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• Published: 24 March 2022

Tobacco and nicotine use

• Bernard Le Foll 1 , 2 ,
• Megan E. Piper 3 , 4 ,
• Christie D. Fowler 5 ,
• Serena Tonstad 6 ,
• Laura Bierut 7 ,
• Lin Lu   ORCID: orcid.org/0000-0003-0742-9072 8 , 9 ,
• Prabhat Jha 10 &
• Wayne D. Hall 11 , 12  

Nature Reviews Disease Primers volume  8 , Article number:  19 ( 2022 ) Cite this article

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• Disease genetics
• Experimental models of disease
• Preventive medicine

Tobacco smoking is a major determinant of preventable morbidity and mortality worldwide. More than a billion people smoke, and without major increases in cessation, at least half will die prematurely from tobacco-related complications. In addition, people who smoke have a significant reduction in their quality of life. Neurobiological findings have identified the mechanisms by which nicotine in tobacco affects the brain reward system and causes addiction. These brain changes contribute to the maintenance of nicotine or tobacco use despite knowledge of its negative consequences, a hallmark of addiction. Effective approaches to screen, prevent and treat tobacco use can be widely implemented to limit tobacco’s effect on individuals and society. The effectiveness of psychosocial and pharmacological interventions in helping people quit smoking has been demonstrated. As the majority of people who smoke ultimately relapse, it is important to enhance the reach of available interventions and to continue to develop novel interventions. These efforts associated with innovative policy regulations (aimed at reducing nicotine content or eliminating tobacco products) have the potential to reduce the prevalence of tobacco and nicotine use and their enormous adverse impact on population health.

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Tobacco is the second most commonly used psychoactive substance worldwide, with more than one billion smokers globally 1 . Although smoking prevalence has reduced in many high-income countries (HICs), tobacco use is still very prevalent in low-income and middle-income countries (LMICs). The majority of smokers are addicted to nicotine delivered by cigarettes (defined as tobacco dependence in the International Classification of Diseases, Tenth Revision (ICD-10) or tobacco use disorder in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)). As a result of the neuro-adaptations and psychological mechanisms caused by repeated exposure to nicotine delivered rapidly by cigarettes, cessation can also lead to a well-characterized withdrawal syndrome, typically manifesting as irritability, anxiety, low mood, difficulty concentrating, increased appetite, insomnia and restlessness, that contributes to the difficulty in quitting tobacco use 2 , 3 , 4 .

Historically, tobacco was used in some cultures as part of traditional ceremonies, but its use was infrequent and not widely disseminated in the population. However, since the early twentieth century, the use of commercial cigarettes has increased dramatically 5 because of automated manufacturing practices that enable large-scale production of inexpensive products that are heavily promoted by media and advertising. Tobacco use became highly prevalent in the past century and was followed by substantial increases in the prevalence of tobacco-induced diseases decades later 5 . It took decades to establish the relationship between tobacco use and associated health effects 6 , 7 and to discover the addictive role of nicotine in maintaining tobacco smoking 8 , 9 , and also to educate people about these effects. It should be noted that the tobacco industry disputed this evidence to allow continuing tobacco sales 10 . The expansion of public health campaigns to reduce smoking has gradually decreased the use of tobacco in HICs, with marked increases in adult cessation, but less progress has been achieved in LMICs 1 .

Nicotine is the addictive compound in tobacco and is responsible for continued use of tobacco despite harms and a desire to quit, but nicotine is not directly responsible for the harmful effects of using tobacco products (Box  1 ). Other components in tobacco may modulate the addictive potential of tobacco (for example, flavours and non-nicotine compounds) 11 . The major harms related to tobacco use, which are well covered elsewhere 5 , are linked to a multitude of compounds present in tobacco smoke (such as carcinogens, toxicants, particulate matter and carbon monoxide). In adults, adverse health outcomes of tobacco use include cancer in virtually all peripheral organs exposed to tobacco smoke and chronic diseases such as eye disease, periodontal disease, cardiovascular diseases, chronic obstructive pulmonary disease, stroke, diabetes mellitus, rheumatoid arthritis and disorders affecting immune function 5 . Moreover, smoking during pregnancy can increase the risk of adverse reproductive effects, such as ectopic pregnancy, low birthweight and preterm birth 5 . Exposure to secondhand cigarette smoke in children has been linked to sudden infant death syndrome, impaired lung function and respiratory illnesses, in addition to cognitive and behavioural impairments 5 . The long-term developmental effects of nicotine are probably due to structural and functional changes in the brain during this early developmental period 12 , 13 .

Nicotine administered alone in various nicotine replacement formulations (such as patches, gum and lozenges) is safe and effective as an evidence-based smoking cessation aid. Novel forms of nicotine delivery systems have also emerged (called electronic nicotine delivery systems (ENDS) or e-cigarettes), which can potentially reduce the harmful effects of tobacco smoking for those who switch completely from combustible to e-cigarettes 14 , 15 .

This Primer focuses on the determinants of nicotine and tobacco use, and reviews the neurobiology of nicotine effects on the brain reward circuitry and the functioning of brain networks in ways that contribute to the difficulty in stopping smoking. This Primer also discusses how to prevent tobacco use, screen for smoking, and offer people who smoke tobacco psychosocial and pharmacological interventions to assist in quitting. Moreover, this Primer presents emerging pharmacological and novel brain interventions that could improve rates of successful smoking cessation, in addition to public health approaches that could be beneficial.

Box 1 Tobacco products

Conventional tobacco products include combustible products that produce inhaled smoke (most commonly cigarettes, bidis (small domestically manufactured cigarettes used in South Asia) or cigars) and those that deliver nicotine without using combustion (chewing or dipping tobacco and snuff). Newer alternative products that do not involve combustion include nicotine-containing e-cigarettes and heat-not-burn tobacco devices. Although non-combustion and alternative products may constitute a lesser risk than burned ones 14 , 15 , 194 , no form of tobacco is entirely risk-free.

Epidemiology

Prevalence and burden of disease.

The Global Burden of Disease Project (GBDP) estimated that around 1.14 billion people smoked in 2019, worldwide, increasing from just under a billion in 1990 (ref. 1 ). Of note, the prevalence of smoking decreased significantly between 1990 and 2019, but increases in the adult population meant that the total number of global smokers increased. One smoking-associated death occurs for approximately every 0.8–1.1 million cigarettes smoked 16 , suggesting that the estimated worldwide consumption of about 7.4 trillion cigarettes in 2019 has led to around 7 million deaths 1 .

In most populations, smoking prevalence is much higher among groups with lower levels of education or income 17 and among those with mental health disorders and other co-addictions 18 , 19 . Smoking is also more frequent among men than women (Figs  1 – 3 ). Sexual and/or gender minority individuals have disproportionately high rates of smoking and other addictions 17 , 20 . In addition, the prevalence of smoking varies substantially between regions and ethnicities; smoking rates are high in some regions of Asia, such as China and India, but are lower in North America and Australia. Of note, the prevalence of mental health disorders and other co-addictions is higher in individuals who smoke compared with non-smokers 18 , 19 , 21 . For example, the odds of smoking in people with any substance use disorder is more than five times higher than the odds in people without a substance use disorder 19 . Similarly, the odds of smoking in people with any psychiatric disorder is more than three times higher than the odds of smoking in those without a psychiatric diagnosis 22 . In a study in the USA, compared with a population of smokers with no psychiatric diagnosis, subjects with anxiety, depression and phobia showed an approximately twofold higher prevalence of smoking, and subjects with agoraphobia, mania or hypomania, psychosis and antisocial personality or conduct disorders showed at least a threefold higher prevalence of smoking 22 . Comorbid disorders are also associated with higher rates of smoking 22 , 23 .

a | Number of current male smokers aged 15 years or older per country expressed in millions. b | Former male smokers aged 45–59 years per country expressed in millions. c | Former male smokers aged 45–59 years per country expressed as the percentage of smokers who stopped. The data shown are for male smokers for the period 2015–2019 from countries with direct smoking surveys. The prevalence of smoking among males is less variable than among females. Data from ref. 1 .

a | Number of current female smokers aged 15 years or older per country expressed in millions. b | Former female smokers aged 45–59 years per country expressed in millions. c | Former female smokers aged 45–59 years per country expressed as the percentage of smokers who stopped. The data shown are for female smokers for the period 2015–2019 from countries with direct smoking surveys. The prevalence of smoking among females is much lower in East and South Asia than in Latin America or Eastern Europe. Data from ref. 1 .

a | Number of current male and female smokers aged 15 years or older per country expressed in millions. b | Former male and female smokers aged 45–59 years per country expressed in millions. c | Former male and female smokers aged 45–59 years per country expressed as the percentage of smokers who stopped. The data shown are for the period 2015–2019 from countries with direct smoking surveys. Cessation rates are higher in high-income countries, but also notably high in Brazil. Cessation is far less common in South and East Asia and Russia and other Eastern European countries, and also low in South Africa. Data from ref. 1 .

Age at onset

Most smokers start smoking during adolescence, with almost 90% of smokers beginning between 15 and 25 years of age 24 . The prevalence of tobacco smoking among youths substantially declined in multiple HICs between 1990 and 2019 (ref. 25 ). More recently, the widespread uptake of ENDS in some regions such as Canada and the USA has raised concerns about the long-term effects of prolonged nicotine use among adolescents, including the possible notion that ENDS will increase the use of combustible smoking products 25 , 26 (although some studies have not found much aggregate effect at the population level) 27 .

Smoking that commences in early adolescence or young adulthood and persists throughout life has a more severe effect on health than smoking that starts later in life and/or that is not persistent 16 , 28 , 29 . Over 640 million adults under 30 years of age smoke in 22 jurisdictions alone (including 27 countries in the European Union where central efforts to reduce tobacco dependence might be possible) 30 . In those younger than 30 years of age, at least 320 million smoking-related deaths will occur unless they quit smoking 31 . The actual number of smoking-related deaths might be greater than one in two, and perhaps as high as two in three, long-term smokers 5 , 16 , 29 , 32 , 33 . At least half of these deaths are likely to occur in middle age (30–69 years) 16 , 29 , leading to a loss of two or more decades of life. People who smoke can expect to lose an average of at least a decade of life versus otherwise similar non-smokers 16 , 28 , 29 .

Direct epidemiological studies in several countries paired with model-based estimates have estimated that smoking tobacco accounted for 7.7 million deaths globally in 2020, of which 80% were in men and 87% were current smokers 1 . In HICs, the major causes of tobacco deaths are lung cancer, emphysema, heart attack, stroke, cancer of the upper aerodigestive areas and bladder cancer 28 , 29 . In some lower income countries, tuberculosis is an additional important cause of tobacco-related death 29 , 34 , which could be related to, for example, increased prevalence of infection, more severe tuberculosis/mortality and higher prevalence of treatment-resistant tuberculosis in smokers than in non-smokers in low-income countries 35 , 36 .

Despite substantial reductions in the prevalence of smoking, there were 34 million smokers in the USA, 7 million in the UK and 5 million in Canada in 2017 (ref. 16 ), and cigarette smoking remains the largest cause of premature death before 70 years of age in much of Europe and North America 1 , 16 , 28 , 29 . Smoking-associated diseases accounted for around 41 million deaths in the USA, UK and Canada from 1960 to 2020 (ref. 16 ). Moreover, as smoking-associated diseases are more prevalent among groups with lower levels of education and income, smoking accounts for at least half of the difference in overall mortality between these social groups 37 . Any reduction in smoking prevalence reduces the absolute mortality gap between these groups 38 .

Smoking cessation has become common in HICs with good tobacco control interventions. For example, in France, the number of ex-smokers is four times the number of current smokers among those aged 50 years or more 30 . By contrast, smoking cessation in LMICs remains uncommon before smokers develop tobacco-related diseases 39 . Smoking cessation greatly reduces the risks of smoking-related diseases. Indeed, smokers who quit smoking before 40 years of age avoid nearly all the increased mortality risks 31 , 33 . Moreover, individuals who quit smoking by 50 years of age reduce the risk of death from lung cancer by about two-thirds 40 . More modest hazards persist for deaths from lung cancer and emphysema 16 , 28 ; however, the risks among former smokers are an order of magnitude lower than among those who continue to smoke 33 .

Mechanisms/pathophysiology

Nicotine is the main psychoactive agent in tobacco and e-cigarettes. Nicotine acts as an agonist at nicotinic acetylcholine receptors (nAChRs), which are localized throughout the brain and peripheral nervous system 41 . nAChRs are pentameric ion channels that consist of varying combinations of α 2 –α 7 and β 2 –β 4 subunits, and for which acetylcholine (ACh) is the endogenous ligand 42 , 43 , 44 . When activated by nicotine binding, nAChR undergoes a conformational change that opens the internal pore, allowing an influx of sodium and calcium ions 45 . At postsynaptic membranes, nAChR activation can lead to action potential firing and downstream modulation of gene expression through calcium-mediated second messenger systems 46 . nAChRs are also localized to presynaptic membranes, where they modulate neurotransmitter release 47 . nAChRs become desensitized after activation, during which ligand binding will not open the channel 45 .

nAChRs with varying combinations of α-subunits and β-subunits have differences in nicotine binding affinity, efficacy and desensitization rate, and have differential expression depending on the brain region and cell type 48 , 49 , 50 . For instance, at nicotine concentrations found in human smokers, β 2 -containing nAChRs desensitize relatively quickly after activation, whereas α 7 -containing nAChRs have a slower desensitization profile 48 . Chronic nicotine exposure in experimental animal models or in humans induces an increase in cortical expression of α 4 β 2 -containing nAChRs 51 , 52 , 53 , 54 , 55 , but also increases the expression of β 3 and β 4 nAChR subunits in the medial habenula (MHb)–interpeduncular nucleus (IPN) pathway 56 , 57 . It is clear that both the brain localization and the type of nAChR are critical elements in mediating the various effects of nicotine, but other factors such as rate of nicotine delivery may also modulate addictive effects of nicotine 58 .

Neurocircuitry of nicotine addiction

Nicotine has both rewarding effects (such as a ‘buzz’ or ‘high’) and aversive effects (such as nausea and dizziness), with the net outcome dependent on dose and others factors such as interindividual sensitivity and presence of tolerance 59 . Thus, the addictive properties of nicotine involve integration of contrasting signals from multiple brain regions that process reward and aversion (Fig.  4 ).

During initial use, nicotine exerts both reinforcing and aversive effects, which together determine the likelihood of continued use. As the individual transitions to more frequent patterns of chronic use, nicotine induces pharmacodynamic changes in brain circuits, which is thought to lead to a reduction in sensitivity to the aversive properties of the drug. Nicotine is also a powerful reinforcer that leads to the conditioning of secondary cues associated with the drug-taking experience (such as cigarette pack, sensory properties of cigarette smoke and feel of the cigarette in the hand or mouth), which serves to enhance the incentive salience of these environmental factors and drive further drug intake. When the individual enters into states of abstinence (such as daily during sleep at night or during quit attempts), withdrawal symptomology is experienced, which may include irritability, restlessness, learning or memory deficits, difficulty concentrating, anxiety and hunger. These negative affective and cognitive symptoms lead to an intensification of the individual’s preoccupation to obtain and use the tobacco/nicotine product, and subsequently such intense craving can lead to relapse.

The rewarding actions of nicotine have largely been attributed to the mesolimbic pathway, which consists of dopaminergic neurons in the ventral tegmental area (VTA) that project to the nucleus accumbens and prefrontal cortex 60 , 61 , 62 (Fig.  5 ). VTA integrating circuits and projection regions express several nAChR subtypes on dopaminergic, GABAergic, and glutamatergic neurons 63 , 64 . Ultimately, administration of nicotine increases dopamine levels through increased dopaminergic neuron firing in striatal and extrastriatal areas (such as the ventral pallidum) 65 (Fig.  6 ). This effect is involved in reward and is believed to be primarily mediated by the action of nicotine on α 4 -containing and β 2 -containing nAChRs in the VTA 66 , 67 .

Multiple lines of research have demonstrated that nicotine reinforcement is mainly controlled by two brain pathways, which relay predominantly reward-related or aversion-related signals. The rewarding properties of nicotine that promote drug intake involve the mesolimbic dopamine projection from the ventral tegmental area (VTA) to the nucleus accumbens (NAc). By contrast, the aversive properties of nicotine that limit drug intake and mitigate withdrawal symptoms involve the fasciculus retroflexus projection from the medial habenula (MHb) to the interpeduncular nucleus (IPN). Additional brain regions have also been implicated in various aspects of nicotine dependence, such as the prefrontal cortex (PFC), ventral pallidum (VP), nucleus tractus solitarius (NTS) and insula (not shown here for clarity). All of these brain regions are directly or indirectly interconnected as integrative circuits to drive drug-seeking and drug-taking behaviours.

Smokers received brain PET scans with [ 11 C]PHNO, a dopamine D 2/3 PET tracer that has high sensitivity in detecting fluctuations of dopamine. PET scans were performed during abstinence or after smoking a cigarette. Reduced binding potential (BP ND ) was observed after smoking, indicating increased dopamine levels in the ventral striatum and in the area that corresponds to the ventral pallidum. The images show clusters with statistically significant decreases of [ 11 C]PHNO BP ND after smoking a cigarette versus abstinence condition. Those clusters have been superimposed on structural T1 MRI images of the brain. Reprinted from ref. 65 , Springer Nature Limited.

The aversive properties of nicotine are mediated by neurons in the MHb, which project to the IPN. Studies in rodents using genetic knockdown and knockout strategies demonstrated that the α 5 -containing, α 3 -containing and β 4 -containing nAChRs in the MHb–IPN pathway mediate the aversive properties of nicotine that limit drug intake, especially when animals are given the opportunity to consume higher nicotine doses 68 , 69 , 70 , 71 , 72 . In addition to nAChRs, other signalling factors acting on the MHb terminals in the IPN also regulate the actions of nicotine. For instance, under conditions of chronic nicotine exposure or with optogenetic activation of IPN neurons, a subtype of IPN neurons co-expressing Chrna5 (encoding the α 5 nAChR subunit) and Amigo1 (encoding adhesion molecule with immunoglobulin-like domain 1) release nitric oxide from the cell body that retrogradely inhibits MHb axon terminals 70 . In addition, nicotine activates α 5 -containing nAChR-expressing neurons that project from the nucleus tractus solitarius to the IPN, leading to release of glucagon-like peptide-1 that binds to GLP receptors on habenular axon terminals, which subsequently increases IPN neuron activation and decreases nicotine self-administration 73 . Taken together, these findings suggest a dynamic signalling process at MHb axonal terminals in the IPN, which regulates the addictive properties of nicotine and determines the amount of nicotine that is self-administered.

Nicotine withdrawal in animal models can be assessed by examining somatic signs (such as shaking, scratching, head nods and chewing) and affective signs (such as increased anxiety-related behaviours and conditioned place aversion). Interestingly, few nicotine withdrawal somatic signs are found in mice with genetic knockout of the α 2 , α 5 or β 4 nAChR subunits 74 , 75 . By contrast, β 2 nAChR-knockout mice have fewer anxiety-related behaviours during nicotine withdrawal, with no differences in somatic symptoms compared with wild-type mice 74 , 76 .

In addition to the VTA (mediating reward) and the MHb–IPN pathway (mediating aversion), other brain areas are involved in nicotine addiction (Fig.  5 ). In animals, the insular cortex controls nicotine taking and nicotine seeking 77 . Moreover, humans with lesions of the insular cortex can quit smoking easily without relapse 78 . This finding led to the development of a novel therapeutic intervention modulating insula function (see Management, below) 79 , 80 . Various brain areas (shell of nucleus accumbens, basolateral amygdala and prelimbic cortex) expressing cannabinoid CB 1 receptors are also critical in controlling rewarding effects and relapse 81 , 82 . The α 1 -adrenergic receptor expressed in the cortex also control these effects, probably through glutamatergic afferents to the nucleus accumbens 83 .

Individual differences in nicotine addiction risk

Vulnerability to nicotine dependence varies between individuals, and the reasons for these differences are multidimensional. Many social factors (such as education level and income) play a role 84 . Broad psychological and social factors also modulate this risk. For example, peer smoking status, knowledge on effect of tobacco, expectation on social acceptance, exposure to passive smoking modulate the risk of initiating tobacco use 85 , 86 .

Genetic factors have a role in smoking initiation, the development of nicotine addiction and the likelihood of smoking cessation. Indeed, heritability has been estimated to contribute to approximatively half of the variability in nicotine dependence 87 , 88 , 89 , 90 . Important advances in our understanding of such genetic contributions have evolved with large-scale genome-wide association studies of smokers and non-smokers. One of the most striking findings has been that allelic variation in the CHRNA5 – CHRNA3 – CHRNB4 gene cluster, which encodes α 5 , α 3 and β 4 nAChR subunits, correlates with an increased vulnerability for nicotine addiction, indicated by a higher likelihood of becoming dependent on nicotine and smoking a greater number of cigarettes per day 91 , 92 , 93 , 94 , 95 . The most significant effect has been found for a single-nucleotide polymorphism in CHRNA5 (rs16969968), which results in an amino acid change and reduced function of α 5 -containing nAChRs 92 .

Allelic variation in CYP2A6 (encoding the CYP2A6 enzyme, which metabolizes nicotine) has also been associated with differential vulnerability to nicotine dependence 96 , 97 , 98 . CYP2A6 is highly polymorphic, resulting in variable enzymatic activity 96 , 99 , 100 . Individuals with allelic variation that results in slow nicotine metabolism consume less nicotine per day, experience less-severe withdrawal symptoms and are more successful at quitting smoking than individuals with normal or fast metabolism 101 , 102 , 103 , 104 . Moreover, individuals with slow nicotine metabolism have lower dopaminergic receptor expression in the dopamine D2 regions of the associative striatum and sensorimotor striatum in PET studies 105 and take fewer puffs of nicotine-containing cigarettes (compared with de-nicotinized cigarettes) in a forced choice task 106 . Slower nicotine metabolism is thought to increase the duration of action of nicotine, allowing nicotine levels to accumulate over time, therefore enabling lower levels of intake to sustain activation of nAChRs 107 .

Large-scale genetic studies have identified hundreds of other genetic loci that influence smoking initiation, age of smoking initiation, cigarettes smoked per day and successful smoking cessation 108 . The strongest genetic contributions to smoking through the nicotinic receptors and nicotine metabolism are among the strongest genetic contributors to lung cancer 109 . Other genetic variations (such as those related to cannabinoid, dopamine receptors or other neurotransmitters) may affect certain phenotypes related to smoking (such as nicotine preference and cue-reactivity) 110 , 111 , 112 , 113 , 114 , 115 .

Diagnosis, screening and prevention

Screening for cigarette smoking.

Screening for cigarette smoking should happen at every doctor’s visit 116 . In this regard, a simple and direct question about a person’s tobacco use can provide an opportunity to offer information about its potential risks and treatments to assist in quitting. All smokers should be offered assistance in quitting because even low levels of smoking present a significant health risk 33 , 117 , 118 . Smoking status can be assessed by self-categorization or self-reported assessment of smoking behaviour (Table  1 ). In people who smoke, smoking frequency can be assessed 119 and a combined quantity frequency measure such as pack-year history (that is, average number of cigarettes smoked per day multiplied by the number of years, divided by 20), can be used to estimate cumulative risk of adverse health outcomes. The Association for the Treatment of Tobacco Use and Dependence recommends that all electronic health records should document smoking status using the self-report categories listed in Table  1 .

Owing to the advent of e-cigarettes and heat-not-burn products, and the popularity of little cigars in the US that mimic combustible cigarettes, people who use tobacco may use multiple products concurrently 120 , 121 . Thus, screening for other nicotine and tobacco product use is important in clinical practice. The self-categorization approach can also be used to describe the use of these other products.

Traditionally tobacco use has been classified according to whether the smoker meets criteria for nicotine dependence in one of the two main diagnostic classifications: the DSM 122 (tobacco use disorder) and the ICD (tobacco dependence) 123 . The diagnosis of tobacco use disorder according to DSM-5 criteria requires the presence of at least 2 of 11 symptoms that have produced marked clinical impairment or distress within a 12-month period (Box  2 ). Of note, these symptoms are similar for all substance use disorder diagnoses and may not all be relevant to tobacco use disorder (such as failure to complete life roles). In the ICD-10, codes allow the identification of specific tobacco products used (cigarettes, chewing tobacco and other tobacco products).

Dependence can also be assessed as a continuous construct associated with higher levels of use, greater withdrawal and reduced likelihood of quitting. The level of dependence can be assessed with the Fagerström Test for Nicotine Dependence, a short questionnaire comprising six questions 124 (Box  2 ). A score of ≥4 indicates moderate to high dependence. As very limited time may be available in clinical consultations, the Heaviness of Smoking Index (HSI) was developed, which comprises two questions on the number of cigarettes smoked per day and how soon after waking the first cigarette is smoked 125 . The HSI can guide dosing for nicotine replacement therapy (NRT).

Other measures of cigarette dependence have been developed but are not used in the clinical setting, such as the Cigarette Dependence Scale 126 , Hooked on Nicotine Checklist 127 , Nicotine Dependence Syndrome Scale 128 , the Wisconsin Inventory of Smoking Dependence Motives (Brief) 129 and the Penn State Cigarette Dependence Index 130 . However, in practice, these are not often used, as the most important aspect is to screen for smoking and encourage all smokers to quit smoking regardless of their dependence status.

Box 2 DSM-5 criteria for tobacco use disorder and items of the Fagerström Test for nicotine dependence

DSM-5 (ref. 122 )

Taxonomic and diagnostic tool for tobacco use disorder published by the American Psychiatric Association.

A problematic pattern of tobacco use leading to clinically significant impairment or distress as manifested by at least two of the following, occurring within a 12-month period.

Tobacco often used in larger amounts or over a longer period of time than intended

A persistent desire or unsuccessful efforts to reduce or control tobacco use

A great deal of time spent in activities necessary to obtain or use tobacco

Craving, or a strong desire or urge to use tobacco

Recurrent tobacco use resulting in a failure to fulfil major role obligations at work, school or home

Continued tobacco use despite having persistent or recurrent social or interpersonal problems caused or exacerbated by the effects of tobacco (for example, arguments with others about tobacco use)

Important social, occupational or recreational activities given up or reduced because of tobacco use

Recurrent tobacco use in hazardous situations (such as smoking in bed)

Tobacco use continued despite knowledge of having a persistent or recurrent physical or psychological problem that is likely to have been caused or exacerbated by tobacco use

Tolerance, defined by either of the following.

A need for markedly increased amounts of tobacco to achieve the desired effect

A markedly diminished effect with continued use of the same amount of tobacco

Withdrawal, manifesting as either of the following.

Withdrawal syndrome for tobacco

Tobacco (or a closely related substance, such as nicotine) taken to relieve or avoid withdrawal symptoms

Fagerström Test for Nicotine Dependence 124

A standard instrument for assessing the intensity of physical addiction to nicotine.

How soon after you wake up do you smoke your first cigarette?

Within 5 min (scores 3 points)

5 to 30 min (scores 2 points)

31 to 60 min (scores 1 point)

After 60 min (scores 0 points)

Do you find it difficult not to smoke in places where you should not, such as in church or school, in a movie, at the library, on a bus, in court or in a hospital?

Yes (scores 1 point)

No (scores 0 points)

Which cigarette would you most hate to give up; which cigarette do you treasure the most?

The first one in the morning (scores 1 point)

Any other one (scores 0 points)

How many cigarettes do you smoke each day?

10 or fewer (scores 0 points)

11 to 20 (scores 1 point)

21 to 30 (scores 2 points)

31 or more (scores 3 points)

Do you smoke more during the first few hours after waking up than during the rest of the day?

Do you still smoke if you are so sick that you are in bed most of the day or if you have a cold or the flu and have trouble breathing?

A score of 7–10 points is classified as highly dependent; 4–6 points is classified as moderately dependent; <4 points is classified as minimally dependent.

DSM-5, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

Young people who do not start smoking cigarettes between 15 and 25 years of age have a very low risk of ever smoking 24 , 131 , 132 . This age group provides a critical opportunity to prevent cigarette smoking using effective, evidence-based strategies to prevent smoking initiation and reduce escalation from experimentation to regular use 131 , 132 , 133 , 134 , 135 .

Effective prevention of cigarette uptake requires a comprehensive package of cost-effective policies 134 , 136 , 137 to synergistically reduce the population prevalence of cigarette smoking 131 , 135 . These policies include high rates of tobacco taxation 30 , 134 , 137 , 138 , widespread and rigorously enforced smoke-free policies 139 , bans on tobacco advertising and promotions 140 , use of plain packaging and graphic warnings about the health risks of smoking 135 , 141 , mass media and peer-based education programmes to discourage smoking, and enforcement of laws against the sale of cigarettes to young people below the minimum legal purchase age 131 , 135 . These policies make cigarettes less available and affordable to young people. Moreover, these policies make it more difficult for young people to purchase cigarettes and make smoking a much less socially acceptable practice. Of note, these policies are typically mostly enacted in HICs, which may be related to the declining prevalence of smoking in these countries, compared with the prevalence in LMICs.

Pharmacotherapy

Three evidence-based classes of pharmacotherapy are available for smoking cessation: NRT (using nicotine-based patches, gum, lozenges, mini-lozenges, nasal sprays and inhalers), varenicline (a nAChR partial agonist), and bupropion (a noradrenaline/dopamine reuptake inhibitor that also inhibits nAChR function and is also used as an antidepressant). These FDA-approved and EMA-approved pharmacotherapies are cost-effective smoking cessation treatments that double or triple successful abstinence rates compared with no treatment or placebo controls 116 , 142 .

Combinations of pharmacotherapies are also effective for smoking cessation 116 , 142 . For example, combining NRTs (such as the steady-state nicotine patch and as-needed NRT such as gum or mini-lozenge) is more effective than a single form of NRT 116 , 142 , 143 . Combining NRT and varenicline is the most effective smoking cessation pharmacotherapy 116 , 142 , 143 . Combining FDA-approved pharmacotherapy with behavioural counselling further increases the likelihood of successful cessation 142 . Second-line pharmacotherapies (for example, nortriptyline) have some potential for smoking cessation, but their use is limited due to their tolerability profile.

All smokers should receive pharmacotherapy to help them quit smoking, except those in whom pharmacotherapy has insufficient evidence of effectiveness (among adolescents, smokeless tobacco users, pregnant women or light smokers) or those in whom pharmacotherapy is medically contraindicated 144 . Table  2 provides specific information regarding dosing and duration for each FDA-approved pharmacotherapy. Extended use of pharmacotherapy beyond the standard 12-week regimen after cessation is effective and should be considered 116 . Moreover, preloading pharmacotherapy (that is, initiating cessation medication in advance of a quit attempt), especially with the nicotine patch, is a promising treatment, although further studies are required to confirm efficacy.

Cytisine has been used for smoking cessation in Eastern Europe for a long time and is available in some countries (such as Canada) without prescription 145 . Cytisine is a partial agonist of nAChRs and its structure was the precursor for the development of varenicline 145 . Cytisine is at least as effective as some approved pharmacotherapies for smoking cessation, such as NRT 146 , 147 , 148 , and the role of cytisine in smoking cessation is likely to expand in the future, notably owing to its much lower cost than traditional pharmacotherapies. E-cigarettes also have the potential to be useful as smoking cessation devices 149 , 150 . The 2020 US Surgeon General’s Report concluded that there was insufficient evidence to promote cytisine or e-cigarettes as effective smoking cessation treatments, but in the UK its use is recommended for smoking cessation (see ref. 15 for regularly updated review).

Counselling and behavioural treatments

Psychosocial counselling significantly increases the likelihood of successful cessation, especially when combined with pharmacotherapy. Even a counselling session lasting only 3 minutes can help smokers quit 116 , although the 2008 US Public Health Service guidelines and the Preventive Services Task Force 151 each concluded that more intensive counselling (≥20 min per session) is more effective than less intensive counselling (<20 min per session). Higher smoking cessation rates are obtained by using behavioural change techniques that target associative and self-regulatory processes 152 . In addition, behavioural change techniques that will favour commitment, social reward and identity associated with changed behaviour seems associated with higher success rates 152 . Evidence-based counselling focuses on providing social support during treatment, building skills to cope with withdrawal and cessation, and problem-solving in challenging situations 116 , 153 . Effective counselling can be delivered by diverse providers (such as physicians, nurses, pharmacists, social workers, psychologists and certified tobacco treatment specialists) 116 .

Counselling can be delivered in a variety of modalities. In-person individual and group counselling are effective, as is telephone counselling (quit lines) 142 . Internet and text-based intervention seem to be effective in smoking cessation, especially when they are interactive and tailored to a smoker’s specific circumstances 142 . Over the past several years, the number of smoking cessation smartphone apps has increased, but there the evidence that the use of these apps significantly increases smoking cessation rates is not sufficient.

Contingency management (providing financial incentives for abstinence or engagement in treatment) has shown promising results 154 , 155 but its effects are not sustained once the contingencies are removed 155 , 156 . Other treatments such as hypnosis, acupuncture and laser treatment have not been shown to improve smoking cessation rates compared with placebo treatments 116 . Moreover, no solid evidence supports the use of conventional transcranial magnetic stimulation (TMS) for long-term smoking cessation 157 , 158 .

Although a variety of empirically supported smoking cessation interventions are available, more than two-thirds of adult smokers who made quit attempts in the USA during the past year did not use an evidence-based treatment and the rate is likely to be lower in many other countries 142 . This speaks to the need to increase awareness of, and access to, effective cessation aids among all smokers.

Brain stimulation

The insula (part of the frontal cortex) is a critical brain structure involved in cigarette craving and relapse 78 , 79 . The activity of the insula can be modulated using an innovative approach called deep insula/prefrontal cortex TMS (deep TMS), which is effective in helping people quit smoking 80 , 159 . This approach has now been approved by the FDA as an effective smoking cessation intervention 80 . However, although this intervention was developed and is effective for smoking cessation, the number of people with access to it is limited owing to the limited number of sites equipped and with trained personnel, and the cost of this intervention.

Quality of life

Generic instruments (such as the Short-Form (SF-36) Health Survey) can be used to evaluate quality of life (QOL) in smokers. People who smoke rate their QOL lower than people who do not smoke both before and after they become smokers 160 , 161 . QOL improves when smokers quit 162 . Mental health may also improve on quitting smoking 163 . Moreover, QOL is much poorer in smokers with tobacco-related diseases, such as chronic respiratory diseases and cancers, than in individuals without tobacco-related diseases 161 , 164 . The dimensions of QOL that show the largest decrements in people who smoke are those related to physical health, day-to-day activities and mental health such as depression 160 . Smoking also increases the risk of diabetes mellitus 165 , 166 , which is a major determinant of poor QOL for a wide range of conditions.

The high toll of premature death from cigarette smoking can obscure the fact that many of the diseases that cause these deaths also produce substantial disability in the years before death 1 . Indeed, death in smokers is typically preceded by several years of living with the serious disability and impairment of everyday activities caused by chronic respiratory disease, heart disease and cancer 2 . Smokers’ QOL in these years may also be adversely affected by the adverse effects of the medical treatments that they receive for these smoking-related diseases (such as major surgery and radiotherapy).

Expanding cessation worldwide

The major global challenge is to consider individual and population-based strategies that could increase the substantially low rates of adult cessation in most LMICs and indeed strategies to ensure that even in HICs, cessation continues to increase. In general, the most effective tools recommended by WHO to expand cessation are the same tools that can prevent smoking initiation, notably higher tobacco taxes, bans on advertising and promotion, prominent warning labels or plain packaging, bans on public smoking, and mass media and educational efforts 29 , 167 . The effective use of these policies, particularly taxation, lags behind in most LMICs compared with most HICs, with important exceptions such as Brazil 167 . Access to effective pharmacotherapies and counselling as well as support for co-existing mental health conditions would also be required to accelerate cessation in LMICs. This is particularly important as smokers living in LMICs often have no access to the full range of effective treatment options.

Regulating access to e-cigarettes

How e-cigarettes should be used is debated within the tobacco control field. In some countries (for example, the UK), the use of e-cigarettes as a cigarette smoking cessation aid and as a harm reduction strategy is supported, based on the idea that e-cigarette use will lead to much less exposure to toxic compounds than tobacco use, therefore reducing global harm. In other countries (for example, the USA), there is more concern with preventing the increased use of e-cigarettes by youths that may subsequently lead to smoking 25 , 26 . Regulating e-cigarettes in nuanced ways that enable smokers to access those products whilst preventing their uptake among youths is critical.

Regulating nicotine content in tobacco products

Reducing the nicotine content of cigarettes could potentially produce less addictive products that would allow a gradual reduction in the population prevalence of smoking. Some clinical studies have found no compensatory increase in smoking whilst providing access to low nicotine tobacco 168 . Future regulation may be implemented to gradually decrease the nicotine content of combustible tobacco and other nicotine products 169 , 170 , 171 .

Tobacco end games

Some individuals have proposed getting rid of commercial tobacco products this century or using the major economic disruption arising from the COVID-19 pandemic to accelerate the demise of the tobacco industry 172 , 173 . Some tobacco producers have even proposed this strategy as an internal goal, with the idea of switching to nicotine delivery systems that are less harmful ( Philip Morris International ). Some countries are moving towards such an objective; for example, in New Zealand, the goal that fewer than 5% of New Zealanders will be smokers in 2025 has been set (ref. 174 ). The tobacco end-game approach would overall be the best approach to reduce the burden of tobacco use on society, but it would require coordination of multiple countries and strong public and private consensus on the strategy to avoid a major expansion of the existing illicit market in tobacco products in some countries.

Innovative interventions

The COVID-19 pandemic has shown that large-scale investment in research can lead to rapid development of successful therapeutic interventions. By contrast, smoking cessation has been underfunded compared with the contribution that it makes to the global burden of disease. In addition, there is limited coordination between research teams and most studies are small-scale and often underpowered 79 . It is time to fund an ambitious, coordinated programme of research to test the most promising therapies based on an increased understanding of the neurobiological basis of smoking and nicotine addiction (Table  3 ). Many of those ideas have not yet been tested properly and this could be carried out by a coordinated programme of research at the international level.

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Acknowledgements

B.Le F. is supported by a clinician-scientist award from the Department of Family and Community Medicine at the University of Toronto and the Addiction Psychiatry Chair from the University of Toronto. The funding bodies had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication. The authors thank H. Fu (University of Toronto) for assistance with Figs 1–3.

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Introduction (B.Le F.); Epidemiology (P.J. and W.D.H.); Mechanisms/pathophysiology (C.D.F., L.B., L.L. and B.Le F.); Diagnosis, screening and prevention (P.J., M.E.P., S.T. and B.Le F.); Management (M.E.P., S.T., W.D.H., L.L. and B.Le F.); Quality of life (P.J. and W.D.H.); Outlook (all); Conclusions (all). All authors contributed substantially to the review and editing of the manuscript.

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B.Le F. has obtained funding from Pfizer (GRAND Awards, including salary support) for investigator-initiated projects. B.Le F. has received some in-kind donations of cannabis product from Aurora and medication donation from Pfizer and Bioprojet and was provided a coil for TMS study from Brainsway. B.Le F. has obtained industry funding from Canopy (through research grants handled by CAMH or the University of Toronto), Bioprojet, ACS, Indivior and Alkermes. B.Le F. has received in-kind donations of nabiximols from GW Pharma for past studies funded by CIHR and NIH. B.Le F. has been an advisor to Shinoghi. S.T. has received honoraria from Pfizer the manufacturer of varenicline for lectures and advice. All other authors declare no competing interests.

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Peer-reviewed

Research Article

The Health Effects of Passive Smoking: An Overview of Systematic Reviews Based on Observational Epidemiological Evidence

Affiliation School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

* E-mail: [email protected]

• Shiyi Cao, 
• Chen Yang, 
• Yong Gan, 

• Published: October 6, 2015
• https://doi.org/10.1371/journal.pone.0139907
• Reader Comments

We aim to systematically summarize the available epidemiological evidence to identify the impact of environmental tobacco smoke on health.

A systematic literature search of PubMed, Embase, Web of Science, and Scopus for meta-analyses was conducted through January 2015. We included systematic reviews that investigated the association between passive smoking and certain diseases. Quantitative outcomes of association between passive smoking and the risk of certain diseases were summarized.

Sixteen meta-analyses covering 130 cohort studies, 159 case-control studies, and 161 cross-sectional studies and involving 25 diseases or health problems were reviewed. Passive smoking appears not to be significantly associated with eight diseases or health problems, but significantly elevates the risk for eleven specific diseases or health problems, including invasive meningococcal disease in children (OR 2.18; 95% CI 1.63–2.92), cervical cancer (OR 1.73; 95% CI 1.35–2.21), Neisseria meningitidis carriage (OR 1.68; 95% CI 1.19–2.36), Streptococcus pneumoniae carriage (OR 1.66; 95% CI 1.33–2.07), lower respiratory infections in infancy (OR 1.42; 95% CI 1.33–1.51), food allergy (OR 1.43; 95% CI 1.12–1.83), and so on.

Conclusions

Our overview of systematic reviews of observational epidemiological evidence suggests that passive smoking is significantly associated with an increasing risk of many diseases or health problems, especially diseases in children and cancers.

Citation: Cao S, Yang C, Gan Y, Lu Z (2015) The Health Effects of Passive Smoking: An Overview of Systematic Reviews Based on Observational Epidemiological Evidence. PLoS ONE 10(10): e0139907. https://doi.org/10.1371/journal.pone.0139907

Editor: Yan Li, Shanghai Institute of Hypertension, CHINA

Received: April 23, 2015; Accepted: September 19, 2015; Published: October 6, 2015

Copyright: © 2015 Cao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

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

Funding: The authors have no support or funding to report.

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

Introduction

Smoking is a major public health problem worldwide. There have been thousands of studies investigating the impact of active smoking on health, and the overall toxic effects of active smoking are generally recognized [ 1 ]. In comparison, the effects of passive smoking on health are not fully understood. Existing studies suggest that passive smoking and active smoking might equally increase the risk of certain diseases, such as female breast cancer [ 2 ], allergic rhinitis, allergic dermatitis, and food allergy [ 3 ]. As early as 1928, Schonherr suspected that inhalation of husbands’ smoke could cause lung cancer among non-smoking wives [ 4 ]. Since then a substantial body of research about environmental tobacco smoke and health has appeared [ 5 ]. But the impact of passive smoking on health remains largely inconclusive and has not been systematically summarized.

Due to the relative small health risks associated with exposure to passive smoking, investigation of this issue requires large study sizes. Difficulties in measuring passive smoking and controlling various confounding factors further add to the uncertainty in any investigation of the effects of passive smoking. Consequently, a meta-analysis, pooling together individual original studies quantitatively, has played an important part in establishing the evidence about the health effects of passive smoking [ 5 ]. Since Zmirou evaluated the respiratory risk of passive smoking by a meta-analysis in the early 1990s, many meta-analyses of observational epidemiological studies have been published to identify the impact of passive smoking on health.

Recognizing that the evidence is accumulating constantly worldwide, we conducted an overview of systematic reviews that have summarized the evidence from observational epidemiological studies on the health effects of passive smoking.

No protocol exists for this overview of systematic reviews.

Data for this research was acquired from previously published papers. Written consent and ethical approval were not required.

Literature search strategy

We attempted to conduct this overview of systematic reviews in accordance with the rationale and guideline recommended by Cochrane handbook 5.1.0 [ 6 ] ( S1 Checklist ). A systematic literature search of PubMed, Embase, Web of Science, and Scopus was conducted in January 2015 using the following search terms with no restrictions: passive smoking, secondhand smoking, environmental tobacco smoke, involuntary smoking, and tobacco smoke pollution. The reference lists of the retrieved articles were also reviewed. We did not contact authors of the primary studies for additional information.

Selection of relevant systematic reviews

Systematic reviews meeting the following criteria were regarded as eligible: (1) the design was meta-analysis, (2) passive smoking was an exposure variable and the outcome was the incidence of certain diseases or health problems, (3) the included original studies were cross-sectional, case-control, or/and cohort study design, (4) the literature search was international or worldwide, and (5) the pooled relative risk (RR) or odds ratio (OR) and the corresponding 95% confidence interval (CI) of specific diseases relating to exposure to passive smoking were reported or could be calculated from the data provided. Systematic reviews in which all included original studies were conducted in one country or region were excluded. We also excluded the meta-analyses that investigated the association between maternal smoking in pregnancy and the health risk of offspring. All potential meta-analyses were independently screened by two authors (SC and CY), who reviewed the titles or/abstracts first and then conducted a full-text assessment. Disagreements between the two reviewers were resolved through discussion with the third investigator (ZL).

Data extraction

The following information was extracted from the studies by two investigators (SC and CY): first author, publication year, country, number and design of the included original studies, and main quantitative estimates of the association of interest.

Quality appraisal

We appraised all the included meta-analyses using the Assessment of Multiple Systematic Reviews (AMSTAR) standard, an 11-item assessment tool designed to appraise the methodological quality of systematic reviews [ 7 ]. The maximum score is 11, and 0–4, 5–8, and 9–11 respectively indicates low, moderate, and high quality [ 8 ]. Disagreements on assessment scores were resolved by discussion among the authors.

Synthesis of the evidence

There may be more than one meta-analysis published regarding the association between passive smoking and risk of a specific disease. We only included the latest meta-analysis and excluded all the previous ones. For each included meta-analysis, we summarized the number and design of the included original studies, the main quantitative estimates of association of interest, heterogeneity between original studies, and so on. In any included meta-analyses, when estimates of association between passive smoking and certain diseases were reported separately for subgroups, we combined the results of the subgroups and calculated common estimates using a fixed-effects model if appropriate.

Literature search

Fig 1 shows the process of study identification and inclusion. Initially, we retrieved 2,079 articles from Pubmed, Emabse, Web of Science, and Scopus. After 1,105 duplicates were excluded, 974 articles were screened through titles and abstracts, of which 858 were excluded mainly because they were original studies or irrelevant reviews. After full-text review of the remaining 116 articles, 100 were further excluded because they did not report the outcomes of interest or their findings were already updated by newer systematic reviews. Finally, 16 meta-analyses were included [ 3 , 9 – 23 ].

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https://doi.org/10.1371/journal.pone.0139907.g001

Characteristics and quality of the included systematic reviews

The main characteristics of the sixteen meta-analyses were summarized in Table 1 . These meta-analyses covered a total of 130 cohort studies, 159 case-control studies, and 161 cross-sectional studies. They were published between 1998 and 2014. The quality scores of these meta-analyses appraised using AMSTAR ranged from 3 to 10. The numbers of meta-analyses with high quality, middle quality, and low quality were 5, 9, and 2 respectively (see Table 2 ).

https://doi.org/10.1371/journal.pone.0139907.t001

https://doi.org/10.1371/journal.pone.0139907.t002

The Main Health Consequences of Passive Smoking

Fig 2 shows the integrated results on the impact of passive smoking on specific diseases. The included 16 meta-analyses covered 25 diseases or health problems. There was statistically significant positive relationship between exposure environmental tobacco smoke and the risk of eleven diseases, especially invasive meningococcal disease in children (OR 2.18; 95% CI 1.63–2.92) and other three diseases or health problems with a 1.5 to 2.0-fold increase in the risk: cervical cancer (OR 1.73; 95% CI 1.35–2.21), Neisseria meningitidis carriage (OR 1.68; 95% CI 1.19–2.36), and Streptococcus pneumoniae carriage (OR 1.66; 95% CI 1.33–2.07). The increase in the risk of other seven diseases associated with exposure to passive smoking was statistically significant but small in impact size (OR was less than 1.5): lower respiratory infections in infancy (OR 1.42; 95% CI 1.33–1.51), food allergy (OR 1.43; 95% CI 1.12–1.83), childhood asthma (OR 1.32; 95% CI 1.23–1.42), lung cancer (OR 1.27; 95% CI 1.17–1.37), stroke (OR 1.25; 95% CI 1.12–1.38), allergic rhinitis (OR 1.09; 95% CI 1.04–1.14), and allergic dermatitis (OR 1.07; 95% CI 1.03–1.12). Of these 25 diseases or health problems, eight diseases were not found to be significantly associated with passive smoking. They were invasive Haemophilus influenzae type B (Hib) disease, invasive pneumococcal disease, Crohn's disease, pancreatic cancer, ulcerative colitis, breast cancer, bladder cancer, and pharyngeal carriage for Hib. In addition, the effects of passive smoking on increased risk of coronary heart disease, tuberculosis, diabetes, and middle ear disease in children (recurrent otitis media, middle ear effusion, and glue ear) were not conclusive, because the number of included studies was small or the quality of the corresponding meta-analysis was low.

https://doi.org/10.1371/journal.pone.0139907.g002

Passive smoking and cancer risk

We investigated the association of passive smoking with the risk of lung cancer, cervical cancer, pancreatic cancer, breast cancer, and bladder cancer. Based on 55 observational studies (7 cohort studies, 25 population-based case-control studies and 23 non-population-based case-control studies), passive smoking were found to be associated with the increased risk of lung cancer (OR 1.27; 95% CI 1.17 to 1.37). The ORs for lung cancer in North America, Asia, and Europe were similar [ 19 ]. 11 case-control studies, involving 3,230 cases and 2,982 controls, suggested a positive relationship between passive smoking and cervical cancer (OR 1.73; 95% CI 1.35–2.21) [ 15 ]. Pancreatic cancer [ 21 ], breast cancer [ 13 ], and bladder cancer were not found to be associated with passive smoking.

Passive smoking and allergic diseases

A meta-analysis of observational studies published in PLOS Medicine systematically reviewed the effects of exposure to environmental smoke on allergic diseases [ 3 ]. The pooled ORs of 63 studies for allergic rhinitis, 58 studies for allergic dermatitis, and 6 studies for food allergies were 1.07 (95% CI 1.03–1.12), 1.09 (95% CI 1.04–1.14), and 1.43 (95% CI 1.12–1.83) respectively. Another meta-analysis investigated the association between passive smoking and the risk of physician-diagnosed childhood asthma [ 9 ], and suggested that there was consistent evidence of a modest positive association between them (OR 1.32; 95% CI: 1.23–1.42).

Passive smoking and pediatric invasive bacterial disease and bacterial carriage

Passive smoking was also thought to be associated with pediatric invasive bacterial disease and bacterial carriage. A meta-analysis involving 30 case-control studies for invasive bacterial disease and 12 cross-sectional studies for bacterial carriage indicated that the risk of invasive meningococcal disease, pharyngeal carriage for Neisseria, meningitidies and Streptococcus pneumoniae were significantly associated with passive smoking, and the ORs were 2.18, 95% CI 1.63 to 2.92), 1.68 (95% CI, 1.19–2.36), and 1.66 (95% CI 1.33–2.07), respectively. The risk of invasive pneumococcal disease, invasive Hib disease, and pharyngeal carriage for Hib were not found to be related to exposure to environmental smoke.

The health effects of environmental tobacco smoke are attracting more and more attention worldwide. Increasing numbers of original studies and meta-analyses are being published focusing on this important issue. In the present overview of systematic reviews based on sixteen systematic reviews involving 450 original observational studies, we found that passive smoking could significantly increase the risk of eleven diseases, especially invasive meningococcal disease in children, cervical cancer, Neisseria meningitidis carriage, and Streptococcus. pneumoniae carriage, but not associated with other eight diseases. Cancers were one of the most common investigated health outcomes associated with passive smoking. We found that exposure to environmental tobacco smoke could increase the risk of lung cancer and cervical cancer, but was not the risk of pancreatic cancer, breast cancer, or bladder cancer. It appears that passive smoking could increase the risk of some diseases among children, especially bacterial infections (e.g., lower respiratory infections in infancy, middle ear disease in children, invasive meningococcal disease in children, allergic diseases in children, and childhood asthma).

Previously, there were some reviews focusing on the health effects of exposure to environmental tobacco smoke. But they were qualitative or only involved children or limited to several diseases [ 24 – 26 ]. We used a systematic overview to summarize the quantitative estimates of the associations between passive smoking and various diseases based on all latest available meta-analyses. It should be noted that, in the present overview, we excluded meta-analyses evaluating the effects of smoking during pregnancy on fetus or offspring health, because the effects was obviously different from the health effects of active smoking or conventional passive smoking in the general population.

The quality of included original studies influences the reliability of the results and conclusions of the corresponding meta-analysis; similarly, the validity of the results of an overview of systematic reviews depends on the quality of the included systematic reviews. We used AMSTAR protocol, an internationally recognized assessment tool, to appraise the methodological quality of all included meta-analyses, and found that there were two meta-analyses with low quality. Accordingly, the conclusions drawn based on these two meta-analyses involving middle ear disease in children and coronary heart disease need to be interpreted with caution.

The evidence level of meta-analyses partly depends on the number and the design type of included original studies. Although there was no consensus about the minimum number of original studies included in meta-analysis, but more caution is needed when an association is assessed based on a small number of original studies. In our overview, we found a significant positive association between passive smoking and tuberculosis (OR 4.01; 95% CI 2.54–6.34), but it was only based on 4 case-control studies. More studies should be conducted to further assess the relationship between them. Similarly, the effect of passive smoking on diabetes was based on 6 cohort studies (OR 1.21; 95% CI 1.07–1.38), and more original studies are also needed.

There were several strengths in our research. Firstly, we followed the primary rationale and method of Cochrane overviews of reviews [ 6 ] to summarize the health consequences of certain exposure. Overview of systematic reviews is primarily intended to summarize multiple reviews addressing the effects of two or more potential interventions for a single condition or health problem. Up to now, most of overviews have been conducted to evaluate the effects of several interventions [ 27 , 28 ], and very few overviews have addressed the effects of a single exposure factor on multiple diseases or health problems based on observational studies. Our present overview expands the application of overviews of systematic reviews. Additionally, our study provides robust and comprehensive scientific information for smoking ban in public places and for educational pamphlets about passive smoking.

Some limitations in our overview should be noted. Firstly, we only included systematic reviews but not original studies. The associations of passive smoking with some diseases might have been investigated by original studies but not synthesized by meta-analyses and, therefore, were not summarized in this overview. Secondly, the mechanism on the health effects of passive smoking was not be examined since our study only intended to summarize relevant observational epidemiological evidence.

In summary, our overview of systematic reviews of up-to-date epidemiological evidence suggests that passive smoking is significantly associated with an increasing risk of many diseases and health problems, especially diseases in children and cancers. This study provides comprehensive population-based evidence about toxic effect of exposure to environmental tobacco smoke and should benefit developing health promotion strategies of smoking control. Stricter regulations against cigarette smoking should be formulated and implemented, because smoking harms not only own health but also the health of neighboring people.

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All the data in this review are from publicly published papers, and we take responsibility for the integrity of the data and the accuracy of the data analysis.

Author Contributions

Conceived and designed the experiments: ZL. Performed the experiments: SC CY. Analyzed the data: SC YG. Contributed reagents/materials/analysis tools: CY. Wrote the paper: SC.

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The Impact of Active and Passive Smoking Upon Health and Neurocognitive Function.

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Tobacco, Nicotine, and E-Cigarettes Research Report Introduction

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

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

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Trends in smoking frequency and smoking intensity, trends in age of first cigarette use, trends in e-cigarette use frequency, conclusions, trends in smoking behaviors among us adolescent cigarette smokers.

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Sunday Azagba , Lauren Manzione , Lingpeng Shan , Jessica King; Trends in Smoking Behaviors Among US Adolescent Cigarette Smokers. Pediatrics March 2020; 145 (3): e20193047. 10.1542/peds.2019-3047

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Identifying trends in smoking behaviors among youth cigarette smokers could inform youth policy and interventions.

Using 2011–2018 National Youth Tobacco Survey data, logistic/linear regressions were used to analyze trends in smoking frequency, intensity, age of first cigarette use, and electronic cigarette (e-cigarette) use frequency among current smokers. Stratified analyses were conducted among male, female, middle school, and high school students and race and ethnicity subgroups separately.

From 2011 to 2018, there was a decrease in smoking ≥10 days (50.0% to 38.3%), ≥20 days (37.2% to 26.3%), and 30 days (26.6% to 18.2%) among current smokers. Smoking prevalence decreased among male, female, high school, non-Hispanic white, and non-Hispanic other students. Overall, light smoking (≤5 cigarettes per day [CPDs]) increased (76.6% to 82.7%), and moderate smoking (6–10 CPDs) decreased (10.7% to 8.3%). Trends in light, moderate, and heavy smoking varied by demographic groups. Age at first cigarette use increased among female (12.28 to 13.29), high school (12.91 to 13.18), and non-Hispanic other students (11.64 to 12.83) and decreased among male students (12.90 to 12.57). From 2014 to 2018, there was an increase in e-cigarette use frequency for ≥10 days (20.8% to 40.9%), ≥20 days (13.5% to 31.7%), and all 30 days (9.3% to 22%).

From 2011 to 2018, current youth cigarette smokers smoked fewer days and fewer CPDs, and age of first cigarette use increased. However, over time, male youth smoked more heavily and started smoking earlier. E-cigarette use increased from 2014 to 2018. Differences by demographic characteristics can inform future research and interventions.

Cigarette use has declined among youth, but it is unclear whether smoking behaviors such as smoking frequency, smoking intensity, and age of first use have changed among continuing smokers.

Between 2011 and 2018, current cigarette-smoking youth smoked fewer days per month and fewer cigarettes per day, and the age of first cigarette use increased. However, over time, male youth smoked more heavily and started smoking earlier.

Despite years of progress, tobacco use is still the leading cause of preventable death in the United States. 1   Since the first Surgeon General Report in 1964, which concluded cigarette smoking substantially contributes to morbidity and mortality, the prevalence of adult cigarette smokers has declined from 42% to 14% in 2017. 1 , 2   However, 34.3 million adults still smoke, and >480 000 Americans die each year because of smoking-related disease. 1 , 2   Smoking is responsible for >87% of lung cancer deaths, 61% of all pulmonary disease deaths, and 32% of all deaths from coronary heart disease. 2   It has also been linked to health conditions in all major organs, including stroke, diabetes, tuberculosis, cancers, and many other chronic diseases. 2   In 2018, 1.18 million high school students and 200 000 middle school students reported smoking cigarettes in the past 30 days. 3   Consequently, 5.6 million US youth are projected to die prematurely from smoking-related causes. 2  

Reducing smoking among youth was one of the goals of the 2009 Family Smoking Prevention and Tobacco Control Act (FSPTCA). 4   The act granted the US Food and Drug Administration (FDA) the authority to regulate the content, marketing, and sale of tobacco products. 4   The use of this authority was specifically focused on restricting tobacco marketing and sales to youth. 4   From 2011 to 2018, the prevalence of cigarette smoking among all US middle school and high school students declined significantly from 15.8% to 8.1%. However, little is known about the trend of smoking behaviors among US youth cigarette smokers during that time.

Many studies on youth smoking have examined smoking prevalence, comparing results between smokers and nonsmokers. 3 , 5 – 7   However, few studies have analyzed behaviors, such as frequency and intensity, specifically among youth cigarette smokers. 8 – 12   These studies tend to include users and nonusers and focus on multiple products, which may mask important findings among cigarette smokers. Despite increases in other product use, such as electronic cigarettes (e-cigarettes), cigarettes remain the most harmful tobacco product, and efforts should be made to continue targeting youth who smoke cigarettes. However, e-cigarettes are also of major concern because they are now the most commonly used tobacco product among US youth. In 2018, 21% of youth reported past 30-day e-cigarette use compared with 8.1% of youth who reported cigarette use. 13  

Vapor products are not without risk and have been linked to >2000 cases of lung injury (e-cigarette or vaping product use–associated lung injury), including 47 deaths. 14   In addition, most youth e-cigarette users report polytobacco use. 15 – 17   Those who use combustible cigarettes and e-cigarettes concurrently could be at risk for increased substance abuse and other risky behavior. 11 , 18 – 20  

Analyzing youth smoking behavior over time provides additional insights to inform policy and prevention efforts. Jones et al 10   found that smoking intensity decreased among current cigarette-smoking youth, with heavy smokers decreasing from 18.0% to 7.8% and light smokers increasing from 67.2% in 1991 to 79.4% in 2009. If youth are transitioning from heavy to light smoking, efforts might be focused on educating youth that light smoking remains harmful. In addition, there is further understanding to be gained from examining trends in youth smoking by demographic characteristics given the disparities in smoking among subpopulations. 7 , 21   Identifying differences in smoking behaviors between demographic groups (eg, male or female sex) could help target populations who are at greatest risk. However, to our knowledge, no studies have examined national trends in youth smoking behaviors since the implementation of the FSPTCA in 2009. The current study used the National Youth Tobacco Survey (NYTS) to examine the trends of smoking behaviors among middle and high school students in the United States from 2011 to 2018.

The NYTS was designed to provide comprehensive national data on tobacco-related indicators for middle school (grades 6–8) and high school (grades 9–12) students to support the design, implementation, and evaluation of comprehensive tobacco prevention and control programs. 22   The NYTS uses a stratified 3-stage cluster sample design and a weighting factor for each student, which results in nationally representative data for public, Catholic, and other private school students enrolled in grades 6 through 12 in the United States. For each year, students in randomly selected US states and the District of Columbia were invited to participate; participation was confidential, voluntary, and approved by parents. During a regular class period, participants completed self-administered, paper-and-pencil, scannable questionnaires that included questions regarding tobacco-related beliefs, attitudes, behaviors, and exposure to pro- and antitobacco influences. For each year, the overall response rates ranged from 63% to 89%, and the number of participants ranged from 17 711 to 24 658. In our study, we restricted our analysis to students who were current smokers and were not missing grade information. Current smokers were defined as students who smoked cigarettes at least once in the 30 days before the survey on the basis of the response to the survey question, “During the past 30 days, on how many days did you smoke cigarettes?” On the basis of the study criteria, 11 123 middle and high school students were included in the analyses.

The main outcome variables of interest were 3 smoking behaviors: smoking frequency (in days), cigarettes smoked per day, and the age of first cigarette use. Smoking frequency items were derived from the question, “During the past 30 days, on how many days did you smoke cigarettes?” Possible answers included “0 days,” “1 or 2 days,” “3 to 5 days,” “6 to 9 days,” “10 to 19 days,” “20 to 29 days,” and “all 30 days.” Consistent with a study conducted by Jones et al, 10   3 dichotomous variables were created to measure trends for smoking frequency: smoked cigarettes ≥10 days, smoked cigarettes ≥20 days, and smoked cigarettes every day (all 30 days).

Cigarettes smoked per day (smoking intensity) was derived from the question “During the past 30 days, on the days you smoked, about how many cigarettes did you smoke per day?” We categorized current smokers by cigarettes smoked per day into 3 categories: light smokers (≤1–5 cigarettes per day [CPDs]), moderate smokers (6–10 CPDs), and heavy smokers (≥11 CPDs).

Age at first cigarette use was measured by using the survey question, “How old were you when you first tried cigarette smoking, even 1 or 2 puffs?” and was analyzed as a continuous variable.

E-cigarette use frequency was derived from the question “During the past 30 days, on how many days did you use e-cigarettes?” for all available years (2014–2018). Three dichotomous variables that were similar to measures of smoking frequency were created to measure trends for e-cigarette frequency: use e-cigarettes ≥10 days, use e-cigarettes ≥20 days, and use e-cigarettes every day (all 30 days). Demographic variables included in the analyses were sex (male or female), race and ethnicity (non-Hispanic white, non-Hispanic African American, Hispanic, or non-Hispanic others), and grade (6th–12th grade). Because of small sample sizes, non-Hispanic Asian American, non-Hispanic American Indian or Alaskan native, non-Hispanic Native Hawaiian or Pacific Islander, and multiple races were recoded into the “non-Hispanic others” group.

We generated national estimates of smoking behaviors (smoking frequency, smoking intensity, age of first cigarette use, and e-cigarette use frequency) among current smokers in middle school and high school students for each year of data independently. Additionally, estimates were calculated for the full sample and in male, female, middle school, and high school subgroups separately. Logistic regression models were used to test the statistical significance of the linear trend for measurements of smoking frequency, smoking intensity, and e-cigarette use frequency. Linear regression models were used to test the statistical significance of the linear trend of the mean age of first cigarette use. The age variable was treated as a continuous variable. Sex, race and ethnicity, and grade were included as covariates. Subgroup trend analyses were conducted among male, female, middle school, and high school students and race and ethnicity separately by using the same covariates except for the stratified criteria. Sampling weights and survey stratum were included in all analyses to account for the complex survey design. All tests were 2 sided and used a 5% significance level. All of the statistical analyses were performed by using SAS 9.4 (SAS Institute, Inc, Cary, NC).

Of the 11 123 students included in our study, 8966 (83.4%) were high school students, and 51.3% were male. More than half of participating students were non-Hispanic white (59.8%), followed by Hispanic (22.8%), non-Hispanic others (9.1%), and non-Hispanic African American (8.3%). Among the included current smokers, 35.2% smoked 1 to 2 days during the 30 days before the survey, 23.5% smoked 3 to 9 days, 11.8% smoked 10 to 19 days, 8.8% smoked 20 to 29 days, and 20.8% smoked all 30 days. In terms of smoking intensity, 80.7% were light smokers (≤5 CPDs), 9.3% were moderate smokers (6–10), and 9.9% were heavy smokers (≥11 CPDs). For e-cigarette use among current smokers, 40.3% did not use e-cigarettes during the past 30 days before the survey, 15.7% used 1 to 2 days, 16.9% used 3 to 9 days, 7.4% used 10 to 19 days, 5.2% used 20 to 29 days, and 12.5% used all 30 days ( Supplemental Table 2 ).

The trends in smoking frequency and smoking intensity for current cigarette users from 2011 to 2018 are presented in Fig 1 . A significant decrease was found in all 3 measures of smoking frequency. The percentage of current smokers smoking ≥10 days, ≥20 days, and all 30 days decreased 11.7 percentage points (from 50.0% to 38.3%), 10.9 percentage points (from 37.2% to 26.3%), and 8.4 percentage points (from 26.6% to 18.2%), respectively, over the 8-year period. Light smoking among current cigarette users increased significantly from 76.6% in 2011 to 82.7% in 2018. Moderate smoking decreased significantly from 10.7% in 2011 to 8.3% in 2018. Heavy smoking decreased from 9.7% in 2011 to 9.0% in 2018, although the trend was not statistically significant for heavy smoking.

Smoking frequency and smoking intensity among current cigarette smokers from 2011 to 2018. A, Smoking frequency. B, Smoking intensity. Smoking frequency was measured by the number of days smoked in the past 30 days: smoked cigarettes ≥10 days, smoked cigarettes ≥20 days, and smoked cigarettes every day (all 30 days). Smoking intensity was measured by the number of cigarettes smoked per day: light smokers (≤1–5 CPDs), moderate smokers (6–10 CPDs), and heavy smokers (≥11 CPDs).

The trends in smoking frequency and smoking intensity for current cigarette users and by demographic characteristics from 2011 to 2018 are presented in Figs 2 and 3 and Supplemental Fig 6 . The percentage of current smokers smoking ≥10 days, ≥20 days, and all 30 days decreased among male, female ( Fig 2 ), high school ( Fig 3 ), non-Hispanic white, and non-Hispanic other students. Similar to all current cigarette users, light smoking increased significantly among female (from 75.9% to 88.4%; Fig 2 ), high school (from 78.1% to 82.1%; Fig 3 ), non-Hispanic white (from 78.9% to 84.1%; Supplemental Fig 6 ), and non-Hispanic other students (from 77.9% to 88.4%; Supplemental Fig 6 ), whereas moderate smoking decreased significantly among female (from 11.0% to 7.4%; Fig 2 ), high school (from 12.0% to 9.2%; Fig 3 ), and non-Hispanic white students (from 12.5% to 9.4%; Supplemental Fig 6 ). In addition, heavy smoking decreased significantly among female students (from 13.1% to 4.2%) but increased significantly among male students (from 5.5% to 12.8%) from 2011 to 2018 ( Fig 2 ). No other significant trends were observed for smoking frequency or smoking intensity.

Smoking frequency and smoking intensity among current cigarette smokers from 2011 to 2018, stratified by sex. A, Smoking intensity. B, Smoking frequency. Current cigarette smokers were defined as students who smoked cigarettes on ≥1 of the 30 days before the survey. Smoking frequency was measured by the number of days smoked in the past 30 days: smoked cigarettes ≥10 days, smoked cigarettes ≥20 days, and smoked cigarettes every day (all 30 days). Smoking intensity was measured by the number of cigarettes smoked per day: light smokers (≤1–5 CPDs), moderate smokers (6–10 CPDs), and heavy smokers (≥11 CPDs). Prevalence and the 95% confidence interval (error bar) were presented for each year.

Smoking frequency and smoking intensity among current cigarette smokers from 2011 to 2018, stratified by age (middle school or high school). A, Smoking frequency. B, Smoking intensity. Current cigarette smokers were defined as students who smoked cigarettes on ≥1 of the 30 days before the survey. Smoking frequency was measured by the number of days smoked in the past 30 days: smoked cigarettes ≥10 days, smoked cigarettes ≥20 days, and smoked cigarettes every day (all 30 days). Smoking intensity was measured by the number of cigarettes smoked per day: light smokers (≤1–5 CPDs), moderate smokers (6–10 CPDs), and heavy smokers (≥11 CPDs). Prevalence and the 95% confidence interval (error bar) were presented for each year.

E-cigarette use frequency among current cigarette smokers from 2014 to 2018, stratified by demographic characteristics. Current cigarette smokers were defined as students who smoked cigarettes on ≥1 of the 30 days before the survey. E-cigarette use frequency was measured by the number of days e-cigarette was used in the past 30 days: used e-cigarettes ≥10 days, used e-cigarettes ≥20 days, and used e-cigarettes every day (all 30 days). The smoking frequency was measured by the number of days smoked in the past 30 days: smoked cigarettes ≥10 days, smoked cigarettes ≥20 days, and smoked cigarettes everyday (all 30 days). Prevalence and the 95% confidence interval (error bar) were presented for each year.

The trends in the age of first cigarette use overall and by demographic characteristics from 2011 to 2018 are presented in Table 1 and Supplemental Table 3 . Over the 8 years, the mean age of first use of cigarettes increased significantly from 12.56 years in 2011 to 12.86 years in 2018. Similarly, in the demographic subgroups, we found a significant increasing trend among female students from 12.28 to 13.29 years and among high school students from 12.91 to 13.18 years during 2011–2018; however, the mean age of first use decreased significantly among male students during the same period from 12.90 to 12.57 years. In addition, the mean age of first use increased significantly from 11.64 to 12.83 years among non-Hispanic other students ( Supplemental Table 3 ). No significant trend in the mean age of first use was found among other demographic subgroups.

Age of First Cigarette Use Among Current Cigarette Smokers From 2011 to 2018, Overall and by Subgroups

Data are presented as mean (95% confidence interval).

Significant increase in the mean age of first cigarette use was found from 2011 to 2018 ( P < .05).

Significant decrease in the mean age of first cigarette use was found from 2011 to 2018 ( P < .05).

The trends in e-cigarette use frequency among current cigarette smokers from 2014 to 2018, stratified by demographic characteristics, are presented in Figs 4 and 5 . The percentage of current smokers using e-cigarettes ≥10 days, ≥20 days, and all 30 days increased 20.1 percentage points (from 20.8% to 40.9%), 18.2 percentage points (from 13.5% to 31.7%), and 12.7 percentage points (from 9.3% to 22.0%), respectively, over the 4-year period ( Fig 4 ). A similar increase was found among male, female, middle school, and high school students as well as race and ethnicity subgroups. However, the trends were not significant for the percentage of current female smokers using e-cigarettes ≥10 days (from 18.6% to 30.1%; Fig 4 ) and percentage of current Hispanic smokers using e-cigarettes ≥20 days (from 18.7% to 26.5%; Fig 5 ) or using e-cigarettes every day (from 15.1% to 20.1%; Fig 5 ).

E-cigarette use frequency among current cigarette smokers from 2014 to 2018, stratified by race and ethnicity. Current cigarette smokers were defined as students who smoked cigarettes on ≥1 of the 30 days before the survey. E-cigarette use frequency was measured by the number of days e-cigarette was used in the past 30 days: used e-cigarettes ≥10 days, used e-cigarettes ≥20 days, and used e-cigarettes every day (all 30 days). NH, non-Hispanic.

We examined 2011–2018 NYTS data to determine trends in smoking frequency, smoking intensity, and age of first cigarette use among current cigarette smokers. Over the period, current youth smokers smoked fewer days and fewer CPDs, and the age of first cigarette use increased. However, in subgroup analyses by grade and sex, we identified important differences.

The percentage of current smokers smoking ≥10 days, ≥20 days, and all 30 days decreased significantly over the 8 years. We found that the percentage of current smokers smoking at least 10, 20, and all 30 days decreased among male, female, high school, non-Hispanic white, and non-Hispanic other subgroups. These trends highlight decreasing cigarette use frequency among current cigarette smokers. In contrast, Bold et al 23   found an increase in frequency of cigarette use from 2013 to 2015 among high school students. However, Bold et al’s 23   study was among Connecticut students, which is not a nationally representative sample, and their analyses did not appear to control for age or grade.

We found that from 2011 to 2018, most youth smokers smoked less intensely. Notably, light smoking (≤5 CPDs) among current cigarette users increased significantly. Similarly, Jones et al 10   found that light smokers increased from 67.2% in 1991 to 79.4% in 2009. We also found that light smoking increased significantly among female, high school, non-Hispanic white, and non-Hispanic other subgroups. In the current study, moderate smoking decreased significantly overall and among female and high school students. The number of previous comparable studies is limited, but authors of a national study of US adults found that from 2005 to 2014, the mean number of cigarettes smoked for adult daily smokers decreased from 16.7 to 13.8. 21   Our results also indicate that heavy smoking decreased significantly among female students but increased significantly among male students from 2011 to 2018, thus highlighting the importance of stratifying by sex.

In the current study, the frequency of e-cigarette use among current smokers increased significantly over the period. This trend was also significant in almost every demographic subgroup. These results are in line with evidence that current youth e-cigarette use increased 78% from 2017 to 2018. 24   This finding suggests that some youth might be reducing cigarette use in favor of e-cigarettes while still continuing to smoke. Although there is some evidence that e-cigarettes contain fewer toxicants than combustible cigarettes, they still contain nicotine, ultrafine particles, chemicals, organic compounds, and heavy metals that can lead to serious health consequences, such as e-cigarette or vaping product use–associated lung injury and cancer. 14 , 25   Evidence also shows that dual use of cigarettes and e-cigarettes is positively associated with illicit substance use, alcohol use, truancy, and poor academic performance and is negatively related to quit intention. 11 , 18 – 20   The increase we observed in e-cigarette use among cigarette smokers is concerning and warrants further investigation.

Over the 8 years analyzed, the mean age of first cigarette use increased significantly. In the demographic subgroup analyses, we found a significant increasing trend among female, high school, and non-Hispanic other students. However, the mean age of first use decreased significantly among male students during the same period. It appears male youth smokers are starting earlier and smoking more intensely.

The contrast found in trends among young men and women could stem from differences in social behavior and roles. 26   Authors of 1 study of high school students concluded that the number of cigarettes smoked in a day is a good measure for current smoking among young women but not young men. 26   In a 2006 study of high school students, smoking was positively associated with buzz, pleasure, taste and/or smell, and stimulation and was negatively associated with exercise and/or sport impairment among boys. Among girls, weight control was positively associated with smoking, whereas negative aesthetics, addiction, and negative mood were negatively associated with smoking. 27   The differences in smoking behaviors by sex are notable because they could impact responses to tobacco control efforts targeted to youth. 27  

In our analyses of NYTS data post-FDA’s regulation of cigarettes, there were important improvements in youth cigarette-smoking frequency, intensity, and age of first use. As part of the FSPTCA, the FDA targets youth and young adults through educational campaigns such as The Real Cost. Some estimates suggest these efforts have reduced youth cigarette use, 28   which is in line with our trend analyses. However, our subgroup analyses highlight that male youth smokers remain a priority population. Additionally, increases in light smoking and e-cigarette use may suggest youth are smoking less but not necessarily quitting. Thus, efforts to educate youth about the harms of any tobacco use might be warranted.

There are several limitations to this study. Because analyses relied on survey responses, the results may be subject to recall bias. In addition, the survey was administered in a school setting, which resulted in the exclusion of youth who are not enrolled or were not in attendance. Survey participation was also optional and required parent permission, which may have introduced nonresponse bias. Despite limitations, this study is unique in its analysis of US youth smoking trends, stratified by sex and age group.

In this study, we used the NYTS to examine the trends of smoking behaviors among middle and high school students in the United States from 2011 to 2018. The percentage of current smokers smoking at least 10, 20, and all 30 days decreased significantly overall and among male, female, and high school subgroups. Past-month e-cigarette use frequency rose significantly, surpassing cigarette use in 2018, highlighting the need for improved e-cigarette prevention and cessation strategies. Light smoking among current cigarette users increased significantly overall and among female and high school subgroups. Moderate smoking decreased significantly overall and among female and high school students. Heavy smoking decreased significantly among female students but increased significantly among male students. The mean age of first use of cigarettes increased significantly overall and among female and high school students but decreased significantly among male students. Differences in results between young men and women are of particular note and can help inform future research and interventions.

Dr Azagba conceptualized and designed the study and supervised all aspects of the study; Mr Shan conducted the data analysis; and all authors contributed to the drafting of the manuscript, critically reviewed the manuscript, and approved the final manuscript as submitted.

FUNDING: No external funding.

cigarette per day

electronic cigarette

Food and Drug Administration

Family Smoking Prevention and Tobacco Control Act

National Youth Tobacco Survey

Competing Interests

Supplementary data, re: trends in smoking behaviors among us adolescent cigarette smokers: letter to the editor.

Article Trends in Smoking Behaviors Among US Adolescent Cigarette Smokers Sunday Azagba, Lauren Manzione, Lingpeng Shan and Jessica King Pediatrics March 2020, 145 (3) e20193047; DOI: https://doi.org/10.1542/peds.2019-3047 Trends in Smoking Behaviors Among US Adolescent Cigarette Smokers: Letter to the Editor Tyler Blair, Student, Utica College • Other Contributors: • Mary Siniscarco, MS, OTR/L, Associate Professor of Health Studies

Dear Editor, We read with great interest the article “Trends in smoking behaviors among US adolescent cigarette smokers” by Azagba et al.1 The authors reported a decline in smoking from 2011 to 2018 in frequency, amplitude, and initial exposure for most age ranges in the youth population (middle school to high school).1 Although most incidences of smoking have decreased, the prevalence of e-cigarettes continues to rise.1,2 “The percent of high school seniors who had used an e-cigarette in the past 30 days increased from 1.5 percent in 2010 to 26.7 percent in 2018.”2 One of the main health concerns related to vaping in youth populations is bronchiolitis obliterans, or, “popcorn lung.”3 Consequently, popcorn lung can cause major damage to the lungs, leading to hospitalizations and in extreme cases, death.3 In order to prevent potential long-term health effects of such prolific lung damage to developing children 4, an aggressive public health campaign regarding an e-cigarette vaping cessation program is indicated, immediately. As health care professionals, we need to begin such an initiative at an elementary school level while utilizing an interdisciplinary approach. In particular, D.A.R.E. (Drug Abuse Resistance Education) has introduced education plans for middle and high school levels to address the present vaping crisis however, such has not been implemented at a national level for all elementary schools.5 An elementary “friendly” prevention approach needs to be instituted at a national level. At present, the state of Minnesota has already implemented a statewide initiative focused on the e-cig and vaping issue at hand with educational resources for students, teachers, parents, and administrators.6 Another disturbing research trend as mentioned by Azagba and colleagues is the fact that boys started smoking sooner and with an increased amplitude;1 such trends may be due to social behavior and roles. 1 Through “consultation and collaboration”7, with other health care workers, Occupational Therapists have a prominent role in health promotion and disease prevention.7 This can be applied to vaping abuse in the elementary school population. Although Occupational Therapists need to operate within their scope of practice, they can specifically offer the following therapeutic interventions to prevent e-cigarette and vaping use such as: “promoting healthy lifestyles; emphasizing occupation as an essential element of health promotion strategies; and providing interventions, not only with individuals but also with populations.”7 In addition to this, they can offer some level of education on the subject matter as a “primary prevention intervention.”7 In sum, as a society, we are in great need of therapeutic intervention with regards to providing e-cigarette vaping cessation educational programs starting at the elementary school level; Occupational Therapists can be part of the interdisciplinary solution.

1 Azagba S, Manzione L, Shan L, King J. Trends in Smoking Behaviors Among US Adolescent Cigarette Smokers. Pediatrics. 2020;145(3). doi:10.1542/peds.2019-3047 2 Office of Adolescent Health. Adolescents and Tobacco: Trends. HHS.gov. https://www.hhs.gov/ash/oah/adolescent-development/substance-use/drugs/t... . Published May 1, 2019. Accessed April 10, 2020. 3 Landman ST, Dhaliwal I, Mackenzie CA, Martinu T, Steele A, Bosma KJ. Life-threatening bronchiolitis related to electronic cigarette use in a Canadian youth. Canadian Medical Association Journal. 2019;191(48). doi:10.1503/cmaj.191402 4 Smoking as an occupation: Occupational therapists' perspectives. Forensicare. https://www.forensicare.vic.gov.au/researcheducation-2/research-projects... . Published February 20, 2017. Accessed April 10, 2020. 5 D.A.R.E. Responds to Vaping Crisis with New Enhancement Lesson. D.A.R.E. America. https://dare.org/d-a-r-e-responds-to-vaping-crisis-with-new-enhancement-... . Accessed April 10, 2020. 6 5 School E-cigarette Toolkit: Addressing Student Use of E-cigarettes and Vapes. Minnesota Department of Health. https://www.health.state.mn.us/communities/tobacco/ecigarettes/docs/scho... . Published October 7, 2019. Accessed April 10, 2020.

7 Occupational Therapy Services in the Promotion of Health and the Prevention of Disease and Disability. American Journal of Occupational Therapy. 2008;62(6):694-703. doi:10.5014/ajot.62.6.694

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Smoking research: basic research, intervention, prevention, and new trends

Affiliation.

• 1 Western Psychiatric Institute and Clinic, University of Pittsburgh, PA 15213-2593.
• PMID: 2700344

Smoking is a behavior that is influenced by a variety of factors that cut across methodologies, disciplines, and content areas within health psychology. The present article is designed to show the diversity and richness of smoking research by examining smoking from four perspective: basic laboratory research, intervention, prevention and deterrence, and new directions in smoking research. Methodologies that were derived from such varied sources as psychopharmacology, behavioral pharmacology, behavior therapy, clinical psychology, public health and health promotion, and social and developmental psychology have been used to study the smoking problem. The subject populations in these investigations ranged from animal models, to the individual smoker attempting to quit, to communities involved in health promotion and public health approaches. Future research should seek to provide new and improved examples of interdisciplinary research within the field of health psychology to multidisciplinary approaches from the basic and applied sciences.

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• Tobacco kills up to half of its users who don’t quit (1-3) .
• Tobacco kills more than 8 million people each year, including an estimated 1.3 million non-smokers who are exposed to second-hand smoke (4) .
• Around 80% of the world's 1.3 billion tobacco users live in low- and middle-income countries.
• In 2020, 22.3% of the world’s population used tobacco: 36.7% of men and 7.8% of women.
• To address the tobacco epidemic, WHO Member States adopted the WHO Framework Convention on Tobacco Control (WHO FCTC) in 2003. Currently 182 countries are Parties to this treaty.
• The WHO MPOWER measures are in line with the WHO FCTC and have been shown to save lives and reduce costs from averted healthcare expenditure.

Leading cause of death, illness and impoverishment

The tobacco epidemic is one of the biggest public health threats the world has ever faced, killing over 8 million people a year around the world. More than 7 million of those deaths are the result of direct tobacco use while around 1.3 million are the result of non-smokers being exposed to second-hand smoke (4) .

All forms of tobacco use are harmful, and there is no safe level of exposure to tobacco. Cigarette smoking is the most common form of tobacco use worldwide. Other tobacco products include waterpipe tobacco, cigars, cigarillos, heated tobacco, roll-your-own tobacco, pipe tobacco, bidis and kreteks, and smokeless tobacco products.

Around 80% of the 1.3 billion tobacco users worldwide live in low- and middle-income countries   (5) , where the burden of tobacco-related illness and death is heaviest. Tobacco use contributes to poverty by diverting household spending from basic needs such as food and shelter to tobacco. This spending behaviour is difficult to curb because tobacco is so addictive.

The economic costs of tobacco use are substantial and include significant health care costs for treating the diseases caused by tobacco use as well as the lost human capital that results from tobacco-attributable morbidity and mortality.

Key measures to reduce the demand for tobacco

Surveillance is key.

Good monitoring tracks the extent and character of the tobacco epidemic and indicates how best to tailor policies. Almost half of the world's population are regularly asked about their tobacco use in nationally representative surveys among adults and adolescents.

More on monitoring tobacco use

Second-hand smoke kills

Second-hand smoke is the smoke that fills restaurants, offices, homes, or other enclosed spaces when people smoke tobacco products. There is no safe level of exposure to second-hand tobacco smoke. Second-hand smoke causes serious cardiovascular and respiratory diseases, including coronary heart disease and lung cancer, and kills around 1.3 million people prematurely every year.

Over a quarter of the world's population living in 74 countries are protected by comprehensive national smoke-free laws.

More on second-hand smoke

Tobacco users need help to quit

Among smokers who are aware of the dangers of tobacco, most want to quit. Counselling and medication can more than double a tobacco user’s chance of successful quitting.

National comprehensive cessation services with full or partial cost-coverage are available to assist tobacco users to quit in only 32 countries, representing around a third of the world's population.

More on quitting tobacco

Pictorial health warnings work

Hard-hitting anti-tobacco mass media campaigns and pictorial health warnings prevent children and other vulnerable groups from taking up tobacco use, and increase the number of tobacco users who quit.

Over half the world’s population live in the 103 countries that meet best practice for graphic health warnings, which includes among other criteria, large (50% or more of the main areas of the package) pictorial health warnings displayed in the local language.

1.5 billion people live in the 36 countries that have aired at least one strong anti-tobacco mass media campaign within the last 2 years.

More on tobacco health warnings

Bans on tobacco advertising lower consumption

Tobacco advertising promotion and sponsorship (TAPS) increases and sustains tobacco use by effectively recruiting new tobacco users and discouraging tobacco users from quitting.

One third of countries (66), representing a quarter of the world’s population, have completely banned all forms of TAPS.

More on tobacco advertising bans

Taxes are effective in reducing tobacco use

Tobacco taxes are the most cost-effective way to reduce tobacco use, especially among youth and low-income groups. A tax increase that increases tobacco prices by 10% decreases tobacco consumption by about 4% in high-income countries and about 5% in low- and middle-income countries.

Even so, high tobacco taxes are rarely implemented. Only 41 countries, with 12% of the world's population, have introduced taxes on tobacco products so that at least 75% of the retail price is tax.

More on tobacco taxes

Illicit trade of tobacco products must be stopped

The illicit trade in tobacco products poses major health, economic and security concerns around the world. It is estimated that 1 in every 10 cigarettes and tobacco products consumed globally is illicit.

Experience from many countries demonstrates that illicit trade can be successfully addressed even when tobacco taxes and prices are raised, resulting in increased tax revenues and reduced tobacco use. 

The WHO FCTC Protocol to Eliminate the Illicit Trade of Tobacco Products (ITP) is the key supply side policy to reduce tobacco use and its health and economic consequences.

More on eliminating the illicit trade of tobacco products

Newer nicotine and tobacco products

Heated tobacco products (HTPs) are tobacco products that produce aerosols containing nicotine and toxic chemicals upon heating of the tobacco, or activation of a device containing the tobacco. They contain the highly addictive substance nicotine, non-tobacco additives and are often flavoured.

Despite claims of “risk reduction”, there is no evidence to demonstrate that HTPs are less harmful than conventional tobacco products. Many toxicants found in tobacco smoke are at significantly lower levels in HTP aerosol but HTP aerosol contains other toxicants found sometimes at higher levels than in tobacco smoke, such as glycidol, pyridine, dimethyl trisulfide, acetoin and methylglyoxal. 

Further, some toxicants found in HTP aerosols are not found in conventional cigarette smoke and may have associated health effects. Additionally, these products are highly variable and some of the toxicants found in the emissions of these products are carcinogens.  

More on heated tobacco products

Electronic cigarettes (or e-cigarettes) are the most common form of electronic nicotine delivery systems (ENDS) and electronic non-nicotine delivery systems (ENNDS) but there are others, such as e-cigars and e-pipes. ENDS contain varying amounts of nicotine and harmful emissions. Use of ENDS/ENNDS products is colloquially referred to as ‘vaping’. However this does not mean that they are harmless or emit water vapour.

E-cigarette emissions typically contain nicotine and other toxic substances that are harmful to users and non-users who are exposed to the aerosols second-hand. Some products claiming to be nicotine-free have been found to contain nicotine.

Evidence reveals that these products are harmful to health and are not safe. However, it is too early to provide a clear answer on the long-term impacts of using them or being exposed to them. Some recent studies suggest that ENDS use can increase the risk of heart disease and lung disorders. Nicotine exposure in pregnant women can have negative health consequences on the fetus, and nicotine, which is a highly addictive substance is damaging for brain development. 

More on e-cigarettes

Nicotine pouches are pre-portioned pouches that contain nicotine and are similar to traditional smokeless tobacco products such as snus in some respects including appearance, inclusion of nicotine and manner of use (placing them between the gum and lip). They are often promoted, as “tobacco-free”, which can be used anywhere and in some jurisdictions, such as the US, they are referred to as “white pouches”.

WHO response

There is a fundamental and irreconcilable conflict between the tobacco industry’s interests and public health policy interests. The tobacco industry produces and promotes a product that has been proven scientifically to be addictive, to cause disease and death and to give rise to a variety of social ills, including increased poverty.

The scale of the human and economic tragedy that tobacco imposes is shocking, and also preventable. The tobacco industry is fighting to ensure the dangers of their products are concealed, but we are fighting back.

The WHO FCTC is a milestone in the promotion of public health. It is an evidence-based treaty that reaffirms the right of people to the highest standard of health, provides legal dimensions for international health cooperation and sets high standards for compliance. Since its entry into force in 2005, the WHO FCTC has 182 Parties covering more than 90% of the world’s population.

In 2007, WHO introduced a practical, cost-effective initiative to scale up implementation of the demand reduction provisions of the WHO FCTC, called MPOWER. 

The 6 MPOWER measures are:

• Monitor tobacco use and prevention policies.
• Protect people from tobacco use.
• Offer help to quit tobacco use.
• Warn about the dangers of tobacco.
• Enforce bans on tobacco advertising, promotion and sponsorship.
• Raise taxes on tobacco.

WHO has been monitoring MPOWER measures since 2007. For more details on progress made for tobacco control at global, regional and country level, please refer to the series of  WHO reports on the global tobacco epidemic.  

  More on MPOWER

(1) Doll R, Peto R, Boreham J, Sutherland I. Mortality in relation to smoking: 50 years' observations on male British doctors. BMJ. 2004 Jun 26;328(7455):1519.

(2) Banks, E., Joshy, G., Weber, M.F. et al. Tobacco smoking and all-cause mortality in a large Australian cohort study: findings from a mature epidemic with current low smoking prevalence. BMC Med 13 , 38 (2015).

(3) Siddiqi, K., Husain, S., Vidyasagaran, A. et al. Global burden of disease due to smokeless tobacco consumption in adults: an updated analysis of data from 127 countries. BMC Med 18 , 222 (2020).

(4)  Global Burden of Disease [database .Washington, DC: Institute of Health Metrics; 2019. IHME,accessed 17 July 2023

(5)   WHO global report on trends in prevalence of tobacco use 2000-2025, fourth edition . WHO, Geneva, 2021

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Key facts about public school teachers in the U.S.

U.S. public school teachers have spent 2024 in the spotlight. The Democratic vice presidential nominee, Minnesota Gov. Tim Walz , has highlighted his previous career as a high school teacher and football coach. And a congressional hearing in June focused on multiple “crises” facing public school teachers , including low pay and overwork.

Here are some key facts about the 3.8 million public school teachers who work in America’s classrooms. These findings primarily come from a fall 2023 Pew Research Center survey of public K-12 teachers and from federal data.

This Pew Research Center analysis focuses on the demographics, experiences and hopes of K-12 public school teachers in the United States.

Demographic data comes from the National Center for Education Statistics and the U.S. Bureau of Labor Statistics .

Data on teachers’ experiences primarily comes from a Center survey of 2,531 U.S. public K-12 teachers conducted from Oct. 17 to Nov. 14, 2023. This post also draws on our survey of 5,188 U.S. workers conducted from Feb. 6 to 12, 2023; it included both part-time and full-time workers who are not self-employed and have only one job or have more than one but consider one to be their primary job.

More information about each survey, including the questions and methodology, can be found at the links in the text.

Most K-12 public school teachers are women. About three-quarters (77%) of teachers are women and 23% are men, according to data from the National Center for Education Statistics (NCES) for the 2020-21 school year, which is the most recent one available. This gender imbalance is especially notable in elementary schools, where 89% of teachers are women. Women make up 72% of middle school teachers and 60% of secondary or high school teachers.

There is far more gender balance among U.S. workers overall, across different industries and occupations. In 2020, women accounted for 47% of workers ages 25 and older, compared with 53% who were men, Bureau of Labor Statistics data shows. “Workers” in this analysis are those ages 25 and older in the U.S. noninstitutionalized civilian population.

The teaching force skews a bit younger than U.S. workers overall. Just 8% of K-12 public school teachers are at least 60 years old, but 16% of U.S. workers are at least 60. Public school teachers are more likely to be in their 30s and 40s than are U.S. workers overall (56% vs. 49%). 

As a group, U.S. public school teachers are considerably less racially and ethnically diverse than their students, according to NCES data. In 2020-21, 80% of public school elementary and secondary teachers identified as non-Hispanic White. Much smaller shares were Hispanic (9%), Black (6%), Asian American or multiracial (2% each). And fewer than 1% identified as Pacific Islander or American Indian and Alaska Native.

By comparison, just under half (46%) of all public school students were non-Hispanic White in 2020. Another 28% were Hispanic, 15% were Black and 5% were Asian. Meanwhile, 4% were multiracial, and about 1% or fewer were American Indian and Alaska Native or Pacific Islander.

The share of the teaching force who is White has declined 7 percentage points between the 1987-88 and 2020-21 school years, but the growth in teachers’ racial and ethnic diversity still has not kept pace with the rapid growth in the diversity of their students over this time span. ( Note: In 2021, the Center published a more detailed version of this analysis  using the most recent data available at that time.)

Only a third of teachers say they’re extremely or very satisfied with their job overall, according to a fall 2023 Center survey of public K-12 teachers . About half (48%) say they’re somewhat satisfied, while 18% say they are not too or not at all satisfied with their job.

Teachers express much lower job satisfaction than U.S. workers overall: 51% of all employed adults say they are extremely or very satisfied with their job, according to a separate Center survey conducted in early 2023 . (Data for U.S. workers excludes those who are self-employed.)

Teachers are especially dissatisfied with certain aspects of the job, including how much they are paid (51% say they are not too or not at all satisfied); the opportunities for training or ways to develop new skills (26%); and the benefits their employer provides (24%).

In fact, 29% of teachers said it was at least somewhat likely they’d look for a new job in the 2023-24 school year. Among these teachers, 40% said it was at least somewhat likely they’d look for a job outside of education entirely.

Most teachers describe their job as stressful and overwhelming. Majorities of teachers say they find their job stressful (77%) or overwhelming (68%) extremely often or often. Some teachers are especially likely to experience this:

• Women: 74% of women teachers say they find teaching to be overwhelming extremely often or often, compared with 49% of men. And 80% of women teachers frequently find the job stressful, compared with 67% of men.
• Elementary and middle school teachers: Educators at these levels are more likely than their counterparts at high schools to say that their job is frequently stressful and overwhelming.

Teachers’ negative feelings may be related to the issues they report with understaffing. Seven-in-ten public K-12 teachers say their school is understaffed, with 15% saying it’s very understaffed. Another 55% say their school is somewhat understaffed. This pattern is consistent across elementary, middle and high schools.

Newer teachers are the most likely to say their job is generally fulfilling and enjoyable. Overall, slim majorities of all K-12 public school teachers say they find their job fulfilling (56%) or enjoyable (53%) extremely often or often.

These sentiments are most common among those who’ve been teaching for less than six years. For instance, 67% of teachers who have been teaching for five years or less say their job is fulfilling extremely often or often. That compares with 52% of teachers with six to 10 years of experience and 54% of those who’ve been teaching for 11 years or more.

Fewer people are completing the educational requirements to be hired as teachers – just one indicator of the field’s growing pipeline problem , NCES data shows. Many K-12 teachers  enter their line of work after getting a bachelor’s degree in education, which includes a teacher preparation program. But some teachers instead meet license requirements through alternative preparation programs , offered through a college or university, state government, nonprofit or other organization.

Both the number and share of new college graduates with a bachelor’s degree in education have decreased over the last few decades . Yet during that span, the overall number and share of Americans with a college degree increased.

In 2021-22, the most recent year with available data, schools conferred about 89,000 education bachelor’s degrees, making up 4% of the total issued that year. In 2000-01, roughly 105,000 undergraduates (8% of the total) graduated with bachelor’s degrees in education.

Teacher preparation programs have also seen a steep decline in enrollment  in recent years, including both traditional programs associated with higher-education institutions and alternative ones. Between the 2012-13 and 2020-21 school years, the number of people who completed teacher prep programs dropped from about 190,000 to 160,000. In 2020-21, 13% of those prospective educators received their prep through alternative programs run by organizations other than institutions of higher education.

Teachers are relatively split on whether they would advise young people to join the profession, according to the Center’s fall 2023 survey. While 48% say they would recommend the profession to a young person starting out today, 52% say they would not.

High school teachers (56%) are more likely than middle school (46%) and elementary school (43%) teachers to recommend the job. This view is also more common among teachers with five years or less of teaching experience than among more veteran educators.

Teachers rate students in their school fairly low when it comes to academic performance and behavior. About half of K-12 public school teachers say the behavior (49%) and academic performance (48%) of most of students at their school is fair or poor. Meanwhile, just 17% say students’ academic performance is excellent or very good, and 13% say the same about student behavior at their school.

In addition to broader issues at their school, teachers report various challenges in their own classrooms. Teachers across all K-12 grade levels say certain student behaviors are major issues in their classroom:

• Showing little to no interest in learning (47% of teachers say this is a major problem)
• Being distracted by their cellphones (33%)
• Getting up and walking around when they’re not supposed to (21%)
• Being disrespectful toward teachers (21%)

Certain problems are more prevalent for older or younger grade levels. For instance, high school teachers report bigger problems with cellphone distraction (72% say it’s a major problem) and students showing little to no interest in learning (58%). Meanwhile, elementary and middle school teachers are more likely than high school teachers to experience students getting up and walking around or being disrespectful toward teachers.

About half of teachers (51%) say that if there’s one thing they want the public to know about them, it’s that teaching is a difficult job and teachers are hardworking. This was the most common response to an open-ended question we asked teachers last fall .

Another 22% of teachers said they want the public to know that teachers care about their students, and 17% want the public to know that teachers are undervalued.

• Education & Politics

Katherine Schaeffer is a research analyst at Pew Research Center .

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Psychedelic drug psilocybin may rewire brain connectivity to treat body dysmorphic disorder, research suggests

by Genomic Press

Body dysmorphic disorder (BDD) is a debilitating mental illness characterized by an obsessive preoccupation with perceived flaws in one's physical appearance. Patients with BDD often have distorted self-image, intrusive thoughts, and compulsive behaviors that significantly impair daily functioning and quality of life. Current therapies have limited efficacy, leaving many sufferers without relief.

A study led by researchers at Columbia University and published in Psychedelics provides hope by revealing how the psychedelic drug psilocybin , the active ingredient in "magic mushrooms," may rewire connectivity of brain circuitry, potentially aiding in the treatment of this debilitating disorder. The paper is titled "Single-Dose Psilocybin Alters Resting State Functional Networks in Patients with Body Dysmorphic Disorder."

In the pilot trial, eight adults with moderate-to-severe BDD that had not responded to standard treatments received a single 25mg oral dose of psilocybin in a supportive setting. Using cutting-edge functional MRI technology, the scientists scanned the participants' brains one day before and one day after the psilocybin session. Sophisticated pattern analysis techniques were then applied to map changes in brain network connectivity and link them to subsequent clinical outcomes.

The results were striking: Just one day after psilocybin administration, the patients exhibited increased connectivity both within a network governing executive functions , and between this network and others involved in processing emotionally salient stimuli and self-referential thinking. Notably, those who showed the greatest strengthening of these neural connections also experienced the most improvement in BDD symptoms one week later.

While preliminary, the findings align with a growing body of evidence indicating that psychedelic compounds like psilocybin can promote mental health by enhancing the brain's capacity for flexibility and integration. By facilitating communication within and between brain networks that are often dysregulated in psychiatric disorders , psilocybin may help restore more adaptive cognitive and emotional functioning.

As the first study of psilocybin in a BDD population, the trial was small and lacked a placebo control. The researchers caution that larger, placebo-controlled studies are needed to verify the efficacy and durability of the treatment. Still, the robust brain-behavior relationships uncovered bode well for the ongoing development of psilocybin therapy.

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• Iran J Nurs Midwifery Res
• v.19(6); Nov-Dec 2014

Experiences of adult smokers from the concepts of smoking: A content analysis

Hossein ebrahimi.

1 Department of Psychiatric Nursing, Faculty of Nursing and Midwifery, Tabriz University of Medical Sciences, Tabriz, Iran

Mohammad Hasan Sahebihagh

2 Student Research Committee, Tabriz Health Service Management Center, Tabriz University of Medical Sciences, Tabriz, Iran

Fazlollah Ghofranipour

3 Department of Health Education, Tarbiat Modares University, Tehran, Iran

JafarSadegh Tabrizi

4 Department of Health Service Management, Tabriz Health Service Management Research Centre, Faculty of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran

Background:

Smoking cigarettes is a risk factor for many physical and mental diseases. About five million people die of smoking every year. Understanding the concept of cigarette smoking can help people develop their knowledge with regard to smoking. A qualitative research seems essential to detect these concepts. Therefore, the present study aims to take into account the experience of adult smokers with regard to the concept of smoking.

Materials and Methods:

This is a qualitative content analysis study conducted on 12 smokers in four selected cities in Iran. Data were collected by in-depth, semi-structured interviews, transcribed verbatim, and simultaneously coded. Subsequently, they were analyzed using the content analysis method.

In the present study, eight concepts (themes), 22 subcategories, and 81 codes have emerged. The obtained concepts are physics of a cigarette, addiction and dependency, habit, feel the need, pleasure, seeking peace, mental involvement, and self-induction.

Conclusions:

The participants’ experiences with regard to cigarette smoking can affect their understanding of the concepts of smoking. The understanding of these concepts by nurses and smokers can enhance their knowledge about the existing facts of smoking, which can act as a foundation for designing preventive methods and smoking cessation programs.

I NTRODUCTION

Cigarettes cause five million deaths in a year around the world. Cigarette smoking is one of the most significant causes of early death.[ 1 ] About 16% of the men's mortality and 7% of women's mortality is considered to be associated with cigarettes.[ 2 ] Cigarette smoking is a risk factor for coronary artery diseases,[ 3 ] renal failure,[ 4 ] cancers, and pulmonary diseases.[ 5 , 6 , 7 ] It is associated with still birth, low fetal growth, pediatric cancers, infant sudden death syndrome, and reduced natural fertility.[ 8 ]

About 25% of the people smoke worldwide.[ 9 ] Although smoking has decreased in the US, it has an ascending trend in some developing countries and in some specific populations, including women.[ 10 ] The World Health Organization (WHO) reports show that the geography of cigarette smoking has shifted from developed countries to developing countries and the problem in Asia has become worse.[ 11 ] In Iran, although the prevalence of smoking has been reported differently in various people and cities, the WHO has reported a prevalence of 20.4% in men, 1% in women, and 10.8% in the entire population.[ 12 ]

Detection of how younger people understand cigarette smoking is a crucial need. Also the thinking processes existing prior to the start of smoking and during consumption of cigarettes must be studied and investigated.[ 13 ] If the concepts related to the health phenomena are understood well, they can help more effectively in the provision of healthcare to people. Concepts provide a higher level of understanding and recognition in relation to the provision of treatment and care programs, and increase the nurses’ skills and power in the prevention of smoking and cigarette cessation programs.[ 14 ]

The current strategies to measure the perception of smoking risk are in numeric estimations and cannot adequately measure the individuals’ feelings and thoughts with regard to measurement of the smoking risk.[ 15 ] A qualitative research can yield a definite percept of the feel of real cigarette smoking among smokers.[ 16 ] A qualitative research will enhance the understanding of the scientists of health science on smoking and enable them to use their knowledge when working with their clients, when giving healthcare, and in general fields of smoking control.[ 17 ] Bredie's findings showed that a motivational and in-depth interview is much more effective for smoking cessation, when compared with the usual recommendations given by physicians and nurses.[ 18 ] Smoking has been frequently studied through qualitative researches by nursing scientists,[ 17 ] but there are few studies on the explanation and development of the smoking concept. Chang (2004), in a study to develop the concept of ‘smoking temptation,’ conducted five semi-structured interviews, with five adult smokers, and obtained five concepts — ‘reaction to situational stimulants’, ‘avoiding the low prestige of smoking,’ ‘nicotine dependency,’ ‘habitual behavior,’ and ‘loss of control’.[ 19 ] In another qualitative content analysis study, children have described smoking as a type of addiction, habit or behavior, which cannot be stopped. They believe that the nature of this addiction has not been well detected. They believe that addiction to cigarette is the negative outcome of smoking behavior. They deeply believe that cigarette is hazardous to health and have expressed that it acts as a sort of trap (being involved in it. with no control). None of the children believe that escape from this is easy.[ 13 ]

Given the importance of concepts in the developing of knowledge, and the role of knowledge in reducing the incidence and prevalence of smoking, as also the low number of studies on the concepts of cigarettes and dependency of smoking as per the culture of the people,[ 20 , 21 ] the present study aims to detect the smokers’ experience from cigarette smoking in the Iranian culture.

M ATERIALS AND M ETHODS

The present study was conducted through a conventional content analysis. The goal of the conventional content analysis was description of the phenomenon, which could be employed when the resources about a phenomenon were low. In the content analysis method, the code categories were directly extracted from the interview transcripts.[ 22 ]

The participants comprised of 12 smokers. Of these, eight were male and four were female. Their ages ranged from 21 to 51 years and their education varied from primary school to a Bachelors degree. With regard to their occupation, two were homemakers, four were workers, four were employees, one was a university student, and one was self-employed. Seven participants resided in Tabriz, two in Tehran, two in Ilam, and one in Boushehr. The Fagestrom test for nicotine dependency was adopted in the present study. This test had six questions, including smoking the first cigarette after waking up (within five minutes = 3, 6-30 minutes = 2, 31-60 minutes = 1, and after 60 minutes = 0), smoking in forbidden places (yes = 1, no = 0), ignoring the first cigarette in the morning (difficult = 1, not difficult = 0), number of cigarettes (31 or more = 3, 21-30 = 2, 11-20 = 1, and 10 or less = 0), number of cigarettes smoked in the morning compared to prior days (more = 2, equal or less = 1), and suffering from a severe disease, with long hours of bed rest during the day (yes = 1, No = 0). The range of scores in this test was 1-11. Scores 1-6 depicted a slight-to-moderate smoker and 7-11 depicted a heavy smoker.[ 23 ] In the present study, the participants’ mean Fagestrom score was 8.33.

The participants in Tabriz were selected from smokers who were acquainted with the researcher. Some other persons were used to facilitate the selection of participants in other cities in Iran. These people selected the participants by talking with their acquaintances, who were smokers, introduced the researcher to them, and conducted the background check for the interviews. The interviews with the participants were conducted in public gardens of the city, their working place, the researcher's office, the participants’ houses or the researcher's house. Twelve interviews were done with 10 participants (two participants underwent two interviews). Two participants wrote out their smoking experience as a scenario and handed it to the researcher. After eight interviews, the researcher attained relative saturation of the data and conducted the remaining four interviews to achieve maximum data saturation. All interviews were conducted in 2012.

The participants underwent deep and semi-structured interviews. At the beginning of the interviews, the research goals and method were explained to the participants. The interviews started with some general questions. The question asked of the smokers was, “Why did you start smoking?’ please tell your story of smoking from the first day to the present.”. During the interview, the participants’ convenience was attended to and at any stage of the interview, whenever the interviewee was tired, the interview would be stopped and restarted after a couple of minutes. The interviews lasted at the most for one hour, and if the participants’ story did not end within one hour, another interview was arranged.

To reach a level of trust with regard to the credibility of the participants, the researcher had a long and close acquaintance with the participants (for two years). The researcher was born in a smoking family and had lived with a smoker for years, had research projects, and needed working experience in the context of smoking. In addition, during the interviews, the interviews were not only recorded, but also listened to, and thereafter, transcribed verbatim. The transcripts and scenarios were reviewed and defined. The content unit, meaning unit, meaning condensed unit, and that were abstracted and labeled with a code. Interviews, transcripts, and scenarios, including the extracted codes, were given to the participants, and were confirmed by them. The consistency of the codes, with the categories and concepts, was checked and confirmed by two colleagues, who were experts at qualitative research. With regard to the dependability, the interviews transcripts were handed to the researcher's coworker, and after he coded the transcripts. The consistency of the codes was checked and confirmed. For confirmability of the study, the sampling mode, question development and interview tool, the method of coding, and category extraction and modification were recorded and documented. To achieve utmost transferability, the participants were selected from a vast spectrum (men, women, young, old, and light and heavy smokers, from various locations in Iran). The findings of the study were handed to a non-participant smoker and their truthfulness and consistency were confirmed by him, in comparison with his own experiences.

This project was approved by the Ethics Committee of Research and Technology Vice-Chancellor of the Tabriz University of Medical Sciences. The participants attended the research through their own interest and a written consent was signed by them before the interviews.

In the present study, 81 codes in 22 subcategories and eight themes were attained. The themes that emerged were physics of a cigarette, addiction and dependency, habit, feel the need, pleasure, seeking peace, mental involvement, and self-induction [ Table 1 ].

Themes, subcategories, and smoking codes

Physics of a cigarette

Based on the participants’ experiences, cigarette as an object is a rolled piece of paper, 5-6 cm in length, which is filled with tobacco, with a filter at one end. This object is lit by putting a flame on one end (the one with no filter) and sucking the air in through the other end (with the filter) with the help of the lips and mouth. The smoke that results from it is inhaled into the lungs through the throat. The cigarette may be held directly by the lips or a cigarette holder. Based on the participants’ experiences, cigarettes are of different qualities and are defined by the nicotine or tar in it. Low-quality cigarettes have high nicotine and tar and their taste is bitter and unfavorable. They smell very bad, are cheap, and give a big flame, with a lot of smoke. After smoking, their filter gets darker in color and dirty compared to quality cigarettes (with low nicotine and tar). Low-quality cigarettes result in severe reactions, even in formal smokers, and cause cough and burning throat. There are different types of cigarettes in the market depending on the type of tobacco, level of tar and nicotine, with or without a filter, and also the type of a filter, with or without flavor, and also the type of flavor, the different manufacturers, and their designs. Participant number six states:

“Cigarettes are different, their nicotine and tar are different. For example, the nicotine in a cigarette may be one unit, and in another, it may be 0.3 or 0.4 unit. Some cigarettes like…. are very heavy so that after smoking, their end gets black. But, when you smoke filter plus cigarettes, although their nicotine is higher, you never feel you are smoking, as their tar is low”

Addiction and dependency

Some participants clearly mentioned that smoking is an addiction that makes the smokers dependent on cigarettes. After nicotine enters their body, the dependency gradually increases through time. Participant number four states:

“After cigarette (nicotine) entered your body, its consumption gradually increases. I don’t know if it is due to its morphine or something! It is its property. When I have no cigarette, I feel I have lost something; I cannot tolerate it at all. I miss it to death.”

Meanwhile, most of the participants avoided using the word ‘addiction’ for smoking and somehow tried to distinguish smoking from addiction. They used the word ‘dependency’ more and defined it as a high craving for a cigarette. The most important property of dependency was the smoker's lack of self-control. These participants were heavy smokers and smoked continuously during the interview. They manifested this behavior due to lack of nicotine and it was more like the behavior of drug abusers toward morphine. Their behavior was such that if they did not smoke for one day, they got a craving for it, and were mentally disturbed. At this point in time, they were restless and confused. Based on the participants’ experiences, dependency referred to that point when the smokers could not smoke, and missed it, and were automatically driven to it. Dependency meant that the smokers liked to smoke when they saw another person smoke, or when there was a pack of cigarettes in front of them and they could not resist the temptation. Dependency meant doing anything for a cigarette when there were none around. It meant getting confused, irritable, aggressive, restless, and not having good sleep if there was no cigarette. It meant buying a cigarette even if it meant a lot of trouble or going out at midnight to distant places to get one. It meant an internal craving for a cigarette. It was a sort of total commitment for the smoker. It meant smoking despite hating it and being a slave to it. It was such that there was no escape for a smoker and he/she accepted any hazard or damage it caused. Female participant, number 11, states:

“I like someone would separate this hell (cigarette) from me. I swear to God to kiss his/her feet. I remember one night, I ran out of cigarettes. It was 1 AM, I got dressed and went out to buy cigarette. In my town (Ilam), nobody leaves home that time of night, but I did that for cigarette. Now everywhere I go, I should firstly have my pack with me. If I have half a pack, I feel it is not adequate, it may finish. I go and buy another pack. We had no money to spend, I broke the charity box and got the money to buy cigarettes!”

Based on the participants’ experiences, the habit of smoking occurs when the smoker lights a cigarette and smokes it, but is unaware of it, similar to breathing, which is a habit and is done without thinking or intention. Smoking is a habit that needs no thinking or hesitation. The participants believe that a habit is a very strong behavior, which overcomes the smokers’ intention in such a manner that stopping this habit is not easy. Smoking changes to a habit shortly after starting it. With an increase in the number of cigarettes, the smoker gets used to the new number; therefore, a reduction in the number of cigarettes is very difficult. Participant number one states:

“When I drive, unintentionally my hand picks up a stick. I say this is the habit of the hand. To hate cigarettes, I left them in water for a couple of days. After they were decayed, I put them in my pocket to be disgusted with its bad smell and quit. I quitted for a month, and then, started again. What a strange habit!”

Comparing themselves with drug abusers, the participants who had experienced smoking as a habit believed that it was different from addiction to drugs. They believed that if smokers did not smoke, they did not face a huge problem and could tolerate a delay in smoking for a couple of hours, while drug abusers displayed more severe signs of substance dependency even one hour after not using the drugs and their behavior got out of control. Participant number three states:

“Smoking does not kill one. For example, if I promise not to smoke, it is not like drugs that if the drug abusers do not take, they die. Cigarettes have nothing in, just you may miss it after one or two days, and like to smoke.”

However, the participants who believed smoking was a habit described that it was worse than drugs, as taking drugs needed the essential tools, which were not necessary for smoking. For instance, drug abusers prepared drugs illegally and could not prepare them in any shop in the town. They had to seek a safe place and needed specific equipment. All these necessary tools limit drug abuse, while in smoking, none of these limitations were present, and hence, the smokers smoked more freely.

Feel the need

Some participants believed that a cigarette was essential for a smokers’ body, similar to food, and smoking was a behavior to fulfill this need. Based on their experiences, high-nicotine cigarettes fulfilled the need of the body for nicotine, and the smoker was not interested in further cigarettes after smoking high-nicotine cigarettes. The body adapted to a higher level of nicotine through an increase in the number of cigarettes in such way that if there was a shortage of nicotine, the smokers increased the number of cigarettes and had stronger puffs to compensate their need for nicotine.

On the contrary, a person whose body is used to a lower amount of nicotine has less demand for cigarettes. Participant number seven states:

“Like when we are hungry and go for food, the same condition is for cigarettes. The body likes a cigarette. The cigarettes with high nicotine compensate the shortage of nicotine in the body, and the smoker is not interested in smoking for a while.”

A high number of participants believed smoking was for pleasure. They claimed that they smoked for pleasure and unavailability of the cigarettes equaled missing that pleasure. Based on their experiences, the pleasure of smoking was when one was informed and smoked, and through a puff, was drawn into his/her dreams, and then, gradually he/she released the smoke. They believed that pleasure was the cause of the habit and smoking as a habit was not a pleasure, but a disgusting experience. Participant number two states:

“I hate smoking as a habit, of course, I myself have lit a cigarette as a habit and smoked, but whenever I noticed the cigarette I am smoking is due to a habit, I hated smoking and threw away the cigarette and smashed it. I smoke just for pleasure.”

Participant number three disagreed with the asbove- mentioned concept of pleasure and smoking habit caused by the cigarette and stated:

’I have found no pleasure in smoking although I have seen some people claiming that. However, I have found no pleasure. For me, it is a habit.‘

Based on the participants’ experiences, the pleasure of a cigarette is in smoking it, and after that, there is no pleasure, but disgust for its bad smell and taste. Almost all the participants mentioned that smoking is very pleasant after drinking a cup of tea and after a meal, especially rich foods, broth, and kebab with rice.

Seeking peace

Most of the participants stated that whenever they were sad or disappointed, they smoked and got peace. Smoking protected them against stress and they de-stressed themselves through smoking. Some other participants counted on the cigarette as a shelter, to take refuge in whenever they felt sad, in order to get peace. Most of the participants considered a cigarette to be their friend in happiness and sorrow. Participant number three states:

‘To my viewpoint, a cigarette is a palliative, sort of a shelter, as whenever I am sad I refuge to, whenever I am happy, I again refuge to. For this reason, it is a support for me.’

Mental involvement

Some participants believed smoking is a mental disease, wherein, smoking, by itself, turned into a mental involvement. Subsequently, the individuals’ curiosity was roused to test smoking, and through testing it and its continuation, one tried to resolve this mental involvement. Participant number three states:

“Something seems to engage your mind, it engages your thought. Something seems to enter your mind and make wheeze, when I smoke a cigarette, it is relieved.”

These participants also believe that such mental involvement plays a role in starting, continuing, and quitting smoking in such a manner that if this involvement is not resolved, cessation is impossible. Participant number eight states:

“I guess, I have tried to quit 4-5 times. Once I dropped the cigarette and promised not to smoke again, but the cigarette had no sooner touched the ground, I felt I was making a mistake, before three days completed, I started again. I myself knew, I would start that again as I had not solved the problem in my mind.”

Self-induction

Some participants believed smoking was dependent on situations and self-induction. They indicated that the temptation for smoking rose in a specific situation. In their view, all concepts of smoking were not real, but they are a sort of self-induced. Participant number three states:

‘It is our self-induction. I talk about myself. I have inducted that myself. I smoke as I am so sad., In fact, I smoke a lot when even I am happy. For example, in a wedding party, it is a happy time, but I again smoke a lot. I think it is a sort of self- induction.’

This participant defines the word ‘self-induction’ as a condition when a person is in one of the above-mentioned situations, he/she smokes. The reason is he/she has associated his/her smoking with these situations. Now, if he/she is in the same situation, but cannot smoke, or he/she is aware of the role of self-induction in such a situation, or he/she eats a special food, which has been associated with that situation, and instead of smoking a cigarette, the person avoids smoking. Participant number eight, who had successfully quit, mentioned the importance of self-induction in smoking and stated that:

‘If someone says the cessation makes no problem for me and I will quit that, this is a self-induction and facilitates cessation. On the contrary, if he/she says, I fear of smoking again, for sure, he/she will smoke again. I kept saying I never smoke. In a day, I repeated I hate cigarettes; I hate cigarettes for ten times. I repeated this phrase continuously until I actually hated cigarettes.’

D ISCUSSION

In the present study, eight major themes emerged based on the participants’ experiences. The findings of the present study showed that cigarettes were available in various types in the market. This was the trick of cigarette-making factories to attract new customers and maintain the loyal ones.

There are evidences to show that the cigarette-making industry targets the young generation and employs various methods (like making flavored cigarettes) to sell its products to them.[ 11 ] Control of the amount of tar and nicotine in cigarettes is another factor that causes a variety of tastes in cigarettes, such as, light or very light cigarettes. The cigarette industry claims that light and very light cigarettes are not hazardous, as their tar and nicotine are controlled; however, the fact is that these cigarettes are as hazardous to people's health as common cigarettes. The findings of the present study show that those who smoke low-nicotine cigarettes have to increase the number of cigarettes or puff more deeply during smoking, to compensate the nicotine needed by their body, which is consistent with the findings of Frieden (2005).[ 10 ]

The findings of the present study show that the participants’ experiences from their smoking concepts are not similar. This may be due to the fact that smokers have no good recollection of their smoking from their early stages of smoking. They understand these concepts more over time and by acquiring more experience from smoking. For instance, understanding the concept of addiction to cigarettes is difficult for someone who is not yet at the stage of dependency. In the present study, addiction to cigarettes is the most extensive and important concept to which the participants point, with different remarks. Although almost all the participants have experienced the addictive nature of cigarettes, they have used the word ‘addiction’ rarely. This shows that addiction is not acceptable as normal behavior in the Iranian culture. Being against the norm and its fear are strong points to prevent smoking. Children who believe that smoking is followed by addiction are never interested in smoking. Meanwhile, those who believe they can smoke without being addicted like to experience smoking.[ 13 ]

The other important concepts that emerged from the present study were pleasure and reaching peace through smoking. These concepts were also reported by Pletcher,[ 24 ] Harwood,[ 25 ] Patkar,[ 26 ] Gilbert,[ 27 ] and Shadel.[ 28 ] Despite the findings of the present study and the above- mentioned studies, it seemed that nurses and health sciences experts did not react properly and disregarded the apparent advantages of cigarettes. The fact was that denial of the positive characteristics of cigarettes did not change the fact and made the smokers guard against preventive and cessation programs, as they found the experts’ claims contrary to their own experiences and believed more in their own experiences. Therefore, nurses and other experts in the domain of health were told not to disregard the apparent positive characteristics of smoking, but confirm them, until they tried to provoke the public realistically, and by doing this, they could explain to them that the peace they acquired by smoking was temporary and what really happened in the long term to the body was that it lowered the body's ability and caused development of various diseases. Long-term smoking was not relaxing, but increased mental disorders like anxiety, fear, and panic.[ 25 ]

Another concept that emerged in the present study was interpretation of smoking behavior as a disease or mental involvement. Mahabee (2013), stated that smoking was a childrens’ disease, as the the highest dependency on cigarette in adults occurred before the age of 18.[ 29 ] The advantage of considering smoking behavior as a disease was accepting that the disease could be the initial step for treatment, and this issue was of great importance for the smokers. The physicians‘ and nurses’ recommendation to quit smoking was a major step toward smoking cessation. Research showed that physicians‘ and nurses’ recommendation, even if conducted for less than five minutes, increased the cessation level three-fold.[ 26 ]

Self-induction was another concept that emerged. This concept showed that smoking should be considered as something more than dependency to drugs, and self-induction to smoke in specific situations should not be ignored. Smokers’ awareness of such an induction may play a valuable role in theprevention or cessation of smoking. In a study, the researchers noticed that adolescents who succeeded in cessation had significantly higher knowledge, compared to those who did not.[ 23 ]

In summary, a better understanding of smoking concepts by nurses and smokers can be effective for smoking prevention and cessation. Therefore, to prevent and treat smoking, we must know these concepts well and target smokers and adolescents with extensive knowledge.

Research limitations: We had to select the participants from persons we were acquainted with, due to lack of preparedness of strangers to undergo interviews and voice recordings. In any case, we tried to select those acquainted persons who varied in their occupation, education, age, and level of dependency to smoking.

A CKNOWLEDGMENTS

This study was the result of a PhD dissertation. The researchers greatly appreciate the Vice-Chancellor for Research and Technology of the Tabriz University of Medical Sciences, as well as the persons facilitating the interviews with the participants in other cities. We acknowledge Dr Hadi Hasankhani for reviewing the consistency, code categorizations, categories, and themes. We truly appreciate the participants, who devoted their time for the interviews and confirmed the research data.

Source of Support: Supported by the Research Vice-Chancellor of the Tabriz University of Medical Sciences

Conflict of Interest: None declared.

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