

• Published: August 9, 2024
• https://doi.org/10.1371/journal.pone.0308781
• Reader Comments

Tobacco use during pregnancy is the main avoidable cause of morbidity and mortality both for pregnant women and their offspring. Between 12 and 22% of pregnant women in industrialized countries smoke during pregnancy, and 13% are unable to stop smoking. Pregnancy is considered an ideal opportunity to intervene and control tobacco use among smokers and their families. However, pregnant women experience barriers to quitting smoking, including social stigma and fear of being judged. Thus, it is necessary to develop interventions for smoking cessation adapted for pregnant women. This paper presents a qualitative study protocol to assess the barriers and facilitators of smoking cessation during pregnancy that female smokers encounter or perceive. It consists of a series of focus groups and individual interviews with female smokers who have been pregnant within the last five years. Participants will be recruited from the Sexual and Reproductive Health Care Services of the Camp de Tarragona. A group of 5–10 women who have been pregnant and tried to quit smoking over the last 5 years will be selected. The data will be collected by means of semistructured interviews. All interviews will be transcribed verbatim, coded and synthesized into categories and main themes. Thematic analysis will be conducted employing an iterative and reflexive approach. The results of this study will offer new perspectives on smoking interventions for pregnant women and enhance our comprehension of the main barriers to and facilitators of smoking cessation during pregnancy. This will contribute to the adaptation of the Tobbstop app, originally designed for the general public, to suit the needs of pregnant women. Consequently, the creation of targeted interventions will positively influence the health outcomes of both pregnant women and newborns.

Trial registration: Clinicaltrials.gov ID: NCT05222958 . The trial was registered 3 February 2022, at https://clinicaltrials.gov/ct2/show/NCT05222958 .

Citation: Agràs-Guàrdia M, Martínez-Torres S, Satué E, Granado-Font E, Pallejà-Millán M, Patricio D, et al. (2024) Experiences of smoking and tobacco use during pregnancy: A qualitative study protocol. PLoS ONE 19(8): e0308781. https://doi.org/10.1371/journal.pone.0308781

Editor: Kehinde Kazeem Kanmodi, Teesside University, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND

Received: May 2, 2023; Accepted: July 30, 2024; Published: August 9, 2024

Copyright: © 2024 Agràs-Guàrdia 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: No datasets were generated or analysed during the current study. All relevant data from this study will be made available upon study completion.

Funding: This study has been funded from Health Institute Carlos III, Ministry of Economy and Competitiveness (Spain), on the 2021 call under the Health Strategy Action 2021-2025, within the National Research Program oriented to Societal Challenges, within the Technical, Scientific and Innovation Research National Plan 2021-2025 (code reference PI21/01058), and Co-funded by the European Regional Development Fund (European Union). The funders did not and will not have a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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

Introduction

Smoking during pregnancy is a preventable risk factor associated with maternal and child morbidity and mortality [ 1 ]. Pregnancy is considered an ideal opportunity to intervene in and control tobacco consumption among smokers and their families [ 2 ]. However, 52.9% of women who smoke daily continue to smoke during pregnancy, and in the absence of intervention, they are likely to continue smoking [ 3 ].

Pregnant smokers face many barriers to and few facilitators of smoking cessation. Different variables, such as sociodemographic, relationship, social, smoking-related, pregnancy-related, health and psychological factors, can predict smoking cessation in pregnancy [ 4 ]. Partner support, willingness to change smoking habits, and the role of smoking in relationships are important factors. Recent studies have concluded that education to increase awareness and information about smoking during pregnancy are relevant. Moreover, providing access to effective interventions such as referrals to smoking cessation services, routine carbon monoxide screening, behavioral support, and pharmacotherapy could help pregnant women quit smoking [ 5 ]. These interventions effectively reduce tobacco consumption in the general population; however, pregnant smokers usually do not actively pursue them [ 6 – 8 ].

Lazarus and Folkman’s model defines the concept of stress by examining the intricate interaction between an individual and his or her environment. This model can be applied to investigate the role of psychological factors in smoking cessation [ 9 ]. According to their framework, anxiety levels depend on one’s ability to manage external demands, internal self-evaluations that exceed the individual’s available resources, and the strategies employed to cope with these stressors [ 10 , 11 ].

This conceptual framework is particularly relevant to our study because smoking cessation is widely recognized as a major source of stress. Although the majority of smokers older than 18 years of age express their desire to quit smoking (52% attempt to quit), only 6% successfully quit smoking after 12 months [ 12 ]. Previous research has highlighted the critical importance of stress-induced cravings, especially in people with high levels of nicotine dependence, who are at greatest risk of not quitting. Implementing stress coping programs has been shown to significantly improve the likelihood of successfully quitting smoking [ 13 ].

Behavioral support is the most effective smoking cessation intervention for pregnant smokers, but only a minority of pregnant smokers access it. Even though pregnant women are often aware of the negative effects of smoking on their fetus and themselves, they face many barriers that make it difficult to quit smoking. It is well known that the psychological and social environment also play important roles [ 13 , 14 ]. Consequently, additional qualitative studies are needed to analyze these barriers to identify strategies to help pregnant women quit smoking.

Digital interventions are accessible support interventions and alternatives to traditional support for smoking cessation. Moreover, digital interventions are preferred by women, as they note the importance of being informed to avoid cravings and continue abstinence [ 15 ].

Currently, only a few digital interventions for pregnant smokers have been developed, and little is known about the acceptability and usability of smartphone apps to aid in smoking cessation during pregnancy. In a study that aimed to determine the opinions of pregnant smokers about the use of an application for smoking cessation, it was concluded that this type of intervention could be feasible. The design of the application was considered a very important element, and pregnant women valued that the content was motivating, educational and personalized [ 16 ].

In a previous study, our research group addressed the effectiveness of an intervention based on gamification, the Tobbstop app, for reducing the prevalence of tobacco consumption in the young population [ 17 , 18 ]. Furthermore, a pilot study of a randomized controlled trial of pregnant smokers showed that pregnant app users had continuous abstinence until delivery; specifically, the prevalence of continuous abstinence until delivery was 57% in the intervention group versus 14% in the control group (p = 0.001) [ 19 ]. Building upon the findings of this pilot study, we intend to conduct a community-based research trial. This trial will be akin to the pilot study but with necessary adjustments to tailor the new Tobbstop app for pregnant women. The research group will conduct a study titled "Effectiveness of an App for Tobacco Cessation in Pregnant Smokers (TOBBGEST): randomized community trial". The Tobbstop app will be based on educational content, smoker support, recreational activities, games, entertainment features, and integrated social networking capabilities. This approach is based on the clinical practice guidelines for smoker support outlined by the Catalan Institute of Health and the Department of Health. The Department of Health is the regional institution responsible for planning health actions. The Catalan Institute of Health is the primary provider of public health services in Catalonia, ensuring healthcare for more than 80% of the population.

The original Tobbstop app was designed for the general public, and the intention was to adapt it to the needs of pregnant women. Considering the results of the study, messages and advice that are considered appropriate will be added, as well as information about the beneficial effects of smoking cessation on maternal, fetal and child health. Additionally, the app will offer audiovisual support in the form of mindfulness sessions and respiratory/muscle relaxation exercises [ 20 ].

We aim to determine the overall perceptions of female smokers regarding the facilitators of and barriers to smoking cessation during pregnancy through a qualitative research approach. The results of this new study will allow us to adapt the Tobbstop application to the needs of this population.

Materials and methods

Aims and objectives.

The aim of this study is to identify the barriers to and facilitators of smoking cessation in pregnant smokers.

The specific objectives are as follows:

• To determine the difficulties or barriers encountered or perceived by pregnant women for smoking cessation.
• To determine the motivators or facilitators that help pregnant smokers stop smoking during pregnancy.
• To learn about the experiences of female smokers during pregnancy and tobacco addiction.

Study design and setting

This study consists of a descriptive qualitative research design with a phenomenology approach and conversational techniques to determine the barriers to and facilitators of smoking cessation in pregnant women.

The Sexual and Reproductive Health Care Unit (Atenció a la salut sexual i reproductiva, ASSIR (Catalan acronym)) is a public Catalan Healthcare service for assistance and educational activities. ASSIR professionals include midwives, gynecologists-obstetricians, nurses, psychologists, and auxiliary administrative personnel who work in different locations in various consultations at health and staff center primary care. This study will be conducted at the ASSIR Centre of Reus (Camp de Tarragona; Spain).

Recruitment

A group of 5–10 women who have smoked and received assistance at the ASSIR Centre for Pregnancy over the past five years and who have attempted to quit smoking will be recruited. The midwives within the ASSIR service, including a designated tobacco cessation expert, will be responsible for the recruitment process in their daily practice. The tobacco cessation expert is a professional with expertise in tobacco cessation and will be available for consultation in case of any uncertainties.

Inclusion criteria:

• Pregnant women who smoked during pregnancy within the past 5 years.
• Pregnant women who consent to participate in the study.

The exclusion criterion is language difficulties. Participants will be women who possess sufficient language proficiency to participate in an interview or focus group. Immigrant women will be asked if they feel capable of conversing in Catalan or Spanish; if their response is negative, they will be excluded. When individuals affirm proficiency but encounter comprehension difficulties during the interview, the research team will consider rejecting the interview.

Participants will be invited to join a focus group on a specific day and time. If they are unable to attend, they will be offered the option to participate in an interview at a time that suits their availability.

The health professionals responsible for recruiting pregnant women will explain the study and will be available to address any questions that may arise. Before conducting the in-depth interview or focus group, a member of the research team will provide participants with information about the study and will distribute an information sheet. Participants will have the opportunity to ask questions. Subsequently, each participant will be asked to sign the informed consent form.

We will employ thematic saturation as a criterion to determine the final number of interviewees [ 21 ]. To achieve information saturation, we will consider the key aspects outlined in S1 Appendix , the interview script, during the participant selection process. These considerations will include factors such as the number of children, the presence or absence of pregnancy-related difficulties, age, and previous experiences with tobacco cessation.

Semistructured interviews and focus groups

A moderator experienced in qualitative research (the principal investigator or a member of the project team) and an observer will perform all the interviews or focus groups. Participants will have no previous contact with the research team before the sessions. Sessions will take place in a private space in the ASSIR center. A thematic scenario will be prepared (see S1 Appendix of the Supplementary Material for content details) that will be followed through the conversation. The interviews will continue until the point of relative saturation on the topic being discussed is reached, with a maximum duration of 90 minutes.

All interviews will be digitally audio-recorded and subject to the informed consent of the participants. In addition, an observer will take field notes during the session. Subsequently, an interviewer, who will record the data verbatim and anonymize any identifying data, will manually transcribe the participants’ information.

Data management plan

Data from focus groups and individual interviews will be recorded, anonymized, analyzed and published. The records will be stored on a private secure informatic medium with password-protected access for exclusive use and validation by the researchers.

There is no intention to reuse these data, so they will be stored until the end of the main project and destroyed five years after publication of the final results.

Data analysis

The data will be analyzed via reflective inductive thematic analysis to identify, interpret and report themes within the data [ 21 ].

First, interview recordings will be listened to and transcribed verbatim, including anonymized question answers/contributions from each group member. Next, before preparing the transcript for analysis, one person or, in case of doubt, multiple individuals will verify the accuracy of the transcription. Once the transcription of the content is approved, the research team will proceed with a semantic content analysis.

A thematic content analysis of the texts collected in the interviews or focus groups will be carried out by at least 2 members of the research team in the following way: (1) an initial reading of all the messages; (2) identification of relevant topics and text messages; (3) fragmentation of text into units of meaning; (4) coding of text by themes; and (5) creating categories based on Lazarus and Folkman’s model and the Cutrona model, grouping the codes; and (6) interpretation of the meanings of each category [ 10 , 11 ].

All the data for analysis will be analyzed and systematically organized using the qualitative analysis software ATLAS.ti (v5.14).

The final topics and categories (and possible subcategories) will be identified by induction, through analysis, deep reflection and discussion among the researchers. Preliminary conclusions will be presented in a meeting with the whole team and will give rise to an in-depth debate from which the conceptual framework will be created to develop an intervention to help pregnant women quit smoking. Furthermore, we will leverage strengths as a primary means of offering support whenever feasible. For instance, if women suggest that it would be beneficial to receive information about “mindfulness” or “nutrition” during the weaning process, these suggestions could be incorporated.

Rigor and quality criteria

To guarantee the rigor and quality of the study, the rigor criteria suggested by Calderón will be followed: epistemological and methodological adequacy, relevance, validity and reflexivity [ 22 ]. The context and characteristics of the participants will be described in the research process. The messages obtained will be analyzed, and there will be a period of reflection that will be carried out by at least 2 members of the research team.

Ethical considerations and declarations

This study will be conducted in agreement with the principles of the revised and updated Helsinki Declaration and Good Clinical Practice. The Clinical Research Ethics Committee of the Primary Care Research Institute (IDIAPJGol) (22/268-P; 25/01/2023) approved this protocol. Data confidentiality will be protected by the Spanish law governing the protection of personal data (Ley Orgánica de Protección de Datos de Carácter Personal y garantía de los derechos digitales; 03/2018, 5 December).

All participants will receive an information sheet from which they will be informed that their participation is anonymous, confidential and voluntary, as well as their right to change their mind (not to participate) at any time up to data verification. Verbal and written consent will be obtained from all participants to participate and be audio-recorded in the study.

The pregnancy and postpartum stages are periods of change and adaptation, during which important physiological changes occur. In addition, these periods are accompanied by worries and fears related to pregnancy, childbirth and motherhood [ 23 ].

While many women quit smoking when they become pregnant, many others continue smoking. These women may be conditioned by many factors that make it difficult for them to quit smoking [ 24 ]. Evidence has shown that the risk of mental health problems is greater in pregnant smokers than in nonpregnant smokers. Moreover, the occurrence of pandemics and sociodemographic and economic crises could lead to behavioral changes during pregnancy, leading to an increase in smoking prevalence [ 25 , 26 ]. Recent studies have reported that frustration in motherhood and having a partner who smokes are key barriers to achieving smoking abstinence during the postpartum period, while body weight maintenance during pregnancy and breastfeeding are facilitators of smoking abstinence [ 27 ]. In view of these factors, we believe that it is necessary to adapt the Tobbstop app based on the feelings and emotions experienced by pregnant women who attempt to quit smoking.

This study will provide information on barriers to and facilitators of the smoking cessation process in pregnant women, which will improve the content of digital interventions considering patient opinions. Moreover, in-depth patient interviews will contribute to a richer understanding of the health needs, lived experiences and barriers to quitting smoking during pregnancy among pregnant women.

Pregnant smokers frequently find themselves ensnared in a detrimental cycle. They turn to smoking as a coping mechanism to cope with stress and mental distress, even though they are aware of the harm it inflicts on both their unborn child and their own health. This leads to a cycle in which smoking exacerbates pregnant women’s feelings of guilt and vulnerability, all while facing societal pressure to quit. Thus, pressure to quit smoking intensifies addictions, suggesting that professionals should adjust their interventions to motivate patients and not stigmatize them [ 28 ]. The Tobbstop app was designed to support pregnant smokers during the quitting process but not to judge them.

This study has several limitations. First, there is the possibility of overrepresentation of groups that tend to spend time participating in focus groups, for example, unemployed individuals. Second, participants will be recruited through convenience sampling in a unique setting with geographic and cultural differences. Third, it must be considered that there are different profiles of pregnant women and that some of those selected may not choose a digital intervention to quit smoking. To mitigate these limitations, we will prioritize maximum variability and heterogeneity when selecting the participant sample.

In summary, this study aims to provide new information for adapting smoking cessation interventions for pregnant women and, consequently, for increasing the success of smoking cessation during pregnancy and the postpartum period.

Supporting information

S1 appendix. semistructured interview guide..

This appendix aims to provide additional information about the study.

https://doi.org/10.1371/journal.pone.0308781.s001

Acknowledgments

We are thankful for the assistance provided by the Primary Health Care Research Institute (IDIAP Jordi Gol) and for their knowledge of qualitative research.

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Smoking Cessation After Diagnosis of Kidney Cancer Is Associated With Reduced Risk of Mortality and Cancer Progression: A Prospective Cohort Study

Affiliations.

• 1 Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France.
• 2 Department of Epidemiology, N.N. Blokhin National Medical Research Centre of Oncology, Moscow, Russia.
• 3 Department of Urology, N.N. Blokhin National Medical Research Centre of Oncology, Moscow, Russia.
• PMID: 36989465
• PMCID: PMC10414692
• DOI: 10.1200/JCO.22.02472

Purpose: To investigate whether postdiagnosis smoking cessation may affect the risk of death and disease progression in patients with renal cell carcinoma (RCC) who smoked at the time of diagnosis.

Methods: Two hundred twelve patients with primary RCC were recruited between 2007 and 2016 from the Urological Department in N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russia. Upon enrollment, a structured questionnaire was completed, and the patients were followed annually through 2020 to repeatedly assess their smoking status and disease progression. Survival probabilities and hazards for all-cause and cancer-specific mortality and disease progression were investigated using extended the Kaplan-Meier method, time-dependent Cox proportional hazards regression, and Fine-Gray competing-risk models.

Results: Patients were followed for a median of 8.2 years. During this time, 110 cases of disease progression, 100 total deaths, and 77 cancer-specific deaths were recorded. Eighty-four patients (40%) quit smoking after diagnosis. The total person-years at risk for this analysis were 748.2 for continuing smoking and 611.2 for quitting smoking periods. At 5 years of follow-up, both overall survival (85% v 61%) and progression-free survival (80% v 57%) rates were higher during the quitting than continuing smoking periods (both P < .001). In the multivariable time-dependent models, quitting smoking was associated with lower risk of all-cause mortality (hazard ratio [HR], 0.51; 95% CI, 0.31 to 0.85), disease progression (HR, 0.45; 95% CI, 0.29 to 0.71), and cancer-specific mortality (HR, 0.54; 95% CI, 0.31 to 0.93). The beneficial effect of quitting smoking was evident across all subgroups, including light smokers versus moderate-heavy smokers and those with early-stage versus late-stage tumors.

Conclusion: Quitting smoking after RCC diagnosis may significantly improve survival and reduce the risk of disease progression and cancer mortality among patients who smoke.

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Conflict of interest statement

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center .

Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians ( Open Payments ).

Vsevolod Matveev

Honoraria: Ipsen, Bayer, AstraZeneca, Janssen, Astellas Pharma, MSD

Expert Testimony: BMS, Bayer, MSD, Janssen

No other potential conflicts of interest were reported.

Extended Kaplan-Meier curves illustrating the…

Extended Kaplan-Meier curves illustrating the probability of (A) overall survival (B) progression-free survival…

Adjusted survival curves illustrating the…

Adjusted survival curves illustrating the probability of overall survival during the quitting smoking…

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Smoking Cessation After Diagnosis of Kidney Cancer Is Associated With Reduced Risk of Mortality and Cancer Progression: A Prospective Cohort Study

Mahdi sheikh.

1 Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France

Anush Mukeriya

2 Department of Epidemiology, N.N. Blokhin National Medical Research Centre of Oncology, Moscow, Russia

Xiaoshuang Feng

Hilary a. robbins, oxana shangina.

Vsevolod Matveev

3 Department of Urology, N.N. Blokhin National Medical Research Centre of Oncology, Moscow, Russia

Paul Brennan

David zaridze.

To investigate whether postdiagnosis smoking cessation may affect the risk of death and disease progression in patients with renal cell carcinoma (RCC) who smoked at the time of diagnosis.

Two hundred twelve patients with primary RCC were recruited between 2007 and 2016 from the Urological Department in N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russia. Upon enrollment, a structured questionnaire was completed, and the patients were followed annually through 2020 to repeatedly assess their smoking status and disease progression. Survival probabilities and hazards for all-cause and cancer-specific mortality and disease progression were investigated using extended the Kaplan-Meier method, time-dependent Cox proportional hazards regression, and Fine-Gray competing-risk models.

Patients were followed for a median of 8.2 years. During this time, 110 cases of disease progression, 100 total deaths, and 77 cancer-specific deaths were recorded. Eighty-four patients (40%) quit smoking after diagnosis. The total person-years at risk for this analysis were 748.2 for continuing smoking and 611.2 for quitting smoking periods. At 5 years of follow-up, both overall survival (85% v 61%) and progression-free survival (80% v 57%) rates were higher during the quitting than continuing smoking periods (both P < .001). In the multivariable time-dependent models, quitting smoking was associated with lower risk of all-cause mortality (hazard ratio [HR], 0.51; 95% CI, 0.31 to 0.85), disease progression (HR, 0.45; 95% CI, 0.29 to 0.71), and cancer-specific mortality (HR, 0.54; 95% CI, 0.31 to 0.93). The beneficial effect of quitting smoking was evident across all subgroups, including light smokers versus moderate-heavy smokers and those with early-stage versus late-stage tumors.

Quitting smoking after RCC diagnosis may significantly improve survival and reduce the risk of disease progression and cancer mortality among patients who smoke.

INTRODUCTION

An estimated 430,000 individuals were diagnosed with kidney cancer and 180,000 died of this disease in 2020. 1 The burden of kidney cancer is higher in North America, Europe, and Oceania, where it ranks among the top 10 most common cancers. 1

• Key Objective
• Approximately 15%-20% of patients with kidney cancer are active smokers at diagnosis. In this study, we aimed to investigate whether quitting smoking could affect the risk of death and disease progression among patients with kidney cancer who smoke.
• Knowledge Generated
• Patients with kidney cancer who smoked at diagnosis were more likely to die when they continued smoking than when they quit smoking after diagnosis (24% v 6% at 3 years; 39% v 15% at 5 years). Quitting smoking after the diagnosis of kidney cancer was associated with almost 50% lower risk for death and 56% lower risk for disease progression. The beneficial effects of smoking cessation were evident across all patient subgroups, including those with early-stage versus late-stage tumors and patients who were light smokers versus moderate-heavy smokers at diagnosis.
• Relevance (M.A. Carducci)
• Although the findings of this report seem intuitive, this paper is important because there is a paucity of evidence that details the effects of cessation after cancer diagnosis. Interventions that support patients in their efforts to stop smoking should be encouraged to improve overall progression outcomes.*
• *Relevance section written by JCO Associate Editor Michael A. Carducci, MD, FACP, FASCO.

Smoking is a known cause of kidney cancer 2 and is estimated to account for 17% of the kidney cancer burden worldwide. 3 Approximately 15%-20% of patients with kidney cancer are active smokers at diagnosis. 4 , 5 Although studies have shown that quitting smoking can reduce the risk for developing kidney cancer, 6 , 7 evidence is limited on whether smokers can still benefit from quitting smoking after the diagnosis of kidney cancer. Limited evidence from retrospective studies indicates better survival among patients with kidney cancer who are former smokers than current smokers. 8 - 12 However, these studies are not conclusive as they have major limitations in their exposure assessment methods. Particularly, smoking data in these studies were either extracted from medical records or collected once at the time of diagnosis or treatment without accounting for the time of smoking cessation or later changes in smoking behavior. 8 - 13 Furthermore, there is no evidence on whether any effects of quitting smoking could vary between light versus moderate-heavy smokers and patients with early-stage versus late-stage kidney cancer.

We conducted a prospective study of patients who were newly diagnosed with kidney cancer and repeatedly assessed smoking behavior during an average follow-up of 8 years to investigate whether postdiagnosis smoking cessation could affect the risk of death and disease progression among these patients.

Study Population and Design

This study included patients with newly diagnosed primary renal cell carcinoma (RCC) who were originally enrolled to a large prospective cohort study of kidney cancer survival in Russia. Participants were enrolled between March 2007 and June 2016 from the Urological Department in the N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russia. The inclusion criteria were residing in Moscow region; having histologically confirmed RCC; not having undergone any previous local or systemic treatment (diagnostic biopsies excluded) for the current tumor; and being a current smoker at the time of diagnosis, which was defined as smoking at least one cigarette per day within the past year before the time of diagnosis. All participants provided written informed consent at enrollment. The study was approved by the ethical committees of the International Agency for Research on Cancer and the Blokhin National Medical Research Center of Oncology.

Baseline Interviews and Questionnaire Data

The participants were interviewed using a structured questionnaire that contained detailed questions on demographics, behavioral factors, different exposures, and health conditions including chronic kidney disease, hypertension, and diabetes mellitus. Height and weight were measured, and BMI was calculated.

Participants were asked about lifetime smoking history, which included queries about the duration and frequency of smoking cigarettes, as well as the average number of cigarettes smoked every day. Participants were also asked about lifetime history of regular alcohol drinking, which is defined as drinking alcoholic beverages at least once a week for 1 year.

Baseline Tumor Data

An expert local team was asked to review all relevant medical documents and complete a questionnaire that included information on the clinical and histopathologic features of the tumor and the existing illness. A central team at the International Agency for Research on Cancer performed regular quality control checks to ensure the quality of the filled questionnaires and data. The classification of tumor stage was performed using the medical documents at the time of diagnosis and before receiving any treatment, on the basis of the 7th edition of the TNM classification system that is proposed by the American Joint Committee on Cancer. 14

Follow-Up Data on Smoking, Clinical Interventions, and Disease Status

The participants were followed annually to record any changes in their smoking behavior and disease status. At each follow-up, the participants or their families were contacted and asked about quitting smoking and, when applicable, the time of smoking cessation. Participants were considered as smoking quitters if they reported to have quit smoking completely during the follow-up time. Otherwise, participants were categorized as continued smokers. During each follow-up, queries were made to collect detailed information on tumor progression, therapeutic interventions, and vital status. When applicable, the corresponding medical records were also reviewed by a local team to determine disease progression. Furthermore, the cohort data are linked to the Moscow cancer and death registries, to minimize the possibility of misclassifications in the outcomes and to record the primary and secondary causes of death, which was done according to the 10th Revision of the International Statistical Classification of Diseases and Related Health Problems. 15

Statistical Analysis

Because participants quit smoking at different time points during the follow-up, we treated quitting smoking as a time-dependent variable in all analyses. 16 - 21 In this approach, data from participants who quit smoking during the follow-up contribute differently than those who continued smoking. Particularly, for participants who quit smoking after diagnosis, the follow-up time is divided into subperiods, where each switch in smoking status (quitting or relapsing smoking) initiates a new subperiod. 16 - 21 For participants who quit smoking, the value of the time-dependent variable is 0 before the time of quitting and changes to 1 from the time of quitting smoking and onward. For those who continued smoking, the value remains 0 during the follow-up. For participants who quit and then relapsed smoking, the value of the time-dependent variable is 0 before the time of quitting and after the time of relapsing smoking. 16 - 21

We used extended Kaplan-Meier curves and Mantel-Byar tests to describe the probability of survival during the continuing smoking and quitting smoking periods. 16 - 18 We used time-dependent Cox proportional hazards regression models to investigate the association between quitting smoking and hazards of death and disease progression. 19 , 20 We further used Fine-Gray competing-risks regression models that account for death from other causes as the competing event, to evaluate the association between quitting smoking and hazards of kidney cancer–specific death. 21

In all models, we defined entry time as the date the participant was diagnosed with RCC, and date of the last contact was defined as the censoring date for participants who were alive at the last contact (through September 12, 2020). For participants who quit smoking during the follow-up, a subperiod that followed smoking after diagnosis was considered as starting at baseline and censored at the time of smoking cessation. Consequently, a subperiod that followed a switch to quitting smoking was considered left-truncated at the time of the switch. To assess the probability of overall survival and hazards of overall mortality, we defined end of follow-up as the date of death from any cause. To assess progression-free survival, we defined end of follow-up time as the date of death from any cause or date of tumor progression (local recurrence or metastasis), whichever occurred first. To assess kidney cancer–specific mortality, we defined end of follow-up time as the date of death from kidney cancer for the event of interest, and date of death from any other cause as the competing event.

The regression models were adjusted for age at diagnosis, sex, chronic health conditions, pack-years of cigarettes smoked, regular alcohol drinking status, tumor stage at diagnosis, and treatments received at the follow-up. All participants underwent surgery, while 34 received targeted therapy, and 12 received immunotherapy. Therefore, we combined targeted therapy and immunotherapy into one treatment variable. Further adjustments for year of diagnosis, education level, BMI at diagnosis, and tumor histology did not change the obtained estimates (Data Supplement, online only). Therefore, we did not include these variables in the main models. Five participants had missing data for the predictor variables and were therefore excluded from this analysis. For each model, we tested the proportional hazards assumption using Schoenfeld's global test, which was met for all variables in the multivariable models, except for tumor stage and treatment, which showed time-varying effects in some models and were therefore treated as time-varying covariates. 22

To account for potential confounders that might affect the survival estimates during the continuing and quitting smoking periods, we separately plotted the adjusted survival curves for each RCC stage. These curves were derived from the adjusted time-dependent regression models where the continuous variables were set at the median values and the categorical variables were set at the reference categories. 23 , 24

We performed stratified analyses and used interaction tests to assess whether the effects of quitting smoking are different across the strata of light smokers (smoked ≤26 pack-years at baseline) versus moderate-heavy smokers (smoked >26 pack-years at baseline), and patients with early-stage (I, II) versus late-stage (III, IV) RCC. For each stratum, we also assessed the association between quitting smoking and the overall survival using the extended Kaplan-Meier method and Mantel-Byar test (quitting smoking was treated as a time-dependent variable).

Since survivorship bias is the main concern in assessing the effect of exposures that vary over time, in addition to using a time-dependent variable for quitting smoking in the main analyses, we performed two sensitivity analyses by excluding participants who quit smoking after 3 and 12 months of diagnosis (ie, participants who survived longer and had more chance to quit smoking).

The type 1 error rate was set at 5% and the statistical analyses were two-sided. The data were analyzed using Stata statistical software version 17.0 (Stata Corporation, College Station, TX).

The study recruited 228 currently smoking patients with kidney RCC. Of these, 16 were excluded because of missing data for the predictor variables (n = 5), having unknown histology (n = 2), or having non–renal cell kidney tumors (n = 9). The remaining 212 current smoker patients with RCC were included in this analysis and none of them were lost to follow-up. The total person-years at risk for this analysis were 748.2 for continuing smoking and 611.2 for quitting smoking periods.

At enrollment, the median age for the included participants was 56.1 years (IQR, 50.4-60.8) and the median BMI was 27.4 (IQR, 24.1-31.4); 80% of the participants were male and 59% had a university degree. More than half of the participants (54%) were diagnosed with stage I tumors, and only few participants underwent targeted therapy (n = 34) or immunotherapy (n = 12; Table ​ Table1 1 ).

Baseline Demographical and Clinical Features Among All Patients, and the Subgroups of Patients Who Continued Smoking and Quit Smoking During the Follow-Up

During the follow-up, 84 participants (40%) reported to have quit smoking, none of whom reported relapsing during the follow up period, while 128 participants (60%) reported to have continued smoking after their diagnosis. Participants who quit versus continued smoking during the follow-up were similar across a range of demographic, behavioral factors, and clinical variables at the time of recruitment (Table ​ (Table1). 1 ). Of the 84 quitters, 47 (56%) quit shortly after diagnosis and before the time of receiving the first treatment, 30 (36%) quit after treatment initiation but during the first year after diagnosis, and seven (8%) quit after the first year of diagnosis (Data Supplement).

At follow-up, mortality and disease progression occurred less often during periods in which the patients quit smoking than when they continued smoking ( P < .001; Fig ​ Fig1). 1 ). The estimated probabilities of overall and progression-free survivals at 3 years were higher during the quitting than continuing smoking periods (overall survival, 94% v 76%; progression-free survival, 90% v 67%; P < .001 for both; Table ​ Table2; 2 ; Fig ​ Fig1). 1 ). Similarly, at 5 years, the probabilities of overall and progression-free survivals were higher during the quitting than continuing smoking periods (overall survival, 85% v 61%; progression-free survival, 80% v 57%; P < .001 for both; Table ​ Table2; 2 ; Fig ​ Fig1). 1 ). The higher probability of survival during the smoking cessation period was evident across all patient subgroups, including light smokers ( P = .007; Data Supplement), moderate-heavy smokers ( P = .013; Data Supplement), and patients with early-stage ( P = .025; Data Supplement) and late-stage ( P = .048; Data Supplement) tumors.

Extended Kaplan-Meier curves illustrating the probability of (A) overall survival (B) progression-free survival among smoker patients with renal cell carcinoma during the quitting smoking versus continuing smoking periods. P values were obtained from the Mantel-Byar test for comparing time-dependent survival data.

Estimates of Survival Among Patients With Renal Cell Carcinoma Who Smoked at the Time of Diagnosis, During Periods of Continued Smoking Compared With Periods of Smoking Cessation

In the multivariable time-dependent regression models, quitting smoking after the diagnosis of cancer was associated with lower risk of all-cause mortality (hazard ratio [HR], 0.51; 95% CI, 0.31 to 0.85), disease progression (tumor recurrence, metastasis, or death; HR, 0.45; 95% CI, 0.29 to 0.71), and kidney cancer–specific death (HR, 0.54; 95% CI, 0.31 to 0.93; Table ​ Table3). 3 ). The beneficial effects of quitting smoking on the hazards of death and disease progression remained comparable after excluding participants who quit smoking after 12 and 3 months of diagnosis (Table ​ (Table3). 3 ). In the stratified analyses, quitting smoking was similarly beneficial for light smokers versus moderate-heavy smokers (Data Supplement), and also for patients with early-stage versus late-stage tumors (Data Supplement).

The Association Between Postdiagnosis Smoking Cessation and Different Outcomes Among Patients With Renal Cell Carcinoma Who Smoked at Diagnosis

The estimated survival probabilities, which were derived from the adjusted time-dependent regression models, consistently showed higher overall and progression-free survival probabilities during the quitting than continuing smoking periods across all RCC stages (Fig ​ (Fig2; 2 ; Data Supplement).

Adjusted survival curves illustrating the probability of overall survival during the quitting smoking versus continuing smoking periods in a 56-year-old male smoker with renal cell carcinoma (A) stage I, (B) stage II, (C) stage III, and (D) stage IV. Estimates are derived from adjusted time-dependent Cox regression models where smoking cessation was treated as a time-varying variable, the continuous covariates were set at the median value (age: 56, smoking: 26 pack-years), and the categorical variables were set at the reference category (male, without chronic health conditions, never regular alcohol drinker, and did not receive targeted/immunotherapy during the follow-up).

In this prospective cohort study, we followed 212 currently smoking patients with RCC for an average of 8 years, of whom 84 participants quit smoking during the follow-up time. At follow-up, the overall and cancer-free survival rates were significantly higher during the quitting than continuing smoking periods. Compared with continuing smoking, quitting smoking was consistently associated with lower hazards of death and disease progression. The beneficial effects of quitting smoking were evident among light smokers and moderate-heavy smokers, as well as among patients with early-stage and late-stage tumors.

To our knowledge, this is the first study that prospectively evaluates the effects of smoking cessation after diagnosis among smoker patients with kidney cancer. In this study, we repeatedly assessed smoking status during the follow-up and found that quitting smoking after diagnosis was associated with almost 50% lower risk for overall death, 46% lower risk for cancer-specific death, and 55% lower risk for disease progression compared with continuing smoking. Previous studies on this topic have been primarily retrospective studies that assessed the effects of smoking status at diagnosis on subsequent RCC survival. A meta-analysis of 14 studies with 343,993 patients with RCC showed that current smokers at diagnosis have almost 60% increased risk of death and around three times increased risk for having poorer progression-free survival than never smokers, while a subgroup analysis of two studies that had investigated the effects of former smoking showed no increased risk for mortality among those who had quit smoking before the time of diagnosis. 13 Another meta-analysis of 24 studies showed a higher risk for RCC incidence among both current (29%) and former (14%) smokers, while the risk for RCC death was 32% higher among current smokers and was null among former smokers. 6 A recent study by Kroeger et al 12 assessed the effects of smoking status at the time of starting targeted therapy on the survival of 1,980 patients with metastatic RCC, and reported a poorer survival among current smokers than never and former smokers. However, similar to other previous studies, smoking status was retrospectively obtained from medical charts or screening forms, and the time of smoking cessation could not be reliably determined. 12

Of all smoker patients in this cohort, 60% continued smoking through the course of their disease, leading to a significant number of extra deaths and progression events. Our results show that the benefits of quitting smoking (which is potentially feasible for all patients and could benefit patients financially) may be similar or even superior to the emerging targeted and immunotherapy treatments that are expensive, require specialized settings, and cannot be accessed by many patients. 25 , 26 We previously observed a similarly significant effect for postdiagnosis smoking cessation on the survival of smoker patients with lung cancer. 27 This evidence highlights the need for collaborative efforts to implement smoking treatment as an integral part of cancer management in patients who smoke. This is particularly important as smoker patients with cancer might feel fatalistic or may not realize that the benefits of smoking cessation apply even after cancer diagnosis. Furthermore, evidence shows that most smoker patients with cancer do not feel ready to quit after the diagnosis and there is still of subset of smoker patients with cancer who are not even recommended by their physicians to quit smoking. 28 - 31

Several biologically plausible mechanisms have been suggested by which smoking can reduce survival in patients with cancer; cigarette smoke contains many carcinogens and mutagens that can directly affect tumor cells and increase their proliferation, migration, invasion, and angiogenesis. 32 Furthermore, smoking can impair the immune response to malignant growth, 32 , 33 affect the response to and complications from some cancer treatments, 34 and accelerate other illnesses including cardiovascular and other chronic diseases in patients with cancer. 34 , 35

To our knowledge, this is the first study that prospectively investigates the effect of quitting smoking after diagnosis of kidney cancer on disease progression and survival rates with repeated assessments of smoking status during the follow-up and a long follow-up period. Also, to our knowledge, this is the first study that showed the beneficial effects of smoking cessation across different subgroups of patients with RCC on the basis of their baseline tumor stage and pack-years of cigarettes smoked. Finally, we used stringent statistical methods to address confounding and survivorship bias. This study also has some limitations including being an observational study with the possibility of measurement errors in the exposure and outcomes. Smoking status was based on self-report, which could have resulted in misclassification. However, the prospective nature of the study and repeated assessment of smoking status could have minimized the possibility of inaccurate responses. Also, if there is any misclassification, it is anticipated to result from over-reporting smoking cessation, which consequently could bias the results toward the null. Another limitation of the current study is its small sample size for the subgroup analyses. Despite observing comparable estimates from the adjusted models across different strata, the estimates from the stratified analyses should be interpreted with caution as there were a small number of outcome cases in some of the strata.

In conclusion, this study provides strong evidence that quitting smoking after the diagnosis of kidney cancer can significantly improve the survival and reduce the risk of disease progression among these patients. Given that up to 20% of patients with kidney cancer are current smokers at diagnosis and most will continue to smoke afterward, 4 , 5 it is critical to integrate smoking treatment into the routine management of these patients.

Honoraria: Ipsen, Bayer, AstraZeneca, Janssen, Astellas Pharma, MSD

Expert Testimony: BMS, Bayer, MSD, Janssen

No other potential conflicts of interest were reported.

Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/World Health Organization.

PRIOR PRESENTATION

Presented in part as an abstract at the World Cancer Congress, Geneva, Switzerland, October 18-20, 2022.

Supported by the International Agency for Research on Cancer (IARC—WHO).

AUTHOR CONTRIBUTIONS

Conception and design: Mahdi Sheikh, Anush Mukeriya, Paul Brennan, David Zaridze

Administrative support: Mahdi Sheikh, Paul Brennan

Provision of study materials or patients: Anush Mukeriya

Collection and assembly of data: Mahdi Sheikh, Anush Mukeriya, Oxana Shangina, Vsevolod Matveev, Paul Brennan, David Zaridze

Data analysis and interpretation: Mahdi Sheikh, Anush Mukeriya, Hana Zahed, Xiaoshuang Feng, Hilary A. Robbins, Paul Brennan, David Zaridze

Manuscript writing: All authors

Final approval of manuscript: All authors

Accountable for all aspects of the work: All authors

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

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