negative effects of smoking essay

Smoking and Its Negative Effects on Human Beings Research Paper

Smoking is one of the most common negative habits that people indulge in. Many health experts have warned that smoking is unhealthy and dangerous to the human health. This essay will discuss the negative effects of smoking on human beings.

Smoking cigarette is addictive that is why many smokers have difficulties in giving up the habit. Cigarettes are produced of tobacco with a large percent of other additives, which account for the largest number of preventable deaths in the world. People who smoke commonly face different health problems, which are caused by tobacco consumption. Therefore, smoking has negative health consequences for smokers and people who live with them and become passive smokers as a result.

The WHO and other health organisations have sensitised people on the dangers of smoking. There are many health conditions which smokers are likely to suffer from (Pampel 61). Their bodies absorb harmful toxins which cigarettes contain which are dangerous to their health.

Smoking is a major health risk which results in heart attacks, strokes, bronchitis, and other respiratory diseases. The accumulation of tobacco and other toxins in the respiratory tract of a smoker makes a person suffer from respiratory health conditions.

Smokers, therefore, are likely to incur huge medical bills when they seek for treatment for these diseases. Many governments spend a lot of money on treating smoking related diseases, which increases the cost of healthcare. Pampel argues that smokers can succumb to such illnesses unless they stop smoking (64).

Tobacco consumption causes dental problems which are difficult to reverse. Smokers are likely to have bad breath, stained teeth and smelly gums. Toxic elements, which cigarettes contain, for instance, tar, have dangerous impacts on human health. These substances cause smokers to have poor dents and even lose their teeth (Peate 362).

Smokers are likely to suffer emotionally and psychologically because poor health and unattractive appearance, caused, for example, by stained or broken teeth, make a person lose his/her own self-esteem. Smokers are likely to be shunned by people close to them because of fetid breath, bad body odour and poor outward appearance. Therefore, people need to be made aware of dental and other health problems they are likely to experience as a result of smoking.

Tobacco consumption causes a lot of deaths in developing countries. These countries have weak laws which do not effectively regulate cigarette selling and consumption. Advertisement implicit messages encourage the young to become smokers. Tobacco advertising in many developed countries has been prohibited. However, some third world countries still allow tobacco advertising, which encourages more people to acquire this bad habit.

The images of sophistication, bravery and glamour which are carried by tobacco adverts easily persuade the young to become smokers. Peate reveals that tobacco companies target adolescents and women to increase their sales (363). These people are easily influenced by what they see in the media. People who begin smoking at early age are likely to be addicted for a longer period than those who develop the habit at mature age (Cox).

Smokers are exposed to various carcinogens in cigarettes. These carcinogens cause cancer and negatively affect human health. Lung, throat, brain, bladder, cervical cancer as well as other forms are caused by smoking. The symptoms are often detected at the time when the smoker’s health condition is already chronic.

Cancer is one of the leading causes of death world wide. A significant number of cancer patients have a history of smoking and tobacco consumption (Peate 365). If people get exposed to exhaled smoke, they are likely to be affected by it. They breathe in toxic components of the exhaled smoke that deposit in their lungs and other respiratory organs. These people can suffer from respiratory illnesses as well.

Women, who smoke during pregnancy, are likely to expose their unborn babies to toxic substances contained in cigarettes. The tar that is present in cigarettes is likely to be embedded in the DNA of a mother, who may pass it on to the child in her womb. These toxic components inhibit the normal growth of a baby in the fetus, which results in death and still births. Cox reveals that if the pregnancy proceeds to full term, the delivered child can have severe brain disorders.

Such children are very slow at learning because their cognitive functions are impaired. Female smokers are likely to become infertile or their reproductive abilities are limited. Nicotine restricts the ability of the female reproductive system to generate estrogen. Many physiological and reproductive functions in women depend on estrogen.

Nicotine is a substance found in cigarettes which is very addictive. People who try to give up smoking experience severe withdrawal symptoms, which restrict their ability to function effectively. They are likely to experience several episodes of depression.

This is because their bodies are used to the intake of nicotine and have difficulties in performing its functions without it (Cox). Nicotine stimulates the human mind just like any other drug, which increases the risk of high blood pressure in a smoker. From the above mentioned, it is easy to conclude that smoking has negative effects on people’s health.

Works Cited

Cox, Jack. “ The Lesser Known Harmful Effects of Smoking .” The Register . 2012. Orange Country Register News . Web.

Pampel, Fred C. Tobacco Industry and Smoking . New York: Infobase Publishing, 2009. Print.

Peate, Ian. “The Effects of Smoking on the Reproductive Health of Men”. British Journal of Nursing 14.7 (2005): 362–366. Print.

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Essay on Smoking

500 words essay on  smoking.

One of the most common problems we are facing in today’s world which is killing people is smoking. A lot of people pick up this habit because of stress , personal issues and more. In fact, some even begin showing it off. When someone smokes a cigarette, they not only hurt themselves but everyone around them. It has many ill-effects on the human body which we will go through in the essay on smoking.

Ill-Effects of Smoking

Tobacco can have a disastrous impact on our health. Nonetheless, people consume it daily for a long period of time till it’s too late. Nearly one billion people in the whole world smoke. It is a shocking figure as that 1 billion puts millions of people at risk along with themselves.

Cigarettes have a major impact on the lungs. Around a third of all cancer cases happen due to smoking. For instance, it can affect breathing and causes shortness of breath and coughing. Further, it also increases the risk of respiratory tract infection which ultimately reduces the quality of life.

In addition to these serious health consequences, smoking impacts the well-being of a person as well. It alters the sense of smell and taste. Further, it also reduces the ability to perform physical exercises.

It also hampers your physical appearances like giving yellow teeth and aged skin. You also get a greater risk of depression or anxiety . Smoking also affects our relationship with our family, friends and colleagues.

Most importantly, it is also an expensive habit. In other words, it entails heavy financial costs. Even though some people don’t have money to get by, they waste it on cigarettes because of their addiction.

How to Quit Smoking?

There are many ways through which one can quit smoking. The first one is preparing for the day when you will quit. It is not easy to quit a habit abruptly, so set a date to give yourself time to prepare mentally.

Further, you can also use NRTs for your nicotine dependence. They can reduce your craving and withdrawal symptoms. NRTs like skin patches, chewing gums, lozenges, nasal spray and inhalers can help greatly.

Moreover, you can also consider non-nicotine medications. They require a prescription so it is essential to talk to your doctor to get access to it. Most importantly, seek behavioural support. To tackle your dependence on nicotine, it is essential to get counselling services, self-materials or more to get through this phase.

One can also try alternative therapies if they want to try them. There is no harm in trying as long as you are determined to quit smoking. For instance, filters, smoking deterrents, e-cigarettes, acupuncture, cold laser therapy, yoga and more can work for some people.

Always remember that you cannot quit smoking instantly as it will be bad for you as well. Try cutting down on it and then slowly and steadily give it up altogether.

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Conclusion of the Essay on Smoking

Thus, if anyone is a slave to cigarettes, it is essential for them to understand that it is never too late to stop smoking. With the help and a good action plan, anyone can quit it for good. Moreover, the benefits will be evident within a few days of quitting.

FAQ of Essay on Smoking

Question 1: What are the effects of smoking?

Answer 1: Smoking has major effects like cancer, heart disease, stroke, lung diseases, diabetes, and more. It also increases the risk for tuberculosis, certain eye diseases, and problems with the immune system .

Question 2: Why should we avoid smoking?

Answer 2: We must avoid smoking as it can lengthen your life expectancy. Moreover, by not smoking, you decrease your risk of disease which includes lung cancer, throat cancer, heart disease, high blood pressure, and more.

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Health Effects of Cigarette Smoking

Smoking and death, smoking and increased health risks, smoking and cardiovascular disease, smoking and respiratory disease, smoking and cancer, smoking and other health risks, quitting and reduced risks.

Cigarette smoking harms nearly every organ of the body, causes many diseases, and reduces the health of smokers in general. 1,2

Quitting smoking lowers your risk for smoking-related diseases and can add years to your life. 1,2

Cigarette smoking is the leading cause of preventable death in the United States. 1

• Cigarette smoking causes more than 480,000 deaths each year in the United States. This is nearly one in five deaths. 1,2,3
• Human immunodeficiency virus (HIV)
• Illegal drug use
• Alcohol use
• Motor vehicle injuries
• Firearm-related incidents
• More than 10 times as many U.S. citizens have died prematurely from cigarette smoking than have died in all the wars fought by the United States. 1
• Smoking causes about 90% (or 9 out of 10) of all lung cancer deaths. 1,2  More women die from lung cancer each year than from breast cancer. 5
• Smoking causes about 80% (or 8 out of 10) of all deaths from chronic obstructive pulmonary disease (COPD). 1
• Cigarette smoking increases risk for death from all causes in men and women. 1
• The risk of dying from cigarette smoking has increased over the last 50 years in the U.S. 1

Smokers are more likely than nonsmokers to develop heart disease, stroke, and lung cancer. 1

• For coronary heart disease by 2 to 4 times 1,6
• For stroke by 2 to 4 times 1
• Of men developing lung cancer by 25 times 1
• Of women developing lung cancer by 25.7 times 1
• Smoking causes diminished overall health, increased absenteeism from work, and increased health care utilization and cost. 1

Smokers are at greater risk for diseases that affect the heart and blood vessels (cardiovascular disease). 1,2

• Smoking causes stroke and coronary heart disease, which are among the leading causes of death in the United States. 1,3
• Even people who smoke fewer than five cigarettes a day can have early signs of cardiovascular disease. 1
• Smoking damages blood vessels and can make them thicken and grow narrower. This makes your heart beat faster and your blood pressure go up. Clots can also form. 1,2
• A clot blocks the blood flow to part of your brain;
• A blood vessel in or around your brain bursts. 1,2
• Blockages caused by smoking can also reduce blood flow to your legs and skin. 1,2

Smoking can cause lung disease by damaging your airways and the small air sacs (alveoli) found in your lungs. 1,2

• Lung diseases caused by smoking include COPD, which includes emphysema and chronic bronchitis. 1,2
• Cigarette smoking causes most cases of lung cancer. 1,2
• If you have asthma, tobacco smoke can trigger an attack or make an attack worse. 1,2
• Smokers are 12 to 13 times more likely to die from COPD than nonsmokers. 1

Smoking can cause cancer almost anywhere in your body: 1,2

• Blood (acute myeloid leukemia)
• Colon and rectum (colorectal)
• Kidney and ureter
• Oropharynx (includes parts of the throat, tongue, soft palate, and the tonsils)
• Trachea, bronchus, and lung

Smoking also increases the risk of dying from cancer and other diseases in cancer patients and survivors. 1

If nobody smoked, one of every three cancer deaths in the United States would not happen. 1,2

Smoking harms nearly every organ of the body and affects a person’s overall health. 1,2

• Preterm (early) delivery
• Stillbirth (death of the baby before birth)
• Low birth weight
• Sudden infant death syndrome (known as SIDS or crib death)
• Ectopic pregnancy
• Orofacial clefts in infants
• Smoking can also affect men’s sperm, which can reduce fertility and also increase risks for birth defects and miscarriage. 2
• Women past childbearing years who smoke have weaker bones than women who never smoked. They are also at greater risk for broken bones.
• Smoking affects the health of your teeth and gums and can cause tooth loss. 1
• Smoking can increase your risk for cataracts (clouding of the eye’s lens that makes it hard for you to see). It can also cause age-related macular degeneration (AMD). AMD is damage to a small spot near the center of the retina, the part of the eye needed for central vision. 1
• Smoking is a cause of type 2 diabetes mellitus and can make it harder to control. The risk of developing diabetes is 30–40% higher for active smokers than nonsmokers. 1,2
• Smoking causes general adverse effects on the body, including inflammation and decreased immune function. 1
• Smoking is a cause of rheumatoid arthritis. 1
• Quitting smoking is one of the most important actions people can take to improve their health. This is true regardless of their age or how long they have been smoking. Visit the Benefits of Quitting  page for more information about how quitting smoking can improve your health.
• U.S. Department of Health and Human Services. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General . Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2014 [accessed 2017 Apr 20].
• U.S. Department of Health and Human Services. How Tobacco Smoke Causes Disease: What It Means to You . Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2010 [accessed 2017 Apr 20].
• Centers for Disease Control and Prevention. QuickStats: Number of Deaths from 10 Leading Causes—National Vital Statistics System, United States, 2010 . Morbidity and Mortality Weekly Report 2013:62(08);155. [accessed 2017 Apr 20].
• Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual Causes of Death in the United States . JAMA: Journal of the American Medical Association 2004;291(10):1238–45 [cited 2017 Apr 20].
• U.S. Department of Health and Human Services. Women and Smoking: A Report of the Surgeon General . Rockville (MD): U.S. Department of Health and Human Services, Public Health Service, Office of the Surgeon General, 2001 [accessed 2017 Apr 20].
• U.S. Department of Health and Human Services. Reducing the Health Consequences of Smoking: 25 Years of Progress. A Report of the Surgeon General . Rockville (MD): U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 1989 [accessed 2017 Apr 20].

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• Open access
• Published: 10 October 2022

Health effects associated with smoking: a Burden of Proof study

• Xiaochen Dai   ORCID: orcid.org/0000-0002-0289-7814 1 , 2 ,
• Gabriela F. Gil 1 ,
• Marissa B. Reitsma 1 ,
• Noah S. Ahmad 1 ,
• Jason A. Anderson 1 ,
• Catherine Bisignano 1 ,
• Sinclair Carr 1 ,
• Rachel Feldman 1 ,
• Simon I. Hay   ORCID: orcid.org/0000-0002-0611-7272 1 , 2 ,
• Jiawei He 1 , 2 ,
• Vincent Iannucci 1 ,
• Hilary R. Lawlor 1 ,
• Matthew J. Malloy 1 ,
• Laurie B. Marczak 1 ,
• Susan A. McLaughlin 1 ,
• Larissa Morikawa   ORCID: orcid.org/0000-0001-9749-8033 1 ,
• Erin C. Mullany 1 ,
• Sneha I. Nicholson 1 ,
• Erin M. O’Connell 1 ,
• Chukwuma Okereke 1 ,
• Reed J. D. Sorensen 1 ,
• Joanna Whisnant 1 ,
• Aleksandr Y. Aravkin 1 , 3 ,
• Peng Zheng 1 , 2 ,
• Christopher J. L. Murray   ORCID: orcid.org/0000-0002-4930-9450 1 , 2 &
• Emmanuela Gakidou   ORCID: orcid.org/0000-0002-8992-591X 1 , 2  

Nature Medicine volume  28 ,  pages 2045–2055 ( 2022 ) Cite this article

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• Risk factors

Matters Arising to this article was published on 14 April 2023

As a leading behavioral risk factor for numerous health outcomes, smoking is a major ongoing public health challenge. Although evidence on the health effects of smoking has been widely reported, few attempts have evaluated the dose–response relationship between smoking and a diverse range of health outcomes systematically and comprehensively. In the present study, we re-estimated the dose–response relationships between current smoking and 36 health outcomes by conducting systematic reviews up to 31 May 2022, employing a meta-analytic method that incorporates between-study heterogeneity into estimates of uncertainty. Among the 36 selected outcomes, 8 had strong-to-very-strong evidence of an association with smoking, 21 had weak-to-moderate evidence of association and 7 had no evidence of association. By overcoming many of the limitations of traditional meta-analyses, our approach provides comprehensive, up-to-date and easy-to-use estimates of the evidence on the health effects of smoking. These estimates provide important information for tobacco control advocates, policy makers, researchers, physicians, smokers and the public.

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Among both the public and the health experts, smoking is recognized as a major behavioral risk factor with a leading attributable health burden worldwide. The health risks of smoking were clearly outlined in a canonical study of disease rates (including lung cancer) and smoking habits in British doctors in 1950 and have been further elaborated in detail over the following seven decades 1 , 2 . In 2005, evidence of the health consequences of smoking galvanized the adoption of the first World Health Organization (WHO) treaty, the Framework Convention on Tobacco Control, in an attempt to drive reductions in global tobacco use and second-hand smoke exposure 3 . However, as of 2020, an estimated 1.18 billion individuals globally were current smokers and 7 million deaths and 177 million disability-adjusted life-years were attributed to smoking, reflecting a persistent public health challenge 4 . Quantifying the relationship between smoking and various important health outcomes—in particular, highlighting any significant dose–response relationships—is crucial to understanding the attributable health risk experienced by these individuals and informing responsive public policy.

Existing literature on the relationship between smoking and specific health outcomes is prolific, including meta-analyses, cohort studies and case–control studies analyzing the risk of outcomes such as lung cancer 5 , 6 , 7 , chronic obstructive pulmonary disease (COPD) 8 , 9 , 10 and ischemic heart disease 11 , 12 , 13 , 14 due to smoking. There are few if any attempts, however, to systematically and comprehensively evaluate the landscape of evidence on smoking risk across a diverse range of health outcomes, with most current research focusing on risk or attributable burden of smoking for a specific condition 7 , 15 , thereby missing the opportunity to provide a comprehensive picture of the health risk experienced by smokers. Furthermore, although evidence surrounding specific health outcomes, such as lung cancer, has generated widespread consensus, findings about the attributable risk of other outcomes are much more heterogeneous and inconclusive 16 , 17 , 18 . These studies also vary in their risk definitions, with many comparing dichotomous exposure measures of ever smokers versus nonsmokers 19 , 20 . Others examine the distinct risks of current smokers and former smokers compared with never smokers 21 , 22 , 23 . Among the studies that do analyze dose–response relationships, there is large variation in the units and dose categories used in reporting their findings (for example, the use of pack-years or cigarettes per day) 24 , 25 , which complicates the comparability and consolidation of evidence. This, in turn, can obscure data that could inform personal health choices, public health practices and policy measures. Guidance on the health risks of smoking, such as the Surgeon General’s Reports on smoking 26 , 27 , is often based on experts’ evaluation of heterogenous evidence, which, although extremely useful and well suited to carefully consider nuances in the evidence, is fundamentally subjective.

The present study, as part of the Global Burden of Diseases, Risk Factors, and Injuries Study (GBD) 2020, re-estimated the continuous dose–response relationships (the mean risk functions and associated uncertainty estimates) between current smoking and 36 health outcomes (Supplementary Table 1 ) by identifying input studies using a systematic review approach and employing a meta-analytic method 28 . The 36 health outcomes that were selected based on existing evidence of a relationship included 16 cancers (lung cancer, esophageal cancer, stomach cancer, leukemia, liver cancer, laryngeal cancer, breast cancer, cervical cancer, colorectal cancer, lip and oral cavity cancer, nasopharyngeal cancer, other pharynx cancer (excluding nasopharynx cancer), pancreatic cancer, bladder cancer, kidney cancer and prostate cancer), 5 cardiovascular diseases (CVDs: ischemic heart disease, stroke, atrial fibrillation and flutter, aortic aneurysm and peripheral artery disease) and 15 other diseases (COPD, lower respiratory tract infections, tuberculosis, asthma, type 2 diabetes, Alzheimer’s disease and related dementias, Parkinson’s disease, multiple sclerosis, cataracts, gallbladder diseases, low back pain, peptic ulcer disease, rheumatoid arthritis, macular degeneration and fractures). Definitions of the outcomes are described in Supplementary Table 1 . We conducted a separate systematic review for each risk–outcome pair with the exception of cancers, which were done together in a single systematic review. This approach allowed us to systematically identify all relevant studies indexed in PubMed up to 31 May 2022, and we extracted relevant data on risk of smoking, including study characteristics, following a pre-specified template (Supplementary Table 2 ). The meta-analytic tool overcomes many of the limitations of traditional meta-analyses by incorporating between-study heterogeneity into the uncertainty of risk estimates, accounting for small numbers of studies, relaxing the assumption of log(linearity) applied to the risk functions, handling differences in exposure ranges between comparison groups, and systematically testing and adjusting for bias due to study designs and characteristics. We then estimated the burden-of-proof risk function (BPRF) for each risk–outcome pair, as proposed by Zheng et al. 29 ; the BPRF is a conservative risk function defined as the 5th quantile curve (for harmful risks) that reflects the smallest harmful effect at each level of exposure consistent with the available evidence. Given all available data for each outcome, the risk of smoking is at least as harmful as the BPRF indicates.

We used the BPRF for each risk–outcome pair to calculate risk–outcome scores (ROSs) and categorize the strength of evidence for the association between smoking and each health outcome using a star rating from 1 to 5. The interpretation of the star ratings is as follows: 1 star (*) indicates no evidence of association; 2 stars (**) correspond to a 0–15% increase in risk across average range of exposures for harmful risks; 3 stars (***) represent a 15–50% increase in risk; 4 stars (****) refer to >50–85% increase in risk; and 5 stars (*****) equal >85% increase in risk. The thresholds for each star rating were developed in consultation with collaborators and other stakeholders.

The increasing disease burden attributable to current smoking, particularly in low- and middle-income countries 4 , demonstrates the relevance of the present study, which quantifies the strength of the evidence using an objective, quantitative, comprehensive and comparative framework. Findings from the present study can be used to support policy makers in making informed smoking recommendations and regulations focusing on the associations for which the evidence is strongest (that is, the 4- and 5-star associations). However, associations with a lower star rating cannot be ignored, especially when the outcome has high prevalence or severity. A summary of the main findings, limitations and policy implications of the study is presented in Table 1 .

We evaluated the mean risk functions and the BPRFs for 36 health outcomes that are associated with current smoking 30 (Table 2 ). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines 31 for each of our systematic reviews, we identified studies reporting relative risk (RR) of incidence or mortality from each of the 36 selected outcomes for smokers compared with nonsmokers. We reviewed 21,108 records, which were identified to have been published between 1 May 2018 and 31 May 2022; this represents the most recent time period since the last systematic review of the available evidence for the GBD at the time of publication. The meta-analyses reported in the present study for each of the 36 health outcomes are based on evidence from a total of 793 studies published between 1970 and 2022 (Extended Data Fig. 1 – 5 and Supplementary Information 1.5 show the PRISMA diagrams for each outcome). Only prospective cohort and case–control studies were included for estimating dose–response risk curves, but cross-sectional studies were also included for estimating the age pattern of smoking risk on cardiovascular and circulatory disease (CVD) outcomes. Details on each, including the study’s design, data sources, number of participants, length of follow-up, confounders adjusted for in the input data and bias covariates included in the dose–response risk model, can be found in Supplementary Information 2 and 3 . The theoretical minimum risk exposure level used for current smoking was never smoking or zero 30 .

Five-star associations

When the most conservative interpretation of the evidence, that is, the BPRF, suggests that the average exposure (15th–85th percentiles of exposure) of smoking increases the risk of a health outcome by >85% (that is, ROS > 0.62), smoking and that outcome are categorized as a 5-star pair. Among the 36 outcomes, there are 5 that have a 5-star association with current smoking: laryngeal cancer (375% increase in risk based on the BPRF, 1.56 ROS), aortic aneurysm (150%, 0.92), peripheral artery disease (137%, 0.86), lung cancer (107%, 0.73) and other pharynx cancer (excluding nasopharynx cancer) (92%, 0.65).

Results for all 5-star risk–outcome pairs are available in Table 2 and Supplementary Information 4.1 . In the present study, we provide detailed results for one example 5-star association: current smoking and lung cancer. We extracted 371 observations from 25 prospective cohort studies and 53 case–control studies across 25 locations (Supplementary Table 3 ) 5 , 6 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 . Exposure ranged from 1 pack-year to >112 pack-years, with the 85th percentile of exposure being 50.88 pack-years (Fig. 1a ).

a , The log(RR) function. b , RR function. c , A modified funnel plot showing the residuals (relative to 0) on the x axis and the estimated s.d. that includes reported s.d. and between-study heterogeneity on the y axis.

We found a very strong and significant harmful relationship between pack-years of current smoking and the RR of lung cancer (Fig. 1b ). The mean RR of lung cancer at 20 pack-years of smoking was 5.11 (95% uncertainty interval (UI) inclusive of between-study heterogeneity = 1.84–14.99). At 50.88 pack-years (85th percentile of exposure), the mean RR of lung cancer was 13.42 (2.63–74.59). See Table 2 for mean RRs at other exposure levels. The BPRF, which represents the most conservative interpretation of the evidence (Fig. 1a ), suggests that smoking in the 15th–85th percentiles of exposure increases the risk of lung cancer by an average of 107%, yielding an ROS of 0.73.

The relationship between pack-years of current smoking and RR of lung cancer is nonlinear, with diminishing impact of further pack-years of smoking, particularly for middle-to-high exposure levels (Fig. 1b ). To reduce the effect of bias, we adjusted observations that did not account for more than five confounders, including age and sex, because they were the significant bias covariates identified by the bias covariate selection algorithm 29 (Supplementary Table 7 ). The reported RRs across studies were very heterogeneous. Our meta-analytic method, which accounts for the reported uncertainty in both the data and between-study heterogeneity, fit the data and covered the estimated residuals well (Fig. 1c ). After trimming 10% of outliers, we still detected publication bias in the results for lung cancer. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for observed RR data and alternative exposures across studies for the remaining 5-star pairs.

Four-star associations

When the BPRF suggests that the average exposure of smoking increases the risk of a health outcome by 50–85% (that is, ROS > 0.41–0.62), smoking is categorized as having a 4-star association with that outcome. We identified three outcomes with a 4-star association with smoking: COPD (72% increase in risk based on the BPRF, 0.54 ROS), lower respiratory tract infection (54%, 0.43) and pancreatic cancer (52%, 0.42).

In the present study, we provide detailed results for one example 4-star association: current smoking and COPD. We extracted 51 observations from 11 prospective cohort studies and 4 case–control studies across 36 locations (Supplementary Table 3 ) 6 , 8 , 9 , 10 , 78 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 . Exposure ranged from 1 pack-year to 100 pack-years, with the 85th percentile of exposure in the exposed group being 49.75 pack-years.

We found a strong and significant harmful relationship between pack-years of current smoking and RR of COPD (Fig. 2b ). The mean RR of COPD at 20 pack-years was 3.17 (1.60–6.55; Table 2 reports RRs at other exposure levels). At the 85th percentile of exposure, the mean RR of COPD was 6.01 (2.08–18.58). The BPRF suggests that average smoking exposure raises the risk of COPD by an average of 72%, yielding an ROS of 0.54. The results for the other health outcomes that have an association with smoking rated as 4 stars are shown in Table 2 and Supplementary Information 4.2 .

a , The log(RR) function. b , RR function. c , A modified funnel plot showing the residuals (relative to 0) on th e x axis and the estimated s.d. that includes the reported s.d. and between-study heterogeneity on the y axis.

The relationship between smoking and COPD is nonlinear, with diminishing impact of further pack-years of current smoking on risk of COPD, particularly for middle-to-high exposure levels (Fig. 2a ). To reduce the effect of bias, we adjusted observations that did not account for age and sex and/or were generated for individuals aged >65 years 116 , because they were the two significant bias covariates identified by the bias covariate selection algorithm (Supplementary Table 7 ). There was large heterogeneity in the reported RRs across studies, and our meta-analytic method fit the data and covered the estimated residuals well (Fig. 2b ). Although we trimmed 10% of outliers, publication bias was still detected in the results for COPD. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for reported RR data and alternative exposures across studies for the remaining health outcomes that have a 4-star association with smoking.

Three-star associations

When the BPRF suggests that the average exposure of smoking increases the risk of a health outcome by 15–50% (or, when protective, decreases the risk of an outcome by 13–34%; that is, ROS >0.14–0.41), the association between smoking and that outcome is categorized as having a 3-star rating. We identified 15 outcomes with a 3-star association: bladder cancer (40% increase in risk, 0.34 ROS); tuberculosis (31%, 0.27); esophageal cancer (29%, 0.26); cervical cancer, multiple sclerosis and rheumatoid arthritis (each 23–24%, 0.21); lower back pain (22%, 0.20); ischemic heart disease (20%, 0.19); peptic ulcer and macular degeneration (each 19–20%, 0.18); Parkinson's disease (protective risk, 15% decrease in risk, 0.16); and stomach cancer, stroke, type 2 diabetes and cataracts (each 15–17%, 0.14–0.16).

We present the findings on smoking and type 2 diabetes as an example of a 3-star risk association. We extracted 102 observations from 24 prospective cohort studies and 4 case–control studies across 15 locations (Supplementary Table 3 ) 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 . The exposure ranged from 1 cigarette to 60 cigarettes smoked per day, with the 85th percentile of exposure in the exposed group being 26.25 cigarettes smoked per day.

We found a moderate and significant harmful relationship between cigarettes smoked per day and the RR of type 2 diabetes (Fig. 3b ). The mean RR of type 2 diabetes at 20 cigarettes smoked per day was 1.49 (1.18–1.90; see Table 2 for other exposure levels). At the 85th percentile of exposure, the mean RR of type 2 diabetes was 1.54 (1.20–2.01). The BPRF suggests that average smoking exposure raises the risk of type 2 diabetes by an average of 16%, yielding an ROS of 0.15. See Table 2 and Supplementary Information 4.3 for results for the additional health outcomes with an association with smoking rated as 3 stars.

a , The log(RR) function. b , RR function. c , A modified funnel plot showing the residuals (relative to 0) on the x axis and the estimated s.d. that includes the reported s.d. and between-study heterogeneity on the y axis.

The relationship between smoking and type 2 diabetes is nonlinear, particularly for high exposure levels where the mean risk curve becomes flat (Fig. 3a ). We adjusted observations that were generated in subpopulations, because it was the only significant bias covariate identified by the bias covariate selection algorithm (Supplementary Table 7 ). There was moderate heterogeneity in the observed RR data across studies and our meta-analytic method fit the data and covered the estimated residuals extremely well (Fig. 3b,c ). After trimming 10% of outliers, we still detected publication bias in the results for type 2 diabetes. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for observed RR data and alternative exposures across studies for the remaining 3-star pairs.

Two-star associations

When the BPRF suggests that the average exposure of smoking increases the risk of an outcome by 0–15% (that is, ROS 0.0–0.14), the association between smoking and that outcome is categorized as a 2-star rating. We identified six 2-star outcomes: nasopharyngeal cancer (14% increase in risk, 0.13 ROS); Alzheimer’s and other dementia (10%, 0.09); gallbladder diseases and atrial fibrillation and flutter (each 6%, 0.06); lip and oral cavity cancer (5%, 0.05); and breast cancer (4%, 0.04).

We present the findings on smoking and breast cancer as an example of a 2-star association. We extracted 93 observations from 14 prospective cohort studies and 9 case–control studies across 14 locations (Supplementary Table 3 ) 84 , 87 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 . The exposure ranged from 1 cigarette to >76 cigarettes smoked per day, with the 85th percentile of exposure in the exposed group being 34.10 cigarettes smoked per day.

We found a weak but significant relationship between pack-years of current smoking and RR of breast cancer (Extended Data Fig. 6 ). The mean RR of breast cancer at 20 pack-years was 1.17 (1.04–1.31; Table 2 reports other exposure levels). The BPRF suggests that average smoking exposure raises the risk of breast cancer by an average of 4%, yielding an ROS of 0.04. See Table 2 and Supplementary Information 4.4 for results on the additional health outcomes for which the association with smoking has been categorized as 2 stars.

The relationship between smoking and breast cancer is nonlinear, particularly for high exposure levels where the mean risk curve becomes flat (Extended Data Fig. 6a ). To reduce the effect of bias, we adjusted observations that were generated in subpopulations, because it was the only significant bias covariate identified by the bias covariate selection algorithm (Supplementary Table 7 ). There was heterogeneity in the reported RRs across studies, but our meta-analytic method fit the data and covered the estimated residuals (Extended Data Fig. 6b ). After trimming 10% of outliers, we did not detect publication bias in the results for breast cancer. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for observed RR data and alternative exposures across studies for the remaining 2-star pairs.

One-star associations

When average exposure to smoking does not significantly increase (or decrease) the risk of an outcome, once between-study heterogeneity and other sources of uncertainty are accounted for (that is, ROS < 0), the association between smoking and that outcome is categorized as 1 star, indicating that there is not sufficient evidence for the effect of smoking on the outcome to reject the null (that is, there may be no association). There were seven outcomes with an association with smoking that rated as 1 star: colorectal and kidney cancer (each –0.01 ROS); leukemia (−0.04); fractures (−0.05); prostate cancer (−0.06); liver cancer (−0.32); and asthma (−0.64).

We use smoking and prostate cancer as examples of a 1-star association. We extracted 78 observations from 21 prospective cohort studies and 1 nested case–control study across 15 locations (Supplementary Table 3 ) 157 , 160 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 . The exposure among the exposed group ranged from 1 cigarette to 90 cigarettes smoked per day, with the 85th percentile of exposure in the exposed group being 29.73 cigarettes smoked per day.

Based on our conservative interpretation of the data, we did not find a significant relationship between cigarettes smoked per day and the RR of prostate cancer (Fig. 4B ). The exposure-averaged BPRF for prostate cancer was 0.94, which was opposite null from the full range of mean RRs, such as 1.16 (0.89–1.53) at 20 cigarettes smoked per day. The corresponding ROS was −0.06, which is consistent with no evidence of an association between smoking and increased risk of prostate cancer. See Table 2 and Supplementary Information 4.5 for results for the additional outcomes that have a 1-star association with smoking.

The relationship between smoking and prostate cancer is nonlinear, particularly for middle-to-high exposure levels where the mean risk curve becomes flat (Fig. 4a ). We did not adjust for any bias covariate because no significant bias covariates were selected by the algorithm (Supplementary Table 7 ). The RRs reported across studies were very heterogeneous, but our meta-analytic method fit the data and covered the estimated residuals well (Fig. 4b,c ). The ROS associated with the BPRF is −0.05, suggesting that the most conservative interpretation of all evidence, after accounting for between-study heterogeneity, indicates an inconclusive relationship between smoking exposure and the risk of prostate cancer. After trimming 10% of outliers, we still detected publication bias in the results for prostate cancer, which warrants further studies using sample populations. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for observed RR data and alternative exposures across studies for the remaining 1-star pairs.

Age-specific dose–response risk for CVD outcomes

We produced age-specific dose–response risk curves for the five selected CVD outcomes ( Methods ). The ROS associated with each smoking–CVD pair was calculated based on the reference risk curve estimated using all risk data regardless of age information. Estimation of the BPRF, calculation of the associated ROS and star rating of the smoking–CVD pairs follow the same rules as the other non-CVD smoking–outcome pairs (Table 1 and Supplementary Figs. 2 – 4 ). Once we had estimated the reference dose–response risk curve for each CVD outcome, we determined the age group of the reference risk curve. The reference age group is 55–59 years for all CVD outcomes, except for peripheral artery disease, the reference age group for which is 60–64 years. We then estimated the age pattern of smoking on all CVD outcomes (Supplementary Fig. 2 ) and calculated age attenuation factors of the risk for each age group by comparing the risk of each age group with that of the reference age group, using the estimated age pattern (Supplementary Fig. 3 ). Last, we applied the draws of age attenuation factors of each age group to the dose–response risk curve for the reference age group to produce the age group-specific dose–response risk curves for each CVD outcome (Supplementary Fig. 4 ).

Using our burden-of-proof meta-analytic methods, we re-estimated the dose–response risk of smoking on 36 health outcomes that had previously been demonstrated to be associated with smoking 30 , 186 . Using these methods, which account for both the reported uncertainty of the data and the between-study heterogeneity, we found that 29 of the 36 smoking–outcome pairs are supported by evidence that suggests a significant dose–response relationship between smoking and the given outcome (28 with a harmful association and 1 with a protective association). Conversely, after accounting for between-study heterogeneity, the available evidence of smoking risk on seven outcomes (that is, colon and rectum cancer, kidney cancer, leukemia, prostate cancer, fractures, liver cancer and asthma) was insufficient to reject the null or draw definitive conclusions on their relationship to smoking. Among the 29 outcomes that have evidence supporting a significant relationship to smoking, 8 had strong-to-very-strong evidence of a relationship, meaning that, given all the available data on smoking risk, we estimate that average exposure to smoking increases the risk of those outcomes by >50% (4- and 5-star outcomes). The currently available evidence for the remaining 21 outcomes with a significant association with current smoking was weak to moderate, indicating that smoking increases the risk of those outcomes by at least >0–50% (2- and 3-star associations).

Even under our conservative interpretation of the data, smoking is irrefutably harmful to human health, with the greatest increases in risk occurring for laryngeal cancer, aortic aneurysm, peripheral artery disease, lung cancer and other pharynx cancer (excluding nasopharynx cancer), which collectively represent large causes of death and ill-health. The magnitude of and evidence for the associations between smoking and its leading health outcomes are among the highest currently analyzed in the burden-of-proof framework 29 . The star ratings assigned to each smoking–outcome pair offer policy makers a way of categorizing and comparing the evidence for a relationship between smoking and its potential health outcomes ( https://vizhub.healthdata.org/burden-of-proof ). We found that, for seven outcomes in our analysis, there was insufficient or inconsistent evidence to demonstrate a significant association with smoking. This is a key finding because it demonstrates the need for more high-quality data for these particular outcomes; availability of more data should improve the strength of evidence for whether or not there is an association between smoking and these health outcomes.

Our systematic review approach and meta-analytic methods have numerous benefits over existing systematic reviews and meta-analyses on the same topic that use traditional random effects models. First, our approach relaxes the log(linear) assumption, using a spline ensemble to estimate the risk 29 . Second, our approach allows variable reference groups and exposure ranges, allowing for more accurate estimates regardless of whether or not the underlying relative risk is log(linear). Furthermore, it can detect outliers in the data automatically. Finally, it quantifies uncertainty due to between-study heterogeneity while accounting for small numbers of studies, minimizing the risk that conclusions will be drawn based on spurious findings.

We believe that the results for the association between smoking and each of the 36 health outcomes generated by the present study, including the mean risk function, BPRF, ROS, average excess risk and star rating, could be useful to a range of stakeholders. Policy makers can formulate their decisions on smoking control priorities and resource allocation based on the magnitude of the effect and the consistency of the evidence relating smoking to each of the 36 outcomes, as represented by the ROS and star rating for each smoking–outcome association 187 . Physicians and public health practitioners can use the estimates of average increased risk and the star rating to educate patients and the general public about the risk of smoking and to promote smoking cessation 188 . Researchers can use the estimated mean risk function or BPRF to obtain the risk of an outcome at a given smoking exposure level, as well as uncertainty surrounding that estimate of risk. The results can also be used in the estimation of risk-attributable burden, that is, the deaths and disability-adjusted life-years due to each outcome that are attributable to smoking 30 , 186 . For the general public, these results could help them to better understand the risk of smoking and manage their health 189 .

Although our meta-analysis was comprehensive and carefully conducted, there are limitations to acknowledge. First, the bias covariates used, although carefully extracted and evaluated, were based on observable study characteristics and thus may not fully capture unobserved characteristics such as study quality or context, which might be major sources of bias. Second, if multiple risk estimates with different adjustment levels were reported in a given study, we included only the fully adjusted risk estimate and modeled the adjustment level according to the number of covariates adjusted for (rather than which covariates were adjusted for) and whether a standard adjustment for age and sex had been applied. This approach limited our ability to make full use of all available risk estimates in the literature. Third, although we evaluated the potential for publication bias in the data, we did not test for other forms of bias such as when studies are more consistent with each other than expected by chance 29 . Fourth, our analysis assumes that the relationships between smoking and health outcomes are similar across geographical regions and over time. We do not have sufficient evidence to quantify how the relationships may have evolved over time because the composition of smoking products has also changed over time. Perhaps some of the heterogeneity of the effect sizes in published studies reflects this; however, this cannot be discerned with the currently available information.

In the future, we plan to include crude and partially adjusted risk estimates in our analyses to fully incorporate all available risk estimates, to model the adjusted covariates in a more comprehensive way by mapping the adjusted covariates across all studies comprehensively and systematically, and to develop methods to evaluate additional forms of potential bias. We plan to update our results on a regular basis to provide timely and up-to-date evidence to stakeholders.

To conclude, we have re-estimated the dose–response risk of smoking on 36 health outcomes while synthesizing all the available evidence up to 31 May 2022. We found that, even after factoring in the heterogeneity between studies and other sources of uncertainty, smoking has a strong-to-very-strong association with a range of health outcomes and confirmed that smoking is irrefutably highly harmful to human health. We found that, due to small numbers of studies, inconsistency in the data, small effect sizes or a combination of these reasons, seven outcomes for which some previous research had found an association with smoking did not—under our meta-analytic framework and conservative approach to interpreting the data—have evidence of an association. Our estimates of the evidence for risk of smoking on 36 selected health outcomes have the potential to inform the many stakeholders of smoking control, including policy makers, researchers, public health professionals, physicians, smokers and the general public.

For the present study, we used a meta-analytic tool, MR-BRT (metaregression—Bayesian, regularized, trimmed), to estimate the dose–response risk curves of the risk of a health outcome across the range of current smoking levels along with uncertainty estimates 28 . Compared with traditional meta-analysis using linear mixed effect models, MR-BRT relaxes the assumption of a log(linear) relationship between exposure and risk, incorporates between-study heterogeneity into the uncertainty of risk estimates, handles estimates reported across different exposure categories, automatically identifies and trims outliers, and systematically tests and adjusts for bias due to study designs and characteristics. The meta-analytic methods employed by the present study followed the six main steps proposed by Zheng et al. 28 , 29 , namely: (1) enacting a systematic review approach and data extraction following a pre-specified and standardized protocol; (2) estimating the shape of the relationship between exposure and RR; (3) evaluating and adjusting for systematic bias as a function of study characteristics and risk estimation; (4) quantifying between-study heterogeneity while adjusting for within-study correlation and the number of studies; (5) evaluating potential publication or reporting biases; and (6) estimating the mean risk function and the BPRF, calculating the ROS and categorizing smoking–outcome pairs using a star-rating scheme from 1 to 5.

The estimates for our primary indicators of this work—mean RRs across a range of exposures, BRPFs, ROSs and star ratings for each risk–outcome pair—are not specific to or disaggregated by specific populations. We did not estimate RRs separately for different locations, sexes (although the RR of prostate cancer was estimated only for males and of cervical and breast cancer only for females) or age groups (although this analysis was applied to disease endpoints in adults aged ≥30 years only and, as detailed below, age-specific estimates were produced for the five CVD outcomes).

The present study complies with the PRISMA guidelines 190 (Supplementary Tables 9 and 10 and Supplementary Information 1.5 ) and Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) recommendations 191 (Supplementary Table 11 ). The study was approved by the University of Washington Institutional Review Board (study no. 9060). The systematic review approach was not registered.

Selecting health outcomes

In the present study, current smoking is defined as the current use of any smoked tobacco product on a daily or occasional basis. Health outcomes were initially selected using the World Cancer Research Fund criteria for convincing or probable evidence as described in Murray et al. 186 . The 36 health outcomes that were selected based on existing evidence of a relationship included 16 cancers (lung cancer, esophageal cancer, stomach cancer, leukemia, liver cancer, laryngeal cancer, breast cancer, cervical cancer, colorectal cancer, lip and oral cavity cancer, nasopharyngeal cancer, other pharynx cancer (excluding nasopharynx cancer), pancreatic cancer, bladder cancer, kidney cancer and prostate cancer), 5 CVDs (ischemic heart disease, stroke, atrial fibrillation and flutter, aortic aneurysm and peripheral artery disease) and 15 other diseases (COPD, lower respiratory tract infections, tuberculosis, asthma, type 2 diabetes, Alzheimer’s disease and related dementias, Parkinson’s disease, multiple sclerosis, cataracts, gallbladder diseases, low back pain, peptic ulcer disease, rheumatoid arthritis, macular degeneration and fracture). Definitions of the outcomes are described in Supplementary Table 1 .

Step 1: systematic review approach to literature search and data extraction

Informed by the systematic review approach we took for the GBD 2019 (ref. 30 ), for the present study we identified input studies in the literature using a systematic review approach for all 36 smoking–outcome pairs using updated search strings to identify all relevant studies indexed in PubMed up to 31 May 2022 and extracted data on smoking risk estimates. Briefly, the studies that were extracted represented several types of study design (for example, cohort and case–control studies), measured exposure in several different ways and varied in their choice of reference categories (where some compared current smokers with never smokers, whereas others compared current smokers with nonsmokers or former smokers). All these study characteristics were catalogued systematically and taken into consideration during the modeling part of the analysis.

In addition, for CVD outcomes, we also estimated the age pattern of risk associated with smoking. We applied a systematic review of literature approach for smoking risk for the five CVD outcomes. We developed a search string to search for studies reporting any association between binary smoking status (that is, current, former and ever smokers) and the five CVD outcomes from 1 January 1970 to 31 May 2022, and included only studies reporting age-specific risk (RR, odds ratio (OR), hazard ratio (HR)) of smoking status. The inclusion criteria and results of the systematic review approach are reported in accordance with PRISMA guidelines 31 . Details for each outcome on the search string used in the systematic review approach, refined inclusion and exclusion criteria, data extraction template and PRISMA diagram are given in Supplementary Information 1 . Title and/or abstract screening, full text screening and data extraction were conducted by 14 members of the research team and extracted data underwent manual quality assurance by the research team to verify accuracy.

Selecting exposure categories

Cumulative exposure in pack-years was the measure of exposure used for COPD and all cancer outcomes except for prostate cancer, to reflect the risk of both duration and intensity of current smoking on these outcomes. For prostate cancer, CVDs and all the other outcomes except for fractures, we used cigarette-equivalents smoked per day as the exposure for current smoking, because smoking intensity is generally thought to be more important than duration for these outcomes. For fractures, we used binary exposure, because there were few studies examining intensity or duration of smoking on fractures. The smoking–outcome pairs and the corresponding exposures are summarized in Supplementary Table 4 and are congruent with the GBD 2019 (refs. 30 , 186 ).

Steps 2–5: modeling dose–response RR of smoking on the selected health outcomes

Of the six steps proposed by Zheng et al. 29 , steps 2–5 cover the process of modeling dose–response risk curves. In step 2, we estimated the shape (or the ‘signal’) of the dose–response risk curves, integrating over different exposure ranges. To relax the log(linear) assumption usually applied to continuous dose–response risk and make the estimates robust to the placement of spline knots, we used an ensemble spline approach to fit the functional form of the dose–response relationship. The final ensemble model was a weighted combination of 50 models with random knot placement, with the weight of each model proportional to measures of model fit and total variation. To avoid the influence of extreme data and reduce publication bias, we trimmed 10% of data for each outcome as outliers. We also applied a monotonicity constraint to ensure that the mean risk curves were nondecreasing (or nonincreasing in the case of Parkinson’s disease).

In step 3, following the GRADE approach 192 , 193 , we quantified risk of bias across six domains, namely, representativeness of the study population, exposure, outcome, reverse causation, control for confounding and selection bias. Details about the bias covariates are provided in Supplementary Table 4 . We systematically tested for the effect of bias covariates using metaregression, selected significant bias covariates using the Lasso approach 194 , 195 and adjusted for the selected bias covariates in the final risk curve.

In step 4, we quantified between-study heterogeneity accounting for within-study correlation, uncertainty of the heterogeneity, as well as small number of studies. Specifically, we used a random intercept in the mixed-effects model to account for the within-study correlation and used a study-specific random slope with respect to the ‘signal’ to capture between-study heterogeneity. As between-study heterogeneity can be underestimated or even zero when the number of studies is small 196 , 197 , we used Fisher’s information matrix to estimate the uncertainty of the heterogeneity 198 and incorporated that uncertainty into the final results.

In step 5, in addition to generating funnel plots and visually inspecting for asymmetry (Figs. 1c , 2c , 3c and 4c and Extended Data Fig. 6c ) to identify potential publication bias, we also statistically tested for potential publication or reporting bias using Egger’s regression 199 . We flagged potential publication bias in the data but did not correct for it, which is in line with the general literature 10 , 200 , 201 . Full details about the modeling process have been published elsewhere 29 and model specifications for each outcome are in Supplementary Table 6 .

Step 6: estimating the mean risk function and the BPRF

In the final step, step 6, the metaregression model inclusive of the selected bias covariates from step 3 (for example, the highest adjustment level) was used to predict the mean risk function and its 95% UI, which incorporated the uncertainty of the mean effect, between-study heterogeneity and the uncertainty in the heterogeneity estimate accounting for small numbers of studies. Specifically, 1,000 draws were created for each 0.1 level of doses from 0 pack-years to 100 pack-years or cigarette-equivalents smoked per day using the Bayesian metaregression model. The mean of the 1,000 draws was used to estimate the mean risk at each exposure level, and the 25th and 95th draws were used to estimate the 95% UIs for the mean risk at each exposure level.

The BPRF 29 is a conservative estimate of risk function consistent with the available evidence, correcting for both between-study heterogeneity and systemic biases related to study characteristics. The BPRF is defined as either the 5th (if harmful) or 95th (if protective) quantile curve closest to the line of log(RR) of 0, which defines the null (Figs. 1a , 2b , 3a and 4a ). The BPRF represents the smallest harmful (or protective) effect of smoking on the corresponding outcome at each level of exposure that is consistent with the available evidence. A BPRF opposite null from the mean risk function indicates that insufficient evidence is available to reject null, that is, that there may not be an association between risk and outcome. Likewise, the further the BPRF is from null on the same side of null as the mean risk function, the higher the magnitude and evidence for the relationship. The BPRF can be interpreted as indicating that, even accounting for between-study heterogeneity and its uncertainty, the log(RR) across the studied smoking range is at least as high as the BPRF (or at least as low as the BPRF for a protective risk).

To quantify the strength of the evidence, we calculated the ROS for each smoking–outcome association as the signed value of the log(BPRF) averaged between the 15th and 85th percentiles of observed exposure levels for each outcome. The ROS is a single summary of the effect of smoking on the outcome, with higher positive ROSs corresponding to stronger and more consistent evidence and a higher average effect size of smoking and a negative ROS, suggesting that, based on the available evidence, there is no significant effect of smoking on the outcome after accounting for between-study heterogeneity.

For ease of communication, we further classified each smoking–outcome association into a star rating from 1 to 5. Briefly, 1-star associations have an ROS <0, indicating that there is insufficient evidence to find a significant association between smoking and the selected outcome. We divided the positive ROSs into ranges 0.0–0.14 (2-star), >0.14–0.41 (3-star), >0.41–0.62 (4-star) and >0.62 (5-star). These categories correspond to excess risk ranges for harmful risks of 0–15%, >15–50%, >50–85% and >85%. For protective risks, the ranges of exposure-averaged decreases in risk by star rating are 0–13% (2 stars), >13–34% (3 stars), >34–46% (4 stars) and >46% (5 stars).

Among the 36 smoking–outcome pairs analyzed, smoking fracture was the only binary risk–outcome pair, which was due to limited data on the dose–response risk of smoking on fracture 202 . The estimation of binary risk was simplified because the RR was merely a comparison between current smokers and nonsmokers or never smokers. The concept of ROS for continuous risk can naturally extend to binary risk because the BPRF is still defined as the 5th percentile of the effect size accounting for data uncertainty and between-study heterogeneity. However, binary ROSs must be divided by 2 to make them comparable with continuous ROSs, which were calculated by averaging the risk over the range between the 15th and the 85th percentiles of observed exposure levels. Full details about estimating mean risk functions, BPRFs and ROSs for both continuous and binary risk–outcome pairs can be found elsewhere 29 .

Estimating the age-specific risk function for CVD outcomes

For non-CVD outcomes, we assumed that the risk function was the same for all ages and all sexes, except for breast, cervical and prostate cancer, which were assumed to apply only to females or males, respectively. As the risk of smoking on CVD outcomes is known to attenuate with increasing age 203 , 204 , 205 , 206 , we adopted a four-step approach for GBD 2020 to produce age-specific dose–response risk curves for CVD outcomes.

First, we estimated the reference dose–response risk of smoking for each CVD outcome using dose-specific RR data for each outcome regardless of the age group information. This step was identical to that implemented for the other non-CVD outcomes. Once we had generated the reference curve, we determined the age group associated with it by calculating the weighted mean age across all dose-specific RR data (weighted by the reciprocal of the s.e.m. of each datum). For example, if the weighted mean age of all dose-specific RR data was 56.5, we estimated the age group associated with the reference risk curve to be aged 55–59 years. For cohort studies, the age range associated with the RR estimate was calculated as a mean age at baseline plus the mean/median years of follow-up (if only the maximum years of follow-up were reported, we would halve this value and add it to the mean age at baseline). For case–control studies, the age range associated with the OR estimate was simply the reported mean age at baseline (if mean age was not reported, we used the midpoint of the age range instead).

In the third step, we extracted age group-specific RR data and relevant bias covariates from the studies identified in our systematic review approach of age-specific smoking risk on CVD outcomes, and used MR-BRT to model the age pattern of excess risk (that is, RR-1) of smoking on CVD outcomes with age group-specific excess RR data for all CVD outcomes. We modeled the age pattern of smoking risk on CVDs following the same steps we implemented for modeling dose–response risk curves. In the final model, we included a spline on age, random slope on age by study and the bias covariate encoding exposure definition (that is, current, former and ever smokers), which was picked by the variable selection algorithm 28 , 29 . When predicting the age pattern of the excess risk of smoking on CVD outcomes using the fitted model, we did not include between-study heterogeneity to reduce uncertainty in the prediction.

In the fourth step, we calculated the age attenuation factors of excess risk compared with the reference age group for each CVD outcome as the ratio of the estimated excess risk for each age group to the excess risk for the reference age group. We performed the calculation at the draw level to obtain 1,000 draws of the age attenuation factors for each age group. Once we had estimated the age attenuation factors, we carried out the last step, which consisted of adjusting the risk curve for the reference age group from step 1 using equation (1) to produce the age group-specific risk curves for each CVD outcome:

We implemented the age adjustment at the draw level so that the uncertainty of the age attenuation factors could be naturally incorporated into the final adjusted age-specific RR curves. A PRISMA diagram detailing the systematic review approach, a description of the studies included and the full details about the methods are in Supplementary Information 1.5 and 5.2 .

Estimating the theoretical minimum risk exposure level

The theoretical minimum risk exposure level for smoking was 0, that is, no individuals in the population are current or former smokers.

Model validation

The validity of the meta-analytic tool has been extensively evaluated by Zheng and colleagues using simulation experiments 28 , 29 . For the present study, we conducted two additional sensitivity analyses to examine how the shape of the risk curves was impacted by applying a monotonicity constraint and trimming 10% of data. We present the results of these sensitivity analyses in Supplementary Information 6 . In addition to the sensitivity analyses, the dose–response risk estimates were also validated by plotting the mean risk function along with its 95% UI against both the extracted dose-specific RR data from the studies included and our previous dose–response risk estimates from the GBD 2019 (ref. 30 ). The mean risk functions along with the 95% UIs were validated based on data fit and the level, shape and plausibility of the dose–response risk curves. All curves were validated by all authors and reviewed by an external expert panel, comprising professors with relevant experience from universities including Johns Hopkins University, Karolinska Institute and University of Barcelona; senior scientists working in relevant departments at the WHO and the Center for Disease Control and Prevention (CDC) and directors of nongovernmental organizations such as the Campaign for Tobacco-Free Kids.

Statistical analysis

Analyses were carried out using R v.3.6.3, Python v.3.8 and Stata v.16.

Statistics and reproducibility

The study was a secondary analysis of existing data involving systematic reviews and meta-analyses. No statistical method was used to predetermine sample size. As the study did not involve primary data collection, randomization and blinding, data exclusions were not relevant to the present study, and, as such, no data were excluded and we performed no randomization or blinding. We have made our data and code available to foster reproducibility.

Reporting summary

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

Data availability

The findings from the present study are supported by data available in the published literature. Data sources and citations for each risk–outcome pair can be downloaded using the ‘download’ button on each risk curve page currently available at https://vizhub.healthdata.org/burden-of-proof . Study characteristics and citations for all input data used in the analyses are also provided in Supplementary Table 3 , and Supplementary Table 2 provides a template of the data collection form.

Code availability

All code used for these analyses is publicly available online ( https://github.com/ihmeuw-msca/burden-of-proof ).

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Acknowledgements

Research reported in this publication was supported by the Bill & Melinda Gates Foundation and Bloomberg Philanthropies. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. The study funders had no role in study design, data collection, data analysis, data interpretation, writing of the final report or the decision to publish.

We thank the Tobacco Metrics Team Advisory Group for their valuable input and review of the work. The members of the Advisory Group are: P. Allebeck, R. Chandora, J. Drope, M. Eriksen, E. Fernández, H. Gouda, R. Kennedy, D. McGoldrick, L. Pan, K. Schotte, E. Sebrie, J. Soriano, M. Tynan and K. Welding.

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Xiaochen Dai, Gabriela F. Gil, Marissa B. Reitsma, Noah S. Ahmad, Jason A. Anderson, Catherine Bisignano, Sinclair Carr, Rachel Feldman, Simon I. Hay, Jiawei He, Vincent Iannucci, Hilary R. Lawlor, Matthew J. Malloy, Laurie B. Marczak, Susan A. McLaughlin, Larissa Morikawa, Erin C. Mullany, Sneha I. Nicholson, Erin M. O’Connell, Chukwuma Okereke, Reed J. D. Sorensen, Joanna Whisnant, Aleksandr Y. Aravkin, Peng Zheng, Christopher J. L. Murray & Emmanuela Gakidou

Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA

Xiaochen Dai, Simon I. Hay, Jiawei He, Peng Zheng, Christopher J. L. Murray & Emmanuela Gakidou

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Contributions

X.D., S.I.H., S.A.M., E.C.M., E.M.O., C.J.L.M. and E.G. managed the estimation or publications process. X.D. and G.F.G. wrote the first draft of the manuscript. X.D. and P.Z. had primary responsibility for applying analytical methods to produce estimates. X.D., G.F.G., N.S.A., J.A.A., S.C., R.F., V.I., M.J.M., L.M., S.I.N., C.O., M.B.R. and J.W. had primary responsibility for seeking, cataloguing, extracting or cleaning data, and for designing or coding figures and tables. X.D., G.F.G., M.B.R., N.S.A., H.R.L., C.O. and J.W. provided data or critical feedback on data sources. X.D., J.H., R.J.D.S., A.Y.A., P.Z., C.J.L.M. and E.G. developed methods or computational machinery. X.D., G.F.G., M.B.R., S.I.H., J.H., R.J.D.S., A.Y.A., P.Z., C.J.L.M. and E.G. provided critical feedback on methods or results. X.D., G.F.G., M.B.R., C.B., S.I.H., L.B.M., S.A.M., A.Y.A. and E.G. drafted the work or revised it critically for important intellectual content. X.D., S.I.H., L.B.M., E.C.M., E.M.O. and E.G. managed the overall research enterprise.

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Correspondence to Xiaochen Dai .

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Extended data

Extended data fig. 1 prisma 2020 flow diagram for an updated systematic review of the smoking and tracheal, bronchus, and lung cancer risk-outcome pair..

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and lung cancer conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 2 PRISMA 2020 flow diagram for an updated systematic review of the Smoking and Chronic obstructive pulmonary disease risk-outcome pair.

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and chronic obstructive pulmonary disease conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 3 PRISMA 2020 flow diagram for an updated systematic review of the Smoking and Diabetes mellitus type 2 risk- outcome pair.

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and type 2 diabetes conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 4 PRISMA 2020 flow diagram for an updated systematic review of the Smoking and Breast cancer risk-outcome pair.

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and breast cancer conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 5 PRISMA 2020 flow diagram for an updated systematic review of the Smoking and Prostate cancer risk-outcome pair.

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and prostate cancer conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 6 Smoking and Breast Cancer.

a , log-relative risk function. b , relative risk function. c , A modified funnel plot showing the residuals (relative to 0) on the x-axis and the estimated standard deviation (SD) that includes reported SD and between-study heterogeneity on the y-axis.

Supplementary information

Supplementary information.

Supplementary Information 1: Data source identification and assessment. Supplementary Information 2: Data inputs. Supplementary Information 3: Study quality and bias assessment. Supplementary Information 4: The dose–response RR curves and their 95% UIs for all smoking–outcome pairs. Supplementary Information 5: Supplementary methods. Supplementary Information 6: Sensitivity analysis. Supplementary Information 7: Binary smoking–outcome pair. Supplementary Information 8: Risk curve details. Supplementary Information 9: GATHER and PRISMA checklists.

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Dai, X., Gil, G.F., Reitsma, M.B. et al. Health effects associated with smoking: a Burden of Proof study. Nat Med 28 , 2045–2055 (2022). https://doi.org/10.1038/s41591-022-01978-x

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Essay on Negative Effects Of Smoking

Students are often asked to write an essay on Negative Effects Of Smoking in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Negative Effects Of Smoking

Introduction to smoking.

Smoking is a bad habit that harms our body. Many people smoke cigarettes, cigars, or pipes. Some people also chew tobacco. These things contain nicotine, a harmful chemical. It’s highly addictive, meaning once you start smoking, it’s very hard to stop.

Health Problems Caused by Smoking

Smoking can cause many health problems. It can lead to lung cancer, heart disease, and stroke. It can also cause other types of cancer, like mouth and throat cancer. Smoking can make it hard to breathe and can cause chronic coughing.

Smoking and Secondhand Smoke

Not only does smoking hurt the smoker, but it also harms others around them. This is called secondhand smoke. It can cause the same health problems in non-smokers. Children exposed to secondhand smoke can get sick more often.

Smoking and Appearance

Smoking can also affect how you look. It can cause yellow teeth and bad breath. It can also cause your skin to age faster, leading to wrinkles. Smoking can even cause hair loss and turn your fingers yellow.

In conclusion, smoking is very harmful. It can cause many health problems and can even harm others around you. It’s best to avoid this bad habit. If you or someone you know smokes, try to quit. Your body will thank you.

250 Words Essay on Negative Effects Of Smoking

Introduction.

Smoking is a harmful habit that many people around the world have. It is bad for our health and the environment. This essay will talk about the negative effects of smoking.

Damages to Health

Smoking hurts our bodies in many ways. It is the main cause of lung cancer. This is a very serious disease that can lead to death. Other than lung cancer, smoking can also cause heart disease. This is because the smoke makes it harder for the heart to pump blood.

Problems for the Environment

Smoking is not just bad for our health, but also for our environment. Cigarette butts are often thrown on the ground, causing pollution. Also, the smoke from cigarettes adds to air pollution. This is bad for all living things, not just humans.

Effects on Others

Smoking is not only harmful to the person who smokes, but also to the people around them. This is called second-hand smoke. It can cause the same health problems as smoking does. This means that even if you do not smoke, you can still get sick from being around someone who does.

In conclusion, smoking is a harmful habit with many negative effects. It causes health problems, harms the environment, and can even make others sick. It is important to avoid smoking for a healthier and safer world.

500 Words Essay on Negative Effects Of Smoking

Smoking is a habit that many people pick up due to various reasons, such as stress, peer pressure, or even out of curiosity. Despite its popularity, smoking has many negative effects on our health and the environment. This essay will discuss these harmful effects in simple terms.

Effects on Personal Health

Firstly, let’s talk about how smoking harms our own health. When you smoke, you inhale many dangerous chemicals. These chemicals can harm nearly every organ in your body. The most commonly known health problem caused by smoking is lung cancer. But that’s not all. Smoking can also lead to other types of cancer, such as mouth cancer and throat cancer.

Apart from cancer, smoking can cause heart disease. The chemicals in smoke make it harder for your heart to work properly. This can lead to heart attacks. Smoking also harms your lungs, making it difficult to breathe. This can lead to diseases like bronchitis and emphysema.

Effects on Others’ Health

Smoking is not only harmful to the smoker but also to those around them. This is called secondhand smoke. When you smoke, the people around you also breathe in the harmful chemicals. This can lead to the same health problems that smokers face. Children are particularly at risk. They can suffer from problems like asthma, ear infections, and even sudden infant death syndrome.

Effects on the Environment

Smoking also hurts our environment. Cigarette butts, which are often thrown away carelessly, are a form of litter. They can take many years to break down and are harmful to wildlife. The smoke from cigarettes also adds to air pollution. This can harm the air we all breathe and contribute to climate change.

Effects on Personal Life

Lastly, smoking can affect your personal life. It can make your clothes and breath smell bad, which can affect your relationships with others. It can also be a costly habit. The money spent on cigarettes could be used for other things like education, hobbies, or saving for the future.

In conclusion, smoking has many negative effects. It harms our health, the health of those around us, our environment, and our personal lives. It’s important to understand these effects and to make healthy choices for ourselves and our communities. Remember, it’s never too late to quit smoking and start living a healthier life.

That’s it! I hope the essay helped you.

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Home — Essay Samples — Nursing & Health — Addictions — Smoking

Essays About Smoking

Smoking essay, types of essay about smoking.

• Cause and Effect Essay: This type of essay focuses on the causes and effects of smoking. It discusses why people start smoking and the consequences of smoking on both the smoker and those around them.
• Argumentative Essay: This essay type aims to persuade the reader about the negative effects of smoking. It presents an argument and provides supporting evidence to convince the reader that smoking is harmful and should be avoided.
• Persuasive Essay: Similar to an argumentative essay, this type of essay aims to persuade the reader to quit smoking. It presents facts, statistics, and other relevant information to convince the reader to stop smoking.

Smoking Essay Example: Cause and Effect

• Identify the causes of smoking: Start by examining why people start smoking in the first place. Is it peer pressure, addiction, stress, or curiosity? Understanding the reasons why people smoke is crucial in creating an effective cause and effect essay.
• Discuss the effects of smoking: Highlight the impact smoking has on an individual's health and the environment. Discuss the risks associated with smoking, such as lung cancer, heart disease, and respiratory problems, and explain how smoking affects non-smokers through secondhand smoke.
• Use reliable sources: To make your essay more convincing, ensure that you use credible sources to back up your claims. Use scientific studies, government reports, and medical journals to support your arguments.
• Provide statistical evidence: Incorporate statistical data to make your essay more impactful. Use figures to show the number of people who smoke, the effects of smoking on the environment, and the costs associated with smoking.
• Offer solutions: Conclude your essay by suggesting solutions to the problem of smoking. Encourage smokers to quit by outlining the benefits of quitting smoking and offering resources for those who want to quit.

Smoking: Argumentative Essay

• Choose a clear position: The writer should choose a side on the issue of smoking, either for or against it, and be clear in presenting their stance.
• Gather evidence: Research and collect facts and statistics to support the writer's argument. They can find data from reliable sources like scientific journals, government reports, and reputable news organizations.
• Address counterarguments: A good argumentative essay will acknowledge opposing viewpoints and then provide a counterargument to refute them.
• Use persuasive language: The writer should use persuasive language to convince the reader of their position. This includes using rhetorical devices, such as ethos, pathos, and logos, to appeal to the reader's emotions and logic.
• Provide a clear conclusion: The writer should summarize the key points of their argument and reiterate their stance in the conclusion.

Persuasive Essay on Smoking

• Identify your audience and their beliefs about smoking.
• Present compelling evidence to support your argument, such as statistics, research studies, and personal anecdotes.
• Use emotional appeals, such as stories or images that show the negative impact of smoking.
• Address potential counterarguments and refute them effectively.
• Use strong and clear language to persuade the reader to take action.
• When choosing a topic for a smoking persuasive essay, consider a specific aspect of smoking that you would like to persuade the audience to act upon.

Hook Examples for Smoking Essays

Anecdotal hook.

Imagine a teenager taking their first puff of a cigarette, unaware of the lifelong addiction they're about to face. This scenario illustrates the pervasive issue of smoking among young people.

Question Hook

Is the pleasure derived from smoking worth the serious health risks it poses? Dive into the contentious debate over tobacco use and its consequences.

Quotation Hook

"Smoking is a habit that drains your money and kills you slowly, one puff after another." — Unknown. Explore the financial and health impacts of smoking in today's society.

Statistical or Factual Hook

Did you know that smoking is responsible for nearly 8 million deaths worldwide each year? Examine the alarming statistics and data associated with tobacco-related illnesses.

Definition Hook

What exactly is smoking, and what are the various forms it takes? Delve into the definitions of smoking, including cigarettes, cigars, pipes, and emerging alternatives like e-cigarettes.

Rhetorical Question Hook

Can we truly call ourselves a smoke-free generation when new nicotine delivery devices are enticing young people? Investigate the impact of vaping and e-cigarettes on the youth.

Historical Hook

Trace the history of smoking, from its ancient roots to its prevalence in different cultures and societies. Explore how perceptions of smoking have evolved over time.

Contrast Hook

Contrast the images of the suave, cigarette-smoking characters from classic films with the grim reality of tobacco-related diseases and addiction in the modern world.

Narrative Hook

Walk in the shoes of a lifelong smoker as they recount their journey from that first cigarette to a battle with addiction and the quest to quit. Their story reflects the struggles of many.

Shocking Statement Hook

Prepare to uncover the disturbing truth about smoking—how it not only harms the smoker but also affects non-smokers through secondhand smoke exposure. It's an issue that goes beyond personal choice.

Quitting Smoking: Strategies for Success

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Can Smoking Be Prevented by Making Tobacco Illegal

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Persuasive Essay Guide

Persuasive Essay About Smoking

Persuasive Essay About Smoking - Making a Powerful Argument with Examples

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Are you wondering how to write your next persuasive essay about smoking?

Smoking has been one of the most controversial topics in our society for years. It is associated with many health risks and can be seen as a danger to both individuals and communities.

Writing an effective persuasive essay about smoking can help sway public opinion. It can also encourage people to make healthier choices and stop smoking. 

But where do you begin?

In this blog, we’ll provide some examples to get you started. So read on to get inspired!

• 1. What You Need To Know About Persuasive Essay
• 2. Persuasive Essay Examples About Smoking
• 3. Argumentative Essay About Smoking Examples
• 4. Tips for Writing a Persuasive Essay About Smoking

What You Need To Know About Persuasive Essay

A persuasive essay is a type of writing that aims to convince its readers to take a certain stance or action. It often uses logical arguments and evidence to back up its argument in order to persuade readers.

It also utilizes rhetorical techniques such as ethos, pathos, and logos to make the argument more convincing. In other words, persuasive essays use facts and evidence as well as emotion to make their points.

A persuasive essay about smoking would use these techniques to convince its readers about any point about smoking. Check out an example below:

Simple persuasive essay about smoking

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Persuasive Essay Examples About Smoking

Smoking is one of the leading causes of preventable death in the world. It leads to adverse health effects, including lung cancer, heart disease, and damage to the respiratory tract. However, the number of people who smoke cigarettes has been on the rise globally.

A lot has been written on topics related to the effects of smoking. Reading essays about it can help you get an idea of what makes a good persuasive essay.

Here are some sample persuasive essays about smoking that you can use as inspiration for your own writing:

Persuasive speech on smoking outline

Persuasive essay about smoking should be banned

Persuasive essay about smoking pdf

Persuasive essay about smoking cannot relieve stress

Persuasive essay about smoking in public places

Speech about smoking is dangerous

Persuasive Essay About Smoking Introduction

Persuasive Essay About Stop Smoking

Short Persuasive Essay About Smoking

Stop Smoking Persuasive Speech

Check out some more persuasive essay examples on various other topics.

Argumentative Essay About Smoking Examples

An argumentative essay is a type of essay that uses facts and logical arguments to back up a point. It is similar to a persuasive essay but differs in that it utilizes more evidence than emotion.

If you’re looking to write an argumentative essay about smoking, here are some examples to get you started on the arguments of why you should not smoke.

Argumentative essay about smoking pdf

Argumentative essay about smoking in public places

Argumentative essay about smoking introduction

Check out the video below to find useful arguments against smoking:

Tips for Writing a Persuasive Essay About Smoking

You have read some examples of persuasive and argumentative essays about smoking. Now here are some tips that will help you craft a powerful essay on this topic.

Choose a Specific Angle

Select a particular perspective on the issue that you can use to form your argument. When talking about smoking, you can focus on any aspect such as the health risks, economic costs, or environmental impact.

Think about how you want to approach the topic. For instance, you could write about why smoking should be banned. 

Check out the list of persuasive essay topics to help you while you are thinking of an angle to choose!

Research the Facts

Before writing your essay, make sure to research the facts about smoking. This will give you reliable information to use in your arguments and evidence for why people should avoid smoking.

You can find and use credible data and information from reputable sources such as government websites, health organizations, and scientific studies. 

For instance, you should gather facts about health issues and negative effects of tobacco if arguing against smoking. Moreover, you should use and cite sources carefully.

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Make an Outline

The next step is to create an outline for your essay. This will help you organize your thoughts and make sure that all the points in your essay flow together logically.

Your outline should include the introduction, body paragraphs, and conclusion. This will help ensure that your essay has a clear structure and argument.

Use Persuasive Language

When writing your essay, make sure to use persuasive language such as “it is necessary” or “people must be aware”. This will help you convey your message more effectively and emphasize the importance of your point.

Also, don’t forget to use rhetorical devices such as ethos, pathos, and logos to make your arguments more convincing. That is, you should incorporate emotion, personal experience, and logic into your arguments.

Introduce Opposing Arguments

Another important tip when writing a persuasive essay on smoking is to introduce opposing arguments. It will show that you are aware of the counterarguments and can provide evidence to refute them. This will help you strengthen your argument.

By doing this, your essay will come off as more balanced and objective, making it more convincing.

Finish Strong

Finally, make sure to finish your essay with a powerful conclusion. This will help you leave a lasting impression on your readers and reinforce the main points of your argument. You can end by summarizing the key points or giving some advice to the reader.

A powerful conclusion could either include food for thought or a call to action. So be sure to use persuasive language and make your conclusion strong.

To conclude,

By following these tips, you can write an effective and persuasive essay on smoking. Remember to research the facts, make an outline, and use persuasive language.

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The Economic Impact of Smoking and of Reducing Smoking Prevalence: Review of Evidence

Victor u ekpu.

1 Adam Smith Business School (Economics Division), University of Glasgow, Glasgow, UK.

Abraham K Brown

2 Nottingham Business School (Marketing Division), Nottingham Trent University, Nottingham, UK.

Associated Data

Supplementary file 1..

Search strategy for PubMed [modified for NIHR (CDR)].

Supplementary File 2.

Summary of results from selected economic studies by types of intervention.

Tobacco smoking is the cause of many preventable diseases and premature deaths in the UK and around the world. It poses enormous health- and non-health-related costs to the affected individuals, employers, and the society at large. The World Health Organization (WHO) estimates that, globally, smoking causes over US$500 billion in economic damage each year.

This paper examines global and UK evidence on the economic impact of smoking prevalence and evaluates the effectiveness and cost effectiveness of smoking cessation measures.

STUDY SELECTION

Search methods.

We used two major health care/economic research databases, namely PubMed and the National Institute for Health Research (NIHR) database that contains the British National Health Service (NHS) Economic Evaluation Database; Cochrane Library of systematic reviews in health care and health policy; and other health-care-related bibliographic sources. We also performed hand searching of relevant articles, health reports, and white papers issued by government bodies, international health organizations, and health intervention campaign agencies.

Selection criteria

The paper includes cost-effectiveness studies from medical journals, health reports, and white papers published between 1992 and July 2014, but included only eight relevant studies before 1992. Most of the papers reviewed reported outcomes on smoking prevalence, as well as the direct and indirect costs of smoking and the costs and benefits of smoking cessation interventions. We excluded papers that merely described the effectiveness of an intervention without including economic or cost considerations. We also excluded papers that combine smoking cessation with the reduction in the risk of other diseases.

Data collection and analysis

The included studies were assessed against criteria indicated in the Cochrane Reviewers Handbook version 5.0.0.

Outcomes assessed in the review

Primary outcomes of the selected studies are smoking prevalence, direct and indirect costs of smoking, and the costs and benefits of smoking cessation interventions (eg, “cost per quitter”, “cost per life year saved”, “cost per quality-adjusted life year gained,” “present value” or “net benefits” from smoking cessation, and “cost savings” from personal health care expenditure).

MAIN RESULTS

The main findings of this study are as follows:

• The costs of smoking can be classified into direct, indirect, and intangible costs. About 15% of the aggregate health care expenditure in high-income countries can be attributed to smoking. In the US, the proportion of health care expenditure attributable to smoking ranges between 6% and 18% across different states. In the UK, the direct costs of smoking to the NHS have been estimated at between £2.7 billion and £5.2 billion, which is equivalent to around 5% of the total NHS budget each year. The economic burden of smoking estimated in terms of GDP reveals that smoking accounts for approximately 0.7% of China’s GDP and approximately 1% of US GDP. As part of the indirect (non-health-related) costs of smoking, the total productivity losses caused by smoking each year in the US have been estimated at US$151 billion.
• The costs of smoking notwithstanding, it produces some potential economic benefits. The economic activities generated from the production and consumption of tobacco provides economic stimulus. It also produces huge tax revenues for most governments, especially in high-income countries, as well as employment in the tobacco industry. Income from the tobacco industry accounts for up to 7.4% of centrally collected government revenue in China. Smoking also yields cost savings in pension payments from the premature death of smokers.
• Smoking cessation measures could range from pharmacological treatment interventions to policy-based measures, community-based interventions, telecoms, media, and technology (TMT)-based interventions, school-based interventions, and workplace interventions.
• The cost per life year saved from the use of pharmacological treatment interventions ranged between US$128 and US$1,450 and up to US$4,400 per quality-adjusted life years (QALYs) saved. The use of pharmacotherapies such as varenicline, NRT, and Bupropion, when combined with GP counseling or other behavioral treatment interventions (such as proactive telephone counseling and Web-based delivery), is both clinically effective and cost effective to primary health care providers.
• Price-based policy measures such as increase in tobacco taxes are unarguably the most effective means of reducing the consumption of tobacco. A 10% tax-induced cigarette price increase anywhere in the world reduces smoking prevalence by between 4% and 8%. Net public benefits from tobacco tax, however, remain positive only when tax rates are between 42.9% and 91.1%. The cost effectiveness ratio of implementing non-price-based smoking cessation legislations (such as smoking restrictions in work places, public places, bans on tobacco advertisement, and raising the legal age of smokers) range from US$2 to US$112 per life year gained (LYG) while reducing smoking prevalence by up to 30%–82% in the long term (over a 50-year period).
• Smoking cessation classes are known to be most effective among community-based measures, as they could lead to a quit rate of up to 35%, but they usually incur higher costs than other measures such as self-help quit-smoking kits. On average, community pharmacist-based smoking cessation programs yield cost savings to the health system of between US$500 and US$614 per LYG.
• Advertising media, telecommunications, and other technology-based interventions (such as TV, radio, print, telephone, the Internet, PC, and other electronic media) usually have positive synergistic effects in reducing smoking prevalence especially when combined to deliver smoking cessation messages and counseling support. However, the outcomes on the cost effectiveness of TMT-based measures have been inconsistent, and this made it difficult to attribute results to specific media. The differences in reported cost effectiveness may be partly attributed to varying methodological approaches including varying parametric inputs, differences in national contexts, differences in advertising campaigns tested on different media, and disparate levels of resourcing between campaigns. Due to its universal reach and low implementation costs, online campaign appears to be substantially more cost effective than other media, though it may not be as effective in reducing smoking prevalence.
• School-based smoking prevalence programs tend to reduce short-term smoking prevalence by between 30% and 70%. Total intervention costs could range from US$16,400 to US$580,000 depending on the scale and scope of intervention. The cost effectiveness of school-based programs show that one could expect a saving of approximately between US$2,000 and US$20,000 per QALY saved due to averted smoking after 2–4 years of follow-up.
• Workplace-based interventions could represent a sound economic investment to both employers and the society at large, achieving a benefit–cost ratio of up to 8.75 and generating 12-month employer cost savings of between $150 and $540 per nonsmoking employee. Implementing smoke-free workplaces would also produce myriads of new quitters and reduce the amount of cigarette consumption, leading to cost savings in direct medical costs to primary health care providers. Workplace interventions are, however, likely to yield far greater economic benefits over the long term, as reduced prevalence will lead to a healthier and more productive workforce.

CONCLUSIONS

We conclude that the direct costs and externalities to society of smoking far outweigh any benefits that might be accruable at least when considered from the perspective of socially desirable outcomes (ie, in terms of a healthy population and a productive workforce). There are enormous differences in the application and economic measurement of smoking cessation measures across various types of interventions, methodologies, countries, economic settings, and health care systems, and these may have affected the comparability of the results of the studies reviewed. However, on the balance of probabilities, most of the cessation measures reviewed have not only proved effective but also cost effective in delivering the much desired cost savings and net gains to individuals and primary health care providers.

It is a known fact that both active and passive smoking are damaging to human health and have associated economic costs. Cigarette smoking is the cause of many preventable diseases, a leads to premature deaths, and accounts for a significant proportion of many health inequalities. The World Health Organization (WHO) currently estimates that each year smoking accounts for about ~6 million deaths worldwide and causes about half a trillion dollars in economic damage annually. 1 This number of smoking-attributable deaths is expected to rise to 7 million by 2020 and to more than 8 million a year by 2030 if the current rate of smoking continues unabated. 2 According to recent statistics from the Action on Smoking and Health, 3 smoking causes ~80% of deaths from lung cancer, ~80% of deaths from bronchitis and emphysema, and ~17% of deaths from heart disease. More than one quarter of all cancer deaths can be attributed to smoking. These include cancer of the lung, mouth, lip, throat, bladder, kidney, pancreas, stomach, liver, and cervix. It is also estimated that globally 600,000 deaths a year are caused by second-hand smoke, and most of these deaths occur among women and children.

The US center for Disease Control and Prevention also reported that cigarette smoking is the proximate cause of over 440,000 premature deaths annually, of which 50,000 is attributable to second-hand smoke. 4 – 6 Recent statistics from the British National Health Service (NHS) Health and Social Care Information Centre 7 shows that smoking accounts for about 100,000 deaths a year in the UK (79,100 in England, 13,000 in Scotland, 5,600 in Wales, and 2,300 in Northern Ireland). This compares with similar studies for UK in 2009, which showed that there were 109,164 deaths due to smoking (19% of all deaths in the UK), of which 27% deaths in men and 11% deaths in women can be traced to smoking. 8 These figures no doubt show that addiction to cigarette smoking poses a lot of health risk and could be loosely described as a death sentence in disguise . Reducing the prevalence of this menace is thus a worthy cause for health care professionals, the government, and society at large.

This paper reviews the major studies on the economics of tobacco smoking and the economic impact of reducing its prevalence. The paper examines the following research questions:

• What are the economic costs and benefits of smoking?
• How effective and cost effective are smoking cessation measures in terms of delivering cost savings and net gains to individuals and primary health care providers?

The economic impact of smoking is twofold: the costs of tobacco use itself, and the costs of reducing its prevalence among smokers. Beyond the face value of cigarette purchases, the costs of tobacco use have more far-reaching health and economic implications on private individuals, families, employers, and taxpayers. The costs of smoking have thus been classified as direct, indirect, and intangible. The direct costs of smoking include the cost of illness due to smoking on affected patients, and the health care expenditure involved in the treatment of smoking-related illnesses (eg, cost of drugs and administrative services). In the UK, direct costs of smoking arise from GP consultations, prescriptions for drugs, and various costs related to treating diseases attributable to smoking. 7 Direct costs could also include the resources used up by other agencies and charitable organizations. 9 The World Bank estimates that about 15% of the aggregate health care expenditure in high-income countries can be attributed to smoking. 10 , 11 In the UK, the direct costs of smoking to the NHS have been estimated at between £2.7 billion and £5.2 billion, which is equivalent to around 5% of the total NHS budget each year. 3 , 7 , 8 , 12 – 14 Smoking also poses considerable indirect costs to society and the nonsmoking public, eg, costs of second-hand smoking, costs to employers in the form of loss of productivity and absenteeism of smokers owing to smoking-related illnesses. 15 In addition, smoking-induced fires, sickness/invalidity benefits, litter, etc are all negative externalities of smoking to society. The direct and indirect costs of smoking can be measured b and hence are tangible costs, whereas there are some costs that cannot be easily quantified, such as loss of life, and the burden of pain and suffering caused by smoking-induced illness. 16 , 17 These unquantifiable costs are often referred to as the intangible costs of smoking.

Just as there are costs emanating from smoking, there are also benefits associated with reducing the incidence or prevalence of smoking. Benefits here refer to the losses that could be avoided by the individuals who quit smoking, such as cost savings from smoking in terms of reduced morbidity and mortality, reductions in the costs of illness, and the marginal risk of disease. 18 Other benefits of reducing smoking prevalence are longevity and improvement in the quality of life of quitters and passive smokers, improved workplace productivity, reduced costs of cleaning up the environment after smoking, reduction in fires caused by smoking, and the resulting damage or destruction, as well as a healthier population, among other benefits. There is a growing body of literature suggesting that smoking cessation interventions, coupled with regulations and legislations, are effective ways to reduce smoking prevalence. 16 , 17 , 19 , 20 Furthermore, there is evidence to suggest that smoking cessation interventions are among the most cost-effective and economically reasonable ways of appropriating health care resources. 5 , 9 – 11 , 21 – 27

This study attempts to review the existing evidence on the economic, health-related, and non-health-related impact of reducing smoking prevalence. First, we summarize the search methods and selection procedure used to conduct the systematic review, and then we examine the quality assessment method used in evaluating the study quality. The paper utilizes two main approaches used by medical researchers for economic evaluation c : cost-effectiveness analysis (CEA) and cost–benefit analysis (CBA). These are discussed in detail in Section “Measures of Evaluating Economic Impact”. The aim of this paper is to identify evidence on the effectiveness and cost effectiveness of smoking cessation interventions and also to identify data that may be of use in the economic modeling of the cost savings and net benefits derivable from investing in smoking cessation programs in the UK. Two specific pieces of work are presented in this review. The Section “Global Evidence on the Economics of Smoking” examines the evidence globally on the costs and benefits attributable to smoking, and then reviews the literature on the effectiveness and cost effectiveness of smoking cessation programs across countries. These will be examined under six broad headings: 1) pharmacological treatment interventions, 2) policy-based interventions, 3) community based interventions, 4) telecoms, media, and technology (TMT)-based interventions, 5) school-based interventions, and 6) workplace- or employer-based interventions. The second major segment of this review (“The Economic Impact of Smoking and Smoking-cessation Interventions in UK”) examines the economic impact of smoking in the UK. The rationale for narrowing down to UK is to assess how these various types of interventions are applied in a single country case study. Here, the costs and benefits of smoking in the UK are examined, as well as the effectiveness and cost effectiveness of UK-specific smoking cessation intervention programs. The Section “Discussion” discusses the main findings of the review by comparing results across types of intervention, across countries, and across measurement outcomes, and in some cases, providing the range of costs or cost savings for each intervention by combining costs from multiple sources. The section also discusses some of the known limitations of the study.

Research Methods

Search methods and selection criteria: overview.

A systematic review produced several studies, out of which a total of 99 literature sources on the economics of smoking and of reducing smoking prevalence were used for the review. We captured major economic studies on the health and economic impact of smoking and cost effectiveness of tobacco policies published between 1992 and 2014, but included only eight relevant studies before 1992. We also performed hand-searching of relevant articles, which produced additional 52 papers, including useful non-economic studies, and health reports and white papers issued by government bodies, international health organizations and health intervention campaign agencies that are usually not included in the electronic databases. This brings the total number of studies included in the review to 151. Of this number, 123 were strictly peer-reviewed medical journals, while 28 were useful government (public health) reports and white papers. This paper benefits strongly from the inclusion and synthesis of high-level evidence from mostly recent studies (eg, 2005–2014), with the implication that newer and better methods, indicators, or measures have been reported in order to aid economic modeling.

Study outcomes

Primary outcomes of the selected studies are smoking prevalence, direct and indirect costs of smoking, and the costs and benefits of smoking cessation interventions (eg “cost per quitter”, “cost per quality of life year gained”, “cost per life saved”, “present value” or “net benefits” from smoking cessation, and “cost savings” from personal health care expenditure).

Identification of studies

Two main electronic databases were searched. These are PUBMED (January 1992 to July 2014) and CRD (NIHS) (January 1992 to July 2014). The reason for the selection of these databases is that they are both very comprehensive databases containing health care-related studies. For example, PUBMED contains more than 23 million citations for biomedical literature from MEDLINE. The CRD database also contains the NHS Economic Evaluation Database, the Cochrane Library of Systematic Reviews in health care and health policy, and other health care-related bibliographic sources. To identify relevant studies for this review, we used a detailed search strategy for each database. These were based on the search strategy developed for PUBMED but revised appropriately for each database to take account of differences such as vocabulary and syntax rules. Key terms used were “economic” or “costs”, or “cost effectiveness” and “smoking”, or “tobacco” for the international evidence section, while the search strategy for the UK segment of the study included “UK” to the list of key words (see Supplementary File 1 ). Other keywords used were “tobacco control”, “smoking reduction”, and “smoking cessation”. We also performed hand searches on other databases such as EconLit, Science Direct, JSTOR, Cochrane Library, and Google Scholar using the same keywords, and this produced most of the papers already contained in PUBMED/MEDLINE and CRD. Unpublished reports, abstracts, brief and preliminary reports were considered for inclusion on the same basis as published reports. There was no restriction based on language or date.

Selection of studies

The authors read all titles and/or abstracts resulting from the search process, and any irrelevant studies were removed. Full copies of the remaining potentially relevant studies were obtained and assessed independently by the authors to ensure that these clearly met all inclusion criteria. Those that were clearly irrelevant or had insufficient information to make a decision were excluded, or the authors were contacted for further information to aid the decision process. Decisions were based on inclusion criteria, ie, types of studies, types of participants, interventions, and outcome measures used. Variations in authors’ opinion were resolved through discussion and consensus.

Under the review of international (non-UK) evidence in Section “Global evidence on the economics of smoking”, we assessed and summarized 36 papers on the costs and benefits of smoking as well as 65 papers on the effectiveness and cost effectiveness of smoking cessation interventions across countries. Though a substantial part of the evidence on the economics of smoking were drawn from the United States, we tried as much as possible to reflect pockets of evidence from other countries around the world, especially from China, the largest producer and consumer of tobacco products, as well as from Australia, Hong Kong, Korea, Thailand, Taiwan, Sweden, France, Belgium, Denmark, India, Turkey, Netherlands, and Canada. 26 , 28 – 42 These countries appear to be known to have carried out comprehensive tobacco control policies. This study reviewed only relevant papers on the effectiveness and cost effectiveness of smoking cessation under six headings: pharmacological interventions (8), policy-based interventions (19), community-based interventions, (10), TMT-based interventions (12), school-based interventions (5) and workplace- or employer-based interventions (7).

With regard to the UK, in Section “The economic impact of smoking and smoking cessation interventions in UK”, this study reviewed 33 papers, 19 on the costs and benefits of smoking in UK and 14 studies on the effectiveness and cost effectiveness of UK-specific smoking cessation interventions. Cost estimates are mostly expressed in US dollars for international evidence (except where stated otherwise) and in British pounds for UK evidence.

Data extraction and management

Data were extracted from published sources using a standard data recording form. Studies that reported primary outcomes were extracted and reviewed. At the first level of screening, we excluded papers that merely described the effectiveness of an intervention without including economic or cost considerations. We also excluded studies that combined smoking cessation with the reduction in the risk of other diseases such as lung cancer, myocardial infarction, chronic obstructive pulmonary disease (COPD), stroke, obesity, diabetes, coronary heart disease, etc. At the second level of screening, we excluded papers in which study design, methods, or outcomes did not appear to be consistent with those of the review as well as publications that appeared more than once in both databases. Figure 1 illustrates the study selection process more clearly.

Flowchart of study selection process.

Risk of bias

The risk of bias in studies was assessed via the criteria described in version 5.0.0 of Cochrane Reviewers Handbook . 43 This is based on the evaluation of six specific methodological domains (ie, sequence generation, allocation concealment, blinding, incomplete outcome data, selective outcome reporting, and other issues). Generally, the six domains are used by answering a prespecified question about the adequacy of each study in relation to each domain, such that a judgment of “Yes” indicates low risk of bias, “No” indicates high risk of bias, and “Unclear” indicates unclear or unknown risk of bias.

For this review, the following domains were used: sequence generation, allocation concealment (avoidance of selection bias), incomplete outcome data, and selective outcome reporting. Blinding was not possible because of the nature of some of the studies/intervention used.

Measures of evaluating economic impact

We now discuss two methods commonly used by medical researchers for economic evaluation: cost effective analysis (CEA) and cost-benefit analysis (CBA).

Cost effectiveness analysis

CEA is a measure of cost savings. It tends to link the cost of an intervention to the health improvements or gains caused by that intervention. Measures of health improvements include cases avoided (CA), hospital days avoided (HDA), deaths averted (DA), and life-years saved (LYS). 5 Other measures include cost per quitter (CPQ) enrolled in community-based cessation programs such as a self-help program, a smoking cessation class, an incentive-based cessation contest, 44 or in a quitline program. 45 The cost effectiveness of a cessation program may not only be looked at in absolute terms but also in relative or comparative terms to other intervention programs because each program may have different dimensions of cost effectiveness. Cost effectiveness is usually measured in ratios. A higher cost effectiveness ratio means that a program is less cost effective than another intervention program. However, Altman et al 44 put forward an argument that the fact that an intervention program yields a high cost effectiveness ratio does not necessarily imply that it is a less desirable outcome. It may well mean that even the most cost-effective program only impacts on a small fraction of the population in need, so that a wiser decision would be to implement as many cost-effective programs that satisfy the needs of more diverse groups of citizens.

Cost–benefit analysis

CBA is an economic technique that is used in evaluating the economic soundness or feasibility of an intervention program. CBA measures both the costs and monetary benefits derivable from an intervention, discounted at their present value. Discounting helps to make divergent outcomes of costs and benefits comparable irrespective of the date at which they occur. According to Phillips and Prowle, 22 there are three basic stages involved when conducting a CBA: (1) the costs incurred in the intervention program must be identified, measured, and assessed; (2) the benefits associated with the intervention also has to be identified, measured, and assessed in which case any input–output misalignments or time-dependent outcomes (eg, of a reduction in smoking prevalence) will have to be adjusted; (3) the costs and adjusted benefits are now combined to arrive at a measure of the net present value of outcomes, ie, the difference between the present value of benefits and the present value of costs. If benefits exceed costs, then the intervention is economically viable, and has a positive net benefit. Otherwise, it has a negative net benefit. Another way of looking at this is to estimate the benefit–cost ratio, that is, the present value of benefits divided by the present value of costs. The higher the benefit–cost ratio, the more desirable is the outcome of the intervention. It should be noted that many health researchers find it difficult to attach monetary values to health outcomes, and hence find the technique less useful than CEA and CUA. 5

Global Evidence on the Economics of Smoking

According to the Campaign for Tobacco-Free Kids, 46 the top five cigarette-consuming countries are China, Russia, United States, Japan, and Indonesia. China consumes more than 35% of the world’s cigarettes, with 53% of males smoking. Philip Morris International, British American Tobacco, Japan Tobacco International, and Imperial Tobacco are the world’s four largest multinational tobacco companies. The largest state tobacco monopoly is the China National Tobacco Corporation, which has the largest share of the global market among all companies. Based on WHO estimates, tobacco use costs the world an estimated $500 billion each year in health care expenditures, productivity losses, fire damage, and other costs. In the US alone, smoking causes more than $193 billion each year in health-related costs, including medical costs and the cost of lost productivity caused by smoking. 5 , 47 New figures from the Campaign for Tobacco-Free Kids show that the social cost of smoking in the US could be estimated at about US$321 billion (ie both smoking-caused health costs of US$170 billion and associated productivity losses of US$151 billion). 59 (See Fig. 2 ). This section examines the economic costs and benefits of smoking in some detail, citing examples from countries where tobacco is in high demand and use.

Smoking-attributable expenditure in the United States (USD billion).

Note: Campaign for Tobacco-Free Kids. 50

Smoking-attributable costs and benefits

As shown earlier, the costs of smoking can be classified into health-related costs and non-health-related costs.

Health-related costs

The health care costs associated with tobacco-related illnesses are extremely high. In the United States, total annual public and private health care expenditures caused by smoking amount to approximately US$170 billion. 59 Measured as a proportion of the gross domestic product (GDP), smoking costs in the US are approximately 1% of the GDP. Many studies have estimated the health-related costs of smoking. These costs include medical expenditure on drugs and administration, smoking-attributable morbidity and mortality, medical costs attributable to passive smoking, maternal smoking, and children smoking. Other direct costs include sickness/invalidity benefits attributable to tobacco abuse. A study by Yang et al 48 reveals three ways in which smoking-attributable expenditures could be measured—average expenditure per inpatient hospitalization (or admission), average expenditure per outpatient visit, and self-medication expenditures. Some other indicators of health care expenditure include smoking-induced emergency and general practitioner visits for adults and children, and use of nursing homes and home-based care. 49

Annual federal and state government smoking-caused Medicaid payments are estimated at US$39.6 billion (federal share: US$22.5 billion; states’ share: US$17.1 billion) (see Fig. 2 ). State-level estimates from USA revealed that the direct costs of smoking in California in 1999 were US$8.6 billion, with nearly half of this amount (47%) going to hospital care, 24% for ambulatory care, 15% for nursing home care, 13% for prescriptions, and 1% for domestic health care services. 4 Fresh statistics from Campaign for Tobacco-Free Kids 50 on state tobacco-related costs and revenues has revealed that smoking-related medical expenditures in US varied dramatically across states, with a low of US$22.4 million in Wyoming to a high of US$3.31 billion in New York. Another report by Armour et al 51 showed that the proportion of health care expenditure attributable to smoking ranged between 6% and 18% across the different states.

The National Drug Strategy in Australia estimated the total social costs of smoking in Australia between 2004 and 2005 at about AUD$31.4 billion, representing 56.2% of total costs of drug abuse in Australia. 16 Of these costs, AUD$12.02 billion or 38.2% was classified as tangible costs, while AUD$19.45 billion or 61.8% was intangible costs. Yang et al 48 estimated the economic burden of smoking for 2008 in China at US$28.9 billion, representing 0.7% of China’s GDP and 3% of national health care expenditures. This figure also averaged US$127.30 per smoker. According to the study, mortality costs contributed the most to smoking-attributable costs in China, followed by outpatient expenditures. Results also show that, as a result of high prevalence rate, a whopping 93% of total economic cost of smoking in China was borne by men. Results from Hong Kong reveal that annual health-related cost of smoking in 1998 was US$688 million. 49 The same study shows that about 5,596 deaths in Hong Kong among adults 35 years of age and above in 1998 was attributable to active smoking, while passive smoking accounted for 1,324 deaths. This brings to a total of 6,920 tobacco-related deaths out of 32,847 deaths. In what seems very surprising, passive smoking accounted for 23% of total smoking-related health care costs in Hong Kong, implying a growing risk of the prevalence of passive smoking. In Taiwan, the total smoking-attributable expenditures (SAEs) totaled US$397.6 million, representing 6.8% of the total medical expenditures for people aged 35 years and over. 52 The mean annual medical expenditure per smoker was US$70 more than that of each nonsmoker.

Although the health risks associated with passive smoking d have been well documented in the literature, little is known about the economic costs. Regular exposure to second-hand smoke (SHS) among nonsmokers both at home and in the workplace could be economically costly in as much as it poses enormous health hazards. Following a recent research conducted by Plescia et al 53 on SHS exposure in North Carolina, the total annual cost of treatment for conditions related to such exposure was estimated to be US$293.3 million in 2009. Though the majority of the SHS victims were children, the most common cases were traceable to cardiovascular conditions. In a similar study in Minnesota by Waters et al, 54 the total annual cost of treatment for conditions associated with SHS was estimated to be US$228.7 million in 2008 dollars—equivalent to US$44.58 per Minnesota resident. Just as passive smoking poses huge health care costs, smoking during pregnancy, otherwise called “maternal smoking”, also has some related cost implications. It is associated with considerably higher child health expenditures as well as increase in overall medical costs. 55 For example, the annual direct medical expenditure for early childhood respiratory illness attributable to maternal smoking totaled US$661 million for all children under the age of six. 56 Further evidence reveals that smoking-attributable neonatal costs in the US represent almost US$367 million in 1996 dollars. 57 Though these costs vary considerably from state to state, they can easily be avoided by implementing temporary cessation programs aimed at pregnant women.

The foregoing statistics indicate that smoking everywhere is very costly in many respects and takes a huge toll on public finances. For most countries, smoking-attributable costs represent the largest single expenditure in total health care costs, with wider implications for the economy.

Non-health-related costs

Besides the health care costs of smoking, there are other costs that the abuse of tobacco imposes on society, and these costs need not be treated as less important. Tobacco-related illnesses and premature mortality impose high productivity costs to the economy because of sick workers and those who die prematurely during their working years. Lost economic opportunities in highly populated developing countries are likely to be particularly severe as tobacco use is high and growing in those areas. 58 Countries that are net importers of tobacco leaf and tobacco products lose millions of dollars a year in foreign exchanges. Fire damage and the related costs are significant. In 2000, about 300,000 or 10% of all fire deaths worldwide were caused by smoking, and the estimated total cost of fires caused by smoking was US$27 billion. 59 Tobacco production and use also damage the environment and divert agricultural land that could be used to grow food.

The economic loss to employers in the form of workplace absenteeism and the resulting lost productivity of their smoking employees is particularly alarming. In specific terms, employers suffer loss of revenue from the days off work and earnings lost from work owing to smoking-induced illness and premature death of its smoking employees during productive years. It is reported that US smokers are absent from work approximately 6.5 days more per year than nonsmokers. They make about six visits more to the health care centers per year than their nonsmoking counterparts, while dependents of smokers visit health care centers four times more than nonsmokers. 23 , 56 Recent US statistics show that the total cost of productivity losses caused by smoking each year amounts to US$151 billion. 47 , 59 This estimate only includes costs from productive work lives shortened by smoking-caused death, and does not include costs from smoking-caused disability during work lives, smoking-caused sick days, or smoking-caused productivity declines when at work, all of which amount to huge economic losses to the US. In California alone, the annual value of lost productivity owing to smoking-related illness between 2000 and 2004 averaged US$8.54 billion (US$6.87 billion for Florida; US$6.79 billion for Texas, and US$6.05 billion for New York), showing that these US states and many others have lost huge productive hours and potential revenue owing to smoking-induced health problems. These results suggest that, if adequate measures are taken by primary health authorities and employers to promote smoking cessation, there will be huge cost savings from smoking-related illnesses and premature deaths.

Absenteeism and premature deaths represent only a fraction of the aggregate indirect burden of smoking to employers. It may well be that even at work smoking-induced illness could retard the performance of smoking employees and translate into lost time and earnings, which may not be easily quantified. Arguing in this light, Thompson and Forbes 60 noted that productivity losses emanating from smoking for the most part arise from short-term absenteeism or from performance at less than full efficiency due to respiratory problems or other smoking-induced illnesses. However, one cannot overlook the impact of other qualitative factors that lead to absenteeism and reduced productivity such as other health indicators (alcohol, weight, exercise, etc), job characteristics (occupation type, income, employment status, hours worked), and demographic characteristics (age, sex, ethnicity, marital status, education, place of work, etc). Evidence from Bush and Wooden 61 revealed that, even after controlling for these factors, smoking was still highly correlated with work-place absenteeism. In fact, in their 1994 paper on the impact of smoking and alcohol on workplace absence, Bush and Wooden concluded that, after controlling for the effect of other variables, employees on smoking status were found to be 1.4 times more likely to be absent, and ex-smokers were found to be 1.3 times more likely to be absent than nonsmokers. Their results also showed that the probabilities of smoking-induced absenteeism differed considerably by sex. For male smokers, the probability of workplace absence surpassed that of male non-smokers by 1.7 times, while for female smokers the probability of absence fell slightly to 1.2 times more than those females who have never smoked.

Apart from smoking-attributable absenteeism, cigarette smoking and its associated activities can also be economically costly when they are the cause of fires. In the study conducted by Collins and Lapsley, 17 the total cost of smoking-attributable fires in New South Wales, Australia, in 2006/2007 was estimated at AUD$51.4 million, with tangible costs representing over three-quarters of the total cost. In USA, smoking-induced fires lead to the death of 2,300 civilians (men, women, and children inclusive) per year, with additional 5,000 injuries per year. 23 , 56 Besides the health care costs of treating injured or burn victims, direct property damaged from fires induced by tobacco has been valued at US$552 million per year. Other costs to employers of workers who smoke include health care claims and benefits not related to health care. 23 There are also some hidden costs that are economically significant to society but often omitted in most studies for the lack of satisfactory data, eg, costs of paramedical and ambulance services, damage caused by smoking-induced forest fires, toxic effects from tobacco consumption, especially amongst children, as well as accidents and other property loss caused by cigarette smoking apart from fires.

Economic benefits of smoking

The cost of smoking notwithstanding, the tobacco industry poses a great deal of benefits, especially to the economy, consumers, and producers. It is therefore imperative to examine the positive economic effects of smoking and, hence, the impact or consequences on these of reducing smoking prevalence. Following previous studies by Thompson and Forbes, 60 Woodfield, 62 and Cohen and Barton, 56 among others, the major benefits of smoking are in economic stimulation, namely income generated from production and consumption, tax yields, employment, and early death of smokers. Taxes on cigarettes have always contributed to government treasury. In 2009, President Barrack Obama signed an act that raised the US federal tax rate on cigarettes from 39 cents to US$1.01 per pack. The 156% tax increase was estimated to earn the US government about US$33 billion in tax over a 4½-year period. There are, however, economic consequences of raising taxes (see “The economics of policy-based interventions” Section).

The World Bank estimates that tobacco farming employs about 33 million people worldwide, and about 15 million of those workers reside in China alone. 63 In China, over 4 million households rely on tobacco for their livelihood, as tobacco farmers, cigarette industry retailers, or employees. 32 In fact, China is the largest producer and consumer of tobacco worldwide. All cigarettes are produced by the Chinese government’s tobacco monopoly company, which produces more than 1.7 trillion cigarettes annually. In 2003, the company generated almost US$2 billion in profits and taxes, while income from tobacco represented about 7.4% of centrally collected government revenue. In terms of consumption, China boasts of a smoking population of 350 million active smokers and 460 million passive smokers. In 2010, about 52.9% of Chinese men and 2.4% of women were current smokers. 48 Given that China is the most populous country in the world, this proportion of smokers translates into enormous earning potential.

Apart from the income benefits of tobacco smoking, another source of benefit, especially to the government, of smoking is the substantial cost savings in pension payments from premature death of smokers. This is a highly debated issue in the literature, because it is premised on the thinking that a shorter life expectancy implies a reduced expenditure on pensions. Thus, attempts to promote this will be deemed socially undesirable and hence cannot be incorporated into social policy design. 60 , 62

Clearly, from the above, therefore, if tobacco farming is to be phased out, many households, investors, and the government itself will suffer huge economic losses. Hence there is a need to strike a balance between the costs and benefits of smoking. But this is easier said than done, especially as the health implications of smoking far outweigh any associated economic returns from the perspective of a socially desirable outcome.

Effectiveness and cost effectiveness of smoking cessation interventions

Because the health hazards attributable to smoking are very significant, the risks of illness or disease are reduced following smoking-cessation interventions. 19 According to a UK General Household Survey in 1998, about 27% of adults (aged 16 years and above) were smokers, and of this figure about 70% wanted to quit smoking. Data from a similar survey conducted in 1994 by the US health authorities indicated that 46.4% of smokers had made serious attempts to stop in the year preceding the survey, but only 5.7% of smokers managed to abstain from smoking after a period of 1 month or more, and only 2.5% of smokers are able to achieve permanent abstinence each year. The reason for this is smoking is an addiction and can hardly be stopped on the basis of will power alone. Evidence from Feenstra et al 11 shows that only ~3%–7% of smokers who attempt to stop smoking on will power are still abstinent after 1 year. In order to enhance quit rates, there must be some deliberate measures to incentivize cessation. There are different forms of smoking cessation interventions, and they range from pharmacological treatment interventions to policy-based interventions, community-based cessation programs, TMT-based interventions, school-based interventions, and workplace- or employer-based interventions.

The aim of this section is to identify and evaluate cross-country evidence on the effectiveness and cost effectiveness of smoking cessation interventions. The idea of carrying out economic evaluations is to identify which interventions utilize the least resources or have greater cost savings, while being most effective in reducing both the number of smokers and the health- and non-health-related risks associated with smoking. By comparing the costs and outcomes of different alternative interventions, economic evaluations help health care professionals and policy makers in deciding the most efficient use of scarce resources. 24 In estimating the effectiveness of cessation interventions, two major indicators are necessary: the number of long-term quitters and the health gains from smoking cessation, measured according to the age and sex of the quitters. 19 In estimating the cost effectiveness of smoking cessation interventions, emphasis is placed on the impact of such interventions on direct cost reductions with respect to smoking-related morbidity and mortality rates as well as the effect on long-term medical expenditure.

Pharmacological treatment interventions

There are several pharmacological agents that are commonly used to aid smokers in their quest to quit smoking. However, we will concentrate on the three major types: nicotine replacement therapy (NRT), bupropion sustained release (SR), and varenicline. These treatment interventions are widely available on prescription, and in the case of NRT as an over-the-counter medication. They are licensed as first-line treatments for use as smoking-cessation aids in the US and the EU, and are widely recommended in many national guidelines. 64

The aim of NRT is to temporarily replace much of the nicotine from cigarettes to reduce motivation to smoke and the physiological and psychological withdrawal symptoms often experienced during a quit attempt, thus easing the transition from cigarette smoking to complete abstinence. It is available in various forms and dosages, including transdermal patches (ie, absorbed slowly through the skin), as chewing gum, oral and nasal sprays, lozenges, sublingual tablets, and inhalers. NRT, in all its commercially available forms, has been found to help people who make a quit attempt to increase their chances of successfully stopping smoking. NRT increase the rate of quitting by as much as 50%–70% regardless of setting. 65

Bupropion was developed as a non-tricyclic antidepressant, and is sometimes preferred by smokers who do not wish to use a nicotine-based treatment, or who have already failed to quit using NRT. The usual dose for smoking cessation is 150 mg once a day for 3 days, increasing to 150 mg twice a day, continued for 7–12 weeks. 64 The quit attempt is generally initiated a week after starting pharmacotherapy. Some studies have shown that bupropion doses up to 300 mg per day does have significant effect in a dose–response fashion on smoking cessation, but does not seem to affect long-term cessation rates (see 66 ).

Varenicline is a selective nicotinic receptor partial agonist, licensed as a prescription-only treatment for smoking cessation in USA in 2006 and in Europe in 2006/2007. The standard regimen is 1 mg twice a day for 12 weeks, with the first week titrated to reduce side effects, and quit date set for the second week. Varenicline has helped ~50% more people to quit than nicotine patch and “other” NRT (tablets, sprays, lozenges, and inhalers) and ~70% more people than nicotine gum. 64 This means that for every 10 people who quit with NRT patch or with “other” NRT, about 15 could be expected to quit with varenicline, and for every 10 who quit with NRT gum, about 17 could be expected to quit with varenicline.

NRT, bupropion, and varenicline all improve the chances of quitting, with low risk of harms, and in some cases, using a combination of these pharmacological treatments could be seen to be even more clinically effective. However, as noted earlier, to justify the investment in any intervention, its effectiveness must be evaluated alongside its cost effectiveness. The cost effectiveness of pharmacological interventions is thus as important as their clinical effectiveness. A review of economic studies on these pharmacological treatment interventions (see Supplementary File 2 ) showed that varenicline and bupropion (with or without behavioral interventions) are more cost effective than NRT measures such as nicotine gum, patch, lozenge, and inhaler. A recent study by the Canadian Agency for Drugs and Technologies 33 found that, if providers’ willingness to pay (WTP) was greater than US$10,000 per QALY gained, then varenicline was the optimal treatment of choice compared to NRT and bupropion.

Several studies have also found that the use of NRT and/or bupropion SR along with GP counseling is both clinical and cost effective in primary health care. For example, Stapleton et al 67 showed that contingent prescriptions could yield additional life years at a cost between £398 (US$724) and £758 (US$1,380) in 1998 UK pounds compared to brief counseling alone. In a similar estimation of the cost effectiveness of treating nicotine dependence (including NRT and counseling), Croghan et al 68 found the aggregate 1-year smoking rate to be 22% with a cost of $9,231 per net life year gained. This cost compares favorably with other medical services that rely only on GP counseling however brief or intensive. Although NRT products can be purchased over the counter, many people have suggested that free NRT treatments yield more positive results in terms of number of quitters than other cessation interventions. For example, Ong and Glantz 69 found that in Minnesota, a free NRT program would generate 18,500 quitters at a cost of US$4,440 per quality of life adjusted years (QALY) compared to implementing a smoke-free workplace policy, which would generate 10,400 quitters at US$506 per QALY.

Nielsen and Fiore 70 conducted a CBA of bupropion SR and nicotine transdermal patch (NTP) to see which of the two, or whether a combination of both, was more cost effective for smoking cessation. The results revealed that bupropion is more cost beneficial than either NTP or bupropion and NTP together, producing a net benefit in the first post-quit year of up to £338 per employee who attempts to quit compared with US $26 for NTP only, US$178 for the two combined, and US$258 for placebo, another pharmaceutical therapeutic that was used in the clinical trials. Thus, according to this study, bupropion is able to offer the most substantial monetary benefits than any other pharmacological treatment. In a more recent study by Bolin et al, 31 the cost effectiveness of varenicline was compared with nicotine patches for smoking cessation in four European countries (Belgium, France, Sweden, and UK). Surprisingly, the results showed that the use of varenicline for smoking cessation was associated with reduced smoking-related morbidity and mortality more than was the case using NRT. The number of morbidities avoided per 1,000 smokers who made attempts to quit ranged from 9.7 in Belgium to 6.5 in UK. The number of QALY gained, per 1000 smokers, was 23 in Belgium, 19.5 in France, 29.9 in Sweden, and 23.7 in UK. The results of the base-case simulations revealed that, with the exception of France, varenicline treatment appeared to be more cost effective and cost saving than NRT. Thus, funding varenicline as a smoking cessation aid is an economically justifiable use of health care resources in these countries.

The economics of policy-based interventions

This subsection takes a look at the global evidence on the economic consequences of policy-based measures that aid smoking cessation. These include price-based measures (eg, increase in tobacco taxes, limitations on tobacco crop subsidies) and non-price measures (eg, no smoking regulations at work and in public places, restriction on sales to minors, and bans on promotion and advertising, etc). Legislative bans could either ban smoking completely (comprehensive) or restrict it to designated areas (partial). Both price-based measures and legislation-based smoking bans or restrictions have been found to yield both health and economic gains, including (1) reduction in smoking prevalence though reductions in the demand for and consumption of cigarettes, (2) significant reductions in the incidence of smoking-related diseases and deaths, (3) reduction in smoking-related medical costs, and (4) large gains in cumulative life years and QALYs. 23 , 36 , 37 , 71 – 79

Increase in tobacco taxes

The most widely used measure to reduce the demand for tobacco is increase in taxes. This puts an upward pressure on tobacco prices, and higher tobacco prices tend to significantly reduce the consumption of tobacco. 74 , 77 According to a World Bank report, 63 when taxes are raised on tobacco, consumption decreases especially in young people; a 10% cigarette price increase results in a 7% decrease in smoking by young people and 4% by the general public. It has also been hypothesized that a price increase of 10% would reduce smoking by 4% in high-income countries and by about 8% in low-and middle-income countries. 23 , 71 In other words, the price elasticity of demand for tobacco is higher in low- and middle-income countries and among populations of young or teenage smokers who are the most responsive to price changes. Smokers in high-income countries are, however, less responsive to price changes. According to Atkinson and Townsend, 80 low price sensitivity means that the revenue argument against tax increases is rather unconvincing. As long as prices do not respond proportionately to tax increases (ie, price elasticity of less than 1), the revenue from tobacco will surely increase when taxes go up since “a fall in consumption is more than offset by the extra tax paid by those who continue to smoke” (pp. 492). Thus, according to Atkinson and Townsend, so long as the reduction in tobacco consumption is attributable to increased duty, the amount of corporate revenue from tobacco is likely to remain unaffected. The World Bank has recommended that “Governments increase tobacco tax to about 65% of retail price”. 63 Increasing tobacco prices also increases the chances of cigarette theft, smuggling, and counterfeiting. The Mackinac Center on Public Policy estimates that profits made illegally from smuggling cigarettes to the US could amount to be between US$10 billion and US$17 billion. 81 Over the years, tobacco tax increases have brought about increases in revenue for the government, even when the incidence of smuggling and tax evasion are discounted. Currently, in most high-income countries where tobacco control policies are very comprehensive, tobacco taxes represent between two-thirds and four-fifths of the retail price of cigarettes, whereas in low- and middle-income countries, they are generally below 50% of the total price.

Apart from the decline in tobacco consumption via increased prices, raising cigarette taxes also poses some potential health and cost-saving benefits. Reduced tobacco consumption leads to a reduction in health care costs as former smokers and their children do not require as much medical care or treatment as they used to. 23 There is also another argument that says that huge tobacco taxes are equitable in the sense that it makes the tobacco industry pay more for the huge economic burden placed by its products to the health care system as well as the negative externalities of same to society. The income generated from tobacco taxes can also be used to finance community education and advertising against tobacco. In China, the largest producer and consumer of tobacco, a recent tobacco tax adjustment has just been implemented and, if this tax increase passes through to retail prices, it is expected to reduce the number of smokers by 630,000 saving 210,000 lives, at a price elasticity of −0.15. 32 Following the same model, a tax increase of 1RMB (or US$0.13) per pack of cigarettes is expected to increase the revenue accruable to the Chinese government by 129 billion RMB (US$17.2 billion), reduce consumption by 3.0 billion packs of cigarettes, reduce the number of smokers by 3.42 million, and save 1.14 million lives. These figures indicate that tobacco tax increase in China can be construed as the most cost-effective measure of smoking cessation.

In summary, tobacco tax increases reduces tobacco consumption via higher cigarette prices, raises government revenue, saves more lives, preserves employment, and reduces tobacco farming. However, whether or not tax increases lead to loss of revenue in the tobacco industry is still a subject of debate, as smuggling and tax evasion help to minimize any losses arising from taxation.

Smoking restrictions in the work place and in public places

It is in recognition of the dangers of passive smoking that many governments institute no smoking restrictions in public places (eg, bars, restaurants, public buses, trains, airports, government buildings, and other public facilities) and private workplaces. Governments are now increasingly sensitive to the need to protect its citizens from the externalities caused by environmental tobacco smoke. Evidence from the US and Canada suggests that smoke-free air policies are associated with a significant reduction in cigarette consumption. 23 , 71 , 82 In a report issued by the United States Environmental Protection Agency, the costs and benefits of a proposed national smoke-free environment act were modeled to identify its net benefits. The proposed policy was meant to curtail significantly smoking in public places entered by more than 10 people per week. The costs considered were costs of implementing and enforcing the restriction, costs of building and maintaining smoking lounges, among other costs. The benefits included savings from smoking-related medical expenditures, heart diseases averted, the value of lives saved, costs averted by a reduction in smoking-induced fires, and gains in productivity. 83 The net present value to society was estimated to fall between US$42 and US$78 billion, and this range was obtained by considering high and low estimates of costs and benefits. In another study by the Stephens et al, 82 they analyzed the relationship between cigarette prices and no-smoking bylaws to the prevalence of smoking in Canada. Results from a comparison of price and policy differences among Canadian provinces showed that the tendency of being a smoker falls with rising cigarette prices and with widespread no-smoking regulations, even after controlling for age, sex, education, and marital status of respondents. They thus concluded that no smoking regulations should be accompanied by an increase in cigarette prices to be more effective. If either were used in isolation, the outcomes will likely produce a lesser impact than the two measures used together.

Bans on tobacco advertisement

Tobacco remains the second most heavily advertised product in the United States besides the automobile industry. 23 Over the years, it has been widely advocated that bans be placed totally on cigarette advertisements and promotional activities. In many countries, this bill has been a subject of controversy or debate. There are those who argue that a partial ban on advertisement has little or no effect on cigarette consumption. 71 , 80 This is because, most adverts, particularly the tobacco-industry-related ones only reveal the brands smoked instead of the quantity smoked. In this sense, therefore, it is difficult to measure the impact of increased or reduced advertising on tobacco consumption. In addition, companies affected by such legislation could seek to utilize alternative forms of media. In an econometric study on high-income countries, Saffer and Chaloupka 84 noted that comprehensive bans on tobacco advertising tend to reduce consumption.

Community-based intervention programs

Smoking cessation programs also come in the form of community-based interventions to educate, inform, and assist smokers in their quitting attempts. According to Secker-Walker et al, 85 a community intervention is defined as “a co-ordinated, multi-dimensional programme aimed at changing adult smoking behaviour, involving several segments of the community and conducted in a defined geographical area, such as a town, city, country, or other administrative district” (pp. 3). These programs could range from community pharmacy-based interventions to group-based counseling, incentive-based smoking cessation contests, use of self-help quit smoking kit, and, in some cases, mass media campaigns directed at certain communities within a defined geographical area. The aim of this section is to identify and assess global evidence on the effectiveness and cost effectiveness of such interventions.

Nine studies on community-based interventions were reviewed, including studies by Altman et al, 44 Secker-Walker et al, 86 Stephens et al, 82 Secker-Walker et al, 87 , 88 Lightwood et al, 89 Hurley and Matthews, 26 , 30 and Simpson and Nonnemaker. 90 Altman et al, as far back as 1987, studied the cost effectiveness and cost distribution of three community-based smoking cessation programs designed for use in the two education communities of the Stanford Five City Project. These programs included (1) smoking cessation class (eight 1-hour training sessions offered to ~8–25 participants where several quitting techniques were taught); (2) incentive-based smoking cessation contest (a 6-week community smoking cessation prize contest where entrants were assessed and rewarded on the basis of their smoking status and habits); and (3) self-help quit smoking kit (included tips on smoking replacement habits, social support available, public commitment, and record keeping and goal setting, among other tips aimed at providing specific actions to aid individual smoking cessation). Results revealed that the self-help quit had the lowest total cost (US$26,190), lowest quit rate (21%), lowest time requirement for participants, and was the most cost effective (with a CER of $50). However, the smoking cessation class was the most effective, requiring the most time from participants, with a quit rate of 35%, but incurring the highest total costs (US$261,589) and was also least cost effective (US$276). The smoking cessation contest was in-between the other two programs, with a total cost of US$82,925, a quit rate of 22%, and a CER of US$151.

A community pharmacy also provides an excellent setting in which to provide a smoking cessation program, as the pharmacy would have regular contact with residents of the area. Thavorn and Chaiyakunapruk 30 evaluated the incremental cost effectiveness of a community-pharmacist-based smoking cessation (CPSC) in Thailand. They found that the CPSC program yielded cost savings and life year gains to the health system. A series of sensitivity analyses, however, demonstrated that both cost savings and life year gains were sensitive to variations in discount rate and long-term smoking quit rate associated with the intervention (see Supplementary File 2 for more details on the results).

Lightwood et al 89 also examined the effect of California’s Tobacco Control Program (CTCP) on aggregate personal health expenditures in the state. The CTCP, which was established in 1989, offered a comprehensive approach to smoking cessation by altering the existing social norms and values among tobacco users. The campaign featured an aggressive media campaign with three themes, namely the tobacco industry lies, nicotine is addictive, and second-hand smoke kills. It also included a radical public policy change, especially in the area of promoting smoke free environments. The findings of the study revealed that, between 1989 and 2004, the California program led to a reduction in personal health care expenditures to the tune of US$86 billion (in 2004 dollars), which would have been expected without the program. Using 95% confidence interval, the cost savings ranged between $28 billion and US$151 billion.

Hurley and Matthews 26 also presented evidence on the cost effectiveness of Australia’s National Tobacco Campaign (NTC), an intensive mass media antismoking campaign, which was launched in 1997. Using a quit benefits model (QBM), the study predicted that the NTC avoided more than 32,000 cases of COPD, 11,000 cases of acute myocardial infarction, 10,000 cases of lung cancer, and 2,500 cases of stroke. The model also predicted the prevention of about 55,000 deaths, 323,000 life-years gain, and 407,000 QALYs, as well as a health care cost savings of AUD$740.6 million. Thus, the NTC was both effective and cost saving.

The above studies as well as other community-based interventions all reveal that a strong and aggressive tobacco control program do not only reduce the number of smokers and its resulting health benefits but also reduce substantially the health care expenditure associated with smoking prevalence. It is worth noting that the benefits of these initiatives may not have been well established quantitatively in the sense that most of these studies reflect potential uncertainty in the estimates and data used as well as differences in the parameters estimated. In some cases, data sufficient to establish definite causality are also lacking. However, on the balance, the community-based cessation initiatives examined appear to yield substantial net benefits.

Telecoms, media, and technology-based interventions

TMT-based interventions refer to electronic and mass media-related means aimed at offering support to effect changes in smoking behavior in adults and young adolescents. Examples include telephone counseling offered through “quitlines” or “helplines”; radio, TV, and print media; and computer and Internet-based intervention programs. A summary of the results of related TMT-based cost effectiveness studies can be found in Supplementary File 2 .

Telephone counselling, quitlines and text messaging

Telephone services can provide information and support for smokers. Counseling may be provided proactively or offered reactively to callers to smoking cessation helplines. 91 Support can be given in individual counseling sessions or in a group therapy where clients can share problems and derive support from one another. Counseling may be helpful in planning a quit attempt and could assist in preventing relapse during the initial period of abstinence. Although intensive face-to-face intervention increases quit rates, there are difficulties in delivering it to large numbers. Telephone counseling may be a way of providing individual counseling more affordably.

Tomson et al 45 examined the cost effectiveness of the Swedish quitline, a free-of-charge service offered to the smoking population in Sweden to aid cessation. About 31% of the study population (354 callers) reported abstinence after 1 year of the implementation of the scheme, leading to an accumulated number of life year saved of 2,400. The cost per quitter ranged between US$311 and US$401. In comparison with other smoking cessation interventions, the study concluded that the Swedish quitline was cost effective. A more recent study by Rasmussen 40 assessed the cost effectiveness of the Danish smoking cessation telephone service “quitline”. The study was based on the number of quitline callers in 2005. A total 511 ex-smokers were estimated to have gained 2172 life years based on prolonged abstinence over 12 months. Discounting life years (LYs) at 3% per annum, the costs per LYS are €213 for ex-smokers with continued abstinence and €137 for ex-smokers with point prevalence abstinence. The sensitivity analysis for a worst case scenario indicates that the costs per LYS are €1199. The author concluded that the Danish reactive telephone counseling to aid smoking cessation appears to be cost effective in comparison with other Danish smoking cessation interventions.

Farrelly et al 92 took a rather different dimension to the study of quitlines by assessing the relative effectiveness and cost effectiveness of television, radio, and print advertisements in generating calls to the New York smokers’ quitline. The results showed that there was a positive and statistically significant association between the call volume and expenditures for television ( P < 0.01) and radio ( P < 0.001) advertisements and a slightly significant effect for expenditures on newspaper advertisement ( P < 0.065). Though television advertising had the largest effect on call volume, differences in advertising costs for different media implied that call volume on the quit-line was least responsive to increases in expenditure on television advertising (0.1%) per US$1000 increase compared to the other mass media: radio (5.7%) and newspaper (2.8%). While it was difficult to determine the optimal mix of expenditures, the bottom line is that all three mass media effectively raised the number of callers to the New York quitline.

Another telecom-based intervention measure is the use of mobile phone text messaging facilities to aid smoking cessation. A study by Guerriero et al 93 used a cohort simulation model to determine the cost effectiveness of smoking cessation support delivered by mobile phone text messaging in the UK, called “Txt2stop”. The cost effectiveness was measured in terms of cost per quitter, cost per life year gained, and cost per QALY gained. The cost of text-based support per 1,000 enrolled smokers was £16,120, which, given an estimated 58 additional quitters at 6 months, equates to £278 per quitter. However, when the future NHS costs saved (as a result of reduced smoking) are included, text-based support would be cost saving. It is estimated that 18 LYs are gained per 1,000 smokers (0.3 LYs per quitter) receiving text-based support, and 29 QALYs are gained (0.5 QALYs per quitter). The deterministic sensitivity analysis indicated that changes in individual model parameters did not alter the conclusion that this is a cost-effective intervention. Similarly, the probabilistic sensitivity analysis indicated a >90% chance that the intervention will be cost saving.

Mass-media-led interventions

Mass media interventions consist of the dissemination through television, radio, print media, and billboards of cessation-related messages, informing smokers and motivating them to quit. Mass media campaigns can be effective in keeping tobacco control on the social and political agenda, in reinforcing community action, and in triggering other interventions. Campaigns are designed either directly to change individuals’ smoking behavior (the risk factor model) or to catalyze other forces of social change (the social diffusion model), which may then lead to change in the social norms about smoking. 94 Social diffusion campaigns, such as those run in Australia, Canada, UK, Thailand, and in some US states, are designed to de-normalize smoking, thus counteracting the tobacco industry’s message that smoking is desirable and harmless.

While many studies have revealed that mass media interventions are effective in reducing smoking prevalence among adults, not many studies have commented on the cost effectiveness of such campaigns. Villanti et al 95 evaluated the cost effectiveness of the American Legacy Foundation’s national “EX” campaign, which ran on radio and TV in 2008 and was designed to promote smoking cessation among adult smokers. The incremental societal cost of EX, in 2009 dollars, was US$166 million. Data from eight designated media market areas studied indicate that, in a hypothetical nationwide cohort of 2,012,000 adult smokers ages 18–49, EX resulted in 52,979 additional quit attempts and 4,238 additional quits and saved 4,450 QALYs. Incremental cost-utility estimates comparing EX to the status quo—that is, the situation that would have existed in eight markets with no campaign and no change in cessation behavior—ranged from a cost of US$37,355 to US$81,301 per QALY, which suggests that the campaign was cost effective. These findings are consistent with previous evidence that national mass media campaigns for smoking cessation in the US can lower smoking prevalence in a cost-effective manner. However, in a study on the cost effectiveness of online, radio, and print tobacco control advertisements targeting 25–39-year-old males in Australia, Clayforth et al 42 found that online advertising could be more cost effective than other non-television advertising media such as radio and press in reaching and affecting target audiences, implying that online campaigns may be a highly cost-effective channel for low-budget tobacco control media campaigns (see Supplementary File 2 for details).

Computer- and internet-based programs

Personal computers, the Internet, and other electronic aids, which are now an indispensable part of daily life for many people around the world, also offer additional means of effecting changes to smoking behavior. These electronic-based measures have been found to be effective and cost effective in reducing smoking prevalence among adults (see 35 , 96 , 97 ). For example, computer-tailored programs that entail the adaption of the content of an intervention to participants’ individual characteristics using computer programs have been found to be both effective and economically efficient. 41 Most often, a questionnaire is used as a screening instrument, in which case answers provided by the smokers on the questions are accumulated into a large data file and are subsequently matched with relevant feedback messages that are ultimately combined into a tailored feedback letter. Tailored interventions are more effective in attracting and keeping a smoker’s attention, resulting in better processing of information. Civljak et al 97 found that Internet programs that were interactive and tailored to individual responses led to higher quit rates than usual care or written self-help at 6 months or longer. There are two types of computer-tailored programs: single computer-tailored programs and multiple computer-tailored programs. A single-tailored feedback message is successful in increasing cessation rates, but dynamically tailored feedback provided on multiple occasions can even be more effective. Due to the automatic generation of the tailored feedback and the fact that computer-tailored interventions are increasingly delivered online, the integration of an internet-based computer-tailored program in the general practice setting might limit the burden on health professionals and patients, reduce facility and administrative costs, and could potentially be time and cost saving. 41 However, the Internet may offer additional benefits when combined with usual pharmacological interventions, such as NRT, varenicline, or other pharmacotherapy.

School-based interventions

Though the majority of smoking-related deaths occur in people aged 35 years or older, the onset of tobacco use occurs primarily in early adolescence, which makes adolescents a special target for smoking prevention projects. Schools have been identified as an ideal site to deliver tobacco prevention programs since they capture the majority of youth across a large age range, including the ages when most young people initiate smoking. The main perceived advantages of school-based intervention programs are that almost all children can be reached through schools, and a focus on education fits naturally with the daily activities of schools. 98 Researchers often employ five types of school-based intervention programs, each based on a different theoretical orientation: (1) information-only curricula, ie, interventions that provide information to oppose tobacco use (also called normative education). These educational programs provide content and activities that seek to correct inaccurate perceptions regarding high prevalence of tobacco use; (2) social competence curricula, a group of interventions that aim to help adolescents refuse offers to smoke by improving their general social competence—including training on life skills such as self-control, self-esteem, decision making, and cognitive skills for resisting interpersonal and media influences; (3) social influence curricula, educational programs that seek to inform youths about the effects of outside influences such as advertising on their behavior, teach them that smoking is not the norm, and give them the skills to refuse cigarettes; (4) combined social competence and social influences curricula, methods that draw on both social competence and social influence approaches, and (5) multimodal programs, which combine curricular approaches with wider initiatives within and beyond the school, including programs for parents, schools, communities, and initiatives to change school policies about tobacco, or state policies about the taxation, sale, availability, and use of tobacco.

Although numerous school-based smoking prevention trials have found short-term decreases in smoking prevalence by up to 30%–70%, there is little or no evidence on the long-term effectiveness of school-based smoking prevention programs. 98 – 100 Tengs et al 101 have reported that the effectiveness of anti-tobacco education programs using the “social influences” model tends to dissipate in 1–4 years, raising questions about the long-term economic efficiency of such initiatives. Using a system-dynamics computer simulation model based on secondary data, the authors evaluated the cost effectiveness of an enhanced nationwide school-based anti-tobacco education and found that over 50 years, cost effectiveness is estimated to lie between US$4,900 and US$340,000 per QALY, depending on the degree and longevity of program effectiveness. Assuming a 30% effectiveness that dissipates in 4 years, cost effectiveness is US$20,000/QALY. A similar study on the cost effectiveness of a school-based tobacco use prevention program in the US, known as Toward No Tobacco Use (TNT), showed that the program was highly effective as the government could expect to save US$13,316 per LY saved and a saving of US8,482 per QALY saved. However, a peer-led intervention, known as ASSIST, aimed at reduced smoking among adolescents in England and Wales, was only valued to yield a modest cost saving, with an incremental cost per student not smoking after 2 years of follow-up at £1,500 (CI = £669–£9,947). Other cost-effectiveness studies on school-based smoking cessation programs are summarized in Supplementary File 2 . From all of these studies, an issue that remains unresolved is the extent to which reductions in adolescent smoking lead to lower smoking prevalence and/or earlier smoking cessation in adulthood.

Workplace interventions

There has been growing interest within the business community regarding interventions against smoking in the workplace. Smoking interventions in the workplace particularly have numerous advantages. First, a large number of people can be contacted, canvassed, and enrolled in programs with relative ease, sometimes with the aid of extensive onsite occupational health facilities. 102 Second, worksites have the potential for higher participation rate than non-workplace environments. Third, worksites have the potential to provide sustained peer group support and positive peer pressure for quitting and staying tobacco-free. Fourth, it provides a particular opportunity to target young men, who traditionally have low general practitioner consultation rates and are thus less likely to benefit from opportunistic health promotion activity in primary care. Fifth, in some workplaces, occupational health staff may be on hand to give professional support. Finally, the employee need not travel to attend cessation programs; hence the workplace provides convenience benefits to the employee. 103 , 104 It is worthy of note that many of these assumptions are based on a model of workplace that is rapidly changing. With many generation-Y employees who change jobs frequently or work from multiple locations, the net benefits from workplace cessations could be expected to become marginal in the long run.

Workplace smoking interventions can take numerous forms, including pharmacological interventions, behavioral interventions, or a combination of both. It could target individuals or specific employee groups. The main strategies include smoking prohibition, incentives, competitions, individual and group counseling, self-help materials, pharmacological therapy, and social and environmental support.

Many health economics researchers have found empirical evidence to support the general belief that smoking intervention programs help a firm’s bottom line by reducing health care costs, absenteeism, and its attendant productivity losses and other employer-related costs. 105 However, there are serious challenges to the reliability and validity of their findings, as some critics of this literature have cited systematic biases affecting the credibility of some of these studies. These biases often manifest themselves in underestimation of costs and overestimation of benefits. Other researchers who have carried out behavioral workplace interventions have found a strong consistency in the correlation between smoking interventions and reduced cigarette consumption and decreased exposure to environmental tobacco smoke. 106 Smedslund et al 103 also compared the cost effectiveness of behavioral workplace interventions compared to pharmacological interventions and found that controlled smoking cessation trials at the worksite showed initial effectiveness, but the effect seemed to decrease over time and was not present beyond 12 months. Jackson et al, 107 however, showed that pharmacological interventions at the workplace seemed to generate 12-month employer cost savings per nonsmoking employee of between $150 and $540. The authors however found that varenicline was more cost beneficial than placebo because it had higher quit rates. Warner et al 105 also found that smoking cessation is a very sound economic investment for the firm, and is particularly profitable when long-term benefits are included, with an eventual benefit–cost ratio of 8.75. Other studies by Ong and Glantz 108 also showed that the first year effect of making all workplaces in the US smoke-free would produce about 1.3 million new quitters and prevent over 950 million cigarette packs from being smoked annually, worth about US$2.3 billion in pretax sales to the tobacco industry. In addition to preventing the risk of smoking-induced diseases such as myocardial infarctions and strokes, smoke-free work places could result in nearly US$49 million in savings in direct medical costs after 1 year. At steady state, more than US$224 million would be saved in direct medical costs annually (see Supplementary File 2 for summary of results).

Overall, this section has examined evidence across countries on the economic impact of smoking and the effectiveness and cost effectiveness of reducing smoking prevalence through intervention programs. It has examined the health-and non-health-related costs and benefits of smoking as well as the effectiveness and cost effectiveness of pharmacological, policy-based, community-based, TMT-based, school-based and workplace- or employer-based smoking cessation interventions carried out through the years by different countries or state public health agencies. Key statistics and examples were drawn from United States, China, Australia, Canada, Hong Kong, Belgium, Taiwan, India, France, and Sweden. Next, this study narrows down by reviewing the economics of smoking in United Kingdom.

The Economic Impact of Smoking and Smoking Cessation Interventions in UK

The costs and benefits of smoking in uk.

Smoking has also been responsible for over 100,000 deaths per annum over the last decade in UK. The number of deaths attributable to smoking in 2005 was estimated at 109,164. 8 The financial and health burden of smoking in UK is enormous. Previous studies have estimated the direct costs of treating smoking-related diseases by the NHS to range somewhere between £1.4 and £1.7 billion every year. 10 , 56 , 109 , 110 A more recent study conducted by Callum et al 12 showed that smoking-attributable costs to the NHS in 2006 was estimated at £2.7 billion. This includes smoking attributable hospital admissions (£1 billion), outpatient attendances (£190 million), general practitioner (GP) consultations (£530 million), practice nurse consultations (£50 million), and GP prescriptions (£900 million). Allender et al 8 estimates the costs of smoking-induced ill health to the NHS to be £5.2 billion in 2005–2006, representing about 5.5% of the total NHS budget that year e (see also 7 ). The cost of smoking in UK is thus increasing every year. The estimates provided by the above studies, however, are conservative cost estimates because they do not include the indirect costs of passive smoking and productivity losses due to smoking-related morbidity and premature mortality. The costs of informal care, smoking-related fires, cleaning costs, and sickness absence payments were also excluded from these estimates.

Cohen and Barton 56 show that approximately 50 million working days f are lost in UK annually due to smoking, valued at £1.71 billion. The British Medical Association 112 estimates that each year in UK, at least 1,000 deaths are attributable to passive smoking and more than 17,000 children under the age of five are admitted to hospital because of the ill effects of second-hand smoke. Parrott and Godfrey 10 have estimated that each year in UK the cost of treating childhood illnesses related to smoking is about £410 million. The same study estimates the damage caused by smoking-related fires to be around £151 million each year in England and Wales. If all these indirect costs estimates are included to the NHS figures, the financial burden of smoking in UK will skyrocket. A more recent report by the Policy Exchange in 2010 attempts to sum up the total estimated costs to society of smoking in UK and puts the figure at £13.74 billion. This includes £2.7 billion cost to the NHS but also the loss in productivity from smoking breaks (£2.9 billion), and increased absenteeism (£2.5 billion). Other costs include cleaning up cigarette butts (£342 million), the cost of fires (£507 million), the loss of economic output from the death of smokers (£4.1 billion), and passive smokers (£713 million).

The study by Allender et al 8 shows the percentage attributable to smoking of total NHS costs for smoking-related conditions in 2005–2006 by countries in UK (see Table 1 ). In England, the cost of smoking is £4.3 billion and this represents about 85% of the total smoking attributable costs in UK. For Wales, Scotland, and Northern Ireland, smoking-attributable cost was £234.2 million, £409.4 million and £127.9 million, respectively. Following the analysis made by this study, the smoking-attributable fraction (SAF) in UK was estimated at 23%. The SAF represents the costs attributable to smoking for smoking-related conditions, as a proportion of total NHS expenditure for those conditions. The smoking-related conditions considered included cardiovascular diseases, COPD, other respiratory conditions, lung/bronchus/trachea cancer, mouth and oral cancer and peptic ulcer disease.

Percentage of NHS costs attributable to smoking in 2005–2006 by countries in UK. 8

In spite of the costs of smoking in UK, there are potential economic benefits that smoking brings to the economy. Just like in other countries, tobacco is a major revenue earner for the government. Thus, a reduction in the prevalence of smoking will bring about significant loss to the Exchequer. According to the HM Revenue and Customs 112 Tobacco Bulletin and Factsheets, the treasury earned £9.5 billion in revenue from tobacco duties in the financial year 2011–2012 (excluding VAT). This amounts to 2% of the total government revenue. Including VAT at an estimated £2.6 billion, total tobacco revenue was £12.1 billion. 113 The price of a pack of 20 premium brand cigarettes currently costs around £7.98, of which £6.17 (or 77%) is tax. 114 The economic benefits of smoking from taxation alone thus appear to be noticeably higher than the direct costs of smoking in UK. A CBA of the effects of increasing tobacco taxation commissioned by ASH (in 115 ) found that a tobacco price increase of 5% would result in net benefits to the economy as a whole of around £10.2 billion over 50 years. The economic benefits in the first 5 years would be around £270 million per year on average.

Apart from government taxation, tobacco companies make huge profits from sale of tobacco products. In 2012, British American Tobacco, which is the world’s second largest tobacco company, produced 694 billion cigarettes worldwide (down from 705 billion in 2011) and reported an operating profit of £5.14 billion, an increase of 15% on 2011. 116 The two major UK tobacco companies—Imperial Tobacco and Gallaher (the latter now owned by JTI)—control around 85% of the UK market.

The economic benefits of smoking in UK could also be seen in terms of employment in the tobacco and dependent industries. According to the National Statistics from Tobacco Manufacturers Association, 117 approximately 5,700 people are employed in tobacco manufacturing in UK. It has been argued that a reduction of smoking might not necessarily imply an overall increase in unemployment. It may well boost employment and output. 56 , 118 , 119 The argument is that, though there will be loss of job in the tobacco industry following smoking cessation, money not expended on tobacco will then be spent elsewhere, thereby increasing the demand for other goods and services, and hence generating employment for some other sectors. The extent, to which this happens, however, depends on the spending patterns of the former smokers. McNicoll and Boyle 118 estimated that a total cessation of cigarette purchases in Glasgow will bring about net benefits to the Scottish economy. They estimated that for every £1 million reduction in cigarette expenditure, there would be a net increase in Scottish output of £1.1 million and a net increase of Scottish employment of 64 jobs. In a similar study by Buck et al, 119 a 40% reduction in smoking—a target set by the 1992 UK Policy document—will have estimated effects of increasing jobs in the UK by 150,000. As noted earlier, a smoking population also has the benefit of achieving savings in pension payments from the premature death of smokers. Manning et al 120 have estimated that every pack of cigarettes smoked reduces the life expectancy by 137 minutes and pension costs by $1.82.

The effectiveness and cost effectiveness of UK-specific smoking cessation programs

This section takes a look at the effectiveness and cost effectiveness of smoking cessation interventions that are specific to the UK and identifies where there are any cost savings or net benefits to the health care system arising from a reduction in smoking prevalence. It reviews high-quality evidence on the economics of smoking cessation programs implemented in the different parts of UK. In 1998, the UK government for the first time took a comprehensive approach to the reduction of smoking prevalence in England when it published a policy paper (called a White Paper), Smoking Kills. This program was aimed at reducing smoking among children and adolescents, and help adult smokers, particularly the disadvantaged ones (including pregnant women) to quit smoking. The strategy involved ban on tobacco advertising, further increases in tobacco prices g , measures to reduce smoking in workplaces and in public places, measures to restrict the sale of tobacco to minors h , and also, for the first time in the history of NHS, the commitment of huge resources to smoking cessation treatment services. Smoking Kills has been able to reduce the average prevalence of smoking in adults (16 years+) in England from 27% before the implementation period to 21% in 2008. 121

NHS smoking cessation treatment services

The White Paper, Smoking kills , sets out guidelines for the provision of specialist smoking cessation services. The United Kingdom was the first country to introduce a national smoking cessation treatment program funded through public taxes. 122 Since then, other countries have implemented similar treatment services, eg, Japan and Taiwan. Since 2000, many smokers have received behavioral support through counseling or special training sessions to aid smoking cessation. In England and other parts of UK, smokers can purchase NRT products from local pharmacies and shops. A report from the National Institute for Clinical Excellence (NICE) 123 in March 2002 showed that NRT and bupropion are some of the most cost-effective treatments of all pharmacological interventions. Their cost effectiveness has been estimated by NICE in terms of cost per life year gained (LYG); NHS treatment services produce a cost of about £3000 per LYG and about £2000 when adjusted using UK discount rates (estimates cited in Ref. 124 , pp. 5). Stapleton 125 reveals that calculations based on the reported performance of the NHS specialist smoking cessation services suggest they are highly cost effective, generating a cost of less than £800 per life-year saved. The same study reveals that during April 2000 and March 2001, about 126,800 smokers made an attempt to quit smoking while attending cessation services. Of these, 48% were abstinent at the end of 4 weeks. The total costs (including treatment and administrative costs) were £21.4 million or £209 when expressed per patient treated.

According to a more recent report for 2005, an estimated 2 million smokers in UK used NRT products (and to a much lesser extent bupropion) to aid in stopping smoking. 122 The effectiveness of these treatment services has also been estimated at ~2%–3% abstinence rates. In all, about 90,000 smokers (out of an estimated 12 million smokers in UK) stopped smoking permanently in 2005, implying that about 0.75% of smokers became ex-smokers due to smoking cessation treatments.

Two very recent studies have also examined the cost effectiveness of NRT, bupropion, and varenicle for preventing or reducing relapse to smoking by abstinent smokers following smoking cessation. 27 , 126 Their findings revealed that, like other interventions, relapse prevention interventions (RPIs) are also likely to be highly cost and clinically effective. When compared to no intervention, using bupropion for relapse prevention resulted in an incremental QALY increase of 0.07 with a concurrent NHS cost saving of £68; NRT and varenicline both caused incremental QALY increases of 0.04 at costs of £12 and £90, respectively. Extensive sensitivity analyses from both studies demonstrated that cost-effectiveness ratios were more sensitive to variations in RPI effectiveness than cost. In addition, even after varying key model parameters, the cost effectiveness of NRT and bupropion generally remained. Cost effectiveness ratios only exceeded the UK NICE benchmark of £20,000 per QALY when drug treatment effects were projected to last for only 1 year.

In summary, NHS treatment services and relapse prevention intervention services have been both clinically and cost effective, generating substantial health and cost savings that are acceptable to health care providers.

Community pharmacy-based smoking cessation

Crealey et al 127 have looked at the cost effectiveness of a community pharmacy-based smoking cessation program in Northern Ireland. Data from a pilot study conducted in two community pharmacies in Belfast were used as the basis of the current study, which examined the costs and effects associated with a formal counseling program for smoking cessation by community pharmacists across Northern Ireland. The Pharmacists Action on Smoking (PAS) model was the only active intervention used in the study. Findings indicate that the cost per life year saved when using the PAS program ranges from £196.76 to £351.45 in men and from £181.35 to £772.12 for women (1997 values), depending on age. This compares favorably with other disease prevention medical interventions such as screening for hypertension or hypercholesterolemia. More recently, Boyd and Briggs 128 examined the cost effectiveness of pharmacy-based versus group behavioral support in smoking cessation services in Glasgow. This study was based on the premise that smokers attending group-based support for smoking cessation are significantly more likely to be successful than those attending pharmacy-based support. The study was conducted using a combination of observational study data and information from the NHS Greater Glasgow and Clyde smoking cessation services. Findings revealed that incremental cost per 4-week quitter for pharmacy-based support was found to be approximately £772 and £1612 for group support, dismissing the earlier hypothesis. Furthermore, estimated incremental cost per QALY for pharmacy-based service is £4400 and £5400 for group support service. The study, however, concludes that both group support and pharmacy-based support for smoking cessation are highly cost effective.

Action Heart promotion program

Action Heart is a cost-effective, community-based heart promotion project, which was implemented between 1991 and 1995 in Wath and Swinton, England. Baxter et al 129 carried out a prospective comparative study to establish whether this community-based coronary heart disease health promotion intervention, undertaken over 4 years, was associated with a reduction in the prevalence in adults of risk factors associated with heart disease, including smoking, as well as to estimate the cost effectiveness of this intervention. Smoking prevalence before and after the intervention was assessed using a questionnaire mailed to residents in both the intervention and control areas. Smoking decreased in the intervention area and increased in the control area between 1991 and 1995. Results showed that the intervention achieved a smoking abstinence rate of 6.9%, while 8.7% more of the sample population consumed low-fat milk between the intervention and control area in the 4-year period. The differences between the areas rose from 4.2% to 9.2%. Total project cost (including allowances for community project officer and worker, consumables and other overheads, other NHS staff, school expenditure, etc) was £110,000. The estimated cost per life year gained was £31.

Heart beat wales (HBW)

Phillips and Prowle 22 also appraised the economics of a no-smoking intervention program named Heart Beat Wales (HBW) carried out between 1985 and 1988. Health benefits were estimated as intermediate and final outcomes. Intermediate outcomes were the reduction in the number of smokers and the amount of tobacco consumed. The final outcomes were presented in the terms of reduced morbidity and mortality in three disease groups—coronary heart disease (CHD), lung cancer, and chronic bronchitis. The program costs included direct cash costs and staff costs. Total cost in year 1 was £72,000, in year 2 £82,000, in year 3 £150,000, and in year 4 £205,000. Results show a net present value of benefits to NHS of £4,134,000. The “economic” appraisal has a present value of benefits of £43,503,000. The estimated cost of a working life year saved is £5.78. The net present value of benefits from reductions in smoking is significantly greater than costs in terms of both the NHS and the economy as a whole in Wales. In addition, the net costs per life year saved reveals that the program generates additional working life years at relatively low cost.

No smoking day

More than two decades after the launch of the “No Smoking Day” (NSD) in UK, Owen and Youdan 130 and Kotz et al 131 evaluated the impact and relevance of this national awareness day. Launched in 1984, the campaign seeks to create an enabling environment for smokers to quit smoking. When the campaign began, smoking prevalence in the UK was more than 33% of adults; in 2003 it dropped to 25%. The campaign expenditure ranges somewhere between £470,000 and £550,000 annually. Results show that follow-up after 1 week indicates awareness of NSD is lower in 2004 than in 1986, 2 years after it was launched. However, awareness is still high at 70% for all smokers. Interestingly, the decline in participation from 18% of aware smokers in 1994 to 7% in 2001 was reversed in 2005 when about 19% either gave up or reduced their smoking on NSD. In 2004, NSD awareness had reached 78% of the smoking population. When compared to the 8.5 million smokers in England, the campaign can be deemed to be effective in reaching its target audience. In addition, media coverage has increased regardless of the fact that the campaign expenditure has remained relatively constant and calls to national smokers’ helpline on NSD are typically four times those received on a normal day. The cost of NSD per smoker was £0.088. The discounted life years gained per smoker in the modal age group 35–44 years was 0.00107, resulting in an incremental cost–effectiveness ratio (ICER) of £82.24 (95% CI 49.7–231.6). Thus, the campaign emerges as an extremely effective and cost-effective public health intervention in aiding smoking cessation.

HEBS’s mass media-led intervention

Ratcliffe et al 132 evaluated the costs and outcomes of a mass media-led antismoking campaign in Scotland, which was conducted by the Health Education Board for Scotland (HEBS). The campaign had three elements or features, namely 1) mass media advertising, including television, outdoor posters, and press; 2) Smokeline , a free telephone quitline to aid smoking cessation; and 3) You can stop smoking , a practical handbook aimed at guiding smokers to renounce smoking. At the end of a 12-month period, about 9.88% of individuals in the follow-up sample reported they have renounced smoking since 6 months after the campaign. The costs of the campaign (including the youth campaign costs) ranged from £1,486,101 to £1,546,420. In terms of costs per quitter, estimates ranged from £189 to £369. The costs per life year saved attributable to the campaign ranged from £304 to £656. Another mass media campaign based on behavior change theory and operating through both traditional and new media, known as Stoptober , was launched in England during late 2012. Brown et al 133 found that Stoptober was both effective and cost effective, as it generated up to 350,000 quit attempts and saved 10,400 discounted life years (DLY) at less than £415 per DLY in the modal age group.

This section has reviewed the economic impact of smoking and reducing its prevalence in UK. Though smoking is beneficial to the UK both in terms of tax revenue and employment, the health- and non-health-related costs of smoking to the NHS and the society far outweigh any benefits that might be accruable at least from a socially desirable perspective. Most smoking cessation interventions implemented in the UK have also been highly effective, reducing the number of smokers and any health risks associated with smoking.

This study reviews major studies on the economics of tobacco smoking and the economic impact of reducing its prevalence both globally and in UK. The findings from the review reveal that tobacco smoking is the cause of many preventable diseases and premature deaths in UK and around the world. It poses enormous health- and non-health-related costs to the affected individuals, employers, and the society at large. The WHO estimates that, globally, smoking causes over US$500 billion in economic damage each year. In the UK, the total estimated costs of smoking to society could be put at £13.74 billion. In the US, a much larger economy by population and GDP, the social cost of smoking is more than 8 times that of UK—US$193 billion (or ~£114 billion) according to estimates from Kahende et al, 5 though this figure is even larger when we consider latest estimates from the Campaign for Tobacco-Free Kids, which puts the social cost of smoking at US$321 billion. 59 About 15% of the aggregate health care expenditure in high-income countries can be attributed to smoking. In the US, the proportion of health care expenditure attributable to smoking ranges between 6% and 18% across different states. In the UK, the direct costs of smoking to the NHS have been estimated at between £2.7 billion and £5.2 billion, which is equivalent to around 5% of the total NHS budget each year. The economic burden of smoking estimated in terms of GDP reveals that smoking accounts for approximately 0.7% of China’s GDP and approximately 1% of US GDP. As part of the indirect (non-health-related) costs of smoking, the total productivity losses caused by smoking each year in the US have been estimated at US$151 billion. Smoking is therefore considerably expensive to countries where its prevalence is high, particularly high-income countries. The costs notwithstanding, smoking has some potential economic benefits to most economies. The economic activities generated from the production and consumption of tobacco provides economic stimulus. It also produces huge tax revenues for most governments, especially in high-income countries, as well as employment in the tobacco industry. Income from the tobacco industry accounts for up to 7.4% of centrally collected government revenue in China. Smoking also yields cost savings in pension payments from the premature death of smokers.

Several measures have been undertaken by most countries (including UK) over the years in order to reduce the prevalence of smoking in adults, children, and pregnant women. These measures range from pharmacological treatment interventions (such as the use of NRT, bupropion, and varenicle) to policy-based measures (tax increases, smoking restrictions, bans on tobacco advertising, etc), community-based interventions (such as smoking cessation contests, classroom education, self-help quit kit, etc), TMT-based measures (such as quitlines, mass media led interventions, internet- and computer-based measures), school-based measures, and workplace interventions. We now discuss some of the findings from the review by comparing results across types of intervention, implementation countries, and measurement outcomes, where possible.

Comparing the effectiveness and cost effectiveness of various interventions

From the review of pharmacological and medical treatment interventions for smoking cessation across countries, it was found that cost per life year saved ranged between US$128 and US$1,450 and up to US$4,400 per QALY saved. Comparing various types of pharmacological interventions, existing studies showed that varenicline (with or without behavioral interventions) seemed to be the most cost-effective therapy, followed by bupropion and NRT. However, the results have a high risk of bias because the manufacturer of varenicline funded most of the studies comparing varenicline with bupropion or NRT. In the UK, it was found that the use of NRT and/or bupropion combined with GP counseling was both clinically effective and cost effective to primary health care providers.

Some studies reveal that pharmacological treatments tend to yield more positive results in terms of number of quitters than other cessation interventions (eg, NRT programs could yield as much as 18,500 quitters at a cost of US$4,440 per QALY compared to implementing a smoke-free workplace policy, which would generate 10,400 quitters at US$506 per QALY). The use of pharmacotherapies such as varenicline when combined with other behavioral treatment interventions (such as proactive telephone counseling and Web-based delivery, or both) is cost effective when measured from both cost per LY and cost per QALY, with costs per additional 6-month nonsmoker and per additional life time quitter ranging from US$1,278 to US$1,617 and from US$2,601 to US$3,291, respectively.

With respect to policy-based measures, increase in tobacco taxes is unarguably the most effective means of reducing the consumption of tobacco and hence the health care costs associated with treating smoking-caused diseases. Findings show that a 10% tax-induced cigarette price increase anywhere in the world reduces smoking prevalence by between 4% and 8%. Apart from reducing the number of smokers and saving lives, increasing tobacco taxes also raise government revenue accruable from tobacco manufacturers and retailers. Thus, as cigarette taxes increase, government tax revenues continue to rise even as smoking prevalence falls. In fact, net public benefits from tobacco tax remain positive only when tax rates are between 42.9% and 91.1%. However, increase in tobacco taxes increases the risk of reduction in employment in tobacco companies and the incidence of cigarette smuggling and tax evasion, further dwindling the net benefits from tax increases. Non-price-based measures (such as smoking restrictions in work places, public places, bans on tobacco advertisement, and raising the legal age of smokers) have also proven to be both effective and cost saving. The health and economic benefits of such measures include reduction in smoking prevalence, reduction in second hand smoke, savings from smoking-related medical expenditures, heart diseases averted, costs averted by a reduction in smoking-induced fires, and gains in productivity. Findings show that the cost–effectiveness ratio of implementing non-price-based smoking cessation legislations range from US$2 to US$112 per LYG, while reducing smoking prevalence by up to 30%–82% in the long term (over 50-year period).

From the perspective of the public health system, community-based intervention programs yield cost savings and life year gains. There are, however, differences in the effectiveness and cost effectiveness of different types of community-based interventions. Smoking cessation classes are known to be most effective among community-based measures since they require more time commitment from participants. They could lead to a quit rate of up to 35%, but they usually incur higher costs. On the other hand, self-help quit smoking kits usually require the lowest time commitment from participants and are usually the most cost effective. Community pharmacies also provide opportunities for regular contact with residents of a local community. On average, community pharmacist-based smoking cessation programs yield cost savings to the health system of between US$500 and US$614 per LYG. Knowledge of the health and economic gains of different community-based measures is highly desirable when health policy decision makers plan the allocation of resources for smoking cessation at the community level. One classic example of an effective community-based campaign is the UK’s “No Smoking Day”. After almost three decades of its launch, the campaign has achieved a 78% awareness rate. It has also reduced smoking prevalence by 14%. With the cost of NSD per smoker at £0.088 and ICER of £82.24, NSD emerges as an extremely cost-effective public health intervention.

Since many people are ambivalent about smoking, it has been widely held that advertising media, telecommunications, and other technology-based interventions usually have positive synergistic effects. In fact, as many studies show, an integrated approach involving a combination of multiple media to deliver a message produces greater effects than relying on one medium alone. However, the outcomes on the effectiveness and cost effectiveness of TMT-based measures have been inconsistent. For example, Farrelly et al 92 examined the effects of expenditure on TV, radio, and print advertising and concluded that, while TV advertising produced the greatest yielded proportionally higher increases in the call rate. Clayforth et al 42 found that online-only advertising campaigns can be substantially more cost effective than other non-television advertising media such as radio, and print media, including when an integrated approach is used. Chen et al 34 , 35 also found that making some form of electronic support available to smokers actively seeking to quit (eg, PC, internet, and other electronic aids) is highly likely to be cost effective. This is true whether the electronic intervention is delivered alongside brief advice or more intensive counseling.

The differences in reported cost effectiveness may be partly attributed to varying methodological approaches, including different inputs used to determine model parameters, especially the different dependent variables tested (eg, calls to a quitline versus intention to quit; visits to a quit website versus online registration to smoking cessation services), disparate levels of resourcing between campaigns, differences in national contexts, and differences in advertising campaigns tested on different media. For example, radio is limited to sound, while traditional print media is confined to static pictures. Further, it is difficult to isolate the effects of individual media due to the tendency for campaigns to typically involve the simultaneous use of different media to optimize results. In such circumstances, it is difficult to attribute results to specific media. Some studies have, however, shown that under a wide variety of conditions, the use of personalized smoking cessation service advice, when combined with telephone counseling, mobile phone messages, or other personalized computer-based intervention measures, is both beneficial for health and cost saving to a health system.

In evaluating the effectiveness of school-based intervention programs aimed at preventing smoking in children and adolescents, many studies have conducted analysis of peer-led programs, analysis of social influences, social competences, gender effects, class competitions, and booster sessions, among other measures. Thomas et al 98 found that all these theoretical approaches were very effective in aiding smoking cessation particularly in the number of youths that were prevented from starting smoking. Numerous smoking prevalence trials have found short-term decreases in smoking prevalence of between 30% and 70%. As with other intervention programs, determining that a program is effective may not be sufficient to justify its implementation since the resources to fund school-based smoking prevention programs are limited. Because of limited financial resources, most school-based smoking cessation programs are usually carried out in multiple schools, most times covering thousands of students across communities or regions within the countries of implementation (eg, TNT in USA; ASSIST in England and Wales; MYTRI in India; SFC in Germany). Total intervention costs could range from US$16,400 to US$580,000 depending on the scale and scope of intervention, and these costs usually cover personnel expenses, costs of materials, travel expenses, and program administration costs. Most studies evaluating the cost effectiveness of school-based programs show that one could expect a saving of approximately between US$2,000 and US$20,000 per QALY saved due to averted smoking after 2–4 years of follow-up.

Finally, from the economic evaluation of smoking cessation activities at the workplace, it is evident that employer-based interventions could be beneficial to both employers and the society at large. For example, Warner et al 105 found that smoking cessation is a very sound economic investment for the firm, and is particularly profitable when long-term benefits are included, with an eventual benefit–cost ratio of 8.75. Jackson et al 107 also showed that pharmacological interventions at the workplace seemed to generate 12-month employer cost savings per nonsmoking employee of between $150 and $540. Other studies by Ong and Glantz 108 also showed that the first-year effect of making all workplaces in the US smoke-free would produce about 1.3 million new quitters and prevent over 950 million cigarette packs from being smoked annually, worth about US$2.3 billion in pretax sales to the tobacco industry. In addition to preventing the risk of smoking-induced diseases such as myocardial infarctions and strokes, smoke-free work places could result in nearly US$49 million in savings in direct medical costs after 1 year. At steady state, more than US$224 million would be saved in direct medical costs annually.

From a review of these and other economic studies, it can be safely deduced that the economic benefits of employer-based smoking cessation measures are likely to be far more greater than the costs involved, particularly on a long-range basis, since reduced worksite smoking prevalence translates into reduced absenteeism, increased productivity, lower health insurance costs, higher cost savings, and higher overall benefit–cost ratio in the long run. Moreover, the economic advantages of workplace anti-tobacco policies seem to be more visible when smoking at the workplace is completely prohibited and no smoking areas are set.

Limitations of the study

Only a few studies examining the long-term effect of smoking cessation interventions were found. Evidence of long-term health and economic benefits of many cessation interventions such as clinical and workplace interventions remains uncertain. A series of sensitivity analyses from many of the studies also show that both cost savings and life year gains are sensitive to variations in the discount rates and the long-term smoking quit rate associated with the intervention. Thus, there is a high risk of uncertainty in some of the cost estimates provided in this study. Another source of error in comparative analysis is the differences in basis for cost comparisons across countries and the impact of inflation on cost estimates. For example, there are significant differences across countries in terms of basic demographic and socioeconomic characteristics, life expectancy of population, and advancements in health care systems. Thus, calculation of life years saved and medical costs of smoking-related diseases are likely to differ significantly across countries. Also, the inflation rates in developing/emerging countries like India, Thailand, Taiwan, and China are likely to be higher than those in developed countries such as USA, UK, Canada, and Australia where inflation rates are known to be somewhat lower. Hence, some studies may overstate the real cost estimates if not properly discounted (ie, adjusted) for inflation, thus making comparisons across time and countries difficult. Finally, it is worth noting that the results of many studies reviewed may not have been well established quantitatively in the sense that most of these studies reflect potential uncertainty in the estimates and data used and, in some cases, data sufficient to establish definite causality are lacking.

Conclusions

Though tobacco smoking may be economically beneficial, its direct costs and externalities to society far outweigh any benefits that might be accruable at least when considered from the perspective of socially desirable outcomes (eg, a healthy population and a vibrant workforce). There are enormous differences in the application and economic measurement of smoking cessation measures across various types of interventions, methodologies, countries, economic settings, and health care systems, and these may have affected the comparability of the results of the studies reviewed. However, on the balance of probabilities, most of the cessation measures reviewed have not only proved effective but also cost effective in delivering the much-desired cost savings and net gains to individuals and primary health care providers.

Supplementary Data

a Cigarette smoking is a major contributor to chronic obstructive pulmonary disease, peripheral and cerebrovasular disease, coronary artery disease (CAD), cancer of the lung or pharynx, larynx, oesophagus, pancreas, bladder, kidney and cervix, peptic ulcer disease, and nonmalignant diseases of the mouth, 134 , 135 among other smoking-induced illnesses.

b For example, evidence from Kahende et al 5 show that in the US, the medical costs (part of direct costs) and productivity losses (part of indirect costs) caused by cigarette smoking can be estimated to be worth US$193 billion annually.

c Other approaches that are not considered in this analysis include Cost Analysis (CA) and Cost Utility Analysis (CUA)—see Kahende et al 5 ).

d Passive smoking has some causal relationships with coronary heart disease, heart attacks, and chronic respiratory symptoms. For children and infants, SHS exposure can also lead to low birth weight, sudden infant death syndrome (SIDS), childhood respiratory illness and Asthma, amongst others. In US, about 53,000 deaths of nonsmokers can be attributed to passive smoking ( 56 :s39).

e The cost of smoking to the NHS Wales has been estimated to be £386 million in 2007/2008, which is equivalent to £129 per head and 7% of total health care expenditure in Wales. 136

f In England and Wales, more than 34 million days are lost through sickness absence resulting from smoking-related ill-health, while in Scotland the cost of productivity loss is ~£400–£450 million. In addition, smoking-induced fires cost about £4 million per annum in Scotland. 10 , 137

g One major issue associated with tax increases is that of smuggling and tax evasion. In the UK, it is estimated that approximately 40% of cigarettes do not have UK duty paid on them. The average cost of such cigarettes is almost half the price of legitimate ones. Taxation policies therefore need to be accompanied by a radical law enforcement mechanism in order to reduce this problem. 122

h Like in many countries, the UK government forbid children under the age of 16 from purchasing tobacco products. However, the effectiveness of this restriction has been called to question as children are able to obtain cigarettes from their older friends, siblings, or vending machines.

ACADEMIC EDITOR: Zubair Kabir, Editor in Chief

FUNDING: Authors disclose no funding sources.

COMPETING INTERESTS: Authors disclose no potential conflicts of interest.

Paper subject to independent expert blind peer review by minimum of two reviewers. All editorial decisions made by independent academic editor. Upon submission manuscript was subject to anti-plagiarism scanning. Prior to publication all authors have given signed confirmation of agreement to article publication and compliance with all applicable ethical and legal requirements, including the accuracy of author and contributor information, disclosure of competing interests and funding sources, compliance with ethical requirements relating to human and animal study participants, and compliance with any copyright requirements of third parties. This journal is a member of the Committee on Publication Ethics (COPE).

Author Contributions

Conceived and designed the experiments: VE and AB. Analyzed the data: VE. Wrote the first draft of the manuscript: VE. Contributed to the writing of the manuscript: AB. Agree with manuscript results and conclusions: VE and AB. Jointly developed the structure and arguments for the paper: VE and AB. Made critical revisions and approved final version: VE and AB. All authors reviewed and approved of the final manuscript.