173

Chapter 4

The Health Benefits of Smoking Cessation

Introduction 177

Methodologic Challenges 177

Cancer 177

Conclusions from Previous Surgeon General’s Reports 177

Biological Mechanisms 178

Literature Review Methods 178

Epidemiologic Evidence 179

Cancers for Which Previous Surgeon General’s Reports Have Concluded That Smoking Cessation Reduces Risk 179

Cancers for Which Previous Reports Have Not Concluded That Smoking Cessation Reduces Risk 182

Synthesis of the Evidence 205

Conclusions 206

Implications 206

Smoking Cessation After a Cancer Diagnosis 206

Conclusions from Previous Surgeon General’s Reports 206

Literature Review Methods 207

Smoking Cessation and All-Cause Mortality in Cancer Patients 207

Evaluation of the Evidence 207

Temporality 212

Consistency 212

Strength of Association 212

Coherence 212

Synthesis of the Evidence 212

Conclusion 213

Implications 213

Cardiovascular Disease 214

Conclusions from Previous Surgeon General’s Reports 214

Literature Review Methods 214

Relevant Mechanistic Data 214

Mechanisms Through Which Smoking Cessation Could Affect Cardiovascular Disease 216

Summary of the Evidence 219

Smoking Cessation and Subclinical Atherosclerosis 219

Summary of the Evidence 220

Smoking Cessation and Cardiovascular Disease 220

Intervention Studies 226

Observational Studies 226

Summary of the Evidence 234

Smoking Cessation and Coronary Heart Disease 234

Summary of the Evidence 239
174

Smoking Cessation and Cerebrovascular Disease 239

Stroke Subtypes 243

Prognosis of Cerebrovascular Disease 249

Summary of the Evidence 250

Smoking Cessation and Atrial Fibrillation 250

Summary of the Evidence 250

Smoking Cessation and Sudden Cardiac Death 250

Summary of the Evidence 251

Smoking Cessation and Heart Failure 251

Summary of the Evidence 255

Smoking Cessation and Venous Thromboembolism 255

Summary of the Evidence 255

Smoking Cessation and Lower-Extremity Peripheral Artery Disease 255

Prognosis of PAD 259

Summary of the Evidence 260

Smoking Cessation and Abdominal Aortic Aneurysm 260

Prognosis of AAA 265

Summary of the Evidence 265

Summary of the Evidence 265

Evaluation of the Evidence 266

Consistency 266

Strength of Association 266

Temporality 266

Specificity 266

Experiment and Biologic Gradient 266

Coherence, Plausibility, and Analogy 267

Synthesis of the Evidence 267

Conclusions 270

Implications 270

Smoking Cessation After a Diagnosis of Coronary Heart Disease 270

Conclusions from Previous Surgeon General’s Reports 271

Biological Basis 271

Literature Review Methods and Other Methodologic Considerations 271

Epidemiologic and Clinical Evidence 272

Smoking Cessation and All-Cause Mortality in Patients with Coronary Heart Disease 272

Smoking Cessation and Cause-Specific Mortality in Cardiac Patients 299

Smoking Cessation and Risk of Recurrence or New Cardiac Events in Cardiac Patients 299

Summary of the Evidence 302

Methodologic Considerations 302

Evaluation of the Evidence 302

Causal Criteria 302

Temporality 302

Consistency 302

Strength of Association 303

Experiment 303

Specificity 303

Coherence 304

Synthesis of the Evidence 304

Conclusions 304

Implications 305
175

Chronic Respiratory Disease 305

Conclusions from Previous Surgeon General’s Reports 305

Literature Review Methods 306

Chronic Obstructive Pulmonary Disease 306

Smoking Cessation and Chronic Obstructive Pulmonary Disease 308

Epidemiology of Mortality from Chronic Obstructive Pulmonary Disease in Relation to Tobacco Cessation 308

How Smoking Cessation Affects the Decline of Lung Function in Smokers 308

Novel Diagnostics for Assessing the Impact of Smoking Cessation on the Progression of Chronic Obstructive 

Pulmonary Disease 313

Synthesis of the Evidence 316

Conclusions 317

Asthma 317

Smoking as a Risk Factor for Asthma 317

Smoking Cessation, Asthma Symptoms, and Lung Function 317

Smoking Cessation Biomarkers and the Microbiome in Asthma 319

Synthesis of the Evidence 320

Conclusions 320

Implications 320

Reproductive Health 320

Conclusions from Previous Surgeon General’s Reports 321

Literature Review Methods 321

Sources of Bias in Observational Studies of Smoking and Reproductive Health 321

Pregnancy Complications 323

Ectopic Pregnancy 323

Spontaneous Abortion 323

Placental Abruption 324

Placenta Previa 324

Premature Rupture of Membranes 325

Preeclampsia 326

Gestational Weight Gain 327

Gestational Diabetes 339

Birth Outcomes 340

Birth Defects 340

Fetal Growth and Birth Weight 340

Stillbirth, Perinatal Mortality, and Infant Mortality 385

Stillbirth 386

Perinatal Mortality 386

Infant Mortality 386

Female Reproductive Health 390

Fertility 390

Age at Menopause 393

Male Reproductive Health 395

Fertility and Sperm Quality 395

Erectile Dysfunction 395

Synthesis of the Evidence 399

Conclusions 399

Implications 400

References 402

The Health Benefits of Smoking Cessation 177

Smoking Cessation

Introduction

Evidence on the health benefits of smoking cessation continues to expand and evolve since the topic was 

last covered comprehensively in the 1990 report of the 

Surgeon General. This chapter primarily reviews the findings published between 2000 and 2017 on disease risks 

from smoking and how these risks change after smoking 

cessation for major types of chronic diseases, including 

cancer, the cardiovascular and respiratory systems, and 

a wide range of reproductive outcomes. The more recent 

studies expand the observational evidence documenting 

the benefits of smoking cessation and provide insights 

into the mechanisms underlying these benefits. The 

review of the effects of smoking cessation on reproductive 

outcomes documents health benefits of maternal smoking 

cessation across all phases of reproduction, from preconception to birth, and also for male reproductive health. 

Chapter 5 summarizes the health benefits of smoking cessation for all-cause mortality in the general population; 

thus, that topic is not discussed here.

This chapter also addresses the clinically relevant benefits of cessation for mitigating the effects of diseases, particularly in persons with cancer and coronary heart disease. 

This general topic received mention in previous Surgeon 

General’s reports (U.S. Department of Health and Human 

Services [USDHHS] 1982, 1983, 1990, 2004), and the consequences of smoking following a diagnosis of cancer received 

specific attention in the 2014 Surgeon General’s report, 

leading to a conclusion that cigarette smoking has adverse 

causal effects on persons already diagnosed with cancer 

(USDHHS 2014). This chapter also reviews cessation and 

cardiovascular disease and the implications of cessation for 

the natural history of chronic obstructive pulmonary disease.

Observational studies should consider factors that 

might differ between those who quit smoking and those 

who continue to smoke. Some persons may quit smoking 

because they are sick, and health-conscious persons may 

be more motivated to quit. In an effort to address bias 

attributable to “sick quitters,” those with preexisting diseases can be excluded from analyses. This strategy also 

addresses “reverse causation,” or quitting because of the 

development of symptoms or a disease. Whenever possible, observational analyses should also adjust for other 

risk factors that may confound the relationship between 

smoking habits and disease risk.

There are methodologic challenges related to 

assessing smoking cessation and its links to health outcomes in both observational and intervention studies. 

Risks in former smokers should be compared with those 

of current or never smokers, thus necessitating a precise definition of former smoking (Lindstrom 2010); the 

same is true for time since cessation, cumulative smoking 

(e.g., pack-years [which is defined as the number of packs 

of cigarettes smoked per day multiplied by the number of 

years smoked], which incorporates both smoking intensity and duration), and changes in smoking status during 

follow-up.

Methodologic Challenges

Conclusions from Previous 

Surgeon General’s Reports

At the time of release of the 1990 Surgeon General’s 

report, the U.S. Surgeon General and/or the International 

Agency for Research on Cancer (IARC) classified six cancers as causally associated with cigarette smoking: cancer 

of the lung, larynx, oral cavity and pharynx, esophagus, 

pancreas, and bladder (USDHHS 1990). The 1990 Surgeon 

This section reviews evidence from epidemiologic 

studies about the impact of smoking cessation on the risk 

of 12 cancers caused by smoking, as concluded in previous 

Surgeon General’s reports (U.S. Department of Health and 

Human Services [USDHHS] 2004, 2014). The types of cancers reviewed for this section include cancers of the lung, 

larynx, oral cavity and pharynx, esophagus, pancreas, 

bladder, stomach, liver, colon and rectum, kidney, and 

cervix and acute myeloid leukemia (AML).

Cancer
A Report of the Surgeon General

178 Chapter 4

General’s report concluded that smoking cessation 

reduced the risk of these six cancers. That report set forth 

nine conclusions about smoking cessation and cancer 

(Table 4.1). The 2004 and 2014 Surgeon General’s reports 

concluded that smoking causes at least six additional cancers beyond those for which the associations were considered causal in 1990: cancer of the stomach, liver, colon 

and rectum, kidney, cervix, and AML (USDHHS 2004, 

2014). However, the 2004 and 2014 Surgeon General’s 

reports did not explicitly conclude that smoking cessation 

reduces the risk of these six additional cancers. 

Biological Mechanisms

Smoking contributes to carcinogenesis through 

multiple biological mechanisms, including direct genotoxicity, hypermethylation of gene promoters, receptormediated pathways, and inflammation (USDHHS 2010, 

2014; Hecht 2012). In addition, smoking has been shown 

to increase the somatic mutation load (Alexandrov et al. 

2016). Collectively, these mechanisms can act at the early 

and late stages of carcinogenesis, implying that smoking 

cessation could have short- and long-term effects on the 

risk of cancer. Regardless of the specific mechanisms, 

smoking cessation ends further increments to cumulative 

exposure to tobacco smoke and, therefore, is expected to 

reduce the risk of cancers caused by smoking, since cumulative exposure does not increase further, allowing repair 

processes to come into play (USDHHS 2010). The particular 

mechanisms that are most important in smoking-induced 

carcinogenesis likely vary by site, as described below. 

Literature Review Methods

For this report, systematic literature reviews were 

not conducted for the six cancers (lung, larynx, oral cavity 

and pharynx, esophagus, pancreas, and bladder) for which 

the 1990 Surgeon General’s report (USDHHS 1990) concluded that smoking cessation reduces risk. Instead, for 

these sites, this report summarizes new evidence from 

large pooled analyses or meta-analyses that were determined to clarify the consequences of smoking cessation. 

For the six smoking-attributable cancer sites for 

which smoking cessation has not previously been concluded to lower risk (stomach, liver, colon and rectum, 

kidney, cervix, and AML), epidemiologic evidence was 

reviewed in great detail (USDHHS 1990, 2004, 2014). The 

evidence review focused on whether relative risks (RRs) 

(a) are lower for former smokers than for current smokers 

and (b)  decrease in former smokers with increasing 

number of years since cessation. Summary RRs for former 

and current smokers of cigarettes, compared with never 

smokers, were identified from the most recent sufficiently 

comprehensive meta-analyses, as found through literature searches conducted in January 2017 of the National 

Library of Medicine’s PubMed service. For some papers, 

current cigarette smokers were the comparison group for 

former smokers.

Table 4.1 Conclusions from the 1990 Surgeon General’s report on the health benefits of smoking cessation and cancer

Conclusions

1. Smoking cessation reduces the risk of lung cancer compared with continued smoking. For example, after 10 years of abstinence, 

the risk of lung cancer is about 30 to 50 percent of the risk for continuing smokers: with further abstinence, the risk continues 

to decline.

2. The reduced risk of lung cancer among former smokers is observed in males and females, in smokers of filter and nonfilter 

cigarettes, and for all histologic types of lung cancer.

3. Smoking cessation lowers the risk of laryngeal cancer compared with continued smoking.

4. Smoking cessation reduces the severity and extent of premalignant histologic changes in the epithelium of the larynx and lung.

5. Smoking cessation halves the risks for cancers of the oral cavity and esophagus, compared with continued smoking, as soon as 

5 years after cessation, with further reduction over a longer period of abstinence.

6. Smoking cessation reduces the risk of pancreatic cancer, compared with continued smoking, although this reduction in risk 

may only be measurable after 10 years of abstinence.

7. Smoking is a cause of bladder cancer; cessation reduces risk by about 50 percent after only a few years, in comparison with 

continued smoking.

8. The risk of cervical cancer is substantially lower among former smokers in comparison with continuing smokers, even in the first 

few years after cessation. This finding supports the hypothesis that cigarette smoking is a contributing cause of cervical cancer.

9. Neither smoking nor smoking cessation are associated with the risk of cancer of the breast.

Source: U.S. Department of Health and Human Services (1990, p. 10).
The Health Benefits of Smoking Cessation 179

Smoking Cessation

The literature searches for the six sites for which 

smoking cessation has not been previously tied to risk 

at the casual level used the term “smoking or tobacco,” 

a term for the specific cancer of interest (e.g., “colorectal 

neoplasms” or “liver neoplasms”), and limited the publication types to “meta-analysis.” The same terms were 

used in literature searches of PubMed to identify, for each 

cancer, individual studies published after the time period 

covered by the most recent comprehensive meta-analysis. 

All studies identified through meta-analyses or literature searches were examined to determine whether they 

included results by the number of years since cessation. 

Results by years since cessation were tabulated in summary tables. Because there were many studies of cessation 

in relation to stomach and colorectal cancer, summary 

tables for these cancers include only results from cohort 

studies, which generally have less potential for bias than 

case-control studies. 

Epidemiologic Evidence

Cancers for Which Previous Surgeon General’s 

Reports Have Concluded That Smoking Cessation 

Reduces Risk

Lung

The 2004 Surgeon General’s report added to the conclusions of the 1990 Surgeon General’s report by noting 

that, while the risk of lung cancer declines with increasing 

numbers of years since cessation, the risk remains higher 

in former smokers than in never smokers, even after many 

years of not smoking (USDHHS 2004). The 2014 Surgeon 

General’s report covered findings from more recent 

reports documenting a rise of RR in smokers (USDHHS 

2014). For this report, epidemiologic studies of smoking 

cessation and risk of lung cancer were reviewed in detail 

in publications by IARC, including two monographs 

(International Agency for Research on Cancer 2004, 2012) 

and a cancer prevention handbook that focused specifically on the effects of smoking cessation (IARC 2007). In 

the handbook, IARC (2007) included meta-analyses with 

separate estimates of summary RRs for smoking cessation grouped by gender and global region. In most groups, 

estimates of summary RRs for former smokers were about 

0.7–0.8 compared with continuing current smokers up 

to 10 years after cessation, about 0.3 from 10 to 19 years 

after cessation, and even lower with longer periods of successful quitting. 

There is an ongoing need to examine the relationship between smoking cessation and lung cancer for the 

following reasons: (a) In the United States, lung cancer due 

to smoking still accounts for the majority of lung cancer 

deaths (U.S. Cancer Statistics Working Group 2019), and 

(b) changes have occurred over time in the epidemiologic 

relationship between smoking and lung cancer (USDHHS 

2014). This report includes data from three large U.S. 

cohorts: the Cancer Prevention Study-II (CPS-II) (lung 

cancer mortality follow-up, 1982–1988) and two cohorts 

with follow-up for the incidence of lung cancer from the 

1990s and 2000s—the CPS-II Nutrition Cohort (Calle 

et  al. 2002) and the Prostate, Lung, Colorectal, and 

Ovarian cancer screening cohort (PLCO) (Pinsky et  al. 

2015) (Figure  4.1). The American Cancer Society provided, specifically for this report, analyses of the CPS-II 

cohort and CPS-II Nutrition Cohort. RRs by the number 

of years since cessation, analyzed as a time-varying variable in 5-year categories, were similar in the three cohorts 

(Figure 4.1, Table 4.2). As shown, a former cigarette smoker’s risk of lung cancer decreases to half that of a similarly aged continuing smoker about 10–15 years after cessation. RRs continue to decline as time since cessation 

increases, but RRs remain higher in former smokers than 

in persons who have never smoked (Table 4.2). Results by 

histologic subtype from the PLCO cohort suggest that RRs 

may decline somewhat more slowly for adenocarcinoma 

than for squamous cell carcinoma (Pinsky et  al. 2015). 

Table 4.3 provides results using never cigarette smokers 

as the reference group rather than current smokers.

A few studies that examined age at smoking cessation, rather than number of years since cessation, consistently showed that compared with continued smoking, the 

earlier the age at quitting, the lower the risk of lung cancer 

(International Agency for Research on Cancer 2004) (Peto 

et al. 2000; Jha et al. 2013; Pirie et al. 2013; Thun et al. 

2013a). Notably, results of these studies indicate that quitting smoking by age 40, rather than continuing to smoke, 

will eliminate most of the excess risk of developing lung 

cancer faced by long-term smokers later in life. 

Since the 1990 Surgeon General’s report, substantial 

research has addressed the genetic determinants of risk for 

lung cancer among cigarette smokers (Chen et al. 2016; 

Liu et al. 2017). Genetic variation in the α5 nicotinic cholinergic receptor subunit (CHRNA5) has been linked to risk 

for lung cancer, as low- and high-risk genotypes have been 

identified. Chen and colleagues (2016), who carried out a 

meta-analysis involving cohort and case-control studies 

from two collaborative groups, found that the number of 

years by which a diagnosis of lung cancer was delayed following cessation was the same for the two genotypes.

Larynx, Oral Cavity, and Pharynx

Previous Surgeon General’s reports have concluded that smoking is a cause of laryngeal cancer (U.S. 

Department of Health, Education, and Welfare [USDHEW] 
A Report of the Surgeon General

180 Chapter 4

1964), cancer of the oral cavity (USDHEW 1979b), and 

cancers of the oral cavity and pharynx (USDHHS 2004). 

The 1990 Surgeon General’s report concluded that 

“smoking cessation lowers the risk of laryngeal cancer 

compared with continued smoking [and] . . . halves the 

risk for cancer of the oral cavity and esophagus . . . as soon 

as 5 years after cessation” (USDHHS 1990, p. 10). 

Results of studies published since the 1990 Surgeon 

General’s report (IARC 2004, 2012; Marron et al. 2010) 

have strengthened the evidence that risks of both laryngeal cancer and cancer of the oral cavity and pharynx are 

approximately halved within 10 years of cessation. Further, 

the International Head and Neck Cancer Epidemiology 

Consortium, which conducted a very large pooled analysis 

of data on smoking cessation from 17 case-control studies 

(Marron et al. 2010) that included a total of 12,040 cases 

and 16,884 controls, found gradients of declining RR with 

increasing numbers of years since cessation. The findings were similar for cancers of the larynx, oral cavity, and 

pharynx. Compared with continued cigarette smokers, 

reductions in RR in former smokers were approximately 

30% within 5 years of cessation, 50% from 5 to 9 years 

after cessation, and 80% 20 or more years after cessation. 

These estimates for RR may actually underestimate the 

decline in this measure resulting from smoking cessation because they were adjusted for pack-years of smoking 

(USDHHS 1990). 

Esophagus

The 1979 Surgeon General’s report concluded 

that smoking is a cause of esophageal cancer (USDHEW 

1979b), and the 1990 Surgeon General’s report concluded that smoking cessation halves the risk of esophageal cancer as soon as 5 years after cessation (USDHHS 

1990). In addition, the 2004 Surgeon General’s report 

concluded that smoking causes squamous cell carcinoma 

of the esophagus, historically the predominant histologic type of cancer at this site, as well as adenocarcinoma 

(USDHHS 2004), which is currently the most common 

type of esophageal cancer in the United States (Hur et al. 

2013; Xie et al. 2017). Studies of esophageal squamous cell 

carcinoma have revealed declining risks with increasing 

number of years since cessation among former smokers 

(IARC 2004, 2007, 2012), and most studies of esophageal 

adenocarcinoma have also found lower risk in former 

cigarette smokers than in current smokers (IARC 2012). 

Notably, a large pooled analysis of esophageal adenocarcinoma and esophageal gastric junction adenocarcinoma from 11 studies, including 10 case-control studies 

and 1  cohort study, found an approximate 30% reduction in relative risk among former cigarette smokers who 

had quit for at least 10 years compared with continuing 

smokers, even after adjusting for pack-years of smoking 

(Cook et al. 2010).

Figure 4.1 Relative risk of lung cancer incidence or mortality by number of years since smoking cessation, 

compared with continued smoking, in three large U.S. cohorts

Source: American Cancer Society, unpublished data.

Note: CPS = Cancer Prevention Study; PLCO = Prostate, Lung, Colorectal, and Ovarian cancer screening cohort.
CPS-II 1982–1988 (mortality)a

CPS-II Nutrition Cohort 

1992–2011 (incidence)b PLCO 1993–2009 (incidence)c

Deaths RR (95% CI) Cases RR (95% CI) Cases RR (95% CI)

Current smokers 2,571 1.00 (referent) 880 1.00 (referent) 271 1.00 (referent)

Never smokers 332 0.05 (0.046–0.059) 358 0.04 (0.035–0.045) 253 0.03 (0.02–0.03)

Former smokers, by 

number of years since 

smoking cessation

— — — — — —

≤5 193 0.91 (0.78–1.06) 293 0.85 (0.74–0.97) 83 0.86 (0.67–1.10)

>5–10 360 0.64 (0.57–0.72) 411 0.68 (0.60–0.74) 90 0.62 (0.48–0.78)

>10–15 220 0.37 (0.32–0.42) 400 0.52 (0.46–0.58) 151 0.41 (0.33–0.51)

>15–20 179 0.26 (0.22–0.30) 361 0.40 (0.35–0.45) 236 0.38 (0.30–0.47)

>20–25 137 0.21 (0.18–0.25) 277 0.27 (0.24–0.31) 173 0.28 (0.22–0.35)

>25–30 82 0.16 (0.13–0.20) 241 0.21 (0.18–0.24) 101 0.23 (0.17–0.30)

>30 97 0.09 (0.07–0.11) 648 0.12 (0.11–0.13) 111 0.18 (0.14–0.23)

The Health Benefits of Smoking Cessation 181

Smoking Cessation

Source: American Cancer Society, unpublished data.

Notes: CI = confidence interval; CPS = Cancer Prevention Study; PLCO = Prostate, Lung, Colorectal, and Ovarian cancer screening 

cohort; RR = relative risk. aAnalyses of the CPS-II mortality cohort were restricted to those 55 years of age and older and excluded ever pipe/cigar smokers, those 

with prevalent cancer, and those with unknown smoking status. Data were adjusted for race, sex, and level of education.

bAnalyses of the CPS-II Nutrition Cohort were restricted to those 55 years of age and older and excluded those with prevalent cancer. 

Data were adjusted for race, sex, and level of education. 

cAnalyses of participants in the PLCO were restricted to those 55 years of age and older and excluded ever smokers with more than 

30 pack-years of cigarette smoking. RRs provided in the published analysis (Pinsky et al. 2015) used never smokers as the referent 

group. Using current smokers as the referent group, Paul Pinsky, Ph.D., of the National Cancer Institute provided equivalent results 

for this report.

Pancreas

The 1990 Surgeon General’s report concluded that 

smoking cessation reduces the risk of pancreatic cancer, 

but noted that “this reduction in risk may only be measurable after 10 years of abstinence” (USDHHS 1990, p. 10). 

In  a meta-analysis performed by Iodice and colleagues 

(2008) of 14  studies with analyses by number of years 

since cessation, the summary RRs, compared with never 

smokers, were 1.74 (95% confidence interval [CI], 1.61–

1.87) for current cigarette smokers, 1.48 (95% CI, 1.25–

1.76) for persons with less than 10 years since smoking 

cessation, 1.15  for persons with 10  or more years since 

cessation, and 0.95 for persons with 20 or more years since 

cessation. In other large pooled analyses of cohort studies 

(Lynch et al. 2009) and case-control studies (Bosetti et al. 

2012), RRs declined with increased time since cessation, 

and no excess risk (compared with never smokers) was 

observed among former smokers with 20 or more years 

since quitting (Bosetti et  al. 2012). Thus, collectively, 

the available scientific evidence indicates that the RR for 

pancreatic cancer declines steadily with increased time 

since cessation and approaches that of never smokers 

approximately 20 years after quitting smoking.

Bladder

The 1990 Surgeon General’s report concluded that 

“[smoking] cessation reduces risk [of bladder cancer] by 

about 50  percent after only a few years in comparison 

with continued smoking” (USDHHS 1990, p.  10). Since 

that report, many studies have provided more evidence 

that RRs for bladder cancer are lower in former cigarette 

smokers than in current smokers and that they decline 

steadily as the number of years since cessation increases 

(IARC 2004, 2012; Freedman et  al. 2011; Jiang et  al. 

2012). In comparisons with continued smoking, most 

studies have observed measurable reductions in risk for 

bladder cancer within 10 years of smoking cessation. In 

the three largest studies (Hartge et  al. 1987; Brennan 

et al. 2000; Freedman et al. 2011), however, each of which 

included more than 2,500 cases of bladder cancer in their 

Table 4.2 Relative risk of lung cancer incidence or mortality by number of years since smoking cessation, compared 

with continued smoking, in three large U.S. cohorts
CPS-II 1982–1988 (mortality)a

CPS-II Nutrition Cohort 

1992–2011 (incidence)b PLCO 1993–2009 (incidence)c

Deaths RR (95% CI) Cases RR (95% CI) Cases RR (95% CI)

Never smokers 332 1.00 (referent) 358 1.00 (referent) 253 1.00 (referent)

Current smokers 2,571 19.21 (17.09–21.59) 880 24.96 (22.02–28.28) 271 35.9 (29.0–44.5)

Former smokers, by 

number of years since 

smoking cessation

— — — — — —

≤5 193 17.48 (14.58–20.96) 293 21.08 (18.03–24.64) 83 30.8 (23.4–40.5)

>5–10 360 12.30 (10.57–14.32) 411 16.96 (14.69–19.56) 90 22.1 (16.9–28.9)

>10–15 220 7.08 (5.96–8.41) 400 12.94 (11.20–14.94) 151 14.8 (11.9–18.2)

>15–20 179 4.93 (4.10–5.92) 361 9.90 (8.54–11.47) 236 13.5 (11.3–16.2)

>20–25 137 4.02 (3.29–4.92) 277 6.73 (5.75–7.88) 173 9.9 (8.1–12.0)

>25–30 82 3.13 (2.46–3.99) 241 5.21 (4.42–6.14) 101 8.1 (6.4–10.2)

>30 97 1.65 (1.32–2.07) 648 2.90 (2.55–3.31) 111 6.4 (5.1–8.0)

Source: American Cancer Society, unpublished data.

Notes: CI = confidence interval; CPS =

cohort; RR = relative risk. aAnalyses of the CPS-II mortality cohort were restricted to those 55 years of age and older and excluded ever pipe/cigar smokers, those 

with prevalent cancer, and those with unknown smoking status. Data were adjusted for race, sex, and level of education.

bAnalyses of the CPS-II Nutrition Cohort were restricted to those 55 years of age and older and excluded those with prevalent cancer. 

Data were adjusted for race, sex, and level of education. 

cAnalyses of participants in the PLCO were restricted to those 55 years of age and older and excluded ever smokers with more than 

30 pack-years of cigarette smoking. RRs provided in the published analysis (Pinsky et al. 2015) used never smokers as the referent 

group. Using current smokers as the referent group, Paul Pinsky, Ph.D., of the National Cancer Institute provided equivalent results 

for this report.

A Report of the Surgeon General

182 Chapter 4

analyses, more than 10 years since cessation was required 

before risk fell in former cigarette smokers to half that of 

continuing smokers.

Cancers for Which Previous Reports Have Not 

Concluded That Smoking Cessation Reduces Risk 

Stomach

The 2004 Surgeon General’s report concluded that 

there was sufficient evidence to infer a causal relationship

between smoking and stomach cancer (USDHHS 2004). 

The association between smoking and this type of cancer 

is independent of Helicobacter pylori infection, an established risk factor for stomach cancer (Moy et al. 2010; IARC 

2012). Potential biological mechanisms include chronic 

inflammation in the stomach and exposure to carcinogens 

in tobacco smoke, including tobacco-specific nitrosamines 

(Li et al. 2014).

A meta-analysis of more than 30 studies of cigarette 

smoking and risk for stomach cancer published through 

2003 (Gandini et al. 2008) found that risk was lower for 

former cigarette smokers (RR = 1.31; 95% CI, 1.17–1.46) 

than for current smokers (RR = 1.64; 95% CI, 1.37–1.95) 

when compared with never smokers. Similar results were 

reported in studies published in 2003 or later (Gonzalez 

et al. 2003; Jee et al. 2004; Koizumi et al. 2004; Wen et al. 

2004; Doll et al. 2005; Fujino et al. 2005; Lindblad et al. 

2005; Sauvaget et al. 2005; Tran et al. 2005; Kurosawa et al. 

2006; Freedman et al. 2007; Kim et al. 2007; Ozasa 2007; 

Sjodahl et  al. 2007; Sung et  al. 2007; Batty et  al. 2008; 

Shikata et al. 2008; Zendehdel et al. 2008; Moy et al. 2010; 

Steevens et  al. 2010; Nomura et  al. 2012; Blakely et  al. 

2013; Tabuchi et al. 2013; Buckland et al. 2015; Chen et al. 

2015; Eom et  al. 2015; Jayalekshmi et  al. 2015; Charvat 

et al. 2016).

Risk for stomach cancer by time elapsed since quitting among former cigarette smokers has been examined 

in nine cohort studies (Chao et al. 2002; Koizumi et al. 

2004; Sauvaget et al. 2005; Freedman et al. 2007; Ozasa 

2007; Zendehdel et al. 2008; Moy et al. 2010; Steevens et al. 

2010; Ordonez-Mena et al. 2016). These studies are summarized in Table 4.4, but the table does not include studies 

that may underestimate the effect of smoking cessation 

(USDHHS 1990). For example, Table 4.4 does not include 

a small study from India that included many dual users 

Table 4.3 Relative risk of lung cancer incidence or mortality by number of years since smoking cessation, compared 

with never smokers, in three large U.S. cohorts
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Chao et al. 

(2002)

• Cohort study (Cancer Prevention Study II)

• Men and women ≥30 years of age

• 1,055,841 participants and 1,505 deaths 

from stomach cancer

• United States

• Follow-up period: 1982–1996

• Men: 

– Smoking status:

○ Never smoker: 1.00 (referent)

○ Current smoker: 2.16 (1.75–2.67)

○ Former smoker: 1.55 (1.28–1.88)

– Number of years since smoking cessation: 

○ Never smoker: 1.00 (referent)

○ ≤10: 1.92 (1.50–2.47)

○ 11–19: 1.64 (1.26–2.14)

○ ≥20: 1.23 (0.95–1.59)

– p for trend among former smokers: 0.0015 

• Women

– Smoking status:

○ Never smoker: 1.00 (referent)

○ Current smoker: 1.49 (1.18–1.88)

○ Former smoker: 1.36 (1.08–1.71)

○ Number of years since smoking cessation:

– Never smoker: 1.00 (referent)

○ ≤10: 1.31 (0.91–1.87)

○ 11–19: 1.46 (1.00–2.13)

○ ≥20: 1.34 (0.95–1.89)

– p trend among former smokers: 0.68 

Adjusted for age; race; level of education; 

familyhistoryof stomachcancer;consumption 

of high-fiber grain foods, vegetables,and

citrus fruits or juices; and use of vitamin C, 

multivitamins, and aspirin

Koizumi et al. 

(2004)

• Two population-based cohort studies

• Men ≥40 years of age

• Cohort 1: 9,980 men and 228 cases 

of stomach cancer

• Cohort2:19,412menand223 cases 

of stomach cancer

• Northern Japan

• Follow-up period:

– Cohort1:1984–1992

– Cohort2:1990–1997

 Smoking status:

– Never smoker: 1.00 (referent)

– Current smoker:1.84(1.39–2.43)

– Formersmoker:1.77(1.29–2.43)

 Number of years since smokingcessation:

– Never smoker: 1.00 (referent)

– <5: 1.72 (1.12–2.64)

– 5–14: 2.08 (1.41–3.07)

– ≥15: 1.31 (0.77–2.21)

Results from the two cohorts were pooled

Adjusted for age, BMI, history of peptic ulcer, 

parental history of stomach cancer, type of health 

insurance, alcohol use, daily intake of pickled 

vegetables, and intake of bean-paste soup

Cohort 1 also adjusted for intake of green or 

yellow vegetables and other vegetables and fruits

Cohort 2 also adjusted for intake of spinach, 

carrots, pumpkin, cabbage, lettuce, Chinese 

cabbage, and oranges and other fruits

Table 4.4 Cohort studies of stomach cancer incidence or mortality, by number of years since smoking cessation

The Health Benefits of Smoking Cessation 183
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Sauvaget et 

al. (2005)

• Cohort study (Life Span Study)

• 38,576 men and women who were in

Hiroshima orNagasaki(Japan) atthe time 

of the atomic bombings in August 1945

• 1,280 cases of stomach cancer

• Japan

• Follow-up period: 1980–1999

 Smoking status:

– Never smoker: 1.00 (referent)

– Current smoker: 1.50 (1.28–1.76)

– Former smoker: 1.37 (1.13–1.66)

 Number of years since smoking cessation:

– Never smoker: 1.00 (referent)

– 1–5: 1.29 (0.90–1.85)

– 6–10: 1.32 (0.88–1.96)

– 11–15: 1.06 (0.67–1.67)

– ≥16: 0.74 (0.54–1.00)

Adjusted for city, sex, sex-specific age, calendar 

period, level of education, and radiation dose

Freedman et al. 

(2007)

• Cohort study (NIH-AARPDiet andHealth 

Study)

• 474,606menandwomen≥50yearsofage 

who were members of AARP

• 188casesof stomachcardiaand187cases 

of stomach non-cardia

• Six states (California, Florida, Louisiana, 

New Jersey, North Carolina, and Pennsylvania) 

and two U.S. metropolitan areas (Atlanta, 

Georgia; and Detroit, Michigan)

• Follow-up period: 1995–2000

• Number of years since smoking cessation:

– Cardia:

 Never smoker: 1.00 (referent)

 Current smoker: 2.87 (1.75–4.73)

 1–4: 2.39 (1.16–4.92)

 5–9: 2.73 (1.55–4.82)

 ≥10: 2.01 (1.32–3.07)

– Non-cardia:

 Never smoker: 1.00 (referent)

 Current smoker: 2.05 (1.33–3.18)

 1–4: 1.18 (0.54–2.62)

 5–9: 1.79 (1.05–3.05)

 ≥10: 1.12 (0.78–1.63)

Adjusted for age, fruit intake, vegetable intake, 

total energy intake, sex, BMI, education level, 

alcohol intake, and physical activity

Analyses of non-cardia cancer additionally 

adjusted for race/ethnicity

A Report of the Surgeon General

184 Chapter 4

Table 4.4 Continued
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Ozasa 

(2007)

• Cohort study(JapanCollaborativeCohort 

Study for Evaluation of Cancer)

• 1,048 deaths from stomach cancer

• Japan

• Follow-up period: starting in 1988

• Men:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.47 (1.19–1.80)

 Former smoker: 1.22 (0.97–1.53)

– Number of years since smoking cessation:

 Never smoker: 1.00 (referent)

 <5: 1.19 (0.84–1.67)

 5–14: 1.25 (0.94–1.67)

 ≥15: 1.14 (0.84–1.55)

• Women:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 0.86 (0.50–1.48)

 Former smoker: 1.07 (0.50–2.28)

– Number of years since smoking cessation:

 Never smoker: 1.00 (referent)

 <5: 0.61 (0.08–4.37)

 5–14: 1.35 (0.43–4.23)

 ≥15: 0.56 (0.07–4.02)

Adjusted for age and area of study

Table 4.4 Continued

The Health Benefits of Smoking Cessation 185
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Zendehdel et al. 

(2008)

• Cohort study

• 336,381 men in the Swedish building industry 

who had records of at least one preventive 

health checkup between 1971 and 1993

• 276 cases of stomach cardia and 1,109 cases 

of stomach non-cardia

• Nord-Trondelag County, Norway

• Follow-up period: from date of initial checkup 

to 2004

• Cardia:

– Smoking status:

 Never smoker: 1.0 (referent)

 Current smoker: 2.3 (1.6–3.3)

 Former smoker: 1.8 (1.2–2.7)

– Number of years since smoking cessation:

 Never smoker: 1.0 (referent)

 <5: 1.9 (1.1–3.4)

 ≥5: 1.7 (1.1–2.6)

– p trend among former smokers: 0.7

• Non-cardia:

– Smoking status:

 Never smoker: 1.0 (referent)

 Current smoker: 1.4 (1.2–1.6)

 Former smoker: 1.3 (1.1–1.5)

– Number of years since smoking cessation:

 Never smoker: 1.0 (referent)

 <5: 1.2 (0.9–1.6)

 ≥5: 1.3 (1.1–1.6)

– p trend among former smokers: 0.6

Adjusted for age and BMI

Definition of smoking included pipe/cigar 

smoking, but study population predominantly 

smoked cigarettes

Moy et al. 

(2010)

• Cohort study (Shanghai Cohort Study)

• 18,244 men 45–64 years of age

• 391 cases of stomach cancer

• Shanghai, China

• Follow-up period: 1986–2005

• Smoking status:

– Never smoker: 1.00 (referent)

– Current smoker: 1.55 (1.23–1.96)

– Former smoker: 1.79 (1.25–2.57)

• Number of years since smoking cessation:

– Never smoker: 1.00 (referent)

– Current smoker: 1.30 (0.82–2.05)

– <5: 1.24 (0.66–2.34)

– 5–9: 0.91 (0.49–1.66)

– ≥10: 0.64 (0.51–0.81)

Adjusted for age, year, and neighborhood

A Report of the Surgeon General

186 Chapter 4

Table 4.4 Continued
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Steevens et al. 

(2010)

• Cohort study (Netherlands Cohort Study)

• 120,852 men and women (3,962 in the 

subcohort for the case-cohort design) 

55–70 years of age

• 164 cases of cardia and 491 cases of 

non-cardia

• The Netherlands

• Follow-up period: 1986–2002

• Number of years since smoking cessation:

– Cardia:

 Never smoker: 1.00 (referent)

 Current smoker: 1.61 (0.97–2.66)

 <10: 1.72 (0.97–3.05)

 10–19: 1.43 (0.81–2.52)

 ≥20: 1.00 (0.53–1.91)

– Non-cardia:

 Never smoker: 1.00 (referent)

 Current smoker: 1.86 (1.39–2.47)

 <10: 1.81 (1.30–2.52)

 10–19: 1.41 (0.98–2.02)

 ≥20: 1.13 (0.77–1.67)

Cases in the case-cohort approach derived from 

entire cohort and number of person-years at risk 

for entire cohort estimated from a subcohort 

of 5,000 men and women who were randomly 

sampled from the total cohort at baseline

Adjusted for age; sex; alcohol use; BMI; level of 

education; energy intake; and intake of fruits, 

vegetables, and fish

Ordonez-Mena 

et al. (2016)

• Collaboration of 19 prospective cohort studies

• 897,021 men and women

• 1,866 cases of stomach cancer and 1,396 deaths 

from stomach cancer

• Europe and United States

• Incidence of stomach cancer:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.74 (1.50–2.02)

 Former smoker: 1.18 (0.95–1.46)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 ≤9: 0.85 (0.60–1.20)

 10–19: 0.68 (0.41–1.12)

 ≥20: 0.69 (0.51–0.93)

– p trend among former smokers: 0.0461

• Death from stomach cancer:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.73 (1.36–2.19)

 Former smoker: 1.31 (1.02–1.68)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 ≤9: 1.13 (0.80–1.58)

 10–19: 0.72 (0.46–1.14)

 ≥20: 0.87 (0.64–1.19)

– p trend among former smokers: 0.2355

Analyses of number of years since smoking 

cessation included only cohorts with these 

data and therefore included substantially 

fewer participants

Adjusted for sex, age, BMI, level of education, 

vigorous physical activity, history of diabetes, 

and alcohol consumption

The Health Benefits of Smoking Cessation 187

Table 4.4 Continued

Notes: AARP = formerly American Association of Retired Persons; BMI = body mass index; CI = confidence interval; NIH = National Institutes of Health; RR = relative risk. aStudies are of cancer incidence unless number of cancer deaths is identified.

bp trend values are shown only if described as being among former smokers.
A Report of the Surgeon General

188 Chapter 4

of cigarettes and bidis (Jayalekshmi et al. 2015), a study 

in which the highest category of number of years since 

quitting was only ≥3  years (Guo et  al. 1994), or studies 

where the number of years since quitting was adjusted for 

duration or pack-years of smoking (Gonzalez et al. 2003; 

Sjodahl et al. 2007; Nomura et al. 2012). In general, risk 

estimates for the highest category of number of years 

since cessation (ranging from >10  years to >20  years) 

were lower than those for categories with fewer numbers 

of years since cessation (Table 4.4). 

Colon and Rectum

The 2014 Surgeon General’s report concluded that 

the evidence was sufficient to infer a causal relationship between cigarette smoking and colorectal cancer 

(USDHHS 2014). For example, Botteri and colleagues 

(2008), in a meta-analysis of 26 studies of the incidence of 

colorectal cancer published through 2008, reported RRs 

of 1.17 (95% CI, 1.11–1.22) for former cigarette smokers 

and 1.07 (95% CI, 0.99–1.16) for current smokers, both 

compared with never smokers. Although the excess risk 

of colorectal cancer associated with current smoking 

overall was relatively small in this meta-analysis, there 

were statistically significant trends for increasing risk 

with increasing years of smoking duration, number of 

cigarettes smoked per day, and number of pack-years. In 

studies of colorectal cancer mortality that were included 

in the meta-analysis, summary RRs were 1.28 (95% CI, 

1.15–1.42) for current smokers based on 14 studies, and 

1.23 (95% CI, 1.14–1.32) for former smokers based on 

12 studies (Botteri et al. 2008). Since 2008, four cohort 

studies that each included more than 1,000 incident cases 

of colorectal cancer (Hannan et al. 2009; Limsui et al. 

2010; Leufkens et al. 2011) or deaths (Parajuli et al. 2014) 

have been published that provide RRs for both current and 

former cigarette smokers. In general, the RRs for current 

smokers were above those for former smokers: 

• 1.27 (95% CI, 1.06–1.52) for current smokers and 

1.23 (95% CI, 1.23 1.11–1.36) for former smokers 

(Hannan et al. 2009);

• 1.22 (95% CI, 1.04–1.41) for current smokers and 

1.18 (95% CI, 1.02–1.36) for former smokers (Limsui 

et al. 2010);

• 1.31 (95% CI, 1.06–1.64) and 1.25 (1.04–1.50) for current and former smokers, respectively, with proximal 

colon cancer; and 0.91 (95% CI, 0.73–1.14) and 1.13 

(95% CI 0.95-1.36) for current and former smokers, 

respectively, with distal colon cancer (Leufkens et al. 

2011); and 

• 1.27 (95% CI, 1.10–1.46) and 1.20 (95% CI, 1.03–

1.38) for current and former smokers, respectively, 

who were men; and 1.30 (95% CI, 1.12–1.52) and 1.08 

(95% CI, 0.90–1.30) for current and former smokers, 

respectively, who were women (Parajuli et al. 2014). 

Taken together, these four studies provide evidence that former smokers have somewhat lower risk for 

colorectal cancer than do current smokers. Twelve cohort 

studies have examined risk of colorectal cancer by time 

since cessation, as summarized in Table 4.5 (Chao et al. 

2000; Rohan et al. 2000; Limburg et al. 2003; Ozasa 2007; 

Kenfield et al. 2008; Weijenberg et al. 2008; Gram et al. 

2009; Hannan et al. 2009; Leufkens et al. 2011; Gong et al. 

2012; Nishihara et al. 2013; Ordonez-Mena et al. 2016). In 

most of these studies (Chao et al. 2000; Rohan et al. 2000; 

Limburg et al. 2003; Kenfield et al. 2008; Weijenberg et al. 

2008; Hannan et al. 2009; Leufkens et al. 2011; Gong et al. 

2012; Ordonez-Mena et al. 2016), the RR point estimates 

for the categories with the greatest number of years since 

smoking cessation (ranging from ≥10 years to ≥40 years) 

were lower than those for categories with fewer number of 

years since cessation.

The influence of smoking cessation on the risk of 

colorectal cancer may be most clearly observable in analyses that focus on smoking-related molecular subtypes, 

including colorectal tumors with microsatellite instability 

(MSI-high) and the cytosine-phosphate-guanine (CpG) 

island methylator phenotype (CIMP-high). Several studies 

have associated smoking with about a two-fold increase in 

risk of MSI-high and CIMP-high colorectal cancer, but not 

with risk of other subtypes of colorectal cancer (Campbell 

et al. 2017). To date, only Nishihara and colleagues (2013) 

have examined time since smoking cessation by molecular subtype. In their study, smoking cessation, compared 

with continued smoking, was associated with considerably 

lower risk of MSI-high and CIMP-high colorectal cancer 

starting 10–20 years after cessation, but risk of other 

subtypes of colorectal cancer was similar in current and 

former smokers and did not change with number of years 

since smoking cessation.

Liver

The 2014 Surgeon General’s report concluded that the 

evidence was sufficient to infer a causal relationship between 

cigarette smoking and liver cancer (USDHHS 2014). 

Potential biological mechanisms include long-term direct 

exposure of the liver to carcinogens in tobacco smoke and 

smoking-induced fibrosis and cirrhosis (USDHHS 2014).

A meta-analysis of 23 studies was carried out for 

the 2014 Surgeon General’s report. The meta-analysis 

provided estimates of the RR for liver cancer for current and former cigarette smokers compared with never 
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Chao et al. 

(2000)

• Cohort study (Cancer Prevention Study II)

• 781,351 men and women ≥30 years of age

• 4,432 deaths from colorectal cancer

• United States

• Follow-up period: 1982–1996

• Current smoker:

– Men: 1.32 (1.16–1.49)

– Women: 1.41 (1.26–1.58)

• Number of years since smoking cessation 

(men and women):

– Never smoker: 1.00 (referent)

– ≤10: 1.32 (1.19–1.47)

– 11–19: 1.20 (1.08–1.35)

– ≥20: 1.04 (0.94–1.16)

– p trend among former smokers: 0.0001

Adjusted for age; race; level of education; family 

history of colorectal cancer; exercise; aspirin 

and multivitamin use; alcohol use; and intake of 

vegetables, high-fiber grain foods, and fatty meats

Models among women also included hormone 

replacement therapy

Presented only sex-specific RRs for current 

smokers compared with never smokers

Rohan et al. 

(2000)

• Cohort study (Canadian National Breast 

Screening Study)

• 56,837 women 40–59 years of age

• 90 deaths from colorectal cancer

• Canada

• Follow-up period: 1982–1993

• Smoking status:

– Never smoker: 1.00 (referent)

– Current smoker: 1.15 (0.61–2.16)

– Former smoker: 1.52 (0.91–2.56)

• Number of years since smoking cessation:

– Never smoker: 1.00 (referent)

– 1–10: 1.74 (0.91–3.33)

– ≥11: 1.33 (0.70–2.57)

Adjusted for age; BMI; hours per week of 

vigorous activity; and intake of dietary fiber, 

calcium, and alcohol; and energy level

Limburg et al. 

(2003)

• Cohort study (Iowa Women’s Health Study)

• 34,467 women 55–69 years of age

• 869 cases of colorectal cancer

• Iowa

• Follow-up period: 1986–1999

• Smoking status:

– Never smoker: 1.00 (referent)

– Current smoker: 1.10 (0.89–1.37)

– Former smoker: 1.21 (1.01–1.45)

• Number of years since smoking cessation:

– Never smoker: 1.00 (referent)

– <10: 1.21 (0.93–1.56)

– 10–19: 1.08 (0.77–1.51)

– 20–29: 1.51 (1.09–2.09)

– – >30: 1.07 (0.71–1.62)

– p trend among former smokers: 0.14

Adjusted for age; BMI; waist-to-hip ratio; 

physical activity; alcohol consumption; hormone 

replacement therapy; and intake of methionine, 

total calories, total fat, sucrose, red meat, 

calcium, folate, and vitamin E

The Health Benefits of Smoking Cessation 189

Table 4.5 Cohort studies of colorectal cancer incidence or mortality, by number of years since smoking cessation
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Ozasa (2007) • Cohort study (Japan Collaborative Cohort 

Study for Evaluation of Cancer)

• 381 deaths from colon cancer and 226 deaths 

from rectal cancer

• Japan

• Follow-up period: starting in 1988

• Men, colon:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.18 (0.80–1.72)

 Former smoker: 1.27 (0.85–1.91)

– Number of years since smoking cessation:

 Never smoker: 1.00 (referent)

 <5: 2.05 (1.23–3.42)

 5–14: 0.96 (0.55–1.68)

 ≥15: 1.27 (0.74–2.17)

• Men, rectum:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.31 (0.85–2.01)

 Former smoker: 0.95 (0.58–1.53)

– Number of years since smoking cessation:

 Never smoker: 1.00 (referent)

 <5: 0.50 (0.19–1.31)

 5–14: 1.16 (0.64–2.10)

 ≥15: 1.00 (0.51–1.96)

• Women, colon:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 0.67 (0.29–1.53)

 Former smoker: 2.05 (0.95–4.41)

– Number of years since smoking cessation:

 Never smoker: 1.00 (referent)

 <5: 3.74 (1.19–11.8)

 5–14: 0.77 (0.10–5.56)

 ≥15: 2.14 (0.52–8.68)

• Women, rectum:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.31 (0.52–3.29)

 Former smoker: 0.68 (0.09–4.95)

– Number of years since smoking cessation:

 Never smoker: 1.00 (referent)

 <5: 2.93 (0.40–21.3)

 5–14: Not reported

 ≥15: Not reported

Adjusted for age and area of study

Table 4.5 Continued

A Report of the Surgeon General

190 Chapter 4
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Kenfield et al.

(2008)

• Cohort study (Nurses’ Health Study)

• 104,519 women 30–55 years of age

• 578 deaths from colorectal cancer

• United States (11 states)

• Follow-up period: 1980–2004

Adjusted for age; follow-up period; history of

hypertension, diabetes, and high cholesterol; 

BMI; change in weight from 18 years of age to

baseline; alcohol intake; physical activity; use 

of oral contraception; hormone replacement

therapy and menopausal status; parental history 

of myocardial infarction before 60 years of 

age; number of cigarettes smoked per day; age 

started smoking; servings of beef, pork, lamb, 

or processed meat; total calcium and folate 

intake; and duration of aspirin use

All covariates updated until diagnosis

Weijenberg et al.

(2008)

• Case-cohort study (subset of the Netherlands

• Cohort Study)

• Men and women 55–69 years of age

• 4,083 persons in subcohort and 648 cases

• of colorectal cancer

• The Netherlands

• Follow-up period: 1989–1994

Gram et al.

(2009)

• Cohort study (The Norwegian Women and

Cancer study)

• 68,160 women 30–69 years of age

• 425 cases of colorectal cancer

• Norway

• Follow-up period: 1996–2005

• Smoking status: 

– Never smoker: 1.00 (referent) 

– Current smoker: 1.63 (1.29–2.05) 

– Former smoker: 1.23 (1.02–1.49) 

• Number of years since smoking cessation: 

– Never smoker: 1.00 (referent) 

– Current smoker: 0.76 (0.55–1.05) 

– <10: 0.95 (0.70–1.29) 

– 10–19: 0.70 (0.53–0.93) 

– ≥20: 0.62 (0.49–0.77) 

– p trend among former smokers: 0.40 

• Smoking status: 

– Never smoker: 1.00 (referent) 

– Current smoker: 0.81 (0.62–1.05) 

– Former smoker: 1.22 (0.97–1.53) 

• Number of years since smoking cessation: 

– Never smoker: 1.00 (referent) 

– <10: 0.96 (0.76–1.22) 

– 10–30: 1.24 (0.96–1.61) 

– >30: 0.78 (0.45–1.33) 

– p = 0.33 

• Smoking status: 

– Never smoker: 1.0 (referent) 

– Current smoker: 1.2 (0.9–1.5) 

– Former smoker: 1.3 (1.0–1.6) 

• Number of years since smoking cessation: 

– Never smoker: 1.0 (referent) 

– Current smoker: 1.2 (1.0–1.5) 

– 1–9: 1.1 (0.8–1.7) 

– 10–19: 1.5 (1.1–2.1) 

– ≥20: 1.1 (0.8–1.5) 

Adjusted for age, menopausal status, use of 

hormonal contraceptives and postmenopausal 

hormonal therapy, BMI, and alcohol consumption

Adjusted for age, sex, family history of colorectal 

cancer, BMI, and alcohol and coffee consumption

Table 4.5 Continued

The Health Benefits of Smoking Cessation 191
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Hannan et al. 

(2009)

• Cohort study (CPS-II Nutrition Cohort)

• 124,751 men and women, most 50–74 years 

of age

• 1,962 cases of colorectal cancer

• United States (21 states)

• Follow-up period: 1992–2005

• Smoking status:

– Never smoker: 1.00 (referent)

– Current smoker: 1.27 (1.06–1.52)

– Former smoker: 1.23 (1.11–1.36)

• Number of years since smoking cessation:

– Never smoker: 1.00 (referent)

– 1–10: 1.48 (1.27–1.73)

– 11–20: 1.33 (1.14–1.55)

– 21–30: 1.28 (1.10–1.49)

– ≥31: 1.03 (0.89–1.19)

– p trend among former smokers: 0.0003

Adjusted for age, BMI, level of education, family 

history of colorectal cancer, physical activity, race, 

aspirin use, alcohol use, vegetable consumption, 

fiber and whole grain consumption, red and 

processed meat consumption, and history 

of endoscopy 

Leufkens et al. 

(2011)

• Cohort study (European Prospective 

Investigation into Cancer and Nutrition)

• 465,879 men and women, most 35–70 years 

of age

• 2,741 cases of colorectal cancer

• 23 centers in 10 European countries 

(Denmark, France, Germany, Greece, Italy, 

the Netherlands, Norway, Spain, Sweden, 

and United Kingdom)

• Follow-up period: 1991–2000

• Smoking status:

– Never smoker: 1.00 (referent)

– Current smoker: 1.08 (0.96–1.21)

– Former smoker: 1.17 (1.07–1.29)

• Number of years since smoking cessation:

– Never smoker: 1.00 (referent)

– ≤4: 1.15 (0.95–1.40)

– 5–9: 1.16 (0.95–1.40)

– 10–14: 1.24 (1.03–1.49)

– 15–19: 1.34 (1.12–1.60)

– 20–24: 1.11 (0.91–1.35)

– ≥25: 1.08 (0.92–1.26)

– p trend among former smokers: 0.52

Adjusted for center, age, sex, weight, height, 

physical activity, level of education, intake 

of energy from fat and nonfat, fiber, fruit, 

vegetables, red meat, processed meat, alcohol, 

and fish 

Gong et al. 

(2012)

• Pooled analysis of eight studies from the 

Genetics and Epidemiology of Colorectal 

Cancer Consortium (Health Professionals 

Follow-up Study; Nurses’ Health Study; 

Prostate, Lung, Colorectal, and Ovarian 

Cancer Screening Trial; VITamins and 

Lifestyle Study; Women’s Health Initiative; 

Colon Cancer Family Registry; Diet, Activity, 

and Lifestyle Survey; and Ontario Familial 

Colorectal Cancer Registry)

• Men and women

• 6,796 cases of colorectal cancer and 

7,770 controls

Adjusted for age, sex, BMI, level of education, 

alcohol intake, and study site

Number of years since smoking cessation 

additionally adjusted for pack-years of smoking

•

–

–

– <15: 1.47 (1.21–1.78)

–

– 25–34: 1.15 (0.85–1.55)

–

Number of years since smoking cessation:

Never smoker: 1.00 (referent)

Current smoker: 1.36 (1.12–1.64)

15–24: 1.31 (1.07–1.60)

≥35: 0.74 (0.47–1.18)

Table 4.5 Continued

A Report of the Surgeon General

192 Chapter 4
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Nishihara et al. 

(2013)

• Two cohort studies:

– Men from the Health Professionals 

Follow-up Study

– Women from the Nurses’ Health Study

• 134,204 men and women

• 1,260 cases of colorectal cancer with 

available tumors

• United States

• Follow-up period:

– Nurses’ Health Study: 1980–2008

– Health Professionals Follow-up Study: 

1986–2008

• Colorectal cancer (all):

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.17 (0.96–1.43)

 Former smoker: 1.18 (1.05–1.34)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 1–4: 0.99 (0.73–1.34)

 5–9: 1.30 (0.99–1.71)

 10–19: 0.96 (0.75–1.23)

 20–39: 0.92 (0.74–1.14)

 ≥40: 1.05 (0.80–1.37)

• CIMP-high:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 2.08 (1.35–3.20)

 Former smoker: 1.30 (0.95–1.76)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 1–4: 1.09 (0.58–2.02)

 5–9: 0.89 (0.48–1.66)

 10–19: 0.52 (0.29–0.93)

 20–39: 0.52 (0.32–0.84)

 ≥40: 0.48 (0.26–0.90)

Adjusted for calendar year, age, sex, BMI, 

family history of colorectal cancer, regular 

use of aspirin, physical activity level, alcohol 

consumption, total caloric intake, and intake 

of red meat

Focused on molecular subtypes of colorectal 

cancer previously established to be smoking 

related, including CIMP-high

Table 4.5 Continued

The Health Benefits of Smoking Cessation 193
Study Design/populationa Exposure estimates: RR (95% CI)b Comments

Ordonez-Mena 

et al. (2016) • Collaboration of 19 prospective cohort studies

• 897,021 men and women

• 12,696 cases of colorectal cancer and 

4,878 deaths from colorectal cancer

• Europe and United States

• Incidence of colorectal cancer:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.20 (1.07–1.34)

 Former smoker: 1.20 (1.15–1.25)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 ≤9: 1.00 (0.87–1.16)

 10–19: 1.11 (0.97–1.27)

 ≥20: 0.88 (0.78–1.00)

• Mortality from colorectal cancer:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.35 (1.16–1.58)

 Former smoker: 1.22 (1.13–1.31)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 ≤9: 1.07 (0.86–1.32)

 10–19: 1.07 (0.87–1.31)

• ≥20: 0.76 (0.63–0.93)

Analyses of number of years since smoking 

cessation included only cohorts with these 

data and therefore included substantially 

fewer participants

Adjusted for sex, age, BMI, level of education, 

vigorous physical activity, history of diabetes, 

and alcohol consumption

Table 4.5 Continued

A Report of the Surgeon General

194 Chapter 4

Notes: BMI = body mass index; CI = confidence interval; CIMP-high = cytosine-phosphate-guanine island methylator phenotype; 

CPS = Cancer Prevention Study; RR = relative risk.

aStudies are of cancer incidence unless number of cancer deaths is identified.

bp trend values are shown only if described as being among former smokers.
The Health Benefits of Smoking Cessation 195

Smoking Cessation

smokers. This meta-analysis reported a lower summary RR 

for former smokers (1.4; 95% CI, 1.1–1.7) than for current 

smokers (1.7; 95% CI, 1.5–1.9). Seven other studies published in 2014 or later found similar results (Everatt et al. 

2014; Moura et al. 2014; Chen et al. 2015; Meyer et al. 2015; 

Pang et al. 2015; Chiang et al. 2016; Niu et al. 2016). Of the 

30 studies overall, only 4 (all case-control studies) reported 

information on risk by number of years since smoking cessation (Table 4.6) (Choi and Kahyo 1991; Goodman et al. 

1995; Ozasa 2007; Hassan et al. 2008). Results from these 

studies are inconsistent and are limited by small samples, 

as the largest (Hassan et al. 2008) included only 154 cases 

of liver cancer among former smokers. 

Cervix

The 1990 Surgeon General’s report concluded that 

“risk of cervical cancer is substantially lower among former 

smokers in comparison with continuing smokers, even in 

the first few years after cessation” (USDHHS 1990, p. 10). 

However, it did not explicitly conclude that smoking cessation reduced risk of cervical cancer. The 2004 Surgeon 

General’s report concluded that there was sufficient evidence 

to infer a causal relationship between cigarette smoking and 

cervical cancer (USDHHS 2004). The association between 

smoking and higher risk of cervical cancer persists when 

adjusted for measures of infection with the human papillomavirus (HPV) (IARC 2012; Roura et al. 2014). Potential 

biological mechanisms include direct genotoxic effects of 

nitrosamines and polyaromatic hydrocarbons from tobacco 

smoke and suppression of the immune system, including 

reduced ability to clear infection caused by HPV (FonsecaMoutinho 2011; Gadducci et al. 2011).

In a meta-analysis of more than 20  studies published through 2003 that used never smokers as the reference group, Gandini and colleagues (2008) found that 

RRs for cervical cancer were lower for former smokers 

(1.26; 95%  CI, 1.11–1.42) than for current smokers 

(1.83; 95% CI, 1.51–2.21) (Roura et al. 2014). Earlier, the 

International Collaboration of Epidemiological Studies of 

Cervical Cancer (ICESCC) (2006) conducted a large pooled 

analysis of 23  studies (8  cohort, 15  case control) that 

included data from most of the studies published up to 

that time. In that analysis, summary RRs for squamous cell 

carcinoma, by far the most common histologic type of cervical cancer (American Cancer Society 2016), were lower 

for former smokers (1.12; 95%  CI, 1.01–1.25) than for 

current smokers (1.60; 95% CI, 1.48–1.73). Smoking was 

not associated with adenocarcinoma of the cervix (0.89; 

95% CI, 0.74–1.06), which accounts for a small proportion 

of cervical cancers (American Cancer Society 2016). RRs 

have also been greater for current smokers than for former 

smokers in studies published after 2006 (Odongua et al. 

2007; Madsen et al. 2008; Roura et al. 2014).

Using data from a subset of studies in its pooled analysis, ICESCC (2006) reported on the risk of cervical cancer 

by number of years since smoking cessation. Table  4.7

summarizes these results and results from two other 

studies published since 2004, including a case-control 

study (Shields et al. 2004) and a cohort study (Roura et al. 

2014). In the pooled analysis, estimates of RR were slightly 

lower for having quit 10 or more years ago versus having 

done so more recently, although trends by number of years 

since smoking cessation were not statistically significant. 

The cohort study (Roura et al. 2014), which was conducted 

in Europe among 308,036 women, included 261 cases of 

invasive cervical cancer and 804 cases of carcinoma in situ 

(CIS) or cervical intraepithelial cancer grade 3 (CIN3). For 

both invasive cancer and CIS/CIN3, Roura and colleagues 

(2014) found statistically significant decreases in risk as 

the number of years since quitting increased, with risk 

reaching less than or about half that in current smokers 

among women who had quit smoking 20 or more years 

earlier. Finally, Shields and colleagues (2004), in a casecontrol study conducted in five U.S. cities, did not find any 

trends related to number of years since quitting; however, 

their study included relatively few former smokers.

Kidney

The 2004 Surgeon General’s report concluded that 

the evidence was sufficient to infer a causal relationship 

between cigarette smoking and kidney cancer (USDHHS 

2004). Biological mechanisms for such a relationship may 

include oxidative stress (Patel et al. 2015) and exposure 

to nitrosamines and other carcinogens in tobacco smoke 

(USDHHS 2004; Clague et al. 2009). 

In a meta-analysis of more than 20 studies of 

smoking and incident kidney cancer, Cumberbatch and 

colleagues (2016) found that the RR for kidney cancer, in 

comparisons with never smokers, was lower for former 

smokers (RR = 1.16; 95% CI, 1.08–1.25) than for current smokers (RR = 1.36; 95% CI, 1.19–1.56). Finally, 10 

studies, all case-control, examined risk for kidney cancer 

by time since quitting among former smokers (Table 4.8) 

(McLaughlin et al. 1984, 1995; La Vecchia et al. 1990; 

McCredie and Stewart 1992; Kreiger et al. 1993; Muscat 

et al. 1995; Yuan et al. 1998; Parker et al. 2003; Hu et al. 

2005; Cote et al. 2012). In most of these studies, the odds 

ratio (OR) for the highest category of number of years 

since quitting (ranging from >10 to >30 years) was lower 

than the OR for categories with fewer years since quitting. 

Acute Myeloid Leukemia

The 2004 Surgeon General’s report concluded that 

the evidence was sufficient to infer a causal relationship 

between smoking and AML (USDHHS 2004). Potential 
Study Design/populationa Exposure estimates: RR (95% CI) Comments

Choi et al. 

(1991)

• Case-control, hospital-based study

• 216 cases of liver cancer in males and 

648 male controls

• Korea

• Time period in which cases were diagnosed: 

1986–1990

• Smoking status:

– Never smoker: 1.00 (referent)

– Current smoker: 1.01 (0.65–1.57)

– Former smoker: 0.65 (0.35–1.19)

• Number of years since smoking cessation:

– Current smoker: 1.00 (referent)

– 1–4: 0.76 (0.31–1.89)

– 5–9: 0.43 (0.15–1.26)

– ≥10: 0.44 (0.11–1.82)

Adjusted for age, marital status, level of 

education, serum hepatitis B virus surface 

antigen, and alcohol consumption

Goodman et al. 

(1995)

• Cohort study (Life Span Study)

• 36,133 men and women who were in

Hiroshima or Nagasaki at the time of

the atomic bombings in August 1945

• 242 cases of liver cancer

• Japan

• Follow-up period: 1980–1989

• Men:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 4.26 (1.87–9.72)

 Former smoker: 4.56 (1.95–10.7)

– Number of years since smoking cessation:

 Never smoker: 1.00 (referent)

 <14: 5.60 (2.15–14.6)

 14–23: 4.11 (1.58–10.7)

 ≥24: 4.04 (1.54–10.6)

• Women:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.58 (0.86–2.88)

 Former smoker: 1.66 (0.76–3.63)

– Number of years since smoking cessation:

 Never smoker: 1.00 (referent)

 <10: 10.4 (2.51–43.5)

 10–24: 1.03 (0.25–4.24)

 ≥25: 2.31 (0.72–7.43)

Adjusted for city, age at time of the atomic 

bombings, attained age, and radiation dose 

to the liver

Table 4.6 Studies of liver cancer incidence or mortality, by number of years since smoking cessation

A Report of the Surgeon General

196 Chapter 4
Study Design/populationa Exposure estimates: RR (95% CI) Comments

Ozasa (2007) • Cohort study (Japan Collaborative Cohort 

Study for Evaluation of Cancer)

• 620 deaths from liver cancer

• Japan

• Follow-up period: starting in 1988

• Men:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.59 (1.20–2.12)

 Former smoker: 1.48 (1.09–2.00)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 <5: 1.27 (0.81–1.98)

 5–14: 1.54 (1.06–2.23)

 ≥15: 1.54 (1.05–2.27)

• Women:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.95 (1.19–3.19)

 Former smoker: 0.76 (0.24–2.39)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 <5: 1.05 (0.14–7.51)

 5–14: 1.40 (0.34–5.69)

 ≥15: Not reported

Adjusted for age and area of study

Hassan et al. 

(2008)

• Case-control, hospital-based study

• 319 cases of liver cancer among men and 

women treated at MD Anderson Cancer 

Center, and 1,061 controls who were 

relatives of the patients

• Houston, Texas

• Time period in which cases were diagnosed: 

2000–2006

• Number of years since smoking cessation:

– Never smoker: 1.0 (referent)

– ≤10: 1.7 (1.0–3.1)

– >10: 1.3 (0.8–1.9)

Adjusted for age, race, level of education, 

marital status, state of residency, hepatitis B 

virus, hepatitis C virus, diabetes, heavy alcohol 

consumption, and family history of cancer

Did not present results by smoking status

Table 4.6 Continued

The Health Benefits of Smoking Cessation 197

Notes: CI = confidence interval; RR = relative risk.

aStudies are of cancer incidence unless the number of cancer deaths is identified.
Study Design/populationa Exposure estimates: RR (95% CI) Comments

International 

Collaboration of 

Epidemiological 

Studies of 

Cervical Cancer 

(2006)

• Collaborative analysis of 23 cohort and 

case-control studies (The International 

Collaboration of Epidemiological Studies 

of Cervical Cancer)

• 9,052 cases of invasive cancer (7,498 with 

data on number of years since smoking 

cessation), 4,489 cases of carcinoma in situ 

or cervical intraepithelial neoplasia III, and 

23,017 controls

• Studies from Algeria, Brazil, Chile, Colombia, 

Costa Rica, Denmark, India, Italy, Mali, Mexico, 

Morocco, Norway, Panama, Paraguay, Peru, 

Philippines, South Africa, Spain, Sweden, 

Thailand, United Kingdom, and United States

• Number of years since smoking cessation:

– Invasive cancer:

 Never smoker: 1.00 (0.94–1.06)

 Current smoker: 1.46 (1.35–1.58)

 1–4: 1.05 (0.87–1.28)

 5–9: 1.08 (0.85–1.38)

 ≥10: 0.99 (0.83–1.18)

– Carcinoma in situ or cervical intraepithelial 

neoplasia III:

 Never smoker: 1.00 (0.91–1.10)

 Current smoker: 1.83 (1.68–1.99)

 1–4: 1.35 (1.05–1.74)

 5–9: 1.35 (0.99–1.83)

 ≥10: 1.19 (0.85–1.66)

Cohort studies analyzed as nested case-control 

studies, with up to four controls selected 

randomly per case according to age

Adjusted for study, study center, age, age at 

first intercourse, duration and use of oral 

contraception, number of full-term pregnancies, 

and lifetime number of sexual partners

Shields et al. 

(2004)

• Case-control, population-based study

• Women 20–74 years of age

• 235 cases of squamous cell carcinoma 

and 209 controls with seropositive human 

papillomavirus

• Controls obtained from random-digit dialing

• Time period in which cases were diagnosed:

1982–1984

• Five U.S. cities (Birmingham, Chicago, 

Denver, Miami, and Philadelphia)

• Smoking status:

– Never smoker: 1.0 (referent)

– Current smoker: 1.9 (1.2–2.8)

– Former smoker: 1.4 (0.8–2.4)

• Number of years since smoking cessation:

– 1–5: 1.0 (referent)

– 6–14: 0.6 (0.2–2.0)

– ≥15: 0.8 (0.3–2.5)

Cases restricted to squamous cell carcinoma

A Report of the Surgeon General

198 Chapter 4

Table 4.7 Studies of cervical cancer incidence by years since smoking cessation
Study Design/populationa Exposure estimates: RR (95% CI) Comments

Roura et al. 

(2014)

• Cohort study (European Prospective 

Investigation into Cancer and Nutrition)

• 308,036 women, most 35–70 years of age

• 261 cases of ICC and 804 cases of CIS or CIN3

• 10 European countries (Denmark, France, 

Germany, Greece, Italy, Norway, Spain, Sweden, 

the Netherlands, and United Kingdom)

• Follow-up period: 1992–2006

• Smoking status:

– ICC:

 Never smoker: 1.0 (referent)

 Current smoker: 1.9 (1.4–2.5)

 Former smoker: 1.5 (1.1–2.1)

– CIS or CIN3:

 Never smoker: 1.0 (referent)

 Current smoker: 2.1 (1.8–2.5)

 Former smoker: 1.5 (1.2–1.8)

– p trend among former smokers: 0.02

• Number of years since smoking cessation:

– ICC: 

 Current smoker: 1.0 (referent)

 ≤4: 1.2 (0.7–2.0)

 5–9: 0.9 (0.5–1.7)

 10–19: 0.8 (0.5–1.3)

 ≥20: 0.4 (0.2–0.8)

– CIS or CIN3:

 Current smoker: 1.0 (referent)

 ≤4: 0.8 (0.6–1.1)

 5–9: 1.0 (0.7–1.3)

 10–19: 0.5 (0.4–0.8)

 ≥20: 0.5 (0.3–0.7)

• Statistically significant p trends for the 

association between smoking-related variables 

and the risk of CIN3/CIS and ICC by risk factor:

– Smoking duration (years); p trends among 

ever smokers: <0.0001 (CIN3/CIS), 0.08 (ICC)

– Lifetime smoking intensity (cig/day);

– p trend among ever smokers: 0.07 (ICC)

– Smoking pack years; p trends among ever 

smokers: 0.001 (CIN3/CIS); 0.07 (ICC)

– Time since quitting; p trends among past 

smokers: 0.02 (CIN3/CIS); 0.02 (ICC)

Adjusted for BMI, marital status, level of 

education, physical activity, number of fullterm pregnancies, and use and duration of 

oral contraception

Table 4.7 Continued

The Health Benefits of Smoking Cessation 199

Notes: BMI = body mass index; CI = confidence interval; CIN3 = cervical intraepithelial neoplasia III; 

aStudies are of cancer incidence unless the number of cancer deaths is identified.
Study Design/populationa Exposure estimates: RR (95% CI) Comments

McLaughlin 

et al. (1984)

•

•

•

•

•

Case-control, population-based study

White men and women 30–85 years of age

495 cases of kidney cancer and 697 controls

Time period in which cases were diagnosed: 

1974–1979

Minneapolis-St. Paul, Minnesota, 

metropolitan area

• Number of years since smoking cessation:

–

–

Men:









Never smoker: 1.0 (referent):

≤10 prior to 1974: 1.7

>10 prior to 1974: 1.1

Current smoker: 1.8

Women:









Never smoker: 1.0 (referent)

≤10 prior to 1974: 1.7

>10 prior to 1974: 1.6

Current smoker: 2.0

Adjusted for age

Confidence intervals not provided

LaVecchia et al. 

(1990)

•

•

•

•

•

•

Case-control, hospital-based study

Cases: Men and women <75 years of age

Controls: Admitted for acute conditions

131 cases of kidney cancer and 394 controls

Time period in which cases were diagnosed: 

1985–1989

Northern Italy

•

•

•

Number of years since smoking cessation:

– Never smoker: 1.0 (referent)

<10: 2.2 (1.1–4.4)

≥10: 1.3 (0.6–2.7)

Adjusted for age, sex, area of residence, level of 

education, and BMI

Did not present results for current smoking 

status

McCredie et al. 

(1992)

Case-control, population-based study

Men and women 20–79 years of age

489 cases of kidney cancer and 523 controls

Time period in which cases were diagnosed: 

1989–1990

New South Wales, Australia

Smoking status:

–

–

–

Never smoker: 1.00 (referent)

Current smoker: 2.17 (1.55–3.02)

Former smoker: 1.41 (1.03–1.95)

Number of years since smoking cessation:

–

–

–

–

Current smoker: 1.00 (referent)

1–12: 0.85 (0.53–1.38)

13–24: 0.89 (0.52–1.53)

≥25: 0.47 (0.22–1.00)

Adjusted for age, sex, method of interview, 

and BMI

Number of years since smoking cessation 

additionally adjusted for duration of cigarette 

smoking and number of cigarettes smoked 

per day

•

•

•

•

•

–

–

A Report of the Surgeon General

200 Chapter 4

Table 4.8 Studies of kidney cancer incidence by number of years since smoking cessation
Study Design/populationa Exposure estimates: RR (95% CI) Comments

Kreiger et al.

(1993)

• Case-control, population-based study

• Men and women 25–69 years of age

• 518 cases of kidney cancer and 1,381 controls

• Time period in which cases were diagnosed:

• 1994–1997

• Ontario, Canada

• Number of years since smoking cessation:

– Men:

 Never smoker: 1.0 (referent)

 Current smoker: 2.3 (1.5–3.4)

 1–4: 2.1 (1.2–3.8)

 5–9: 1.8 (1.0–3.3)

 10–19: 2.1 (1.3–3.4)

 ≥20: 1.3 (0.8–2.1)

– Women:

 Never smoker: 1.0 (referent)

 Current smoker: 2.2 (1.5–3.2)

 1–4: 1.4 (0.6–2.9)

 5–9: 1.6 (0.7–3.7)

 10–19: 1.9 (0.8–4.2)

 ≥20: 1.5 (0.7–3.1)

Adjusted for age and BMI

McLaughlin

et al. (1995)

• Case-control, population-based study

• Men and women 20–79 years of age

• 1,732 cases of kidney cancer and 2,309 controls

• Time period in which cases were diagnosed: 

1989–1991

• Six study centers in five countries: Australia 

(Sydney), Denmark, Germany (Berlin and 

Heidelberg), Sweden (Uppsala), and United 

States (Minnesota)

• Smoking status:

– Never smoker: 1.0 (referent)

– Current smoker: 1.4 (1.2–1.7)

– Former smoker: 1.2 (1.0–1.4)

• Number of years since smoking cessation:

– Current smoker: 1.0 (referent)

– ≤5: 0.90 (0.7–1.2)

– 6–15: 0.84 (0.7–1.1)

– 16–25: 0.75 (0.6–1.0)

– >25: 0.85 (0.6–1.1)

Adjusted for age, sex, study center, and BMI

Number of years since smoking cessation 

additionally adjusted for number of cigarettes 

smoked per day

Table 4.8 Continued

The Health Benefits of Smoking Cessation 201
Study Design/populationa Exposure estimates: RR (95% CI) Comments

Muscat et al. 

(1995)

• Case-control, hospital-based study

• Cases: Men and women diagnosed at hospitals 

in the study areas

• Controls: Hospitalized for conditions unrelated 

to tobacco use

• 788 cases of kidney cancer and 779 controls

• Time period in which cases were diagnosed: 

1977–1993

• Multicenter hospitals in New York (New York 

City and New Hyde Park), Illinois (Chicago 

and Hines), Michigan (Detroit), and 

Pennsylvania (Philadelphia)

• Men:

– Smoking status:

 Never smoker: 1.0 (referent)

 Current smoker: 1.4 (1.02–2.0)

 Former smoker: 0.9 (0.7–1.5)

– Number of years since smoking cessation:

 Never smoker: 1.0 (referent)

 1–5: 1.6 (0.9–2.6)

 6–10: 2.2 (1.2–4.4)

 >10: 0.7 (0.5–0.9)

• Women

– Smoking status:

 Never smoker: 1.0 (referent)

 Current smoker: 1.0 (0.7–1.6)

 Former smoker: 1.1 (0.7–1.7)

– Number of years since smoking cessation:

 Never smoker: 1.0 (referent)

 1–5: 1.0 (0.4–2.2)

 6–10: 1.3 (0.3–6.0)

 >10: 1.1 (0.6–1.8)

Adjusted for age and level of education

Yuan et al. 

(1998)

• Case-control, population-based study

• Non-Asian men and women 25–74 years of age

• 1,204 cases of kidney cancer and 1,204 controls

• Time period in which cases were diagnosed: 

1986–1994

• Los Angeles, California

• Smoking status:

– Never smoker: 1.00 (referent)

– Current smoker: 1.53 (1.23–1.90)

– Former smoker: 1.24 (1.02–1.50)

• Number of years since smoking cessation:

– Never smoker: 1.00 (referent)

– 1–9: 1.33 (1.02–1.74)

– 10–19: 1.25 (0.94–1.64)

– ≥20: 1.15 (0.89–1.50)

Adjusted for level of education

Parker et al. 

(2003)

• Case-control, population-based study

• Men and women 40–85 years of age

• 387 cases of kidney cancer and 2,333 controls

• Time period in which cases were diagnosed: 

1985–1987

• Iowa

• Number of years of smoking cessation:

– Current smoker: 1.00 (referent)

– Never smoker: 0.6 (0.4–0.9)

– <10: 0.7 (0.4–1.1)

– 10–19: 0.8 (0.5–1.2)

– 20–29: 0.7 (0.4–1.1)

– ≥30: 0.5 (0.3–1.0)

Adjusted for age, sex, BMI, history of 

hypertension, and pack-years of smoking

Table 4.8 Continued

A Report of the Surgeon General

202 Chapter 4
Study Design/populationa Exposure estimates: RR (95% CI) Comments

Hu et al. (2005) • Case-control, population-based study

• Men and women 20 years of age and older

• 1,279 cases of kidney cancer and 5,370 controls

• Time period in which cases were diagnosed: 

1994–1997

• Eight Canadian provinces: Alberta, British 

Columbia, Manitoba, Newfoundland, Nova 

Scotia, Ontario, Prince Edward Island, 

and Saskatchewan

• Men:

– Smoking status:

 Never smoker: 1.0 (referent)

 Current smoker: 0.9 (0.7–1.2)

 Former smoker: 1.2 (1.0–1.5)

– Number of years since smoking cessation:

 Never smoker: 1.0 (referent)

 ≤10: 1.5 (1.0–2.3)

 11–20: 1.1 (0.8–1.5)

 21–30: 1.2 (0.8–1.6)

 ≥31: 1.0 (0.7–1.4)

• Women:

– Smoking status:

 Never smoker: 1.0 (referent)

 Current smoker: 0.9 (0.7–1.2)

 Former smoker: 1.3 (1.0–1.6)

– Number of years since smoking cessation:

 Never smoker: 1.0 (referent)

 ≤10: 1.5 (0.8–2.6)

 11–20: 0.6 (0.4–1.1)

 ≥20: 1.1 (0.7–1.6)

Adjusted for age; Canadian province; level of 

education; BMI; alcohol use; and consumption 

of meats, vegetables, and fruits

Number of years since smoking cessation 

additionally adjusted for pack-years of smoking

Table 4.8 Continued

The Health Benefits of Smoking Cessation 203
Study Design/populationa Exposure estimates: RR (95% CI) Comments

Cote et al. 

(2012)

• Case-control, population-based study

• Men and women 20–79 years of age

• 1,217 cases of kidney cancer and 1,235 controls

• Time period in which cases were diagnosed: 

2002–2007

• Detroit (Michigan) and Chicago (Illinois)

• White:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.46 (1.05–2.04)

 Former smoker: 0.99 (0.78–1.25)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 ≤5: 1.34 (0.83–2.17)

 6–15: 0.82 (0.53–1.25)

 16–25: 0.61 (0.39–0.94)

 ≥25: 0.62 (0.39–1.01)

• Black:

– Smoking status:

 Never smoker: 1.00 (referent)

 Current smoker: 1.16 (0.81–1.65)

 Former smoker: 0.81 (0.56–1.18)

– Number of years since smoking cessation:

 Current smoker: 1.00 (referent)

 ≤5: 0.97 (0.51–1.85)

 6–15: 0.73 (0.42–1.26)

 16–25: 0.72 (0.38–1.37)

 ≥25: 0.47 (0.25–0.88)

Adjusted for age, study site, sex, BMI, education 

level, family history of kidney cancer, and 

hypertension

Number of years since smoking cessation 

additionally adjusted for pack-years of smoking

Table 4.8 Continued

A Report of the Surgeon General

204 Chapter 4

Notes: BMI = body mass index; CI = confidence interval; OR = odds ratio.

aStudies are of cancer incidence unless number of cancer deaths is identified.
The Health Benefits of Smoking Cessation 205

Smoking Cessation

mechanisms include inhalation of benzene, a known 

cause of leukemia, and radioactive substances in tobacco 

smoke (Thomas and Chelghoum 2004; USDHHS 2004; 

Lichtman 2007).

In a meta-analysis of 5 cohort and 12 case-control 

studies of smoking and AML, Colamesta and colleagues 

(2016) reported separate summary RRs for cohort and casecontrol studies. For the cohort studies, summary RR estimates were 1.45 (95% CI, 1.08–1.94) for former smokers 

and 1.52 (95% CI, 1.10–2.14) for current smokers. For the 

case-control studies, summary RRs were 1.21 (95%  CI, 

1.03–1.41) for former smokers and 1.36 (95%  CI, 1.11–

1.66) for current smokers. This meta-analysis also pooled 

data that included information on number of years since 

cessation from three case-control studies (Severson et al. 

1990; Kane et  al. 1999; Musselman et  al. 2013). In the 

pooled analysis, risk declined with increasing time since 

smoking cessation, with no statistically significant reduction in risk among former smokers who had quit within 

10 years compared with continuing smokers (OR = 1.01; 

95% CI, 0.60–1.72). The risk was lower for those who had 

quit for 10–20 years (OR = 0.74; 95% CI, 0.53–1.03) and 

even lower for those who had quit for more than 20 years 

(OR = 0.59; 95% CI, 0.45–0.78).

Synthesis of the Evidence

The 1990 Surgeon General’s report concluded that 

smoking cessation reduces the risk of six cancers: lung, 

larynx, oral cavity and pharynx, esophagus, pancreas, 

and bladder (USDHHS 1990). Results of studies published since 1990 expand the role of smoking as a cause of 

cancer and support the reduction of cancer risk following 

smoking cessation.

The 2004 and 2014 Surgeon General’s reports concluded that smoking causes at least six additional cancers 

beyond those for which the associations were considered 

causal in 1990: stomach, liver, colon and rectum, kidney, 

cervix, and AML (USDHHS 2004, 2014). The 12  types of 

cancer reviewed in this section have all been judged to be 

caused by cigarette smoking in reports of the U.S. Surgeon 

General (USDHHS 2014) and IARC (IARC 2012)—based on 

evaluating the evidence against criteria for causality utilized 

in Surgeon Generals’ reports, including consistency across 

studies, temporal relationship of association, strength of 

association, and biological plausibility (USDHHS 2004).

These same criteria have been used to evaluate the 

evidence on smoking cessation. Because smoking cessation reduces cumulative exposure to tobacco smoke across 

the life course, biological plausibility alone, coupled with 

appropriate temporality, supports the conclusion that 

smoking cessation reduces the risk of all 12  cancers 

that have been causally linked to cigarette smoking. 

Additionally, epidemiological evidence documents that 

the risk for most of these cancers drops progressively as 

the time since successful quitting lengthens, and findings 

are generally consistent across studies.

The effect of smoking cessation on risk for lung 

cancer is particularly important because lung cancer is 

the largest contributor to smoking-attributable cancer 

mortality in the United States and the number of new 

cases continues to increase (U.S. Cancer Statistics 

Working Group 2019). Since 1990, many studies have 

been published characterizing how risk for lung cancer 

changes with time since smoking cessation. As noted 

previously, results from many studies (Calle et al. 2002; 

IARC 2007; Pinsky et al. 2015) indicate that, in comparison with smokers who do not quit, RRs for lung cancer 

decline steadily after smoking cessation, with RRs for 

former smokers falling to half those of RRs for continuing 

smokers after approximately 10–15 years of cessation. 

While the 2004 and 2014 Surgeon General’s reports 

concluded that smoking causes cancers of the stomach, 

colon and rectum, kidney, and cervix and AML (USDHHS 

2004, 2014), the two reports did not explicitly conclude 

that smoking cessation reduces the risk for these cancers. For four of these malignancies (stomach, kidney, 

cervix, and AML), RRs are consistently lower among 

former cigarette smokers than among current smokers, 

supporting a causal association between smoking cessation and lower risk for these cancers. Similarly, the 2004 

and 2014 Surgeon General’s reports also concluded that 

smoking causes cancer of the liver (USDHHS 2004, 2014). 

This report considered four specific studies showing that 

RRs decline in former smokers with time since smoking 

cessation. These findings were consistent with the metaanalysis of 29 studies conducted for the 2014 Surgeon 

General’s report that documented a much lower RR in 

former smokers than in current smokers, compared with 

never smokers (USDHHS 2014). Taken together, these 

epidemiological findings support a causal association 

between smoking cessation and lower risk for liver cancer. 

In studies of colorectal cancer, RRs for former 

smokers have not been consistently lower than those for 

current smokers. However, in many of the studies where 

lower RRs have not been observed for former smokers, current smokers likely did not have sufficiently long induction 

periods to fully reflect the long-term effects of smoking. 

In addition to the studies where lower RRs were observed, 

other evidence supports the hypothesis that smoking cessation reduces risk of colorectal cancer. This evidence 

includes studies that document substantially lower RRs 

for colorectal adenoma, an established precursor lesion for 

colorectal cancer, among former smokers than among current smokers. These studies have also found declining RRs 
A Report of the Surgeon General

206 Chapter 4

for colorectal cancer among former smokers with increased 

time since smoking cessation, particularly for specific 

molecular subtypes that are associated with smoking. Taken 

together, these epidemiological findings, including those of 

incident colorectal cancer and established precursor lesions 

for colorectal cancer, support a causal association between 

smoking cessation and lower risk for colorectal cancer.

Conclusions

1. The evidence is sufficient to infer that smoking 

cessation reduces the risk of lung cancer. 

2. The evidence is sufficient to infer that smoking 

cessation reduces the risk of laryngeal cancer. 

3. The evidence is sufficient to infer that smoking 

cessation reduces the risk of cancers of the oral 

cavity and pharynx

4. The evidence is sufficient to infer that smoking 

cessation reduces the risk of esophageal cancer. 

5. The evidence is sufficient to infer that smoking 

cessation reduces the risk of pancreatic cancer.

6. The evidence is sufficient to infer that smoking 

cessation reduces the risk of bladder cancer. 

7. The evidence is sufficient to infer that smoking 

cessation reduces the risk of stomach cancer.

8. The evidence is sufficient to infer that smoking 

cessation reduces the risk of colorectal cancer.

9. The evidence is sufficient to infer that smoking 

cessation reduces the risk of liver cancer.

10. The evidence is sufficient to infer that smoking 

cessation reduces the risk of cervical cancer.

11. The evidence is sufficient to infer that smoking 

cessation reduces the risk of kidney cancer.

12. The evidence is sufficient to infer that smoking 

cessation reduces the risk of acute myeloid leukemia.

13. The evidence is sufficient to infer that the relative 

risk of lung cancer decreases steadily after smoking 

cessation compared with the risk for persons continuing to smoke, with risk decreasing to half that 

of continuing smokers approximately 10–15  years 

after smoking cessation and decreasing further with 

continued cessation.

Implications

The evidence that smoking cessation reduces cancer 

risk has long been an important part of the rationale for 

efforts—including educational, clinical, health systems, 

community, and population-based interventions and initiatives to make evidence-based, barrier-free cessation 

services widely available—to motivate and help smokers 

to quit. This report’s conclusion that smoking cessation 

reduces the risk of several additional types of cancer further strengthens that rationale and provides an opportunity for broadening and intensifying messages about the 

important role that smoking cessation plays in cancer 

prevention.

Smoking Cessation After a Cancer Diagnosis

This section reviews evidence of the health benefits 

of smoking cessation at the time of a cancer diagnosis or 

after that diagnosis compared with continuing to smoke. 

At the time of cancer diagnosis, approximately 20–30% of 

all cancer patients self-reported current cigarette smoking 

(Warren and Simmons 2018); however, self-reported rates 

of smoking were typically lower than biochemically confirmed smoking, as smokers with cancer may misrepresent their smoking. Among long-term cancer survivors, 

the smoking prevalence is approximately 9% (Warren 

and Simmons 2018). This review is limited to all-cause 

mortality, an integrative indicator, and does not explore 

disease progression or recurrence, cancer-specific mortality, second primary cancer, quality of life, or treatment 

toxicity as outcomes of interest.

Conclusions from Previous 

Surgeon General’s Reports

Previous reports of the Surgeon General have not 

evaluated the health benefits of smoking cessation after 

a cancer diagnosis, but smoking is causally associated 

with diseases of every major organ system and is therefore 
The Health Benefits of Smoking Cessation 207

Smoking Cessation

strongly linked with all-cause mortality (USDHHS 2014).

The 2014 Surgeon General’s report concluded that 

smoking increases all-cause mortality. The 2014 report 

was also the first to conclude that continued smoking 

after a cancer diagnosis causes adverse health outcomes 

among cancer patients or survivors (i.e., persons who have 

been diagnosed with cancer) (U.S. Department of Health 

and Human Services [USDHHS] 2014). Smoking cessation has been shown to reduce all-cause mortality in the 

general population (USDHHS 2014), providing strong justification for the hypothesis that cessation after a cancer 

diagnosis will result in improved survival compared with 

continued smoking. Given the conclusions in the 2014 

Surgeon General’s report about the adverse health effects 

that cancer patients who smoke can experience, a review 

of the evidence on smoking cessation after a cancer diagnosis is important.

Literature Review Methods

The literature search for this section followed 

the strategy used in the 2014 Surgeon General’s report 

(USDHHS 2014), which queried the National Library 

of Medicine’s MEDLINE database for “smoking” and 

“cancer.” Studies were considered for inclusion if they met 

three criteria:

• They were original reports that compared all-cause

mortality between (a)  current smokers who were

diagnosed with cancer but continued smoking and

(b) patients who had quit smoking within 1 year of a

cancer diagnosis or patients who had quit smoking

after a cancer diagnosis;

• They had a baseline and final cohort size of at least

100 cancer patients, including cigarette smokers

and quitters; and

• They were published from 2000 to 2016.

Studies were excluded if they reported findings on only 

continued smoking after a cancer diagnosis versus quitting smoking substantially before a cancer diagnosis. 

Smoking Cessation and All-Cause 

Mortality in Cancer Patients

Ten studies (seven prospective cohort studies 

and three retrospective cohort studies) reporting on 

10,975 patients met the inclusion criteria (Table 4.9). The 

studies are grouped in the table by their reference group: 

never smokers, current smokers who did not stop smoking 

with diagnosis (referred to as persistent smokers), and 

quitters. The cohorts were composed of patients with 

lung cancer (four studies), with head/neck cancer (three 

studies), with breast cancer (one study), and with multiple 

types of cancer (two studies). Eight studies did not specify 

the treatment modality (surgery, radiotherapy, chemotherapy), and two patient cohorts were composed exclusively of patients treated with radiotherapy (Al-Mamgani 

et al. 2014; Roach et al. 2016).

Three prospective cohort studies (Al-Mamgani et al. 

2014; Choi et  al. 2016; Passarelli et  al. 2016) compared 

continued smoking and quitting smoking with never 

smoking. In all three studies, continued smoking after a 

cancer diagnosis significantly increased risk of mortality 

compared with never smoking, and the risk of mortality 

for quitters was greater than that for never smokers but 

not as great as that for continuing smokers.

Three studies (Sardari Nia et  al. 2005; Sandoval 

et al. 2009; Chen et al. 2010) compared quitting smoking 

with persistent smoking using persistent smokers as 

the referent. Quitting was significantly associated with 

reduced all-cause mortality in two studies, with associations that were significant in patients with non-small cell 

lung cancer (relative risk [RR] = 0.34; 95% CI, 0.16–0.71) 

(Sardari Nia et  al. 2005) and in patients with small cell 

lung cancer (hazard ratio [HR] = 0.55; 95% CI, 0.38–0.79) 

(Chen et al. 2010), but not in a study of patients with oral 

cavity cancer (RR  =  0.92; 95%  CI, 0.46–1.84) (Sandoval 

et al. 2009).

Four studies compared continued cigarette smoking 

with quitting, using quitters as the referent (Tao et  al. 

2013; Al-Mamgani et al. 2014; Dobson Amato et al. 2015; 

Roach et al. 2016). In all four studies, continued smoking 

was associated with increased all-cause mortality relative to quitting. For a group of 1,632 male cancer patients 

from the Shanghai Cancer Cohort (Tao et al. 2013), results 

by disease site showed (a) a significantly increased risk of 

all-cause mortality in persistent (continued) smokers for 

lung cancer (HR  =  1.89; 95%  CI, 1.18–3.02), colorectal 

cancer (HR = 3.46; 95% CI, 1.69–7.10), and bladder cancer 

(HR = 17.29; 95% CI, 2.25–132.64) and (b) indication of 

increased mortality in other cancers (HR = 1.49; 95% CI, 

0.92–2.40).

Evaluation of the Evidence

This is the first review in a report of the Surgeon 

General on the potential health benefits of smoking cessation after a cancer diagnosis. This section considers scientific evidence with reference to five key guidelines for 
Study Design/population Follow-up period

Comparison 

group(s) Definitions of groups Findings

Reference group: 

Never smokers

Yang et al. (2015a) •

•

•

Prospective cohort

2,548 patients with

colorectal cancer from 

CPS II

153 current smokers

at baseline

• Every 2 years

from 1997 to

December 31,

2010

•

•

Quitters

Persistent

smokers

•

•

•

Neversmokers:Thosewhonever

smoked

Quitters: Those who hadquit

smoking after a cancer diagnosis

Persistent smokers: Those

who continued to smoke after a

cancer diagnosis

• Adjusted RR:

–

–

–

Never smokers: 1.0(referent)

Quitters: 1.94 (95% CI,

1.29–2.91)

Persistent smokers: 2.33

(95% CI, 1.62–3.34)

• RR for quitters vs. persistent

smokers: 0.833 (p = 0.37,

1.94 vs. 2.33)

Choi et al. (2016) •

•

•

•

•

Prospective cohort

590 patients withhead

or neck cancer

146 persistent smokers

at any time after a

cancer diagnosis

99 quitters

University of Michigan

•

•

Every 3 months

for 2 years

Annually after

the first 2 years

until 8 years of

follow-up or

September 11,

2011, whichever

came first

•

•

Quitters

Persistent

smokers

•

•

•

Neversmokers:Thosewhonever

smoked

Quitters: Those who hadquit

within the first 3 months of

diagnosis of squamous cell

carcinoma (head or neck) and

remained a quitter through the

first 2 years after the diagnosis

Persistent smokers:Those who

smoked at any time after a cancer

diagnosis (defined as continuing

smokers in the study)

• Adjusted HR:

–

–

–

Never smokers: 1.0 (referent)

Quitters: 2.38 (95% CI,

1.29–4.36)

Persistent smokers: 2.71

(95% CI, 1.48–4.98)

• RR for quitters vs. persistent

smokers: 0.877 (2.38 vs. 2.71,

calculated)

Passarelli et al. 

(2016)

• Median follow-up

of 6 years after

diagnosis

•

•

Quitters

Persistent

smokers

•

•

•

Never smokers: Those who never 

smoked

Quitters: Those who had quit 

smoking during the year before the 

cancer diagnosis and remained a 

quitter after the diagnosis

Persistent smokers: Those who 

reported actively smoking during 

the year before the cancer diagnosis 

and after the diagnosis

• Adjusted HR:

–

–

–

Neversmokers: 1.0 (referent)

Quitters: 2.34 (95% CI, 

1.85–2.96)

Persistent smokers: 2.57

(95% CI, 2.06–3.21)

• RR for quitters vs. persistent 

smokers: 0.911 (2.34 vs. 2.57, 

calculated)

•

•

•

•

Prospective cohort

4,562patientswithbreast 

cancer, as a part of the

Collaborative Breast Cancer

Study and Collaborative

Women’sLongevity Study

424 persistent smokers

352 quitters

Table 4.9 Cohort studies that compared all-cause mortality in persons who were smokers at the time of a cancer diagnosis but had quit smoking after 

the diagnosis with those who continued smoking after the diagnosis

A Report of the Surgeon General

208 Chapter 4
Study Design/population Follow-up period

Comparison 

group(s) Definitions of groups Findings

Reference group: 

Persistent smokers

Sardari Nia et al.

(2005)

•

•

•

•

•

Prospective cohort

321 patients with non-small 

cell lung cancer

169 persistent smokers

35 quitters

Belgium

•

•

•

Every 4 months 

in Years 1 and 2

Every 6 months 

in Year 3

Annually from 

Years 4 to 6 

through January 

2003

• Quitters •

•

Persistent smokers: Patients who 

continued smoking (defined as 

current smokers in the study)

Quitters: Patients who had stopped 

smoking between the cancer 

diagnosis and the surgery. (1 week 

to more than 19 years)

•

•

Persistent smokers: 1.0 (referent)

Quitters: unadjusted RR = 0.34

(95% CI, 0.16–0.71)

Chen et al. (2010) •

•

•

•

•

Retrospective cohort

284 patients with limitedstage, small cell lung cancer

76 persistent smokers

87 quitters

Mayo Clinic

• At 6 months after 

diagnosis, then 

annually until 

December 2003

• Quitters •

•

Persistent smokers: Those who 

never quit smoking

Quitters: Those who had quit 

smoking at the time of or after 

the cancer diagnosis

•

•

Persistent smokers: 1.0 (referent)

Quitters: adjusted HR = 0.55

(95% CI, 0.38–0.79)

Sandoval et al.

(2009)

•

•

•

•

•

•

Prospective cohort

146 patients with oral 

cavity cancer

101 patients who were 

current smokers at baseline

30 persistent smokers at 

1-year follow-up

55 quitters

Spain

• At 1 year and 

2 years after 

diagnosis

• Quitters • Persistent smokers: Those 

who were classified as current 

smokers at diagnosis of oral cancer 

and continued to smoke after

the diagnosis

• Quitters: Those who had quit 

smoking after the diagnosis, 

defined as quitting smoking at 

1-year follow-up

•

•

Persistent smokers: 1.0 (referent)

Quitters: unadjusted RR = 0.92 

(95% CI, 0.46–1.84)

Table 4.9 Continued

The Health Benefits of Smoking Cessation 209
Study Design/population Follow-up period

Comparison 

group(s) Definitions of groups Findings

Reference group: 

Quitters

Tao et al. (2013) •

•

•

Prospective cohort

Shanghai Cohort Study

1,632 male patients 

with cancer

– 288 with lung cancer

– 362 with stomach cancer

– 248 with colorectal cancer

– 107 with bladder cancer

– 132 with prostate cancer

– 492 with other cancer

• 197 persistent smokers

• 214 quitters

• Annually for 

25 years through 

2010

• Persistent 

smokers

• Quitters: Those who had quit 

smoking after a cancer diagnosis 

and remained quit throughout 

follow-up

• Persistent smokers: Those who 

continued to smoke after a cancer 

diagnosis throughout follow-up

• Adjusted HR:

– Quitters: 1.0 (referent)

– Persistent smokers: 1.76 

(95% CI, 1.37–2.27)

• RR for quitters vs. persistent 

smokers: 0.568 (95% CI, 

0.441–0.730)

Al-Mamgani et al.

(2014)

• Retrospective cohort

• 549 patients with T1a

glottic cancer

• 52 persistent smokers

after radiotherapy

• 215 quitters

• At the end of

radiotherapy:

– Weeks 4 and 6

– Months 3, 6, 12,

18, and 24

• Year 1: Every 2 

months

• Years 2 and 3:

Every 3 months

• Year 4 and beyond:

Every 6 months

• Persistent

smokers

• Quitters: Those who had stopped

smoking after radiotherapy for

T1a glottic cancer

• Persistent smokers: Those

who continued to smoke after

radiotherapy for T1a glottic cancer

• Surviving percentage (not defined,

but implied as 10-year survival):

– Persistent smokers: 36%

– Quitters: 70% (p <0.001)

• RR for quitters vs. persistent

smokers: 0.190 (95% CI,

0.126–0.288, calculated)

Dobson Amato

et al. (2015)

• Prospective cohort

• 224 patients with lung

cancer, all of whom were

enrolled in a telephone-based

tobacco treatment program

• 129 persistent smokers at

last follow-up

• 95 quitters at last follow-up

• Roswell Park Cancer 

Institute

• Survival duration

was assessed in

May 2014

• Persistent

smokers

• Quitters: Those who reported

having at least 24 hours’ abstinence

since the previous contact or

follow-up assessment, or who had

quit before the initial contact

• Persistent smokers: Current

smokers found at every contact

not to have quit

• Adjusted HR:

– Quitters: 1.0 (referent)

– Persistent smokers: 1.79

(95% CI, 1.14–2.82)

• RR for quitters vs. persistent

smokers: 0.558 (95% CI,

0.355–0.877)

Table 4.9 Continued

A Report of the Surgeon General

210 Chapter 4
Study Design/population Follow-up period

Comparison 

group(s) Definitions of groups Findings

Reference group: 

Quitters (continued)

Roach et al. (2016) • Retrospective cohort

• 119 patients with lung 

cancer who were current 

smokers and treated 

with SBRT

• 87 persistent smokers

• 32 quitters

• Physical exam 

every 3 months 

for Years 1 and 2

• Chest CT scan 

every 3 months for 

Years 1 and 2, then 

every 6 months 

thereafter

• Follow-up from 

2004 to 2013

• Persistent 

smokers

• Quitters: Those who had quit 

smoking after SBRT

• Persistent smokers: Those who 

smoked during and after SBRT

• Adjusted HR:

– Quitters: 1.0 (referent)

– Persistent smokers: 2.07 (95% 

CI, 1.02–4.2)

• RR for quitters vs. persistent 

smokers: 0.483 (95% CI, 

0.238–0.980)

Table 4.9 Continued

The Health Benefits of Smoking Cessation 211

Notes: CI = confidence interval; CPS = Cancer Prevention Study; CT = computed tomography; HR = hazard ratio; RR = risk ratio; SBRT = stereotactic body radiation therapy.
A Report of the Surgeon General

212 Chapter 4

causal inference set out in the 1964 and 2004 Surgeon 

General’s reports (U.S. Department of Health, Education, 

and Welfare 1964; USDHHS 2004).

Temporality

All studies evaluated the effects of smoking cessation after a cancer diagnosis. In all the studies, the temporal relationship was appropriate for causation because 

evaluation of smoking status, including smoking cessation, preceded the outcome of all-cause mortality.

Consistency

Six of the seven studies that directly compared 

smoking cessation with continued smoking observed significant improvements in all-cause mortality (Sardari Nia 

et  al. 2005; Sandoval et  al. 2009; Chen et  al. 2010; Tao 

et al. 2013; Al-Mamgani et al. 2014; Dobson Amato et al. 

2015). In the three studies that compared the risks of continued smoking or smoking cessation after a cancer diagnosis with never smoking, quitting smoking reduced risk 

compared with continued smoking (Yang et  al. 2015a; 

Choi et al. 2016; Passarelli et al. 2016). The consistency 

of the observations extended across multiple types of 

cancer: head/neck, lung, breast, colorectal, bladder, and 

prostate. Observations spanned treatments with surgery, 

chemotherapy, or radiotherapy. Studies varied in geographic location and time span and in methodologic definitions for smoking status. Thus, in the broad range of 

the studies across cancer sites, treatments, and definitions of changes in smoking status, evidence consistently 

showed an improvement in all-cause mortality as a result 

of smoking cessation.

Strength of Association

The 2014 Surgeon General’s report observed a 51% 

median increase in risk of all-cause mortality among 

cancer patients who were smokers compared with those 

who were never smokers (USDHHS 2014). For comparison, a review of 22  population-based cohorts from the 

Consortium on Health and Ageing: Network of Cohorts in 

Europe and the United States (CHANCES) found a doubled 

risk of all-cause mortality in current smokers and a 30% 

increased risk in former smokers compared with never 

smokers, reflecting an approximately 50% higher risk 

for current smokers compared with those who had quit 

smoking (Müezzinler et  al. 2015). In the seven cohorts 

reviewed for this report that compared the effects of continued smoking and smoking cessation on all-cause mortality, the median relative risk of all-cause mortality was 

1.82. Thus, with regard to all-cause mortality, the strength 

of the association between smoking and the reduction in 

risk for quitters is similar among cancer survivors and the 

general population.

Existing scientific evidence indicates that cancer 

patients substantially underreport their smoking: approximately 30% of patients who were smokers based on cotinine level reported themselves as nonsmokers (Khuri 

et al. 2001; Warren et al. 2012; Morales et al. 2013; Alberg 

et al. 2015). Thus, the associations between self-reported 

smoking and all-cause mortality, as reported in the 2014 

Surgeon General’s report, may be conservative.

Coherence

Smoking cessation at any age reduces all-cause 

mortality (USDHHS 2010, 2014; Thun et al. 2013b; 

Müezzinler et  al. 2015). The adverse effects of smoking 

and the benefits of smoking cessation are well established 

for many diseases in the general population, including 

coronary heart disease, pulmonary disease, stroke, and 

other chronic health conditions. Smoking cessation 

reduces the risk of developing multiple types of cancer. 

Cigarette smoking by cancer patients increases allcause mortality and cancer-specific mortality (USDHHS 

2014). Much is known about the mechanisms by which 

smoking causes cancer (USDHHS 2010). Among these 

mechanisms, smoking appears to increase tumor progression. In experimental systems, constituents of cigarette smoke promote more aggressive phenotypes in 

cancer cells (Sobus and Warren 2014; Warren et al. 2014). 

A body of experimental evidence suggests that nicotine 

may promote all proliferation and tumor progression 

and increase risk for metastasis (Schaal and Chellappan 

2014). Thus, smoking cessation among cancer patients 

would be anticipated to reduce all-cause mortality by 

reducing both noncancer-related mortality and cancerrelated mortality. The 2014 Surgeon General’s report 

identified a 51% median increased risk of all-cause mortality among cancer patients who smoked compared with 

cancer patients who quit smoking.

Synthesis of the Evidence

Ten studies in this section met the inclusion criteria, all including participants who were current smokers 

at the time of cancer diagnosis and who were evaluated for 

smoking cessation after diagnosis. The findings showed a 

benefit of cessation across a variety of cancer diagnoses 

and treatments. The magnitude of the observed associations is consistent with established reductions in all-cause 

mortality for smoking cessation in the general population. 

Given the relatively small body of evidence, limitations 

in the quality of the evidence, and the breadth of cancer 
The Health Benefits of Smoking Cessation 213

Smoking Cessation

diagnoses and treatments, current evidence is suggestive 

but not sufficient to conclude that the observed reductions in all-cause mortality following smoking cessation 

generalize to all types of malignancies and modalities of 

treatment. The 2014 Surgeon General’s report concluded 

that “quitting smoking improves the prognosis of cancer 

patients” (USDHHS 2014, p. 9). This cancer-specific conclusion contrasts with nonspecific, all-cause mortality, 

as considered above.

Conclusion

1. The evidence is suggestive but not sufficient to infer

a causal relationship between smoking cessation

and improved all-cause mortality in cancer patients

who are current smokers at the time of a cancer

diagnosis.

Implications

The evidence suggests that smoking cessation after 

a cancer diagnosis can significantly reduce all-cause mortality relative to continued smoking. This evidence is consistent with the known reduction in all-cause mortality 

due to smoking cessation in the general population. Thus, 

smoking cessation likely reduces all-cause mortality in 

cancer patients.

These conclusions strengthen the scientific basis 

for existing recommendations that emphasize the importance of quitting smoking after a cancer diagnosis. Many 

large national and international cancer organizations recommend addressing tobacco use among cancer patients. 

The American Society of Clinical Oncology (ASCO) and 

the American Association for Cancer Research (AACR)—

two of the largest clinical oncology and research organizations—maintain updated recommendations for 

addressing tobacco use in cancer patients. These organizations advocate for tobacco control, development of 

methods to facilitate smoking cessation, and practical 

approaches to enhance clinical care and research (AACR 

n.d.; ASCO n.d.). The International Association for the

Study of Lung Cancer (IASLC) offers advanced recommendations for addressing tobacco use, particularly in

the context of cancer care and lung cancer screening

(IASLC n.d.). Recognizing the importance of addressing

tobacco use and the lack of standardized approaches to

screening, the National Cancer Institute (NCI) and the

AACR developed standardized approaches for assessing

tobacco use in clinical cancer research trials (Land et al.

2016). Similar standardized approaches to screening

recommended by the NCI and AACR can also be applied 

to clinical care. Using these approaches, the National 

Comprehensive Cancer Network (NCCN) initiated the 

first series of recommendations to address tobacco use 

in all cancer patients who report having smoked during 

the past 30 days (NCCN n.d.). These guidelines follow the 

same format and approach as other clinical cancer guidelines, offering a resource to facilitate support for smoking 

cessation in a format that oncologists are familiar with. 

Although guidelines are available, they are not always 

implemented completely (Goldstein et al. 2013; Toll et al. 

2013; Gritz et al. 2014; Gallaway et al. 2019), and tobacco 

treatment/cessation programs are not always offered in all 

cancer centers (Gallaway et al. 2019), suggesting a need 

to identify and address barriers to adoption of guidelines.

At present there is no standard format to promote 

smoking cessation in cancer patients. The context of 

addressing tobacco use in cancer patients is different from 

the context of addressing tobacco use in the general population of persons who do not have cancer because cancer 

patients are commonly presented with life-changing diagnoses and will regularly return for treatment for several months or years (Warren et al. 2014). The change in 

clinical care patterns associated with a new cancer diagnosis can affect frequency of follow-up with clinical providers and the perceived urgency of addressing tobacco 

use. Recognizing the clinical importance of tobacco use 

and tobacco cessation with the importance of developing 

approaches across a wide spectrum of clinical settings, 

NCI initiated in 2017 a Cancer Center Cessation Initiative 

(C3I) to fund the development of dedicated tobacco cessation approaches in 22 NCI Designated Cancer Centers 

(NCI 2018). In 2018, an additional 20  centers received 

funding at the same level (Croyle et  al. 2019). Results 

from these centers are expected to help refine standardized approaches to screening for tobacco use and providing evidence-based support for smoking cessation. 

Furthermore, Warren and colleagues (2019) modeled 

the incremental costs due to failure of first-line cancer 

treatments because of continued smoking. Compared 

with nonsmokers, the attributable costs were estimated 

as $2.1 million per 1,000 patients or $10,700 per patient. 

These estimates strengthen the rationale for encouraging 

cessation among persons being treated for cancer.

The evidence reviewed in the 2014 Surgeon 

General’s report documented the harm of smoking by 

persons with a cancer diagnosis, and this report builds 

on that finding by showing that such harm is reduced 

to some extent by smoking cessation. The conclusions 

of this report strengthen the rationale for aggressively 

promoting and supporting smoking cessation in cancer 

patients and survivors.
A Report of the Surgeon General

214 Chapter 4

Cardiovascular Disease

Conclusions from Previous 

Surgeon General’s Reports

The 1990 Surgeon General’s report on the health 

benefits of smoking cessation (U.S. Department of Health 

and Human Services [USDHHS] 1990) provided several 

conclusions on smoking cessation and CVD (Table 4.10) 

that were updated in subsequent reports. Table 4.10 summarizes the major conclusions related to smoking cessation and CVD from the 1990, 2001, 2004, and 2010 

Surgeon General’s reports.

Literature Review Methods

For this Surgeon General’s report, a literature 

review was conducted to update the cessation-specific 

findings from the 1990, 2001, 2004, 2006, 2010, and 2014 

Surgeon General’s reports. The search was restricted 

to English-language papers available on PubMed and 

published between January 2000 and August  31, 2017. 

Medical Subject Headings (MeSH) in PubMed were used 

to capture relevant articles. Retrieved articles included at 

least one term related to smoking cessation (e.g., “former 

smokers”) and at least one term related to CVD (e.g., “coronary heart disease” [CHD]) or a term to describe the 

mechanism of disease (e.g., “thrombosis”). Citations from 

relevant retrieved articles and previous Surgeon General’s 

reports and targeted searches were used to identify articles not captured by the search.

Relevant Mechanistic Data

Previous Surgeon General’s reports have provided 

detailed reviews of potential mechanisms underlying how 

smoking and smoking cessation could affect the development of CVD (USDHHS 1983, 1990, 2004, 2006, 2010, 

2014). This section reviews the links between smoking cessation and the following CVDs: CHD, cerebrovascular diseases, atrial fibrillation (AF), sudden cardiac death (SCD), 

heart failure, venous thromboembolism (VTE), lowerextremity peripheral artery disease (PAD), and abdominal 

aortic aneurysm (AAA). These diseases share some underlying mechanisms, and multiple risk factors contribute to 

each disease; for example, atherosclerosis and thrombosis 

are important for most of these diseases (International 

Agency for Research on Cancer [IARC] 2007). 

Approximately 92.1 million American adults 20 

years of age or older (more than 1 in 3 adults) have one 

or more types of cardiovascular disease (CVD), and by 

2030 almost 44% of the population will have some form 

of CVD (Benjamin et al. 2017). In 2014, coronary heart 

disease (CHD) was listed on the death certificate for 

approximately 1 of every 7 deaths (Benjamin et al. 2017; 

National Center for Health Statistics 2017). The CVDs 

comprise some of the most common causes of death: 

CHD, congestive heart failure (CHF), cerebrovascular 

disease (including stroke), atherosclerosis (including 

aortic aneurysm), and hypertension. In the United States, 

CVD has accounted for more deaths since 1919 than any 

other major cause of death (Benjamin et al. 2019). CHD 

(43.2%) is the leading cause of death attributable to CVD, 

followed by stroke (16.9%), heart failure (9.3%), high 

blood pressure (9.8%), diseases of the arteries (3.0%), 

and other CVDs (Benjamin et al. 2019). In 2015, CVD 

was the leading cause (41.2%) of smoking-attributable 

age-standardized disability-adjusted life-years (DALYs), 

a combined indicator of smoking-attributable mortality 

and disease burden (GBD 2015 Tobacco Collaborators 

2017). Since the first Surgeon General’s report in 1964, 

the rates of age-adjusted CVD mortality have declined 

greatly; a reduction in smoking has been a major contributing factor to the decline in CHD mortality in particular 

(USDHHS 2014).

From 2014 to 2015, the average annual direct (medical) plus indirect costs of heart disease were estimated to 

total $218.7  billion (Benjamin et  al. 2019). Heidenreich 

and colleagues (2011) projected that the direct (medical) 

cost of CHD in the United States would increase by approximately 200%, from $272.2 billion in 2010 to $818.1 billion in 2030.

Surgeon General’s reports published since 1990 have 

not systematically covered the benefits of smoking cessation with regard to risk and outcomes for men and women 

with CVD. This section expands on previous reports by 

summarizing current knowledge of the effects of smoking 

cessation on risk of CVD and the natural history of this 

disease. This is not a systematic update, given the scope 

of the literature, and it does not cover all topics. Instead, 

this section provides examples of new findings that expand 

our understanding of conclusions from previous reports. 

Because of the wide range of research on this topic, this 

review focuses, where relevant, on summarizing results 

from meta-analyses or pooled analyses of findings from 

multiple cohorts and clinical trials. 
The Health Benefits of Smoking Cessation 215

Smoking Cessation

Atherosclerosis is the key underlying pathophysiologic process leading to most clinical manifestations of 

CVD, including CHD, cerebrovascular disease, and PAD. 

Atherosclerosis involves the hardening and narrowing 

of arteries because of deposition of lipids in the inner 

layers of arteries, fibrosis, and thickening of the arterial wall. This complex process involves the deposition of 

lipids, inflammatory and immune responses to oxidized 

lipids, and endothelial dysfunction. When the processes 

involved in atherosclerosis culminate in thrombosis, this 

can lead to myocardial infarction (MI) or ischemic stroke 

(Nagareddy and Smyth 2013). 

Key mechanisms through which smoking and 

smoking cessation affect atherogenesis and thrombosis include endothelial function and injury, oxidative 

stress, hemostatic factors (platelet function, fibrinogen, 

and d-dimer), fibrinolysis, inflammation, lipid modification, and vasomotor function (IARC 2007). Smoking and 

smoking cessation may also influence CVD risk through the 

effect of oxygen demand and supply on cardiovascular function (USDHHS 2004) and through effects on occurrence of 

arrhythmias and coronary artery spasm (USDHHS 1990).

The 1990 Surgeon General’s report focused primarily 

on how smoking affects or may affect mechanisms leading 

to CVD and described mechanisms that could come into 

play when smokers quit (USDHHS 1990). The report concluded that some CVD effects of smoking appeared to be 

reversed within days or weeks of quitting (e.g., increased 

platelet activation, changes in clotting factors, level of carboxyhemoglobin, occurrence of coronary artery spasm 

and ventricular arrhythmias), but that other effects 

(e.g., advance of atherosclerosis, proliferation of smooth 

Table 4.10 Conclusions from previous Surgeon General’s reports on smoking cessation and cardiovascular disease

Year of report (page numbers) Conclusions

USDHHS (1990, pp. 10–11) 1. Compared with continued smoking, smoking cessation substantially reduces risk of CHD

among men and women of all ages.

2. The excess risk of CHD caused by smoking is reduced by about half after 1 year of smoking

abstinence and then declines gradually. After 15 years of abstinence, the risk of CHD is similar

to that of persons who have never smoked.

3. Among persons with diagnosed CHD, smoking cessation markedly reduces the risk of

recurrent infarction and cardiovascular death. In many studies, this reduction in risk of

recurrence or premature death has been 50% or more.

4. Smoking cessation substantially reduces the risk of peripheral artery occlusive disease compared

with continued smoking.

5. Among patients with peripheral artery disease, smoking cessation improves exercise tolerance,

reduces the risk of amputation after peripheral artery surgery, and increases overall survival.

6. Smoking cessation reduces the risk of both ischemic stroke and subarachnoid hemorrhage

compared with continued smoking. After smoking cessation, the risk of stroke returns to the

level of never smokers; in some studies this has occurred within 5 years, but in others as long

as 15 years of abstinence were required.

USDHHS (2001, pp. 13–14) 1. The risk for coronary heart disease among women is substantially reduced within 1 or 2 years

of smoking cessation. This immediate benefit is followed by a continuing but more gradual

reduction in risk to that among nonsmokers by 10 to 15 or more years after cessation.

2. In most studies that include women, the increased risk for stroke associated with smoking is

reversible after smoking cessation; after 5 to 15 years of abstinence, the risk approaches that

of women who have never smoked.

3. Smoking is a strong predictor of the progression and severity of carotid atherosclerosis among

women. Smoking cessation appears to slow the rate of progression of carotid atherosclerosis.

4. Women who are current smokers have an increased risk for peripheral vascular atherosclerosis.

Smoking cessation is associated with improvements in symptoms, prognosis, and survival.

USDHHS (2004, p. 25) 1. Quitting smoking has immediate as well as long-term benefits, reducing risks for diseases

caused by smoking and improving health in general.

USDHHS (2010, p. 11) 1. Smoking cessation reduces the risk of cardiovascular morbidity and mortality for smokers

with or without coronary heart disease.

2. The use of nicotine or other medications to facilitate smoking cessation in people with known

cardiovascular disease produces far less risk than the risk of continued smoking.

Notes: CHD = coronary heart disease.
A Report of the Surgeon General

216 Chapter 4

muscle cells, lipid deposition) may be irreversible or only 

slowly reversible.

The 2004 Surgeon General’s report provided a 

detailed overview of mechanisms linking smoking with CVD 

development. That report concluded that smoking (1) promotes endothelial injury and cell dysfunction; (2) produces 

a substantial shift in hemostatic balance at the endothelium, leading to atherosclerosis and thrombotic complications; (3)  diminishes the ability of the blood to carry 

oxygen; and (4) increases physiologic demands of the myocardium (USDHHS 2004). Through these mechanisms, 

smoking results in substantial adverse alterations in the 

cardiovascular system’s hemostatic balance, explaining the 

relationship between smoking and the subclinical and clinical manifestations of atherosclerosis. The 2010 Surgeon 

General’s report reviewed in detail the mechanisms 

through which cigarette smoking causes CHD (USDHHS 

2010), concluding that smoking produces insulin resistance that could, in tandem with chronic inflammation, 

accelerate the development of macrovascular and microvascular complications, such as nephropathy.

The 2014 Surgeon General’s report expanded on the 

research related to the mechanisms through which cigarette smoking affects cardiovascular function, focusing on 

how smoking affects atherogenesis, endothelial function, 

thrombosis, and inflammation (USDHHS 2014). The year 

before, Csordas and Bernard (2013) reviewed the biology 

of the atherothrombotic effects of smoking. Elsewhere, 

Messner and Bernhard (2014) reviewed how smoking 

causes endothelial dysfunction and initiates atherogenesis. The next sections highlight some of the findings 

related to mechanisms through which smoking cessation 

could alter the development and progression of CVD.

Mechanisms Through Which Smoking Cessation 

Could Affect Cardiovascular Disease

As described in the 2010 Surgeon General’s report, 

there are multiple mechanisms by which cigarette 

smoking contributes to acute cardiovascular events and 

increases the risk for developing CVDs over the long term 

(USDHHS 2010). Smoking cessation terminates exposure 

to the constituents and metabolites in tobacco smoke that 

drive some of these mechanisms, leading to both rapid 

and more delayed reduction of risk.

Carbon Monoxide and Nicotine

Several specific components of cigarette smoke are 

directly relevant to the benefits of smoking cessation: 

carbon monoxide (CO), nicotine, and oxidant gases, which 

contribute to inflammation. Tobacco smoke contains high 

concentrations of CO, which is a gas (USDHHS 2010). 

The mechanisms by which CO may contribute to acute 

cardiovascular events are well characterized. CO binds 

to hemoglobin, reducing oxygen-carrying capacity, and 

also shifts the oxyhemoglobin desaturation curve so that 

less oxygen is released to tissues from hemoglobin. The 

half-life of CO is brief: smoking-related CO in the body is 

cleared within several days of cessation (USDHHS 2010).

Nicotine is pharmacologically active and sympathomimetic in its action, causing release of catecholamines 

from the neurons and from the adrenal gland. This release 

of catecholamines transiently increases heart rate and 

blood pressure and results in vasoconstriction, which can 

contribute to myocardial hypoxia and, hence, increase risk 

for acute cardiovascular events. Successful smoking cessation ends exposure to nicotine and provides an immediate 

benefit in terms of reducing risk for acute cardiac events. 

Hemodynamic Effects

Smoking impairs vascular endothelial function 

and activates the sympathetic nervous system. In combination with underlying atherosclerosis, these hemodynamic consequences of smoking increase the risk for 

CVD events. Alterations in vasomotor function because of 

smoking appear to be substantially reversible, suggesting 

the important role that smoking cessation and smokefree 

environments can play in reducing the burden of CVDs 

(USDHHS 2010).

Endothelial Effects

The endothelium plays a role in vascular tone, 

growth, thrombogenicity, and inflammation (Lerman 

and Zeiher 2005). Dysfunction and injury of the endothelium affects atherogenesis initiation and the development of acute CVD events, and endothelial dysfunction is 

an independent risk factor for CVD morbidity and mortality (USDHHS 2010). Smoking may impair regeneration 

of the endothelium; however, 2–4 weeks of cessation has 

been associated with increases in the number of progenitor cells, which is indicative of repair of the endothelium 

(Kondo et al. 2004).

Both active smoking and exposure to secondhand 

smoke can alter coronary and peripheral arterial vasomotion among persons with or without CHD (Czernin 

and Waldherr 2003). Correspondingly, evidence suggests 

that  smoking cessation can improve endothelial functioning. Smoking cessation leads to improved endothelialdependent vasodilation in veins in the human hand within 

24  hours of cessation (Moreno  Jr et  al. 1998). Reduced 

altered brachial artery flow-mediated dilation (FMD) is an 

early marker for endothelial dysfunction and a risk factor 

for CVD. Smoking is associated with reduced FMD. This 

relationship is dose related and may be reversible, as a 

weaker association has been observed in former smokers 
The Health Benefits of Smoking Cessation 217

Smoking Cessation

(Celermajer et al. 1993; Raitakari et al. 1999). Johnson and 

colleagues (2010) reported on a clinical trial that assessed 

smoking cessation pharmacotherapies in 1,504 smokers; 

among the 36% of participants who quit smoking, FMD 

increased by 1% (from 6.2% +/- 4.4% to 7.2% +/- 4.2%) 

after 1 year—a relative gain of approximately 15%. In contrast, FMD did not change among those who continued 

to smoke. Results were similar after adjusting for artery 

diameter, reactive hyperemia, low-density lipoprotein cholesterol, and the presence of a smokefree rule in the home.

In another study, smoking “light” cigarettes 

(a  type of cigarette that was claimed by manufacturers 

to produce less tobacco tar than a regular cigarette when 

smoked) was not associated with improved FMD relative 

to smoking regular cigarettes, providing evidence that 

“light” cigarettes are not a less harmful alternative to 

higher yield cigarettes for reducing CVD risk (Amato et al. 

2013). In cross-sectional adjusted analyses of data from 

the Bogalusa Heart Study, former cigarette smokers, compared with current smokers, had higher small-artery compliance, as estimated by radial artery pressure pulse contour analysis, and decreased systemic vascular resistance, 

with a trend of improvement with increased time since 

cessation (Li et al. 2006). In the U.S.-based Multi-Ethnic 

Study of Atherosclerosis (MESA), McEvoy and colleagues 

(2015b) did not find consistent associations between 

smoking status (current, former, or never) and measures 

of vascular dynamics and function (carotid distensibility, 

aortic distensibility, or FMD). In addition, time since cessation was not associated with these outcomes, possibly 

because of the older ages of the participants.

Studies have also found that smoking cessation 

is associated with changes in biomarkers of endothelial function, dysfunction, or activation. In an intervention study focused on lifestyle changes in young adults 

with family histories of premature CHD, those who quit 

smoking had significantly lower concentrations of intercellular adhesion molecule-1 (ICAM-1), a biomarker of 

endothelial activation, compared with those continuing to 

smoke (Tonstad et al. 2005). Elsewhere, in a small study of 

a smoking cessation intervention among persons at high 

risk of CVD, ICAM-1 decreased among quitters after 1 year 

of cessation but increased among persons who continued 

to smoke (Halvorsen et al. 2007). Other markers related 

to endothelial function, thrombotic state, or inflammation (E-selectin, interleukin  6, sCD40 ligand, tumor 

necrosis factor  a, von  Willebrand factor, and C-reactive 

protein [CRP]) did not change during the study period. 

In a small study of young, healthy smokers, coronary vasomotor abnormality appeared to improve after 1 month of 

smoking cessation (Morita et al. 2006). Later, Huang and 

colleagues (2016) examined two Swedish cohorts to assess 

the relationships of smoking with 80  protein markers 

known to be related to CVD risk. In replication analyses, 

current cigarette smoking was associated with 10  proteins representing endothelial dysfunction, inflammation, 

neointimal formation, foam cell formation, and plaque 

instability (Huang et  al. 2016). Among former smokers, 

no consistent associations were observed.

A systematic review of the literature concluded that 

the evidence was uncertain as to whether smoking cessation leads to a reversal in arterial stiffness (Doonan 

et al. 2010). In the Atherosclerosis Risk in Communities 

(ARIC) study of older adults, among women, femoralankle pulse wave velocity, a measure of arterial stiffness, 

was lower in current smokers and former smokers than 

in never smokers, and lower in former smokers than in 

current smokers (Camplain et al. 2016). Among women, 

both smoking status and cumulative smoking exposure 

were associated with lower peripheral arterial stiffness. 

Among men, this study did not find a relationship between 

smoking cessation and a reversal in arterial stiffness, and 

it did not reveal an association with time since smoking 

cessation or with carotid-femoral pulse wave velocity.

Thrombogenic Effects

The 2010 Surgeon General’s report noted that 

smoking-mediated thrombosis appears to be a major 

factor in the pathogenesis of acute cardiovascular events 

and described how smoking leads to alterations in the 

blood and in the blood vessels that promote thrombosis, 

a pathologic reaction that can result in smoking-related 

MI or stroke (USDHHS 2010). The report summarized 

how the hypercoagulable state associated with both active 

smoking and exposure to secondhand smoke is evident in 

the epidemiology of related cardiovascular events and in 

the rapid decline in risk of such events after smoking cessation (USDHHS 2010).

In cross-sectional analyses of 19,600  participants 

from the Third National Health and Nutrition Examination 

Survey (NHANES III, conducted from 1988 to 1994), cigarette smoking was strongly and positively associated with 

elevated levels of fibrinogen and homocysteine, which are 

markers of a hypercoagulable state (fibrinogen is also a 

marker of inflammation) (Bazzano et al. 2003). In addition, there was a dose-response relationship with these 

markers. Compared with never smokers, former smokers 

(median of 10 years since cessation) had higher odds of 

elevated fibrinogen but not of elevated homocysteine. 

Additionally, current smokers had higher odds of elevated 

fibrinogen compared with former smokers. Further analyses of data from the NHANES III showed a trend of lower 

levels of fibrinogen with increasing time since smoking 

cessation: After approximately 5 years of cessation, levels 

were similar to those of never smokers (Bakhru and 

Erlinger 2005).
A Report of the Surgeon General

218 Chapter 4

Among 174  smokers who underwent an intensive 12-month smoking cessation program, levels of 

von Willebrand factor (a marker of circulating endothelialcoagulative activation) decreased significantly 2, 6, and 

12 months after smoking cessation compared with baseline among those who maintained cessation at each 

follow-up (Caponnetto et  al. 2011). In those who quit 

smoking, concentrations of d-dimer, prothrombin fragment 1 + 2, platelet factor-4, and β-thromboglobulin (all 

markers of circulating endothelial-coagulative activation) were significantly lower 6 and 12 months after cessation compared with baseline. In a nicotine replacement 

therapy trial among 197  men, those who quit smoking 

had improved plasma fibrinogen, reactive capillary flow, 

and transcutaneous partial oxygen tension (three parameters of blood flow) after 6 months of cessation compared 

with levels measured at baseline (Haustein et  al. 2002). 

Hematocrit levels and white blood cell counts were lower 

in quitters compared with those who relapsed; this suggests decreased inflammation in these individuals, as 

white blood cells play an important role in the inflammatory process. Changes in plasma viscosity and erythrocyte 

deformability were inconclusive.

Other studies have also found that circulating levels 

of fibrinogen are higher in smokers and decrease with cessation, with one study finding a decreased rate of fibrinogen 

synthesis and lower plasma fibrinogen concentrations 

just 2  weeks after cessation (Hunter et  al. 2001). Blann 

and colleagues (1997) found decreases in many hematologic and coagulation indices in former smokers who used 

nicotine gum or patches to quit smoking; there were few 

additional changes after the participants no longer used 

any nicotine replacement products. Lúdvíksdóttir and colleagues (1999) observed similar results for atherogenic 

and thrombogenic factors in a smoking cessation trial 

involving a nicotine nasal spray versus placebo.

Inflammation

Research suggests that smoking leads to a chronic 

inflammatory state, activates monocytes, and enhances 

the recruitment and adhesion of leukocytes to blood 

vessel walls, an important step in vascular inflammation 

(USDHHS 2010). Evidence indicates that vascular inflammation, in turn, appears to play a role in atherogenesis; 

and markers of inflammation, such as CRP, predict the 

risk of future CVD events (Libby et al. 2002).

Several studies have explored the relationships 

between smoking and markers of inflammation, such as 

CRP (Bermudez et al. 2002; Bazzano et al. 2003; Bakhru 

and Erlinger 2005; Helmersson et al. 2005; Ohsawa et al. 

2005; Madsen et al. 2007; Hastie et al. 2008; Levitzky et al. 

2008; Lao et al. 2009; Reichert et al. 2009; Asthana et al. 

2010; Zatu et al. 2011; Golzarand et al. 2012; Marano et al. 

2015; McEvoy et  al. 2015b; Kianoush et  al. 2017; King 

et al. 2017). In most of these studies, current and former 

smokers had higher levels of inflammatory markers than 

nonsmokers (Bermudez et al. 2002; Bazzano et al. 2003; 

Helmersson et al. 2005; Madsen et al. 2007; Hastie et al. 

2008; Levitzky et al. 2008; Lao et al. 2009; Golzarand et al. 

2012; Marano et al. 2015; McEvoy et al. 2015b; Kianoush 

et al. 2017), and in five of the studies inflammatory levels 

decreased in former smokers with increasing time since 

smoking cessation (Bakhru and Erlinger 2005; Ohsawa 

et  al. 2005; Reichert et  al. 2009; McEvoy et  al. 2015b; 

Kianoush et al. 2017).

In the cross-sectional analyses of data from NHANES 

III (described previously), cigarette smoking was independently and positively associated with elevated levels of CRP, 

and there was a dose-response relationship (Bazzano et al. 

2003). In analyses of the odds of having either a detectable 

CRP or a clinically elevated CRP level, former smokers 

had higher odds compared with never smokers but lower 

odds compared with current smokers. Additional analyses showed a trend of decreasing white blood cell counts 

and clinically detectable CRP with increased time since 

smoking cessation: Approximately 5 years after cessation, 

white blood cell counts and the odds of detectable CRP 

did not differ significantly from those of never smokers 

(Bakhru and Erlinger 2005).

In the Brazilian Longitudinal Study of Adult Health 

(ELSA-Brasil), among 4,121 former smokers, time since 

cessation was inversely related to levels of high-sensitivity 

CRP (Kianoush et al. 2017). Similarly, in the U.S.-based 

MESA cohort, levels of high-sensitivity CRP were higher 

in current smokers than in former smokers, and levels of 

high-sensitivity CRP decreased with increased time since 

cessation (McEvoy et al. 2015b). Notably, this study used 

cotinine to classify smoking status. In a cross-sectional 

study by Hastie and colleagues (2008), levels of CRP 

were similar in never and former smokers approximately 

5  years after cessation. In that study, extent of lifetime 

smoking (assessed by number of pack-years) was a predictor of levels of CRP after smoking cessation, independent of time since cessation, suggesting that levels of CRP 

may be higher in smokers because of a secondary effect, 

such as tissue damage caused by inflammation.

In observational analyses of 1,504 smokers enrolled 

in a smoking cessation trial in which 36% of participants 

had abstained for 1 year, smoking cessation was not associated with level of CRP (Asthana et al. 2010). There was 

also no relationship of smoking intensity to CRP, although 

smoking intensity was associated with increased white 

blood cell counts. The authors suggested that the effects 

of adiposity on levels of CRP may have masked the relationship between smoking and CRP. A study by King and 

colleagues (2017) of 1,652  smokers attempting to quit 
The Health Benefits of Smoking Cessation 219

Smoking Cessation

examined six inflammatory markers of CVD risk: CRP, 

D-dimer, fibrinogen, urinary F2 isoprostane:creatinine

(F2:Cr) ratio, white blood cell count, and myeloperoxidase. After 1  year, 21% of participants had successfully

quit. Cessation was associated with an improved F2:Cr

ratio and decreased white blood cell counts independent of weight change but not with other inflammatory

markers. Smoking intensity was associated with the F2:Cr

ratio, myeloperoxidase, and white blood cell counts. The

authors concluded that smoking cessation may have led to

reduced inflammation by lowering oxidative stress.

Lipid Abnormalities

Cigarette smoking is associated with lipid profiles 

that are likely to contribute to the development of atherosclerosis and CVD risk, a topic reviewed in depth in the 

2010 Surgeon General’s report (USDHHS 2010). Much 

evidence supports the conclusion that smoking is associated with higher levels of triglycerides (which in turn 

are associated with levels of very-low-density lipoproteins, 

total triglycerides, and apolipoprotein  B [APO  B]), with 

modestly higher levels of low-density lipoproteins cholesterol (LDL-C), and with lower levels of plasma highdensity lipoprotein cholesterol (HDL-C) and apolipoprotein A-I (APO  A-I) (USDHHS 2010). The 2010 Surgeon 

General’s report also found that plasma lipid and lipoprotein levels among former cigarette smokers were typically 

similar to those of nonsmokers.

In a meta-analysis of articles published from 1966 to 

2000, Maeda and colleagues (2003) concluded that, based 

on analyses from 27 prospective studies, smoking cessation 

is associated with beneficial increases in HDL-C. In this 

analysis, changes in the levels of total cholesterol, LDL-C, 

and triglycerides were not significant. Later, Forey and 

colleagues (2013), in a meta-analysis of 45 studies, found 

that levels of HDL-C increased rapidly (within weeks) after 

cessation, but there was no clear pattern after that time. 

In a study conducted by Gepner and colleagues 

(2011), a clinical trial of cessation pharmacotherapies in 

1,504 smokers that was included in the meta-analysis by 

Forey and colleagues (2013), those who successfully quit 

(36% of participants) had, at 1-year follow-up, higher 

levels of HDL-C, total HDL, and large HDL particles compared with baseline. Smoking cessation was not, however, associated with changes in LDL-C or LDL size. These 

results were similar to those reported in the meta-analysis 

by Maeda and colleagues (2003). Importantly, smokers 

in the study by Gepner and colleagues (2011) generally 

had a higher body mass index (BMI) than those in previous studies and thus were more representative of the 

contemporary U.S. population. Elsewhere, in two reports 

based on a study in which participants were on the nicotine patch for 32 days and then taken off it for 45 days, 

HDL-C levels did not increase significantly among former 

smokers on the patch, but those levels increased quickly 

after they stopped using the patch (Moffatt et  al. 2000; 

Chelland Campbell et al. 2008). Of note, nicotine products 

were used in some arms of the trial by Gepner and colleagues (2011), but that trial did observe higher levels of 

total HDL at 1-year follow-up. 

Summary of the Evidence

Substantial evidence shows that smoking cessation 

is associated with an improvement in many pathogenetic 

factors involved in processes through which cigarette 

smoking causes CVD. Some effects appear to be rapidly 

reversible with smoking cessation, but other effects may 

reverse much more slowly or not at all. Evidence indicates that smoking cessation (1) leads to a reduction in 

markers of inflammation and hypercoagulability and to 

rapid changes in levels of HDL-C in a favorable direction 

and (2) may lead to improved endothelial function. 

Smoking Cessation and 

Subclinical Atherosclerosis

According to the 2004 Surgeon General’s report, the 

evidence is sufficient to infer a causal relationship between 

smoking and subclinical atherosclerosis (USDHHS 2004). 

That report addressed the implications of this conclusion, 

finding that cigarette smoking has a causal relationship 

with the full natural history of atherosclerosis—from the 

early stages that are detected by subclinical markers to the 

late, often fatal, stages. Findings presented at that time 

indicated the potential for smoking cessation (including 

quitting and then maintaining cessation) to prevent more 

advanced, clinically symptomatic disease. 

The 2001 Surgeon General’s report concluded that 

smoking is a strong predictor of the progression and 

severity of carotid atherosclerosis among women and that 

smoking cessation appears to slow the rate at which carotid 

atherosclerosis progresses (USDHHS 2001). Since this 

report appeared, additional approaches have been developed to measure subclinical atherosclerosis, and more 

evidence has been published indicating that smoking cessation can slow the progression of atherosclerosis.

As described in the 2004 Surgeon General’s report, 

examining measures of subclinical atherosclerosis facilitates assessment of the relationship between smoking and 

the earlier, preclinical stages of the atherosclerotic disease 

process. In studies of subclinical measures among healthy 

persons, findings may be less susceptible to reverse causation, as there is no onset of symptoms that could lead to 

cessation and distort the temporal relationship between 
A Report of the Surgeon General

220 Chapter 4

smoking and CVD. The possibility of reverse causation 

(for  clinical and subclinical outcomes) is of particular 

concern for cross-sectional analyses in which it may not 

be possible to ascertain temporality.

Table  4.11 describes findings from 12  studies that 

have assessed the relationships between smoking cessation and subclinical atherosclerosis (Kiechl et  al. 2002; 

Baldassarre et  al. 2009; Jöckel et  al. 2009; Liang et  al. 

2009; Jiang et al. 2010; Kweon et al. 2012; Lehmann et al. 

2014; McEvoy et  al. 2015b; Yang et  al. 2015b; Hansen 

et al. 2016; Hisamatsu et al. 2016; Kianoush et al. 2017). 

Studies in many different populations have found, generally, that smoking is positively associated with the presence, extent, and progression of atherosclerosis measured 

in different vascular beds. Compared with never cigarette 

smokers, both current and former smokers tend to have 

more extensive atherosclerosis, although former smokers 

generally have less extensive atherosclerosis than current 

smokers. Studies in other populations and studies of other 

markers for atherosclerosis have reported similar findings 

(Fowkes et al. 2013; Yi et al. 2015; Pacheco et al. 2016). 

Time since smoking cessation is also related to the extent 

of atherosclerosis, with less atherosclerotic burden as time 

since cessation increases (Jiang et al. 2010; Kweon et al. 

2012; McEvoy et al. 2015b; Hansen et al. 2016; Hisamatsu 

et al. 2016; Kianoush et al. 2017).

Hansen and colleagues (2016) conducted one of several studies assessing the relationship between smoking 

cessation and the progression of atherosclerosis. This 

study examined a subcohort of the prospective Malmö Diet 

and Cancer study in Sweden and found that, compared 

with never smokers, former smokers had an adjusted difference in the yearly progression rate of 0.0074 millimeters (mm) per year (95% confidence interval [CI], 0.0018–

0.0129) in maximal intimal-media thickness (IMT) in the 

carotid bifurcation (Table 4.11). But compared with never 

smokers, moderate smokers had an adjusted difference of 

0.0106 mm (95% CI, 0.0038–0.0175) and heavy smokers 

had an adjusted difference of 0.0146 mm (95% CI, 0.0016–

0.0230). Among former smokers, as time since smoking 

cessation increased, there was a reduction in yearly progression of IMT in the carotid bifurcation and in the rate 

of lumen reduction, with a distinct lowering in progression rates more than 5 years after cessation. In a study of 

127 smokers in the Netherlands, successful smoking cessation for 2 years did not result in slowing of the increase in 

carotid IMT or a reduction in the thickening of the carotid 

artery, a finding potentially attributable to the study’s 

small size and relatively short follow-up (data not shown 

in table) (van  den Berkmortel et  al. 2004). Carotid IMT 

is a predictor of future CVD events (Lorenz et al. 2007), 

although its measurement may have no added value for 

predicting cardiovascular risk (Den Ruijter et al. 2012).

Results from cross-sectional analyses in 2000–2003 

of the Heinz Nixdorf Recall Study in Germany were used 

to estimate the slowing by cessation of coronary artery 

calcification (CAC), compared with continued smoking 

(Table 4.11). Compared with continued smoking, smoking 

cessation at 45, 55, and 65 years of age was estimated to 

slow CAC progression at 75 years of age by 9, 6, and 3 years, 

respectively (Jöckel et al. 2009). CAC is a predictor of future 

CVD events (Pletcher et  al. 2004; Chaikriangkrai et  al. 

2017). Although the findings from Jöckel and colleagues 

(2009) were based on modeling assumptions and crosssectional data, their results suggest that smoking cessation may reduce the progression of atherosclerosis, which 

could potentially reduce the risk of future clinical CVD.

Several studies (Table  4.11) have assessed associations between smoking and the ankle-brachial index (ABI), 

which is also known as the ankle-arm index (McEvoy et al. 

2015b; Hisamatsu et al. 2016; Kianoush et al. 2017). The 

ABI is the ratio of blood pressure in the lower leg to that in 

the upper arm. A low ABI is associated with an increased 

risk of CHD and of CVD (Lin et  al. 2013). The ABI has 

been used as a way to assess the presence of PAD, but it 

does not assess which blood vessels are narrow or blocked. 

In two studies (Table 4.11), former smoking was associated with higher odds of a low ABI compared with never 

smoking (McEvoy et al. 2015b; Kianoush et al. 2017), and 

in three studies, increased time since quitting was associated with lower odds of having a low ABI (McEvoy et al. 

2015b; Hisamatsu et al. 2016; Kianoush et al. 2017). For 

example, in the MESA cohort, the odds ratio (OR) for an 

ABI <1.0  was 0.91 (95%  CI, 0.86–0.96) for every 5-year 

increment since smoking cessation (McEvoy et al. 2015b). 

The relationship between smoking cessation and clinical 

manifestations of PAD is discussed in more detail in a 

later section. 

Summary of the Evidence

Evidence indicates that smoking cessation reduces 

the development and progression of markers of subclinical 

atherosclerosis, with the degree of reduction increasing 

as time since cessation increases. This pattern of change 

in markers provides mechanistic background on the evidence of how smoking cessation reduces risk of CVD. 

Smoking Cessation and 

Cardiovascular Disease

The 2010 Surgeon General’s report concluded that 

smoking cessation reduces the risk of cardiovascular morbidity and mortality for cigarette smokers with or without 

CHD (USDHHS 2010). This report also found that there 
Study Design/population Main results Comments

Kiechl et al. 

(2002)

• Prospective cohort (Bruneck Study)

• 826 healthy or sick participants, 40–79 years 

of age, 50% men, 26% former smokers

• 1990–1995

• Italy

• Follow-up: 5 years

• Outcome: carotid IMT, early atherogenesis 

(nonstenotic plaques), advanced atherogenesis 

(stenosis >40%)

• Current and former smokers had increased 

risk of early atherogenesis only if they had 

chronic infections; risks were similar in 

never, former, and current smokers without 

chronic infection

• Advanced atherogenesis developed 

independently of chronic infection; risk 

returned to normal soon after cessation

Impact of smoking on atherosclerosis appears to 

be partially mediated by chronic infections

Baldassarre et al. 

(2009)

• Cross-sectional study

• 1,804 consecutive patients’ first visit to 

lipid clinic, 21–85 years of age, 48% men, 

21% former smokers

• 2000–2003

• Italy

• Outcome: carotid IMT (mean, total, 

and maximum)

• Carotid IMT was highest in current smokers, 

then former smokers, then never smokers

• Only after adjusting for risk factors was 

carotid IMT significantly higher among 

current smokers than former smokers

• Carotid IMT was positively associated with 

pack-years of smoking among both former 

and current smokers

Results may not be generalizable to populations 

without dyslipidemi

Liang et al. 

(2009)

• Cross-sectional and prospective analyses 

(Collaborative Study of Cardiovascular and 

Cardiopulmonary Epidemiology)

• 1,132 participants, 35–64 years of age;

34% men; 3% former smokers at baseline; free 

of myocardial infarction, stroke, and diabetes

• Scanned in 1993–1994 and 2002

• China

• Exposure: smoking status at baseline and 

consistency during follow-up

• Outcome: mean common carotid IMT

• Mean adjusted IMT was 0.72 mm for consistent

current smokers, 0.71 mm for former and 

inconsistent smokers, and 0.70 mm for 

consistent never smokers (p for trend <0.01)

• Compared with consistent never smokers, 

consistent current smokers had higher 

adjusted odds of carotid plaques; a similar 

pattern was observed among former smokers 

and former/inconsistent smokers, but the 

results were not significant

—

Jöckel et al. 

(2009)

• Cross-sectional study (Heinz Nixdorf Recall 

Study)

• 4,078 participants, 45–75 years of age, 50% men, 

without manifest CHD (myocardial infarction 

or coronary revascularization) or stroke

• Scanned in 2000–2003

• Germany

• Outcome: CAC

• Smoking cessation at 45, 55, or 65 years of 

age was associated with CAC at the age of 

75 years that would have been reached 9, 6, 

or 3 years earlier, respectively, had smoking 

continued

• CAC accumulation slowed after cessation, but 

advanced CAC persisted for a long time

Results are based on predictions from regression 

models run separately by smoking status; models 

were not run separately for men and women

Table 4.11 Studies on the association between smoking cessation and subclinical atherosclerosis

The Health Benefits of Smoking Cessation 221
Study Design/population Main results Comments

Jiang et al. 

(2010)

• Cross-sectional study

• 959 men, 50–85 years of age, 26% former 

smokers

• Scanned in 2006–2007

• China

• Outcome: mean common carotid IMT, 

presence of CCA plaques; CCA atherosclerosis 

defined as CCA-IMT ≥1.0 mm or with a 

stenosis diameter ≥20%

• IMT and number of plaques increased from 

never, to former, to current smokers

• Longer duration since cessation was associated 

with decreased odds of the presence and 

severity of atherosclerosis in CCA (explored 

in categories of 1–9, 10–19, ≥20 years since 

cessation; observed benefit compared with 

current smokers for ≥10 years since quitting)

—

Kweon et al. 

(2012)

• Cross-sectional study (Dong-gu Study)

• 2,503 men, ≥50 years of age, 51% former 

smokers

• Scanned in 2007–2009

• Korea

• Outcome: CCA-IMT, carotid plaque, 

CCA diameter

• Compared with never smokers, current 

smokers had greater CCA IMT, CCA diameter, 

and odds of carotid plaque

• Among former smokers, CCA IMT and CCA 

diameter decreased with years since cessation; 

not observed for carotid plaque

• For current smokers, but not for former 

smokers, a dose-response relationship was 

observed between pack-years of smoking 

and CCA IMT

Only men were included in analysis because of a 

very low prevalence of smoking among women

Lehmann et al. 

(2014)

• Prospective study (Heinz Nixdorf Recall 

Study)

• 1,261 participants, 45–75 years of age, 

27% men, no detectable CAC at first scan, 

no history of CHD or stroke

• Scanned in 2000–2003, rescanned 5 years later

• Germany

• Outcome: onset of detectable CAC

• Compared with never smokers, onset of 

detectable CAC occurred approximately

10 years earlier among current smokers and

5 years earlier among former smokers

• Among women, in adjusted analyses, current 

smokers had higher odds of progression

to detectable CAC than never smokers; 

no association for former smokers

• Among men, smoking was not related to 

CAC onset

Unclear whether there was adjustment for other 

factors in the analysis of time to detectable CAC

Table 4.11 Continued

A Report of the Surgeon General

222 Chapter 4
Study Design/population Main results Comments

McEvoy et al. 

(2015b)

• Cross-sectional study (Multi-Ethnic Study of 

Atherosclerosis) 

• 6,796 multiethnic participants, 45–84 years

of age, 47% men, 38% former smokers, free 

of CVD 

• 2000–2002 

• United States (six centers) 

• Outcomes: mean internal carotid IMT, CAC, 

and ABI 

• Difference in log (IMT)a (95% CI):

• Never smoker: 0.00 (referent)

– Former smoker: 0.05 (0.03–0.07)

– Current smoker: 0.09 (0.06–0.12)

• Odds ratio of CAC >0 (95% CI):

• Never smoker: 1.00 (referent)

– Former smoker: 1.28 (1.21–1.57)

– Current smoker: 1.79 (1.49–2.14)

• Odds ratio of CAC >75th percentile (95% CI):

• Never smoker: 1.00 (referent)

– Former smoker: 1.18 (0.99–1.41)

– Current smoker: 1.38 (1.08–1.77)

• Odds ratio of ABI <1 (95% CI):

• Never smoker: 1.00 (referent)

– Former smoker: 1.24 (1.02–1.50)

– Current smoker: 2.22 (1.74–2.83)

• Time since quitting was independently 

associated with atherosclerosis; for example, 

OR of CAC >0 was 0.94 (95% CI, 0.90–0.97) 

for each 5 years since quitting

—

Yang et al. 

(2015b)

• Cross-sectional study (Northern Manhattan 

Study)

• 1,743 multiethnic participants, ≥39 years of 

age, 40% men, 38% former smokers, free 

of stroke

• Years of data collection: not provided

• New York, New York (northern Manhattan)

• Outcome: carotid plaque echodensity divided 

into quintiles

• Compared with never smokers, current 

smokers were more likely to have soft or 

calcified plaques

• Compared with never smokers, former smokers 

were more likely to have echodense plaques

More research is needed to understand whether 

plaque morphology mediates the relationship 

between smoking and clinical CVD

Table 4.11 Continued

The Health Benefits of Smoking Cessation 223
Study Design/population Main results Comments

Hansen et al. 

(2016)

• Prospective cohort (Malmö Diet and Cancer 

cardiovascular cohort)

• 2,992 middle-aged participants, 41% men, 

35% former smokers, free of CVD

• 1991–1994 baseline and 2007–2012 visit 

(subcohort of those born 1926–1945)

• Sweden

• Outcomes: mean common carotid IMT and 

maximum carotid bifurcation, degree of

lumen diameter reduction

• Difference in IMT progression (mm/year) 

(95% CI):

– CCA:

 Never smoker, unexposed to secondhand 

smoke: 1.00 (referent)

 Former smoker: 0.0014 (0.0001–0.0028)

 Moderate smoker (1–15 cigarettes smoked 

per day): 0.0027 (0.0010–0.0044)

 Heavy smoker (>15 cigarettes smoked 

per day): 0.0041 (0.0020–0.0062)

– Carotid bifurcation:

 Never smoker, unexposed to secondhand 

smoke: 1.00 (referent)

 Former smoker: 0.0074 (0.0018–0.0129)

 Moderate smoker: 0.0106 (0.0038–0.0175)

 Heavy smoker: 0.0146 (0.0061–0.0230)

• Differences in rate of diameter reduction 

(%/year) (95% CI):

– Never smoker, unexposed to secondhand 

smoke: 1.00 (referent)

– Former smoker: 0.25 (0.001–0.36)

– Moderate smoker: 0.25 (0.11–0.38)

– Heavy smoker: 0.43 (0.26–0.59)

• Stronger associations for current smokers

• With >5 years since cessation, rate of IMT 

bifurcation progression decreased; similar 

pattern for lumen reduction

Similar resultswhenadjustedfor inflammatory 

markers 

Table 4.11 Continued

A Report of the Surgeon General

224 Chapter 4
Study Design/population Main results Comments

Hisamatsu et al. 

(2016)

• Cross-sectional study (Shiga Epidemiological 

Study of Subclinical Atherosclerosis)

• 1,019 Japanese men, 40–79 years of age, 

50% former smokers, free of CVD

• 2006–2008

• Japan

• Outcomes: ABI <1.1; mean carotid IMT; 

AoAC and CAC

• Former smoking was associated with higher 

carotid IMT (IMT >1.0 mm, OR = 1.94 

[95% CI, 1.13–3.34]) and AoAC (AoAC >0, 

OR = 2.55 [95% CI, 1.45–4.49]) compared 

to never smokers

• Current smoking was positively associated 

with all four outcomes:

– CAC >0, OR = 1.79 (95% CI, 1.16–2.79)

– Carotid IMT >1.0 mm, OR = 1.88 (95% CI, 

1.02–3.47)

– AoAC >0, OR = 4.29 (95% CI, 2.30–7.97)

– ABI <1.1, OR = 1.78 (95% CI, 1.16–2.74)

• For most outcomes, a dose-response 

relationship was observed between pack-years 

of smoking and daily consumption for current 

and former smokers. Time since cessation was 

linearly associated with less atherosclerotic 

burden for all four outcomes

• p for trend <0.05

—

Kianoush et al. 

(2017)

• Cross-sectional study (Brazilian Longitudinal 

Study of Adult Health)

• 14,103 civil servants, 35–74 years of age; 45% 

men; multiethnic (52% White, 28% Brown 

[mixed], 16% Black, and 4% Asian or other); 

30% former smokers, free of prevalent disease 

(including CVD)

• 2008–2010

• Brazil (multicenter cohort, six cities)

• Outcomes: mean carotid IMT, ABI, and CAC

• Compared with never smokers, former 

smokers had higher IMT and odds of ABI ≤1.0 

(p = <.001)

• Compared with never smokers, current 

smokers had higher IMT, odds of ABI ≤1.0, 

and odds of CAC >0 (p = <.001)

• Among former smokers, time since quitting 

was negatively associated with carotid IMT, 

ABI ≤1.0, and CAC >0 (p = <.001)

—

Table 4.11 Continued

The Health Benefits of Smoking Cessation 225

Notes: ABI = ankle-brachial index; AoAC = aortic artery calcium; CAC = coronary artery calcification; CCA = common carotid artery; CHD = coronary heart disease; 

CVD = cardiovascular disease; IMT = intimal-media thickness; mm = millimeters.

aNatural log-transformed IMT.
A Report of the Surgeon General

226 Chapter 4

was not enough evidence to conclude that reducing 

the number of cigarettes smoked per day reduces the 

risk for CVD. Among current smokers, however, a doseresponse relationship has been observed between the 

number of cigarettes smoked per day and the incidence 

of CVD (USDHHS 2010; Benjamin et al. 2017). The next 

section briefly summarizes the evidence that supports 

these conclusions.

Intervention Studies

Much of the evidence linking smoking cessation to 

reduced risk of CVD morbidity and mortality is based on 

observational studies, but the link has also been observed 

in intervention studies directed at increasing cessation. 

The 1990 Surgeon General’s report, which summarized 

results from several clinical trials, found that, overall, 

such interventions tend to decrease risk of CHD or CVD 

mortality. Among these studies, some had interventions 

directed at only smoking cessation, and others addressed 

risk factors in addition to smoking (USDHHS 1990). For 

some of these studies, findings from long-term follow-up 

have been reported subsequently. 

One example is the Lung Health Study, a clinical 

trial started in 1986 that compared a 10-week smoking 

cessation program with usual care among 5,887 smokers 

with asymptomatic airway obstruction (Anthonisen et al. 

2005). The intervention involved strong messaging by 

a physician and a total of twelve 2-hour group sessions 

using behavior modification and nicotine gum. Those 

who quit smoking entered a maintenance program that 

focused on coping skills; this group was described as the 

special-intervention group.

Part of the intervention group received ipratropium, 

a treatment for chronic obstructive pulmonary disease 

and asthma, and the rest of that group received a placebo 

inhaler. A separate group (controls) received care as usual. 

Over 14  years of follow-up, the all-cause mortality rate 

was higher in the usual-care group than in the specialintervention group (hazard ratio [HR]  =  1.18; 95%  CI, 

1.02–1.37). The benefit of cessation was most pronounced 

among the 21.7% of the special-intervention group who 

had quit smoking at 5 years (only 5.4% of usual-care participants had quit). Although there were no significant differences in rates of CHD mortality or CVD mortality, these 

rates were lower in the special-intervention group than 

in the usual-care group. Finally, in observational analyses comparing sustained quitters, intermittent quitters, 

and continuing smokers in this study, smoking status 

was significantly related to unadjusted risk of CHD and 

CVD, with the highest risk among those who continued 

to smoke. 

In the Oslo cardiovascular study, which began in 

1972, 1,232  men free of CVD and diabetes—with total 

serum cholesterol levels of 6.9–8.9  millimoles/liter 

(mmol/L) (80% were smokers)—participated in a 5-year 

intervention study (Hjermann et  al. 1981). At clinical 

visits every 6  months, those in the intervention group 

received dietary advice, and smokers in the intervention 

group were advised to quit. At 40-year follow-up, the intervention group had a reduced risk of death from MI versus 

the control group (HR = 0.71; 95% CI, 0.51–1.00). Most of 

the reduction in MI risk occurred during the first 15 years 

of follow-up; the survival curves for MI were parallel after 

that point (Holme et al. 2016). There was no significant 

difference in all-cause mortality from MI at 40  years, 

although there was a reduction in risk of dying among 

the intervention group across the first 15 years that was 

statistically significant at follow-up. At 5-year follow-up, 

the rate of CHD, MI, and SCD combined was 47% lower 

in the intervention group than in the control group, with 

an estimated 25% of the benefit attributable to smoking 

cessation (Hjermann et al. 1981). Follow-up at 8.5 years 

found a significant reduction in CHD incidence, similar to 

that found at 5 years, among the intervention group compared with the control group; this analysis also observed 

increases in the rate of smoking in the intervention group 

after the end of the trial (Hjermann et al. 1986).

In the Multiple Risk Factor Intervention Trial 

(MRFIT), which was initiated in 1973, 12,866 men at high 

risk of CHD were randomized to usual care or to a multifactor special intervention aimed at lowering serum 

cholesterol and blood pressure and promoting smoking 

cessation. Over follow-up averaging 7  years (during the 

active-intervention period), the rates of the composite 

outcomes of fatal or nonfatal CHD and of fatal or nonfatal 

CVD were significantly lower in the special-intervention 

group than in the usual-care group, by 14% (95%  CI, 

3–24%) for CHD and by 11% (95% CI, 1–21%) for CVD 

(Stamler et al. 2012). Rates of a priori defined endpoints 

(CHD death, CHD death or nonfatal MI, CVD death, and allcause death), however, did not differ significantly between 

the two groups, possibly because of inadequate statistical 

power (Multiple Risk Factor Intervention Trial Research 

Group 1982; Gotto Jr 1997). Importantly, because the 

interventions in the MRFIT and the Oslo cardiovascular 

study did not focus solely on smoking cessation, the effects 

of the smoking cessation intervention cannot be readily 

separated from the effects of the other interventions.

Observational Studies

Much evidence from observational studies supports 

previous conclusions that smoking cessation decreases 

risk of CVD. Based on analyses of mortality in two historical cohorts (Cancer Prevention Study I [CPS I, 1959–

1965] and II [CPS II, 1982–1988]) and five contemporary 

cohorts followed from 2000 to 2010, Thun and colleagues 
The Health Benefits of Smoking Cessation 227

Smoking Cessation

(2013a) concluded that smoking cessation at any age 

reduces the risk of smoking-related death, including 

death from CVD; that much of the excess risk of all-cause 

mortality can be avoided by quitting smoking before 

40 years of age, with additional benefit from quitting earlier (Doll et al. 2004; Jha et al. 2013; Pirie et al. 2013); and 

that quitting smoking completely is much more beneficial than reducing the number of cigarettes smoked per 

day. For example, an analysis of data from the National 

Health Interview Survey found that, on average, smokers 

who quit at 25–34 years of age gained 10 years of life compared with those who continued to smoke; smokers who 

quit at 35–44 years of age gained 9 years; and smokers who 

quit at 45–54 years of age gained 6 years (Jha et al. 2013). 

Similarly, the 50-year analysis of the British Doctors’ 

Study showed that, among men born close to 1920, longterm cigarette smoking beginning in early adulthood tripled age-specific mortality rates, while quitting at 50 years 

of age halved the hazard and quitting at 30 years of age 

avoided most of the hazard (Doll et al. 2004).

Mons and colleagues (2015), who performed a 

pooled analysis of individual-level data from European and 

U.S. cohorts (Consortium on Health and Ageing: Network 

of Cohorts in Europe and the United States [CHANCES]), 

assessed the relationship between smoking cessation 

and risk of cardiovascular mortality in women and men 

60 years of age and older. Smoking was strongly related 

to increased cardiovascular mortality; compared with current smokers, the adjusted HR of cardiovascular mortality 

in former smokers was lower by 0.85 for each 10 years of 

smoking cessation (95%  CI, 0.82–0.89), providing evidence of the benefit of smoking cessation among adults 

60 years of age and older. Former smokers had a higher 

risk of cardiovascular mortality than never smokers 

(Table 4.12 and Figures 4.2a and 4.2b), but the evidence 

suggests a trend of decreasing excess risk as the number 

of years since cessation increases (Table 4.12).

Mons and colleagues (2015) also measured the relationships between smoking cessation and risk advancement periods, which are the average periods of time by 

which the occurrence of an outcome (such as death) 

attributable to a risk factor is advanced in exposed versus 

nonexposed persons (Brenner et  al. 1993; Mons et  al. 

2015). In general, the risk advancement period decreased 

as time since smoking cessation increased. For instance, 

risk advancement periods ranged from 3.75 years (95% CI, 

2.78–4.71) among those who had quit more than 5 years 

earlier to -0.79 years (95% CI, -0.12–1.69) among those 

who had quit 20 or more years earlier.

Many studies have assessed the relationships between 

time since cessation or cumulative exposure and CVD risk. 

For example, in the Nurses’ Health Study, former cigarette smokers had an increased risk of vascular mortality 

compared with never smokers (adjusted HR  =  1.32; 

95% CI, 1.20–1.44) (Kenfield et al. 2008), and compared 

with current smokers, the risk of vascular mortality 

trended downward with increased time since cessation 

(from <5 years to ≥20 years). In the ARIC study of Whites 

and African Americans, former smokers had a 17% significantly greater risk of CVD (defined as MI or stroke) compared with never smokers, with similar elevations observed 

by race and sex (Table 4.13) (Huxley et al. 2012). The benefit of smoking cessation increased as time since cessation 

increased; those who had quit 10  or more years earlier 

had a 33% lower risk of CVD than those who continued to 

smoke (Table 4.13). In the MESA cohort, former smokers 

(median cessation at 22  years of age [+/-  13  years]) did 

not have a significantly higher adjusted HR for all-cause 

CVD compared with never smokers (Table 4.13) (McEvoy 

et al. 2015a). Among current smokers in that same cohort, 

there was a dose-response relationship, as more packyears were associated with a higher risk of CVD, but this 

trend was not observed among former smokers. Another 

analysis of data from the MESA cohort found that former 

smokers—regardless of duration, intensity, or recency of 

cessation—were not at increased risk of CVD compared 

with never smokers (Nance et al. 2017).

Similar findings have been observed in many different populations. For example, in a cohort in China, 

deaths attributable to tobacco-related causes trended 

downward with increased time since smoking cessation 

(He et  al. 2014). A similar pattern was observed in that 

study for deaths attributable to vascular causes (CHD or 

stroke), where compared with current smokers, those who 

had quit for 2–7 years had 0.82 times (95% CI, 0.46–1.47) 

the risk and those who had quit for 8 or more years had 

0.71 times (95% CI, 0.42–1.20) the risk. This pattern did 

not hold for all subtypes of vascular disease, but there were 

limited cases within these categories. In Japan, in a cohort 

of healthy, young, and middle-aged persons, adjusted risk 

of CVD events decreased as time since cessation increased, 

with risk being significantly lower 4 or more years after 

cessation (data not shown) (Kondo et al. 2011).

Similar results have been found among persons 

with diabetes. In a meta-analysis of persons with diabetes, 

former smokers had an increased risk of CVD, CVD mortality (Table  4.12), and total mortality compared with 

never smokers (Pan et  al. 2015). In the Framingham 

Offspring Cohort (included in the meta-analysis by Pan 

and colleagues [2015]), among persons without diabetes, 

nonsmokers, those who had quit for 4 or fewer years, and 

those who had quit for more than 4 years, all had lower 

adjusted risks of CVD than current smokers (Table 4.13) 

(Clair et al. 2013). Similar patterns were observed among 

those with diabetes, but results were not statistically 

significant.
Study Design/population Findings: RR (95% CI) Comments

Mons et al. 

(2015) 

• Individual-level meta-analysis

• 434,278 men and women, ≥60 years of age, 

47% former smokers

• 31,802 CVD deaths

• 25 prospective cohorts

• Data collected from different cohorts in 

various years from the 1980s to the 2010s

• Europe and North America

• Mean follow-up: 1.6–14.8 years (approximately 

8–13 years for most studies)

• Outcome: CVD mortality

• Smoking status:

– Never smoker: 1.00 (referent)

– Former smoker: 1.37 (1.25–1.49)

– Current smoker: 2.07 (1.82–2.36)

• Years since smoking cessation (never vs. 

former smoker):

– Never smoker: 1.00 (referent)

– Former smoker:

 <5: 1.74 (1.51–2.01)

 5–9: 1.60 (1.36–1.88)

 10–19: 1.43 (1.24–1.64)

 ≥20: 1.15 (1.02–1.30)

• Years since smoking cessation (current vs. 

former smoker):

– Current smoker: 1.00 (referent)

– Former smoker:

 <5: 0.90 (0.81–1.00)

 5–9: 0.84 (0.73–0.95)

 10–19: 0.78 (0.71–0.85)

 ≥20: 0.61 (0.54–0.69)

Figure 1 in Mons and colleagues (2015) provides 

more details on results by smoking status

Pan et al.(2015) • Meta-analysis 

• Men and women, >18 years of age with type 1 

or type 2 diabetes mellitus

• Prospective cohort studies:

– CVD: 7 studies for former smokers, 

16 studies for current smokers

– CVD mortality: 8 studies for former 

smokers, 13 studies for current smokers

• Sample:

– CVD: n = 1,028,982; cases = 94,929

– CVD mortality: n = 37,550; cases = 3,163

• United States, Europe, China, New Zealand, 

Australia, and other international collaborations

• Studies included in the meta-analysis were 

published between 1989 and 2015

• Outcomes: CVD and CVD mortality

• CVD:

– Never smoker: 1.00 (referent)

– Former smoker: 1.09 (1.05–1.13)

– Current smoker: 1.44 (1.34–1.54)

• CVD mortality:

– Never smoker: 1.00 (referent)

– Former smoker: 1.15 (1.00–1.32)

– Current smoker: 1.49 (1.29–1.71)

—

a

a

A Report of the Surgeon General

228 Chapter 4

Notes: CI = confidence interval; CVD = cardiovascular disease; RR = risk ratio.

aSome overlap exists between the cohorts included in these publications.

Table 4.12 Meta-analyses of observational studies on smoking cessation and incidence of total cardiovascular disease
The Health Benefits of Smoking Cessation 229

Smoking Cessation

Figure 4.2a Results from the meta-analyses of the association between current and never smoking status and 

cardiovascular mortality

Study

Number of 

events/total

Hazard ratio 

(95% CI)a

ELSA 777/5,128 1.94 (1.55–2.41)

EPIC-Elderly Greece 899/9,325 2.00 (1.61–2.49)

EPIC-Elderly Spain 173/5,023 2.03 (1.29–3.19)

EPIC-Elderly Sweden 148/3,165 2.56 (1.74–3.78)

EPIC-Elderly the Netherlands 277/6,561 2.63 (1.93–3.58)

ESTHER 304/5,062 2.08 (1.51–2.86)

HAPIEE Czech Republic 117/2,742 3.15 (1.90–5.23)

HAPIEE Lithuania 126/4,021 3.49 (2.10–5.81)

HAPIEE Poland 127/3,118 2.52 (1.59–3.98)

HAPIEE Russia 345/3,876 2.25 (1.59–3.17)

MORGAM Brianza 70/672 2.33 (1.19–4.55)

MORGAM Catalonia 25/725 3.20 (0.55–18.54)

MORGAM FINRISK 904/5,326 2.31 (1.88–2.83)

MORGAM Gostrup 427/2,328 1.65 (1.31–2.06)

MORGAM KORA Augsburg 712/3,060 2.50 (2.02–3.10)

MORGAM Northern Sweden 55/859 1.78 (0.83–3.83)

MORGAM SHIP Greifswald 121/1,259 1.24 (0.66–2.33)

MORGAM Warsaw 53/360 0.86 (0.41–1.82)

NHANES 1,762/5,571 1.51 (1.31–1.75)

NIH-AARP 22,683/330,305 2.75 (2.63–2.87)

SENECA 296/1,850 1.48 (1.02–2.14)

SHARE 171/25,835 1.67 (1.03–2.72)

SMC 30/3,519 4.14 (1.62–10.61)

Tromsø 947/3,834 1.68 (1.39–2.02)

Zutphen 253/754 1.83 (1.23–2.71)

Summary estimates

Fixed effects model 2.45 (2.36–2.54)

Random effects model 2.07 (1.82–2.36)

Source: Mons et al. (2015), with permission.

Note: CI = confidence interval; ELSA = English Longitudinal Study of Aging; EPIC = European Prospective Investigation into Cancer 

and Nutrition; ESTHER = Epidemiological Investigations on Opportunities for Prevention, Early Detection and Optimised Treatment 

of Chronic Diseases in the Elderly Population; FINRISK = a large Finnish population survey on risk factors on chronic, noncommunicable diseases; HAPIEE = Health, Alcohol, and Psychosocial factors In Eastern Europe; KORA = Kooperative Gesundheitsforschung 

in der Region Augsburg (Cooperative Health Research in the Augsburg Region); MORGAM = Monica Risk Genetics Archiving and 

Monograph; NHANES = National Health and Nutrition Examination Survey; NIH-AARP = National Institutes of Health–American 

Association of Retired Persons; SENECA = Survey Europe on Nutrition in the Elderly; SHARE = Survey of Health, Aging, and 

Retirement in Europe; SMC = Swedish Mammography Cohort.

aTest for heterogeneity: τ2 = 0.023, p <0.001, I2 = 68.7%. 
A Report of the Surgeon General

230 Chapter 4

Figure 4.2b Results from the meta-analyses of the association between former and never smoking status and 

cardiovascular mortality

Study

Number of 

events/total

Hazard ratio 

(95% CI)a

ELSA 777/5,128 1.44 (1.22–1.69)

EPIC-Elderly Greece 899/9,325 1.50 (1.23–1.83)

EPIC-Elderly Spain 173/5,023 1.81 (1.15–2.85)

EPIC-Elderly Sweden 148/3,165 1.24 (0.83–1.87)

EPIC-Elderly the Netherlands 277/6,561 1.62 (1.22–2.16)

ESTHER 304/5,062 1.09 (0.82–1.44)

HAPIEE Czech Republic 117/2,742 2.09 (1.30–3.36)

HAPIEE Lithuania 126/4,021 2.05 (1.25–3.35)

HAPIEE Poland 127/3,118 1.51 (0.97–2.35)

HAPIEE Russia 345/3,876 1.79 (1.25–2.57)

MORGAM Brianza 70/672 1.47 (0.67–3.19)

MORGAM Catalonia 25/725 3.50 (0.59–20.78)

MORGAM FINRISK 904/5,326 1.41 (1.18–1.68)

MORGAM Gostrup 427/2,328 0.88 (0.68–1.15)

MORGAM KORA Augsburg 712/3,060 1.70 (1.41–2.06)

MORGAM Northern Sweden 55/859 2.07 (1.10–3.90)

MORGAM SHIP Greifswald 121/1,259 0.72 (0.47–1.11)

MORGAM Warsaw 53/360 1.04 (0.47–2.31)

NHANES 1,762/5,571 1.13 (1.01–1.26)

NIH-AARP 22,683/330,305 1.53 (1.48–1.58)

SENECA 296/1,850 1.04 (0.74–1.47)

SHARE 171/25,835 1.34 (0.91–1.97)

SMC 30/3,519 1.12 (0.47–2.71)

Tromsø 947/3,834 1.30 (1.09–1.55)

Zutphen 253/754 1.15 (0.78–1.69)

Summary estimates

Fixed effects model 1.47 (1.43–1.51)

Random effects model 1.37 (1.25–1.49)

Source: Mons and colleagues (2015).

Notes: CI = confidence interval; ELSA = English Longitudinal Study of Aging; EPIC = European Prospective Investigation into 

Cancer and Nutrition; ESTHER = Epidemiological Investigations on Chances of Preventing, Recognizing Early and Optimally 

Treating Chronic Diseases in an Elderly Population; HAPIEE = Health, Alcohol, and Psychosocial factors In Eastern Europe; 

KORA = Kooperative Gesundheitsforschung in der Region Augsburg (Cooperative Health Research in the Augsburg Region); 

MORGAM = Monica Risk Genetics Archiving and Monograph; NHANES = National Health and Nutrition Examination Survey; 

NIH-AARP = National Institutes of Health-American Association of Retired Persons; SENECA = Survey Europe on Nutrition in 

the Elderly; SHARE = Survey of Health, Aging, and Retirement in Europe; SMC = Swedish Mammography Cohort.

aTest for heterogeneity: τ2 = 0.067, P < 0.001, I2 = 82.3%.
Study Design/population Findings: RR (95% CI) Comments

Kondo et al.

(2004)

• Case-control study

• 29 men

• Mean age:

– Nonsmokers: 43.9 years of age

– Smokers: 38.9 years of age

• Nagoya, Japan (years not reported)

• Smoking cessationledto rapidrestorationof

progenitor cells and endothelial progenitor

cell levels

• Circulating progenitor cells andendothelial

progenitor cells increased rapidly after

cessation (p <0.0001) and decreased after

resumption of smoking to a level similar to

that before cessation (p = 0.0031)

—

He et al. (2006) • Cross-sectional study

• 2,334 participants

• 60 years of age or older

• 2001–2002

• Beijing, China

• Smoking cessation was associated with

decreased risks of PAD. Excess risk of PAD was

nearly eliminated after stopping smoking for

10 or more years:

– Never smoker (referent)

– Current smoker 1.57 (1.16–2.13), p <0.01

– Former smoker: 1.42 (1.02–1.98), p <0.05

—

Kenfield et al.

(2008)

• Prospective cohort (Nurses’ HealthStudy)

• 104,519 women

• 1980–2004

• United States

• Compared with never smokers, former

cigarette smokers had an increased risk

of vascular mortality (adjusted HR = 1.32;

95% CI, 1.20–1.44)

Most of the excess risk of vascular mortality

due to smoking canbe eliminatedrapidlyupon

cessationandwithin20 years forlungdiseases

Huxley et al. 

(2012)a,b

• Prospective cohort (Atherosclerosis Risk in 

Communities Study)

• 14,200 participants with 2,777 CVD events,

45–64 years of age, 43% men, 31% former

smokers at baseline, 15% quit during followup, African Americans (27%) and Whites,

free of CHD or stroke

• 1987–2007

• United States (four communities)

• Mean follow-up: 17.1 years

• Outcome: CVDevents (myocardial infarction, 

stroke)

• Compared with never smokers, former 

smokers had a 17% higher risk of CVD

• Compared with never smokers, current 

smokers had:

– Men: 70% higher risk of CVD

– Women: >200% higher risk of CVD

• Years since smoking cessation(overall):

– Continuous smokers: 1.00 (referent)

– 1–3: 0.87 (0.67–1.14)

– 4–9: 0.90 (0.69–1.16)

– ≥10: 0.67 (0.45–1.01)

– p trend: 0.061 (0.69 in African Americans,

0.044 in Whites)

—

The Health Benefits of Smoking Cessation 231

Table 4.13 Observational studies on smoking cessation and cardiovascular disease
Study Design/population Findings: RR (95% CI) Comments

Clair et al. 

(2013)a,b

• Prospective cohort (FraminghamOffspring)

• 3,251 participants and 631 CVDevents

• Baseline: mean age = 47.8 years, 48% men,

mostly White, 26% quit for >4 years and

9% quit for ≤4 years, free of CVD

• 1984–2011

• United States

• Mean follow-up: 25 years

• Outcome:CVD(definedasCHD,cerebrovascular

events, PAD, or congestive heart failure)

• Amongparticipantswithoutdiabetesmellitus:

– Current smokers: 1.00 (referent)

– Former smokers (quit ≤4 years): 0.47

(0.23–0.94)

– Former smokers (quit >4 years): 0.46

(0.34–0.63)

– Nonsmokers: 0.30 (0.21–0.44)

• Similar results in those with diabetes, but not

significant (included in the meta-analysis by

Pan and colleagues [2015] in Table 4.13)

—

McEvoy et al.

(2015a)a

• Prospective cohort (Multi-Ethnic Study of

Atherosclerosis)

• 6,814 multiethnic participantswith 638CVD

events, 45–84 years of age, 47% men,

38% former smokers, free of CVD

• 1996–2011

• United States

• Median follow-up 10.2 years

• Outcome: all-cause CVDc

• Risk of CVD by smoking status:

– Never smoker: 1.00 (referent)

– Former smoker: 1.07 (0.89–1.29)

– Current smoker: 1.70 (1.32–2.18)

Median cessation among former smokers was

22 (+/-13) years; smoking exposure confirmed

by levels of urinary cotinine

Nance et al.

(2017)

• Multi-Ethnic Study of Atherosclerosiscohort

• 6,814participants free of clinicalheartdisease

at baseline

• 45–84 years of age

• 47% men, 53% women

• 2000–2002

• United States

• Former smokers—regardless ofduration,

intensity, or recency—were not at increased

risk for suggesting that risk may drop

precipitously from the time of quitting

• Current smoker:

– CVDH: HR = 1.98 (1.51–2.60), p <0.0005

– CVDA: HR = 1.80 (1.42–2.29), p <0.0005

– CHDH: HR = 1.94 (1.38–2.74), p <0.0005

– CHDA: HR = 1.66 (1.23–2.22), p = 0.001

• Former smoker:

– CVDH: HR = 0.89 (0.72–1.11), p = 0.308

– CVDA: HR = 1.06 (0.89–1.27), p = 0.496

– CHDH: HR = 0.91 (0.69–1.20), p = 0.507

– CHDA: HR = 1.13 (0.92–1.40), p = 0.251

—

A Report of the Surgeon General

Table 4.13 Continued

Notes: CHD = coronary heart disease; CHDA = CHDH, definite angina, probable angina if followed by revascularization; CHDH = coronary heart disease hard (myocardial 

infarction, resuscitated cardiac arrest, CHD death); CI = confidence interval; CVD = cardiovascular disease; CVDA = CVDH, CHDH, atherosclerotic death, CVD death; 

CVDH = CHDH, stroke death, stroke; HR = hazard ratio; PAD = peripheral artery disease; RR = risk ratio.

232 Chapter 4
The Health Benefits of Smoking Cessation 233

aMeasure(s) of association adjusted for covariate(s).

bPooled logistic regression analyses.

cAll-cause CVD events defined as all-cause CHD events plus cerebrovascular accident (CVA), transient ischemic attack, or ischemic or hemorrhagic stroke; CVA death; and 

other CVD death.

Table 4.13 Continued
A Report of the Surgeon General

234 Chapter 4

Summary of the Evidence

The additional evidence reviewed in this section strengthens the basis for previous conclusions that 

smoking cessation reduces the risk of CVD morbidity and 

mortality. For those who quit, there are short-term benefits 

in terms of reduced risk for CVD and a continued decline 

over the long term as time since cessation increases. 

Smoking Cessation and 

Coronary Heart Disease

CHD, the most common form of heart disease in 

the United States, results in part from the buildup of 

plaque (atherosclerosis) on the walls of coronary arteries 

(Centers for Disease Control and Prevention [CDC] 2015). 

MI, or heart attack, occurs when the flow of blood to part 

of the heart muscle is reduced or blocked, damaging that 

part of the heart muscle or causing it to die. The main 

cause of MI is plaque in the coronary arteries; a less 

common cause is severe spasm or contraction of a coronary artery (CDC 2017).

In the United States, someone has an MI once every 

40 seconds (Benjamin et al. 2017). Approximately 7.9 million adults (20 years of age or older) have had an MI, and 

8.7 million have angina pectoris (Benjamin et al. 2017).

In the CHANCES study of women and men 60 years 

of age or older, cigarette smoking was strongly associated 

with acute coronary events (confirmed fatal and nonfatal 

coronary events, such as acute MI, unstable angina pectoris, or coronary death) (Mons et al. 2015). Overall, risk 

of acute coronary events was higher in former smokers 

than in never smokers, and compared with risk among 

current smokers, risk of acute coronary events in former 

smokers decreased greatly as the number of years since 

cessation increased (Table  4.14). Compared with current smokers, the adjusted HR of acute coronary events 

decreased by 0.83 for every 10 years of smoking cessation 

(95% CI, 0.78–0.89).

Similarly, in pooled analyses of two older cohorts 

and five contemporary cohorts that were restricted to men 

and women 55  years of age or older, smoking cessation 

was associated with lower rates of death from CHD compared with the rate of current smokers, but risk of CHD 

death was higher among former smokers compared with 

never smokers (Table  4.14) (Thun et  al. 2013a). Among 

the five contemporary cohorts in that study, benefits generally increased among those who had quit at younger 

ages or who had quit for longer periods of time, but compared with the risk among never smokers, risks remained 

elevated for many years. Among women who had quit for 

30 or more years and among men who had quit for 40 or 

more years, risk of CHD death was similar to that of never 

smokers. Risks of CHD mortality were not elevated among 

men and women who had quit before they were 40 years 

of age. Similar results, showing that the greatest benefit 

occurred among those who had quit at younger ages, were 

observed in a large cohort study of women in the United 

Kingdom (Table 4.15) (Pirie et al. 2013).

The 2014 Surgeon General’s report (USDHHS 2014) 

noted that the pattern of declining CHD risk with increasing 

time since cessation was not as strong among the contemporary cohorts analyzed by Thun and colleagues (2013a) 

as with earlier observational analyses (including the Lung 

Health Study and MRFIT cohorts) that reported a larger 

decline in CVD risk as time since cessation increased. The 

report attributed this difference to the fact that analyses by 

Thun and colleagues (2013a) focused on older adults.

In a meta-analysis of studies comparing smoking as 

a risk factor for CHD in women and men, the adjusted relative risk (RR) of CHD was higher in women than in men 

for current cigarette smokers compared with nonsmokers, 

but the risk did not differ between women and men who 

were former smokers (Huxley and Woodward 2011).

Pujades-Rodriguez and colleagues (2015) reported 

on the relationship between smoking and initial presentations of CVD in the CALIBER (ClinicAl research using 

LInked Bespoke studies and Electronic health Records) 

(University College London n.d.), drawing on linked electronic health records of 1.93 million persons 30 years of 

age or older in England. In age-adjusted analyses (stratified by sex and general practice), the hazards of stable 

angina, unstable angina, MI, and sudden coronary death 

decreased gradually with increasing time since smoking 

cessation (Table 4.15). After 10 years of cessation, former 

smokers tended to have the same hazard of CHD outcomes as never smokers (not shown in table), although 

the HR for sudden coronary death in women (HR = 2.74; 

95% CI, 1.36–5.51) remained elevated. The main analysis 

imputed smoking status for 523,611 participants. Results 

were similar for complete case analyses (1.41 million persons with smoking status) and when adjusting for other 

variables. It is unclear, however, how many persons in this 

study had missing covariates and whether any analyses 

were run without imputed covariates, which could have 

influenced the validity of the findings.

In the Nurses’ Health Study (included in the pooled 

analysis by Thun and colleagues [2013]), former smokers 

had an increased risk of CHD mortality compared with 

never smokers (adjusted HR = 1.24; 95% CI, 1.09–1.42) 

(Kenfield et  al. 2008). Compared with current smokers, 

former smokers showed a trend of decreased risk of CHD 

mortality with increased time since cessation (from fewer 

than 5 years to 20 or more years). In this study, former 

smoking was also associated with risk of all CHD events 
Study Design/population Findings: RR (95% CI) Comments

Thun et al. 

(2013a)a,b

• Pooled analysis

• Men and women, ≥55 years of age

• Two historical cohorts (CPS I and II) and 

five contemporary cohorts:

b

– CPS I: n = 518,982; cases = 17,809

– CPS II: n = 746,485; cases = 16,308

– Contemporary cohorts: n = 956,756;

cases = 22,622

• United States

• Follow-up:

– CPS I: 1959–1965

– CPS II: 1982–1988

– Contemporary cohorts: 2000–2010

• Outcome: CHD deaths

 CPS I:

– Men:

 Never smoker: 1.00 (referent)

 Former smoker: 1.28 (1.21–1.36)

 Current smoker: 1.69 (1.61–1.77)

– Women:

 Never smoker: 1.00 (referent)

 Former smoker: 1.39 (1.22–1.59)

 Current smoker: 1.56 (1.46–1.67)

 CPS II:

– Men:

 Never smoker: 1.00 (referent)

 Former smoker: 1.27 (1.21–1.33)

 Current smoker: 1.78 (1.69–1.88)

– Women:

 Never smoker: 1.00 (referent)

 Former smoker: 1.27 (1.19–1.36)

 Current smoker: 2.00 (1.88–2.13)

 Contemporary cohorts:

– Men:

 Never smoker: 1.00 (referent)

 Former smoker: 1.43 (1.37–1.48)

 Current smoker: 2.50 (2.34–2.66)

– Women:

 Never smoker: 1.00 (referent)

 Former smoker: 1.44 (1.38–1.51)

 Current smoker: 2.86 (2.65–3.08)

—

Table 4.14 Meta-analyses and a pooled analysis of observational studies on smoking cessation and incidence of coronary heart disease

The Health Benefits of Smoking Cessation 235
Study Design/population Findings: RR (95% CI) Comments

Mons et al. 

(2015)

• Individual-level meta-analysis of 19 prospective

cohorts

• 64,221 men and women, ≥60 years of age, 

47% former smokers, excluded those with a 

history of acute coronary events

• Europe

• Studies included data collected from different 

cohorts from various years from the 1980s to 

the 2010s

• Mean follow-up: 1.6–14.8 years (approximately

8–13 years for most studies)

• Outcome: acute coronary events

• Smoking status:

– Never smoker: 1.00 (referent)

– Former smoker: 1.18 (1.06–1.32)

– Current smoker: 1.98 (1.75–2.25)

• Years since smoking cessation:

– Current smoker: 1.00 (referent)

– <5: 0.84 (0.72–0.98)

– 5–9: 0.86 (0.72–1.02)

– 10–19: 0.69 (0.58–0.82)

– ≥20: 0.58 (0.46–0.72)

—

Pan et al. 

(2015) 

• Meta-analysis of prospective cohort studies:

• 13 studies of former smokers

• 21 studies of current smokers

• 1,009,457 men and women, >18 years of 

age with diabetes mellitus (type 1 or 2), 

38,752 cases

• Studies in the meta-analysis were published 

between 1989 and 2015

• United States, Europe, China, New Zealand, 

and other international collaborations

• Outcome: CHD

• Smoking status:

– Never smoker: 1.00 (referent)

– Former smoker: 1.14 (1.00−1.30)

– Current smoker: 1.51 (1.41−1.62)

—

a,b 

a

A Report of the Surgeon General

236 Chapter 4

Table 4.14 Continued

Notes: CHD = coronary heart disease; CI = confidence interval; CPS = Cancer Prevention Study; RR = risk ratio.

aThere was some overlap between cohorts included in two or more of these publications in this table.

bHistorical cohorts: CPS I (1959–1965) and CPS II (1982–1988). Contemporary cohorts (2000–2010): National Institutes of Health–American Association of Retired Persons 

Diet and Health Study, CPS II Nutrition Cohort, Women’s Health Initiative (women only), Nurses’ Health Study (women only), and Health Professionals Follow-Up Study 

(men only).
Study Design/population Findings: RR (95% CI) Comments

Song and Cho 

(2008)a

• Prospective cohort

• 475,734 men, 30–58 years of age in 1990,

6% quitters,

b 16% ex-smokers,b free of stroke

or myocardial infarction, 2,164 cases of CHD

• 1992–2001

• Korea

• Mean follow-up: 8.83 years

• Outcome: myocardial infarction

• Nonreducing heavy smoker (>20 cigarettes 

per day), moderate smoker (10–19 cigarettes 

per day), light smoker (<10 cigarettes per day); 

reducer from heavy to moderate smoking; 

reducer from heavy to light smoking; reducer 

from moderate to light smoking; quitter from 

any smoking status; sustained ex-smoker; 

and sustained never smoker

• Smoking status:b

– Current smoker (by smoking intensity):

 Non-reducing heavy smoker 1.00 (referent)

 Moderate smoker: 0.74 (0.65–0.85)

 Light smoker: 0.65 (0.57–0.75)

– Quitter: 0.43 (0.34–0.53)

– Sustained ex-smoker: 0.37 (0.32–0.44)

– Never smoker: 0.29 (0.25–0.34)

Women not included because of their low 

percentage of smoking

Pirie et al. 

(2013)a

• Prospective cohort (Million Women Study)

• 1.2 million women; 55 years of age (median)

at baseline; 28% former smokers; free of

prior cancer (other than nonmelanoma skin

cancer), heart disease, stroke, and current 

respiratory disease treatment; 4,458 cases 

of CHD among never or current smokers

• 1996–2011

• United Kingdom

• Mean follow-up: 12 years

• Outcome: CHD mortality

• Age (in years) quit smoking:

– Never smoker: 1.00 

(referent)

– <25: 0.8 

– 25–34: 1.0 

– 35–44: 1.4

c 

– 45–54: 1.9 

Exact CIs not reported for these results; total 

number of CHD cases not provided

McEvoy et al. 

(2015a)a

• Prospective cohort (Multi-Ethnic Study of

Atherosclerosis)

• 6,814 participants, 45–84 years of age,

47% men, multiethnic, 38% former smokers, 

free of CVD at baseline; 284 hard CHD events

and 449 all-cause CHD events

• 1996–2011

• United States

• Median follow-up: 10.2 years

• Outcomes: hard CHD and all-cause CHDd

• Hard CHD events:

– Never smoker: 1.00 (referent)

– Former smoker: 0.93 (0.70–1.24)

– Current smoker: 1.70 (1.18–2.45)

• All-cause CHD events:

– Never smoker: 1.00 (referent)

– Former smoker: 1.14 (0.91–1.42)

– Current smoker: 1.55 (1.14–2.10)

Median length of cessation among former 

smokers was 22 (+/-13) years; smoking exposure 

confirmed by urinary cotinine

Table 4.15 Observational studies on smoking cessation and incident coronary heart disease

The Health Benefits of Smoking Cessation 237
Study Design/population Findings: RR (95% CI) Comments

PujadesRodriguez et al. 

(2015)

• Prospective cohort

• 1.93 million participants, ≥30 years of age, 

49% men, predominantly White (also South 

Asian and Black), 16.2% former smokers 

(among those with smoking data); drawn from 

CALIBER program (linked electronic health 

records); no history of CVD, 4,253 cases of 

myocardial infarction in former smokers

• 1997–2010

• England

• Median follow-up: 6 years

• Myocardial infarction by smoking status 

(age-adjusted):

– Current smoker: 1.00 (referent)

– Former smoker (years since quitting):

 <2: 0.55 (0.34–0.88)

 2–9: 0.52 (0.41–0.65)

 ≥10: 0.45 (0.38–0.55)

• Stronger association with more time since 

cessation for outcomes of unheralded 

coronary death and unstable angina

– Former smoker (years since quitting):

 <2: 1.01 (0.60–1.71)

 2–9: 0.76 (0.47–1.23)

 ≥10: 0.61 (0.41–0.89)

– Former smoker (years since quitting):

 <2: 1.05 (0.55–1.99)

 2–9: 0.86 (0.63–1.18)

 ≥10: 0.63 (0.52–0.77)

• Weaker trend for outcome of stable angina

– Former smoker (years since quitting):

 <2: 1.03 (0.66–1.60)

 2–9: 0.88 (0.69–1.12)

 ≥10: 0.81 (0.81–0.99)

Imputed smoking status in the main 

analyses, as smoking data were missing in 

523,611 participants; results were similar for

complete case analysis (1.41 million participants 

with smoking status) and when adjusted for 

other potential confounders; unclear how many 

persons had missing covariates and whether 

analyses were run without imputed covariates, 

which might have influenced validity of findings

A Report of the Surgeon General

Table 4.15 Continued

Notes: CALIBER = Clinical research using LInked Bespoke studies and Electronic health Records; CHD = coronary heart disease; CI = confidence interval; CVD = cardiovascular disease; RR = risk ratio.

aMeasure(s) of association adjusted for covariate(s).

bSmoking categories based on smoking status in 1990 baseline exam and change in status from 1990 to 1992 exams: non-reducing heavy smoker (≥20 cigarettes per day), 

moderate smoker (10–19 cigarettes per day), light smoker (<10 cigarettes per day), reducer from heavy to moderate, reducer from heavy to light, reducer from moderate 

to light, quitter from any smoking status, sustained ex-smoker, sustained never smoker. Results for reducers not shown in table.

cLower boundary of 95% CI >1.0.

dHard CHD events defined as myocardial infarction or death from CHD. All-cause CHD events defined as hard CHD events plus definite angina, probable angina resulting 

in revascularization, and resuscitation after cardiac arrest.

238 Chapter 4
The Health Benefits of Smoking Cessation 239

Smoking Cessation

(fatal and nonfatal), but there was a stronger association 

for current smokers than for former smokers (Hu et al. 

2000; Stampfer et al. 2000). In the MESA cohort, former 

smokers (median cessation: 22  years [+/-  13  years]) did 

not have a higher adjusted hazard for either a more 

strictly defined or a more broadly defined CHD outcome 

(Table 4.15) (McEvoy et al. 2015a). Despite a positive doseresponse relationship between pack-years of smoking and 

CHD among current smokers, the dose-response relationship was null among former smokers (data not shown). 

Both a high-sensitivity CRP ≥3  mg/L and, particularly, 

a CAC >100 identified current smokers with a higher RR 

of CHD. In a large cohort of Korean men, both those who 

quit smoking within 2 years before the start of follow-up 

and those who had quit for a longer period had a lower 

adjusted hazard of MI compared with current heavy 

smokers (Table 4.15) (Song and Cho 2008).

Lee and colleagues (2012) used a negative exponential distribution to quantitatively estimate how rapidly the risk of CHD declines following smoking cessation. Estimates from this approach were used to inform 

a special report from the American Heart Association and 

the American College of Cardiology on the longitudinal 

risks and benefits of therapies to prevent cardiovascular 

problems among Medicare patients (Lloyd-Jones et  al. 

2017). Based on a literature search and on consultation 

within their own team and with biostatistical and content 

experts, Lloyd-Jones and colleagues (2017) concluded that 

the approach set forth by Lee and colleagues (2012) was 

the most rigorous methodology for estimating the longitudinal reduction in MI risk associated with tobacco 

cessation. The quantitative review by Lee and colleagues 

(2012) had estimated that the excess risk of CHD associated with smoking decreased by 50% at 4.40 years after 

cessation (95% CI, 3.26–5.95), but there was a substantial range in the estimate of the time required to achieve 

a 50% decrease in CHD risk across the studies, from less 

than 2 years to greater than 10 years. The cohort studies 

considered by Lee and colleagues (2012) had little followup time after 2000, and alternative models to the negative 

exponential model were not considered. It should be noted 

that Philip Morris funded the research for this paper.

In line with IARC (2007), the risk of MI appears to 

decrease asymptotically as time since cessation increases, 

eventually reaching the risk among never smokers. In 

another modeling paper, Hurley (2005) also observed a 

rapid decrease in the risk of acute MI within 1–2 years of 

cessation, followed by a slower decline thereafter.

Summary of the Evidence

Building on evidence reviewed in previous Surgeon 

General’s reports, additional studies have added to the 

evidence base indicating that smoking cessation reduces 

the risk of CHD. The risk declines rapidly in the period 

immediately following cessation and then declines at a 

slower rate in the longer term. In some studies, the risk 

for CHD in former smokers eventually decreases to that of 

never smokers.

Smoking Cessation and 

Cerebrovascular Disease

Cerebrovascular disease results from interruptions 

in the flow of arterial blood to the brain, resulting in a 

syndrome of mild-to-severe neurologic deficits. Deficits 

can be temporary (transient ischemic attack) or permanent (stroke). In the United States, cerebrovascular disease is the fifth leading cause of death (Kochanek et al. 

2016), responsible for approximately 140,000 deaths each 

year (Yang et  al. 2017). In 2017 it was estimated that 

7.7 million U.S. adults 18 years of age or older have had 

a stroke (Benjamin et  al. 2017). Ischemic stroke, which 

results from an obstruction in a blood vessel that blocks 

the supply of blood to the brain, accounts for an estimated 87% of strokes in the United States (Benjamin 

et al. 2017). Hemorrhagic stroke occurs when a weakened 

blood vessel ruptures and causes either an intracerebral 

(within the brain) hemorrhage (ICH) or a subarachnoid 

hemorrhage (SAH). From 2014 to 2015, the annual direct 

(medical) plus indirect costs of stroke in the United States 

was estimated to be $45.5 billion (Benjamin et al. 2019). 

Heidenreich and colleagues (2011) projected that the 

direct (medical) cost of stroke will increase by 238% from 

2010 to 2030.

Previous Surgeon General’s reports (USDHHS 

1989, 2004) have concluded that smoking is a cause of 

stroke. The 1990 Surgeon General’s report concluded 

that smoking cessation reduces the risk of both ischemic 

stroke and SAH compared with continued smoking, and 

that the risk of stroke returns to that of never smokers 

5–15 years after quitting (USDHHS 1990) (Table  4.10). 

Similarly, the 2001 Surgeon General’s report concluded 

that in most studies including women, the increased 

risk for stroke associated with smoking is reversible after 

smoking cessation; after 5–15 years of abstinence, the risk 

among former smokers approaches that of women who 

have never smoked (USDHHS 2001) (Table 4.10).

Several pooled studies or meta-analyses have found 

that smoking cessation is associated with a reduced risk of 

stroke or stroke mortality (Table 4.16) (Feigin et al. 2005; 

Peters et  al. 2013; Thun et  al. 2013a; Mons et  al. 2015; 

Pan et al. 2015). Peters and colleagues (2013), in a metaanalysis of prospective cohort studies from around the 

world that were published between January 1, 1966, and 
Study Design/population Findings: RR (95% CI) Comments

Feigin et al. 

(2005)a

•

•

•

•

•

•

Meta-analysis of five longitudinal studies

and three case-control studies

Men and women

Number of cases for analysis of current 

smoking:

– Longitudinal studies: 453

– Case-control studies: 607

Follow-up: 5–22 years

Studies included in the meta-analysis were 

published between 1966 and 2015

United States, Europe, and Asia-Pacific region

• Outcome: subarachnoid hemorrhage

• Longitudinal studies:

– Never smoker vs. former smoker:





Never smoker: 1.00 (referent)

Former smoker: 1.9 (1.5–2.3)

– Nonsmoker vs. current smoker:





Nonsmoker: 1.00 (referent)

Current smoker: 2.2 (1.3–3.6)

• Case-control studies:

– Never smoker vs. former smoker:





Never smoker: 1.00 (referent)

Former smoker: 2.3 (2.2–2.4)

– Nonsmoker vs. former smoker:





Nonsmoker: 1.00 (referent)

Current smoker: 3.1 (2.7–3.5)

—

Table 4.16 Observational studies (meta-analyses and pooled analyses) on smoking cessation and cerebrovascular disease 

A Report of the Surgeon General

240 Chapter 4
Study Design/population Findings: RR (95% CI) Comments

Thun et al. 

(2013a)a,b

•

•

•

•

Pooled analysis

Men and women, ≥55 years of age

Two historical cohorts (CPS I and II)

and five contemporary cohortsc

Sample:

– CPS I: n = 518,982; 5,890 deaths

from stroke

– CPS II: n = 746,485; 4,037 deaths

from stroke

•

•

•

Contemporary cohorts: 956,756; 7,536

United States

Follow-up:

–

–

CPS I: 1959–1965

CPS II: 1982–1988

•

•

Contemporary cohorts: 2000–2010

Outcome: deaths from stroke

• CPS I:

– Men:







Never smoker: 1.00 (referent)

Former smoker: 0.95 (0.83–1.09)

Current smoker: 1.38 (1.26–1.52)

– Women:







Never smoker: 1.00 (referent)

Former smoker: 1.46 (1.19–1.78)

Current smoker: 1.51 (1.35–1.69)

• CPS II:

– Men:







Never smoker: 1.00 (referent)

Former smoker: 1.07 (0.95–1.20)

Current smoker: 1.97 (1.74–2.23)

– Women:







Never smoker: 1.00 (referent)

Former smoker: 1.16 (1.03–1.31)

Current smoker: 2.19 (1.96–2.44)

• Contemporary cohorts:

– Men:







Never smoker: 1.00 (referent)

Former smoker: 1.16 (1.07–1.25)

Current smoker: 1.92 (1.66–2.21)

– Women:







Never smoker: 1.00 (referent)

Former smoker: 1.15 (1.07–1.22)

Current smoker: 2.10 (1.87–2.36)

—

Peters et al. 

(2013)a

• Meta-analysis of prospective cohorts

– Current smokers: 76 cohorts 

– Former smokers: 72 cohorts 

• Men and women, ≥18 years of age: 

– Current smokers: n = 3,817,289;

39,042 cases of stroke

– Former smokers: n = 3,534,330;

36,449 cases of stroke

• Studies in the meta-analysis were published 

between January 1, 1996, and January 26, 2013 

• United States, Europe, and Asia-Pacific region 

• Outcome: fatal and nonfatal stroke

• Men:

–

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 1.08 (1.03–1.13)

Nonsmoker: 1.00 (referent)

Current smoker: 1.67 (1.49–1.88)

• Women:

–

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 1.17 (1.12–1.22)

Nonsmoker: 1.00 (referent)

Current smoker: 1.83 (1.58–2.12)

—

Table 4.16 Continued

The Health Benefits of Smoking Cessation 241
Study Design/population Findings: RR (95% CI) Comments

Mons et al. 

(2015)a,b

• Individual-level meta-analysis of

19 prospective cohorts

• 66,136 men and women, ≥60 years of age, 

approximately 47% former smokers, 

excluded those with a history of stroke, 

4,052 cases of stroke

• Years of data collection: not provided

• Europe

• Mean follow-up: 1.6–14.8 years (8–13 years

• for most studies)

• Outcome: stroke

• Smoking status:

– Never smoker: 1.00 (referent)

– Former smoker: 1.17 (1.07–1.26)

– Current smoker: 1.58 (1.40–1.78)

• Years since quitting:

– Current smoker: 1.00 (referent)

– Former smoker:

 <5: 0.97 (0.79–1.19)

 5–9: 0.98 (0.74–1.31)

 10–19: 0.79 (0.69–0.92)

 ≥20: 0.67 (0.60–0.76)

—

Pan et al. (2015) • Meta-analysis of prospective cohort studies:

– 9 studies of former smokers

– 15 studies of current smokers

• 1,013,724 men and women >18 years of 

age with diabetes mellitus (type 1 or 2); 

33,170 cases of stroke

• Studies in the meta-analysis were published 

between 1989 and 2015

• United States, Europe, China, and other

international collaborations

• Outcome: stroke

• Smoking status:

– Never smoker: 1.00 (referent)

– Former smoker: 1.04 (0.87–1.23)

– Current smoker: 1.54 (1.41–1.69)

—

Table 4.16 Continued

A Report of the Surgeon General

242 Chapter 4

Notes: CI = confidence interval; CPS = Cancer Prevention Study; RR = risk ratio.

aThere was some overlap between cohorts that were included in two or more of the publications in this table.

bHistorical cohorts: CPS I (1959–1965) and CPS II (1982–1988). 

cContemporary cohorts (2000–2010): National Institutes of Health–American Association of Retired Persons Diet and Health Study, CPS II Nutrition Cohort, Women’s 

Health Initiative (women only), Nurses’ Health Study (women only), and Health Professionals Follow-Up Study (men only).
The Health Benefits of Smoking Cessation 243

Smoking Cessation

January 26, 2013, found that, compared with nonsmokers 

(who were either never smokers or former smokers), the 

risk of stroke in current smokers was 83% higher (95% CI, 

1.58–2.12) for women and 67% higher for men (95% CI, 

1.49–1.88) (Table  4.16) (Peters et  al. 2013). Compared 

with never smoking, former smoking was associated with 

a 17% higher risk of stroke among women (95% CI, 1.12–

1.22) and an 8% higher risk among men (95% CI, 1.03–

1.13). There was no evidence of a difference in the benefit of smoking cessation between women and men. This 

analysis did not evaluate the relationships between risk of 

stroke and smoking duration or time since quitting.

Mons and colleagues (2015) examined individual data 

from the CHANCES study (European and North American 

cohorts) to assess the relationship between smoking cessation and risk of stroke in women and men 60 years of 

age or older, and found that smoking was strongly associated with increased risk of stroke. Overall, former smokers 

had a higher risk of stroke than never smokers. Compared 

with current smokers, there was a dose-response relationship, with risk decreasing among former smokers as years 

since cessation increased (Table 4.16). In this comparison, 

the adjusted HR of stroke was 0.87 for every 10 years of 

smoking cessation (95% CI, 0.84–0.91). Similarly, Thun 

and colleagues (2013a) reported that smoking cessation reduced rates of death from stroke in two older and 

five contemporary cohorts restricted to men and women 

55 years of age or older (Table 4.16), with a greater benefit generally found among those who had quit at younger 

ages. Risk of stroke mortality among former smokers 

tended to decrease as time since cessation increased.

Similarly, in a large cohort study of women in 

the United Kingdom, most of the benefit from cessation occurred among those who had quit at younger 

ages (Table  4.17) (Pirie et al. 2013). Elsewhere, in the 

Nurses’ Health Study (included in the pooled analysis 

by Thun and colleagues [2013]), former smokers had an 

increased risk of cerebrovascular mortality compared with 

never smokers (adjusted HR = 1.27; 95% CI, 1.06–1.51) 

(Kenfield et al. 2008). Compared with current smokers, 

risk of cerebrovascular-disease mortality decreased among 

former smokers with increased time since cessation (from 

fewer than 5 years to 20 or more years). In contrast to 

the Nurses’ Health Study, the British Regional Heart 

Study found that former light smokers (1–19 cigarettes 

per day) did not have an increased risk of stroke when 

compared with never smokers; current heavy smokers 

(≥21 cigarettes per day), however, had an increased risk 

(Wannamethee et al. 1995). In that study, compared with 

never smokers, former smokers had 1.7 times the adjusted 

hazard of stroke (95% CI, 0.9–4.8); there was not a consistent pattern of decreasing risk with increased time since 

cessation, but this pattern was seen in some categories. 

Similar findings have been reported by many other 

studies (Table  4.17). In a case-control study of young 

women (15–40 years of age) with ischemic stroke, former 

smokers did not have an increased risk of stroke compared with never smokers, but this study had the potential limitation of recall bias (Bhat et al. 2008). The Strong 

Heart Study, a population-based cohort recruited from 

13 American Indian tribes/communities, found that current and former smokers had an increased adjusted hazard 

of stroke compared with never smokers (Zhang et al. 2008). 

For this study, former smoking was defined as having 

smoked 100 or more cigarettes in one’s lifetime, having 

smoked cigarettes regularly in the past, and not smoking 

currently. In a meta-analysis of persons with diabetes mellitus, former smokers did not have an increased risk of 

stroke compared with never smokers (Pan et al. 2015).

In an analysis similar to the one of CHD, Lee and 

colleagues (2014) quantitatively estimated reduction in 

stroke risk following smoking cessation. In a fixed-effects 

model, they estimated that the excess risk of stroke associated with smoking decreased by 50% after 4.78 years of 

smoking abstinence (95% CI, 2.17–10.50), which is similar 

to the time needed to realize a 50% reduction in risk that 

they had estimated for CHD. There was considerable unexplained heterogeneity in the results, however, making a 

definitive conclusion challenging; the random-effects estimate for a 50% reduction was 3.08 years (95% CI, 1.32–

7.16). Hurley (2005), in another modeling paper, observed 

a rapid decrease in risk of stroke shortly after cessation 

(within 1–2 years), followed by a slower decline.

Stroke Subtypes

Several studies have assessed relationships between 

smoking cessation and subtypes of stroke (SAH, ICH, and 

ischemic stroke) (Kawachi et al. 1993; Kurth et al. 2003a,b; 

Feigin et al. 2005; Sturgeon et al. 2007; Song and Cho 2008; 

Pujades-Rodriguez et al. 2015; Lindbohm et al. 2016). 

In a meta-analysis of longitudinal and case-control 

studies by Feigin and colleagues (2005), former smoking 

was associated with twice the risk of SAH compared with 

never smoking (Table  4.16). Some of the studies in this 

meta-analysis assessed amount smoked or time since cessation or examined subtypes of stroke. Kurth and colleagues 

(2003a,b) assessed associations between smoking and 

hemorrhagic stroke subtypes in men (Physician’s Health 

Study) and women (Women’s Health Study) (Table 4.17). 

In both studies, former smokers and never smokers had 

no significant difference in risk of total hemorrhagic 

stroke, ICH, and SAH (Table  4.17). Earlier, Kawachi and 

colleagues (1993) reported that, in women in the Nurses’ 

Health Study, the excess risk for total strokes decreased 

within approximately 2–4  years after smoking cessation 

compared with the risk among current smokers. Those 
Study Design/population Findings: RR (95% CI) Comments

Kurth (2003a)a •

•

•

•

•

•

Prospective cohort (observational analyses 

of Women’s Health Study, a randomized 

controlled trial)

39,783 women, 40–84 years of age at entry, 

95% White, apparently healthy and free of 

stroke at baseline, seven hemorrhagic strokes

1993–2003

United States

Mean follow-up: 9 years

Outcome: hemorrhagic stroke (and subtypes)

Similar patterns for subtype analysis of

intracerebral hemorrhage and subarachnoid

hemorrhage

• Total hemorrhagic stroke:

–

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 0.97 (0.55–1.72)

Current smoker (<20 cigarettes smoked

per day): 1.93 (0.75–5.02)

Current smoker (≥20 cigarettes smoked

per day): 3.29 (1.72–6.29)

•

—

Kurth (2003b)a •

•

•

•

•

•

Prospective cohort (observational analyses

of Physicians’ Health Study, a randomized

controlled trial)

22,022 male physicians, 40–84 years of age at

entry, 92% White, apparently healthy and free

of stroke at baseline, 139 cases of stroke

1982–2002

United States

Mean follow-up: 17.8 years

Outcome: hemorrhagic stroke (and subtypes)

• Total hemorrhagic stroke:

–

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 0.76 (0.53–1.09)

Current smoker (<20 cigarettes smoked

per day): 1.65 (0.61–4.50)

Current smoker (≥20 cigarettes smoked

per day): 2.36 (1.38–4.02)

• Similar patterns for subtype analysis of

intracerebral hemorrhage and subarachnoid

hemorrhage

—

Bhat et al. 

(2008)a

• Case-control (Stroke Prevention in Young 

Women Study)

• Females, 15–40 years of age, 466 cases

of stroke and 604 controls (random-digit

dialing; matched by age and geographic

region of residence)

•

•

•

Recruited in 1992–1996 and 2001–2003

United States (greater Baltimore–Washington,

D.C., area)

Outcome: ischemic stroke

• Smoking status:

Never smoker: 1.00 (referent)

Former smoker: 1.0 (0.6–1.4)

Current smoker (cigarettes smoked per day):

–

–

–

○

○ 

○ 

○ 

○

All: 2.6 (1.9–3.6) 

1–10: 2.2 (1.5–3.3)

11–20: 2.5 (1.6–3.8)

21–39: 4.3 (1.8–10)

≥40: 9.1 (3.2–26)

Potential for recall bias

Table 4.17 Observational studies on smoking cessation and cerebrovascular disease

A Report of the Surgeon General

244 Chapter 4
Study Design/population Findings: RR (95% CI) Comments

Song and Cho 

(2008)a

• Prospective cohort

• 475,734 men, 30–58 years of age in 1990, 

6% quitters,b 16% ex-smokers,b free of 

stroke or myocardial infarction, 6,092 cases 

of stroke

•

•

•

•

1992–2001

Korea

Mean follow-up: 8.83 years

Outcome: total stroke

• Smoking status:b

– Current smoker:













Non-reducing heavy smoker

(≥20 cigarettes per day): 1.00 (referent)

Moderate smoker: (10–19 cigarettes

per day): 0.86 (0.78–0.93)

Light smoker (<10 cigarettes per day):

0.84 (0.77–0.93)

– Quitter: 0.70 (0.62–0.80)

– Ex-smoker: 0.53 (0.48–0.58)

– Never smoker: 0.57 (0.52–0.63)

• Similar patterns observed for stroke subtypes 

(ischemic stroke, hemorrhagic stroke, and 

subarachnoid hemorrhage):

– Hemorrhagic stroke: lighter smokers and 

quitters did not have a significantly different 

risk vs. heavy smokers

– Subarachnoid hemorrhage: moderate 

smokers (10–19 cigarettes per day) did 

not have a lower risk than heavy smokers 

(≥20 cigarettes per day)

—

Zhang et al. 

(2008)a

•

•

•

•

•

•

Prospective cohort (Strong Heart Study)

4,507 participants from 13 American Indian 

tribes/communities, 45–74 years of age, 

41% men, no history of stroke, 306 events 

of stroke

1989–2004

Arizona, North Dakota, Oklahoma, and 

South Dakota

Mean follow-up: 13.4 years

Outcome: stroke

• Smoking status:c

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 1.6 (1.14–2.25)

Current smoker: 2.38 (1.69–3.36)

—

Table 4.17 Continued

The Health Benefits of Smoking Cessation 245
Study Design/population Findings: RR (95% CI) Comments

Kim et al. 

(2012a)a

•

•

•

•

•

Case-control study (multicenter)

Participants, 30–84 years of age (mean 

age: 50.7 years); 39% men; 426 cases and 

426 age–sex-matched controls (recruited 

from siblings, friends, or neighbors of 

controls); free of stroke, dementia, or other 

neurological diseases

Recruited in 2002–2004

Korea

Outcome: subarachnoid hemorrhage

• Smoking status:

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 1.79 (0.86–3.75)

Current smoker: 2.84 (1.63–4.97)

• Years since quitting (current vs. former 

smoker):

–

–

Current smoker: 1.00 (referent)

Former smoker





<5: 0.94 (0.41–2.16)

≥5: 0.41 (0.17–0.97)

• Years since quitting (never vs. former smoker):

–

–

Never smoker: 1.00 (referent)

Former smoker:





<5: 2.71 (1.07–6.81)

≥5: 1.17 (0.46–3.00)

• Smoking intensity (current vs. former smoker):

–

–

Current smoker: 1.00 (referent)

Former smoker:





1–19 cigarettes per day: 0.36 (0.13–1.01)

≥20 cigarettes per day: 0.84 (0.40–1.78)

• Smoking intensity (never vs. former smoker):

–

–

Never smoker: 1.00 (referent)

Former smoker:





1–19 cigarettes per day: 0.99 (0.32–3.06)

≥20 cigarettes per day: 2.34 (1.02–5.36)

Potentialforbiasbecauseof recallandselection 

of controls from siblings, friends, or neighbors

Table 4.17 Continued

A Report of the Surgeon General

246 Chapter 4
Study Design/population Findings: RR (95% CI) Comments

Tse et al. 

(2012)a

•

•

•

•

•

•

Prospective cohort (extension of 7-5 China

Stroke Prevention Project)

26,607 participants ≥35 years of age, 

47% men, free of stroke; former smokers

included 7.2% of men and 1.5% of women; 

1,108 cases of stroke

1986–2000

China

Mean follow-up: 9.5 years

Outcomes: total stroke, ischemic stroke, 

and hemorrhagic stroke

• Men

– Total stroke:







Never smoker: 1.00 (referent)

Former smoker: 1.35 (1.00–1.81)

Current smoker: 1.39 (1.15–1.67)

– Similar patterns for ischemic and 

hemorrhagic stroke

• Women:

– Total stroke:







Never smoker: 1.00 (referent)

Former smoker: 0.86 (0.45–1.65)

Current smoker: 1.34 (1.06–1.69)

– Similar patterns for ischemic and 

hemorrhagic stroke

Limited power to detect associations because of 

few former smokers 

Pirie et al. 

(2013)a

•

•

•

•

•

•

Prospective cohort (Million Women’s Study)

1.2 million women; stopped smoking before 

55 years of age (at baseline); 28% former 

smokers, and free of prior cancer (other than 

nonmelanoma skin cancer), heart disease, 

stroke, and current respiratory disease 

treatment; 2,986 cases of cerebrovascular 

disease among never or current smokers

1996–2011

United Kingdom

Mean follow-up: 12 years

Outcome: cerebrovascular disease mortality

• Age (in years) quit smoking

–

–

–

–

–

Never smoker: 1.00 (referent)

<25: 0.9

25–34: 0.9

35–44: 1.1

45–54: 1.3d

Exact CIs not reported for these results;total 

cases of cerebrovascular disease not provided

PujadesRodriguez et al. 

(2015)

• Prospective cohort

• 1.93 million participants; ≥30 years of age; 

49% men, predominantly White (also South 

Asian and Black), and 16.2% former smokers 

(among those with smoking data); drawn from 

CALIBER program (linked electronic health 

records); no history of CVD; and 1,558 cases 

of ischemic stroke in former smokers

•

•

•

1997–2010

England

Median follow-up: 6 years

• Ischemic stroke by smoking status (ageadjusted):

–

–

–

–

Current smoker: 1.00 (referent)

Former smoker (<2 years): 0.62 (0.32–1.22)

Former smoker (2–9 years): 0.63 (0.45–0.87)

Former smoker (≥10 years): 0.51 (0.43–0.61)

• Reduced risk for longer time since cessation 

for outcomes of transient ischemic attack, 

subarachnoid hemorrhage, and intracerebral 

hemorrhag

See Table 4.17 for concerns about validity

Table 4.17 Continued

The Health Benefits of Smoking Cessation 247
Study Design/population Findings: RR (95% CI) Comments

Lindbohm et al. 

(2016)a

•

•

•

•

•

•

Prospective cohort (FINRISK Survey)

65,521 participants, 45 years of age (median), 

48% men, no prior subarachnoid hemorrhage 

at baseline, 492 cases of subarachnoid 

hemorrhage

1972–2011

Finland

Median follow-up: 21.1 years (full cohort) 

and 14.8 years (cases)

Outcome: subarachnoid hemorrhage

• Age quit smoking:

–

–

–

Never smoker: 1.00 (referent)

Recent quitter (<6 months): 1.93 (0.98–3.79)

Former smoker (quit for >6 months): 

1.34 (0.98–1.82)

– Current smoker (cigarettes per day):









1–10: 2.54 (1.90–3.40)

11–20: 2.82 (2.14–3.70)

21–30: 3.79 (2.51–5.71)

≥31: 3.91 (1.97–7.75)

—

Table 4.17 Continued

A Report of the Surgeon General

248 Chapter 4

Notes: CALIBER = Clinical research using LInked Bespoke studies and Electronic health Records; CI = confidence interval; FINRISK = a large Finnish population survey 

on risk factors on chronic, noncommunicable diseases; RR = risk ratio. aMeasure(s) of association adjusted for covariate(s).

bSmoking categories based on smoking status in 1990 exam and change from 1990 to 1992: non-reducing heavy smoker (≥20 cigarettes per day), moderate smoker 

(10–19 cigarettes per day), light smoker (<10 cigarettes per day), quitter from any smoking status, sustained ex-smoker, sustained never smoker. Results in reducers not 

shown in table.

cFormer smoking defined as having smoked ≥100 cigarettes, having smoked cigarettes regularly in the past, and not smoking currently.

dLower boundary of 95% CI >1.0 (CIs not provided).
The Health Benefits of Smoking Cessation 249

Smoking Cessation

researchers found a similar pattern of decreasing risk as 

time since cessation increased for ischemic stroke and 

SAH (Kawachi et  al. 1993). Elsewhere, in a case-control 

study, the adjusted odds of SAH due to ruptured intracranial aneurysm were higher among current cigarette 

smokers than former smokers (Kissela et al. 2002).

More recent research has produced similar findings, 

but associations have been less consistent for ICH than for 

SAH (Table  4.17). In the FINRISK study cohort (a large 

Finnish population survey on risk factors for chronic, noncommunicable diseases) (Lindbohm et  al. 2016), former 

smokers had a decreased risk of SAH compared with current smokers. In a nationwide, multicenter, case-control 

study in Korea (Kim et  al. 2012a), former smokers who 

had quit for 5 or more years had a lower adjusted risk of 

SAH than current smokers. This study also found a pattern 

of lower risk for former smokers with lower levels of prior 

smoking intensity. The study, however, may have been 

biased because of faulty recall of smoking history and selection of controls who were siblings, friends, or neighbors. 

Earlier, in a large cohort of Korean men, in a comparison 

with heavy smokers, former smokers who quit smoking 

2  years or less before the start of follow-up had a lower 

adjusted hazard of total stroke, ischemic stroke, and SAH 

(Song and Cho 2008). A similar pattern, although not statistically significant, was observed for hemorrhagic stroke. 

Compared with heavy smokers, former smokers who had 

stopped smoking for a longer period of time had lower 

adjusted hazards of all types of strokes. Elsewhere, in  a 

pooled analysis of the ARIC study and the Cardiovascular 

Health Study, there was no clear relationship between 

smoking status and ICH (not shown in tables) (Sturgeon 

et al. 2007). 

In a hospital-based case-control study comparing 

patients with ruptured aneurysms against controls with 

unruptured aneurysms, the adjusted odds of ruptured 

cerebral aneurysm were 1.26 (95% CI, 0.98–1.61) in current smokers versus former smokers (Can et  al. 2017). 

In that study, former smokers had higher adjusted odds 

of ruptured aneurysm than never smokers (OR  =  1.56; 

95% CI, 1.31–1.86). These findings are in line with those 

in the meta-analysis performed by Feigin and colleagues 

(2005) that compared SAH cases with healthy controls. 

In this analysis, current smokers had a two- to three-fold 

increase in risk of SAH compared with never smokers, 

and the risk was approximately twice as great in former 

smokers as it was in never smokers.

In the electronic health records-based CALIBER program (Table 4.17), the age-adjusted hazards of transient 

ischemic attack, ischemic stroke, SAH, and ICH gradually 

decreased with increased time since smoking cessation 

(Pujades-Rodriguez et al. 2015). After 10 years of cessation, former smokers tended to have the same hazard of 

these cerebrovascular-disease outcomes as never smokers 

(not shown in table). Note that the section on CHD in this 

chapter discussed concerns about the validity of this study.

In a multicenter, population-based prospective 

cohort study in China (Table 4.17), men who were former 

smokers had a higher risk of stroke than those who were 

never smokers (HR = 1.35; 95% CI, 1.00–1.81) (Tse et al. 

2012). Among women, there was no significant difference 

in this comparison (HR = 0.86; 95% CI, 0.45–1.65), but 

there were only 11  cases of stroke. Further, power was 

limited because of the low prevalence of former smokers.

Prognosis of Cerebrovascular Disease

Among four randomized controlled trials that 

assessed the rate of smoking cessation following cerebrovascular disease with follow-ups ranging from 6 months to 

3.5 years, the overall cessation rate was 23.9% (42 of 176) 

among those who received a smoking cessation intervention and 20.8% (37 of 178) for those who did not receive 

one (Edjoc et  al. 2012). Elsewhere, in a single study of 

110 patients with acute stroke, 40% had stopped smoking 

1  year after hospital admission; the best predictors of 

cessation were insular damage and a prestroke intention to stop (Suner-Soler et al. 2012). Finally, in a study 

of 198 patients, 21.7% gave up smoking within 6 months 

after their first stroke (Bak et al. 2002).

Among persons with cerebrovascular disease, findings from several studies suggest that former cigarette 

smokers have a lower risk of morbidity or mortality compared with those who continue to smoke after developing cerebrovascular disease. For example, in a literature review, Straus and colleagues (2002) estimated that 

smoking cessation would reduce the risk of a new stroke 

by 33% (95% CI, 29–38%) in survivors of stroke.

In a British study that followed 308 men and women 

with a history of stroke for an average of 7.5 years, current smokers had 2.27 times the adjusted risk of mortality 

(95% CI, 1.12–4.57) of never smokers, and former smokers 

had 1.46 times the risk (95% CI, 0.87–2.43) (Myint et al. 

2006). In an Australian cohort of 1,589 cases of first-ever 

and recurrent stroke, among those who survived 28 days 

after the index event, the adjusted hazard of death or a 

nonfatal vascular event was higher for current smokers 

than former smokers (HR = 1.23; 95% CI, 1.00–1.50) (Kim 

et  al. 2012b). In addition, former smokers had a higher 

adjusted hazard for such an outcome than never smokers 

(HR  =  1.18; 95%  CI, 1.01–1.39). Using data from the 

Registry of the Canadian Stroke Network, Edjoc and colleagues (2013) reported that, among patients with stroke, 

former smoking was associated with a reduced risk of the 

presenting stroke’s severity, of mortality at 30 days, and of 

a prolonged stay in the hospital when compared with current smoking; the results varied by stroke subtype.
A Report of the Surgeon General

250 Chapter 4

Summary of the Evidence

Building on evidence reviewed in previous Surgeon 

General’s reports, the additional studies reviewed in this 

report further strengthen the evidence that smoking 

cessation reduces the risk of stroke morbidity and mortality and that the risk of such outcomes decreases with 

increased time since cessation.

Smoking Cessation 

and Atrial Fibrillation

Atrial fibrillation (AF) is a condition in which the atria 

(upper chambers of the heart) beat irregularly. Earlier estimates of the prevalence of AF in the United States ranged 

from approximately 2.7 to 6.1 million persons (Go et al. 

2001; Miyasaka et al. 2006), but it is estimated that prevalence will increase to approximately 12.1 million in 2030 

(Colilla et al. 2013). AF is associated with an increased risk 

of mortality, including mortality attributable to CVD and 

non-CVD causes (Benjamin et al. 2017).

Zhu and colleagues (2016) found in a meta-analysis of 

16 prospective studies (286,217 patients and 11,878 cases 

of AF) that cigarette smoking was associated with a higher 

risk of AF (RR  =  1.23; 95%  CI, 1.08–1.39). Findings on 

AF related to current, former, and never smokers were 

available from 8 of the 16 studies. Former smokers had 

1.16  times the risk of AF (95%  CI, 1.00–1.36), and current smokers had 1.39 times the risk (95% CI, 1.11–1.36) 

compared with never smokers. Time since cessation was 

not assessed in any of the studies. Among persons with AF, 

smoking has also been associated with an increased risk 

of adverse events (Albertsen et al. 2014; Kwon et al. 2016). 

In the cohorts of the ARIC study and the Cardiovascular 

Health Study, current, but not former, smoking was associated with an increased risk of CVD deaths or ischemic 

stroke among persons with AF (Kwon et al. 2016). In the 

Danish Diet and Cancer study, former smoking was associated with an increased risk of thromboembolism or 

death among women with AF but not among men with AF 

(Albertsen et al. 2014).

Summary of the Evidence

A meta-analysis found that current and former 

cigarette smoking is associated with a higher risk of AF 

than never smoking, and the pooled estimate for former 

smokers was lower than that for current smokers. Findings 

from other studies regarding AF-related adverse events 

are mixed. No additional evidence is currently available 

on how the risk of AF changes with smoking cessation or 

with time since cessation.

Smoking Cessation and 

Sudden Cardiac Death

Cardiac arrest is the cessation of cardiac mechanical 

activity, as confirmed by the absence of signs of circulation 

(Jacobs et al. 2004). Although it is a leading cause of death, 

the absence of nationwide surveillance standards makes it 

difficult to understand the epidemiology of cardiac arrest 

in the United States (Benjamin et al. 2017). Sudden cardiac death (SCD) is an unexpected death without an 

obvious noncardiac cause that occurs, if witnessed, within 

1  hour of symptom onset or, if not witnessed, within 

24  hours of the person’s last being observed in normal 

health, although it is challenging to apply these criteria in 

practice (Benjamin et al. 2017). SCD can be attributable to 

cardiac or noncardiac causes; it is usually presumed to be 

attributable to cardiac causes unless another explanation 

can be identified. Based on the Resuscitation Outcomes 

Consortium registry of all emergency management system 

(EMS)-attended calls in 2015 for out-of-hospital cardiac 

arrests in eight U.S. and three Canadian regions, the incidence of out-of-hospital cardiac arrests assessed by EMS 

was estimated to be 110.8 persons per 100,000 (95% CI, 

108.9–112.6) (Benjamin et al. 2019). Based on this registry, 

the rate of survival to hospital discharge for EMS-treated 

out-of-hospital cardiac arrest was 11.4% (95%  CI, 10.4–

12.4%) in adults, and survival after bystander-witnessed 

ventricular fibrillation was 37.4% (95%  CI, 32.7–42.0%) 

for patients of any age (Benjamin et al. 2017).

The 2014 Surgeon General’s report reviewed epidemiologic evidence from several studies showing that 

cigarette smoking is associated with SCD of all types. 

During 30 years of follow-up of 101,018 women without 

known CHD, stroke, or cancer at the 1980 baseline in 

the Nurses’ Health Study, there were 351  SCD events, 

of which 148  occurred in former smokers (Sandhu 

et  al. 2012). Overall, compared with never smokers, 

the adjusted hazard of SCD was higher among current 

smokers (HR  =  2.44; 95%  CI, 1.80–3.31) and former 

smokers (HR = 1.40; 95% CI, 1.10–1.79). Compared with 

current cigarette smokers, former smokers had a lower 

risk of SCD (HR = 0.58; 95% CI, 0.43–0.77). The risk of 

SCD decreased linearly over time after quitting smoking 

(p for trend <0.0001). After 15 years of cessation, the risk 

was significantly lower in former smokers than in current 

smokers; after 20 years of cessation, the risk was similar 

in former smokers and never smokers. In analyses stratified by CHD status, women with CHD who quit smoking 

tended to have a higher risk of SCD than never smokers, 

while increased risk of SCD dropped within 5 years and did 

not decline further among those who quit and did not have 

CHD (p-value interaction = 0.15). Among women who quit, 
The Health Benefits of Smoking Cessation 251

Smoking Cessation

those without CHD had a more rapid reduction in SCD 

risk than those with CHD (p-value interaction = 0.03). 

Similar findings have been observed among populations with known CHD (Vlietstra et al. 1986; Peters et al. 

1995; Goldenberg et al. 2003) or with prior cardiac arrest 

(Hallstrom et al. 1986). For example, among 3,122 patients 

with previous MI or stable angina, smoking was associated with an increased risk of SCD, and those who quit 

smoking had a decreased risk of SCD (Goldenberg et al. 

2003). Compared with never smokers (43 cases of SCD), 

current smokers had 2.47  times (95%  CI, 1.46–4.49, 

30 cases) the adjusted risk of SCD, while former smokers 

did not have an elevated adjusted risk (HR = 1.06; 95% CI, 

0.70–1.62, 83 cases). 

In a study of data from the CALIBER program in 

England, which uses electronic health records, there was 

no pattern of decreased age-adjusted risk of cardiac arrest 

or SCD with increasing time since smoking cessation 

(not shown) (Pujades-Rodriguez et al. 2015). In this study, 

however, current smoking also was not associated with 

increased hazard of this outcome compared with never 

smoking; the section on CHD discusses concerns about 

the validity of this study. 

Summary of the Evidence

Several studies show that smoking cessation is associated with a reduced risk of SCD. The majority of these 

studies were carried out among patients with prior CHD. 

A large study in women found a similar association; however, among those with and without CHD, results show 

a quicker benefit from smoking cessation among those 

without known CHD. In this study, the risk of SCD 

returned to that of never smokers after approximately 

20 years of cessation.

Smoking Cessation 

and Heart Failure

Heart failure results from the inability of the heart 

to pump sufficient blood and deliver enough oxygen to 

support other organs in the body. An estimated 6.5 million U.S. adults have heart failure (Benjamin et al. 2017); 

in 2014, heart failure was mentioned on the death certificate for one in every eight deaths (Benjamin et al. 2017; 

National Center for Health Statistics 2017). Approximately 

half of those with heart failure die within 5 years of diagnosis (Roger et al. 2004; Benjamin et al. 2017). In 2012, 

heart failure cost the United States an estimated $30.7 billion in direct and indirect costs; this figure is projected to 

increase to $69.8 billion by 2030 (Heidenreich et al. 2013). 

The prevalence of heart failure is projected to increase to 

approximately 46% by 2030; thus, more than 8  million 

persons 18 years of age or older are expected to have heart 

failure in that year (Heidenreich et al. 2013).

The 1990 Surgeon General’s report did not address 

smoking cessation and risk for heart failure. The 2004 

Surgeon General’s report suggested that CHD caused by 

smoking may contribute to heart failure and that this 

contribution is likely mediated by CHD (USDHHS 2004). 

Regardless, the pathophysiologic mechanisms underlying 

the development of heart failure overlap with the effects of 

cigarette smoking on the cardiovascular system (Suskin 

et al. 2001). This section briefly reviews the literature on 

smoking cessation and the development and prognosis of 

heart failure.

Ahmed and colleagues (2015) reported on the relationships in the Cardiovascular Health Study between 

prolonged smoking cessation (>15 years) and risk of heart 

failure and death among 4,482 adults 65 years of age or 

older who were free of heart failure at baseline. During 

the 13-year follow-up, former smokers had risks for incident heart failure (adjusted HR = 0.99; 95% CI, 0.85–1.16) 

and all-cause mortality (adjusted HR  =  1.08; 95%  CI, 

0.96–1.20) that were similar to those of never smokers 

(Table 4.18). In another cohort study of older adults, both 

current and former smokers had elevated risk of heart 

failure compared with the risk among never smokers 

(Table 4.18) (Gopal et al. 2012). 

In the Cardiovascular Health Study, compared 

with never smokers, former heavy smokers (≥32  packyears) had a higher risk of heart failure (multivariableadjusted HR  =  1.31; 95%  CI, 1.03–1.65) and mortality 

(multivariable-adjusted HR = 1.26; 95% CI, 1.06–1.49 [not 

shown in table]) (Ahmed et al. 2015). Compared with current smokers, however, former heavy smokers had a lower 

risk of mortality (age-, sex-, and race-adjusted HR = 0.64; 

95% CI, 0.53–0.77) but not of heart failure (age-, sex-, and 

race-adjusted HR = 0.97; 95% CI, 0.74–1.28). Overall, this 

study found that after prolonged smoking cessation the 

risk of heart failure was similar between former smokers 

and never smokers, but not for former heavy smokers with 

cumulative consumption of 32 or more pack-years.

In the CALIBER program in England, the ageadjusted HR for heart failure decreased with increased 

time since smoking cessation (Table  4.18); 2  years after 

cessation, the age-adjusted hazard of heart failure was 

not elevated compared with never smokers (not shown 

in table) (Pujades-Rodriguez et  al. 2015). In a study of 

267,010 Australian men and women 45 years of age or older 

with self-reported smoking status that had been linked to 

administrative hospital data, former smokers and current smokers had a higher adjusted hazard of heart failure 

hospitalization compared with never smokers (Tran et al. 

2015). Risks of hospitalization for heart failure decreased 
Study Design/population Findings: RR (95% CI) Comments

Suskin et al. 

(2001)a

•

•

•

•

•

•

Prospective cohorts (observational analyses 

of two multicenter trials included in the Study 

of Left Ventricular Dysfunction Prevention 

and Intervention)

6,704 participants with left ventricular 

ejection fraction <35% but no history of overt 

congestive heart failure, mean 60 years of 

age, 86% men, predominantly White but also 

African American and other races/ethnicities, 

55% former smokers

Years of data collection: not provided

Belgium, Canada, and United States

Mean follow-up: 41 months (treatment trial) 

and 37 months (prevention trial)

Main outcome: total mortality

• Total mortality:

–

–

–

–

Never smoker: 1.00 (referent)

Former smoker (quit ≤2 years): 1.10 

(0.94–1.29)

Former smoker (quit >2 years): 0.95 

(0.82–1.09)

Current smoker: 1.40 (1.21–1.63)

• Similar results for mortality from congestive 

heart failure, hospitalization for congestive 

heart failure, hospitalization for MI, and 

mortality or hospitalization because of 

congestive heart failure or MI

—

Shah et al. 

(2010)a

•

•

•

•

•

•

Prospective cohort (observational analyses of 

Survival and Ventricular Enlargement trial)

924 patients with left ventricular dysfunction 

3–16 days after MI, restricted to smokers at 

baseline who survived to 6 months without 

interim event, 82% men, 54 years of age 

(mean), 63% quit smoking, 85 deaths

Years of data collection: not provided

United States

Median follow-up: 42 months

Main outcome: death

• Total mortality:

–

–

Current smoker: 1.00 (referent)

Former smoker (months of 

consistent cessationb):









6: 0.57 (0.36–0.91)

12: 0.58 (0.33–0.99)

16: 0.60 (0.34–1.07)

24: 0.53 (0.25–1.08)

• Similar results for outcomes of death or 

recurrent MI and death or hospitalization 

for heart failure

• Similar trend of decreased risk at 6 months 

of cessation for endpoint of death or recurrent 

MI, hospitalization for heart failure, or stroke

—

Table 4.18 Observational studies on smoking cessation and heart failure (incident heart failure and heart failure-related complications)

A Report of the Surgeon General

252 Chapter 4
Study Design/population Findings: RR (95% CI) Comments

Gopal et al. 

(2012)a

•

•

Prospective cohort (Health, Aging, and Body 

Composition Study)

2,125 participants, 70–79 years of age (mean:

73.6 years), 30% men, Whites and African 

Americans, 35% former smokers, all Medicare 

beneficiaries and without prevalent heart

failure, 231 cases of heart failure

•

•

•

•

Recruited in 1997–1998

United States

Median follow-up: 9.4 years

Outcome: heart failure

• Smoking status:

–

–

–

Never smoker: 1.00 (referent)

Former smoker (overall): 1.31 (0.98–1.75)

Current smoker (overall): 1.73 (1.15–2.59)

• Smoking intensity (number of pack-yearsc):

–

–

Never smoker: 1.00 (referent)

Former smoker:







1–11: 1.05 (0.64–1.72)

12–35: 1.23 (0.82–1.83)

>35: 1.64 (1.11–2.42)

– Current smoker:







1–11: 1.92 (0.76–4.88)

12–35: 1.67 (0.89–3.15)

>35: 1.71 (0.97–3.01)

—

Ahmed et al. 

(2015)a

•

•

•

•

•

•

Prospective cohort (Cardiovascular 

Health Study)

4,482 participants, ≥65 years of age, 40% men, 

multiple races/ethnicities (Whites, African 

Americans, others), 29% former smokers who 

quit >15 years earlier without prevalent heart 

failure, 1,204 cases of heart failure

1989–1993 (baseline)

United States (four counties)

Follow-up: 13 years

Main outcome: heart failure

• Former smokers restricted to those who had 

quit >15 years

• Smoking status:

–

–

–

Never smoker: 1.00 (referent)

Former smoker (overall): 1.07 (0.91–1.25)

Current smoker (overall): 1.19 (0.99–1.44)

• Smoking intensity (number of pack-yearsc):

–

–

Never smoker: 1.00 (referent)

Former smoker:









<8: 1.06 (0.83–1.36)

8–15: 0.86 (0.62–1.20)

16–31: 0.99 (0.77–1.28)

≥32: 1.31 (1.03–1.65)

• Similar results for outcome of mortality, 

but stronger association for current smokers:

– 2.17 (1.91–2.47)

—

Table 4.18 Continued

The Health Benefits of Smoking Cessation 253
Study Design/population Findings: RR (95% CI) Comments

PujadesRodriguez et al. 

(2015)a

•

•

•

•

•

Prospective cohort

1.93 million participants; ≥30 years of age; 

49% men, predominantly White (also South 

AsianandBlack), and 16.2%former smokers 

(amongthosewithsmokingdata);drawnfrom 

CALIBER program (linked electronic health 

records); no history of CVD; 4,097 cases of 

heart failure in former smokers

1997–2010

England

Median follow-up: 6 years

• Heart failure by smoking status (age-adjusted):

–

–

Current smoker: 1.00 (referent)

Former smoker (years since quitting):







<2: 0.87 (0.60–1.26)

2–9: 0.72 (0.52–0.99)

>10: 0.60 (0.44–0.81)

See Table 4.17 for concerns about validity

Table 4.18 Continued

A Report of the Surgeon General

254 Chapter 4

Notes: CALIBER = Clinical research using LInked Bespoke studies and Electronic health Records; CI = confidence interval; CVD = cardiovascular disease; MI = myocardial 

infarction; RR = risk ratio.

aMeasure(s) of association adjusted for covariate(s).

bDuration of consistent smoking cessation after MI, compared with continuation of smoking, among those who were stable baseline smokers and survived up to that time 

without recurrent MI or hospitalization for heart failure.

cPack-years = number of packs of cigarettes smoked per day multiplied by the number of years smoked cigarettes.
The Health Benefits of Smoking Cessation 255

Smoking Cessation

with increased time since quitting; the decrease was substantially different between current and former smokers 

after 25 or more years of cessation.

In their analyses of data from 4,850 elderly participants free of overt CHD, heart failure, and significant valvular disease in the ARIC study, Nadruz and colleagues 

(2016) found that, after adjusting for potential confounders, current smokers had a greater left-ventricular 

mass index and left-ventricular mass/volume ratio, a 

higher prevalence of left-ventricular hypertrophy, and 

worse diastolic function than never smokers. In contrast, 

former smokers showed echocardiographic features similar to those of never smokers.

Other researchers have assessed the relationship 

between smoking cessation and elevated risk of complications related to heart failure and found associations 

between cessation and decreased risk of hospitalization for 

or mortality from heart failure and other adverse events. 

For example, the prevention and intervention trials of the 

Study of Left Ventricular Dysfunction studied 6,704 persons with a left ventricular ejection fraction <0.35 with or 

without symptoms of congestive heart failure. Compared 

with never smokers (Table 4.18), former smokers had no 

difference in adjusted risk of overall mortality, mortality 

from congestive heart failure, hospitalization for congestive heart failure, hospitalization for MI, or risk of mortality or hospitalization due to congestive heart failure or 

MI (Suskin et al. 2001). Risks were similar in those who 

had stopped smoking for 2 or fewer years and those who 

had quit more than 2 years earlier. In contrast, continued 

smoking was associated with higher risk of overall mortality, hospitalization for congestive heart failure, hospitalization for MI, and mortality or hospitalization due 

to congestive heart failure or MI. Suskin and colleagues 

(2001) concluded that smoking cessation was associated 

with a rapid decrease in risk of morbidity and mortality 

among these participants. The reduction in mortality was 

similar in magnitude to the decrease from (a) the appropriate use of an angiotensin-converting enzyme inhibitor 

or beta-adrenergic blocking agents, or (b) all commonly 

used treatments of spironolactone among patients with 

reduced left ventricular systolic function and symptoms 

of congestive heart failure.

In the Survival and Ventricular Enlargement trial 

involving patients with left ventricular dysfunction after 

MI, 924  participants were stable smokers at baseline. 

Among those who survived to 6 months without a recurrent event, those who had quit for 6 months had a lower risk 

of death than those who continued to smoke (Table 4.18) 

(Shah et al. 2010). Similar patterns were observed during 

follow-up at 12, 16, and 24 months and for composite endpoints (death or hospitalization for heart failure; death or 

recurrent MI). At 6 months of cessation after an MI, there 

was a similar trend toward lower risk for the combined 

endpoint of death, MI, hospitalization for heart failure, or 

stroke (adjusted HR = 0.72; 95% CI, 0.52–1.01). Earlier, 

in a cohort of 4,024  patients receiving dialysis, the rate 

of new-onset congestive heart failure (based on hospital 

claims data) was similar in former smokers and never 

smokers (Foley et  al. 2003). These findings indicate the 

importance of smoking cessation among persons who are 

at elevated risk for complications related to heart failure 

(Suskin et al. 2001; Shah et al. 2010).

Summary of the Evidence

There is limited evidence that smoking cessation is 

associated with a reduced risk of incident heart failure and 

adverse events related to heart failure. 

Smoking Cessation and 

Venous Thromboembolism

The term “venous thromboembolism” (VTE) refers 

to a blood clot that forms in a vein; an embolism occurs 

when the clot breaks free. The incidence of VTE in the 

United States has been estimated to be approximately 

300,000 to 600,000 per year (Silverstein et al. 1998; White 

et al. 2005; Spencer et al. 2006), but these estimates are 

based on older data (Benjamin et al. 2017). A systematic 

review and meta-analysis (covering 1980–2013) found 

that, compared with never smoking, current smoking 

(RR  =  1.23; 95%  CI, 1.14–1.33; 15  studies) and former 

smoking (RR = 1.10; 95% CI, 1.03–1.17; 14 studies) are 

associated with an increased risk of incident VTE (Cheng 

et  al. 2013). This study did not evaluate the association 

between time since smoking cessation and risk of VTE. 

Summary of the Evidence

A meta-analysis showed that current and former cigarette smokers have an increased risk of VTE when compared with never smokers, and the RR for former smokers 

is lower than that for current smokers. There is no evidence available on how the risk of VTE changes with time 

since cessation. 

Smoking Cessation and LowerExtremity Peripheral Artery Disease

Peripheral artery disease (PAD) results from the narrowing (usually due to atherosclerosis) of the peripheral 

arteries leading to the legs, abdominal organs, arms, and 

head. This disorder most commonly affects the arteries 
A Report of the Surgeon General

256 Chapter 4

of the legs. The presence of PAD of the lower limbs can 

be detected by measuring the ABI, which is the ratio of 

blood pressure in the lower leg to that in the upper arm 

(as discussed in the earlier section on smoking cessation and subclinical atherosclerosis). Importantly, a low 

ABI does not indicate which blood vessels are narrowed 

or blocked. Approximately 8.5 million people in the U.S. 

have PAD (CDC 2016a). One symptom of PAD is intermittent claudication, or leg cramping induced by exercise (also known as classic claudication). An estimated 

10% of persons with PAD have intermittent claudication, 

approximately 40% have no leg pain, and 50% have other 

leg symptoms (Hirsch et al. 2001; Benjamin et al. 2017). 

PAD leads to impaired function and reduces quality of 

life. Further, PAD is a systemic atherosclerotic disease, 

and is therefore a risk factor for poor clinical outcomes, 

including CHD and stroke (Heald et al. 2006; Benjamin 

et al. 2017).

The 1983 Surgeon General’s report concluded that 

cigarette smoking is the most powerful risk factor predisposing men and women to atherosclerotic peripheral 

vascular disease (USDHHS 1983). According to the 2004 

Surgeon General’s report, the evidence is sufficient to infer 

a causal relationship between smoking and atherosclerosis (USDHHS 2004), as discussed earlier in this section. 

The 2004 Surgeon General’s report concluded that “the 

new findings on subclinical disease indicate the potential 

for preventing more advanced and clinically symptomatic 

disease through quitting smoking and maintained cessation” (USDHHS 2004, p. 379).

The 1990 Surgeon General’s report discussed 

results from two small studies comparing the risk of 

PAD between smokers and former smokers, finding that 

former smokers had a 50–58% lower risk of PAD than current smokers (Hughson et al. 1978; Jacobsen et al. 1984). 

Several studies of persons with PAD found that those who 

quit smoking had improved performance and overall survival. Since 1990, the literature on this topic has grown 

substantially, as reviewed in the next two sections. 

A meta-analysis conducted by Lu and colleagues 

(2014) quantified the association between active smoking 

and PAD. This meta-analysis, which was restricted to 

studies examining the risk of developing PAD, defined PAD 

on the basis of an ABI ≤0.90, a claudication questionnaire, 

or peripheral angiography. Although the risk of PAD was 

lower for former smokers than for current smokers, the 

risk of PAD in both groups was still significantly higher 

than that for never smokers. Compared with nonsmokers, 

current smokers had 2.71 times the pooled odds of PAD 

(95% CI, 2.28–3.21). As shown in Figure 4.3, there were 

40 estimates in this meta-analysis (Lu et al. 2014) of the 

risk of PAD gathered from 29 studies of former smokers 

compared with never smokers. Of the 40  estimates, 

29 (72.5%) were statistically significant, and the pooled OR 

comparing former with never smokers was 1.67 (95% CI, 

1.54–1.81). This estimate included studies of the general 

population, as well as studies of persons with underlying 

diseases, such as diabetes mellitus.

Lu and colleagues (2014) identified two studies 

(Törnwall et al. 2000; Cui et al. 2006) that compared risk 

of PAD between former and current smokers and found a 

reduced risk of PAD among former smokers. In the Finnish 

Alpha-Tocopherol, Beta-Carotene Cancer Prevention 

Study, among a cohort of 26,872 male smokers who were 

50–69 years of age at entry, the HR of PAD during a median 

follow-up of 4 years in former smokers was 0.86 (95% CI, 

0.75–0.99) compared with the HR among current smokers 

(Törnwall et al. 2000). As this study did not include never 

smokers, its results were not included in the pooled estimate reported by Lu and colleagues (2014). In the report 

by Cui and colleagues (2006) on a cross-sectional study 

of 1,215 elderly Japanese men, those authors found that, 

compared with current smokers, there was no significant 

difference in the odds of PAD (ABI <0.90) after less than 

10 years of smoking cessation (OR = 0.8; 95% CI, 0.4–1.8) 

or after 10–19 years of cessation (OR = 1.0; 95% CI, 0.4–

2.2) (Cui et al. 2006). The risk of PAD was reduced, however, among those who had quit smoking for 20 or more 

years (OR = 0.3; 95% CI, 0.1–0.9).

The meta-analysis by Lu and colleagues (2014) 

focused on publications that reported ORs or RRs, and it 

treated RRs as ORs. Several other key articles on this topic 

that were not included in the meta-analysis—because of a 

restriction or publication after the literature search or for 

another reason—are described below.

Fowkes and colleagues (1992) reported that lifetime 

cumulative cigarette smoking was strongly related to risk 

of PAD, with additional risks among current and former 

smokers abstinent less than 5 years. Elsewhere, in a cohort 

of Icelandic men, when compared with never smoking, 

former smoking was associated with having 3.5 times the 

odds of prevalent intermittent claudication and 2.3 times 

the odds of incident intermittent claudication during 

follow-up from 1968 to 1986; neither of these ORs was 

significant (Ingolfsson et al. 1994). Among smokers, those 

who smoked 15 or more cigarettes per day had a higher 

risk of incident intermittent claudication. In a later study, 

Foley and colleagues (2003) reported that in a cohort of 

4,024 patients receiving dialysis, former smokers had an 

adjusted rate of peripheral vascular disease similar to that 

of lifelong nonsmokers. In a prospective cohort study 

of 39,825  initially healthy women from the Women’s 

Health Study, Conen and colleagues (2011) reported that 

smoking cessation substantially reduced the risk of symptomatic PAD, but former smokers still had an excess risk 

of PAD compared with never smokers. Compared with 
The Health Benefits o

Figure 4.3 Comparison of risk of peripheral arterial disease between former and never smokers

Study Estimate (95% CI) Weight (%)aGeneral population

Skalkidis et al. 1989 (MF) 2.30 (0.40–15.20) 0.19Bowlin et al. 1994 (M) 1.43 (1.05–1.95) 3.37Leng et al. 1995 (MF) 2.15 (1.21–3.82) 1.53Ögren et al. 1996 (M) 3.10 (1.40–6.90) 0.90Hooi et al. 1998 (asymptomatic) (MF) 1.60 (1.10–2.40) 2.62Hooi et al. 1998 (symptomatic) (MF) 2.70 (1.40–5.40) 1.19Meijer et al. 2000 (MF) 1.15 (0.75–1.78) 2.30Passos et al. 2001 (MF) 3.10 (1.20–8.50) 0.62Fowler et al. 2002a (M) 2.10 (1.60–2.60) 4.16Jensen et al. 2005 (F) 1.70 (1.10–2.70) 2.19Jensen et al. 2005 (M) 1.70 (0.90–3.20) 1.31Zheng et al. 2005 (African M) 6.60 (2.00–21.50) 0.44Zheng et al. 2005 (African F) 2.30 (1.50–3.50) 2.36Zheng et al. 2005 (White M) 10.40 (3.80–28.30) 0.59Zheng et al. 2005 (White F) 1.90 (1.40–2.60) 3.37Kennedy et al. 2005 (MF) 1.32 (0.94–1.87) 3.02He et al. 2006 (stop 2–9 years) (M) 1.74 (1.01–2.98) 1.68He et al. 2006 (stop ≥10 years) (M) 1.18 (0.68–2.03) 1.65He et al. 2006 (stop 2–9 years) (F) 1.27 (0.59–2.73) 0.96He et al. 2006 (stop ≥10 years) (F) 0.93 (0.37–2.31) 0.70Woo et al. 2006 (MF) 2.00 (1.18–3.38) 1.75Bendermacher et al. 2007 (MF) 1.40 (1.20–1.60) 5.48Agarwal et al. 2009 (MF) 1.55 (1.16–2.08) 3.57Cacoub et al. 2009 (>1 year) (MF) 1.38 (1.15–1.66) 4.95Cacoub et al. 2009 (≤1 year) (MF) 2.48 (1.79–3.42) 3.22Kröger et al. 2009 (MF) 1.99 (1.44–2.75) 3.23Alzamora et al. 2010 (MF) 2.19 (1.34–3.58) 1.93Lakshmanan et al. 2010 (M) 2.03 (1.39–2.98) 2.69St-Pierre et al. 2010 (M) 1.14 (0.59–2.21) 1.23Aboyans et al. 2011 (MF) 1.39 (0.97–1.97) 2.93Lee et al. 2011 (M) 2.31 (1.20–4.42) 1.26Subtotal (I-squared = 52.3%, p = 0.000) 1.76 (1.58–1.97) 67.40
A Report of the Surgeon General

258 Chapter 4

Study Estimate (95% CI) Weight (%)aDisease study population

Adler et al. 2002 (DM) (MF) 0.80 (0.37–1.72) 0.95O'Hare et al. 2002 (hemodialysis) (wave 3, 4) (MF) 1.27 (1.13–1.42) 5.85O'Hare et al. 2002 (hemodialysis) (wave 1) (MF) 1.55 (1.31–1.83) 5.17Rajagopalan et al. 2006 (<1 year) (hemodialysis) (MF) 1.68 (1.41–2.01) 5.03Rajagopalan et al. 2006 (>1 year) (hemodialysis) (MF) 1.51 (1.38–1.65) 6.13Norman et al. 2006 (DM) (MF) 1.16 (0.62–2.15) 1.36Li et al. 2007 (DM) (MF) 1.79 (1.30–2.46) 3.27Luo et al. 2007 (HT) (MF) 1.79 (1.40–2.29) 4.10Tavintharan et al. 2009 (DM) (MF) 2.55 (1.05–6.20) 0.74Subtotal (I-squared = 54.0%, p = 0.026) 1.52 (1.36–1.69) 32.60

Overall (I-squared = 54.7%, p = 0.000) 1.67 (1.54–1.81) 100.00

Source: Lu et al. (2014), with permission.Note: CI = confidence interval; DM = diabetes mellitus; F = females; HT = hypertension; M = males; MF = males and females.

aWeights are from random effects analysis.Figure 4.3 Continued
The Health Benefits of Smoking Cessation 259

Smoking Cessation

current smokers, the adjusted HR of symptomatic PAD 

among former smokers was 0.39 (95% CI, 0.24–0.66) for 

less than 10 years of cessation, 0.28 (95% CI, 0.17–0.46) 

for 10–20 years of cessation, and 0.16 (0.10–0.26) for more 

than 20 years of cessation. Compared with never smokers, 

the adjusted HR of symptomatic PAD among former 

smokers was 3.16 (95% CI, 2.04–4.89).

In the CALIBER program, the age-adjusted HR of 

PAD decreased substantially with increased time since 

smoking cessation (Pujades-Rodriguez et  al. 2015). 

Compared with current smokers, former smokers who had 

quit for more than 10 years had an age-adjusted HR for 

PAD of 0.27 (95% CI, 0.22–0.33). Compared with women 

who had never smoked, however, the age-adjusted hazard 

of PAD was still elevated significantly in women who had 

quit smoking for 10 or more years (HR = 1.36; 95% CI, 

1.11–1.67). 

Smoking has also been associated with other forms 

of PAD, such as Raynaud’s disease or syndrome, which is 

a form of functional PAD that begins with severe vasoconstriction followed by dilatation (widening of the blood vessels) not due to blockage. Various studies have associated 

current smoking with Raynaud’s, with a stronger association evident in men than in women. In the Framingham 

Offspring cohort, former smokers did not have an elevated risk of Raynaud’s compared with never smokers 

(Brand et al. 1997; Suter et al. 2007). Smoking cessation 

is recommended for persons with Raynaud’s, because the 

vasoconstrictive substances in cigarettes likely make the 

condition worse (Pope 2007). The IARC’s (2007) review 

on smoking cessation found consistent evidence from a 

number of small case series that smoking cessation was 

associated with improved thromboangiitis obliterans 

(Buerger’s disease), which is an inflammatory, obliterative 

disease that affects small- and medium-sized arteries, is 

unrelated to atherosclerosis, and is specific to smokers. 

Later, Klein-Weigel and colleagues (2016) concluded that 

smoking cessation is the most important intervention 

among patients with Buerger’s disease.

Prognosis of PAD

In addition to its association with the onset of PAD, 

smoking or the continuation of smoking after a PAD diagnosis is a major risk factor for the progression of PAD and 

PAD-related outcomes (Jonason and Ringqvist 1985; Ameli 

et al. 1989; Wiseman et al. 1989; Selvarajah et al. 2014). 

Correspondingly, current clinical guidelines recommend 

smoking cessation among patients with PAD (Olin et al. 

2010; Rooke et al. 2011; Smith Jr et al. 2011; Tendera et al. 

2011; Gerhard-Herman et al. 2017).

A systematic review that assessed the effects of clinical interventions for persons with chronic PAD (based 

on literature searched through 2005) concluded that 

smoking cessation combined with exercise may increase 

walking distance (Cassar and Bachoo 2006). This conclusion was based on a randomized controlled study 

that assessed the impact of a “stop smoking and keep 

walking” intervention compared with usual care among 

882 Australian men 65–79 years of age who had early PAD 

(Fowler et al. 2002b). Specifically, the intervention combined a community-based intervention of smoking cessation (where applicable) with increased physical activity. 

At 12 months, a higher proportion of men in the intervention group had an improved maximum walking distance 

compared with those in the usual-care group (23%  vs. 

15%, p  =  0.008). In addition, compared with the control group, more men in the intervention group reported 

walking more than three times per week for recreation 

(34% vs. 25%, p = 0.01). Also, although the finding was 

not statistically significant, more men in the intervention 

group had stopped smoking (12% vs. 8%, p = 0.43).

A systematic review of smoking cessation and prognosis for PAD based on a 1996 search (Girolami et  al. 

1999) summarized some of the findings reported in the 

1990 Surgeon General’s report (USDHHS 1990). Most of 

the findings showed that smoking cessation was associated with favorable outcomes. A study of 415 smokers with 

intermittent claudication and an ABI <0.9, however, found 

no difference in deterioration of the ABI at 1 year between 

current smokers and former smokers (Smith et al. 1996). 

Of note, this analysis adjusted only for diabetes status; 

former smokers were more likely than current smokers 

to have diabetes.

In a registry of 467 stable outpatients who smoked 

and had symptomatic PAD, those who quit smoking had, 

during a mean follow-up of 14  months, a nonadjusted 

relative risk of death of 1.83 (95%  CI, 0.65–5.15) compared with continuing smokers (Álvarez et al. 2013). This 

study was limited by the small number of events, however, making it challenging to draw conclusions. In an 

earlier study, among 138  patients with peripheral arterial occlusive disease, a subgroup of 38 patients who had 

smoked an average of 1.5 packs of cigarettes per day for 

more than 42  years had more severe claudication pain, 

lower oxygen uptake at peak exercise, and a higher oximeter electrode power than a subgroup of 100 patients who 

had quit smoking for an average of 7 years (Gardner 1996). 

Results were similar after adjusting for baseline ABI. In 

a later study of 204 patients with claudication or critical 

limb ischemia who had undergone lower-extremity angiography, smoking cessation was associated with a lower 

5-year adjusted HR of mortality (HR = 0.33; 95% CI, 0.13–

0.80) and improved amputation-free survival (HR = 0.40;

95% CI, 0.19–0.83) compared with those who continued

to smoke (Armstrong et  al. 2014). Nonsignificant HRs

were observed in this study for MI, stroke, and major
A Report of the Surgeon General

260 Chapter 4

amputation (there were few cases of these outcomes); a 

nonsignificant HR in the opposite direction was observed 

for major adverse limb events.

Summary of the Evidence

There is evidence that former cigarette smokers 

have a lower risk of incident PAD than current smokers 

and that the risk of PAD decreases with increased time 

since smoking cessation. Compared with never smokers, 

former smokers typically have an increased risk of PAD. 

Despite few large prospective cohort studies assessing 

these associations, evidence suggests that smoking cessation is associated with improved prognosis among persons 

with PAD.

Smoking Cessation and 

Abdominal Aortic Aneurysm

An aortic aneurysm is a ballooning or bulging area 

on the aorta wall, which can lead to rupture or dissection (a split between the layers of the wall of the aorta, 

thus trapping blood) (American Heart Association 2017). 

The prevalence of abdominal aortic aneurysms (AAAs) 

extending 2.9–4.9 centimeters (cm) among men has been 

estimated to be 1.3% in those 45–54  years of age and 

12.5% in those 75–85 years of age; the prevalence among 

women has been estimated at 0% (45–54  years of age) 

and 5.2% (75–85 years of age) (Hirsch et al. 2006). These 

estimates, however, came predominantly from cohorts of 

White men and women. Ruptures in patients with AAA are 

more common in current smokers (a doubling of risk) 

and among women (almost four times the risk) (Sweeting 

et al. 2012). 

According to the 2004 Surgeon General’s report, 

the evidence is sufficient to infer a causal relationship 

between smoking and AAA (USDHHS 2004). That report 

stated that “smoking is one of the few currently avoidable 

causes of this frequently fatal disease” (p. 397). According 

to the 1990 Surgeon General’s report (USDHHS 1990), 

former smokers have a reduced risk of death from aortic 

aneurysm compared with current smokers, but the report 

noted that more detailed analyses by duration of smoking 

abstinence are needed. The 1990 report did not provide 

any formal conclusions about smoking cessation and AAA.

The 1990 report discussed results from five prospective cohort studies that compared risk of death from AAA 

between former smokers and current smokers. Overall, 

in men there was a consistent pattern of a reduced risk 

of death from AAA among former smokers compared with 

current smokers. At the time, evidence was more limited 

in women. Since publication of the 1990 report, many 

additional studies have been published on this topic, as 

summarized below and in Table 4.19.

In 1999, a literature review concluded that smoking 

was strongly associated with AAA (Blanchard 1999). Some 

of the studies in this review examined associations with this 

outcome between former smokers and never smokers. For 

example, during 40 years of follow-up of the British Doctors’ 

Study, the rate of death from non-syphilitic AAA (standardized for age and calendar period) was more than four times 

as high among current smokers and more than twice as 

high among former smokers as among never smokers 

(CIs not provided) (Doll et al. 1994). In the Cardiovascular 

Health Study of older Americans, the prevalence of AAA 

was 6.8% for never smokers, 11.5%  for former smokers, 

and 14.4% for current smokers (Alcorn et al. 1996).

Several observational studies published in 1997 or 

later have assessed the relationship between smoking cessation and the incidence or prevalence of AAA. Overall, the 

evidence suggests that smoking cessation is associated 

with a decreased risk of AAA (Lederle et  al. 1997, 2000, 

2003; Wilmink et al. 1999; Singh et al. 2001; Wong et al. 

2007; Forsdahl et al. 2009; Kent et al. 2010; Stackelberg 

et  al. 2014; Tang et  al. 2016). Even so, compared with 

never smokers, former smokers tend to have an increased 

risk of AAA that can persist for decades after quitting 

(Wong et al. 2007).

Findings from observational studies on cessation and 

AAA are summarized in Table  4.19. For example, in two 

cohorts of veterans undergoing screening in the Aneurysm 

Detection and Management study, the OR for AAA (diameter 

≥4.0 cm) among former smokers compared with current 

smokers was 0.73 (95% CI, 0.66–0.82) for every 10 years 

of smoking cessation (Lederle et al. 1997, 2000). In addition, after accounting for number of years smoked, risk of 

AAA was higher in current smokers than in former smokers 

(Table 4.19). In a later study, in a large cohort of patients who 

underwent ultrasound screening for AAA, former smokers 

had a lower prevalence of AAA than current smokers, and 

risk decreased as duration of cessation increased from 

less than 5 years to more than 10 years (Kent et al. 2010). 

Similar patterns of decreasing risk as duration of cessation 

increased were observed in other studies (Wong et al. 2007; 

Stackelberg et al. 2014; Tang et al. 2016). 

According to data from 2002 from CPS II that was 

reported in the 2004 Surgeon General’s report, mortality 

attributable to AAA was significantly higher among men 

and women who were current smokers compared with 

never smokers (USDHHS 2004). Risk of mortality due to 

AAA was lower in former smokers than in current smokers 

but was higher in former smokers than in never smokers. 

Pujades-Rodriguez and colleagues (2015), in their analysis of data from the CALIBER program, reported that the 

age-adjusted HR of AAA tended to decrease with increased 
Study Design/population Findings: RR (95% CI) Comments

Lederle et al. 

(1997, 2000)a

•

•

•

•

•

Cross-sectional analyses (Aneurysm Detection 

and Management)

Two cohorts of veterans, 50–79 years of age, 

97% men, 87% White (also African American 

and other races/ethnicities), no history of AAA

Sample sizes and number of AAAs (≥3.0 cm):

– Cohort 1: n = 73,451; 3,366 AAAs

– Cohort 2: n = 52,745; 1,917 AAAs

Screened in 1992–95 and 1995–97, 

respectively

United States

• Cohort 1:

– AAA 3.0–3.9 cm diameter





Current smoker: 1.00 (referent)

Former smoker (per 10 years since 

quitting): 0.81 (0.76−0.86)

– AAA ≥4.0 cm diameter





Current smoker: 1.00 (referent)

Former smoker (per 10 years since 

quitting): 0.72 (0.65−0.79)

• Cohort 2: similar findings

—

Wilmink et 

al. (1999)a

•

•

•

•

Nested case-control study

Men, >50 years of age, 210 cases of AAA (>29 

cm) from AAA screening study, 237 agematched controls, 64% of cases and 63% of 

controls were former smokers

Years of data collection: not provided

Huntingdon, United Kingdom

• Smoking status:

–

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 4.0 (1.7–9.5)

Current smoker: 9.0 (3.4–24.0)

Similar results when reclassified based 

on cotinine level

• Years since quitting:

–

–

Current smoker: 1.00 (referent)

Former smoker











1–5: 0.62 (0.2–1.7)

6–10: 0.47 (0.2–1.3)

11–20: 0.61 (0.3–1.3)

21–30: 0.28 (0.1–0.7)

≥30 years: 0.20 (0.1–0.4)

– When also adjusted for duration of smoking, 

results trended toward weaker associations

Adjusting for duration of smoking in the 

time-since-quitting analysis might lead 

to over adjustment (results not shown)

Lederle et al. 

(2003)

•

•

•

•

•

Prospective cohort (Cancer Prevention Study II)

508,351 participants; >30 years of age; 

tended to be White, married, and educated; 

1,296 deaths from AAA

Participants were screened between October 

1992 and March 1995

United States (all 50 states)

Follow-up: 14 years

• Smoking status:

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 2.4

Current smoker: 6.0

Unpublished data presented in systematic 

review; 95% CIs not provided; adjusted for 

age and potentially other factors

The Health Benefits of Smoking Cessation 261

Table 4.19 Observational studies on smoking cessation and abdominal aortic aneurysm
Study Design/population Findings: RR (95% CI) Comments

Wong et al. 

(2007)a

•

•

•

•

Prospective cohort (Health Professionals 

Follow-Up Study)

39,352 men, 40–75 years of age at baseline, 

10% current smokers at baseline, healthy 

(no prior CVD), excluded nondrinkers who 

had quit in prior 10 years, 376 cases of AAA

1986–2002

United States

• Smoking status:

– Current smoker: 1.00 (referent)

– Former smoker (years since quitting):





<10: 6.5 (4.5–9.3)

≥10: 2.5 (1.8–9.3)

– Current smoker (number of cigarettes 

smoked per day):









1–4: 1.8 (0.4–7.4)

5–14: 5.9 (3.0–11.4)

15–24: 14.2 (9.4–21.5)

≥25: 15.2 (9.9–23.3)

—

Forsdahl et al. 

(2009)a

•

•

•

•

Prospective cohort study (Tromsø)

4,345 participants, 25–82 years of age at 

baseline, 59.5 years of age (mean), 37% former 

smokers, no AAA or unknown AAA status, 

119 incident cases of AAA

1994–2001

Norway

• Smoking status:

–

–

Never smoker: 1.00 (referent)

Former smoker (years since quitting):







<10: 2.88 (1.23–6.75)

10–19: 2.90 (1.25–6.72)

≥20: 1.26 (0.54–2.96)

– Current smoker (number of cigarettes 

smoked per day):







<10: 6.19 (2.86–13.38)

10–19: 9.78 (4.89–19.58)

≥20: 13.72 (6.12–30.78)

Logistic regression used; cross-sectional 

analyses (Singh et al. 2001) found smoking 

was a risk factor for prevalence of AAA

Kent et al. 

(2010)a

• Cross-sectional analysis (prevalence in cohort, 

Life Line Screening database)

• 3.1 million participants without prior repair 

of AAA, <85 years of age, 63.1 years of age 

(mean), 35% men, 87% White (also Hispanic, 

African American, Native American, and Asian), 

and 23,446 with AAA (≥3 cm)

• Screened in 2003–2008

• United States

• Smoking status:

–

–

Current smoker: 1.00 (referent)

Former smoker (years since quitting):







<5: 0.87 (0.84–0.912)

5–10: 0.68 (0.65–0.71)

>10: 0.42 (0.41–0.43)

Table 4.19 Continued

262 Chapter 4

A Report of the Surgeon General
Study Design/population Findings: RR (95% CI) Comments

PujadesRodriguez et al. 

(2015)

• Prospective cohort

• 1.93 million participants, ≥30 years of age, 

49% men, predominantly White (also South 

Asian and Black), 16.2% former smokers 

(among those with smoking data); drawn from 

CALIBER program (linked electronic health 

records), no history of CVD, 1,238 cases of 

AAA in former smokers

• 1997–2010

• England

• Median follow-up: 6 years

• AAA by smoking status (age-adjusted):

– Current smoker: 1.00 (referent)

– Former smoker (years since quitting):

 <2: 0.84 (0.47–1.51)

 2–9: 0.78 (0.52–1.17)

 >10: 0.25 (0.20–0.32)

See Table 4.17 for concerns about validity

Stackelberg 

et al. (2014)a

• Two prospective cohorts (Cohort of Swedish 

Men and Swedish Mammography Cohort)

• Participants 46–84 years of age, 37% of 

men were former smokers, 25% of women 

were former smokers, no known diagnosis 

of AAA or cancer (other than nonmelanoma 

skin cancer)

• Sample sizes and number of AAAs by cohort:

– Cohort of Swedish Men: 42,596, 958 AAA

– Swedish Mammography Cohort: 35,550, 

199 AAA

• 1998–2011

• Sweden

• Mean follow-up: 12.7 years

• Men:

– Never smoker: 1.00 (referent)

– Former smoker (<20 years since quitting): 

3.77 (3.08–4.63)

– Former smoker (≥20 years since quitting): 

1.61 (1.27–2.03)

– Current smoker (<20 pack-years): 3.06

(2.37–3.95)

– Current smoker (≥20 pack-years): 6.55 

(5.36–7.99)

• Women:

– Never smoker: 1.00 (referent)

– Former smoker (<20 years since quitting): 

4.63 (3.04–7.06)

– Former smoker (≥20 years since quitting): 

0.82 (0.35–1.92)

– Current smoker (<20 pack-years): 7.01

(4.63–10.62)

– Current smoker (≥20 pack-years): 6.55 

(5.36–7.99)

Less power to detect associations in women 

(199 cases) than in men (958 cases)

Table 4.19 Continued

The Health Benefits of Smoking Cessation 263
Study Design/population Findings: RR (95% CI) Comments

Tang et al. 

(2016)a

•

•

•

•

•

•

Prospective cohort (Atherosclerosis Risk in 

Communities Study)

26% former smokers

15,703 participants, 45–64 years of age at 

baseline, 45% men, 26% former smokers 

at baseline, African Americans (27%) and 

Whites, no prior repair of AAA, excluded 

uncertain AAA status during follow-up, 

590 incident clinical AAAs, 5,578 participants 

underwent ultrasound screening from 2011 

to 2013 (identified 75 asymptomatic AAAs)

1987–2011

United States

Median follow-up: 22.5 years

• Incident clinical AAAs:

– Baseline smoking status:







Never smoker: 1.00 (referent)

Former smoker: 2.45 (1.85–3.25)

Current smoker: 7.59 (5.78–10.0)

– Longitudinal smoking status:









Never smoker: 1.00 (referent)

Quit before first visit: 1.83 (1.19–2.81) 

Recent quitterb: 3.50 (1.53–8.04) 

Continuous smoker: 6.41 (3.67–11.2)

• Similar pattern of associations with prevalent 

asymptomatic AAAs detected in 2011–2013 

subgroup

—

Table 4.19 Continued

A Report of the Surgeon General

264 Chapter 4

Notes: AAA = abdominal aortic aneurysm; CALIBER = Clinical research using LInked Bespoke studies and Electronic health Records; CI = confidence interval; 

cm = centimeter; RR = risk ratio.

aMeasure(s) of association adjusted for covariate(s).

bRecent quitter defined as someone who had quit for at least 3–8 years after the first visit in 1987.
The Health Benefits of Smoking Cessation 265

Smoking Cessation

time since smoking cessation (Table 4.19). Even so, in a 

comparison restricted to men and using never smokers as 

the referent, the age-adjusted hazard of AAA was still elevated in those who had quit smoking for 10 or more years 

(HR = 1.47, 95% CI, 1.10–1.95).

Prognosis of AAA

In the Aneurysm Detection and Management study, 

Bhak and colleagues (2015) assessed 534 veterans for the 

clinical risk factors associated with the expansion rate of 

AAA (i.e., the rate at which the AAA widens). The expansion 

rate of AAA is important to monitor, because (1) the risk of 

an AAA rupture is proportional to the maximum diameter 

of the AAA and (2) the mortality rate for rupture is high 

in those with aneurysms greater than 4–5 cm in diameter 

(Hirsch et al. 2006). Current smokers had an aortic expansion rate 0.05  cm/year greater (95%  CI, 0.2–0.8) than 

former smokers—a 19% increase (Bhak et al. 2015).

Bhak and colleagues (2015) performed a pooled analysis of individual-level data from 12 studies. In one of the 

12 studies, Sweeting and colleagues (2012) found that, compared with former and never smoking, current smoking 

increased the growth rate of AAA by 0.35 mm/year, and the 

rupture rate was twice as high in men and women who 

were current smokers as it was in nonsmokers. In another 

of the 12 studies (Brady et al. 2004), among 1,743 patients 

in the United Kingdom Small Aneurysm Trial, the growth 

rate of AAA was 0.42 mm/year higher in current smokers 

than in former smokers (95%  CI, 0.17–0.68). There was 

no difference in the growth rate of AAA between former 

and never cigarette smokers. Using this same study population, Brown and Powell (1999) found that the adjusted 

hazard of AAA rupture was lower in former smokers 

(HR = 0.59; 95% CI, 0.39–0.89) than in current smokers. 

Other researchers have also found that smoking or a history of smoking is associated with an increased growth 

rate in AAA (Chang et al. 1997; Lindholt et al. 2001).

Koole and colleagues (2012) assessed the relationships between smoking status and outcomes of endovascular aneurysm repair among 8,638 patients (2,406 former 

smokers) in the European Collaborators on Stent/Graft 

Techniques for Aortic Aneurysm Repair study. Compared 

with never smokers, former and current smokers were 

more likely to need percutaneous transluminal angioplasty procedures or stents at the time of surgery (10.5%, 

11.8%, and 13.7%, respectively). Regarding late complications, however, current smokers and former smokers had 

fewer endoleaks than never smokers. Current cigarette 

smokers (adjusted HR  =  1.45; 95%  CI, 1.03–2.05) and 

former smokers (adjusted HR = 1.23; 95% CI, 0.87–1.72) 

were more likely than never smokers to have migration of 

the stent graft.

Summary of the Evidence

Substantial evidence suggests that former smokers 

have a lower risk of incident AAA than current smokers 

and that risk decreases with increasing time since 

smoking cessation. Compared with never smokers, former 

smokers have an increased risk of AAA that can persist for 

decades. The evidence also suggests that the diameter of 

AAA expands at a lower rate in former smokers compared 

with current smokers.

Summary of the Evidence

This section builds on the 1990 (USDHHS 1990) 

and subsequent Surgeon General’s reports (USDHHS 

2001, 2004, 2006, 2010, 2014), providing an updated and 

overarching summary of what is now known about the 

relationships between smoking cessation and CVD outcomes. Previous Surgeon General’s reports concluded 

that smoking cessation reduces the risk of CHD, PAD, 

ischemic stroke, SAH, and, more broadly, CVD morbidity 

and mortality (Table  4.10). These past reports also concluded that smoking cessation reduces risk of recurrent 

MI or CVD death among persons with CHD and improves 

exercise tolerance, reduces risk of amputation, and 

improves overall survival among patients with PAD. In 

particular, the 2001 Surgeon General’s report concluded 

that smoking cessation appears to slow the rate of progression of carotid atherosclerosis in women and is associated with improvements in symptoms, prognosis, and 

survival among women with peripheral vascular atherosclerosis (USDHHS 2001). The evidence presented in this 

report shows that smoking cessation benefits persons at 

any age, reducing relative risk of CVD for smokers and the 

burden of disease from cardiovascular causes.

This section summarizes the large body of evidence 

related to the benefits of smoking cessation for reducing 

risk of CVD outcomes, considering evidence from mechanistic, epidemiologic, and clinical studies and applying 

established guidelines for causal inference (consistency; 

strength of association; temporality; specificity; experiment and biologic gradient; and coherence, plausibility, and analogy). Previous reports (U.S. Department 

of Health, Education, and Welfare [USDHEW] 1964; 

USDHHS 2004) have described this approach to causal 

inference. The approach is used here to systematically 

develop the basis for causal conclusions. As described in 

the 2004 Surgeon General’s report, rather than serving 

as a checklist for assessing causal inference, these causal 

criteria are used to integrate multiple lines of evidence 

(USDHHS 2004). 
A Report of the Surgeon General

266 Chapter 4

Evaluation of the Evidence

Consistency

The relationships between smoking status and cessation with most of the outcomes described here have 

been extensively studied in well-designed and adequately 

powered studies (using observational and experimental 

designs) across different populations and time periods. 

Multiple studies have found that smoking cessation is 

associated with reduction in inflammatory markers and 

hypercoagulability and with rapid improvement in levels 

of HDL-C. Several, but not all, studies have found an association between smoking cessation and improved endothelial function. Much evidence documents the fact that 

former cigarette smokers tend to have less extensive subclinical atherosclerosis than current smokers and that 

smoking cessation is followed by slower progression of 

atherosclerosis, particularly for the outcomes of carotid 

IMT and ABI.

Many studies have also found that, compared with 

current smokers, former smokers have a lower risk of 

incident CVD, CHD, stroke, and AAA and that the risks 

decrease with increasing time since cessation. Studies 

support similar associations between smoking cessation 

and outcomes related to AF, SCD, heart failure, VTE, and 

PAD, although the evidence is more limited with regard 

to reduced risk with increased time since cessation. 

Additionally, smoking cessation is consistently associated 

with reduced risk of recurrent infarction and CVD death 

among patients with CHD (USDHHS 1990). Similarly, for 

persons who have already had a stroke, cessation reduces 

risk for recurrent events. Studies have also found that 

among patients with PAD, morbidity and mortality are 

lower in former smokers than in current smokers; in addition, the expansion rate of AAA is lower in former smokers 

than in current smokers. 

Strength of Association

For many CVD outcomes, there is consistent evidence of a substantial reduction in risk among former 

smokers compared with current smokers; after a certain 

amount of time has elapsed since cessation, the risk for 

some outcomes among former smokers even approaches 

that of never smokers. For example, research estimates 

that the excess risk of CHD decreases by half approximately 4–5  years after cessation, albeit with substantial 

variation in estimates among studies, and then gradually 

approaches the risk of never smokers. For stroke, a similar 

pattern has been observed, although the risk may not reach 

that of never smokers. Smoking is strongly related to the 

risk of AAA; former smokers (particularly those who have 

quit for long periods) tend to have a substantially lower 

risk than those who continue to smoke. For example, in 

adjusted analyses in the ARIC study, compared with never 

smokers, current smokers had 6.41  times the risk of a 

clinical AAA (95% CI, 3.67–11.2); recent quitters (who had 

quit for at least 3–8 years) had 3.50 times the risk (95% CI, 

1.53–8.04); and longer term quitters had 1.83 times the 

risk (95% CI, 1.19–2.81) (Tang et al. 2016).

Temporality

Many of the studies reviewed here are prospective 

in nature, and thus smoking status or smoking cessation 

was measured before the incident outcome. For measurements of biomarkers, several studies assessed changes in 

these biomarkers after cessation; similar analyses have 

been carried out for markers of subclinical atherosclerosis. Although some studies are cross-sectional in nature, 

prospective cohort studies have been carried out for each 

of the main outcomes discussed, thereby ensuring that 

smoking cessation preceded the occurrence of the health 

outcomes. The potential for reverse causality has also 

been accounted for in these studies to diminish the potential for such bias.

Specificity

In line with observations of reduced risk of overall 

CVD morbidity or mortality among former smokers compared with current smokers, similar reductions were 

observed for major causes of CVD morbidity and mortality, 

such as CHD and stroke and many other subtypes of CVD.

Experiment and Biologic Gradient

Both smoking cessation and time since cessation 

serve as naturally occurring changes in exposure status 

that can be used to infer the effect of the intervention of 

stopping smoking. The temporal pattern of declining risk 

after smoking cessation is strong evidence for a causal 

benefit of quitting and reflects a waning of the processes 

of injury caused by smoking. For most of the CVD outcomes reviewed in this report, most cited studies found a 

reduction in risk after cessation, followed by a pattern of 

a continued decrease in risk with longer time since cessation. In parallel, studies using biomarkers found greater 

reductions in inflammatory markers and hypercoagulability with increasing time since cessation. Evidence from 

observational studies and clinical trials supports a rapid 

(within weeks) improvement in levels of HDL-C after cessation, with no clear pattern of change after that time 

(Forey et al. 2013). Complementary evidence comes from 

studies showing greater reduction in risk with longer 

time since cessation for outcomes of incident CVD, congestive heart failure, stroke, and AAA. For the outcomes 

of incident AF, SCD, heart failure, VTE, and PAD, there 
The Health Benefits of Smoking Cessation 267

Smoking Cessation

is less evidence available on how risk of these outcomes 

changes with time since cessation, although the available 

evidence supports a decrease in risk with increased time 

since cessation for SCD (Sandhu et al. 2012), heart failure 

(Pujades-Rodriguez et al. 2015), and PAD (Cui et al. 2006; 

Conen et al. 2011; Pujades-Rodriguez et al. 2015).

The 1990 Surgeon General’s report estimated that 

excess risk of CHD is reduced by about half after 1 year of 

smoking cessation and that risk of CHD is similar among 

former and never smokers after 15 years of smoking cessation (USDHHS 1990). Similarly, the 2001 Surgeon 

General’s report concluded that there is a substantial 

reduction in risk of CHD among women within 1–2 years 

of cessation; such a reduction in risk gradually continued 

to reach that of nonsmokers 10–15  or more years after 

cessation (USDHHS 2001). More recent analyses using an 

exponential distribution to quantitatively estimate how 

rapidly CHD risk decreases after smoking cessation indicate that the excess risk of CHD associated with smoking 

decreases by 50% about 4.4 years after cessation (95% CI, 

3.26–5.95) (Lee et al. 2012). The risk then decreases asymptotically toward the risk among never smokers, as was also 

reported by the IARC (2007). Another model suggests a 

rapid decline in risk of acute MI soon after cessation, followed by a slower decline to a risk close to that of never 

smokers (Hurley 2005).

Similarly, the 1990 Surgeon General’s report concluded that after smoking cessation, the risk of stroke 

returns to that of never smokers within 5–15  years 

(USDHHS 1990). The 2001 Surgeon General’s report 

modified this conclusion slightly, stating that in most 

studies, including studies of women, the increased risk 

of stroke associated with smoking is reversible after cessation, with this risk approaching that of never smokers 

after 5–15 years of cessation. Another modeling study by 

Lee and colleagues (2014) estimated that the excess risk 

of stroke associated with smoking decreases by 50% after 

4.78 years (95% CI, 2.17–10.50), but there was considerable unexplained heterogeneity. The modeling study by 

Hurley (2005) reported a rapid decrease in risk of stroke 

shortly after cessation (within 1–2  years), followed by a 

slower decline; the decline in risk of stroke was not as rapid 

as the decline in risk of acute MI following cessation, and 

the risk of stroke was estimated to remain elevated even 

among long-time former smokers. Evidence also supports 

a reduction in risk of mortality and of subsequent CVD 

events among patients with CHD who quit smoking after 

an index CHD event compared with those who continue to 

smoke (Wilson et al. 2000; Critchley and Capewell 2003; 

Twardella et  al. 2004, 2006; Shah et  al. 2010; Breitling 

et al. 2011a) (Table 4.20). Studies of the impact of counseling on smoking cessation have also found reduced risk 

of all-cause mortality among patients who received or 

were randomized to receive such counseling (Mohiuddin 

et al. 2007; Van Spall et al. 2007; Bucholz et al. 2017).

Coherence, Plausibility, and Analogy

Evidence linking smoking cessation to reduced risk 

of CVD should be considered within the broader context 

of mechanistic research on smoking and CVD. Previous 

reports concluded that smoking initiates several pathogenetic mechanisms that underlie the development of CVD 

(USDHHS 2004, 2010, 2014). The 1990 and 2001 Surgeon 

General’s reports and the present updated review have 

provided evidence of how smoking cessation can reverse 

or slow these pathogenetic processes (USDHHS 1990) 

and slow the progression of subclinical atherosclerosis 

(USDHHS 2001).

Previous reports have also concluded that smoking 

causes CVD, including subclinical atherosclerosis, CHD, 

stroke, and AAA (USDHHS 2004). Much evidence supports a dose-response relationship between pack-years of 

smoking and risk of CVD. Evidence from the present report 

and previous reports supports the benefits of smoking cessation in terms of reducing risk of CVD. Multiple studies 

have found a larger relative benefit of cessation among 

those who quit smoking at younger ages (compared with 

those who quit later in life), which also aligns with research 

on the dose-response relationship between smoking and 

risk of CVD (Doll et al. 2004; Jha et al. 2013; Pirie et al. 

2013; Thun et al. 2013a). However, given the increasing 

rates of the various CVDs with increasing age, substantial absolute reductions in the number of CVD events and 

deaths can still be made by quitting smoking at older ages.

Synthesis of the Evidence

The conclusions presented below are based on interpretations of multiple lines of evidence from a framework built around the guidelines for causal inference. 

Generally, when the evidence (a) is strong and consistent, 

(b) shows that former smokers have a lower risk of a CVD

outcome (clinical or subclinical) compared with current

smokers, (c)  shows that the risk of a CVD outcome in

former smokers decreases with increased time since cessation, and (d) results from well-designed and sufficiently

powered studies, then such evidence is deemed sufficient

to support the conclusion that smoking cessation causes a

reduction in risk of the CVD outcome. When evidence for

CVD outcomes is not as strong (e.g., if evidence on how

CVD risk changes with time since cessation is not sufficient), then the evidence is deemed to be suggestive but

not sufficient that smoking cessation decreases the risk of

these outcomes.
Study Design/population Findings: RR (95% CI) Comments

Critchley and 

Capewell (2003)

• Meta-analysis of 20 prospectivecohorts:

–

–

Totalmortalityanalysis: n = 12,603; 

2,928 cases

Nonfatal MI analysis: n = 6,089;779 cases

• Participants with prior CHD:

–

–

–

Mean: 55 years of age

20%of caseswerewomen(6studiesof 

men only)

28–77% cessation rates (mean:45%)

•

•

•

•

Moststudiesbeganinthe1960sor1970s

Most from UnitedStatesorEurope;onefrom 

Japan; and one from India

Follow-up: 2–26 years; mean: 5 years

Outcomes: total mortality and nonfatalMI

• Total mortality:

–

–

Continued smokers: 1.00 (referent)

Cessation group: 0.64 (0.58–0.71)

• Nonfatal MI:

–

–

Continued smokers: 1.00 (referent)

Cessation group: 0.68 (0.57–0.82)

Restriction to high-quality studies yielded 

similarresults;resultswerealsosimilaracross 

studies, irrespective of age, sex, index cardiac 

event, country, or year the studybegan

Dagenais et al. 

(2005)a

• Prospectiveanalyses of clinical trial (Heart 

Outcomes Prevention Evaluation)

• 8,905 participants with stable CVD or diabetes 

and one additional risk factor (approximately 

50% had prior MI); 58% were former smokers

• Cases (restricted to thosewhosurvivedfor 

6 months):

–

–

–

–

CVD death: 641

MI: 978

Stroke: 358

Total mortality: 1,021

• Started in 1993

• Median follow-up: 4.5 years

• Cardiovascular death, MI, or stroke:

–

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 0.91 (0.80–1.03)

Current smoker: 1.37 (1.14–1.64)

Similar findingsforindividualoutcomes 

of CVD death, MI, and stroke

• Mortality:

–

–

–

Never smoker: 1.00 (referent)

Former smoker: 0.93 (0.80–1.08)

Current smoker:1.99(1.63–2.44)

• No consistent pattern for increased risk of

heart failure, revascularization, unstable

angina,oroccurrenceofmicroalbuminuria

—

A Report of the Surgeon General

268 Chapter 4

Table 4.20 Observational studies (meta-analyses and individual cohorts) on smoking cessation and prognosis of coronary heart disease or 

cardiovascular disease
Study Design/population Findings: RR (95% CI) Comments

Breitling et 

al. (2011a)a

•

•

•

•

•

•

Prospective cohort study (Long-Term Success 

of Cardiologic Rehabilitation Therapy study)

1,062 participants:

– Mean: 59 years of age

– 85% male with acute MI, coronary 

syndrome, or coronary artery intervention 

seen for rehabilitation

– 154 cases who had secondary CVD events

Started in 2000

Germany

Median follow-up: 8.1 years

Outcome: secondary CVD events

• Abstained from smoking according to 

self-report:

–

–

–

–

Continued smoker: 1.00 (referent)

Quit after event: 0.38 (0.20–0.73)

Quit before event: 0.62 (0.40–0.97)

Never smoker: 0.47 (0.28–0.78)

• Restricted to those who did not change 

status for 1–3 years:

–

–

–

–

Continued smoker: 1.00 (referent)

Quit after event: 0.17 (0.06–0.44)

Quit before event: 0.42 (0.25–0.70)

Never smoker: 0.32 (0.18–0.55)

Similar findings for 1-year and 3-year follow-ups 

(Twardella et al. 2004, 2006)

Table 4.20 Continued

The Health Benefits of Smoking Cessation 269

Notes: CHD = coronary heart disease; CI = confidence interval; CVD = cardiovascular disease; MI = myocardial infarction; RR = risk ratio. aMeasure(s) of association adjusted for covariate(s).
A Report of the Surgeon General

270 Chapter 4

Conclusions

1. The evidence is sufficient to infer that smoking

cessation reduces levels of markers of inflammation and hypercoagulability and leads to rapid

improvement in the level of high-density lipoprotein cholesterol.

2. The evidence is sufficient to infer that smoking cessation leads to a reduction in the development of

subclinical atherosclerosis, and that progression

slows as time since cessation lengthens.

3. The evidence is sufficient to infer that smoking cessation reduces the risk of cardiovascular morbidity

and mortality and the burden of disease from cardiovascular disease.

4. The evidence is sufficient to infer that the relative risk of coronary heart disease among former

smokers compared with never smokers falls rapidly

after cessation and then declines more slowly.

5. The evidence is sufficient to infer that smoking cessation reduces the risk of stroke morbidity and mortality.

6. The evidence is sufficient to infer that, after smoking 

cessation, the risk of stroke approaches that of never

smokers.

7. The evidence is suggestive but not sufficient to infer

that smoking cessation reduces the risk of atrial

fibrillation.

8. The evidence is suggestive but not sufficient to infer

that smoking cessation reduces the risk of sudden

cardiac death among persons without coronary

heart disease.

9. The evidence is suggestive but not sufficient to infer

that smoking cessation reduces the risk of heart

failure among former smokers compared with persons who continue to smoke.

10. Among patients with left-ventricular dysfunction,

the evidence is suggestive but not sufficient to infer

that smoking cessation leads to increased survival

and reduced risk of hospitalization for heart failure.

11. The evidence is suggestive but not sufficient to infer

that smoking cessation reduces the risk of venous

thromboembolism.

12. The evidence is suggestive but not sufficient to

infer that smoking cessation substantially reduces

the risk of peripheral arterial disease among former

smokers compared with persons who continue to

smoke, and that this reduction appears to increase

with time since cessation.

13. The evidence is suggestive but not sufficient to infer

that, among patients with peripheral arterial disease, smoking cessation improves exercise tolerance, reduces the risk of amputation after peripheral

artery surgery, and increases overall survival.

14. The evidence is sufficient to infer that smoking cessation substantially reduces the risk of abdominal

aortic aneurysm in former smokers compared with

persons who continue to smoke, and that this reduction increases with time since cessation.

15. The evidence is suggestive but not sufficient to infer

that smoking cessation slows the expansion rate of

abdominal aortic aneurysm.

Implications

The evidence is clear and certain that smoking cessation reduces the risk for major CVD outcomes. The 

decline over time in the prevalence of adult cigarette 

smoking has contributed to the decline of CVD mortality. 

Intensified efforts by clinicians, healthcare systems, communities, and states to encourage and help smokers to 

quit will contribute to reducing the burden of CVD at the 

patient and population levels.

Heart disease is the leading cause of death in the 

United States for both men and women (Xu et al. 2018). 

The term “heart disease” refers to several types of heart 

conditions. In the United States the most common type of 

heart disease is coronary artery disease, which affects the 

Smoking Cessation After a Diagnosis of Coronary Heart Disease

blood flow to the heart. Smoking is a key risk factor for 

developing coronary heart disease (CHD) (U.S. Department 

of Health and Human Services [USDHHS] 2004). 

This section reviews the evidence on the benefits 

of cigarette smoking cessation in people with established 
The Health Benefits of Smoking Cessation 271

Smoking Cessation

CHD. It focuses on the endpoints of all-cause mortality, 

cause-specific mortality, and the incidence of new or 

recurrent cardiac events. As advances in clinical treatment regimens for CHD have improved the prognosis for 

persons with cardiovascular events, the previously established evidence that smoking represents a causal factor for 

CHD has led to studies investigating the potential benefit 

of smoking cessation for reducing risk of mortality after a 

diagnosis. The body of evidence on this topic, which began 

to emerge in the 1970s, has grown to the point that substantial scientific evidence now exists on this topic.

Conclusions from Previous 

Surgeon General’s Reports

Previous Surgeon General’s reports have not specifically evaluated the evidence concerning the impact of cigarette smoking cessation on mortality after a diagnosis of 

CHD; in fact, this is the first Surgeon General’s report to 

address the potential health benefits of smoking cessation 

after such a diagnosis. Previous reports have concluded 

that sufficient evidence exists to infer that smoking causes 

premature death, multiple diseases, and other adverse 

health effects (USDHHS 2014). The 1990 report, which 

focused on the benefits of smoking cessation, reported 

conclusions on the decline in risk for CHD and stroke 

among those who quit smoking compared with those who 

continued to smoke. In addition, the report concluded 

that, “Among persons with diagnosed CHD, smoking cessation markedly reduces the risk of recurrent infarction 

and cardiovascular death. In many studies this reduction 

in risk of recurrence or premature death has been 50 percent or more” (USDHHS 1990, p. 260). The report noted a 

lack of relevant findings for stroke. 

Considering the biological processes by which 

smoking increases risk for multiple diseases and mortality, 

the adverse health effects of smoking would be expected 

to apply to persons diagnosed with CHD in the same way 

as they apply to persons in the general population who 

are at risk for first events. The 2010 Surgeon General’s 

report, How Tobacco Smoke Causes Disease, detailed the 

many mechanisms leading to these adverse health effects 

(USDHHS 2010). 

Biological Basis

This review emphasizes all-cause mortality, causespecific mortality, and the incidence of new or recurrent 

cardiac events. Regarding all-cause mortality, the mortality burden from smoking is largely attributable to its 

role in causing multiple types of cancer, various cardiovascular diseases, and chronic obstructive pulmonary disease 

(COPD). Many aspects of the pathogenesis of these diseases in smokers have been characterized, and these same 

mechanisms would apply to persons who have been diagnosed with CHD (USDHHS 2010). With regard to the risk 

for cardiovascular disease following cessation, the risk for 

several consequences of smoking—including endothelial 

dysfunction, increased risk for thrombosis, and reduced 

oxygen delivery—would be expected to lessen in the short 

term after cessation (USDHHS 2010). As detailed in the 

2014 Surgeon General’s report, in addition to causally 

increasing risk for specific disease endpoints, smoking 

causes systemic inflammation and oxidative stress and 

has widespread and complex effects on immune function 

(USDHHS 2014). The 2004 Surgeon General’s report concluded that smoking causes overall poorer health that 

leaves smokers with a diminished health status compared 

with nonsmokers (USDHHS 2004).

Literature Review Methods and 

Other Methodologic Considerations

The literature search strategy for this review was 

designed to have high sensitivity by searching broadly 

in the MEDLINE database and then manually identifying articles with evidence on the association between 

smoking cessation in patients with CHD and clinical 

endpoints. For example, key terms in the initial search 

included “smoking cessation” and “coronary heart disease” OR “cardiovascular disease.” The relevant evidence 

identified was most abundant on the specific topics of the 

associations between persistent smoking versus quitting 

smoking with the outcomes of all-cause mortality, causespecific mortality (focused on cardiac causes of death and 

sudden death), and risk of new or recurrent cardiac events. 

Consequently, the evidence review for this section focuses 

on these three endpoints.

Because of the methodologic limitations of other 

designs, the summary tables in this section include data 

only from original research reports on prospective cohort 

studies. Relevant systematic reviews and meta-analyses 

were incorporated into the discussion of the evidence, but 

they were not included in the evidence tables. The reference lists of all published papers reviewed, including the 

systematic reviews, were searched to check for potentially 

eligible studies.

Several points relevant to considerations of methodology were consistent across the range of outcomes 

addressed. First, because all evidence summarized in the 

evidence tables was generated from prospective cohort 
A Report of the Surgeon General

272 Chapter 4

studies, it benefited from the methodologic strengths 

of such studies in addressing the question of the effect 

of smoking cessation in patients with CHD. Specifically, 

these were studies of cohorts of patients diagnosed with 

a specific heart disease, most often myocardial infarction (MI), or who had undergone a specific cardiovascular procedure such as percutaneous coronary intervention (PCI) or coronary bypass surgery. In all the studies, 

smoking status was measured at the time of initial diagnosis. To assess the health effects of smoking cessation, 

areas of interest included findings only from those who 

were current smokers at the time of diagnosis; this review 

did not consider results pertaining to those who were 

never smokers or former smokers at diagnosis. Further, 

a follow-up measurement of smoking status after baseline was required to distinguish those who quit smoking 

(henceforth called “quitters”) from those who remained 

smokers (henceforth called “persistent smokers”). The 

timing of the follow-up assessment of smoking status represents a key study design feature because only patients 

who survived to the follow-up assessment were eligible 

for inclusion in the cohorts, as explained below. The more 

remote the follow-up assessment from the start of followup, the greater the likelihood for cohort attrition due to 

mortality; to the extent that persistent smokers experience greater mortality soon after the cardiac diagnosis, 

there would be an increasing bias toward the null with a 

lengthening interval from baseline to follow-up. 

The definitions of “quitters” and “persistent 

smokers” varied across studies, ranging from sustained 

abstinence or continued smoking across several longitudinal follow-up points to self-reported quitting or 

continued smoking at a single follow-up time point. 

Alternatively, in some studies smoking status was analyzed as a time-dependent variable to account for the many 

possible transitions in smoking status that can take place 

over time. After the baseline assessment, current smokers 

could be classified as quitters or persistent smokers on 

the basis of a follow-up assessment; at that point, the prospective follow-up for outcomes began. With these shared 

features of study design, this body of evidence is focused 

specifically on those who were current smokers at the 

time of the cardiac diagnosis, with the analysis targeting 

the effect of quitting compared with persistent smoking 

within this population. Of note, several studies were initially randomized treatment trials in which sufficient data 

had been collected to address smoking cessation within 

the context of a subsequent observational cohort study of 

trial participants.

For the endpoint of all-cause mortality, evidence tables (Tables  4.21 and  4.22) present details of 

34 reports from 32 studies. The index diagnosis used to 

define the patient cohorts was MI (or included MI with 

other conditions such as angina) in the majority (61%) 

of studies on this topic. Other index diseases were coronary artery disease (CAD) (15% of studies); CHD (6% of 

studies); and in one study, cardiac arrest. Among studies 

that defined the cohort on the basis of an index procedure, the most common procedures were PCI (9%  of 

studies) and coronary artery bypass surgery (6%). The 

studies included in the evidence tables for cause-specific 

mortality (Table  4.23) and new/recurrent cardiac events 

(Table 4.24) numbered 13 and 15, respectively.

Epidemiologic and Clinical Evidence

Smoking Cessation and All-Cause Mortality 

in Patients with Coronary Heart Disease

Table 4.21 summarizes studies (N = 24) of cohorts of 

patients who were current smokers at the time of a CHD 

diagnosis that assessed the association between smoking 

cessation and all-cause mortality by comparing quitters 

and persistent smokers (the referent). Although all the 

studies relied on prospective cohorts, they varied widely in 

sample size, population composition, duration of followup, and consideration of potential confounding variables. 

Sample sizes ranged from 87 to 8,489 persons, and followup ranged from 6  months to 30  years. Some estimates 

of relative risk (RR) were unadjusted, and others were 

extensively adjusted for demographic, lifestyle, family history, or clinical characteristics. Despite this variability in 

design features, the results across studies were consistent, as illustrated by the forest plot in the top portion 

of Figure 4.4. When quitters were compared with persistent smokers, this forest plot, which illustrates results 

for the 24 studies that included an RR estimate and 95% 

confidence interval (CI) for all-cause mortality, shows 

that the RR estimates in every case were less than 1.0. 

The estimates ranged from 0.11  to 0.93, with a median 

RR of 0.55, or a reduction of 45% in the rate of mortality. The study showing the weakest association (Chow 

et al. 2010) (RR = 0.93; 95% CI, 0.59−1.46) also had the 

shortest follow-up (6  months); this may be too brief a 

period to observe the full impact of quitting (versus persistent smoking) on mortality. When the results of this 

study were presented on the basis of a composite outcome 

of MI or stroke or death, the results aligned more closely 

with those of other studies (RR = 0.74; 95% CI, 0.53–1.02) 

(Chow et al. 2010).

One of the 24 studies (Breitling et al. 2011a) in 

Table 4.21 measured self-reported smoking and also incorporated a biomarker of smoking (blood concentration of 

cotinine). This study found that smoking classification 

based on self-reports alone underestimated the strength of 
Study Design/population Findings: RRa (95% CI) Comments

Wilhelmsson 

et al. (1975)

•

•

•

•

•

•

•

405 male patients with first MI who were 

current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 3 months after MI

231 quitters, 174 persistent smokers

Study period: 1968–1972

Sweden

2-year follow-up results presented

• 0.51(0.27–0.96) Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

Risk ratio calculated on basis of data presented 

in Table 5 in Wilhelmsson and colleagues (1975)

Sparrow and

Dawber (1978)

• Framingham Study

• 195 patients with MI who were current 

smokers at diagnosis

• All current smokers at baseline

• Categorized as former smokers or persistent

smokers based on smoking status after

• data collection immediately preceding and 

following MI (indeterminate timing)

• 56 quitters, 139 persistent smokers

• Cohort established 1949, 22 years of follow-up 

through 1978

• United States

• 6-year follow-up results presented

• 0.62(0.33–1.15) Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

on page 429 in Sparrow and Dawber (1978)

Risk ratio calculated on basis of data presented 

Baughman et al. 

(1982)

• 87 patients with MI who were current 

smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status after infarct 

(indeterminate timing)

• 45 quitters, 42 persistent smokers

• Enrollment period: 1968–1971, with follow-up 

through 1978

• United States

• 99-month mean follow-up (survivors)

• 0.35(0.18–0.66) Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

Risk ratio calculated on basis of data presented 

at top of right-hand column on page 877 in

Baughman and colleagues (1982)

Table 4.21 Summary of results from prospective cohort studies of patients with coronary heart disease who were cigarette smokers at diagnosis, 

comparing all-cause mortality in those who quit smoking with persistent cigarette smokers

The Health Benefits of Smoking Cessation 273
Study Design/population Findings: RRa (95% CI) Comments

Mulcahy et al

(1982) 

• 517 male patients <60 years of age with first 

diagnosis of unstable angina or MI who were

current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters if stopped smoking at 

least 3 months before last follow-up or death 

(indeterminate timing)

• 282 quitters, 235 persistent smokers

• Enrollment period: 1961–1975 with follow-up 

through 1979

• Ireland

• 99-month mean follow-up (survivors)

• 0.59 (0.47–0.73) Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

Risk ratio calculated on basis of data presented 

in Table 1 in Mulcahy and colleagues (1982)

Aberg et al. 

(1983)

• 983 male patients with first MI who were

current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 3-month follow-up

• 542 quitters, 441 persistent smokers

• Enrollment period: 1968–1977

• Sweden

• 10.5 years maximum follow-up

• All-cause mortality:

– All ages: 0.63 (0.50–0.79)

– ≤50 years of age: 0.46 (0.25–0.84)

– >50 years of age: 0.65 (0.50–0.83)

• 5-year survival:

– Quitters: 84%

– Persistent smokers: 78%

– p <0.0001

Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

Presented survival plots and p values only from 

Cox proportional hazards regression models

Risk ratio calculated from data presented in 

Table 6 in Aberg and colleagues (1983)

Perkins and Dick

(1985)

• 119 patients with first-time diagnosis of MI

who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent 

smokers based on smoking status after MI 

(indeterminate timing)

• 52 quitters, 67 persistent smokers

• Enrollment period: 1974–1977

• United Kingdom

• 5-year follow-up

• 0.39(0.20–0.74) Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

Table II in Perkins and Dick (1985)

Risk ratio calculated from data presented in 

Table 4.21 Continued

A Report of the Surgeon General

274 Chapter 4
Study Design/population Findings: RRa (95% CI) Comments

Rønnevik et al. 

(1985)

•

•

•

•

•

•

•

453 patients with first-time diagnosis of AMI 

who were current smokers at diagnosis 

within a randomized controlled trial

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status after MI on basis of 

continued follow-up (indeterminate timing)

276 quitters, 177 persistent smokers

Enrollment period: 1978–1979

Norway

Mean follow-up: 17.3 months

• All-cause mortality (placebo group): 0.74 

(0.42–1.30)

Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

Results presented limited to placebo group 

because of observed interaction of treatment 

(timolol) with smoking

Risk ratio calculated from data presented in 

Table 3 in Rønnevik and colleagues (1985)

Hallstrom et al. 

(1986)

• 310 patients with cardiac arrest who were 

current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status 2 months or less 

after cardiac arrest

• 91 quitters, 219 persistent smokers

• Study period: 1970–1981

• United States

• Mean follow-up: 47.5 months

• 0.79 (0.50–1.06) Quitters vs. persistent smokers (referent)

Unadjusted risk ratios

Risk ratio calculated from data presented in 

bottom right-hand column of page 272 of 

Hallstrom and colleagues (1986)

Burr et al. 

(1992)

•

•

•

•

•

•

•

•

•

DART

1,186 nondiabetic male patients ≤70 years

of age with MI who were current smokers at 

diagnosis and survived at least 6 months

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 6-month follow-up

665 quitters, 521 persistent smokers

Study period: indeterminate

United Kingdom

18-month follow-up

• 0.52 (0.32–0.83) Quitters vs. persistent smokers (referent)

Unadjusted risk ratios

Mortality ratios based on average annual 

mortality rates

Unadjusted risk ratio calculated from Table 2 

in Burr and colleagues (1992)

Table 4.21 Continued

The Health Benefits of Smoking Cessation 275
Study Design/population Findings: RRa (95% CI) Comments

Cavender et al. 

(1992)

• CASS

• 284 patients with angiographically confirmed 

CAD who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 6-month follow-up

• 97 quitters, 187 persistent smokers

• Enrollment period: 1974–1979

• United States and Canada (15 clinical sites)

• 10-year follow-up

• All-cause mortality: 0.63 (0.40–0.97)

• 10-year survival:

– Quitters: 80%

– Persistent smokers: 69%

– p = 0.025

Quitters vs. persistent smokers (referent)

Unadjusted risk ratios

“Persistent smoker” defined as a person 

who smoked during the follow-up interval 

(questionnaires every 6 months)

Risk ratio calculated from data presented in 

the title of Figure 2 in Cavender and colleagues 

(1992); a Cox proportional hazards model was 

fit with smoking as a time-dependent covariate 

to account for quitters who reverted to smoking

Cox proportional hazards model showed that 

smoking during 50% and 100% of the follow-up 

period increased theRR of death by 1.56 and 

1.73, respectively

Survival plots and p values presented only from 

Cox proportional hazards regression models

Gupta et al. 

(1993)

•

•

•

•

•

•

•

225 patients with CHD who were current 

smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status since the time of

diagnosis of CAD (indeterminate timing)

173 quitters, 52 persistent smokers

Study baseline: 1980

India

Approximately 6-year follow-up

• 0.70 (0.49–1.01) Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

Risk ratio calculated from data presented on 

page 127 of Gupta and colleagues (1993)

Adjusted hazards ratio comparing persistent 

smokers to quitters plus nonsmokers presented 

in Table 3 in Gupta and colleagues (1993) 

underestimated association because of inclusion 

of nonsmokers in the reference category; hazard 

ratio was 1.28 (95% CI, 1.01–2.09) after adjusting 

for sex, age, hypertension, cholesterol, diabetes, 

and history of MI or congestive heart failure

Table 4.21 Continued

A Report of the Surgeon General

276 Chapter 4
Study Design/population Findings: RRa (95% CI) Comments

Tofler et al. 

(1993)

• MILIS study

• 641 patients with AMI who were current 

smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 6-month follow-up

• 360 quitters, 281 persistent smokers

• Enrollment period: 1974–1979

• United States

• 4-year follow-up results presented

• All-cause mortality:

– Total: 0.48 (0.31–0.73)

– <12 years of education: 0.63 (0.39–1.03)

– ≥12 years of education: 0.39 (0.18–0.89)

Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

Table 3 in Tofler and colleagues (1993)

Risk ratio calculated from data presented in 

Greenwood et al. 

(1995)

•

•

•

•

•

•

•

•

ASSET

532 patients with MI who were current 

smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 1-month follow-up

396 quitters, 136 persistent smokers

Study period: 1986–1988 (enrollment)

England

6.3-year median follow-up

•

•

All-cause mortality: 0.56 (0.33–0.98)

10-year survival:

–

–

–

Quitters: 80%

Persistent smokers: 69%

p = 0.025

Quitters vs. persistent smokers (referent) 

Logistic regression models

Adjusted for age, history of diabetes, history 

of angina, and treatment with antiarrhythmic 

drugs at discharge

Herlitz et al. 

(1995)

• 217 patients with AMI who were current 

smokers at diagnosis and survived at least

1 year

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status after 1 year of 

follow-up

• 115 quitters, 102 persistent smokers

• Enrollment period: 1986–1987

• Sweden

• 4-year follow-up results presented

• 0.55 (0.34–0.91) Quitters vs. persistent smokers (referent) 

Unadjusted risk ratios

Risk ratio calculated on basis of data presented 

in text and mortality rates presented in Figure 2 

in Herlitz and colleagues (1995)

Table 4.21 Continued

The Health Benefits of Smoking Cessation 277
Study Design/population Findings: RRa (95% CI) Comments

Kinjo et al. 

(2005)

•

•

•

•

•

•

•

•

OACIS study

1,424 patients with AMI who were current 

smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent 

smokers based on smoking status 3 months 

after discharge

1,056 quitters, 368 persistent smokers

Study period: 1998–2003

Japan

2.5-year mean follow-up

• Adjusted hazard ratio: 0.39 (0.20–0.77) Quitters vs. persistent smokers (referent)

Proposed hazards models

Adjusted for sex, age, BMI, hypertension, 

dyslipidemia, diabetes, obesity, prior MI, prior 

angina pectoris, prior cerebrovascular disease, 

heart rate, Killip class ≥2, anterior wall MI, 

atrial fibrillation, ventricular fibrillation, 

and revascularization

Gerber et al. 

(2009)

• ISFAMI

• 798 patients ≤65 years of age with first-time

MI who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status during follow-up

• 417 quitters, 381 persistent smokers

• Study period: 1992–2005

• Israel

• 13.2-year median follow-up

• Adjusted odds ratio: 0.63 (0.48–0.82) Quitters vs. persistent smokers (referent)

Proportional hazards models, with smoking 

modeled as time-dependent covariate

Adjusted for sex, age, ethnicity, education, 

income, employment, hypertension, dyslipidemia, 

diabetes, obesity, physical activity, Q-wave AMI, 

CABG, PTCA, unstable angina pectoris, and 

heart failure during follow-up

Chow et al. 

(2010)

•

•

•

•

•

•

•

•

OASIS 5 trial

4,324 patients with unstable angina or MI 

who were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status after 30 days of 

follow-up

2,802 quitters, 1,522 persistent smokers

Study baseline: 2003–2005

41 countries

6-month follow-up

• Adjusted odds ratio: 0.93 (0.59–1.46) Quitters vs. persistent smokers (referent)

Logistic regression models

Paper presented measures of association as odds 

ratios, but because they were from a prospective 

cohort study, these are RR estimates

Adjusted for sex, age, hypertension history, 

diabetes, prior MI, BMI, creatinine, PCI/CABG 

before 30 days, and medications

Table 4.21 Continued

A Report of the Surgeon General

278 Chapter 4
Study Design/population Findings: RRa (95% CI) Comments

Shah et al. 

(2010)

• SAVE trial

• 731 patients with AMI with left ventricular 

systolic dysfunction who were current 

smokers at diagnosis

• All current smokers at baseline who survived

at least 6 months

• Categorized as quitters or persistent smokers 

based on smoking status after 6 months of 

follow-up

• 463 quitters, 268 persistent smokers

• Study baseline: 1987–1990

• United States

• 42-month median follow-up

• Adjusted hazard ratio for all-cause mortality

by follow-up interval:

– 6 months: 0.57 (0.36–0.91)

– 12 months: 0.58 (0.33–0.99)

– 16 months: 0.60 (0.34–1.07)

– 24 months: 0.53 (0.25–1.08)

Quitters vs. persistent smokers (referent)

Proportional hazards regression models

Propensity score (on basis of 24 parameters) 

adjusted model

Reduction in risk started early and was 

maintained over time

Results presented combined mortality with 

MI or hospitalization for heart failure

Breitling et al. 

(2011a)

•

•

•

•

•

•

•

•

•

KAROLA study

1,062 total patients with AMI, coronary 

syndrome, coronary artery intervention 

who were current smokers at diagnosis

All results presented in table limited to 

current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at rehabilitation 

discharge

Numbers of quitters and persistent smokers 

vary by classification method

85% men, mean 59 years of age

Study baseline: 2000

Germany

8.1-year median follow-up

• Outcome was fatal or nonfatal secondary 

cardiovascular disease events (MI, ischemic 

stroke, deaths with cardiovascular disease 

as the main cause):

–

–

–

Self-report plus cotinine (169 quitters, 

154 persistent smokers): adjusted hazard 

ratio 0.38 (0.20–0.73)

Self-report plus cotinine, limited to those 

who remained quitters or persistent 

smokers throughout follow-up (101 quitters, 

98 persistent smokers): adjusted hazard 

ratio 0.17 (0.06–0.44)

Self-report only (204 quitters, 53 persistent 

smokers): adjusted hazard ratio 0.75 

(0.35–1.60)

Hazard ratio for quitters vs. persistent smokers

Results indicate that using a biomarker of 

smoking results in greater magnitude of risk 

reduction compared with self-report alone

Results indicate that magnitude of risk reduction 

is greater when maintaining abstinence

Taken in combination, these findings indicate 

that the association with quitting smoking is 

likely underestimated in most studies because 

studies of this type typically have not used 

biomarkers and continuous maintenance of 

smoking abstinence

Earlier results from this same study showing 

similar findings were included in Twardella 

and colleagues (2006)

Adjusted for sex, age, diabetes, triglycerides,

total and LDL cholesterol, and ACE inhibitor 

at discharge

Table 4.21 Continued

The Health Benefits of Smoking Cessation 279
Study Design/population Findings: RRa (95% CI) Comments

Chen et al. 

(2012)

• 8,489 patients undergoing PCI (stent

implantation) who were current smokers

at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status during follow-up 

(indeterminate timing)

• 4,440 quitters, 4,049 persistent smokers

• Study period: 2004–2010

• China

• 3.0-year median follow-up

• Adjusted hazard ratio: 0.11 (0.06–0.22) Hazard ratio for quitters vs. persistent 

smokers

Adjusted for sex, age, diabetes, prior MI, 

hypertension, hyperlipidemia, prior bypass 

surgery, unstable angina, family history of 

CHD, ejection fraction, lesion type, reference 

vessel diameter, lesion length, restenotic 

lesion, calcification, angulated/total occlusion, 

thrombus, predilation, stent length, 

and postdilation

Álvarez et al. 

(2013)

•

•

•

•

•

•

•

•

•

FRENA registry

1,182 patients who were current smokers 

at diagnosis

475 with CAD, 240 with CVD, 467 with PAD

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 4-month follow-up

512 quitters, 670 persistent smokers

Study period: 2003–2010

Spain

14-month mean follow-up

• Adjusted hazard ratio: 0.51 (0.22–1.15) Mortality ratio for quitters vs. persistent smokers

Adjusted for comorbidity, atrial fibrillation, 

medications, and creatinine clearance

de Boer et al. 

(2013)

• 497 patients undergoing PCI who were

current smokers at diagnosis and survived

at least 1 year

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 1-year follow-up

• 210 quitters, 287 persistent smokers

• Study baseline: 1980–1985

• Netherlands

• 19.5-year median follow-up, 30 years maximum

• 56 years of age average

• All cause-mortality: adjusted hazard ratio 

0.57 (0.46–0.71)

• 30-year survival: 2.1 times as high in quitters

as in persistent smokers (29% vs. 14%)

• Life expectancy: 2.1 years longer in quitters

vs. persistent smokers (18.5 vs. 16.4 years)

Adjusted hazard ratio comparing quitters plus 

nonsmokers vs. persistent smokers

Having the baseline age of the cohort combined 

with a 30-year follow-up period enabled unique 

evaluation of impact on survival; adjustments 

not clearly specified, but there appears to have 

been adjustment for sex, age, indication for PCI, 

diabetes, prior MI, hypertension, hyperlipidemia, 

prior bypass surgery, multivessel disease, clinical 

success of PCI, and family history of CHD

Table 4.21 Continued

A Report of the Surgeon General

280 Chapter 4
Study Design/population Findings: RRa (95% CI) Comments

Liu et al. (2013) •

•

•

•

•

•

•

430 male CHD patients undergoing PCI who 

were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status immediately after 

the index procedure (indeterminate)

283 quitters, 147 persistent smokers

Study baseline: 2009–2010, follow-up to 2012

China

Follow-up 27.2 months (assumed to be average)

• Risk ratio: 0.17 (0.05–0.63) Risk ratio calculated from data presented in 

Table 2 in Liu and colleagues (2013); data 

represent major clinical outcomes for persistent 

smokers, quitters, and nonsmokers

Adjusted hazard ratio comparing persistent 

smokers to quitters plus nonsmokers presented 

in Table 3 in Liu and colleagues (2013) will 

underestimate association because of inclusion 

f nonsmokers in the reference group; hazard 

ratio was 2.43 (95% CI, 1.17–5.05) after 

adjusting for age, hypertension, dyslipidemia, 

aspirin use, and statin use

Hammal et al. 

(2014)

• APPROACH registry

• 2,583 patients undergoing coronary 

angiography for CAD who were current 

smokers at diagnosis and survived at least 

1 year

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 1-year follow-up

• 1,519 quitters, 1,064 persistent smokers

• Study period: 2003–2010

• Canada

• 42.2-month mean follow-up

• 56 years of age (mean)

• Outcome all-cause mortality plus comparison

of survival:

– Total cohort (unmatched): 0.54 (0.39–0.73)

– Subgroup receiving medical treatment 

(matched): 0.59 (0.31–1.11)

– Subgroup receiving revascularization:

0.46 (0.22–0.96)

– Survival in total cohort: 95.7% in quitters vs. 

92.0% in persistent smokers

– Survival in subgroup receiving medical 

treatment: 93.0% in quitters vs. 88.0% 

in persistent smokers

– Survival in subgroup receiving

revascularization: 94.9% in quitters vs. 

88.9% in persistent smokers (p <0.05)

Quitters vs. persistent smokers

Risk ratios calculated from data presented in 

Table 7 in Hammal and colleagues (2014)

No explicit adjustments; matching was on 

basis of propensity scores

Table 4.21 Continued

The Health Benefits of Smoking Cessation 281

Notes: ACE = angiotensin-converting enzyme; AMI = acute myocardial infarction; APPROACH = Alberta Provincial Project for Outcomes Assessment in Coronary Heart 

Disease; ASSET = Anglo-Scandinavian Study of Early Thrombolysis; BMI = body mass index; CABG = coronary artery bypass grafting; CAD = coronary artery disease; 

CASS = Coronary Artery Surgery Study; CHD = coronary heart disease; CI = confidence interval; DART = Diet and Reinfarction Trial; FRENA = Factores de Riesgo y 

ENfermedad Arterial [Registry]; ISFAMI = Israel Study of First Acute Myocardial Infarction; KAROLA = Langzeiterfolge der Kardiologischen Anschlussheilbehandlung 

(Long-Term Success of Cardiologic Rehabilitation Therapy); LDL = low-density lipoprotein; MI = myocardial infarction; MILIS = Multicenter Investigation of Limitation of 

Infarct Size; OACIS = Osaka Acute Coronary Insufficiency Study; OASIS = Organization to Assess Strategies in Acute Ischemic Syndromes; PAD = peripheral artery disease; 

PCI = percutaneous coronary intervention; PTCA = percutaneous transluminal coronary angioplasty; RR = relative risk; SAVE = Sleep Apnea Cardiovascular Endpoints.

aRR unless specified otherwise.
Study Design/population Findings: RR (95% CI) Comments

Salonen (1980) •

•

•

•

•

•

•

•

523 male patients ≤65 years of age with MI

who were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 6-month follow-up

221 quitters, 302 persistent smokers

Enrollment period: 1968–1977

Finland

3-year follow-up

• 1.7 (1.1–2.6) Persistent smokers vs. quitters (referent) 

Unadjusted rate ratios

Daly et al. (1983) • 374 patients with unstable angina or MI

• who were current smokers at diagnosis and 

survived at least 2 years

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 2-year follow-up

• 217 quitters, 157 persistent smokers

• Enrollment period: 1974–1979

• Ireland

• 7.4-year mean follow-up, 13-year follow-up after 

smoking status defined

• 2.8 (p <0.01) Persistent smokers vs. quitters (referent)

Mortality ratios calculated from average annual 

mortality rates

Unadjusted rate ratios

Presented survival plots and p values only from 

Cox proportional hazards regression models

Johansson et al. 

(1985)

•

•

•

•

•

•

•

•

156 female patients with MI who were current 

smokers at diagnosis and survived at least

3 months

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 3 months of 

follow-up

81 quitters, 75 persistent smokers

Study period: 1968–1977

Ireland

7.4-year mean follow-up, 13-year follow-up 

after smoking status defined

•

•

Unadjusted: 2.3 (1.2–4.4)

Fully adjusted: 2.7 (CI not presented)

Persistent smokers vs. quitters (referent) 

Unadjusted rate ratios

Cox proportional hazards models; fully adjusted 

model included mean peak SAST, Q waves, and 

angina pectoris known before the infarction

Presented survival plots

Example of adjustment resulting in stronger 

association

A Report of the Surgeon General

282 Chapter 4

Table 4.22 Summary of results from prospective cohort studies of patients with coronary heart disease who were cigarette smokers at diagnosis, 

comparing all-cause mortality in those who remained persistent smokers with those who quit smoking
Study Design/population Findings: RR (95% CI) Comments

Vliestra et al. 

(1986)

• CASS

• 4,165 patients with angiographically confirmed 

CAD who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at time of diagnosis

• 1,490 quitters, 2,675 persistent smokers

• Enrollment period: 1975–1977

• United States (15 clinical sites)

• 5-year follow-up results presented 

• 1.55 (1.29–1.85) Persistent smokers vs. quitters (referent)

Quitters had a worse prognostic profile than 

persistent smokers at baseline

The definition of persistent smoker was selfreported smoking at every follow-up

The definition of quitter was someone who 

quit 1 year before study entry and reported 

not smoking at every follow-up

Cox proportional hazards models using a 

propensity-score approach to adjust for covariates

Propensity-score adjustment approach on basis 

of the following variables: age, sex congestive 

heart failure score, left ventricular wall motion 

score, CAGE 50, surgery, left ventricular enddiastolic blood pressure, hypertension, diabetes, 

Gensini score, prior MI, degree of functional 

impairment because of congestive heart failure, 

left main coronary stenosis of ≥50%

Hermanson 

et al. (1988)

•

•

•

•

•

•

•

•

CASS

1,893 patients with CAD who were current 

smokers at diagnosis

All current smokers at baseline

Categorized as quitters based on quitting 

smoking within 1 year before the baseline 

angiogram

807 quitters, 1,086 persistent smokers

Enrollment period: 1974–1979

United States

Average follow-up: 5.3 years

•

•

All-cause mortality, total: 1.7 (1.4–2.0)

All-cause mortality stratified by age 

group (years):

–

–

–

–

–

–

55–64: 1.7 (1.4–2.1)

≥70: 1.6 (1.1–2.3)

55–59: 1.5 (1.1–2.0)

60–64: 2.0 (1.5–2.6)

65–69: 1.4 (0.9–2.0)

≥70: 3.3 (1.5–7.1)

Persistent smokers vs. quitters (referent)

Hazard ratios

Same CASS as in Vliestra and colleagues (1986)

Presented age-specific associations

Table 4.22 Continued

The Health Benefits of Smoking Cessation 283
Study Design/population Findings: RR (95% CI) Comments

Peters et al. 

(1995)

• CAST I and CAST II

• 1,026 patients with left ventricular dysfunction 

after MI who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 4-month follow-up

• 517 quitters, 509 persistent smokers

• Enrollment period: 1987–1991

• United States

• 15.5-month mean follow-up

• 1.64 (0.97–2.79) Persistent smokers vs. quitters (referent)

Cox proportional hazards regression models 

using smoking as a time-dependent covariate

Adjusted for sex, age, angina, heart failure, 

ejection fraction, history of MI, diabetes, 

hypertension, history of coronary artery 

angioplasty or bypass grafts, history of 

diabetes, history of congestive heart failure, 

CAST treatment condition, angina, use of 

thrombolytic agents during qualifying MI, 

and other study-specific treatment variables

Voors et al. 

(1996)

•

•

•

•

•

•

•

167 patients with coronary bypass surgery who 

were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 1 year of follow-up

72 quitters, 95 persistent smokers

Enrollment period: 1976–1977

Netherlands

15 years of follow-u

• 0.9 (0.5–1.6) Persistent smokers vs. quitters (referent) 

Cox proportional hazards regression models

This result is for the complete follow-up period 

from 1 year to 15 years after surgery

In Table 6 in Voors and colleagues (1996), the 

result for 5 to 15 years after surgery was an RR of 

1.7 (95% CI, 0.8–3.5) adjusted for sex, age, plus 

the following variables if p <0.10 (unclear from 

text which variables met this criterion): obesity; 

elevated cholesterol and triglyceride levels; 

angina; heart failure; ejection fraction; history 

of MI, diabetes, and/or hypertension; family 

history of CAD, diabetes, and/or congestive

heart failure; and number of vessels diseased 

and other characteristics of index diagnosis

Hasdai et al. 

(1997)

• 1,169 patients who had undergone successful 

percutaneous coronary revascularization who 

were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status during follow-up

• 435 quitters, 734 persistent smokers

• Study period: 1979–1995

• United States

• 4.5-year mean follow-up, 16-year maximum

• 1.44 (1.02–2.11) Persistent smokers vs. quitters (referent) 

Proportional hazards models

Adjusted for significant differences in 

baseline variables

Unclear which variables were included in the 

model, but baseline variables included sex, age, 

angina, heart failure, ejection fraction, diabetes, 

hypertension, and family history of CAD

Table 4.22 Continued

A Report of the Surgeon General

284 Chapter 4
Study Design/population Findings: RR (95% CI) Comments

van Domburg 

et al. (2000)

•

•

•

•

•

•

•

556 patients who had undergone CABG surgery 

who were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status >1 year after CABG 

(median 2.8 years)

238 quitters, 318 persistent smokers

Study period: 1971–1980

Netherlands

20-years median follow-up (range 13–26 years)

• 1.68 (1.33–2.13) Persistent smokers vs. quitters (referent)

Proportional hazards models

Adjusted for sex, age, vessel disease, ejection 

fraction, and complete revascularization

Zhang et al. 

(2015)

• SYNTAX

• 1,793 patients with complex CAD who were 

current smokers at diagnosis

• Use of time-dependent covariates may have 

included all participants (never, former, and 

current smokers at baseline)

• Smoking categorized at 6 months, 1 year, 

3 years, and 5 years of follow-up

• Indeterminate study period

• Multicenter, multinational study

• 5 years of follow-up

• 1.80 (1.27–2.54) Smoking status analyzed as a time-dependent 

covariate

Cox proportional hazards regression models 

Composite endpoint of death/MI/stroke

Never precisely specified, but this estimate 

likely included the total study population, 

including never smokers and former smokers 

as well as current smokers at baseline

Assume adjusted for other independent 

predictors listed in Table 3 in Zhang and 

colleagues (2015): PCI vs. CABG, age, COPD, 

PVD, LVEF <30%, amiodarone therapy on 

discharge (never specified in text)

Table 4.22 Continued

Notes: CABG = coronary artery bypass grafting; CAD = coronary artery disease; CAGE 50 = number of segments with coronary artery stenosis ≥50%; CASS = Coronary 

Artery Surgery Study; CAST = Cardiac Arrhythmia Suppression Trial; CI = confidence interval; COPD = chronic obstructive pulmonary disease; LVEF = left ventricular 

ejection fraction; MI = myocardial infarction; PVD = peripheral vascular disease; PCI = percutaneous coronary intervention; RR = relative risk; SAST = serum aspartate 

amino transferase; SYNTAX = SYNergy between Percutaneous Coronary Intervention with TAXus and Cardiac Surgery Trial.

The Health Benefits of Smoking Cessation 285
Study Design/population Findings: RR (95% CI) Comments

Wilhelmsson 

et al. (1975)

•

•

•

•

•

•

•

405 male patients with first MI who were 

current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 3 months 

following MI

231 quitters, 174 persistent smokers

Study period: 1968–1972

Sweden

2-year follow-up results presented

• Cardiovascular death: 2.05 (0.99–4.27) Persistent smokers vs. quitters (referent)

Unadjusted risk ratios

Risk ratio calculated using the data presented in 

Table 5 in Wilhelmsson and colleagues (1975)

Salonen (1980) • 523 male patients ≤65 years of age with MI

• who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 6-month follow-up

• 221 quitters, 302 persistent smokers

• Enrollment period: 1968–1977

• Finland

• 3-year follow-up

• Ischemic heart disease: 1.6 (1.0–2.7)

• Other cardiovascular disease: 1.5 (0.3–8.0)

Persistent smokers vs. quitters (referent) 

Unadjusted risk ratios

Mulcahy et al. 

(1982)

•

•

•

•

•

•

•

517 male patients <60 years of age with first 

diagnosis of unstable angina or MI who were 

current smokers at diagnosis

All current smokers at baseline

Categorized as quitters based on stopping 

smoking at least 3 months before the last 

follow-up or death (indeterminate timing)

282 quitters, 235 persistent smokers

Enrollment period: 1961–1975, with follow-up 

through 1979

Ireland

99-month mean follow-up (survivors)

•

•

•

Cardiac failure: 2.70 (0.84–8.66)

Sudden death: 1.77 (1.23–2.54)

Fatal MI: 1.68 (1.04–2.72)

Persistent smokers vs. quitters (referent)

Unadjusted risk ratios

Risk ratio calculated using data presented in 

Table 2 in Mulcahy and colleagues (1982)

A Report of the Surgeon General

286 Chapter 4

Table 4.23 Summary of results from prospective cohort studies of patients with coronary heart disease who were cigarette smokers at diagnosis, 

comparing cause-specific mortality from cardiac endpoints and sudden death in those who remained persistent cigarette smokers with 

those who quit smoking
Study Design/population Findings: RR (95% CI) Comments

Daly et al. (1983) • 374 patients with unstable angina or MI

• who were current smokers at diagnosis and 

survived at least 2 years

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 2-year follow-up

• 217 quitters, 157 persistent smokers

• Enrollment period: 1974–1979

• Ireland

• 7.4-year mean follow-up, 13-year follow-up 

after smoking status defined

• Vascular causes: 2.4 (p <0.01)

• Fatal reinfarction: 2.6 (p = 0.02)

• Sudden death: 1.6 (p = 0.14)

Persistent smokers vs. quitters (referent) 

Unadjusted risk ratios

Mortality ratios based on average annual 

mortality rates

Presented survival plots and p values only from 

Cox proportional hazards regression models

Rønnevik et al. 

(1985)

•

•

•

•

•

•

•

453 patients with first-time diagnosis of acute 

MI who were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status after MI with 

continued follow-up (indeterminate time)

276 quitters, 177 persistent smokers

Enrollment period: 1978–1979

Norway

Mean follow-up 17.3 months

• Cardiac causes (placebo group): 1.17 

(0.62–2.22)

Persistent smokers vs. quitters (referent) 

Unadjusted risk ratios

Risk ratio calculated from data presented in 

Table 3 in Rønnevik and colleagues (1985)

Results presented limited to the placebo group 

because of an observed interaction of the 

treatment (timolol) with smoking

Hallstrom et al. 

(1986)

• 310 patients with cardiac arrest who were 

current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status 2 months or less 

after cardiac arrest

• 91 quitters, 219 persistent smokers

• Study period: 1970–1981

• United States

• Mean follow-up 47.5 months

• Cardiac arrest: 1.55 (0.98–2.45) Persistent smokers vs. quitters (referent)

Unadjusted risk ratios

Risk ratio calculated from data presented on 

page 272 in Hallstrom and colleagues (1986)

The Health Benefits of Smoking Cessation 287

Table 4.23 Continued
Study Design/population Findings: RR (95% CI) Comments

Vliestra et al. 

(1986)

•

•

•

•

•

•

•

•

CASS Trial

4,165 patients with angiographically confirmed 

coronary artery disease who were current 

smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at time of diagnosis

1,490 quitters, 2,675 persistent smokers

Enrollment period: 1975–1977

United States (15 clinical sites)

5-year follow-up results presented

•

•

•

Cardiac contributing: 1.60 (0.89–2.86)

Sudden death: 1.82 (1.14–2.89)

MI: 1.78 (1.36–2.33)

Persistent smokers vs. quitters (referent)

Cox proportional hazards models using a 

propensity score approach to adjust for covariates

Quitters had a worse prognostic profile than 

persistent smokers at baseline

The definition of persistent smoker was selfreported smoking at every follow-up; the 

definition of a quitter was someone who had 

quit 1 year before study entry and reported 

not smoking at every follow-up

Propensity-score adjustment approach based 

on age, sex, congestive heart failure score, 

left ventricular wall motion score, CAGE 50, 

surgery, left ventricular end-diastolic blood

pressure, hypertension, diabetes, Gensini score, 

prior MI, degree of functional impairment 

because of congestive heart failure, left main 

coronary stenosis of ≥50%

Hermanson 

et al. (1988)

• CASS

• 1,893 patients with CAD who were current 

smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters based on quitting 

smoking within 1 year before the baseline 

angiogram

• 807 quitters, 1,086 persistent smokers

• Study period: 1974–1979 (enrollment)

• United States

• Average follow-up 5.3 years

• Cardiac causes: 1.37 (p = .001) Persistent smokers vs. quitters (referent) 

Hazard ratios

Overall and stratified by age group 

Same CASS as in Vliestra et al. (1986)

Risk ratio calculated from data presented on 

page 1,367 of Hermanson and colleagues (1988)

Table 4.23 Continued

A Report of the Surgeon General

288 Chapter 4
Study Design/population Findings: RR (95% CI) Comments

Gupta et al. 

(1993)

•

•

•

•

•

•

•

225 patients with CHD who were current 

smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status since the time of 

diagnosis of CAD (indeterminate)

173 quitters, 52 persistent smokers

Study baseline: 1980

India

~ 6-year average follow-up

• Sudden death: 1.48 (0.81–2.71) Persistent smokers vs. quitters (referent)

Unadjusted risk ratios

Risk ratio calculated from data presented on 

page 127 of Gupta and colleagues (1993)

Peters et al. 

(1995)

• CAST I and CAST II

• 1,026 patients with left ventricular dysfunction 

after MI who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 4-month follow-up

• 517 quitters, 509 persistent smokers

• Enrollment period: 1987–1991

• United States

• 15.5-month mean follow-up

• Arrhythmic mortality: 1.80 (0.88–3.67) Persistent smokers vs. quitters (referent)

Cox proportional hazards regression models 

using smoking as a time-dependent covariate

Adjusted for sex, age, angina, heart failure, 

ejection fraction, history of MI, diabetes, 

hypertension, history of coronary artery 

angioplasty or bypass grafts, history of 

diabetes, history of congestive heart failure, 

CAST treatment condition, angina, use of 

thrombolytic agents during qualifying MI, 

and other study-specific treatment variables

Hasdai et al. 

(1997)

•

•

•

•

•

•

•

1,169 patients who had undergone successful 

percutaneous coronary revascularization who 

were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status during follow-up

435 quitters, 734 persistent smokers

Study period: 1979–1995

United States

4.5-year mean follow-up, 16 years maximum

• Cardiac causes: 1.49 (0.89–2.51) Persistent smokers vs. quitters (referent)

Proportional hazards models 

Adjusted for significant differences in 

baseline variables 

Unclear which variables were included in the

model, but baseline variables included sex, age, 

angina, heart failure, ejection fraction, diabetes, 

hypertension, and family history of CAD

Table 4.23 Continued

The Health Benefits of Smoking Cessation 289
Study Design/population Findings: RR (95% CI) Comments

vanDomburg 

et al. (2000)

• 556 patients who had undergone CABG surgery 

who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status >1 year after CABG 

(median 2.8 years)

• 238 quitters, 318 persistent smokers

• Study period: 1971–1980

• Netherlands

• 20-year median follow-up (range 13–26 years)

• Cardiac causes: 1.75 (1.30–2.37) Persistent smokers vs. quitters (referent)

Proportional hazards models

Adjusted for sex, age, vessel disease, ejection 

fraction, and complete revascularization

Liu et al. (2013) •

•

•

•

•

•

•

•

430 male CHD patients undergoing

percutaneous coronary intervention who were 

current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status immediately after the 

index procedure (indeterminate)

283 quitters, 147 persistent smokers

Study baseline: 2009–2010, follow-up to 2012

China

Follow-up 27.2 months (assumed to be average)

• Cardiac causes: 7.7 (0.9–68.8) Persistent smokers vs. quitters (referent)

Risk ratio calculated from data presented in 

Table 2 in Liu and colleagues (2013)

Table 4.23 Continued

A Report of the Surgeon General

290 Chapter 4

Notes: CABG = coronary artery bypass grafting; CAD = coronary artery disease; CAGE 50 = number of segments with coronary artery stenosis ≥50%; CASS = Coronary Artery 

Surgery Study; CAST = Cardiac Arrhythmia Suppression Trial; CHD = coronary heart disease; CI = confidence interval; MI = myocardial infarction; RR = relative risk.
Study Design/population Findings: RR (95% CI) Comments

Wilhelmsson 

et al. (1975)

•

•

•

•

•

•

•

405 male patients with first MI who were 

current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 3 months 

following MI

231 quitters, 174 persistent smokers

Study period: 1968–1972

Sweden

2-year follow-up results presented

• Reinfarction: 0.49 (0.29–0.82) Persistent smokers vs. quitters (referent) 

Unadjusted risk ratios

Risk ratio calculated based on the data presented 

in Table 5 in Wilhelmsson and colleagues (1975)

Sparrow and 

Dawber (1978)

• Framingham Study

• 195 patients with MI who were current 

smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status after data collection 

immediately preceding and following MI 

(indeterminate timing)

• 56 quitters, 139 persistent smokers

• Cohort established 1949: 22 years of follow-up 

through 1978

• United States

• 6-year follow-up results presented

• Reinfarction: 0.76 (0.37–1.58) Persistent smokers vs. quitters (referent) 

Unadjusted risk ratios

Risk ratio calculated based on data presented 

on page 430 in Sparrow and Dawber (1978)

Aberg et al. 

(1983)

•

•

•

•

•

•

•

983 male patients with first MI who were 

current smokers at diagnosis 

All current smokers at baseline 

Categorized as quitters or persistent smokers 

based on smoking status at 3-month follow-up 

542 quitters, 441 persistent smokers 

Enrollment period: 1968–1977 

Sweden 

10.5-year maximum follow-up

• Reinfarction: 0.67 (0.53–0.84) Persistent smokers vs. quitters (referent) 

Unadjusted risk ratios

Risk ratio calculated from data presented in 

Table 7 in Aberg and colleagues (1983)

The Health Benefits of Smoking Cessation 291

Table 4.24 Summary of results from prospective cohort studies of patients with coronary heart disease who were cigarette smokers at diagnosis, 

comparing incidence of cardiac endpoints in those who remained persistent cigarette smokers with those who quit smoking or vice versa
Study Design/population Findings: RR (95% CI) Comments

Perkins and Dick 

(1985)

• 119 patients with first-time diagnosis of MI 

who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent 

smokers based on smoking status after MI 

(indeterminate time)

• 52 quitters, 67 persistent smokers

• Enrollment period: 1974–1977

• United Kingdom

• 5-year follow-up

• Reinfarction: 3.87 (0.81–18.37) Persistent smokers vs. quitters (referent)

Unadjusted risk ratios

Risk ratio calculated from data presented in 

Table II in Perkins and Dick (1985)

Rønnevik et al. 

(1985)

•

•

•

•

•

•

•

453 patients with first-time diagnosis of acute 

MI who were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status after MI based on 

continued follow-up (indeterminate time)

276 quitters, 177 persistent smokers

Enrollment period: 1978–1979

Norway

Mean follow-up 17.3 months

• MI: 0.54 (0.32–0.93) Persistent smokers vs. quitters (referent) 

Unadjusted risk ratios

Results presented limited to the placebo group 

because of an observed interaction of treatment 

(timolol) with smoking

Risk ratio calculated from data presented in 

Table 3 in Rønnevik and colleagues (1985)

Table 4.24 Continued

A Report of the Surgeon General

292 Chapter 4
Study Design/population Findings: RR (95% CI) Comments

Vliestra et al. 

(1986)

• CASS

• 4,165 patients with angiographically confirmed 

CAD who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at time of diagnosis

• 1,490 quitters, 2,675 persistent smokers

• Enrollment period: 1975–1977

• United States (15 clinical sites)

• 5-year follow-up results presented

• 5-year MI hospitalization: 0.63 (0.51–0.78) Persistent smokers vs. quitters (referent)

Cox proportional hazards models using a 

propensity score approach to adjust for covariates

Propensity-score adjustment approach on basis 

of the following variables: age, sex, congestive 

heart failure score, left ventricular wall motion 

score, CAGE 50, surgery, left ventricular enddiastolic blood pressure, hypertension, diabetes, 

Gensini score, prior MI, degree of functional 

impairment because of congestive heart failure, 

left main coronary stenosis of ≥50%

Quitters had a worse prognostic profile than 

persistent smokers at baseline

The definition of persistent smoker was selfreported smoking at every follow-up; the 

definition of a quitter was someone who had 

quit 1 year before study entry and reported 

not smoking at every follow-up

Herlitz et al. 

(1995)

•

•

•

•

•

•

•

•

217 patients with acute MI who were current 

smokers at diagnosis and survived at least

1 year

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status after 1 year of 

follow-up

115 quitters, 102 persistent smokers

Enrollment period: 1986–1987

Sweden

4-year follow-up results presented

• Reinfarction: 0.99 (0.42–2.33) Persistent smokers vs. quitters (referent) 

Unadjusted risk ratios

Risk ratio calculated from data presented in 

Table 4 in Herlitz and colleagues (1995)

Table 4.24 Continued

The Health Benefits of Smoking Cessation 293
Study Design/population Findings: RR (95% CI) Comments

Voors et al. 

(1996)

• 167 patients with coronary bypass surgery 

who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 1 year of follow-up

• 72 quitters, 95 persistent smokers

• Enrollment period: 1976–1977

• Netherlands

• 15 years of follow-up

• MI: 2.3 (1.1–5.1)

• Reoperation: 2.5 (1.1–5.9)

• Angina:

– 1–15 years post-surgery: 1.2 (0.8–1.7)

– 5–15 years post-surgery: 2.0 (1.1–3.6

Persistent smokers vs. quitters (referent) 

Cox proportional hazards regression models

Adjusted for sex, age, plus the following variables 

if p <0.10 (unclear from text which variables 

met this criterion): obesity, diabetes, elevated 

cholesterol and triglyceride levels, hypertension, 

history of heart failure, preoperative angina 

pectoris, family history of CAD, number of vessels 

diseased, completeness of revascularization, 

number of distal anastomoses, left ventricular 

function, history of MI, indication for operation, 

presence of collateral arteries, left main CAD, and 

proximal left anterior descending artery disease

Hasdai et al. 

(1997)

•

•

•

•

•

•

•

1,169 patients who had undergone successful 

percutaneous coronary revascularization who 

were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status during follow-up

435 quitters, 734 persistent smokers

Study period: 1979–1995

United States

4.5-year mean follow-up, 16 years maximum

• MI: 0.68 (.54–.86) Quitters vs. persistent smokers (referent) 

Proportional hazards model

Never smokers were used as the referent for 

estimating the RRs; 0.68 was the RR of MI for 

quitters vs. never smokers, and 1.44 (1.02–2.11) 

was the RR for death for persistent smokers vs. 

never smokers

Adjusted for significant differences in 

baseline variables

Unclear which variables were included in the 

model, but baseline variables included sex, age, 

angina, heart failure, ejection fraction, diabetes, 

hypertension, and family history of CAD

A Report of the Surgeon General

294 Chapter 4

Table 4.24 Continued
Study Design/population Findings: RR (95% CI) Comments

van Domburg 

et al. (2000)

• 556 patients who had undergone CABG surgery 

who were current smokers at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status >1 year after CABG 

(median 2.8 years)

• 238 quitters, 318 persistent smokers

• Study period: 1971–1980

• Netherlands

• 20-year median follow-up (range 13–26 years)

• Repeat CABG/PTCA: 1.41 (1.02–1.94) Persistent smokers vs. quitters (referent)

Proportional hazards models

Adjusted for sex, age, vessel disease, ejection 

fraction, and complete revascularization

Chow et al. 

(2010)

•

•

•

•

•

•

•

•

OASIS trial

4,324 patients with unstable angina or MI 

who were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status after 30 days of 

follow-up

2,802 quitters, 1,522 persistent smokers

Study baseline: 2003–2005

41 countries

6-month follow-up

•

•

MI: 0.57 (0.36–0.89)

Stroke: 0.40 (0.14–1.17)

Quitters vs. persistent smokers (referent) 

Logistic regression models

Paper presented measures of association as odds 

ratios, but for this prospective cohort study, 

these were converted to RR

Adjusted for sex, age, hypertension history, 

diabetes, prior MI, BMI, creatinine, PCI/CABG 

before 30 days, and medications

Chen et al. 

(2012)

• 8,489 patients undergoing PCI (stent 

implantation) who were current smokers 

at diagnosis

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status during follow-up 

(indeterminate timing)

• 4,440 quitters, 4,049 persistent smokers

• Study period: 2004–2010

• China

• 3.0-year median follow-up

• Repeat revascularization: 1.59 (1.36–1.85) Hazard ratio for quitters vs. persistent smokers

Adjusted for sex, age, diabetes, prior MI, 

hypertension, hyperlipidemia, prior bypass 

surgery, unstable angina, family history of 

CHD, ejection fraction, lesion type, reference 

vessel diameter, lesion length, restenotic 

lesion, calcification, angulated/total occlusion, 

thrombus, predilation, stent length, 

and postdilation

The Health Benefits of Smoking Cessation 295

Table 4.24 Continued
Study Design/population Findings: RR (95% CI) Comments

Álvarez et al. 

(2013)

•

•

•

•

•

•

•

•

•

FRENA registry

1,182 patients who were current smokers

at diagnosis

475 with CAD, 240 with CVD, 467 with PAD

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status at 4-month follow-up

512 quitters, 670 persistent smokers

Study period: 2003–2010

Spain

14-month mean follow-up

• MI: 0.70 (0.26–1.88) Mortality ratio for quitters vs. persistent smokers 

Adjusted for comorbidity, atrial fibrillation, 

medications, and creatinine clearance 

Choi et al. 

(2013)

• Prospective cohort

• 275 patients who were current smokers at 

diagnosis of MI

• All current smokers at baseline

• Categorized as quitters or persistent smokers 

based on smoking status at 4-month follow-up

• 144 quitters, 131 persistent smokers

• Study period: 1999–2008

• South Korea

• Regularly followed for 1 year after MI

• Re-intervention or MI: 2.9 (0.2–33.0) Persistent smokers vs. quitters (referent)

Risk ratio for re-intervention or MI

Not clear that the estimate was adjusted for 

any factors

Liu et al. (2013) •

•

•

•

•

•

•

•

430 male CHD patients undergoing PCI who

were current smokers at diagnosis

All current smokers at baseline

Categorized as quitters or persistent smokers 

based on smoking status immediately after the 

index procedure (indeterminate)

283 quitters, 147 persistent smokers

Study baseline: 2009–2010, follow-up to 2012

China

Follow-up 27.2 months (assumed to be average)

•

•

Revascularization: 2.89 (1.05–8.0)

MI:

–

–

1.4% in persistent smokers

0% in quitters

• RR for quitters vs. persistent = 0.0

Persistent smokers vs. quitters (referent)

Risk ratio calculated from data presented in 

Table 2 in Liu and colleagues (2013)

Adjusted hazard ratio comparing persistent 

smokers to quitters plus nonsmokers presented 

in Table 3 in Liu and colleagues (2013) will 

underestimate association because of inclusion 

of nonsmokers in the referent

Hazard ratio was 2.43 (95% CI, 1.17–5.05) after 

adjusting for age, hypertension, dyslipidemia, 

aspirin use, and statin use

Table 4.24 Continued

A Report of the Surgeon General

Notes: BMI = body mass index; CABG = coronary artery bypass grafting; CAD = coronary artery disease; CAGE 50 = number of segments with coronary artery stenosis ≥50%;

CASS = Coronary Artery Surgery Study; CHD = coronary heart disease; CI = confidence interval; CVD = cardiovascular disease; FRENA = Factores de Riesgo y ENfermedad

Arterial [Registry]; MI = myocardial infarction; OASIS = Organization to Assess Strategies in Ischemic Syndromes; PAD = peripheral artery disease; PCI = percutaneous 

coronary intervention; PTCA = percutaneous transluminal coronary angioplasty; RR = relative risk.

296 Chapter 4
The Health Benefits o

Figure 4.4 Relative risk for all-cause mortality after cardiac event among those who were current smokers when diagnosed, b

Study Relative risk (95% CI)Quit vs. persistent

Wilhemsson et al. 1975 0.51 (0.27–0.96)Sparrow et al. 1978 0.62 (0.33–1.15)Baughman et al. 1982 0.35 (0.18–0.66)Mulcahy et al. 1982 0.59 (0.47–0.73)Aberg et al. 1983 0.63 (0.50–0.79)Perkins et al. 1985 0.39 (0.20–0.74)Rønnevik et al. 1985 0.74 (0.42–1.30)Hallstrom et al. 1986 0.79 (0.50–1.06)Burr et al. 1992 0.52 (0.32–0.83)Cavender et al. 1992 0.63 (0.40–0.97)Gupta et al. 1993 0.70 (0.49–1.01)Tofler et al. 1993 0.48 (0.31–0.73)Greenwood et al. 1995 0.56 (0.33–0.98)Herlitz et al. 1995 0.55 (0.34–0.91)Kinjo et al. 2005 0.39 (0.20–0.77)Gerber et al. 2009 0.63 (0.48–0.82)Chow et al. 2010 0.93 (0.59–1.46)Shah et al. 2010 0.57 (0.36–0.91)Breitling et al. 2011 0.38 (0.20–0.73)Chen et al. 2012 0.11 (0.06–0.22)Álvarez et al. 2013 0.51 (0.22–1.15)de Boer et al. 2013 0.57 (0.46–0.71)Liu et al. 2013 0.17 (0.05–0.63)Hammal et al. 2014 0.54 (0.39–0.73)

Persistent vs. quit

Salonen et al. 1980 1.70 (1.10–2.60)Johansson et al. 1985 2.30 (1.20–4.40)Vliestra et al. 1986 1.55 (1.29–1.85)Hermanson et al. 1988 1.70 (1.40–2.00)Peters et al. 1995 1.64 (0.97–2.79)Voors et al. 1996 0.90 (0.50–1.60)Hasdai et al. 1997 1.44 (1.02–2.11)van Domburg et al. 2000 1.68 (1.33–2.13)Zhang et al. 2015 1.80 (1.27–2.54) 

Note: CI = confidence interval.
A Report of the Surgeon General

298 Chapter 4

the association between cessation and mortality compared 

with classification of smoking by both self-reported and 

biomarker data. These results replicated previous findings 

from this research group (Twardella et al. 2006). Because 

most findings are based on self-reported smoking status, 

the pattern of associations in comparisons of self-reported 

with biomarker-based classification suggests that the 

associations observed in studies that rely on self-reported 

smoking may be underestimated because of the misclassification from self-reports. 

Table 4.22 summarizes studies in cohorts of patients 

with CHD that assessed the association between smoking 

cessation and all-cause mortality by comparing persistent 

smokers with quitters as the reference group; the lower 

portion of Figure 4.4 presents a forest plot for the nine 

reports that included an RR and a 95%  CI. Among the 

10 reports from the 9 studies detailed in Table 4.22, all but 

1 report showed an RR estimate of 1.44 or greater for persistent smokers. As can be seen in the forest plot, seven of 

the nine RR estimates it contains were statistically significant. The median RR was 1.67, indicative of an increase 

of two-thirds in the all-cause mortality rate in persistent 

smokers compared with quitters.

Taken together, the results of the studies summarized in Tables 4.21 and 4.22 and in Figure 4.4 show very 

clear, consistent, and strong associations. In total, 97% 

(31/32) of the studies reported associations indicating that 

smoking cessation was associated with a reduction in allcause mortality when compared with persistent smoking. 

These associations were statistically significant in 78% 

(25/32) of the studies—a high proportion, given that 

25% (8/32) of the studies had total samples of fewer than 

300  patients and the median follow-up period was only 

4.5 years. These results align closely with the results of 

meta-analyses published in 1999 (van Berkel et al. 1999) 

and in 2003 (Critchley and Capewell 2003) that reported 

summary RRs in quitters versus persistent smokers of 

0.62  (95%  CI, 0.57–0.68) (van  Berkel et  al. 1999) and 

0.64 (95% CI, 0.58–0.71) (Critchley and Capewell 2003), 

respectively. When these associations are viewed from 

the reverse perspective of comparing persistent smokers 

with quitters, they are of a magnitude similar to the association of smoking with all-cause mortality in general 

cohorts, as reported in the 2014 Surgeon General’s report 

(USDHHS 2014).

A central issue in assessing this body of evidence 

is that among current cigarette smokers diagnosed with 

CHD, those who quit may differ from persistent smokers 

in ways that could generate an apparent benefit of smoking 

cessation that reflects confounding. Many of the associations presented in the evidence tables in the present 

report are not adjusted for any potential confounding variables. The results in Table 4.21 that begin with the study 

of Kinjo and colleagues (2005) and then go up through a 

2014 report were estimated mainly with Cox proportional 

hazard models that adjusted for a wide range of potential 

confounding variables. These 10 studies had RR estimates 

that ranged from 0.11 to 0.93, with a median of 0.52. Only 

3  of the 17  RR estimates were 0.63  or higher, and the 

3 lowest RRs equaled 0.11 (once) and 0.17 (twice), with 

those results indicating a very strong protective effect for 

quitting. Notably, the studies that compared the characteristics of quitters with persistent smokers found that 

quitters tended to be older and to have a predominance 

of other characteristics associated with a worse prognosis. This pattern could lead to confounding that would 

diminish a true association.

The presence of confounding is supported by the 

increased association observed in some studies that 

adjusted for potential confounding variables. For example, 

in the study by Johansson and colleagues (1985), which 

compared persistent smokers with quitters, the unadjusted RR of death was 2.3 for the persistent smokers, 

and after adjustment for the key prognostic factors that 

differed between persistent smokers and quitters, the RR 

increased to 2.7 (Table 4.22). Thus, confounding appears 

an unlikely explanation for the finding of reduced all-cause 

mortality in quitters versus persistent smokers among 

those who were current smokers at the time of diagnosis 

with a cardiac condition. In contrast, it could be helpful 

in explaining the results of studies in which quitters, not 

persistent smokers, were the referent. 

Concerns about confounding can be further 

addressed by analyzing evidence from studies of smoking 

cessation interventions that provide evidence to address 

this issue. For example, in an observational cohort study 

of 13,815  patients diagnosed with MI who were current 

smokers discharged alive from the hospital, those who 

received an inpatient smoking cessation intervention were 

compared with those who did not receive this intervention (Bucholz et al. 2017). At 30 days of follow-up, those 

who received the intervention had significantly reduced 

all-cause mortality (hazard ratio [HR]  =  0.77; 95%  CI, 

0.62–0.96), and this benefit persisted even after 17 years 

of follow-up (HR = 0.93; 95% CI, 0.89–0.96) after adjustment for a wide range of potential confounding variables. 

Elsewhere, in a randomized controlled trial of an 

intensive smoking cessation intervention (n = 109) compared with usual care (n = 100) in a population of 30- to 

75-year-olds diagnosed with acute cardiovascular disease, after 2 years of follow-up the intervention group had 

4.3 times the proportion of continuous abstinence from 

smoking compared with the usual-care group (Mohiuddin 

et al. 2007). During this same 2-year interval, compared 

with the usual-care group, the intervention group experienced a 44% reduction in hospitalizations (RR = 0.56; 
The Health Benefits of Smoking Cessation 299

Smoking Cessation

95% CI, 0.37–0.85) and a reduction of more than threequarters in all-cause mortality (RR = 0.23; 95% CI, 0.07–

0.79) (Mohiuddin et al. 2007). Given the randomized trial 

design, this study provides experimental evidence of the 

association between smoking cessation and reduced fatal 

and nonfatal outcomes. Associations of this magnitude 

from a high-quality experimental study with relatively 

short-term follow-up provide strong evidence supporting 

an immediate and direct benefit of quitting and greatly 

reduce the likelihood that uncontrolled confounding 

explains the results of the observational studies.

Smoking Cessation and Cause-Specific 

Mortality in Cardiac Patients

The indication of a strong inverse association 

between smoking cessation and all-cause mortality after 

patients are diagnosed with CHD raises a question as to 

which causes of death are affected. Table  4.23 presents 

20 specific associations comparing persistent smokers to 

quitters from 13 studies of cohorts of patients with CHD 

that assessed smoking cessation in relation to causespecific mortality; these studies focused on either specific 

cardiac endpoints or sudden death. The 16 RR estimates 

with CIs are summarized in forest plots in Figure 4.5. 

The results shown in Figure  4.5 are stratified by 

cause-of-death groups, with “cardiac” and “cardiac contributing” comprising the largest group (n = 9 data points), 

followed by sudden death (n = 3 data points), fatal reinfarction (n = 2 data points), and 1 each for ischemic heart 

disease and arrhythmic mortality. The visual impression 

of consistently strong associations shown in Figure 4.5 is 

reinforced by the complete evidence in Table 4.23, as all 

20 associations presented in the table indicate increased 

risk associated with persistent smoking, with RRs ranging 

from 1.17 to 7.70, with a median of 1.60. The RRs were 

statistically significant in 45% (9/20), a smaller proportion than observed for all-cause mortality; because the 

magnitudes of the RRs were similar for all-cause and 

cause-specific mortality, the reduced statistical precision 

due to the smaller numbers of deaths for cause-specific 

compared with all-cause mortality likely explains the 

lower proportion of significant estimates. This body of evidence demonstrates that in current smokers diagnosed 

with CHD, the reduction in all-cause mortality associated 

with smoking cessation is attributable, at least in part, to a 

reduction in mortality from cardiac outcomes and sudden 

death. Cigarette smoking is an established cause of MI 

and other cardiovascular endpoints, as reviewed in prior 

Surgeon General’s reports (USDHHS 1983, 2010, 2014); 

thus, the associations reviewed in Table 4.23 and summarized in a forest plot in Figure 4.5 are consistent with prior 

evidence on this topic in the general population.

Smoking Cessation and Risk of Recurrence 

or New Cardiac Events in Cardiac Patients

Studies in cohorts of patients with CHD who were 

current smokers at the time of diagnosis that assessed 

the risk of new or recurrent cardiac events in relation to 

quitting versus persistent smoking are summarized in 

Table 4.24 and, for those studies with RRs and 95% CIs, 

in forest plots in Figure  4.6. Thirteen studies provided 

results for MI, including the outcomes of “reinfarction” 

and “MI hospitalization”; consistent with Figure 4.6, the 

associations tended to be either strongly in the protective 

direction for quitters compared with persistent smokers 

as the reference category (85% [11/13] RRs ≤0.76; overall 

median RR = 0.67) or, alternatively, strongly in the direction of increased risk for persistent smokers relative to 

quitters as the referent. Of the two studies with results 

not strongly in the protective direction, the associations 

were null in one (RR = 0.99; 95% CI, 0.42–2.33) (Herlitz 

et al. 1995) and positive in the other (RR = 3.87; 95% CI, 

0.81–18.37) (Perkins and Dick 1985). As seen in Figure 4.6, 

these two studies introduce heterogeneity. The overall 

results of these studies comprise a strong body of evidence 

indicating that smoking cessation after a diagnosis of a 

previous MI or other cardiac disease reduces the risk of MI.

The results for the endpoints of stroke, angina, or 

repeat procedures also indicate benefit from smoking cessation—that is, reduced risk in quitters versus persistent 

smokers. One study found that quitters had a lower risk 

of stroke (RR = 0.40; 95% CI, 0.14–1.17) compared with 

persistent smokers, but the results were not statistically 

significant (Chow et  al. 2010). The one study of angina 

(Voors et  al. 1996) found a weak, nonsignificant association for the entire follow-up period (RR = 1.2; 95% CI, 

0.8–1.7), but a significant association for the period from 

5 to 15 years after surgery (RR = 2.0; 95% CI, 1.3–3.6). 

Four studies reported results using repeat procedures as 

endpoints; these included repeat coronary artery bypass 

grafting/percutaneous transluminal coronary angioplasty 

(CABG/PTCA), reoperation, and repeat vascularization. 

Three studies observed increased risk for repeat procedures—CABG/PTCA, reoperation, or repeat vascularization—in persistent smokers when quitters were the referent (RR  ≥1.4). In the fourth study, authored by Chen 

and colleagues (2012), the results were strongly in the 

opposite direction, with an RR of 1.59 (95% CI, 1.36–1.85) 

for repeat revascularization in quitters compared with 

persistent smokers as the referent. This discrepant result 

notwithstanding, the overall evidence summarized in 

Table 4.24 and Figure 4.6 indicates reduced risk associated 

with smoking cessation relative to persistent smoking for 

the occurrence of adverse cardiac events among patients 

with CHD who were current smokers at diagnosis.
A Report of the Surgeon General

300 Chapter 4Figure 4.5 Cause-specific mortality from cardiovascular endpoints and sudden death in persistent smokers versus quitte

Study Relative risk (95% CI)Cardiac

Wilhemsson et al. 1975 2.05 (0.99–4.27)Salonen et al. 1980 1.50 (0.30–8.00)Mulcahy et al. 1982 2.70 (0.84–8.66)Rønnevik et al. 1985 1.17 (0.62–2.22)Hallstrom et al. 1986 1.55 (0.98–2.45)Vliestra et al. 1986 1.60 (0.89–2.86)Hasdai et al. 1997 1.49 (0.89–2.51)van Domburg et al. 2000 1.75 (1.30–2.37)Liu et al. 2013 7.70 (0.87–68.27)

Sudden death

Mulcahy et al. 1982 1.77 (1.23–2.54)Vliestra et al. 1986 1.82 (1.14–2.89)Gupta et al. 1993 1.48 (0.81–2.71)

Fatal reinfarction

Mulcahy et al. 1982 1.68 (1.04–2.72)Vliestra et al. 1986 1.78 (1.36–2.33)

Ischemic heart disease

Salonen et al. 1980 1.60 (1.00–2.70)

Arrhythmic mortality

Peters et al. 1995 1.80 (0.88–3.67)

Note: CI = confidence interval.
The Health Benefits o

Figure 4.6 Comparison of incidence of new cardiac endpoints among persistent smokers and quitters

Study Relative risk (95% CI)Myocardial infarction or hospitalization or reinfarction

Quit vs. persistent

Wilhemsson et al. 1975 0.49 (0.29–0.82)Sparrow et al. 1978 0.76 (0.37–1.58)Aberg et al. 1983 0.67 (0.53–0.84)Perkins et al. 1985 3.87 (0.81–18.37)Rønnevik et al. 1985 0.54 (0.32–0.93)Vliestra et al. 1986 0.63 (0.51–0.78)Herlitz et al. 1995 0.99 (0.42–2.33)Chow et al. 2010 0.57 (0.36–0.89)Álvarez et al. 2013 0.70 (0.26–1.88)

Persistent vs. quit

Voors et al. 1996 2.30 (1.10–5.10)Choi et al. 2013 2.86 (0.25–33.04)

Stroke 

Quit vs. persistent

Chow et al. 2010 0.40 (0.14–1.17)

Angina

Persistent vs. quit

Voors et al. 1996 (1- to 15-year follow-up)

1.20 (0.80–1.70)

Voors et al. 1996 (5- to 15-year follow-up)

2.00 (1.10–3.60)

Repeat procedures (CABG/PTCA/vascularization) 

Quit vs. persistent

Chen et al. 2012 1.59 (1.36–1.85)

Persistent vs. quit

Voors et al. 1996 2.50 (1.10–5.90)van Domburg et al. 2000 1.41 (1.02–1.94)Liu et al. 2013 2.89 (1.05–8.00)

Note: CABG = coronary artery bypass grafting; CI = confidence interval; PTCA = percutaneous transluminal coronary angioplasty.
A Report of the Surgeon General

302 Chapter 4

Summary of the Evidence

This review is the first Surgeon General’s report 

to address the benefits of smoking cessation specifically 

in patients diagnosed with CHD. The importance of this 

topic is amplified by the fact that survival after a diagnosis 

of CHD has improved markedly during the past several 

decades (e.g., Savastano et al. 2014). Within this focus on 

the health benefits of cessation among patients already 

diagnosed with CHD, evidence was summarized on associations of cessation (versus persistent smoking) with allcause mortality, deaths from cardiac causes and sudden 

death, and risk of recurrent or new cardiac events. 

Methodologic Considerations

This review focused on direct evidence regarding 

the potential health benefits of smoking cessation—that 

is, quitting rather than continuing to smoke—among 

patients with CHD who were current smokers at the time of 

the index event. All the studies used in the review involved 

a prospective cohort, ensuring that the temporal relationship between cessation and outcome was correctly characterized. The evidence was abundant: Among the identified 

studies included in the evidence tables on the association between smoking cessation and important outcomes, 

there were 34 reports on all-cause mortality, 13 (yielding 

20 distinct associations) on cause-specific mortality, and 

15 on the risk of new or recurrent cardiac events. Thus, the 

strength with which inferences can be made is enhanced 

by the focus, quality, and scope of the evidence.

However, the potential role of confounding is a 

concern in drawing inferences from this body of evidence because (1)  some associations considered were 

not adjusted for potential confounding variables and 

(2) among current cigarette smokers diagnosed with CHD, 

those who quit may have had a lower risk profile. A comparison of results from a study (Johansson et al. 1985) that 

used both unadjusted results and those that were adjusted 

for potential confounders indicated, however, that the 

adjusted results tended to be equal to or stronger than the 

unadjusted results. Thus, despite the potential for confounding to threaten the internal validity of the evidence, 

confounding is unlikely to have affected the validity of the 

overall evidence. 

Compared with cohort studies in the general population, another noteworthy feature of follow-up studies 

of smoking cessation in patients with CHD is that the 

duration of follow-up tends to be shorter, sometimes only 

6  months, and the median follow-up in this review was 

just 4.5 years. By contrast, 10 years was the median length 

of follow-up in cohort studies of smoking, in relation to 

all-cause mortality in the general population, that were 

included in the meta-analysis of Gellert and colleagues 

(2012). With a shorter duration of follow-up, fewer endpoints will be observed, and precision is reduced for estimating differences in outcome rates between quitters and 

persistent smokers. 

Another caveat is that most studies included in this 

review relied on self-reports to determine smoking status; 

the results of two studies that compared biochemical 

assessments of smoking status with self-reported smoking 

suggest that relying on self-reported smoking alone can 

underestimate the true association (Twardella et al. 2006; 

Breitling et al. 2011a).

Evaluation of the Evidence

Causal Criteria

This Surgeon General’s report is the first to consider the potential health benefits of smoking cessation 

in patients after a diagnosis of CHD. The report considers 

the totality of the evidence and references key criteria 

for causation established in the 1964 and 2004 Surgeon 

General’s reports (U.S. Department of Health, Education, 

and Welfare [USDHEW] 1964; USDHHS 2004). 

Temporality

The studies included in the evidence tables all had 

similar design features commonly used in prospective 

cohort studies. First, they studied patients who were current smokers when diagnosed with CHD. Second, patients 

were followed and reassessed to determine who quit 

smoking and who remained a smoker. Third, after quitters were distinguished from persistent smokers, there 

was subsequent follow-up for mortality and/or new cardiac events. Therefore, appropriate temporality is evident because, in all studies reviewed, smoking cessation 

preceded the occurrence of health outcomes in patients 

with CHD.

Consistency

The preponderance of the high-quality, focused 

bodies of evidence reviewed in this section showed that 

among patients who were current smokers when diagnosed with CHD, quitting smoking was consistently associated with reduced all-cause mortality compared with 

continuing to smoke. The studies focused primarily on 

MI as the index diagnosis, but they also included people 

with established CHD; the results were consistent regardless of the index condition. The studies were carried out 
The Health Benefits of Smoking Cessation 303

Smoking Cessation

in a wide range of geographic locations; spanned several 

decades of research; and varied widely in methodology, 

such as sample size, timing of the measurement of change 

in smoking status, definition of quitters and persistent 

smokers, and control for potential confounding variables. 

Despite the potential for this variability to introduce 

inconsistencies across studies, a very clear, consistent set 

of results accrued over time. The evidence about causespecific mortality and new or recurrent cardiac events also 

was highly consistent.

Strength of Association

The strength of the association observed for the outcome of all-cause mortality is best viewed in context of the 

existing evidence from the general population. The association between smoking and overall mortality was reviewed 

in the 1979 Surgeon General’s report with a finding that 

the RR for overall mortality in cigarette smokers compared 

with nonsmokers was 1.7 (USDHEW 1979b), which is quite 

similar to an estimate arrived at in 2014 based on data in 

the 1964 Surgeon General’s report (Schumacher et  al. 

2014). Because patients with CHD tend to be older than the 

general population, evidence specific to elderly populations 

is relevant. A systematic review of smoking and all-cause 

mortality in the elderly (defined as ≥60 years old) estimated 

a summary RR across studies of 1.83 (95% CI, 1.65–2.03) 

for current smoking versus never smoking (Gellert et al. 

2012). Against this backdrop, the evidence for the association between smoking cessation and all-cause mortality in 

patients with CHD is of similar magnitude to findings from 

studies in the general population. In comparisons with persistent smokers, the median RR for all-cause mortality was 

0.545  for those who quit smoking cigarettes; conversely, 

in reports that compared persistent smokers with quitters, 

the median RR was 1.67. The comparable magnitude of 

these associations is notable, considering that results for 

the general population are based on current versus never 

smokers, whereas the evidence reviewed here contrasts 

quitters with persistent smokers within a population made 

up entirely of current smokers at baseline.

The evidence presented for cause-specific mortality as an endpoint showed that, compared with quitting 

smoking, persistent smoking was strongly associated with 

increased mortality from cardiovascular disease endpoints 

and sudden death, with the median RR of 1.6 being very 

similar to that observed for all-cause mortality. Among 

patients with CHD who were current smokers when diagnosed, the risk of new or recurrent cardiac events was 

also observed to be strongly reduced by smoking cessation compared with persistent smoking; for example, the 

median RR for MI was 0.67.

When this body of evidence is viewed collectively, 

a consistent and coherent pattern of findings emerges 

showing that among patients with CHD who are smokers 

when they are diagnosed, compared with those who 

remain smokers, those who quit smoking have a reduced 

risk of (1)  dying from all causes and, specifically, dying 

from cardiovascular disease or experiencing sudden death 

and (2) experiencing new or recurrent cardiac events. The 

observed associations were strong, and the magnitude of 

these associations is even more impressive when the methodologic issues discussed above that would tend to bias 

these associations toward the null are carefully considered.

Experiment

For drawing causal inferences, studies of smoking 

cessation interventions that include results for clinical 

endpoints provide very strong evidence. In what can be 

viewed as quasi-experimental evidence, a large-scale, 

observational prospective cohort study found a strong allcause mortality benefit in patients diagnosed with MI who 

received an inpatient smoking cessation intervention compared with those who did not receive an inpatient smoking 

cessation intervention (Bucholz et al. 2017). Earlier, in a 

randomized controlled trial of an intensive smoking cessation intervention compared with usual care among 

patients diagnosed with acute coronary syndrome or 

decompensated heart failure, the intervention group experienced marked and statistically significant reductions in 

all-cause mortality and hospitalizations (Mohiuddin et al. 

2007). Strong associations from an experimental study 

favor the likelihood of an actual direct and causal association and weigh against uncontrolled confounding as an 

explanation of the results of the observational studies. The 

studies that provide direct evidence on this question consistently indicate that compared with persistent smoking, 

smoking cessation leads to substantial decreases in allcause mortality.

Specificity

The relevance of the criterion of specificity to the 

evidence considered in this report lies in the comparison 

of the results for cause-specific mortality with the results 

for all-cause mortality. These results are similar. A substantial reduction in all-cause mortality associated with 

smoking cessation that was paralleled by a similar reduction for specific cardiac causes of death provides evidence 

to support the conclusion that at least a portion of the 

health benefits of smoking cessation in patients with CHD 

results from reduced risk of death from cardiac causes. 

The mortality reduction experienced in quitters would 

also be expected to be present for other causes of death 

known to be caused by smoking, but the evidence base 

ascertained for this review provided little evidence on 

this question.
A Report of the Surgeon General

304 Chapter 4

Coherence

The causal criterion of coherence weighed heavily 

in evaluating the overall body of evidence as to whether 

smoking cessation can be considered a cause of mortality 

reduction in patients with CHD. The evidence on mortality reduction in patients with CHD following cessation 

needs to be interpreted in the context of the larger body 

of evidence on smoking cessation in relation to mortality 

in the general population. Previous Surgeon General’s 

reports have concluded that smoking causes increased allcause mortality in the general population. Based on the 

causal criterion of coherence, smoking cessation would 

be expected to decrease all-cause mortality in patients 

with heart disease, as in the general population. Similarly, 

because active smoking is causally associated with many 

adverse cardiac endpoints, it would be expected a priori 

that smoking cessation in patients with CHD would be 

associated with reduced risk of developing recurrent 

CHD. The combination of the substantial body of evidence 

reviewed here, which documents that smoking cessation 

is associated with reduced risk of death and disease, along 

with the fact that this evidence is in accord with a priori 

expectations about the known adverse health effects of 

smoking in the general population, strengthens the argument inferring a causal association.

Further adding to the coherence of the evidence are 

the established roles of smoking in causing endothelial 

dysfunctions and increasing risk for thrombosis, two etiologic pathways that contribute substantially to ischemic 

heart disease (USDHHS 2010; Barua and Ambrose 2013; 

Vanhoutte et al. 2017). Increasing endothelial production of adhesion molecules and decreasing production of 

vasodilators are some known mechanisms through which 

smoking causes endothelial dysfunction (USDHHS 2010). 

In addition, through adverse effects on endothelial cells, 

as well as on platelets, fibrinogen, and coagulation factors, 

smoking increases the risk of thrombosis, a key mechanism in the pathogenesis of MI and stroke (USDHHS 

2010; Barua and Ambrose 2013). McEvoy and colleagues 

(2015b) examined three sets of markers in participants in 

the Multi-Ethnic Study of Atherosclerosis (MESA): inflammatory biomarkers, vascular dynamics and function, and 

subclinical atherosclerosis. Inflammatory markers were 

lower in former smokers compared with current smokers, 

and a longer time since quitting was associated with lower 

inflammatory markers. Results from a few studies provide 

evidence that in current smokers diagnosed with heart disease, quitting smoking is associated with biomarker profiles of reduced risk compared with persistent smoking. 

For example, smoking cessation in patients with acute MI 

was associated with improved coronary endothelial function, an improvement not seen in nonsmokers (Hosokawa 

et al. 2008). Further, in patients with CAD, smoking cessation resulted in a reduced risk profile for macrophage 

cholesterol efflux (Song et al. 2015).

Synthesis of the Evidence

An extensive body of relevant evidence from prospective cohort studies was identified and reviewed. All 

studies were based on cohorts of patients who were current cigarette smokers when diagnosed with heart disease 

and who were followed up to first determine if they had 

quit smoking or continued to smoke and then to determine their vital status and to identify new or recurrent 

cardiac events. Most of this overall high-quality evidence 

indicates that in patients who are current smokers when 

diagnosed with heart disease, smoking cessation after 

the diagnosis is strongly and causally associated with 

reduced all-cause mortality. In patients with heart disease who are current smokers when diagnosed, the evidence indicates that smoking cessation reduces the risk 

of dying by almost one-half, a very strong clinical benefit. 

Not only is this unequivocally demonstrated in the data 

from prospective cohort studies, but the corroborating 

experimental evidence on this topic strongly reinforces 

this conclusion. Additionally, the evidence reviewed here 

demonstrates that the health benefits of smoking cessation after a heart disease diagnosis extend to mortality 

specifically from cardiac causes and sudden death. Third, 

the evidence indicates that smoking cessation is associated with decreased risk of new or recurrent cardiac 

events. Based on the causal criterion of coherence, the 

known causal associations between smoking and these 

outcomes in the general population support the causal 

nature of the associations. 

Because all the currently available evidence is from 

prospective studies, the temporal nature of the association is not ambiguous. The evidence for each outcome 

showed a high degree of consistency across diverse study 

populations and measurement approaches. These characteristics of the evidence clearly indicate that in current smokers diagnosed with heart disease, smoking 

cessation is associated with reduced risk of all-cause 

mortality, cause-specific mortality, and new or recurrent 

cardiac events.

Conclusions

1. In patients who are current smokers when diagnosed with coronary heart disease, the evidence 

is sufficient to infer a causal relationship between 
The Health Benefits of Smoking Cessation 305

Smoking Cessation

smoking cessation and a reduction in all-cause 

mortality.

2. In patients who are current smokers when diagnosed with coronary heart disease, the evidence 

is sufficient to infer a causal relationship between 

smoking cessation and reductions in deaths due to 

cardiac causes and sudden death. 

3. In patients who are current smokers when diagnosed with coronary heart disease, the evidence 

is sufficient to infer a causal relationship between 

smoking cessation and reduced risk of new and 

recurrent cardiac events.

Implications

The evidence summarized in this section documents that cigarette smoking cessation has a profoundly 

positive impact on overall survival in patients who are 

current cigarette smokers when diagnosed with CHD. 

The reductions in risk are substantial for total mortality 

and cardiovascular disease-specific outcomes. Estimates 

across studies indicate that smoking cessation reduces 

relative risks for these outcomes by 30–40%. Considered 

in the context of current knowledge of the health benefits of smoking cessation in the general population, 

cessation of smoking would be expected to have major 

health benefits in patients diagnosed with CHD. This evidence has clear clinical implications. Current cigarette 

smokers who are diagnosed with CHD can improve their 

prognosis by quitting smoking. Providing evidence-based 

smoking cessation services to patients with CHD who 

smoke would be expected to have a substantial beneficial impact on their prognosis, with the magnitude of the 

benefits in some instances even equaling or exceeding 

that of other state-of-the-art therapies. A Cochrane 

review found evidence for efficacy of smoking cessation 

interventions in patients hospitalized for cardiovascular 

disease (Rigotti et al. 2012). The critical role of smoking 

cessation in cardiac rehabilitation is already recognized 

in evidence-based medicine guidelines (King et al. 2005; 

Smith et al. 2006); the new conclusions of this report 

can be cited in further emphasizing to the public health, 

clinical, and patient and caregiver communities just how 

critical it is to provide evidence-based smoking cessation services to cardiac patients. In particular, cardiologists who provide care to patients who have experienced 

cardiovascular events should (a) clearly communicate to 

these patients that quitting smoking is the most important action they can take to improve their prognosis and 

(b)  offer patients evidence-based cessation treatments, 

including counseling, medications, and referral to more 

intensive assistance, including state quitlines (Fiore 

et al. 2008; U.S. Preventive Services Task Force 2015).

Tobacco smoke contains thousands of chemical components that are inhaled and then deposited throughout 

the large and small airways and alveoli of the lungs (U.S. 

Department of Health and Human Services [USDHHS] 

2010). The toxic components of cigarette smoke injure 

the lungs through a variety of mechanisms, including 

oxidative injury and inflammation, carcinogenesis, and 

effects on the immune system (USDHHS 2010, 2014). 

For example, acrolein and formaldehyde impair ciliary 

clearance and nitrogen oxides cause inflammation of the 

airways, while cadmium and hydrogen cyanide result in 

direct oxidant injury and impaired oxidative metabolism 

(USDHHS 2010). Cigarette smoke initiates an inflammatory process that results in direct destruction of lung 

parenchyma that is mediated through (a)  the release of 

proteinases that damage the extracellular matrix of the 

lung, (b) apoptosis because of oxidative stress, and (c) loss 

of matrix–cell attachment and ineffective repair of elastin 

and other extracellular matrix components that enlarge 

the airspace (USDHHS 2010, 2014). Although successful 

smoking cessation ends daily exposure to innumerable 

injurious compounds, the prolonged deleterious effects 

of tobacco smoke result in irreversible impairment in 

immune responses, changes in the makeup of the lung 

microbiome, and continued lung injury even after cessation (USDHHS 2014).

This section provides an update on the evidence 

about smoking cessation and respiratory health among 

persons with chronic obstructive pulmonary disease 

(COPD) or asthma.

Conclusions from Previous 

Surgeon General’s Reports

Associations of cigarette smoking with chronic 

respiratory diseases, including COPD, asthma, and interstitial lung diseases, have been addressed in numerous 

Surgeon General’s reports since 1964 (U.S. Department 

Chronic Respiratory Disease
A Report of the Surgeon General

306 Chapter 4

Table 4.25 Conclusions about smoking cessation and chronic respiratory disease from previous 

Surgeon General’s reports

Report Conclusions

USDHHS (2010, p. 10) • Smoking cessation remains the only proven strategy for reducing the pathogenetic processes 

leading to chronic obstructive pulmonary disease.

USDHHS (1990, p. 11) • Smoking cessation reduces rates of respiratory symptoms such as cough, sputum production, 

and wheezing, and respiratory infections such as bronchitis and pneumonia, compared with 

continued smoking.

• For persons without overt chronic obstructive pulmonary disease (COPD), smoking cessation 

improves pulmonary function about 5 percent within a few months after cessation.

• Cigarette smoking accelerates the age-related decline in lung function that occurs among never 

smokers. With sustained abstinence from smoking, the rate of decline in pulmonary function 

among former smokers returns to that of never smokers.

• With sustained abstinence, the COPD mortality rates among former smokers decline in 

comparison with continuing smokers.

USDHHS (1984, p. 10) • Cessation of smoking leads eventually to a decreased risk of mortality from COLD compared 

with that of continuing smokers. The residual excess risk of death for the ex-smoker is directly 

proportional to the overall lifetime exposure to cigarette smoke and to the total number of years 

since one quit smoking. However, the risk of COLD mortality among former smokers does not 

decline to equal that of the never smoker even after 20 years of cessation.

USDHEW (1979a, p. 18) • Cessation of smoking definitely improves pulmonary function and decreases the prevalence 

of respiratory symptoms. Cessation reduces the chance of premature death from chronic 

bronchitis and emphysema.

Notes: COLD = chronic obstructive lung disease; COPD = chronic obstructive pulmonary disease; USDHEW = U.S. Department of 

Health, Education, and Welfare; USDHHS = U.S. Department of Health and Human Services.

of Health, Education, and Welfare [USDHEW] 1964). The 

1964 report concluded that cigarette smoking is the most 

important cause of chronic bronchitis (USDHEW 1964). 

The principal topic of the 1984 report was COPD (USDHHS 

1984), and later reports addressed active smoking, exposure to secondhand smoke, and major respiratory diseases (USDHHS 2004, 2006, 2014). The conclusions from 

these reports addressed the causation and exacerbation of 

chronic respiratory disease by tobacco smoking; the risks 

of respiratory infections, a frequent contributor to exacerbation of chronic respiratory diseases; and the benefits 

of cessation (USDHEW 1964; USDHHS 1984). Several 

Surgeon General’s reports have addressed the health benefits of smoking cessation for COPD; these conclusions are 

listed in Table 4.25.

Literature Review Methods

MEDLINE, SCOPUS, and EMBASE were searched for 

studies that focused on smoking cessation and COPD or 

asthma and were published between January 1, 2008, and 

May 26, 2016. A systematic literature search was created 

for PubMed and translated to the EMBASE and SCOPUS 

databases. A combination of controlled vocabulary and 

keyword terms was used for each of the following concepts: (1) smoking cessation, (2) respiratory phenomena, 

(3)  asthma, (4)  chronic obstructive pulmonary disease, 

(5) emphysema, and (6) chronic bronchitis. Studies that 

did not focus on smoking cessation were excluded. To formulate conclusions, evidence cited in the 2014 Surgeon 

General’s report on smoking was considered along with 

any newly available evidence. Search results were limited 

to studies published in English and to original research. 

The primary search identified 1,977 items. Two independent reviewers identified 45  articles through consensus 

after reviewing the titles and abstracts. After a full review 

of the 45 articles, 24 articles (17 on COPD and 7 on asthma) 

were selected as relevant for this update.

Chronic Obstructive 

Pulmonary Disease

This section addresses advances in the evidence base 

on COPD and smoking cessation and the implications of 

the new findings. Our current understanding of the pathogenesis of COPD underscores the importance of smoking 

cessation in slowing and eventually ending lung damage 

associated with tobacco smoke. The occurrence of clinical 
The Health Benefits of Smoking Cessation 307

Smoking Cessation

COPD reflects a long course of progressive deterioration 

of lung function that can begin before conception, as 

maternal smoking during pregnancy affects the development of lungs in fetuses (Cook et al. 1998; Checkley et al. 

2010, 2016).

COPD is a common, preventable, and treatable disease characterized by persistent respiratory symptoms 

and airflow limitation that is due to airway and/or alveolar abnormalities usually caused by significant exposure 

to noxious particles or gases (Celli et al. 2004; USDHHS 

2014; Benditt n.d.) (Figure 4.7). The development of airflow limitation among those with COPD is usually progressive and reflects the ongoing processes of lung injury 

that are initiated and sustained by persistent exposure to 

tobacco smoke (Rabe et al. 2007). Thus, smoking cessation 

is critical in preventing COPD, slowing its progression, 

and treating this disorder. Although previous definitions 

have focused on phenotypes of COPD, such as chronic 

bronchitis and emphysema, the diagnosis of COPD has 

now been standardized on the basis of spirometry and 

the presence of airflow obstruction (i.e., a reduced ratio 

of forced expiratory volume at 1 second [FEV1] to forced 

vital capacity [FVC]) that does not fully reverse after 

bronchodilation (Tashkin and Murray 2009). Previously, 

COPD was defined by a fixed ratio (post-bronchodilator 

FEV1/FVC <70%) (Rabe et al. 2007). There is debate, however, on using the lower limit of normal for selected reference populations as the best approach to standardizing 

the interpretation of spirometry results by accounting for 

age, sex, height, and race (Mannino et al. 2007; Swanney 

et al. 2008; Miller et al. 2011b; Mannino and Diaz-Guzman 

2012; Quaderi and Hurst 2017).

Thus, FEV1/FVC is generally used to define COPD, 

but FEV1 and the rate of decline of FEV1 have been the 

two most widely used outcome measures for clinical trials 

related to COPD. These indicators are also associated 

Figure 4.7 Flow-volume loops for a person with (obstruction) and without (normal) chronic obstructive 

pulmonary disease

Source: Benditt (n.d.). Copyright © University of Washington, 2004.

Note: RV = residual volume; TLC = total lung capacity.
A Report of the Surgeon General

308 Chapter 4

with measures of health-related quality of life and mortality (Wise 2006). Additionally, however, there is evidence 

to support the presence of considerable smoking-related 

respiratory disease among persons with normal lung function. For example, in a study by Woodruff and colleagues 

(2016), half of current or former smokers with preserved 

pulmonary function exhibited respiratory symptoms, 

and former smokers with preserved lung function had 

higher rates of exacerbation events than lifelong nonsmokers. Sensitive imaging approaches are now used to 

quantify changes in the lungs, including emphysema, that 

have health implications. Oelsner and colleagues (2014) 

found higher all-cause mortality among former and current smokers with emphysematous changes on computed 

tomography (CT) and preserved pulmonary function. 

However, the analysis did not find differences in the risk of 

having such changes by smoking status.

Smoking Cessation and Chronic Obstructive 

Pulmonary Disease

Cigarette smoking is the most common cause of 

COPD in the United States (Xu et  al. 1992; Anthonisen 

et  al. 1994; Perret et  al. 2014) and is a consistent and 

strong risk factor for the development of COPD (USDHHS 

2014). In the United States, the population-attributable 

risk for developing COPD caused by smoking has been 

estimated to be as high as 80–90% (Eisner et  al. 2010; 

USDHHS 2014). Although observational evidence shows 

that air pollution adversely affects persons with COPD, 

not starting to smoke and smoking cessation remain the 

only proven prevention strategies for reducing the risk 

of developing chronic respiratory diseases caused by cigarette smoking (Xu et  al. 1992; Anthonisen et  al. 1994; 

Abramson et al. 2015). Smoking cessation can prevent or 

delay the development of airflow limitation and slow the 

progression of chronic respiratory disease; it is the only 

intervention that has been shown to reduce the rate of 

FEV1 decline in both men and women (Thomson et  al. 

2004) and to reduce all-cause mortality among those with 

COPD (Anthonisen et al. 2005).

Epidemiology of Mortality from Chronic 

Obstructive Pulmonary Disease in Relation 

to Tobacco Cessation

The relationship between temporal trends in the 

decline of smoking prevalence and trends in COPD morbidity and mortality is complex, as evidenced by data collected in the United States (Mannino and Buist 2007). 

Prevalence estimates of COPD have limited validity 

because symptoms related to COPD, such as dyspnea on 

exertion and limitation in physical activity, are nonspecific 

(Tashkin and Murray 2009). Nonetheless, some trends 

are quickly apparent from surveillance data. Among all 

U.S. adults, age-adjusted mortality from COPD increased 

from 29.4  per 100,000  population in 1968 to 67.0  per 

100,000  population in 1999 and then declined slightly 

to 63.7  per 100,000  population in 2011 (Ford 2015). 

Mortality from COPD among men has declined since 1999, 

but among women, the age-adjusted mortality continues 

to increase (Ford 2015). Despite this narrowing of the difference between men and women, mortality rates in men 

continue to exceed those in women (Ford 2015). Notably, 

among certain population subgroups (i.e.,  Black men, 

White men, adults 55–64 years of age, adults 65–74 years 

of age), mortality rates have declined during the past 

decade (Ford 2015).

How Smoking Cessation Affects the Decline 

of Lung Function in Smokers

The 1990 Surgeon General’s report on the health 

benefits of smoking cessation cited only three studies concerning the effect of smoking cessation on the decline 

of lung function (USDHHS 1990). The 1990 report did 

provide a conclusion that “With sustained abstinence 

from smoking, the rate of decline of pulmonary function in former smokers returns to that of never smokers” 

(USDHHS 1990, p 349). Since the 1990 report, both clinical and population studies have examined the association 

between cessation of tobacco smoking and the decline of 

lung function. 

The Lung Health Study, a randomized clinical trial 

of smoking cessation and respiratory outcomes, evaluated the effect of an intensive smoking cessation intervention (combined randomly with either the inhaled bronchodilator ipratropium bromide or placebo) on the rate of 

FEV1 decline among 5,887 cigarette smokers 35–60 years 

of age with mild-to-moderate airflow limitation from 

COPD (Anthonisen et  al. 1994). Participants who continued to smoke had a greater decline in FEV1 at the 

5-year follow-up (Figure  4.8) compared with those who 

quit. In a separate analysis of data from the Lung Health 

Study, a decrease in the number of cigarettes smoked by 

continued smokers did not reduce the rate of decline of 

lung function compared with complete cessation, unless 

the number of cigarettes smoked was reduced by at least 

85% (Simmons et al. 2005). The benefit of a lower decline 

of FEV1 among participants in the smoking intervention 

program compared with the control group persisted over 

11 years of follow-up (Anthonisen et al. 2002; Murray et al. 

2002). Participants in the smoking intervention group had 

a lower decline of FEV1 than participants receiving usual 

care (the control group) (Anthonisen et al. 2002). Men who 

quit smoking at the beginning of the Lung Health Study 

had a rate of decline in FEV1 of 30.2 milliliters (mL)/year, 

whereas this measure declined at 21.5 mL/year in women 
The Health Benefits of Smoking Cessation 309

Smoking Cessation

who quit. Men who continued to smoke throughout the 

11  years of follow-up experienced an FEV1 decline of 

66.1 mL/year, and women who continued to smoke experienced a decline of 54.2 mL/year (Anthonisen et al. 1994). 

At the 14.5-year follow-up, all-cause mortality was lower 

in the intervention group than in the usual-care group 

(8.8  per 1,000  person-years  vs. 10.4  per 1,000  personyears, p = 0.03) (Anthonisen et al. 2005).

Several studies have examined how quickly benefits of smoking cessation are observed. In an analysis of 

a 6-year follow-up of 4,451 Japanese American men participating in the Honolulu Heart Program, Burchfiel and 

colleagues (1995) reported that the rate of FEV1 decline 

was reduced in participants who quit smoking compared 

with those who continued smoking. These researchers 

also found that, after 2 years of successful cessation, the 

reduced rate of FEV1 decline among quitters approximated that of participants who never smoked. In contrast, 

the rate of FEV1 decline in the first 2 years was similar 

between quitters and those who continued to smoke. This 

last finding suggests that the effects of smoking cessation 

on decline in lung function are not immediate and may 

take up to 2 years to be manifested.

Table  4.26 summarizes reports published in 2009 

or later offering further evidence on smoking cessation 

and the natural history of COPD and other respiratory 

outcomes from long-term studies. Studies and trials 

have continued to demonstrate immediate improvement 

in self-reported respiratory symptoms at 1  to 3  months 

after cessation (Louhelainen et al. 2009; Etter 2010) and 

an improvement in FEV1 and in COPD-specific outcomes 

at 1  year after quitting (Tashkin et  al. 2011; Dhariwal 

et  al. 2014). Smoking cessation has a beneficial effect 

at any age, although the benefit was found to be more 

pronounced among persons who quit before 30 years of 

age compared with those who quit after 40 years of age 

(Kohansal et al. 2009).

Although smoking cessation results in less severe 

respiratory symptoms, the inflammatory burden may persist. In a prospective cohort, Louhelainen and colleagues 

(2009) found oxidant and protease burden in airways 

(using sputum as a proxy to measure airway inflammation) that persisted for months after smoking cessation. 

Versluis and colleagues (2009) found that adenosine 

receptor mechanisms may be implicated in the progression of the inflammatory response after cessation in cigarette smokers with COPD. Specifically, the expression of 

adenosine receptors increased in some sputum cell types 

and sputum adenosine levels appeared to rise in those with 

COPD 1 year after smoking cessation (Versluis et al. 2009). 

Figure 4.8 Impact of smoking cessation and resumption on FEV1 decline in the Lung Health Study cohort of 

patients with chronic obstructive pulmonary disease

Source: Scanlon and colleagues (2000, p. 384). Reprinted with permission of the American Thoracic Society. Copyright © 2018 

American Thoracic Society. The American Journal of Respiratory and Critical Care Medicine is an official journal of the American 

Thoracic Society.

Note: FEV1 = forced expiratory volume at 1 second.
A Report of the Surgeon General

310 Chapter 4

Table 4.26 Studies on smoking cessation and chronic obstructive pulmonary disease, 2009–2017

Study Design/population Findings

Lung function

Kohansal et al. 

(2009)

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

Prospective cohort

4,391 participants 13–71 years of age with two 

or more valid spirometry measurements during 

follow-up periods (1971–1997) of the Framingham 

Offspring Study

Participants divided into three groups: 

 – Never smokers (n = 1,578)

Continuous smokers (n = 754)

Other smokers, which included former smokers

(n = 2,059)

Never smokers and continuous smokers were 

further divided into categories of healthy and 

nonhealthy 

Smoking cessation had a beneficial effect at any age, 

but it was more pronounced in earlier quitters 

The rate of FEV1 decline in both male and female 

smokers who quit before age 30 was indistinguishable 

from healthy never smokers

In contrast, smokers who quit after 40 years of age 

showed a significantly enhanced rate of decline of FEV1

versus healthy never smokers and earlier quitters, but 

their rate was not significantly different from that of 

continuous smokers

The mean FEV1 decline value among continuous 

smokers (with 95% CI) was 38.2 ml (33.9–42.6) for males 

and 23.9 ml (20.9–27.0) for females, with p = 0.001 for 

male vs. female (p ≤0.05 versus healthy never smokers)

Louhelainen 

et al. (2009)

Prospective cohort

61 smokers:

 – 21 with chronic bronchitis or COPD

15 with asthma

25 asymptomatic

Followed 3 months after smoking cessation

Although symptoms improved after smoking cessation, 

oxidant and protease burden in the airways continued 

for months after cessation

Takabatake 

et al. (2009)

Prospective cohort

82 former smokers with COPD

Followed for 30 months 

CDC6 may be one of the susceptibility genes that 

contributes to rapid decline in lung function despite 

smoking cessation in patients with COPD

Versluis et al. 

(2009)

Prospective cohort

26 smokers who had successfully quit for at least 

1 year:

 – 11 with COPD

15 asymptomatic

Followed at 1 year after cessation 

Adenosine-related effector mechanisms are involved in 

the persistence and progression of the inflammatory 

response in COPD after 1 year of smoking cessation

Mazur et al. 

(2011)

Prospective cohort

474 current smokers

155 with COPD symptoms

319 no symptoms

Followed for 2 years, with 111 succeeding 

in cessation

After 2 years of follow-up, levels of surfactant protein 

A were higher in those who continued smoking 

compared with those who quit

Tashkin et al. 

(2011)

Randomized controlled trial 

504 participants (smokers with mild-tomoderate COPD:

 – 250 in the varenicline treatment group

254 in the placebo treatment group

In this 1-year cessation trial of smokers with COPD, 

continuous abstinence compared with continuous 

smoking significantly improved (p = 0.0069) mean 

change from baseline in post-bronchodilator FEV1

(although the difference subsequently narrowed) and 

total scores on the Clinical COPD Questionnaire at 

12 weeks, with sustained improvement thereafter 

on that instrument

Dhariwal et al. 

(2014)

Prospective cohort

358 heavy smokers screened:

 – 38 with COPD

55 with normal spirometry

Control group: 19 nonsmokers

Followed for 1 year

Smoking cessation had differential effects on lung 

function (FEV1 and gas transfer) and features 

revealed on high-resolution CT images (emphysema 

and micronodules)

Smoking cessation in patients with COPD caused 

transient improvement in FEV1 and decreased the 

presence of micronodules
The Health Benefits of Smoking Cessation 311

Smoking Cessation

Table 4.26 Continued

Study Design/population Findings

Lung function 

(continued)

Ito et al. (2015) • 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

Cross-sectional

93 participants divided into four groups:

 – Former smokers with COPD (n = 23)

Smokers with COPD (n = 17)

Current smokers (n = 27)

Nonsmokers (n = 26)

One year after smoking cessation, participants with 

COPD had improved mucociliary clearance

Respiratory 

symptoms

Etter (2010) Prospective cohort

Visitors to Stop-tabac.ch website

18 years of age or older

15,916 participants at baseline

1,831 participants at 1-month follow-up

Smoking cessation was followed by a rapid and 

substantial improvement in self-reported respiratory 

symptoms 

In the 252 baseline smokers who had quit smoking at 

30-day follow-up, there was a substantial decrease in

the proportion of participants who declared that they

often coughed even without a cold (from 51.6% at

baseline to 15.5% at follow-up), expectorated when

they coughed in the morning (from 47.6% to 19.4%),

were out of breath after climbing stairs or after a quick

walk (from 75.0% to 48.4%), and who had a wheezing

respiration (from 33.7% to 10.3%) (p = 0.001 for all

before/after comparisons)

Josephs et al. 

(2017)

Retrospective cohort

16,479 patients with COPD with outcomes over 

3 years

8,941 former smokers 

Former smokers had significantly reduced risk of death,

hospitalization, and visits to the emergency department

Compared with active smokers, ex-smokers had 

significantly reduced risk of death, with a hazard 

ratio (95% CI) of 0.78 (0.70–0.87); hospitalization, 

0.82 (0.74–0.89); and emergency department 

attendance, 0.78 (0.70–0.88)

Imaging

Ashraf et al. 

(2011)

Prospective cohort

726 current and former smokers 

Aged 50–70 years 

Smoking history of more than 20 pack-years. 

Former smokers were only included if they had 

quit smoking after the age of 50 years and less 

than 10 years before inclusion. 

All subjects had to have an FEV1 at least 30% 

of predicted normal.

Followed for more than 2 years

Current smoking status was associated with lower 

lung density and a difference in lung density between 

current and former smokers who were observed at 

baseline, which corresponded closely to changes in 

lung density after cessation 

After smoking cessation (n = 77) 15th percentile 

density (PD15) decreased by 6.2 g/l (p < 0.001) in 

the first year, and by a further 3.6 g/l (p < 0.001) in 

the second year, after which no further change could 

be detected; moreover, the first year after relapse to 

smoking (n = 18) PD15 increased by 3.7 g/l (p = 0.02)

Miller et al. 

(2011a)

Prospective cohort

10 former smokers with COPD after 4 years 

of not smoking

Cessation of tobacco smoking in heavy smokers 

with moderately severe emphysema was associated 

with evidence of persistent airway inflammation and 

progression of emphysema on CT

Shaker et al. 

(2011)

Prospective cohort

36 former smokers with COPD

Followed for 2–4 years

Inflammation partly masked the presence of emphysema

on CT, and smoking cessation resulted in a paradoxical 

fall in lung density, which resembled rapid progression 

of emphysema; this fall in density likely resulted from 

an anti-inflammatory effect of smoking cessation
A Report of the Surgeon General

312 Chapter 4

Table 4.26 Continued

Study Design/population Findings

Imaging 

(continued)

Hoesein et al. 

(2013)

• 

• 

• 

• 

Prospective cohort

3,670 male smokers

1- and 3-year follow-up

Follow-up CT and pulmonary testing

Current smokers had yearly FEV1 decline of 69 mL, 

and participants who had quit smoking more than 

5 years earlier had a yearly decline of 57.5 mL

Compared with current smokers, participants who 

had quit smoking more than 5 years earlier showed 

significantly lower rates of progression of emphysema 

on CT

Hlaing et al. 

(2015)

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

Prospective cohort

45 persons with COPD who stopped smoking

Followed for 1 year

On the CT image, significant decreases occurred in 

mean lung density and the attenuation value separating

the least 15% pixels, but there was a significant increase 

in the percentage of the relative area of the lungs with 

attenuation values <-950 Hounsfield units

Takayanagi 

et al. (2017)

Prospective cohort

58 patients with COPD at the time of their 

enrollment at the hospital and 2 years later

Airway disease and vascular remodeling may be 

reversible to some extent through smoking cessation 

and appropriate treatment

Immunity

Roos-Engstrand

et al. (2009)

Case-control 

19 persons with stable COPD:

 – 7 smokers

12 former smokers

Compared with 12 age-matched never smokers 

and 13 pack-years-matched smokers with normal 

lung function

Five years after smoking cessation, former smokers 

with COPD had significantly higher percentages of 

CD8+ cells compared with never smokers

DNA methylation

Tsaprouni et al. 

(2014)

Cross-sectional

Discovery cohort: 464 participants who were either 

diagnosed with CAD (n = 238) or were considered 

healthy (controls, n = 226):

 – Current smokers (n = 22)

Former smokers (n = 263)

Never smokers (n = 179)

Replication cohort: 356 female participants, all twins: 

 – Current smokers (n = 41)

Former smokers (n = 104)

Never smokers (n = 211)

The effect of smoking on DNA methylation was 

partially reversible following smoking cessation 

for longer than 3 months

Wan et al. 

(2012)

Cross-sectional

Discovery cohort: 1,085 participants with 

≥5 pack-years of cigarette smoking and reported 

FEV1 limitation, as well as one eligible sibling 

with ≥5 pack-years of cigarette smoking:

 – Current smokers (n = 396)

Former smokers (n = 689)

Replication cohort: 369 participants with 

FEV1 limitation: 

 – Never smokers (n = 68)

Current smokers (n = 103)

Former smokers (n = 198)

The existence of dynamic, site-specific methylation 

changes in response to smoking may contribute 

to the risks associated with cigarette smoking that 

persist after cessation

Notes: CI = confidence interval; COPD = chronic obstructive pulmonary disease; CT = computed tomography; FEV1 = forced expiratory 

volume at 1 second; CAD = coronary artery disease; mL = milliliter.
The Health Benefits of Smoking Cessation 313

Smoking Cessation

In a later study, Mazur and colleagues (2011) assessed 

levels of surfactant protein A (SP-A) among smokers, 

nonsmokers, and former smokers over a 2-year period. 

Although plasma SP-A levels tended to decline among 

those who quit smoking, no significant difference from 

baseline was evident at the 2-year follow-up. A difference 

in plasma SP-A levels was evident, however, between those 

who quit and active smokers, whose SP-A levels continued 

to increase (Mazur et al. 2011). 

Novel Diagnostics for Assessing the Impact 

of Smoking Cessation on the Progression of 

Chronic Obstructive Pulmonary Disease

Since the earlier Surgeon General’s reports on this 

topic (USDHHS 1984, 2004), new techniques—such as 

imaging—have been used to investigate the natural history of COPD. These techniques have provided insights 

into structural changes and genomics, epigenomics, and 

other “-omics” approaches that help to better understand 

the molecular determinants of COPD risk and the persistence of risk after cessation. Furthermore, novel therapeutic options—such as epigenetic regulation—can be 

reprogrammed, potentially modifying risk and supporting 

treatment of disease states (Sakao and Tatsumi 2011).

Imaging

Quantitative volumetric CT scanning, a wellestablished diagnostic modality, can assess pathology in 

vivo, enabling morphologic phenotyping of three critical 

components of the progression of COPD: emphysema 

(Bankier et al. 2002; Madani et al. 2008), thickening of the 

airway wall (Orlandi et al. 2005; Coxson 2008), and trapping of expiratory air (Mets et al. 2012). These measures 

correlate with pathologic measures of emphysema and 

small airways disease and predict such clinical outcomes 

as FEV1 decline (Mohamed Hoesein et al. 2011) and frequency of exacerbation (Han et al. 2011). Additionally, the 

growing adoption of annual CT scans to screen for lung 

cancer makes possible volumetric analysis at a population 

level over time, providing a powerful tool for assessing 

changes in lung structure after cessation of exposure to 

tobacco smoke, at least in this high-risk group. Low-dose 

CT used in annual screening enables the assessment of airways and lung parenchyma with less radiation compared 

with conventional CT scanning. Examining the effects of 

cessation on volumetric CT imaging is complicated, however, by the contradiction between the reported shortterm and long-term effects of smoking. Specifically, previous studies have demonstrated that current cigarette 

smoking increases measurements of lung density and that 

these changes are most likely a result of accumulation of 

particulate matter resulting in inflammation (Grydeland 

et  al. 2009), but over the long term, the emphysematous changes related to inhaling tobacco smoke result 

in low lung density (Ashraf et  al. 2011). It is important 

that changes in lung density over the short term not be 

interpreted as either the progression of emphysema or 

improvement in that condition. Smoking cessation has 

been shown to reduce lung density, and the rate of reduction increases at 2  years post-cessation (Scanlon et  al. 

2000; Ashraf et al. 2011). At 2 years post-cessation, lung 

density stabilizes, suggesting a reversal of the inflammatory sequelae of exposure to tobacco smoke, which is consistent with findings on lung function in the Lung Health 

Study (Scanlon et al. 2000; Ashraf et al. 2011). A similar 

study by Takayanagi and colleagues (2017) demonstrated 

progression of emphysema, particularly in the subgroup of 

patients with exacerbations, but imaging findings related 

to airway disease and pulmonary vasculature did not 

change in proportion to the progression of emphysema.

Advances in Epigenetics

Epigenetics is defined as the study of mechanisms 

that cause heritable changes in gene expression rather 

than alterations in the underlying sequence of deoxyribonucleic acid (DNA) (Dupont et al. 2009). Epigenetics 

can help measure the extent to which gene expression is 

altered in response to environmental exposure. Because 

epigenetics is a dynamic process, tracking the epigenome 

over time in relation to smoking cessation becomes relevant. Recent studies have demonstrated a role of DNA 

methylation, one of the main forms of epigenetic modification, in the pathways of smoking and smoking-induced 

diseases via the regulation of gene expression and genome 

stability (Figure 4.9). Methylation may underlie diseasespecific gene expression changes, and characterization of 

these changes is a critical first step toward the identification of epigenetic markers and the possibility of developing novel epigenetic therapeutic interventions for 

COPD (Vucic et al. 2014). 

Smoking alters the bronchial airway epithelial transcriptome and induces expression of genes involved in the 

regulation of oxidative stress, xenobiotic metabolism, and 

oncogenesis while suppressing those involved in the regulation of inflammation and tumor suppression (Spira et al. 

2004). DNA methylation studies have been performed on 

a range of samples, including whole-blood homogenates 

and cells obtained from bronchial brushing and buccal 

swabbing (Breitling et al. 2011b; Tsaprouni et al. 2014; 

Guida et al. 2015; Wan et al. 2015).

An increasing number of smoking-related CpG sites 

(sites with a cytosine nucleotide next to a guanine nucleotide in the linear sequence) in various genes—such as 

aryl-hydrocarbon receptor repressor (AHRR), coagulation 

factor II receptor-like 3 (F2RL3), and G protein-coupled 
A Report of the Surgeon General

314 Chapter 4

receptor 15  (GPR15)—have been discovered by 

epigenome-wide association studies based on samples of 

whole blood; these markers have shown utility as quantitative biomarkers of current and past smoking exposure and 

predictors of smoking-related disease risk (Figure  4.10) 

(Breitling et al. 2011b; Tsaprouni et al. 2014; Guida et al. 

2015). Breitling and colleagues (2011b) found that DNA 

methylation was significantly lower in smokers than 

nonsmokers (percent difference in methylation  =  12%; 

p = 2.7 × 10-31) in F2RL3 and correlated negatively with 

the number of smoked cigarettes and positively with the 

duration of smoking abstinence. Similar exposure-related 

differences in the methylation of this gene were seen in 

another study, with the intensity of F2RL3 methylation 

increasing gradually in long-term (>20 years) quitters to 

levels similar to that of never smokers (Zhang et al. 2014).

Guida and colleagues (2015) conducted epigenomewide association studies to capture the dynamics of 

smoking-induced epigenetic changes after smoking cessation using genome-wide methylation profiles obtained 

from blood samples in 745  women from two European 

populations. The authors found that LRRN3 also was significantly overexpressed in current smokers as compared 

with never smokers (fold change = 2.85; p = 2.1 × 10−24). 

Similar to the findings of Breitling and colleagues (2011b), 

Guida and colleagues (2015) demonstrated a doseresponse relationship between methylation and time since 

cessation. The expression of only one additional gene, 

FOXO3, was found to be upregulated in current smokers 

(fold change = 1.27; p = 4.3 × 10−6) (Guida et al. 2015). 

Wan and colleagues (2012) assessed the impact 

of DNA methylation after smoking cessation over time 

among those in the International COPD Genetics Network 

(n = 1,085), followed by replication in the Boston Severe 

Early Onset COPD study (n  =  369). These investigators 

identified a novel locus (GPR15) associated with cigarette 

smoking and found evidence to suggest that the existence 

of smoking-related, site-specific methylation changes 

may contribute to extended risks associated with cigarette smoking after cessation. Among former smokers, 

participants with the highest cumulative exposure to 

smoke and shortest duration of smoking cessation had the 

lowest mean methylation, but participants with the lowest 

cumulative exposure to smoke and the longest duration of 

cessation had the highest mean methylation, suggesting 

a dose-dependent response. Tsaprouni and colleagues 

Figure 4.9 Cigarette smoking and DNA methylation

Source: Lee and Pausova (2013). Copyright © 2013 Lee and Pausova.
The Health Benefits of Smoking Cessation 315

Smoking Cessation

(2014) showed that the effect of smoking on DNA methylation was partially reversible following cessation of more 

than 3 months. That study additionally used whole-blood, 

ribonucleic acid (RNA) sequencing to demonstrate evidence of the higher expression of PSEN2, PRSS23, RARA, 

F2RL3, GPR15, CPOX, AHRR, and RPS6KA2 genes among 

former and current smokers. Only GPR15 showed a clear 

trend of higher gene expression in smokers compared 

with nonsmokers, suggesting that a reduction in methylation levels observed in smokers leads to higher levels of 

RNA transcription (Tsaprouni et al. 2014). 

Advances in Proteomics

Smoking-related inflammation secondary to lung 

disease has been well described in earlier reports (USDHHS 

2014). The 2014 Surgeon General’s report concluded that 

sufficient evidence exists to infer that components of cigarette smoke affect the immune system and that some of 

these effects are immune system activating, while others 

are immunosuppressive (USDHHS 2014). Alterations 

in innate and adaptive immunity result in both emphysema and airway remodeling, and a range of pathways 

for inflammatory biomarkers related to smoking have 

been described (Ito et al. 2006; USDHHS 2014). Profiles 

of inflammatory biomarkers change after smoking cessation. The Evaluation of COPD Longitudinally to Identify 

Predictive Surrogate Endpoints (ECLIPSE) study (Coxson 

et al. 2013) found that several circulating biomarkers were 

associated with both the severity (SP-D, soluble receptor 

for advanced glycation end products [sRAGE], CCL18) 

and progression (SP-D, sRAGE, fibrinogen, interleukin 

[IL]  6, and CRP) of emphysema assessed by volumetric 

Figure 4.10 Epigenome-wide association study Manhattan plot and Q-Q plot for smoking status in the 

Cardiogenics Cohort

Source: Tsaprouni and colleagues (2014), with permission.

Note: In Panel A, the vertical axis indicates (-log10 transformed) observed p values, and the dotted horizontal line indicates the 

threshold of significance (p = 10−6) to select markers for replication. Previously reported loci are indicated in blue, and new loci and 

new signals in known loci are marked in red. Panel B illustrates the distribution of the p values.
A Report of the Surgeon General

316 Chapter 4

CT imaging. Circulating biomarkers may provide an 

additional proxy for lung inflammation and emphysematous change. SP-D, one of several surfactant proteins, is 

thought to be related to pulmonary immunity (Kishore 

et al. 2006) and is higher in persons with COPD (Lomas 

et  al. 2009). This relative increase is believed to reflect, 

in part, inflammation in the lung leading to degradation 

and leakage into the circulation. sRAGE is thought to protect against inflammation, and low levels of sRAGE have 

been associated with several inflammatory diseases, such 

as diabetes and cardiovascular disease (Raposeiras-Roubín 

et  al. 2010). Although the biomarkers discussed in this 

chapter thus far were found to be associated with lower 

baseline lung density and accelerated decline in lung density among smokers, whether the low levels of sRAGE and 

SP-D are a contributing factor or a consequence of COPD 

is unclear (Coxson et al. 2013). Circulating sRAGE could 

be a useful biomarker in monitoring the consequences 

of novel interventions such as the administration of retinoic acid, stem cell technology, and the use of growth factors targeting the emphysema component of COPD and 

smoking cessation (Coxson et al. 2013).

Biomarkers in sputum also have been found to 

change after smoking cessation. In a cross-sectional study 

of 240 participants, Titz and colleagues (2015) found that 

the sputum proteome and the transcriptome of former 

smokers largely approached those in never smokers. 

Nevertheless, some long-term effects of prior smoking 

remain evident in the sputum of former smokers, as indicated by the increase in IFNG and NFKB signaling, which 

are both associated with an M1 polarization in the sputum 

of former smokers (Titz et al. 2015). Singh and colleagues 

(2011) found that IL-18R protein expression was higher on 

alveolar macrophages in the lung tissue of COPD patients 

(mean:  23.2%) compared with controls (mean:  2% in 

former smokers and 2.5% in nonsmokers). 

Advances in the Microbiome

The role of the microbiome in COPD pathogenesis 

has become an active area of research (Martinez et  al. 

2013; Sze et al. 2014; Mammen and Sethi 2016). Studies 

have shown that tobacco smoking affects both the oral 

and intestinal microbiota (Biedermann et al. 2013; Morris 

et al. 2013), but it is not clear whether the lung microbiota is also affected by tobacco cessation (Morris et  al. 

2013; Yu  et  al. 2016). Some researchers postulate that 

alterations of the gut microbiome may help to explain 

mechanisms of inflammation in the lung that lead to 

the development of COPD or its exacerbations (Martinez 

et al. 2013; Sze et al. 2014; Malhotra and Olsson 2015). 

Research has revealed that smoking cessation also leads 

to changes in the microbiome, but it is uncertain whether 

smoking cessation leads to higher or lower bacterial diversity and whether specific families of bacteria are consistently affected (Delima et al. 2010; Biedermann et al. 2013; 

Munck et al. 2016; Yu et al. 2016). 

Synthesis of the Evidence

Evidence considered in this report strengthens the 

foundation for inferring that smoking cessation remains 

the only intervention that attenuates loss of lung function over time among those with COPD and reduces risk 

of developing COPD in cigarette smokers (USDHHS 1984, 

2004, 2014). The beneficial effect of cessation in slowing 

the decline of lung function in persons with COPD is well 

documented and was stated in a conclusion of the 1990 

Surgeon General’s report; the rate of decline decreases 

after cessation and is maintained at the new lower level 

unless smoking is resumed (USDHHS 1990). The available 

evidence shows an immediate benefit over several years 

for the rate of decline, but does not show whether further 

gains occur subsequently. Clinical studies show recovery 

of lung function and improvement in respiratory symptoms shortly after cessation, but inflammation continues 

to exist months after cessation. 

Unfortunately, COPD is a progressive disease in the 

face of sustained smoking, and at the time of diagnosis the 

loss of lung function is irreversible. However, further progression can be prevented by cessation. Support for this 

conclusion, reinforcing that of the 1990 report, comes 

from the understanding that smoking leads to inflammation and injury of the lungs and from mounting epidemiological evidence that cessation slows the accelerated loss 

of lung function in smokers. Turning to the criteria used 

for causal inference in these reports, temporality is appropriate (i.e., cessation is followed by changes in the progression of COPD), the biological basis for a benefit of cessation has been well established in prior Surgeon General’s 

reports, and the epidemiological evidence is consistent. 

Further insights on mechanisms are emerging. 

Recent imaging studies suggest that there are longerterm benefits of cessation (e.g., research has shown measurable reductions in lung density on CT imaging 2 years 

after cessation). Accordingly, the mechanisms by which 

smoking cessation attenuates the decline of lung function 

and reduces the risk of COPD need to be better understood. 

Many studies using new approaches are now 

underway. Studies using biomarkers and omics can provide 

insights into the potential mechanisms by which smoking 

cessation could attenuate declines in lung function. This 

review did not find any evidence to link genetic makeup 

to how cessation affects this decline. However, studies that 

evaluated the emerging areas of epigenetics, proteomics, 

and the microbiome have yielded promising findings. 
The Health Benefits of Smoking Cessation 317

Smoking Cessation

Conclusions

1. Smoking cessation remains the only established

intervention to reduce loss of lung function over time

among persons with chronic obstructive pulmonary

disease and to reduce the risk of developing chronic

obstructive pulmonary disease in cigarette smokers.

2. The evidence is suggestive but not sufficient to infer

that airway inflammation in cigarette smokers persists months to years after smoking cessation.

3. The evidence is suggestive but not sufficient to infer

that changes in gene methylation and profiles of

proteins occur after smoking cessation.

4. The evidence is inadequate to infer the presence or

absence of a relationship between smoking cessation and changes in the lung microbiome.

Asthma

Asthma is characterized by variable airflow obstruction, and its symptoms include wheezing and dyspnea 

with exertion (Chung et al. 2014). Chronic changes in the 

airway, referred to as airway remodeling, can lead to irreversible loss of lung function (Pascual and Peters 2005). 

The 2004 and 2014 Surgeon General’s reports (USDHHS 

2004, 2014) reviewed the topic of active smoking and 

asthma in children and adults, a topic updated here to 

focus on smoking cessation. Smoking has detrimental 

effects on asthma morbidity. Compared with nonsmokers 

with asthma, smokers with asthma have more severe symptoms, higher rates of hospitalization, accelerated decline 

in lung function, a shift from eosinophilia toward neutrophilia, and impaired therapeutic response to inhaled and 

oral corticosteroids (Thomson et  al. 2004; McLeish and 

Zvolensky 2010). 

Smoking as a Risk Factor for Asthma

The 2014 Surgeon General’s report concluded that 

the evidence is suggestive but not sufficient to infer a 

causal relationship between active smoking and the incidence of asthma in adults. With regard to exacerbation of 

asthma, the report concluded that the evidence is sufficient to infer a causal relationship between active smoking 

and exacerbation of asthma in adults. In the United States, 

cigarette smoking is prevalent among persons with 

asthma. Data from 2010 from the Behavioral Risk Factor 

Surveillance System show that nearly 17% of people 

without asthma smoked, and 21% of people with asthma 

smoked (CDC n.d.). For example, Silverman and colleagues 

(2003) examined nearly 2,000 persons 18–54 years of age 

who presented at an emergency department with acute 

asthma. Asthma symptoms and smoking status were 

assessed via structured interview. Of persons presenting at 

the emergency department with acute asthma, 35% were 

current cigarette smokers, and an additional 23% were 

former smokers. Interestingly, no difference in pulmonary 

function was seen between smokers and nonsmokers upon 

their arrival in the emergency department.

Some observational evidence shows an association 

between incident asthma and smoking, but the evidence 

is mixed (McLeish and Zvolensky 2010). The association 

of smoking with asthma is stronger among certain subgroups of the population. Specifically, among women, the 

prevalence of asthma is higher among cigarette smokers 

compared with nonsmokers, but findings have not been 

consistent in showing a similar difference in the prevalence of asthma among men (McLeish and Zvolensky 

2010). Additionally, women who quit smoking may have 

a higher asthma remission rate (Holm et al. 2007). Most 

studies concerning adolescents have found higher rates 

of smoking among adolescents with asthma than among 

those without asthma (McLeish and Zvolensky 2010). 

Among adults, this trend is less consistent, possibly 

because of smoking cessation among adults with asthma. 

The U.S. Black Women’s Health Study, a prospective 

cohort study with 46,182 participants, found an exposureresponse relationship between smoking and the incidence 

of adult-onset asthma. Adjusted hazard ratios for former 

active smoking, current active smoking, and exposure to 

secondhand smoke were, respectively, 1.36  (95%  confidence interval [CI], 1.11–1.67), 1.43 (95% CI, 1.15–1.77), 

and 1.21 (95% CI, 1.00–1.45) compared with never active 

or never passive smoking (Coogan et al. 2015). Although 

current evidence suggests a possible causal relationship 

between active smoking and the incidence of asthma in 

adults, the evidence is not sufficient to state conclusively 

whether smoking is a directly causal risk factor, per the 

conclusion of the 2014 Surgeon General’s report (McLeish 

and Zvolensky 2010; USDHHS 2014). 

Smoking Cessation, Asthma 

Symptoms, and Lung Function

Asthma-related morbidity and mortality are higher 

in current cigarette smokers compared with never smokers 

(Thomson et al. 2004). Smokers with asthma have more 

severe symptoms (Althuis et al. 1999; Siroux et al. 2000), 

a greater need for rescue medications (Gallefoss and Bakke 

2003), and poorer health status compared with never 

smokers (Gallefoss and Bakke 2003; Jang et  al. 2010). 

In  an experimental study of smokers with asthma, the 

decrement in FEV1 after smoking cessation was inversely 

associated with baseline FEV1. This finding suggests that 
A Report of the Surgeon General

318 Chapter 4

smokers with asthma who have worse lung function may 

be particularly susceptible to the acute effects of tobacco 

smoke (Jang et al. 2010). Compared with nonsmokers with 

asthma, smokers with atopic asthma are less responsive to 

inhaled adenosine and corticosteroids, which may point 

toward differences in airway inflammation (Oosterhoff 

et al. 1993; Lazarus et al. 2007). Admission rates to hospital for asthma and hospital-based care are higher in 

smokers than in those who have never smoked (Prescott 

et al. 1997; Sippel et al. 1999), although possibly not in 

younger adult smokers (Rasmussen et  al. 2002). The 

6-year mortality rate following a near-fatal asthma attack 

is higher for smokers than nonsmokers (age-adjusted odds 

ratio [OR] = 3.6; 95% CI, 2.0–6.2) (Marquette et al. 1992).

In combination, cigarette smoking and asthma 

accelerate the decline of lung function to a greater degree 

than either factor alone (Lange et al. 1998; Apostol et al. 

2002). For example, the Copenhagen City Heart Study, 

which included longitudinal measurement of FEV1 over 

a 15-year period, found that the average decline in FEV1 

among persons with asthma was greater in smokers than 

nonsmokers (Lange et al. 1998). The average annual decline 

in FEV1 in men with asthma who were 40–59 years of age 

was 33 mL/year in nonsmokers (n = 36) and 58 mL/year in 

smokers (n = 150; p <0.001) (Lange et al. 1998). The combination of chronic hypersecretion of mucus and smoking 

in adults with asthma was associated with a greater decline 

in FEV1 than in adults without asthma (Lange et al. 1998). 

A study of 4,000  adults who were 18–30  years of age at 

enrollment (Apostol et al. 2002) and who were followed for 

more than 10 years with serial spirometry measurements 

found that the decline in FEV1 was 8.5% in never smokers 

without asthma (n = 2,393), 10.1% in never smokers with 

asthma (n = 437), and 11.1% in smokers without asthma 

(n = 514). The combination of having asthma and smoking 

≥15 cigarettes per day (n = 101) had a synergistic effect on 

the decline in lung function, resulting in a 17.8% decline 

in FEV1 over 10 years (Apostol et al. 2002). 

Cigarette smoking has been found to decrease the 

effectiveness of inhaled corticosteroids (Thomson et  al. 

2004). The mechanisms of corticosteroid resistance in 

smokers with asthma are not well understood, but this 

resistance could result from alterations in the phenotypes of airway inflammatory cells (e.g., increased neutrophils, reduced eosinophils); changes in the glucocorticoid 

receptor α-to-β ratio (e.g.,  overexpression of glucocorticoid receptor β); and increased activation of proinflammatory transcription factors (e.g.,  nuclear factor-κB) or 

reduced activity of histone deacetylase (Thomson et  al. 

2004). Chalmers and colleagues (2002), who examined the 

effect of treatment with inhaled fluticasone propionate on 

morning and evening peak expiratory flow (PEF) among a 

cohort of steroid-naïve smokers and nonsmokers, found 

that the mean morning PEF increased significantly more 

in nonsmokers than in smokers (27 liters [L]/minute vs. 

-5 L/minute). Inhaled corticosteroids that are often prescribed to treat the exacerbations discussed in this chapter 

thus far appear to be less effective in treating asthma 

among smokers (Chalmers et  al. 2002). Chaudhuri 

and colleagues (2006) examined the effects of smoking 

cessation on lung function and airway inflammation 

among 32 smokers with asthma at 6 weeks and found a 

decreased proportion of sputum neutrophils (mean percent difference, 29  [51  to  -8]; p  =  0.013) among those 

who quit smoking, suggesting a possible mechanism for 

improved response to inhaled corticosteroids after cessation (Chaudhuri et al. 2006). 

Several studies have examined smoking cessation and 

its association with asthma symptoms and lung function 

(Table 4.27). For example, Tønnesen and colleagues (2005) 

examined the effects of smoking cessation and reduction in 

smoking on asthma symptoms. Participants were divided 

into three groups: smokers who had reduced their cigarette consumption (to fewer than seven cigarettes per day), 

former smokers who had achieved complete cessation, and 

smokers who continued smoking as usual. Participants in 

both the smoking reduction and smoking cessation groups 

also used nicotine replacement therapy as an aid to reduce 

or quit use. Those in the cessation group experienced significant decreases in the use of rescue inhalers, frequency 

of daytime asthma symptoms, and bronchial hyperreactivity, and they had a 25% reduction in inhaled steroids 

(Tønnesen et al. 2005). In addition, persons in this group 

reported significant improvements in both their overall 

and asthma-related quality of life. Compared with those 

in the cessation group, improvements were not as great 

among those who reduced their consumption of cigarettes. Chaudhuri and colleagues (2006) found significant improvements in spirometry (FEV1 and PEF) among 

former smokers after 1 week of cessation, and the improvements continued through 6 weeks of cessation. Moreover, 

asthma control improved, and after 6 weeks of cessation, 

counts of sputum neutrophils decreased. 

Observational studies suggest that cigarette 

smoking increases the risk for poor asthma control by 

as much as 175% for such outcomes as asthma attacks, 

interference with daily activities, and greater severity of 

wheezing and breathlessness (McLeish and Zvolensky 

2010). The wide range of effect sizes appears to be attributable in large measure to differences in methodology 

across these investigations. Regardless, cigarette smoking 

among persons with asthma is associated with increased 

risk of mortality, more frequent asthma attacks, exacerbations of the disease, and symptoms such as wheezing 

and nighttime awakenings (McLeish and Zvolensky 2010). 

In persons with asthma, smoking cessation is associated 
The Health Benefits of Smoking Cessation 319

Smoking Cessation

with improvements in lung function (specifically PEF), 

the number of asthma symptoms, treatment outcomes, 

and asthma-specific quality-of-life scores. 

Smoking Cessation Biomarkers and the 

Microbiome in Asthma

Counts of sputum neutrophils, an indicator of 

airway inflammation, are reported to be higher in heavy 

smokers with mild asthma compared with nonsmokers 

with asthma (Chalmers et  al. 2001). Sputum concentrations of cytokines such as IL-8 are also higher in smokers 

with asthma (Chalmers et al. 2001), but sputum concentrations in other cytokines, such as IL-18, are suppressed 

in smokers with asthma (McKay et al. 2004). The elevated 

sputum neutrophil count found in high-intensity smokers 

with asthma may be partly responsible for their reduced 

responsiveness to corticosteroids (Meagher et  al. 1996). 

Unlike eosinophils, which are exquisitely sensitive to corticosteroids, neutrophils are poorly responsive to corticosteroid therapy (Green et al. 2002), and their survival and 

proliferation are promoted by glucocorticoids. In a study 

of 32  smokers, smoking cessation resulted in reduction 

in induced sputum neutrophils by bronchoalveolar lavage 

among subjects with asthma but no change in mediator 

levels (Chaudhuri et  al. 2006). In contrast, research on 

the effect of smoking cessation on airway inflammation in 

COPD has shown that elevated levels of most inflammatory cells, including neutrophils, persist in former smokers 

Table 4.27 Studies on smoking cessation and asthma, 2009–2017

Study Design/population Findings

Tønnesen et al. 

(2005)

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

Prospective cohort

220 smokers with asthma:

 – 79 reducers (reduced consumption to 

<7 cigarettes per day)

82 quitters

59 continued smokers

Reduction and cessation groups used NRT 

as cessation aid

Quitters reported a significant decrease in use 

of rescue inhalers, frequency of daytime asthma 

symptoms and bronchial hyperactivity, and 

reduction in inhaled steroid use

Those in this group also reported significant 

improvement both in overall and asthma-related 

quality of life

Chaudhuri et al. 

(2006)

Prospective cohort

32 smokers with asthma:

 – 21 quitters

11 continued smokers

Followed up for 6 weeks 

Recorded PEF morning and night

Lung function in quitters improved significantly within

a week of stopping smoking and these improvements 

continued through 6 weeks of cessation

Broekema et al. 

(2009)

Cross-sectional

147 patients with asthma:

 – 66 never smokers

46 former smokers

35 current smokers 

Epithelial characteristics in former smokers were 

similar to those in never smokers, suggesting 

that smoke-induced changes can be reversed by 

smoking cessation

Jang et al. (2010) Prospective cohort 

22 patients with asthma who continued to smoke

10 patients with asthma who quit smoking at 

3 months

Measured FEV1

Patients with asthma who quit smoking showed 

less airway obstruction

Cerveri et al. 

(2012)

Prospective cohort 

9,092 with asthma

1,045 without asthma at 9-year follow-up

Smoking was significantly less frequent among 

participants with asthma than in the rest of the 

population (26 vs. 31%; p <0.001)

Polosa et al. 

(2014)

Prospective cohort 

18 e-cigarette users with mild-to-moderate asthma

Followed up for 24 months 

E-cigarette use ameliorated both objective and 

subjective asthma outcomes, and beneficial effects 

may persist in the long term

Munck et al. 

(2016)

Prospective cohort 

44 patients with asthma, of whom 25 quit smoking 

at 12 weeks

Although tobacco smokers with asthma had a greater 

bacterial diversity in the induced sputum compared 

with nonsmoking healthy controls, smoking cessation 

did not change microbial diversity

Notes: FEV1 = forced expiratory volume at 1 second; PEF = peak expiratory flow.
A Report of the Surgeon General

320 Chapter 4

(Turato et al. 1995; Domagala-Kulawik et al. 2003; Willemse 

et  al. 2004) and that inflammation can even increase 

(Willemse et al. 2005). Only a few studies have specifically 

assessed the lung microbiome among former smokers with 

asthma (Charlson et al. 2010; Huang et al. 2011; Morris 

et al. 2013), with Munck and colleagues (2016) finding that 

current smokers had greater bacterial diversity in their 

induced sputum and that smoking cessation did not lead 

to changes in microbial diversity at 12 weeks.

Synthesis of the Evidence

Cigarette smoking has adverse effects on the respiratory health of people with asthma and has been found 

to causally contribute to the worsening of asthma. 

Asthma involves chronic inflammation of the airways, 

and smoking has been shown to increase inflammation, 

with clinical consequences. Smoking cessation has been 

linked to improvement in a variety of clinical indicators, 

including fewer asthma symptoms; less frequent use of 

inhalers, including inhaled corticosteroids; and improved 

outcomes, including an attenuation in the decline of lung 

function, fewer asthma exacerbations, and lower mortality. 

In the 2014 Surgeon General’s report, the evidence 

was considered sufficient to infer a causal relationship 

between active smoking and asthma exacerbations in 

adults. The report did not specifically address smoking 

cessation, while offering the recommendation that people 

with asthma should not smoke, given the causal association of smoking with exacerbations.

The evidence reviewed in this report documents that 

smoking cessation improves lung function, reduces symptoms, and improves treatment outcomes among persons 

with asthma. Cohort studies have documented that cigarette smoking acts synergistically with asthma to accelerate 

the decline of lung function. With regard to the natural history of asthma, the findings of cohort studies also suggest 

that smoking cessation can attenuate the decline of lung 

function among persons with asthma (Apostol et al. 2002). 

Because smoking is a powerful cause of inflammation of the respiratory tract, cessation would be expected 

to reduce inflammation in people with asthma, thereby 

improving clinical status. Thus it is biologically plausible 

that smoking cessation would improve outcomes in people 

with asthma who smoke. The observational evidence 

is consistent with this conclusion but limited in scope, 

and there are few studies that have followed people with 

asthma over longer periods of time to characterize how 

outcomes change with increasing duration of cessation.

Conclusions

1. The evidence is suggestive but not sufficient to infer 

that smoking cessation reduces asthma symptoms 

and improves treatment outcomes and asthmaspecific quality-of-life scores among persons with 

asthma who smoke. 

2. The evidence is suggestive but not sufficient to infer 

that smoking cessation improves lung function 

among persons with asthma who smoke. 

Implications

While the evidence remains “suggestive” concerning 

smoking cessation and clinical outcomes in people with 

asthma who smoke, clinicians should recommend cessation for their patients with asthma who smoke. Smoking 

worsens the status of those with asthma, and the evidence 

reviewed in this report shows favorable consequences of 

quitting. Even the perception of a causal relationship with 

asthma among smokers may be an impetus for cessation 

(Godtfredsen et al. 2001). 

Further research is needed to address gaps in the 

evidence related to smoking cessation and asthma. One 

area that requires further investigation is the relationship 

between cigarette smoking and the response to corticosteroids among persons with asthma. The mechanisms for 

this relationship are not well understood, and smoking 

cessation studies can help to elucidate pathways and 

potential therapies, including the potential role of neutrophils in corticosteroid resistance in asthma.

Reproductive Health

The first Surgeon General’s report addressed the 

deleterious effects of maternal smoking on fetal growth 

(U.S. Department of Health, Education, and Welfare 

[USDHEW] 1964). Subsequent Surgeon General’s reports 

identified causal associations between active smoking and 

other adverse reproductive health outcomes for women 

or men, including decreased female fertility, pregnancy 

complications, preterm delivery, and erectile dysfunction (U.S.  Department of Health and Human Services 

[USDHHS] 2014). Although the effects of smoking on 

reproductive health are well established, the benefits of 

smoking cessation for reproductive health have been 

studied less extensively. This section provides current 

information on the potential benefits of smoking cessation 
The Health Benefits of Smoking Cessation 321

Smoking Cessation

for maternal health during pregnancy, for birth outcomes, 

and for female and male reproductive health.

Conclusions from Previous 

Surgeon General’s Reports

The 1990 Surgeon General’s report on the health 

benefits of smoking cessation included six conclusions on 

smoking cessation and reproductive health (Table  4.28) 

(USDHHS 1990). The report concluded that women who 

stopped smoking before or during the first trimester of 

pregnancy had infants with a birth weight similar to that 

seen among never smoking or nonsmoking women, while 

smoking cessation later in pregnancy increased infants’ 

birth weights relative to those of infants born to women 

who continued to smoke throughout pregnancy. In contrast, reductions in smoking intensity during pregnancy 

did little to reverse the smoking-related reduction of 

birth weight. The 1990 report also found that women who 

stopped smoking experienced natural menopause at an 

age similar to that of nonsmoking women, which was 1 to 

2 years later than women who were active smokers. 

Four subsequent Surgeon General’s reports provided updated conclusions on the reproductive health 

effects of smoking and the biological mechanisms underlying these effects. However, these reports did not address 

the effects of smoking cessation (USDHHS 2001, 2004, 

2010, 2014). 

Literature Review Methods

A systematic literature review was conducted to 

update the cessation-specific conclusions of the 1990 

Surgeon General’s report. The search was restricted 

to English-language articles available on PubMed or 

EMBASE  and published between January  2000 and 

February 2017. In the PubMed search strategy (Table 4.29), 

Medical Subject Headings (“MeSH”) terms were used to 

capture relevant articles. Retrieved articles included at 

least one term related to smoking cessation (e.g., “former 

smokers”) and at least one term related to reproductive 

health (e.g.,  “pregnancy”). Citations from retrieved articles and past Surgeon General’s reports were used to identify articles not captured by the search, including several 

articles published between 1997 and 1998.

Sources of Bias in Observational Studies 

of Smoking and Reproductive Health

Most studies related to prenatal maternal smoking, 

smoking cessation, and health outcomes rely on self-reports 

to characterize maternal smoking, but findings from several studies indicate that the use of self-reports to determine smoking status in pregnant women substantially 

misclassifies exposure as a result of underreporting. For 

example, various studies that assessed smoking cessation 

using both self-reports and biochemical markers, such 

as salivary or urinary cotinine, have found that pregnant 

women consistently underreport being smokers and generally overreport cessation (George et al. 2006; England 

et al. 2007; Andersen et al. 2009; Shipton et al. 2009; Dietz 

et al. 2011; Rode et al. 2013). Notably, in a study of women 

participating in a randomized trial for preeclampsia prevention, an analysis that included cotinine-validation of 

self-reported quit status found that the degree of misclassification was lower among women who reported never 

smoking or who reported quitting before pregnancy than 

among women who reported quitting after becoming 

pregnant (England et al. 2007; Rode et al. 2013). In this 

study, misclassification from over-reporting of cessation 

led to a modest overestimation of the magnitude of associations between maternal smoking and such outcomes as 

birth weight and small-for-gestational age (SGA) (England 

et al. 2007). Finally, reports on quitting late in pregnancy 

may be subject to more misclassification than reports on 

quitting early in pregnancy (Tong et al. 2015).

The degree of misclassification of smoking status 

varies across studies. Factors that may have contributed 

to this variation include the type of biomarker and the 

cut point selected for classification of active smoking, the 

country where the study was conducted, whether women 

were aware that biochemical validation would occur, 

when during the pregnancy the women were asked about 

smoking, the woman’s smoking intensity, and the woman’s 

age and other sociodemographic factors. Estimates of the 

percentage of true active smokers misclassified as quitters 

or nonsmokers have ranged from 23% to 25% (England 

et al. 2007; Shipton et al. 2009; Dietz et al. 2011), while 

estimates of the percentage of self-reported quitters who 

had evidence from a biomarker of active smoking have 

ranged from 0% to 25% (George et al. 2006; Andersen et al. 

2009; Rode et al. 2013; Tong et al. 2015). Differential misclassification of smoking status by such factors as intensity of smoking can bias the results of studies examining 

the effects of smoking or smoking cessation on birth outcomes. For example, England and colleagues (2007) found 

that women who misreported cessation were more likely 

to be light smokers (1–9 cigarettes per day) than women 

who accurately reported their smoking status. This misclassification may bias estimates of associations between 

smoking status during pregnancy and birth outcomes, 

such as hypertensive disorders of pregnancy and SGA, for 

both quitters (e.g.,  by including continuing smokers in 

the group classified as quitters) and continuing smokers 
A Report of the Surgeon General

322 Chapter 4

Table 4.28 Conclusions from the 1990 Surgeon General’s report on the health benefits of smoking cessation and 

reproductive health

Conclusions

1. Women who stop smoking before becoming pregnant have infants of the same birth weight as those born to never smokers.

2. Pregnant smokers who stop smoking at any time up to the 30th week of gestation have infants with higher birth weight than 

do women who smoke throughout pregnancy. Quitting in the first 3 to 4 months of pregnancy and abstaining throughout the 

remainder of pregnancy protect the fetus from the adverse effects of smoking on birth weight.

3. Evidence from two intervention trials suggests that reducing daily cigarette consumption without quitting has little or no 

benefit for birth weight.

4. Recent estimates of the prevalence of smoking during pregnancy, combined with an estimate of the relative risk of low birth 

weight outcome in smokers, suggest that 17 to 26 percent of low birth weight births could be prevented by eliminating smoking 

during pregnancy: in groups with a high prevalence of smoking (e.g., women with less than a high school education), 29 to 

49 percent of low birth weight births might be prevented by elimination of cigarette smoking during pregnancy. 

5. Approximately 30 percent of women who are cigarette smokers quit after recognition of pregnancy, with greater proportions 

quitting among married women and especially among women with higher levels of educational attainment.

6. Smoking causes women to have natural menopause 1 to 2 years early. Former smokers have an age at natural menopause 

similar to that of never smokers.

Source: USDHHS (1990, p. 410). 

Table 4.29 PubMed systematic search strategy

Smoking search terms Reproductive health search termsa

smoking cessation OR “former 

smoker” OR “former smokers” 

OR ex-smok* OR exsmok* OR 

quit* smok* OR stop* smok*

reproduction OR reproductive OR Reproductive Health[mh] OR Reproductive Medicine[mh] OR 

birth OR Parturition[mh] OR pregnancy OR pregnan* OR gestation* OR fertility OR infertility OR 

fertile OR infertile OR fecundability OR fecundity OR subfertility OR “sub-fertility” OR Subfertile 

OR “sub-fertile” OR amenorrhea OR conception OR Fertilization[mh] OR “spontaneous abortion” 

OR “Abortion, Spontaneous”[mh] OR stillbirth OR Miscarriage* OR Fetal Death[mh] OR preterm 

OR Premature Birth[mh] OR “Infant, Premature”[mh] OR “Obstetric Labor, Premature”[mh] 

OR placenta OR Placenta Diseases[mh] OR preeclampsia OR “Pre-Eclampsia”[mh] OR “preeclampsia” OR “fetal growth” OR Fetal Development[mh] OR Fetal Growth Retardation[mh] OR 

birthweight OR “birth weight” OR “Infant, Low Birth Weight”[mh] OR Birth Weight[mh] OR 

“fetal mortality” OR Fetal Mortality[mh] OR “neonatal mortality” OR “perinatal mortality” OR 

Perinatal Mortality[mh] OR Perinatal Death[mh] OR “infant mortality” OR Infant Mortality[mh] 

OR congenital OR Congenital Abnormalities[mh] OR SIDS OR Sudden Infant Death[mh] OR 

“Sudden Infant Death” OR menopause OR “sexual performance” OR “sexual dysfunction” OR 

“Sexual Dysfunction, Physiological”[mh] OR erection OR Penile Erection[mh] OR erectile OR 

Erectile Dysfunction[mh] OR impotence OR “Impotence, Vasculogenic”[mh] OR sperm OR 

Spermatozoa[mh] OR Spermatogenesis[mh] OR semen OR Semen Analysis[mh] OR Prenatal 

OR “pre-natal” OR Prenatal Care[mh] OR Prenatal Injuries[mh] OR Prenatal Diagnosis[mh] 

OR “Embryonic and Fetal Development”[mh]

Notes: Mh = to search Medical Subjects Headings (MeSH) in MEDLINE or PubMed.

aUsed in conjunction with all smoking search terms.

(e.g., by omitting light smokers because they incorrectly 

reported cessation) (England et al. 2007). 

Many studies of the association of tobacco use 

with pregnancy outcomes have assessed smoking status 

at a single point during pregnancy, but because women 

may change their patterns of tobacco use during pregnancy by quitting, cutting back, and/or relapsing, using a 

single assessment of exposure can result in misclassification of exposure across a pregnancy (Pickett et al. 2003, 

2005). For example, in a prospective cohort of Dutch 

women, 34% reported cessation during the first trimester, 

but were later reclassified as continuing smokers after 

responding to questionnaires in the second and third 

trimesters (Bakker et  al. 2011). Thus the assessment of 
The Health Benefits of Smoking Cessation 323

Smoking Cessation

smoking status at a single time point rather than multiple 

time points during pregnancy can result in misclassification of exposure (Pickett et al. 2009). 

Overall, women who smoke differ from those who 

do not in several ways with regard to lifestyle and behaviors, leading to the potential for confounding (Subar 

et al. 1990; Midgette et al. 1993; Maxson et al. 2012). For 

example, smokers may be more likely than nonsmokers 

to use alcohol and/or illicit substances that can affect 

birth outcomes (Coleman-Cowger et al. 2017). Fully controlling for these differences in estimating the benefits of 

quitting can be difficult, but failure to do so may result 

in unrecognized residual confounding, which was illustrated, for example, in a study of Swedish women. There, 

Juárez and Merlo (2013) compared results of a conventional multivariable linear regression analysis with those 

of a multilevel analysis that used siblings to estimate 

woman-specific, smoking-associated changes in birth 

weight (i.e., comparing the birth weights of infants born 

to the same woman whose exposure to smoking changed 

between pregnancies and controlling for birth order). The 

association between maternal smoking behavior and birth 

weight remained significant in the sibling analysis, but it 

was attenuated in comparison with the conventional analysis. Specifically, the babies of women who smoked heavily 

throughout pregnancy had an adjusted reduction in birth 

weight of 303 grams (g) relative to those of nonsmokers 

in the conventional analysis; in the sibling analysis, the 

reduction was 226 g. Using similar methods in a cohort 

of Danish births, Obel and colleagues (2016) also found 

that the association between smoking during pregnancy 

and low birth weight (<2,500 g) was moderately attenuated in a sibling analysis in comparison with a conventional analysis (adjusted odds ratio [aOR]  =  1.68 and 

2.60, respectively). 

Pregnancy Complications

Ectopic Pregnancy

An ectopic pregnancy, which occurs when implantation of the fertilized ovum takes place outside the uterus, 

most often in the fallopian tubes, affects an estimated 1% 

to 2% of pregnancies (CDC 1995; Van Den Eeden et  al. 

2005). The 1990 Surgeon General’s report found only 

sparse evidence that current or former smokers were 

at higher risk of ectopic pregnancy (Chow et  al. 1988; 

USDHHS 1990; Kalandidi et  al. 1991; Stergachis et  al. 

1991; Parazzini et  al. 1992; Phillips et  al. 1992; Saraiya 

et  al. 1998; Bouyer et  al. 2003; Karaer et  al. 2006), but 

the 2014 Surgeon General’s report found sufficient evidence to conclude that active smoking causally increases 

the risk of ectopic pregnancy (USDHHS 2014). Potential 

mechanisms underlying this relationship identified from 

animal research include damage to a fallopian tube or dysfunction of that structure, damage to the oviduct epithelium, a decrease in the ratio of ciliated to secretory oviductal cells, a decrease in smooth muscle contractions of 

the oviduct, and decreased oviductal blood flow (USDHHS 

2014). A review of studies that included former smokers 

with an ectopic pregnancy found that the majority of 

studies reported no significant association between that 

outcome and past smoking (Chow et al. 1988; Kalandidi 

et al. 1991; Stergachis et al. 1991; Parazzini et al. 1992; 

Phillips et al. 1992; Saraiya et al. 1998; Bouyer et al. 2003; 

Karaer et al. 2006).

Summary of the Evidence

The 2014 Surgeon General’s report concluded that 

“the evidence is sufficient to infer a causal relationship 

between maternal active smoking and ectopic pregnancy” 

(USDHHS 2014, p. 487). A systematic review of the literature did not identify additional studies since that report 

that assessed the risk of ectopic pregnancy among former 

smokers. Therefore, a new conclusion on smoking cessation and ectopic pregnancy is not provided in this report. 

Spontaneous Abortion

Spontaneous abortion is defined as the involuntary termination of an intrauterine pregnancy before 

20 weeks’ gestation, although it is sometimes defined as 

occurring before 28 weeks. Recognized spontaneous abortion occurs in approximately 12% of pregnancies, usually 

before 12 weeks’ gestation (McNair and Altman 2011). Very 

early losses may go unrecognized, and the true incidence 

of pregnancy loss may be as high as 30% to 45% (Wilcox 

et al. 1988; Eskenazi et al. 1995). 

The 1990 Surgeon General’s report did not provide a conclusion about the association between smoking 

cessation and spontaneous abortion because of a paucity 

of research among former smokers. The 2004 Surgeon 

General’s report, however, reviewed the evidence on an 

association between maternal smoking and spontaneous 

abortion, finding the evidence suggestive but not sufficient to infer a causal relationship (USDHHS 2004), and 

cessation was not examined. The 2010 Surgeon General’s 

report updated the 2004 report, but it did not include conclusions on the strength of evidence for causality. Proposed 

mechanisms underlying a potential association that were 

set forth in that report included effects of hypoxia due to 

exposure to CO, vasoconstrictive and antimetabolic effects 

resulting from placental insufficiency, and the direct 

toxic effects of constituents in cigarette smoke (USDHHS 

2010). The 2014 Surgeon General’s report noted that 
A Report of the Surgeon General

324 Chapter 4

studies have found associations between active smoking 

and spontaneous abortion, but it considered the evidence 

suggestive but not sufficient to reach a causal conclusion, 

in part because of study limitations, including difficulty 

controlling for potential confounders and a lack of data on 

conception karyotype (USDHHS 2014). 

Summary of the Evidence

The 2014 Surgeon General’s report concluded that 

“the evidence is suggestive, but not sufficient, to infer a 

causal relationship between maternal active smoking and 

spontaneous abortion” (USDHHS 2014, p. 489). However, 

a systematic review of the literature identified no known 

studies that have specifically assessed the association 

between smoking cessation and risk of spontaneous abortion; therefore, this report does not make any new conclusions regarding this outcome.

Placental Abruption

Placental abruption, which affects an estimated 

0.3% to 2% of pregnancies (Ananth et  al. 2015; Ruiter 

et al. 2015), is the premature separation of the placenta 

from the uterine wall (Rasmussen et  al. 1996; Ananth 

et  al. 2001, 2005; Kyrklund-Blomberg et  al. 2001; Luke 

et  al. 2017; Räisänen et  al. 2018). Placental abruption 

can lead to perinatal mortality (Raymond and Mills 1993; 

Ananth and Wilcox 2001; Kyrklund-Blomberg et al. 2001; 

Räisänen et  al. 2018), neonatal asphyxia (Heinonen and 

Saarikoski 2001), preterm delivery, significant maternal 

blood loss, and disseminated intravascular coagulation 

(Hladky et al. 2002). 

The only study on the risk of placental abruption 

(Naeye 1980) cited in the 1990 Surgeon General’s report 

(USDHHS 1990) found that smoking for more than 

6 years was associated with an increased risk of placental 

abruption, but that women who quit smoking by their 

first prenatal visit were not at increased risk of placental 

abruption relative to never smokers. The 2004 Surgeon 

General’s report found sufficient evidence to conclude that 

maternal smoking increases the risk of placental abruption, and it included one study demonstrating increased 

risk of this event in former smokers (Spinillo et al. 1994; 

USDHHS 2004). That study, however, was limited by its 

small sample, and it did not include information about the 

timing of cessation. The 2010 Surgeon General’s report 

reviewed potential mechanisms underlying the association between smoking and abruption, including smokingrelated degenerative and/or inflammatory changes in the 

placenta, reduced vitamin C levels and impaired collagen 

synthesis in smokers, microinfarcts, and atheromatous 

changes in placental vessels (USDHHS 2010). That report 

identified one study indicating that, when women stop 

smoking between pregnancies, their risk of abruption is 

similar to that of nonsmokers (Ananth and Cnattingius 

2007). Because abruption is a rare outcome, large, population-based samples are needed to study risk factors for 

its occurrence. One study published since the 2010 report 

(Räisänen et al. 2014) had a sufficient sample to examine 

smoking cessation and placental abruption. In this population-based cohort of more than 1  million births in 

Finland, Räisänen and colleagues (2014) found that placental abruption occurred in 0.3% of pregnancies among 

both nonsmokers and women who quit smoking during 

the first trimester of pregnancy, but in 0.6% of pregnancies among women who continued to smoke after the first 

trimester. That study, however, did not include adjustments for covariates, and the results of testing for statistical significance were not presented. A smaller study of 

births at an Australian hospital found that women who 

were smokers at the first antenatal visit did not differ significantly in risk of placental abruption from nonsmokers 

(aOR  =  0.82; 95% confidence interval [CI], 0.27–2.44) 

or from women who quit smoking within a year before 

their first antenatal visit (aOR = 2.45; 95% CI, 0.20–29.29) 

(Bickerstaff et al. 2012). 

Summary of the Evidence

The 2004 Surgeon General’s report found sufficient 

evidence to conclude that maternal smoking increases the 

risk of placental abruption. Since then, only two studies 

have examined smoking cessation and risk of placental 

abruption, and both had important methodological limitations. Consequently, the evidence is inadequate to infer 

that smoking cessation before or during early pregnancy 

reduces the risk of placental abruption compared with 

continued smoking. 

Placenta Previa

Placenta previa is the complete or partial obstruction of the cervix by the placenta, a problem that affects 

an estimated 0.4% to 0.7% of births (Comeau et al. 1983; 

Iyasu et  al. 1993; Faiz and Ananth 2003; Luke et  al. 

2017). Placenta previa can lead to important maternal 

and infant complications, including preterm delivery, 

hemorrhage, and even maternal, fetal, or neonatal death 

(Salihu et al. 2003; Creasy et al. 2004). One mechanism 

through which smoking could increase risk for this condition is compensatory placental enlargement in response 

to chronic hypoxia and ischemia resulting from smoking 

(USDHHS 2010).

The 1990 Surgeon General’s report cited only one 

study examining the risk of placenta previa among former 

smokers (Naeye 1980); this study found that women who 

quit smoking before or during early pregnancy were 
The Health Benefits of Smoking Cessation 325

Smoking Cessation

at increased risk relative to never smokers. The 2004 

Surgeon General’s report found sufficient evidence to 

conclude that active smoking increases the risk of placenta previa, but it did not address risk in former smokers 

(USDHHS 2004). Since the 2004 report, two studies have 

examined placenta previa in quitters. In a study of Finnish 

women, Räisänen and colleagues (2014) observed that placenta previa occurred in an estimated 0.2% of pregnancies in each of four exposure groups (nonsmokers, women 

who quit smoking during the first trimester, women who 

continued to smoke after the first trimester, and women 

for whom no information was available on their smoking 

status). As indicated earlier, however, the study did not 

adjust for covariates, and the results of testing for significance were not presented. In their study of Australian 

women, Bickerstaff and colleagues (2012) found that 

women who had quit smoking in the 12 months before 

entry into prenatal care had a reduced risk of placenta 

previa compared with those still smoking when they 

entered prenatal care, but the difference was not statistically significant (aOR = 0.45; 95% CI, 0.16–1.29). 

Summary of the Evidence

Since the 2004 Surgeon General’s report, only two 

studies have examined smoking cessation and risk of placental abruption, and both had important methodological 

limitations. Consequently, the evidence is inadequate to 

determine whether smoking cessation before or during 

pregnancy reduces the risk of placenta previa compared 

with continued smoking. 

Premature Rupture of Membranes

Premature rupture of the membranes (PROM) 

refers to rupture of the amniotic sac before the onset of 

labor. When this occurs before 37 weeks’ gestation, it is 

referred to as preterm PROM (PPROM). PPROM complicates 1–2% of pregnancies, and it may contribute to up to 

40% of preterm deliveries (Arias and Tomich 1982; Mercer 

et al. 2000; Lee and Silver 2001; Bond et al. 2017; Mercer 

2017). PPROM (Smith et  al. 2005) increases perinatal 

morbidity and mortality through increased rates of preterm delivery and by elevating the risk of intra-amniotic 

infection, neonatal sepsis, placental abruption, and pulmonary hypoplasia (Bond et  al. 2017; Sim et  al. 2017). 

Risk factors for PPROM include nutritional deficiencies 

in vitamin C (Hadley et al. 1990; Casanueva et al. 1993; 

Woods Jr et al. 2001; Siega-Riz et al. 2003), copper (Artal 

et  al. 1979; Kiilholma et  al. 1984), and zinc (Sikorski 

et al. 1988; Harger et al. 1990; Ekwo et al. 1992; Scholl 

et  al. 1993); vaginal bleeding (Harger et  al. 1990; Ekwo 

et al. 1992; Committee on Practice Bulletins—Obstetrics 

2016); bacterial vaginosis (Kurki et al. 1992; Mercer et al. 

2000); and intra-amniotic infections (Naeye and Peters 

1980; Ekwo et al. 1993; Heffner et al. 1993; Asrat 2001; 

Committee on Practice Bulletins—Obstetrics 2016). 

PROM may result from structural deficiencies of the chorioamniotic membranes (Lee and Silver 2001; Tchirikov 

et al. 2018), disruptions in collagen metabolism (Draper 

et al. 1995; Tchirikov et al. 2018), and accelerated senescence of membranes because of high levels of oxidative 

stress (Menon et al. 2014). 

The 1990 Surgeon General’s report on smoking 

cessation did not consider associations between cessation and PROM. The 2004 Surgeon General’s report on 

smoking concluded that active smoking causally increases 

the risk of PROM (USDHHS 2004). Hypothesized mechanisms included effects of smoking on the immune system, 

resulting in increased risk of genital tract infections or 

inflammatory responses or reductions in nutrients, such 

as vitamin C (USDHHS 2010). One study included in the 

2004 report assessed risk in former smokers; the aOR for 

PPROM among quitters compared with never smokers 

was less than that for continuing smokers versus never 

smokers (aOR = 1.58; 95% CI, 0.77–3.27 and aOR = 2.08; 

95% CI, 1.37–3.13, respectively), suggesting that smoking 

cessation may reduce the risk of PPROM compared with 

continued smoking (Harger et al. 1990). 

Four studies published since the 2004 Surgeon 

General’s report have examined the risk of PROM and/or 

of PPROM in smokers and quitters. Bickerstaff and colleagues (2012) found that the risk of term PROM in 

women who had quit smoking in the 12 months before 

entry into prenatal care did not differ significantly from 

that of women still smoking when they entered prenatal care (aOR = 0.61; 95% CI, 0.33–1.15). Later, Blatt 

and colleagues (2015) analyzed data from certificates of 

live births in Ohio and found that women who quit after 

the second trimester had a higher incidence of PROM 

(5.3%) than nonsmokers and continuing smokers (2.8% 

and 3.2%, respectively), but they did not report results 

of testing for statistical significance or adjustments for 

confounders. In  a subsample of women in this cohort 

with a previous preterm delivery, Wallace and colleagues 

(2017) found that second-trimester quitters also experienced the highest prevalence of PROM (14.4%), with 

rates of 6.2% and 7.3% for nonsmokers and continuing 

smokers, respectively. Again, potential confounding was 

not addressed, and it is possible that the findings could 

be explained by reverse causation (i.e.,  the occurrence 

of pregnancy complications could have motivated latepregnancy cessation). Finally, in a study involving data 

from three randomized trials of metronidazole for bacterial vaginosis that included more than 4,000  deliveries, 

Andres and colleagues (2013) found no differences in risk 

of PPROM between nonsmokers (4.1%), smokers who 
A Report of the Surgeon General

326 Chapter 4

quit during pregnancy (4.2%), and continuing smokers 

(4.5%); the OR for quitters was 1.04 (95% CI, 0.55–1.95) 

in a comparison with nonsmokers. Adjustment for demographic and obstetrical factors did not change this finding.

Summary of the Evidence

The 2004 Surgeon General’s report found sufficient 

evidence to conclude that maternal smoking increases 

the risk of PROM (USDHHS 2004). Since then, studies 

examining the effect of smoking cessation compared 

with continuing to smoke on the risk of PROM have not 

shown significant reductions in risk, and in one sample 

from Ohio, PROM risk appears to have increased in quitters. Therefore, the evidence is inadequate to determine 

whether smoking cessation before or during pregnancy 

reduces the risk of PROM compared with continuing 

to smoke.

Preeclampsia

Preeclampsia is a syndrome of reduced organ perfusion attributable to vasospasm and endothelial activation that is marked by proteinuria, hypertension, and dysfunction of the endothelial cells lining the uterus, with 

onset after 20 weeks’ gestation. Eclampsia refers to a condition in which preeclampsia is accompanied by generalized seizures not explained by other causes (Cunningham 

et al. 2013). Preeclampsia affects an estimated 1% to 6% 

of pregnancies (Abalos et al. 2013). Advances in research 

during the past 15 years have led to significant progress 

in our understanding of the etiology of preeclampsia. 

A process known as pseudo-vascularization enables 

increased uteroplacental perfusion and adequate oxygen 

and nutrient transport to the fetus by converting lowcapacity uterine spiral arteries into high-capacitance, lowresistance vessels; this requires the upregulation of proangiogenic molecules in processes completed by around 

20 weeks’ gestation. Evidence indicates that preeclampsia 

is a manifestation of an imbalance between proangiogenic factors, such as placental growth factor (PlGF), and 

antiangiogenic factors, such as soluble fms-like tyrosine 

kinase  1 (sFlt-1) and soluble endoglin (sEng). Elevated 

levels of sFlt-1 and reduced levels of PlGF have been documented in women with preeclampsia, and evidence of 

this imbalance can precede the onset of clinical disease 

(Chaiworapongsa et al. 2004; Levine et al. 2004; Robinson 

et al. 2006). Importantly, pseudo-vascularization is incomplete in preeclampsia; cytotrophoblasts do not adequately 

invade the spiral arteries, resulting in placental ischemia, 

downregulation of proangiogenic vascular endothelial 

growth factor (VEGF) family molecules, and upregulation of antiangiogenic placental factors, such as sFlt-1 and 

sEng. The etiology of abnormal placentation that precedes 

preeclampsia is uncertain, but it may involve placental 

hypoxia, oxidative stress, and genetic factors (Jim  and 

Karumanchi 2017).

An inverse association between maternal cigarette 

smoking and the risk of preeclampsia has been recognized 

for decades, and now some mechanistic understanding 

exists of this association. Smoking during pregnancy has 

been associated with reduced sFlt-1 levels in uncomplicated pregnancies (Levine et  al. 2006; Jeyabalan et  al. 

2008), and a reduction in the ratio of sFlt-1:PlGF has been 

described in smokers with preeclampsia (Jääskeläinen 

et  al. 2017). Notably, reductions in the risk of preeclampsia have not been observed in users of smokeless 

tobacco, suggesting that nicotine is not the agent responsible for reduced risk in cigarette smokers. In an sFlt-1 

preeclampsia-like mouse model, treatment with low-dose 

CO prevented late-gestation hypertension, proteinuria, 

and reduced Bowman’s space in the kidneys (Venditti et al. 

2014), supporting a role for CO rather than nicotine. 

Some investigators have proposed that preeclampsia 

is a two-stage disease, requiring abnormal placentation, 

insufficient invasion of extravillous cytotrophoblasts, 

insufficient remodeling of the maternal spiral arteries, 

and reduced placental perfusion in the first stage, followed 

by the clinical stages of the disease that involve the release 

of damaging endothelial factors into the maternal circulation (Roberts and Hubel 2009; Palei et al. 2013; Gathiram 

and Moodley 2016). It is unclear whether smoking could 

affect the risk of preeclampsia in one or both of these 

stages. Developing a better understanding of the implications of the timing of exposure to cigarette smoking in the 

risk of preeclampsia could lead to a better understanding 

of the underlying pathophysiological process and point to 

potential treatments. 

The 1990 Surgeon General’s report found that the 

available data supported the idea that former smokers 

were at reduced risk of preeclampsia relative to never 

smokers (although to a lesser extent than active smokers) 

(Marcoux et al. 1989; USDHHS 1990), but there was inadequate evidence from which to draw causal conclusions 

(USDHHS 1990). The 2004 Surgeon General’s report 

concluded that maternal active smoking is causally associated with reduced risk of preeclampsia, but it did not 

review the outcomes with regard to former smokers 

(USDHHS 2004). The 2010 and 2014 reports reviewed 

potential underlying mechanisms (summarized above), 

but they did not review the outcomes for risk relative to 

smoking cessation. 

A 2007 review of preeclampsia and smoking included 

six studies of the risk of preeclampsia in quitters (England 

and Zhang 2007); of the three studies that evaluated risk 

in women who quit before pregnancy, none found a significant protective effect among quitters (Marcoux et al. 
The Health Benefits of Smoking Cessation 327

Smoking Cessation

1989; England et al. 2002; Parazzini et al. 2003). Four of 

the six studies examined cessation during pregnancy: one 

found a significantly reduced risk in quitters (Sibai et al. 

1995), and three reported point estimates less than unity 

but no statistically significant associations (Marcoux et al. 

1989; Martin et al. 2000; England et al. 2002). Finally, one 

study combined women who quit before pregnancy with 

women who quit during early pregnancy and reported 

no significant associations for any intensity of smoking 

(Zhang et al. 1999).

Table 4.30 presents eight studies published in 2007 

or later and not included in the above review that assessed 

the relationship between smoking status (including cessation) and risk of preeclampsia. One of the eight (England 

et al. 2007) was a reanalysis of an earlier study (England 

et al. 2002) that was included in the review by England 

and Zhang (2007), but in the reanalysis, the authors used 

urine cotinine to validate cessation. Two of the eight 

studies combined preeclampsia with gestational hypertension and thus did not evaluate preeclampsia separately 

(England et al. 2007; Blatt et al. 2015); two assessed cessation before pregnancy (Blatt et al. 2015; Kharkova et al. 

2017); one combined cessation before pregnancy with 

cessation during early pregnancy (England et  al. 2007); 

and six assessed cessation during pregnancy (Fasting 

et al. 2009; Xiong et al. 2009; Wikstrom et al. 2010; Engel 

et al. 2013; Räisänen et al. 2014; Blatt et al. 2015). Five 

of the eight studies reported results of statistical testing, 

and none found a significant reduction in the risk of preeclampsia among quitters. Two of the three studies not 

reporting results of statistical testing reported prevalence 

estimates in quitters that were lower than those in nonsmokers (Räisänen et al. 2014; Blatt et al. 2015), but in 

one study, this was only true for women who quit in the 

second trimester (Blatt et al. 2015), and neither of these 

studies adjusted for potential confounders (preeclampsia 

was not a primary outcome in either study). Of the six 

studies assessing cessation during pregnancy, the timing 

of cessation varied, including at greater than 28  weeks 

gestation (Fasting et al. 2009), in the first 20 weeks gestation or the second 20 weeks gestation (Xiong et al. 2009), 

between 15 and 30 weeks gestation (Wikstrom et al. 2010), 

in the first trimester or in the second trimester (Engel 

et  al. 2013), and in the first trimester (Räisänen et  al. 

2014; Blatt et al. 2015).

All eight studies found lower point estimates for risk 

of preeclampsia among women who continued to smoke 

during pregnancy compared with women who did not 

smoke (range of aORs  =  0.5–0.8) (England et  al. 2007; 

Fasting et al. 2009; Xiong et al. 2009; Wikstrom et al. 2010; 

Engel et al. 2013; Räisänen et al. 2014; Blatt et al. 2015; 

Kharkova et al. 2017). Findings were statistically significant in four studies (England et al. 2007; Wikstrom et al. 

2010; Engel et al. 2013; Kharkova et al. 2017) and not significant in one study (Xiong et al. 2009), and the results 

of statistical testing were not presented in three studies 

(Fasting et al. 2009; Räisänen et al. 2014; Blatt et al. 2015). 

Of interest, one of the three studies with a significant 

finding was a large population-based study in Sweden in 

which women who did not smoke at the first antenatal 

visit, but who had resumed by the third trimester, had a 

significantly reduced risk of preeclampsia compared with 

women who did not smoke during pregnancy (aOR = 0.65; 

95% CI, 0.50–0.85) (Wikstrom et al. 2010).

Summary of the Evidence

The 2004 Surgeon General’s report concluded 

that maternal active smoking is causally associated with 

reduced risk of preeclampsia (USDHHS 2004). Results 

of studies published since the 2004 report provide additional support that continued smoking during pregnancy is associated with reduced risk of preeclampsia. 

However, the review did not find substantial evidence to 

support an inverse association between smoking before or 

during early pregnancy and reduced risk of preeclampsia 

among women who quit smoking before late pregnancy. 

Therefore, the evidence is insufficient to conclude that 

smoking during early or mid-pregnancy alone, and not 

during late pregnancy, is associated with a reduced risk 

of preeclampsia. Continued smoking may reduce the risk 

of preeclampsia through its effects on angiogenic factors 

late in pregnancy rather than through upstream effects 

on placentation during early pregnancy, but the evidence is currently insufficient to draw conclusions about 

such mechanisms. 

Gestational Weight Gain

Weight gain associated with smoking cessation has 

been well described in the general population (reviewed 

by Bush et al. 2016), but it has been less well studied in 

pregnant and postpartum women. Fear of weight gain 

and/or weight retention could be a barrier to cessation or 

sustained abstinence from smoking in pregnant and postpartum women (Lawson 1994; Hotham et al. 2002; Berg 

et al. 2008). Gaining weight above the recommended levels 

(Institute of Medicine [IOM] 2009) can result in infants’ 

being born large for gestational age (Goldstein et al. 2017), 

and weight gain below the recommended levels can result 

in infants’ being born small for gestational age or with low 

birth weight (Siega-Riz et  al. 2009). Smoking cessation 

during pregnancy could have unintended adverse effects 

on pregnancy or other health outcomes by increasing the 

number of pregnancies with excessive weight gain; conversely, smoking cessation-related weight gain could also 

reduce the number of pregnancies with inadequate weight 
Study Design Tobacco exposure Outcome definition Outcomes/findings Comments

England et al. 

(2002) (original 

analysis); 

England et al. 

(2007)

(reanalysis)

•

•

•

•

Randomized trial for 

preeclampsia prevention 

(2007 study was a 

reanalysis of 2002 study)

n = 4289

1992–1995

United States (multisite)

•

•

l

•

•

•

•

•

Nonsmokers: Never smoked regularly

Quit before pregnancy: Quit before 

ast menstrual period, validated with 

cotinine mid-pregnancy

Quit during pregnancy: Quit after last 

menstrual period, validated with cotinine 

mid-pregnancy

Continued smoking: Smoking at 

study enrollment

Smoking status based on self-reports 

obtained at study enrollment

(13–21 weeks’ gestation) in 2007 study

Quit status validated with urine cotinine 

concentration obtained mid-pregnancy 

(mean: 28 weeks)

For 2007 analysis, quit groups were 

combined

2002 analysis:

• Preeclampsia: Gestational 

hypertension plus 

proteinuria within 7 days 

or the development of 

HELLP syndrome or 

eclampsia in the presence 

of hypertension

2007 analysis: 

• Hypertensive disorders 

of pregnancy: Pregnancyassociated hypertension 

without proteinuria, 

preeclampsia, or 

eclampsia

2002 analysis—adjusted RR for 

preeclampsia (95% CI):

•

•

•

Quit before pregnancy: 1.1 (0.7–1.7)

Quit during pregnancy: 0.9 (0.6–1.3)

Continued smoking: 0.7 (0.5–1.1)

2007 reanalysis—crude and adjusted OR 

for hypertensive disorders of pregnancy 

(95% CI):

• Quit preconception or by mid-pregnancy:

–

–

Unadjusted: 0.9 (0.8–1.2)

Adjusted: 1.1 (0.9–1.3)

• Continued smoking:

–

–

Unadjusted: 0.6 (0.5–0.7)

Adjusted 0.6 (0.5–0.8)

Reanalysis of data used in 

2002 study after obtaining 

cotinine validation of 

smoking status

Results adjusted for 

maternal BMI, study 

center, and private 

health insurance

Did not account for 

alcohol or substance use

Fasting et al. 

(2009)

• Prospective intervention 

study to prevent allergies 

in children

• n = 711

• 2000–2002

• Norway

• Nonsmoker: Not smoking when 

became pregnant

• Quit smoking: Smoking when became 

pregnant, quit by study enrollment

• Continued smoking: Smoking when 

became pregnant, still smoking

at enrollment

• Smoking status based on self-reports 

collected at enrollment (median 

gestational age: 11 weeks, all <28 weeks)

Preeclampsia assessed by 

maternal questionnaire

Number (%) of women with preeclampsia

• Nonsmoker: 21 (4%)

• Quit smoking: 11 (10%)

• Continued smoking: 1 (2%)

Results not adjusted for 

potential confounders

Results of statistical 

testing not presented

Did not account for 

alcohol or substance use

A Report of the Surgeon General

328 Chapter 4

Table 4.30 Studies on smoking cessation and preeclampsia
Study Design Tobacco exposure Outcome definition Outcomes/findings Comments

Xiong et al.

(2009)

•

•

•

•

Case-control study

n = 337

2003–2006

Quebec, Canada

•

•

•

•

•

Nonsmokers: Did not smoke before 

or during pregnancy

Quit smoking early: Smoked during 

pregnancy but quit in the first 20 weeks

Quit smoking late: Smoked during 

pregnancy but quit in the second 

20 weeks of pregnancy

Continued smoking: Smoked before 

and during pregnancy

Smoking status based on self-reports 

ascertained from interviews conducted 

during postpartum period

Preeclampsia: Blood 

pressure at least 140/90

on two occasions at 

least 4 hours apart after 

20 weeks’ gestation and 

with proteinuria

Unadjusted and adjusted OR for 

preeclampsia (95% CI):

•

•

Nonsmokers: Reference

Quit smoking early:

–

–

Unadjusted: 0.91 (0.42–1.96)

Adjusted 1.03 (0.41–2.60)

• Quit smoking late:

–

–

Unadjusted: 0.79 (0.21–2.96)

Adjusted 0.78 (0.12–5.02)

• Continued smoking:

–

–

Unadjusted: 0.63 (0.23–1.73)

Adjusted 0.62 (0.16–2.37)

Results adjusted for 

maternal age, race,

education, marital 

status, family income, 

BMI, gravidity, abortion, 

alcohol consumption,

and cesarean section

Did not account for 

alcohol or substance use

Wikström et al. 

(2010)

• Population-based 

cohort study

• Swedish Medical Birth 

Register

• Singleton, term births

• n = 379,214

• 1999–2006

• Swede

• Nonuser: Did not smoke or use tobacco 

at either study visit (early or late)

• Quit by late pregnancy: Smoked at the 

early visit but not the late visit

• Continued smoking: Smoked at the 

time of both visits (early and late)

• Started smoking by late pregnancy: 

Did not smoke at early visit but 

smoked at late visit

• Smoking status obtained by midwives 

from maternal self-reports at entry into 

prenatal care (<15 weeks’ gestation) and 

at 30–32 weeks’ gestation

Preeclampsia identified 

using ICD-10 codes

Blood pressure ≥140/90 

with proteinuria after 

20 weeks’ gestation

Adjusted OR for preeclampsia:

• Nonsmoker: Reference

• Quit by late pregnancy: 0.94 (0.83–1.08)

• Continued smoking: 0.50 (0.45–0.56)

• Started smoking by late pregnancy: 

0.65 (0.50–0.85)

Results adjusted for earlypregnancy BMI, maternal 

age, parity, and years of 

education

Did not account for 

substance use

Engel et al. 

(2013)

•

•

•

•

Population-based 

prospective cohort

n = 70,729

1999–2008

Norway

•

•

•

•

•

•

•

•

Nonsmoker: Never smoked

Smoked first trimester only

Smoked first and second trimesters

Smoked first and third trimesters

Smoked third trimester only

Smoked all trimesters

Smoking status obtained from maternal 

interviews conducted in early pregnancy 

(~18 weeks) and late pregnancy

(~30 weeks)

Preeclampsia obtained 

from registry, diagnosis 

obtained by midwife from 

antenatal medical record

Adjusted OR for preeclampsia (95% CI):

•

•

•

•

•

•

Nonsmoker: Reference

Smoked first trimester only: 0.99 

(0.87–1.11)

Smoked first and second trimesters: 

0.89 (0.64–1.23)

Smoked first and third trimesters: 

0.62 (0.31−1.27)

Smoked third trimester only: 0.78 

(0.20−3.09)

Smoked all trimesters: 0.57 (0.46–0.70)

Results adjusted for parity, 

maternal education, BMI, 

education level, diabetes, 

and multiple observations 

per woman

Did not account for 

alcohol or substance use

Table 4.30 Continued

The Health Benefits of Smoking Cessation 329
Study Design Tobacco exposure Outcome definition Outcomes/findings Comments

Räisänen et al 

(2014)

• Population based 

retrospective cohort

• Finnish Medical 

Birth Register 

• Singleton deliveries, 

live or stillborn after 

22 weeks’ gestation

• n = 1,164,953

• 1991–2010

• Finland

• Nonsmokers

• Quit smoking: Quit during the first 

trimester

• Continued smoking: Still smoking 

after the first trimester

• Smoking history based on self-reports 

ascertained from the Finnish Medical 

Birth Register

• Details on when and how data were 

collected were not reported

Preeclampsia definition 

and ascertainment not 

described

Percentage preeclampsia:

• Nonsmokers: 2.0%

• Quit smoking: 1.1%

• Continued smoking: 1.3%

Results not adjusted for 

potential confounders

Results of statistical 

testing not presented

Did not account for 

alcohol or substance use

Blatt et al. 

(2015)

•

•

•

•

•

Population-based 

retrospective cohort

Ohio certificates of 

live birth

n = 927,424

2006–2012

Ohio

•

•

•

•

•

•

Nonsmoker: Did not smoke during 

the 3 months before pregnancy or 

during pregnancy

Quit preconception: Smoked during 

the 3 months before pregnancy but 

not during pregnancy

Quit first trimester: Smoked first 

trimester only

Quit second trimester: Smoked first 

and second trimester, not third

Continued smoking: Smoked 

throughout pregnancy

Smoking history ascertained from vital 

statistics data and certificates of live birth

Gestational hypertension/

preeclampsia combined; 

obtained from certificate 

of live birth

Percentage gestational hypertension/

preeclampsia:

•

•

•

•

•

Nonsmokers: 4.6%

Quit preconception: 5.2%

Quit first trimester: 4.9%

Quit second trimester: 4.2%

Continued smoking: 3.3%

Findings not adjusted for 

potential confounders

Results of statistical 

testing not presented

Did not account for 

alcohol or substance use

Kharkova et al. 

(2017)

• Population-based study 

using registry data

• n =39,566

• 2006–2009

• Russia

• Nonsmokers: Did not smoke before or 

during pregnancy

• Quit smoking: Smoked before but not 

during pregnancy

• Continued smoking: Smoked before 

and during pregnancy

• Smoking status based on self-reports 

obtained at first antenatal visit

Preeclampsia or eclampsia 

classified according to ICD10 definitions: hypertension 

≥140/90 accompanied by 

edema and proteinuria 

with onset after 20 weeks’ 

gestation; eclampsia was 

convulsions or coma in 

pregnant or puerperal 

women with hypertension, 

edema, or proteinuria

OR for eclampsia/preeclampsia:

• Smokers: Reference

• Quit smoking:

– Unadjusted: 1.09 (0.91–1.30)

– Adjusted: 1.10 (0.91–1.32)

• Nonsmokers:

– Unadjusted: 1.32 (1.19–1.47)

– Adjusted: 1.37 (1.23–1.54)

maternal age, residence, 

ethnicity, marital status, 

parity, alcohol abuse, 

year of delivery,BMI, and 

excessive weight gain

Results adjusted for

Did not account for 

substance use

Table 4.30 Continued

A Report of the Surgeon General

330 Chapter 4

Notes: BMI = body mass index; CI = confidence interval; kg = kilogram; ICD = International Classification of Diseases; lbs = pounds; HELLP = hemolysis, elevated liver enzymes, and low platelet 

count; OR = odds ratio; RR = risk ratio: SD = standard deviation.
The Health Benefits of Smoking Cessation 331

Smoking Cessation

gain. In 2015, 48% of U.S. women gained weight in excess 

of recommended levels, and 21% gained below recommended levels (CDC 2016b).

The 1990 Surgeon General’s report noted that, compared with continued smoking, cessation during pregnancy may be associated with increased gestational weight 

gain (USDHHS 1990). More recent Surgeon General’s 

reports have not addressed gestational weight gain and 

smoking cessation. 

In a 2017 Cochrane Review of psychosocial interventions for supporting women to stop smoking during 

pregnancy, two of the identified randomized clinical trials 

addressed weight gain and also included biochemical validation of cessation (Chamberlain et al. 2017). One found a 

significant increase in weight gain by 8 months’ gestation 

of 1.0  kilogram (kg) (2.2  pounds [lbs]) in the intervention versus the control group (Sexton and Hebel 1984); 

the other, which had fewer participants, found a 2.8-kg 

(6.2 lbs) unadjusted increase in weight gain among quitters 

compared with continuing smokers (Washio et al. 2011). 

This difference was no longer significant after adjustment 

for potential confounders (including pre-pregnancy BMI), 

but those possible confounders did not include gestational 

age at delivery. A significant increase in mean gestational 

weight gain per 10% increase in the number of negative 

smoking tests (during the course of the study) was not 

significant after adjustment for birth weight, suggesting 

that at least some of the potential effects of cessation on 

weight gain were from an increase in fetal growth (Washio 

et al. 2011).

Various observational studies have also found 

increased gestational weight gain in quitters compared with 

continuing smokers. Of six observational studies published 

since 2000, one examined gestational weight gain among 

women by smoking status across two consecutive pregnancies (Abrevaya 2008), and five examined this outcome by 

smoking status in individual pregnancies (Favaretto et al. 

2007; Adegboye et al. 2010; Rode et al. 2013; Blatt et al. 

2015; Hulman et al. 2016) (Table 4.31). Each of the latter 

five studies examined cessation at different time points in 

the conception and timing of pregnancy: two examined 

cessation before pregnancy (Favaretto et  al. 2007; Blatt 

et  al. 2015), four examined cessation during pregnancy 

(Favaretto et  al. 2007; Adegboye et  al. 2010; Blatt et  al. 

2015; Hulman et al. 2016), and two examined cessation by 

combining those who quit before and during pregnancy 

(Favaretto et al. 2007; Rode et al. 2013). None of the five 

studies compared gestational weight gain or rate of weight 

gain before and after smoking cessation. Four of the five 

studies (Favaretto et al. 2007; Adegboye et al. 2010; Rode 

et al. 2013; Hulman et al. 2016) adjusted for at least some 

potential confounders (including pre-pregnancy BMI) in 

some of the analyses. Four of the five studies (Favaretto 

et al. 2007; Adegboye et al. 2010; Rode et al. 2013; Hulman 

et  al. 2016 ) assessed gestational weight gain using recommendations from the IOM, which are specific for prepregnancy BMI (Rasmussen et al. 2009).

In the single study examining weight gain by smoking 

status across pregnancies, Abrevaya and colleagues (2008) 

found a significantly greater gain in gestational weight 

during the second pregnancy among women who quit 

smoking between pregnancies compared with those who 

smoked during both pregnancies, even after adjusting for 

potential confounders. However, a limitation of this study 

was that smoking patterns were reduced to a few simplified categories. If smoking cessation during pregnancy 

does increase weight gain, then the effect could have been 

missed using this approach. 

All five of the studies of individual pregnancies 

found that gestational weight gain in quitters was higher 

than gestational weight gain in continuing smokers 

(range: 0.5–2.8  kg). The comparisons were statistically 

significant in three of the five studies (Adegboye et  al. 

2010; Rode et al. 2013; Blatt et al. 2015), and statistical 

comparisons were not presented in the other two studies 

(Favaretto et al. 2007; Hulman et al. 2016). Adegboye and 

colleagues (2010) found that women who quit smoking 

during the first trimester gained 1.5-kg more weight 

than women who continued to smoke during pregnancy 

(unadjusted, p  <0.001). Rode and colleagues (who combined women who quit smoking before and during pregnancy) reported weight gains of 15.9  kg in quitters and 

13.3 kg in continuing smokers, and the differences were 

significant after adjustment. Blatt and colleagues found, 

in unadjusted analyses, that women who quit smoking in 

the first or second trimester gained 6.2- and 3.3-pounds 

(2.8 kg and 1.5 kg, respectively) more weight than women 

who continued to smoke during pregnancy (Blatt et  al. 

2015). Hulman and colleagues (2016) examined cessation 

during pregnancy and trajectories of gestational weight 

gain based on weight gain in the first trimester and rate 

of weight gain in the second and third trimesters. The 

authors reported higher projected weight gains of 2.7 kg 

(adjusted for pre-pregnancy BMI) in quitters compared 

with continuing smokers, but did not report whether the 

findings were statistically significant. Favaretto and colleagues (2007) found a modest increase in gestational 

weight gain in women who quit smoking before or during 

pregnancy compared with those who continued to smoke 

during pregnancy: unadjusted estimates extrapolated to 

delivery were 13.4 kg and 12.9 kg, respectively. However, 

the authors did not stratify results by the timing of cessation with conception and did not report results of significance testing for this portion of the analysis.

Four of the five studies examining individual 

pregnancies and comparing quitters with nonsmokers 
Study Study design Tobacco exposure Outcome definition Results Comments

Sexton and 

Hebel (1984)

•

•

•

•

•

Randomized controlled 

trial of a behavioral 

intervention to increase 

smoking cessation

Enrolled pregnant 

women <18 weeks’ 

gestation who smoked at 

least 10 cigarettes/day at 

or just before pregnancy

n = 935

Years of data collection 

not reported

Maryland

•

•

•

Quit smoking by late pregnancy 

(8th month)

Continued smoking in late pregnancy 

(8th month)

Cessation confirmed with salivary 

thiocyanate collected during 8th month 

of pregnancy

Gestational weight gain 

during the 8th month 

of pregnancy

Mean gestational weight gain:

•

•

•

•

Control group: 11.9 kg

Intervention group: 12.9 kg

Difference: 1.0 kg

p <0.05

Results not adjusted for 

confounders or gestational 

age at last measurement

Did not account for 

alcohol or substance use

A Report of the Surgeon General

332 Chapter 4

Table 4.31 Studies on smoking cessation and gestational weight gain
Study Study design Tobacco exposure Outcome definition Results Comments

Favaretto et al. 

(2007)

• Prospective cohort study

• n = 4,000

• 1991–1995

• Brazil

• Nonsmoker: Never smoked

• Continued smoking: Smoking at least 

1 cigarette/day as of study interview

• Quit smoking:

– >6 months before pregnancy

– Between 6 months before pregnancy 

and conception

– Between conception and midpregnancy

• Smoking history ascertained from 

maternal interviews conducted during 

the second trimester

Gestational weight 

gain calculated using 

information from chart

review; used last measured 

weight and extrapolated 

to delivery

Mean gestational weight gain (SD):

• Measured: 

– Never smoked: 11.2 kg (5.8 kg) 

– Quit smoking (groups combined): 

12.1 kg (6.1 kg) 

– Continued smoking: 11.7 (6.5 kg) 

• Extrapolated: 

– Never smoker: 12.4 kg (6.1 kg) 

– Quit smoking (groups combined): 

13.4 kg (6.2 kg) 

– Continued smoking: 12.9 kg (6.8 kg) 

Difference in gestational weight gain 

by timing of cessation (95% CI):

• Never smoked: Reference

• Before conception:

– Unadjusted: 0.14 kg (-0.54–0.81 kg)

– Adjusted: 0.53 kg (-0.12–1.19 kg)

• Quit <6 months before conception:

– Unadjusted: 0.90 (0.19–1.62 kg)

– Adjusted: 1.00 (0.32–1.69 kg)

• Quit after conception through midpregnancy:

– Unadjusted: 1.78 (0.98–2.57 kg)

– Adjusted: 1.54 (0.78−2.31 kg)

Adjusted RR for weight gain in excess 

of IOM standards (95% CI):

• Never smoked: Reference 

• Quit overall: 1.2 (1.05–1.37) 

• Quit <6 months before conception: 

1.14 (0.94–1.38) 

• Quit after conception through midpregnancy: 1.34 (1.10–1.63) 

Results adjusted for 

maternal age, education, 

race, parity, clinical center, 

and pre-pregnancy BMI

Did not account for 

alcohol or substance use 

Table 4.31 Continued

The Health Benefits of Smoking Cessation 333
Study Study design Tobacco exposure Outcome definition Results Comments

Abrevaya et al. 

(2008)

•

•

•

•

•

•

•

Population-based, 

retrospective 

cohort study

Linked Michigan 

certificates of live birth

First and second 

pregnancies in which 

women smoked during 

the first pregnancy

n = 14,731 (18–24 years 

of age)

n = 8,044 (25–30 years

of age)

1989–2004

Michigan

•

•

•

•

Smoking status across pregnancies

Quit smoking: Smoked during the 

first pregnancy, not during the 

second pregnancy

Continued smoking in both pregnancies

Smoking status based on smoking 

history collected for certificates of live 

birth, which used one question on 

tobacco use during pregnancy (yes/no)

Gestational weight gain 

obtained from certificates 

of live birth

Difference in mean gestational weight 

gain among women who smoked during 

the first pregnancy (95% CI):

•

•

Quit smoking: Reference

Continued smoking:

–

–

18–24 years of age: -1.99 lbs 

(-2.50– -1.49 lbs)

25–30 years of age: -2.10 lbs 

(-2.67– -1.54 lbs)

Results adjusted for 

maternal race, education, 

income, population, 

interpregnancy interval, 

year of birth, trimester 

of first prenatal visit, 

presence of father’s name 

on birth certificate, 

number of prenatal visits, 

and first-birth value of 

the outcome 

Did not account for 

alcohol or substance use

Adegboye et al. 

(2010)

• Retrospective 

cohort study

• Risk factors for 

postpartum weight 

retention

• Singleton pregnancies

• n = 1,753

• 1984–1985

• Sweden

• Nonsmokers: Did not smoke 

during pregnancy

• Quit smoking: Quit smoking during 

first trimester and remained abstinent 

throughout pregnancy

• Continued smoking: Continued to 

smoke during pregnancy

• Smoking status based on self-reports 

but details not reported

Gestational weight gain 

calculated by subtracting 

maternal weight at

the end of gestation 

from self-reported prepregnancy weight

Compared with IOM 

(2009) recommendations

Unadjusted mean gestational weight 

gain (SD):

• Nonsmoker: 14.1 kg (4.0 kg)

• Quit smoking: 15.3 kg (4.4 kg)

• Continued smoking: 13.8 kg (4.3 kg)

• p <0.001, ANOVA

OR (95% CI) for gestational weight gain 

in excess of IOM recommendations:

• Nonsmoker: Reference

• Quit smoking:

– Unadjusted: 1.6 (1.1–2.1)

– Adjusted: 2.0 (1.4–3.0)

• Continued smoking:

– Unadjusted: 1.0 (0.8–1.3)

– Adjusted: 1.3 (0.9–1.8)

Results adjusted for birth 

weight, gestational age, 

parity, pre-pregnancy BMI, 

alcohol consumption, 

physical activity, and 

breakfast frequency

Did not account for 

substance use

Table 4.31 Continued

A Report of the Surgeon General

334 Chapter 4
Study Study design Tobacco exposure Outcome definition Results Comments

Washio et al. 

(2011)

•

•

•

•

•

Randomized controlled 

trial of a voucher 

incentive to increase 

smoking cessation

Pregnant smokers

n = 154

2001–2006

Vermont

•

•

•

Quit smoking: Past 7-day abstinence 

confirmed by urine cotinine at the 

end of pregnancy

Continued smoking: Not abstinent 

at the end of pregnancy

Not reported when cessation data 

were collected

Weight at delivery and prepregnancy weight

Mean gestational weight gain (SD):

• Control group: 15.0 +/- 0.8 kg

–

–

–

Intervention group: 15.0 +/- 0.9 kg

Difference = 0.0 kg

p = 0.97

• Quit smoking: 17.2 +/- 1.1 kg

–

–

–

Continued smoking: 15.4 +/- 0.6 kg

Difference = 2.8 kg

p = 0.04

Adjusted mean difference in gestational 

weight gain:

• Quit smoking vs. continued smoking:

–

–

2.4 kg

p = 0.06

• Mean increase in gestational weight 

gain of 0.34 kg per 10% increase

in cessation:

–

–

p = 0.03 (results adjusted for 

pre-pregnancy BMI and parity)

p = 0.13 (results adjusted for 

pre-pregnancy BMI, parity, and 

birth weight)

Loss of significance after 

adjustment for birth 

weight suggests that the 

increase in gestational 

weight gain in quitters 

compared with continuing 

smokers was attributable 

in part to increased 

fetal growth

Table 4.31 Continued

The Health Benefits of Smoking Cessation 335
Study Study design Tobacco exposure Outcome definition Results Comments

Rode et al.

(2013)

• Prospective cohort of 

pregnant women who 

received an intervention 

to be smokefree

• Singleton, term 

pregnancies

• n = 1,774

• 1996–1999

• Denmark

• Nonsmokers: Not defined

• Quit smoking: Quit immediately before 

or during pregnancy

• Continued smoking: Not further defined 

• Smoking status based on self-reports 

assessed at 12–18 weeks’ and 37 weeks’ 

gestation and 1 year postpartum

• Salivary cotinine obtained in a subgroup 

at 16 and 37 weeks’ gestation

Gestational weight 

gain at 37 weeks’ 

gestation compared with 

recommendations from 

IOM (2009)

Mean gestational weight gain at 37 weeks 

(SD), difference in gestational weight 

gain (95% CI):

• Nonsmokers: 13.46 kg (4.71 kg) 

(reference)

• Quit smoking:

– Unadjusted: 2.44 kg (1.86–3.03 kg)

– Adjusted: 2.01 kg (1.51–2.64 kg)

Adjusted OR (95% CI) for gestational 

weight gain in excess of IOM 

recommendations:

• Nonsmokers: Reference

• Quit smoking: 1.9 (1.5–2.4)

• Continued smoking: 1.2 (0.9–1.5)

Weight gain adjusted 

for pre-pregnancy BMI, 

gestational age, and parity

Salivary cotinine for

subgroup reported but 

report did not describe 

whether it was integrated 

into main analysis

Did not account for 

alcohol or substance use

OR for gaining in excess 

of IOM recommendations 

adjusted for gestational 

age and preeclampsia

Blatt et al. 

(2015)

•

•

•

•

•

Population-based 

retrospective 

cohort study

Ohio certificates of 

live birth

n = 927,424

2006–2012

Ohio

•

•

•

•

•

•

Nonsmoker:Did not smoke during 

the 3 months before pregnancy 

or during pregnancy 

Quit smoking before pregnancy: Smoked 

during the 3 months before pregnancy 

but not during pregnancy 

Quit smoking firsttrimester: Smoked first 

trimester only 

Quit smoking second trimester: Smoked 

first and second trimester, notthird 

Continued smoking: Smoked throughout 

pregnancy 

Smoking history ascertained from vital 

statistics data and certificates of live birth 

Gestational weight gain 

calculated from maternal 

weight at delivery vs. 

preconception weight

Mean gestational weight gain (SD):

•

•

•

•

•

•

Nonsmoker: 31.2 lbs (+/- 16.9 lbs)

Quit smoking before pregnancy: 

36.4 lbs (+/- 18.8 lbs)

Quit smoking first trimester: 

36.5 lbs (+/- 19.2 lbs)

Quit smoking second trimester: 

33.6 lbs (+/- 19.5 lbs)

Continued smoking: 30.3 lbs 

(+/- 8.9 lbs)

All comparisons: p <0.001

Findings not adjusted for 

potential confounders

Did not account for 

alcohol or substance use

Table 4.31 Continued

A Report of the Surgeon General

336 Chapter 4
Study Study design Tobacco exposure Outcome definition Results Comments

Hulman et al. 

(2016)

• Longitudinal 

cohort study

• Singleton pregnancies

• n = 509

• 2013

• Ontario, Canada

• Nonsmokers:Women who never smoked 

• Quit smoking: Smoked previously 

but quit when they found out they 

were pregnant 

• Continued smoking: Still smoking at 

study assessment

• Smoking status based on maternal 

self-reports obtained during survey 

conducted at ~32 weeks’ gestation

Gestational weight 

gain calculated from 

pre-pregnancy weight 

(or first available 

antenatal visit) and serial 

weight measurements 

obtained from medical 

record review

Rate of weight gain 

(kg/week) in second and 

third trimesters compared 

with recommendations 

from IOM:

• Underweight: 0.44–0.58

• Normal: 0.35–0.50

• Overweight: 0.23–0.33

• Obese: 0.17–0.27

Mean gestational weight gain (95% CI) 

based on trajectories for the end of the 

39th week:

• Nonsmoker: 14 kg

• Quit smoking: 16.7 kg (15.1–18.4 kg)

• Continued smoking: 14 kg

Total first trimester gestational weight 

gain (95% CI):

• Nonsmoker: 1.7 kg (1.4–2.1 kg)

• Quit smoking: 1.2 kg (0.3–2.1 kg)

• Continued smoking: 3.5 kg (2.4–4.6 kg)

Rate of weight gain in second and third 

trimesters:

• Quit smoking: 0.60 kg/week 

(0.54–0.65 kg/week)

• Vs. nonsmokers: +22% (11–34%)

• Vs. continued smokers: +53% (32–75%)

Rate of weight gain by IOM categories: 

kg/week (95% CI):

• Nonsmoker:

– Underweight: 0.52 (0.42–0.62)

– Normal: 0.51 (0.49–0.54)

– Overweight: 0.52 (0.48–0.55)

– Obese: 0.38 (0.33–0.42)

• Quit smoking:

– Underweight: 0.62 (0.50–0.73)

– Normal: 0.61 (0.56–0.67)

– Overweight: 0.62 (0.56–0.68)

– Obese: 0.48 (0.41–0.54)

• Continued smoking:

– Underweight: 0.44 (0.33–0.56)

– Normal: 0.44 (0.37–0.50)

– Overweight: 0.44 (0.37–0.51)

– Obese: 0.30 (0.23–0.37)

Results adjusted for 

maternal age, race, parity, 

marital status, education, 

income, and BMI

Did not account for 

alcohol or substance use

Table 4.31 Continued

The Health Benefits of Smoking Cessation 337

Notes: ANOVA = analysis of variance; BMI = body mass index; CI = confidence interval; IOM = Institute of Medicine; kg = kilograms; lbs = pounds; OR = odds ratio; RR = relative risk; 

SD = standard deviation.
A Report of the Surgeon General

338 Chapter 4

(Favaretto et  al. 2007; Adegboye et  al. 2010; Rode et  al. 

2013; Blatt et al. 2015) found a significant increase in gestational weight gain in quitters (range: 0.5–2.4 kg). One 

study did not report statistical comparisons (Hulman 

et al. 2015). The two studies examining cessation before 

pregnancy both found significant increases in gestational 

weight gain among women who quit before but close to 

the time of conception in comparisons with nonsmokers 

(range: 1.0–2.4  kg) (Favaretto et  al. 2007; Blatt et  al. 

2015). The study by Favaretto and colleagues (2007) also 

found that weight gain in women who had quit more than 

6  months before conception did not differ significantly 

from that of nonsmokers, even after adjusting for potential confounders. Of the four studies examining cessation 

during pregnancy, three (Favaretto et al. 2007; Adegboye 

et al. 2010; Blatt et al. 2015) reported significant increases 

in weight in quitters compared with nonsmokers. 

Adegboye and colleagues (2010) and Blatt and colleagues 

(2015) examined cessation in the first trimester, which 

was associated with increases in weight gain of 1.2  kg 

(Adegboye et  al. 2010) and 1.1  kg (Blatt et  al. 2015), 

respectively. Blatt and colleagues (2015) also described a 

significant increase in weight gain (2.4 kg) among women 

who quit during the second trimester in a comparison 

with nonsmokers. Favaretto and colleagues (2007) examined cessation between conception and mid-pregnancy 

(20–28 weeks gestation) and found a 1.54-kg increase in 

weight gain in quitters compared with nonsmokers after 

adjusting for pre-pregnancy BMI and other potential confounders. Hulman and colleagues (2016) also examined 

cessation during pregnancy and reported that projected 

gestational weight gain, based on weight gain trajectories and adjusted for confounders, was higher by 2.7 kg 

in quitters than in nonsmokers, but results of testing for 

statistical significance were not presented. Rode and colleagues reported a 2.0-kg (95%  CI, 1.5–2.6  kg) increase 

in adjusted gestational weight gain in women who quit 

smoking before or during pregnancy compared with 

women who were nonsmokers (Rode et al. 2013).

Two of the four studies examining cessation during 

pregnancy also compared weight gain early and late in 

pregnancy. Rode and colleagues (2013) found that at 

16 weeks’ gestation no differences existed in weight gain 

when nonsmokers, women who quit before or during 

pregnancy, and continuing smokers were compared after 

adjustment for pre-pregnancy BMI, gestational age, and 

parity. By 37 weeks’ gestation, however, women who had 

quit smoking had a significant, adjusted 4.4-lb [2.0  kg] 

increase in weight gain in comparison with nonsmokers, 

while continuing smokers and nonsmokers did not experience relative increases in weight gain. In contrast, Hulman 

and colleagues (2016) found that continuing smokers 

gained more than twice as much weight during the first 

trimester as women who quit smoking upon learning of 

their pregnancy (adjusted difference  =  3.0  kg [6.6  lbs] 

after controlling for sociodemographic characteristics 

and pre-pregnancy BMI). The weekly rate of weight gain in 

the second and third trimesters was highest, however, in 

women who quit smoking during pregnancy. Quitters had 

a 22% faster rate of weight gain in the second and third 

trimesters of pregnancy compared with nonsmokers and a 

53% faster rate of weight gain compared with continuing 

smokers (Hulman et al. 2016).

Four studies (Favaretto et al. 2007; Adegboye et al. 

2010; Rode et  al. 2013; Hulman et  al. 2016) examined 

gestational weight gain with respect to IOM recommendations (IOM 1990). Two studies (Favaretto et  al. 2007; 

Adegoye et al. 2010) found that women who quit smoking 

during pregnancy were significantly more likely to gain 

weight in excess of IOM recommendations compared with 

nonsmokers, even after controlling for pre-pregnancy 

BMI and other factors (adjusted RR: 1.34 [95% CI, 1.10–

1.63]; and adjusted OR: 2.0  [95%  CI, 1.4–3.0], respectively). Rode and colleagues (2013) found that the percentage of women who gained in excess of IOM guidelines 

differed significantly by smoking status (45.9%, 34.6%, 

and 31.3% for women who quit before or during pregnancy, continuing smokers, and nonsmokers, respectively, P  <  0.001), and after adjustment for gestational 

age and preeclampsia, quitters were significantly more 

likely to gain in excess of IOM recommendations than 

nonsmokers (OR  1.9 95%  CI 1.5-2.4). Adjusted models 

comparing quitters with continuing smokers were not 

reported (Rode et al. 2013). Hulman and colleagues (2016) 

examined IOM recommendations for rate of weight gain 

and found that women who quit smoking during pregnancy on average gained above the rate recommended by 

the IOM in the second and third trimesters for all prepregnancy BMI categories, and weight gain by women 

who continued to smoke varied by pre-pregnancy BMI 

category (under- and normal-weight women on average 

gained within the recommended rate range while overweight and obese women gained faster than the recommended rate). Among nonsmokers, only those who were 

underweight gained at a rate within IOM recommendations; all other groups gained at a rate exceeding IOM recommendations (Hulman et al. 2016).

Summary of the Evidence

The evidence describing the associations between 

smoking status, quitting, and gestational weight gain has 

expanded considerably since the 1990 Surgeon General’s 

report, but there has been some variation in the covariates included in the analytic models and in the time points 

used to define smoking cessation (e.g.,  preconception, 

in early gestation, by mid-pregnancy, during gestation). 
The Health Benefits of Smoking Cessation 339

Smoking Cessation

Nonetheless, the evidence is sufficient to infer that women 

who quit smoking shortly before or during pregnancy 

gain more weight during gestation than women who continue to smoke, and the findings are consistent, including 

data from two randomized clinical trials. The evidence is 

suggestive but not sufficient to infer that women who quit 

smoking before or during pregnancy gain more weight 

during gestation than nonsmokers. The evidence is suggestive but not sufficient to infer that women who quit 

smoking before or during pregnancy are at increased risk 

of excess weight gain, per IOM guidelines, compared with 

nonsmokers. However, very little evidence could be used 

to compare the risk of excess gestational weight gain in 

quitters with that in continuing smokers.

Prenatal smoking cessation has substantial health 

benefits for mothers and offspring, and providing assistance with weight management while promoting smoking 

cessation could help to optimize outcomes.

Gestational Diabetes

Gestational diabetes mellitus (GDM), which is 

defined as carbohydrate intolerance leading to hyperglycemia with onset or first recognition during pregnancy, 

affects 4% to 9% of pregnancies in the United States 

(DeSisto et al. 2014). Although this complication usually 

resolves after delivery, up to one-third of affected women 

have diabetes or impaired glucose metabolism at postpartum screening. Women with GDM are at increased risk 

for cesarean delivery, and their infants are at increased 

risk for macrosomia (i.e.,  being large for gestational 

age), neonatal hypoglycemia, and fetal hyperinsulinemia 

(Hyperglycemia and Adverse Pregnancy Outcome Study 

Cooperative Research Group 2008). Most women who 

develop GDM have preexisting impaired beta cell function and chronic insulin resistance that is characteristic 

of type 2 diabetes, and women with a history of GDM are 

at substantially increased risk for the future development 

of type 2 diabetes, providing evidence of a common underlying mechanism (Mack and Tomich 2017). Furthermore, 

GDM is consistently associated with both higher prepregnancy BMI and excessive gestational weight gain 

(Brunner et al. 2015; Najafi et al. 2019).

The 1990 Surgeon General’s report did not examine 

smoking and GDM, but the 2001 Surgeon General’s report 

on women and smoking described inconsistent evidence 

of an association between smoking and GDM (USDHHS 

2001). The 2014 Surgeon General’s report did not examine 

smoking and GDM, but did conclude that smoking is 

causally associated with type  2 diabetes and did address 

smoking cessation and risk of type 2 diabetes (USDHHS 

2014). In one large study, the risk of incident type 2 diabetes for short-term quitters was higher than that of current smokers but decreased to the level for never smokers 

by 12 years (Yeh et al. 2010; USDHHS 2014). In another 

large study, the risk of type 2 diabetes decreased to that of 

nonsmokers 5 years after quitting in women and 10 years 

after quitting in men (Will et  al. 2001; Wendland et  al. 

2008; USDHHS 2014). The transient increase in risk for 

quitters may be the result of short-term effects on weight 

gain. The 2014 report did not address GDM specifically.

In light of the potential for increased short-term 

morbidity associated with weight gain following smoking 

cessation, an increase in gestational weight gain associated with smoking cessation could be associated with 

adverse pregnancy outcomes, such as GDM or macrosomia, regardless of whether smoking itself is directly 

causally associated with GDM (Rasmussen et  al. 2009). 

Therefore, smoking cessation and GDM were reviewed 

in this section absent an established causal relationship 

between active smoking and GDM in these reports. 

Five studies on smoking and GDM published 

since the 2001 report included prevalence estimates for 

GDM among nonsmokers, former smokers, and continuing smokers (England et  al. 2004; Fasting et  al. 

2009; Erickson and Arbour 2012; Räisänen et  al. 2014; 

Blatt et al. 2015). Three of these were large, populationbased studies (Erickson and Arbour 2012; Räisänen 

et al. 2014; Blatt et al. 2015), and two were small, clinicbased studies (England et al. 2004; Fasting et al. 2009). 

Räisänen and colleagues (2014) reported a greater prevalence of GDM among women who quit smoking in the 

third trimester (9.8%) compared with never smokers 

(7.6%) and with continuing smokers (7.6%); Erickson 

and Arbour (2012) reported the lowest GDM prevalence 

in continuing smokers (3.8%  to 4.9%), with prevalence 

equaling 5.4% in quitters and 6.7% in nonsmokers; and 

Blatt and colleagues (2015) reported the lowest prevalence 

in nonsmokers (5.4%) and a slightly higher prevalence in 

preconception quitters (5.8%) and in first- and secondtrimester quitters (5.6% and 5.5%, respectively). In none 

of these three studies was GDM the primary outcome of 

interest, and none reported results of testing for statistical significance in direct comparisons or the results of 

adjusted analyses. The study populations in these analyses 

were very large, however.

In one of the two smaller studies, England and colleagues (2004) reported a significant increase in mean 

adjusted plasma glucose concentration after a 1-hour, 50-g 

glucose challenge in continuing smokers compared with 

never smokers (112.6 milligrams per deciliter [mg/dL] vs. 

108.3 mg/dL, p <0.01), but no differences were seen when 

never smokers were compared with women who had quit 

before pregnancy (108.5  mg/dL) or during pregnancy 

(109.5  mg/dL). Compared with nonsmokers, continued 

smoking was significantly associated with GDM (aOR = 1.9; 

95%  CI, 1.0–3.6), but no significant associations were 
A Report of the Surgeon General

340 Chapter 4

observed for smoking with cessation before (aOR  =  0.8; 

95% CI, 0.3–2.1) or during pregnancy (aOR = 1.4; 95% CI, 

0.5–2.9) (England et al. 2004). In the other of the smaller 

studies, Fasting and colleagues (2009) reported identical 

estimates of GDM prevalence (3%) for never smokers and 

smokers who quit early in pregnancy and an estimate of 

5% for women who continued to smoke. GDM was not the 

primary outcome of interest, however, and the number of 

GDM cases was small (only three each in the groups of 

quitters and continuing smokers), and an adjusted analysis was not performed. 

Summary of the Evidence

Only a limited number of studies on the relationship 

between smoking cessation and GDM were identified, and 

in the majority of those studies, GDM was not the main 

outcome of interest, potentially limiting assessment for 

relevant covariates and confounders. Thus, the evidence 

is inadequate to determine whether smoking cessation 

during pregnancy increases the risk of gestational diabetes. 

Birth Outcomes

Birth Defects

The 2014 Surgeon General’s report concluded 

that there was sufficient evidence to infer a causal relationship between maternal smoking in early pregnancy 

and increased risk for orofacial clefts (USDHHS 2014). 

However, the evidence was suggestive but not sufficient to 

infer an increased risk for other birth defects—including 

clubfoot, gastroschisis, and atrial septal heart defects—for 

women who smoke in early pregnancy (USDHHS 2014). 

Based on the available scientific evidence, the 2014 report 

recommended providing information on the risk of orofacial clefts as part of efforts to reduce smoking prior to 

conception and in early pregnancy (USDHHS 2014); however, few studies have specifically assessed the risk for orofacial clefts among women who are former smokers. One 

study has assessed the risk for any major anomaly among 

women who quit smoking during the first trimester compared with women who did not smoke during pregnancy 

(Räisänen et al. 2014). However, due to the limited number 

of studies published to date specifically related to cessation and risk for specific birth defect categories, including 

orofacial clefts, this report does not reach any new conclusions regarding these outcomes. 

Fetal Growth and Birth Weight

The effects of maternal smoking on birth weight 

have been recognized since the 1964 Surgeon General’s 

report, which found that infants of smokers were more 

likely than those of nonsmokers to weigh less than 

2,500 g at birth (USDHEW 1964). Birth weight is determined by both gestational age at delivery and the rate of 

fetal growth, and subsequent Surgeon General’s reports 

have addressed these factors separately when examining 

birth weight as an outcome. The 1990 Surgeon General’s 

report noted that the risk of being small for gestational 

age (typically defined as weight ≤10th percentile for gestational age) was 3.5- to 4-fold higher in infants of smokers 

than in infants of nonsmokers (USDHHS 1990). The 

report concluded that babies of women who quit smoking 

before conception did not experience smoking-related 

reductions in fetal growth, while cessation before the 

third trimester significantly attenuated the deleterious 

effects of maternal smoking on fetal growth (USDHHS 

1990). The 2004 Surgeon General’s report found sufficient 

evidence to infer a causal relationship between smoking 

and both fetal growth restriction and reduced gestational 

age/increased preterm delivery (USDHHS 2004). It confirmed the 1990 Surgeon General’s report’s finding that 

cessation eliminates much of the reduction in birth 

weight caused by maternal smoking (USDHHS 2004). The 

2014 Surgeon General’s report explored in depth the relationships between smoking and fetal growth. The report 

concluded that nicotine is unlikely to be the main contributor in tobacco smoke to fetal growth restriction, with 

products of combustion likely playing a major role in this 

regard (USDHHS 2014). This report did not address the 

benefits of smoking cessation, however.

Several subsequent studies have supported the conclusions of the 1990 and 2004 Surgeon General’s reports 

that smoking cessation attenuates the adverse effects of 

smoking on fetal growth and birth weight. There are several methodologic challenges, however, in studies of fetal 

growth and birth weight. First, fetal growth is not linear, 

and the most rapid rate of growth occurs in the third trimester (Kiserud et al. 2017). As a consequence, assessing 

the timing of tobacco exposure with respect to position on the fetal growth curve is essential to characterizing the mechanisms through which tobacco use exerts 

adverse effects and cessation benefits fetal growth. Many 

of the studies identified in the literature review, however, 

did not assess tobacco use and cessation across the entire 

pregnancy. Second, as previously described, smokers 

typically differ from nonsmokers in numerous behavioral, obstetrical, and other health-related factors, and a 

failure to control for potential confounders may result in 

residual confounding. High-quality data on many potentially important exposures for fetal growth, such as use of 

alcohol and/or illicit drugs, are often lacking in registries 

and other commonly used sources of data. 
The Health Benefits of Smoking Cessation 341

Smoking Cessation

Birth Weight

Table 4.32 presents 40 studies that examined birth 

weight and smoking cessation during pregnancy. Studies 

varied in the use of biochemical validation of reported cessation, in descriptions about the timing of cessation, and 

in adjustments for potential confounders. Twenty of the 

studies addressed gestational age by restricting the analysis to term infants and/or adjusting for gestational age 

(Hrubá and Kachlik 2000; Lindley et  al. 2000; England 

et al. 2001a,b, 2007; Mendez et al. 2008; Nijiati et al. 2008; 

Sasaki et al. 2008; Andersen et al. 2009; Kabir et al. 2009; 

Prabhu et al. 2010; Vardavas et al. 2010; Bakker et al. 2011; 

Benjamin-Garner and Stotts 2013; Juarez and Merlo 2013; 

Miyake et al. 2013; Rode et al. 2013; Slatter et al. 2014; 

Suzuki et al. 2014, 2016; Hayes et al. 2016); 25 included 

adjustment for at least some additional confounders 

(Lindley et al. 2000; England et al. 2001a,b, 2007; Dejmek 

et al. 2002; Wen et al. 2005; Abrevaya 2008; Nijiati et al. 

2008; Sasaki et al. 2008; Andersen et al. 2009; McCowan 

et al. 2009; Prabhu et al. 2010; Vardavas et al. 2010; Bakker 

et al. 2011; Benjamin-Garner and Stotts 2013; Himes et al. 

2013; Juarez and Merlo 2013; Miyake et al. 2013; Murphy 

et al. 2013; Rode et al. 2013; Meghea et al. 2014; Suzuki 

et  al. 2014, 2016; Bailey 2015; Yan and Groothuis 2015; 

Hayes et al. 2016); and 9 included biochemical validation of 

smoking cessation (England et al. 2001a,b; Secker-Walker 

and Vacek 2002; Malchodi et al. 2003; England et al. 2007; 

Andersen et al. 2009; Benjamin-Garner and Stotts 2013; 

Rode et  al. 2013; Bailey 2015; Hayes et  al. 2016). Five 

studies did not differentiate between either quitting before 

pregnancy and quitting during early pregnancy or a combination of both and, thus, could not isolate the effects 

of quitting during pregnancy (Hrubá and Kachlik 2000; 

England et  al. 2007; Vardavas et  al. 2010; Murphy et  al. 

2013; Rode et  al. 2013). Nineteen studies used smoking 

status in late pregnancy to categorize exposure groups, 

thus those studies did not combine late quitters with continuing smokers, or women who relapsed with women 

who remained abstinent (Lindley et  al. 2000; England 

et  al. 2001a,b, 2007; Dejmek et  al. 2002; Secker-Walker 

and Vacek 2002; Malchodi et al. 2003; Andersen et al. 2009; 

Bakker et  al. 2011; Benjamin-Garner and Stotts 2013; 

Himes et al. 2013; Juarez and Merlo 2013; Miyake et al. 

2013; Murphy et al. 2013; Rode et al. 2013; Slatter et al. 

2014; Bailey 2015; Blatt et  al. 2015; Yan and Groothuis 

2015; Wallace et al. 2017). Only two studies adjusted for 

or otherwise addressed alcohol and other substance use 

(Murphy et al. 2013; Bailey 2015), and seven adjusted for 

alcohol use but not other substance use (Dejmek et al. 2002; 

Wen et al. 2005; Sasaki et al. 2008; McCowan et al. 2009; 

Bakker et al. 2011; Miyake et al. 2013; Yan and Groothuis 

2015), and one excluded women who used illicit drugs 

(Himes et al. 2013). Five studies accounted for gestational 

age and also adjusted for confounders, included biochemical validation of quit status, and incorporated well-defined 

exposure groups that included smoking status in late pregnancy (England et al. 2001a,b, 2007; Andersen et al. 2009; 

Benjamin-Garner and Stotts 2013; Rode et al. 2013). None 

of these five adjusted for alcohol or illicit drug use. 

Despite these methodologic differences, most of the 

40 studies found that (a) women who continued to smoke 

past early pregnancy delivered infants of lower birth 

weight than those of nonsmokers and (b) cessation before 

or during pregnancy attenuated or eliminated this effect. 

These findings were consistent in studies controlling for 

gestational age at birth and/or excluding preterm deliveries 

(Lindley et al. 2000; England et al. 2001b, 2007; Mendez 

et al. 2008; Nijiati et al. 2008; Sasaki et al. 2008; Andersen 

et al. 2009; Kabir et al. 2009; Prabhu et al. 2010; Vardavas 

et  al. 2010; Bakker et  al. 2011; Juarez and Merlo 2013; 

Miyake et al. 2013; Rode et al. 2013; Slatter et al. 2014; 

Suzuki et  al. 2014, 2016) and in studies that addressed 

illicit drug and/or alcohol use (Dejmek et al. 2002; Wen 

et al. 2005; Sasaki et al. 2008; McCowan et al. 2009; Bakker 

et al. 2011; Himes et al. 2013; Miyake et al. 2013; Murphy 

et al. 2013; Bailey 2015; Yan and Groothuis 2015).

Four of the 40  studies validated smoking status 

while also adjusting for gestational age or restricting 

the study to term births, adjusting for potential confounders, and assessing smoking status in late pregnancy. 

Results from the two studies comparing quitters with 

nonsmokers found no difference in mean adjusted birth 

weight (England et al. 2007; Andersen et al. 2009), and the 

other two studies were randomized clinical trials of cessation interventions and thus compared quitters with continuing smokers (England et al. 2001b; Benjamin-Garner 

and Stotts 2013). In these two studies, the adjusted mean 

difference in birth weight between infants of quitters and 

those of continuing smokers was an excess of 100  and 

300 g, respectively. However, England and colleagues (2007) 

combined women who quit before pregnancy with women 

who quit during pregnancy and, thus, could not address 

the effect of cessation during pregnancy.

One large study (previously described) used a 

sibling-comparison analysis to address the problem of 

potential uncontrolled confounding in the relationship between smoking during pregnancy and the birth 

weight of offspring (Juarez and Merlo 2013). Compared 

with the conventional analysis performed with all singleton births in the dataset, the sibling analysis revealed 

a reduced effect of smoking on gestational age–adjusted 

birth weight. In the sibling analysis, continuous smoking 

through pregnancy reduced birth weight by 162 g for light 

smokers (≤10 cigarettes per day) and by 226 g for heavy 

smokers (>10  cigarettes per day), versus reductions of 
Study Design/population Exposure groups/how determined Estimate of effects Comments

Hrubá and

Kachlik (2000)

•

•

•

•

•

Retrospective,

clinic-based study

Term, singleton deliveries

n = 1,147

Years of data collection 

not reported

Czech Republic

•

•

•

•

Nonsmokers: Never smoked

Quit smoking: Smoked but quit before

pregnancy or during the first trimester

Continued smoking: Smoked throughout 

pregnancy, either daily or occasionally

Smoking status based on self-report 

from interview conducted shortly 

after delivery

Mean birth weight (SD) and difference in 

mean birth weight (among women

without exposure to secondhand smoke):

•

•

•

Nonsmokers: 3,383 g (456) (reference)

Quit smoking: 3,414 g (459), +31 g

Continued smoking: 3,298 g (484), -85 g

Analysis restricted to

term births

Results not adjusted for 

potential confounders

Analysis stratified by exposure 

to secondhand smoke

Did not account for alcohol 

or illicit drug use

Lindley et al. 

(2000)

• Population-based, 

retrospective cohort study

• Analysis of births from the 

Swedish Birth Registry

• ≥32 weeks’ gestation at 

delivery, excluded pregnancies with complication or 

congenital malformations

• n = 15,185

• 1991–1992

• Sweden

• Nonsmoker: Not a smoker or less than 

daily smoker at first prenatal visit

• Quit smoking: Smoked daily at first 

prenatal visit but did not smoke at 

late visit

• Continued smoking: Smoked at first 

and late prenatal visits:

– Light smoker: 1–9 cigarettes/day

– Heavy smoker: ≥10 cigarettes/day

• Smoking status based on self-reports at 

first and late (~32 weeks) prenatal visits

Mean adjusted birth weight and difference

in mean adjusted birth weight:

Nonsmokers: 3,459 g, p <0.001

Quit smoking: -26 g (not significant)

Continued smoking

Light smokers: -136 g, p <0.001

– Heavy smokers: -175 g, p <0.001

Results adjusted for sex of 

the infant, gestational age, 

parity, maternal age, height, 

and BMI

Did not account for alcohol 

or illicit drug use

England et al. 

(2001b)

•

•

•

•

•

Randomized clinical trial 

of a smoking cessation 

intervention

Singleton, term 

pregnancies

n = 926

1987–1991

Multiple centers in the 

United States

•

•

•

–

–

–

•

Quit smoking before enrollment: Smoked 

within 1 week of learning they were 

pregnant but quit by enrollment

Quit smoking after enrollment: Smoked 

within 1 week of learning they were 

pregnant and at enrollment but quit 

after enrollment

Continued to smoke:

Did not change: Cotinine, 

cigarettes/day changed by <50%

Reduced: Reduced cotinine, 

cigarettes/day by >50%

Increased: Increased cotinine, 

cigarettes/day by >50%

Smoking status based on self-report 

obtained at enrollment and in the third 

trimester, validated using urine cotinine 

collected concurrently

Mean adjusted birth weight (95% CI) and 

difference in mean adjusted birth weight 

(95% CI)

• Self-report:

–

–

Continued to smoke/did not change: 

3,205 g (reference)

Quit smoking after enrollment:

•

•

+286 g (196–376 g)

Cotinine validated:

–

–

Continued to smoke/did not change: 

3,216 g (reference)

Quit smoking after enrollment:

•

•

+197 g (94–301 g)

Mean adjusted birth weight of those 

who reduced or increased cotinine or 

cigarettes/day did not differ from that 

of women who did not change

Only smokers enrolled; 

no nonsmoker comparison 

group

Analysis restricted to 

term births

Results adjusted for maternal 

age, parity, race, BMI, state 

of clinic’s location, sex of the 

infant, and gestational age

Did not account for alcohol 

or illicit drug use

•

•

•

–

A Report of the Surgeon General

342 Chapter 4

Table 4.32 Studies on smoking cessation and birth weight
Study Design/population Exposure groups/how determined Estimate of effects Comments

MacArthur et al. 

(2001)

• Randomized clinical 

trial of a behavioral 

intervention of

antismoking education 

with long-term follow-up

• n = 1,853

• 1981–1982

• Alabama

• Nonsmokers: Not smoking at enrollment

• Quit smoking by 6 weeks

• Quit smoking 7–16 weeks

• Quit smoking ≥17 weeks

• Continued smoking

• Smoking status based on self-reports at 

enrollment into prenatal care

Unadjusted mean birth weight and 

difference in mean birth weight:

• Nonsmokers: 3,455 g (reference)

• Quit by 6 weeks: 3,433 g, -12 g

• Quit 7-16 weeks: 3,389 g, -56 g

• Quit ≥17 weeks: 3,327 g, -118 g

• Continued smoking: 3,149 g, -296 g 

Results not adjusted for 

potential confounders

Did not account for 

alcohol or substance use

Direct statistical 

comparisons between 

groups not shown

Dejmek et al.

(2002)

•

•

•

•

Population-based 

retrospective cohort

n = 6,866

1994–1999

Czech Republic

•

•

•

•

•

•

•

•

Nonsmoker: Not smoking when 

pregnancy recognized

Quit after pregnancy recognized:

Moderate smokers: 1–10 cigarettes/day

Heavy smokers: >10 cigarettes/day

Continued smoking:

Moderate smokers: 1–10 cigarettes/day

Heavy smokers: >10 cigarettes/day

Smoking status based on self-reports 

obtained at delivery

Difference in mean adjusted birth weight 

(95% CI):

•

•

Nonsmoker (reference)

Quit after pregnancy recognized:

–

–

Moderate smoker: -22 g (-64–19 g)

Heavy smoker: -66 g (-146–14 g)

• Continued smoking:

–

–

–

–

1–10 cigarettes/day: -152 g

(-185– -117 g)

>10 cigarettes/day: -259 g

(-342– -175 g)

Results adjusted for 

maternal age, district, 

ethnicity, education, 

parity, sex, height, prepregnancy weight, alcohol 

consumption, and season

Did not account for illicit 

drug use

The Health Benefits of Smoking Cessation 343

Table 4.32 Continued
Study Design/population Exposure groups/how determined Estimate of effects Comments

Secker-Walker 

and Vacek 

(2002)

• Randomized clinical trial 

of a smoking cessation 

intervention

• Singleton births

• n = 240

• 1988–1992

• Vermont

• Quit smoking: Smoked at enrollment 

but quit in late pregnancy (~35 weeks’ 

gestation)

• Continued smoking: Smoked at 

enrollment and in late pregnancy:

– Reduced by <50%

– Reduced by ≥50%

• Smoking status based on selfreports and urine cotinine obtained 

at enrollment into prenatal care 

[14.6 (7.0) weeks] and near the end 

of pregnancy [35.0 (1.2) weeks]

Mean infant birth weight (95% CI):

• Self-report (adjusted results were adjusted 

for number of cigarettes smoked/day at 

first visit):

– Reduced <50%:

 Unadjusted: 3,203 g (3,127–3,278 g)

 Adjusted: 3,203 g (3,128–3,278 g)

– Reduced ≥50%:

 Unadjusted: 3,239 g (3,096–3,382 g)

 Adjusted: 3,267 g (3,124–3,410 g)

– Quit:

 Unadjusted: 3,446 (3,298–3,594 g)

 Adjusted: 3,413 g (3,270–3,556 g)

• With biochemical validation (adjusted 

results were adjusted for cotinine 

concentration at first visit):

– Reduced <50%:

 Unadjusted: 3,205 g (3,124–3,286 g)

 Adjusted: 3,214 g (3,133–3,295 g)

– Reduced ≥50%:

 Unadjusted: 3,184 g (3,069–3,298 g)

 Adjusted: Reduced 3,226 g (3,114– 

3,338 g)

– Quit (based on self-reports):

 Unadjusted: 3,465 g (3,306–3,624 g)

 Adjusted: 3,447 g (3,291–3,604 g)

Difference in mean adjusted infant 

birth weight:

• Quit vs. reduced <50%:

– Self-report: 210 g

– Cotinine validated: 233 g

All study participants were 

smokers at the time of 

recruitment; no nonsmoker 

comparison group

Did not account for alcohol 

or illicit drug use

Table 4.32 Continued

A Report of the Surgeon General

344 Chapter 4
Study Design/population Exposure groups/how determined Estimate of effects Comments

Malchodi et 

al. (2003)

•

•

•

•

Randomized clinical trial 

of a smoking cessation 

intervention

n = 142

1998–2000

Connecticut

•

•

•

•

Quit smoking: Smoked daily in the week 

before learning they were pregnant but 

quit by 36 weeks’ gestation

Continued smoking: Smoked daily in 

the week before learning they were 

pregnant and were still smoking at 

36 weeks’ gestation:

– 1–6 cigarettes/day

– >6 cigarettes/day

Smoking status based on self-reports

Quit status confirmed with both expired 

CO and urine cotinine collected at

36 weeks

Mean birth weight (SD):

•

•

•

Continued smoking, 1–6 cigarettes/day: 

3,071 g (525)

Continued smoking, >6 cigarettes/day: 

2,841 g (447)

Quit smoking: 3,289 g (592)

Difference in mean birth weight:

• Quit smoking vs. continued smoking

>6 cigarettes/day: +448 g, p <0.01

All study participants were 

smokers; no nonsmoker 

comparison group

Results not adjusted for 

potential confounders

Authors reported that no 

baseline variables were 

associated with infant 

birth weight

Did not account for alcohol 

or illicit drug use

Vogazianos et al. 

(2005) 

• Population-based 

retrospective cohort

• n = 59,014

• 1990–1996

• Cyprus

• Nonsmoker: Did not smoke before or 

during pregnancy

• Quite smoking: Smoked before but not 

during pregnancy; not clear how many 

women quit smoking during pregnancy 

and how they were categorized

• Continued smoking: Smoked before 

and during pregnancy

• Smoking status based on retrospective 

self-reports; exact timing of data 

collection not reported

Mean birth weight:

• Nonsmoker: 3,254 g

• Quit smoking: 3,258 g

• Continued smoking: 3,162 g

Difference in mean birth weight (95% CI):

• Quit smoking vs. nonsmoker: 

+4 g (-29–37 g)

• Continued smoking vs. nonsmoker: 

-92 g (-124– -59 g)

Results not adjusted for 

potential confounders

Did not account for alcohol

or illicit drug use

Wen et al. 

(2005)

•

•

•

•

•

•

Wen et al. (2005)

Pregnancy Risk Assessment 

Monitoring System

Singleton, live births

n = 9,499

1989–1992

Taipei City, Taiwan

•

•

Nonsmokers: Details not provided

Quit smoking: Quit by the time of the 

first prenatal visit in the first trimester; 

not clear if this included those who quit 

before pregnancy

•

•

Continued smoking: Smoked after the 

first visit in the first trimester

Smoking status based on self-reports

Mean adjusted birth weight (SD) and 

difference in mean adjusted birth weight:

•

•

•

Continuing smokers: 3,027 g (450) 

(reference) 

Nonsmokers: 3,184 g (430 g), +157 g,

p <0.05 

Quit smoking: 3,195 g (447 g), +168 g, 

p <0.05 

Results not adjusted for 

maternal age, parity, alcohol

use, and sex of the infant

Did not account for illicit 

drug use

Table 4.32 Continued

The Health Benefits of Smoking Cessation 345
Study Design/population Exposure groups/how determined Estimate of effects Comments

England et al. 

(2007)

• Randomized trial for 

preeclampsia prevention

• Nulliparous women

• n = 4,289

• 1992–1995

• Multiple centers in the 

United States

• Nonsmokers: Never smoked regularly

• Quit before pregnancy: Quit before last 

menstrual period and validated with 

cotinine mid-pregnancy

• Quit during pregnancy: Quit after last 

menstrual period and validated with 

cotinine mid-pregnancy

• Quit before/during pregnancy: Women 

from two previous categories combined

• Continued smoking: Smoking at 

study enrollment

• Smoking status based on self-reports 

obtained at study enrollment

• (13–21 weeks’ gestation)

• Quit status validated with urine cotinine 

concentration obtained mid-pregnancy 

(mean: 28 weeks’ gestation)

Mean adjusted birth weight (SE) and 

difference in mean adjusted birth weight:

• Nonsmokers: 3,232 g (12.3 g) (reference)

• Quit before or during pregnancy, selfreport: 3,233 g (17.7 g), +1 g

• Quit before or during pregnancy, cotinine 

validated: 3,253 g (19.3 g), +21 g

• Continued smoking: 3,071 g (19.1 g), 

-161 g, p <0.05

Results adjusted for 

maternal BMI, race, study 

center, sex of the infant, 

and gestational age

Did not account for alcohol 

or illicit drug use

Abrevaya et al. 

(2008)

•

•

•

•

•

Analysis of linked 

certificates of live births

First and second singleton 

pregnancies in which 

women smoked during 

the first pregnancy

n = 22,775

1989–2004

Michigan

•

•

•

Quit smoking between pregnancies: 

Smoked during the first pregnancy but 

not during the second pregnancy 

Continued smoking during both 

pregnancies: Smoked during first and 

second pregnancies 

Smoking status based on smoking 

history collected from certificates of 

live births,which used one question on 

tobacco use during pregnancy (yes/no) 

Mean adjusted birth weight (SD) and 

difference in mean adjusted birth weight 

(95% CI):

• 18–24 years of age:

–

–

Quit: 3,258 g (545 g) (reference)

Continued smoking: -134 g 

(-152– -115 g)

• 25–30 years of age:

–

–

Quit: 3,317 g (536 g) (reference)

Continued smoking: -115 g 

(-138– -92 g)

Results adjusted for maternal 

race, education, income, 

population, interpregnancy 

interval, year of birth, 

trimester of first prenatal 

visit, presence of father’s 

name on birth certificate, 

number of prenatal visits, 

and first-birth value of 

the outcome 

Did not account for alcohol 

or illicit substance use

Table 4.32 Continued

A Report of the Surgeon General

346 Chapter 4
Study Design/population Exposure groups/how determined Estimate of effects Comments

Mendez et al. 

(2008)

• Prospective cohort study

of childhood overweight

• Term births

• n = 482

• 1997–1998

• Spain

• Nonsmokers: Never smoked

• Quit smoking before pregnancy

• Quit smoking during the first trimester

• Continued smoking: Still smoking 

during the second trimester

• Smoking status based on self-reports

Mean unadjusted birth weight (SD) and 

difference in mean adjusted birth weight:

• Nonsmokers/quit smoking before 

pregnancy: 3,282 g (442 g)

• Quit smoking during the first trimester:

3,259 g (417 g), +23 g

• Continued smoking: 3,085 g (430 g), 

-197 g, p <0.05 compared with 

nonsmokers/women who quit smoking 

before pregnancy

Analysis restricted to 

term births

Results not adjusted for 

potential confounders

Did not account for alcohol 

or illicit drug use

Nijiati et al. 

(2008)

•

•

•

•

•

Prospective cohort study

Singleton births

n = 939

2006

Hiroshima, Japan

•

•

•

•

•

Nonsmokers: Did not smoke before or 

during pregnancy

Quit smoking: Quit during pregnancy

Continued smoking: Smoked before and 

continued smoking during pregnancy

Smoking status based on self-reports 

ascertained by questionnaire

Did not describe when questionnaire 

was administered, when women quit 

smoking, and procedures for follow-up 

and outcomes ascertainment

Mean birth weight (SD) and difference 

in mean birth weight:

• Nonsmokers:

–

–

Unadjusted: 3,075 g (368 g) (reference)

Adjusted 3,241 g (377 g) (reference)

• Quit smoking:

–

–

Unadjusted: 3,043 g (421 g), -32 g

Adjusted: 3,197 g (377 g), -44 g

• Continued smoking:

–

–

Unadjusted: 2,897 g (348 g), -178 g

Adjusted: 3,099 g (462 g), -142 g,

p = 0.0004

Results adjusted for sex 

of the infant, parity, maternal 

age, mother’s BMI and 

height, gestational age, and 

exposure to secondhand 

smoke during pregnancy

Did not account for alcohol 

or illicit drug use

Sasaki (2008) • Prospective cohort study 

of gene–environment 

interactions in women

• Singleton pregnancies

• Excluded women with 

pregnancy complications 

(hypertension, diabetes)

• n = 460

• 2002–2005

• Sapporo, Japan

• Nonsmokers: Did not smoke during 

pregnancy

• Quit smoking: Quit in the first trimester

• Continuing smokers: Smoked after the 

first trimester

• Smoking status based on self-reports 

ascertained from a questionnaire 

administered at study enrollment

Mean unadjusted birth weight (SD) 

(Kruskal-Wallis test, p = 0.003) and 

difference in mean adjusted birth weight:

• Nonsmokers: 3,078 g (347 g) (reference)

• Quit smoking: 3,138 g (384 g), -60 g

• Continued smoking: 2,961 g (386 g),

-117 g

Difference in mean adjusted birth weight:

• Nonsmokers (reference)

• Quit smoking: -31 g

• Continued smoking: -148 g

Results adjusted for 

maternal age, height, weight, 

gestational weight gain, 

alcohol use, parity, sex of 

the infant, gestational age, 

and income

Did not account for illicit 

drug use

Table 4.32 Continued

The Health Benefits of Smoking Cessation 347
Study Design/population Exposure groups/how determined Estimate of effects Comments

Andersen et 

al. (2009)

•

•

•

•

•

Clinic-based study of 

endothelial function by 

smoking status

Term pregnancies without 

complications (diabetes, 

hypertension)

n = 266

2003–2004

Denmark

•

•

•

•

Nonsmoker: Did not smoke before 

pregnancy

Quit smoking: Smoked during pregnancy 

but quit by 18 weeks’ gestation

Continued smoking: Smoked 

throughout pregnancy

Smoking status based on self-reports 

ascertained from questionnaire and 

validated with serum cotinine 

Mean unadjusted birth weight (95% CI) 

and difference in mean birth weight

•

•

Nonsmoker: 3.65 kg (3.01–4.50 kg) 

(reference)

Quit smoking: 3.60 kg (3.06–4.55 kg),

-0.05 kg

• Continued smoking: 3.30 kg (2.54–4.14):

–

–

Unadjusted: -364 g

Adjusted: -242 g, p = 0.002

Analysis restricted to

term births

Birth weight difference 

for continued smoking vs. 

nonsmokers adjusted for 

endothelial nitric oxide 

synthase, pre-pregnancy 

BMI, parity, gestational 

age, and sex of the infant

Did not account for alcohol 

or illicit drug use

Fasting et al. 

(2009)

• Prospective intervention

• of allergy prevention

• in children

• n = 711

• 2000–2002

• Norway

• Nonsmoker: Not smoking when 

became pregnant

• Quit smoking: Smoking when became 

pregnant but quit by enrollment

• Continued smoking: Smoking when 

became pregnant and still smoking 

at enrollment

• Smoking status based on self-reports 

collected at study enrollment (median 

gestational age 11 weeks, all <28 weeks)

Mean birth weight (SD) and difference 

in mean birth weight:

• Nonsmoker: 3,646 g (518 g) (reference)

• Quit smoking: 3,628 g (497 g), -14 g

• Continued smoking: 3,449 g (486 g), 

-197 g

Results not adjusted for 

potential confounders

Did not account for alcohol

or illicit drug use

Did not show direct 

statistical comparisons 

between groups

Johansson et al. 

(2009)

•

•

•

•

•

Births from the Swedish 

Birth Registry

First and second 

consecutive, singleton 

pregnancies

n = 555,046

1983–2002

Sweden

•

•

•

•

•

Nonsmoker: Did not smoke during 

either pregnancy

Quit smoking: Smoked during first but 

not during second pregnancy

Started smoking: Smoked during second

but not during first pregnancy

Continued smoking: Smoked during 

both pregnancies

Smoking status ascertained from 

Swedish Birth Registry, as derived from 

first antenatal visit, typically <15 weeks’ 

gestation; no information on cessation 

during pregnancy

Mean birth weight second pregnancy (SD) 

and difference in mean birth weight:

•

•

•

•

•

First pregnancy for each exposure 

group (reference)

Nonsmoker: 3,658 g (535 g), +173 g

Quit smoking: 3,643 g (539 g), +233 g

Started smoking: 3,520 g (545 g), +80 g

Continued smoking: 3,430 g (539 g),

+119 g

Quit status defined across 

pregnancies but not 

within pregnancies

Results not adjusted for 

potential confounders

Did not account for alcohol 

or substance use

Did not show direct 

statistical comparisons 

between groups

Table 4.32 Continued

A Report of the Surgeon General

348 Chapter 4
Study Design/population Exposure groups/how determined Estimate of effects Comments

Kabir et al.

(2009)

• Cross-sectional study 

of changes in smoking 

status after a workplace

• Singleton, live births

• n = 15,241

• 2003 and 2005

• Ireland

• Nonsmokers: Never smokers

• Quit smoking: Former smokers

• Continued smoking: Current smokers

• Smoking status based on self-reports

• No details of how and when smoking 

status was ascertained

• Authors reported that smoking status 

across different periods of gestation 

was not available

Mean adjusted birth weight (95% CI) and 

difference in mean adjusted birth weight:

• 2003:

– Nonsmoker: 3,527 g (3,450–3,604 g)

(reference)

– Quit smoking: 3,549 g (3,435–3,663 g),

+22 g

– Continued smoking: 3250 g

(3,157–3,343 g), -370 g

• 2005:

– Nonsmoker: 3,503 g (3,426–3,580 g) 

(reference)

– Former smoker: 3,547 g 

(3,433–3,661 g), +44 g

– Current smoker: 3,220 g 

(3,127–3,313 g), -283 g

Results adjusted for 

gestational age

Results not adjusted for 

smoking ban other potential 

confounders

Did not account for alcohol 

or substance use

McCowan et al. 

(2009)

•

•

•

•

Prospective cohort study 

designed to develop 

screening tests for 

pregnancy complications

n = 2,504

2004–2007

New Zealand and Australia

•

•

•

•

•

Nonsmokers: Did not smoke during 

pregnancy

Quit smoking: Smoked during pregnancy 

but quit before being interviewed at

15 weeks’ gestation

Continued smoking: Smoked at 15 weeks’ 

gestation

Smoking status based on self-reports 

ascertained at 15 weeks’ gestation

Mean adjusted birth weight (SD) and 

difference in mean adjusted birth weight:

•

•

•

•

Nonsmoker: 3,409 (592 g) (reference)

Quit smoking: 3,479 g (560 g) +70 g

(-6–146 g), p = 0.09

Continued smoking: 3,139 (751g) -270 g 

(-350– -190 g), p <0.001

Results adjusted for maternal 

age; ethnicity; marital 

status; employment; BMI; 

bleeding during pregnancy; 

folic acid use; multivitamin 

use; alcohol consumption

at 15 weeks’ gestation; and 

scores for depression, stress, 

or anxiety

Did not account for illicit 

drug use

Adegboye et al. 

(2010)

• Retrospective cohort 

study of risk factors 

for postpartum weight 

retention

• Singleton pregnancies

• n = 1,753

• 1984–1985

• Sweden

• Nonsmokers: Never smoked

• Quit smoking: Quit smoking during 

first trimester and remained abstinent 

throughout pregnancy

• Continued smoking: Continued to 

smoke during pregnancy

• Smoking status based on self-reports 

collected after delivery; details

not reported

Mean unadjusted birth weight (SD):

• Nonsmoker: 3.5 kg (0.5 kg)

• Quit smoking: 3.4 kg (0.5 kg)

• Continued smoking 3.3 kg (0.5 kg)

• p <0.001

Results not adjusted for 

potential confounders

Did not account for alcohol 

or substance use

Table 4.32 Continued

The Health Benefits of Smoking Cessation 349
Study Design/population Exposure groups/how determined Estimate of effects Comments

Prabhu et al. 

(2010)

•

•

•

•

Prospective cohort 

study of risk factors 

for childhood asthma 

and allergy

n = 1,924

1997–1999

Scotland

•

•

•

•

•

•

Nonsmoker: Never smoked or quit 

smoking before pregnancy (additional 

details related to timing of cessation 

not reported)

Quit smoking: Quit in first trimester

Continued smoking in first trimester:

No change in number of cigarettes/day

Reduced number of cigarettes/day

Smoking status based on self-reports 

obtained at enrollment in the first 

trimester and at 32 weeks’ gestation

Difference in mean adjusted birth weight 

(95% CI):

•

•

•

•

Continued smoking, no change in 

number of cigarettes/day (reference) 

Nonsmoker: +290 g (115–463 g) 

Reduced number of cigarettes/day:

+104 g (-73–282 g) 

Quit smoking: +246 g (46–445 g) 

Results adjusted for sex of 

the infant, maternal height, 

plasma alpha-tocopherol 

and cholesterol, paternal 

smoking, and gestational age

Did not account for alcohol 

or substance use

Vardavas et al. 

(2010)

• Population-based 

cohort study

• n = 1,400

• 2007–2008

• Crete, Greece

• Nonsmoker: Did not smoke from 

3 months before and throughout 

pregnancy

• Quit smoking: Stopped smoking 

between 3 months before pregnancy 

and 12 weeks’ gestation

• Continued smoking: Smoked at 

12 weeks’ gestation

• Smoking status based on self-reports 

obtained at enrollment, second, and 

third trimesters

Mean unadjusted birth weight (SD) and 

difference in mean adjusted birth weight 

(95% CI):

• Nonsmoker: 3,171 g (473 g) (reference)

• Quit smoking: 3,207 g (465 g), +39 g

(-18–96 )

• Continued smoking: 3,059 g (498 g),

-119 g (-177– -62 g)

Results adjusted for 

gestational age, parity, 

origin (Greek/non-Greek), 

maternal education, age, 

and sex of the infant

Did not account for alcohol 

or illicit drug use

Bakker et al. 

(2011)

•

•

•

•

Population-based, 

prospective cohort study

n = 5,389

2001–2005

Netherlands

•

•

•

•

•

•

Nonsmokers: Did not smoke during 

pregnancy

Quit smoking: Smoked during pregnancy 

but only during first trimester

Continued smoking (categories collapsed 

for analysis):

Second trimester: Smoked during 

pregnancy and during second trimester

Third trimester: Smoked during 

pregnancy and during third trimester

Smoking status based on self-reports 

obtained in each trimester of pregnancy

Mean birth weight (SD) and difference in 

mean birth weight (95% CI):

•

•

Nonsmokers: 3,473 g (547 g) (reference)

Quit smoking:

–

–

–

Unadjusted: 3,418 g (555 g), -55 g,

p <0.05

Adjusted, single assessment: -14 g 

(-49–20 g)

Adjusted, repeated assessment of 

smoking status: +38 g (-3–79 g)

• Continued smoking:

–

–

–

Unadjusted: 3,274 g (500 g), -199 g,

p <0.01

Adjusted, single assessment: -157 

(-194-120 g)

Adjusted, repeated assessment of 

smoking status: -143 (-175– -111 g)

Results adjusted for 

maternal age, BMI, height, 

education, ethnicity, parity, 

alcohol consumption, 

caffeine intake, folic acid 

intake, maternal stress, 

gestational age at birth, 

and sex of the fetus

Did not account for illicit 

drug use

Table 4.32 Continued

A Report of the Surgeon General

350 Chapter 4
Study Design/population Exposure groups/how determined Estimate of effects Comments

BenjaminGarner and 

Stotts (2013)

• Randomized trial of a 

behavioral intervention 

for smoking cessation

• Term, singleton 

pregnancies

• 2001–2004

• n = 260

• 2001–2004

• Texas

• Quit smoking: Salivary cotinine 

<15 ng/mL in late pregnancy 

(36 weeks’ gestation)

• Light smoker: Salivary cotinine 

<150 ng/mL at enrollment, continued 

smoking (stayed light or increased 

to heavy)

• Heavy smoker: Salivary cotinine 

≥150 ng/mL at enrollment, continued 

smoking (stayed heavy or decreased 

to light)

• Smoking status based on self-report and 

salivary cotinine obtained at enrollment 

(16–26 weeks’ gestation), 36 weeks’ 

gestation, and 6 weeks postpartum 

Mean unadjusted birth weight (SD) and 

difference in mean unadjusted birth 

weight:

• Quit smoking: 3,415 g (521g) (reference)

• Light smoker, stayed light: 3,252 g 

(504 g), -163 g

• Light smoker, increased to heavy: 3,212 g

(447 g), -203 g

• Heavy smoker, decreased to light: 3,315 g

(368 g), -100 g

• Heavy smoker, stayed heavy: 3,116 g

(447 g), 299 g

• Pairwise comparison found that the only 

significant difference was between heavy 

smokers who stayed heavy smokers and 

quitters (p = 0.02). Findings did not 

change after adjustment for potential 

confounders (p = 0.05).

Randomized cessation trial, 

and thus no comparison 

group of nonsmokers

Results adjusted for maternal 

age, race/ethnicity, parity, 

education, income, sex of 

the infant, gestational age 

at delivery, pre-pregnancy 

BMI, and gestational weight 

gain (education and parity 

removed from final models)

Restricted to term births 

Did not account for alcohol 

or substance use

Himes et al. 

(2013)

•

•

•

•

Prospective cohort study

Date not provided

n = 119

Rhode Island

•

•

•

•

Nonsmokers:Did not smoke 

during pregnancy 

Quit smoking: Smoked during 

pregnancy but quit before delivery 

Smoked throughout pregnancy 

Smoking status throughout pregnancy 

based on self-reports obtained 

in third trimester of pregnancy, 

>28weeks’ gestation

Mean unadjusted birth weight (SD) and 

difference in mean birth weight:

•

•

•

Smokers: 3,162 g (434 g) (reference)

Nonsmokers: 3,464 g (444 g), +302 g

Quit smoking: 3,557 g (504 g), +395 g

Differences between 

continuing smokers and 

nonsmokers and quitters 

were statistically significant, 

even after adjusting for 

socioeconomic status, 

maternal age, income, and 

education (data not shown)

Excluded women who used 

illicit drugs

Table 4.32 Continued

The Health Benefits of Smoking Cessation 351
Study Design/population Exposure groups/how determined Estimate of effects Comments

Juarez and 

Merlo (2013)

• Births from the Swedish 

Medical Birth Register

• Singleton, term births

• n = 677,922 births for 

conventional analysis

• n = 62,941 siblings for 

sibling analysis

• 2002–2010

• Sweden

• Nonsmokers: Not smoking at either early 

or late antenatal visit

• Continued smoking: Smoking at early 

and late antenatal visits:

– Light, light smoker

– Light, heavy smoker

– Heavy, light smoker

– Heavy, heavy smoker

• Quit smoking: Smoked at first but not 

second antenatal visit:

– Light, quit smoking

– Heavy, quit smoking

• Started smoking: Did not smoke at first 

antenatal visit but smoked at second 

antenatal visit:

– Nonsmoker, light smoker

– Nonsmoker, heavy smoker

• Light smokers: 1–9 cigarettes/day

• Heavy smokers: ≥10 cigarettes/day

• Smoking status obtained from the 

Swedish Medical Birth Register which 

relies on self-reported data collected 

during early (10–12 weeks’ gestation) 

and late (30–32 weeks’ gestation) 

antenatal visits

Difference in mean adjusted birth weight 

(95% CI):

• Conventional analysis:

– Nonsmokers (reference)

– Quit smoking:

 Light, quit: -47 g (-55– -40 g)

 Heavy, quit: -79 g (-100– -58 g)

– Continued smoking:

 Heavy, heavy: -303 g (-313– -292 g)

 Light, heavy: -265 g (-279– -250 g)

 Heavy, light: -254 g (-266– -242 g)

 Light, light: -221 g (-227– -214 g)

 Started smoking:

 Nonsmoker, light: -129 g 

(-142– -117 g)

 Nonsmoker, heavy: -142 g 

(-177– -108 g)

• Sibling analysis:

– Nonsmokers (reference)

– Quit smoking:

 Light, quit: -29 g (-42– -16 g)

 Heavy, quit: -1 g (-46– –44 g)

– Continued smoking:

 Heavy, heavy: -226 g (-274– -179 g)

 Light, heavy: -259 g (-309– -209 g)

 Heavy, light: -194 g (-238– -151 g)

 Light, light: -162 g (-178– -147 g)

– Started smoking:

 Nonsmoker, light: -77 g (-97– -57 g)

 Nonsmoker, heavy: -83 g 

(-140– -25 g)

– Effects of smoking on birth weight

were attenuated by 6–78 g using 

sibling analysis compared 

with traditional analysis 

Results adjusted for 

gestational age, marital 

status, maternal age, birth 

order, sex of the newborn, 

pregnancy complications 

(diabetes, hypertension, 

urinary problems), and 

use of snus

Did not account for alcohol 

or substance use

Table 4.32 Continued

A Report of the Surgeon General

352 Chapter 4
Study Design/population Exposure groups/how determined Estimate of effects Comments

Miyake et al. 

(2013)

•

•

•

•

Prospective cohort study

n = 1,565

2007–2008

Japan

•

•

•

•

•

•

Nonsmoker: Did not smoke during 

pregnancy

Quit smoking:

First trimester: Smoked during 

first trimester only

Second or third trimester: Smoked 

during second or third trimester

but not throughout pregnancy

Continued smoking: Smoked 

throughout pregnancy

Smoking status for each trimester 

of pregnancy based on self-reports 

obtained after delivery

Mean adjusted birth weight (95% CI) and 

difference in mean adjusted birth weight:

•

•

•

•

•

Nonsmoker: 3,011 g (2,994, 3,027) 

(reference)

Quit smoking first trimester: 3,028 g 

(2,951–3,104 g), +17 g

Quit smoking second or third trimester: 

2,958 g (2,838–3,079 g), -53 g

Continued smoking: 2,841 g 

(2,738–2,944 g), -170 g

p for trend = 0.005 

Results adjusted for 

maternal age, residence,

education, employment, 

alcohol consumption, and 

BMI; family structure; 

gestational age at birth; 

and sex of the infant

Did not address illicit 

drug use

Murphy et al. 

(2013)

• Prospective cohort study

• Singleton pregnancies

• n = 1,216

• 2010–2011

• Dublin, Ireland

• Nonsmoker: Not defined

• Quit smoking: Smoked during 6 months 

before pregnancy but quit by first 

prenatal visit

• Continued smoking: Smoked during 

6 months before pregnancy, at first 

prenatal visit, and during third trimester

• Smoking status based on self-reports 

obtained at enrollment and third 

trimester

Mean birth weight (SD) and difference in 

mean adjusted birth weight (95% CI):

• Nonsmoker: 3,496 g (509 g) (reference)

• Quit smoking: 3,503 (491 g), +7 g

(-81–95 g)

• Continued smoking: 3,305 g (491 g),

-191 g (-194– -88 g)

Results adjusted for maternal 

age, BMI, nationality, 

unplanned pregnancy, 

private healthcare, alcohol 

use, and illicit drug use

Rode et al. 

(2013)

•

•

•

•

•

Prospective cohort study

Singleton, term 

pregnancies

n = 1,774

1996–1999

Copenhagen, Denmark

•

•

•

•

•

•

Nonsmokers: Not defined

Quit smoking: Quit smoking immediately 

before or during pregnancy

Continued smoking: Not defined

Smoking status based on self-reports 

and on salivary cotinine obtained in a 

subgroup at 16 and 37 weeks’ gestation

Smoking status assessed at 12–18 weeks’ 

gestation, 37 weeks’ gestation, and

1 year postpartum

Mean birth weight (SD) and difference in 

mean birth weight (95% CI):

•

•

Nonsmokers: 3,675 g (482 g) (reference) 

Quit: 3,670 g (510 g) 

–

– 

Unadjusted difference: +4 g (-66–64 g) 

Adjusted difference: +26 g (-29–81 g) 

• Continued smoking: 3,405 g (487 g) 

–

–

Unadjusted difference:-270 g 

(-333– -208 g) 

Adjusted difference:-260 g

(-318– -204 g) 

Results adjusted for prepregnancy BMI, gestational 

age, and parity

Restricted to term births

Did not account for alcohol 

or substance use

Salivary cotinine for 

subgroup reported but 

not integrated into main 

analysis

Table 4.32 Continued

The Health Benefits of Smoking Cessation 353
Study Design/population Exposure groups/how determined Estimate of effects Comments

Meghea et al. 

(2014)

• Prospective cohort study

• n = 474

• 2008–2009

• Romania

• Nonsmokers: Not smoking when learned 

of pregnancy

• Quit smoking: Quit upon learning of 

pregnancy

• Continued smoking: Smoking at time 

of study interview (gestational age 

not reported)

• Smoking history based on self-reports 

obtained at study enrollment (gestational 

age not reported)

Mean unadjusted birth weight and 

difference in mean birth weight:

• Nonsmoker: 3382 g (reference)

• Quit smoking: 3340 g

– Unadjusted: -42 g

– Adjusted: -48 g

• Continued smoking: 3176 g

– Unadjusted: -206 g, p <0.05

– Adjusted: -165 g

Results adjusted for stress, 

depressive symptoms, 

maternal age >35 years old, 

education, rural residence, 

marital status, and 

nulliparity 

or substance use

Did not account for alcohol 

Räisänen et al. 

(2014)

•

•

•

•

•

Finnish Medical Birth 

Register

Singleton deliveries, 

live or stillborn

n = 1,164,953

1991–2010

Finland

•

•

•

•

Nonsmokers: Not defined

Quitters: Quit smoking during first 

trimester

Continuing smokers: Smoked after 

first trimester

Smoking history ascertained from 

the Finnish Medical Birth Register

Mean unadjusted birth weight (SD) and 

difference in mean birth weight:

•

•

•

Nonsmokers: 3,575 g (547 g) (reference)

Quitters: 3,531 g (546 g), -44 g

Continuing smokers: 3,383 g (586 g),

-192 g

Results not adjusted for 

potential confounders

Results of statistical testing 

not provided.

Did not account for alcohol 

or substance use

Slatter et al. 

(2014)

• Study of smoking and 

placental pathology

• Singleton, term births

• Excluded women with 

diabetes or hypertension

• n = 236

• 2009–2011

• New Zealand

• Nonsmokers: Did not smoke 

during pregnancy

• Quit smoking: Stopped smoking at 

least 4 weeks before delivery

• Continued smoking: Smoked during 

pregnancy and up to delivery

• Smoking history based on self-reports 

obtained at the time placentas

were collected

Mean unadjusted birth weight (SD) and 

difference in mean adjusted birth weight:

• Nonsmokers: 3.56 kg (0.36 kg)

• Quit smoking: 3.64 kg (0.59 kg), +0.08 kg

• Continuing smokers: 3.29 kg (0.49 kg),

-0.27 kg

Results not adjusted for 

potential confounders, but 

restricted to term births

Did not account for alcohol 

or substance use 

Table 4.32 Continued

A Report of the Surgeon General

354 Chapter 4
Study Design/population Exposure groups/how determined Estimate of effects Comments

Suzuki et al. 

(2014)

•

•

•

•

•

Prospective cohort study

Singleton deliveries

1991–2006

n = 2,663

Japan

•

•

•

•

•

•

Nonsmokers: Never smoked

Quit smoking before pregnancy

Quit smoking during early pregnancy

Continued smoking: Smoking at 

study enrollment

Smoking exposure categories not 

further defined

Smoking history based on self-reports 

obtained during early pregnancy 

(usually first trimester)

Mean unadjusted birth weight (SD):

•

•

•

•

Nonsmokers: 3,069 g (387 g)

Quit before pregnancy: 3,052 g (393 g)

Quit during early pregnancy: 3,046 g 

(409 g)

Continued smoking: 2,902 g (409 g)

Mean adjusted birth weight and difference 

in mean adjusted birth weight, by sex:

• Boys: 

–

–

–

–

Nonsmokers: 3,084 g (reference) 

Quit smoking before pregnancy: 

3,015 g, 69 g, p = 0.2 

Quit smoking during early 

pregnancy: 3,065 g,-19 g, p = 0.9 

Continued smoking: 2,960 g,-124 g, 

p = 0.002 

• Girls: 

–

–

–

–

Nonsmokers: 3,039 g (reference) 

Quit smoking before pregnancy: 

3,029 g, 10 g, p = 0.99 

Quit smoking during early pregnancy: 

3,063 g, +24 g, p = 0.8 

Continued smoking: 2,888 g,-151 g, 

p = 0.002 

Results adjusted for 

maternal age, parity, BMI,

and gestational age

Did not account for alcohol 

or substance use

Bailey (2015) • Randomized clinical trial 

of smoking cessation 

intervention

• n = 1,486

• 2008–2012

• Tennessee

• Quit smoking: Smoked at first prenatal 

visit but quit by third trimester

• Continued smoking: Smoked at first 

prenatal visit and still smoking in the 

third trimester

• Smoking history based on self-reports 

obtained at first prenatal visit

• Quit status ascertained in third trimester 

by exhaled CO, urine cotinine, and selfreport at delivery

Mean adjusted birth weight and 

difference in mean adjusted birth weight:

• Quit smoking: 3,216 g, +204 g

• Continued smoking: 3,012 g (reference)

• p <0.001

Randomized cessation trial 

and thus no comparison 

group of nonsmokers

Results adjusted for 

maternal age, education, 

marital status, insurance 

status, and marijuana use

Examined alcohol use, 

but it was not significant 

in the model

Table 4.32 Continued

The Health Benefits of Smoking Cessation 355
Study Design/population Exposure groups/how determined Estimate of effects Comments

Blatt et al. 

(2015)

•

•

•

•

Population-based 

retrospective cohort 

study using Ohio 

certificates of live birth

n = 927,424

2006–2012

Ohio

•

•

•

•

•

•

Nonsmoker: Did not smoke during 

3 months before pregnancy or 

during pregnancy

Quit smoking before pregnancy: Smoked 

during 3 months before pregnancy but 

not during pregnancy

Quit smoking, first trimester: Smoked 

during first trimester only

Quit smoking, second trimester: Smoked 

during first and second trimesters, but 

not third trimester

Continued smoking: Smoked 

throughout pregnancy

Smoking history ascertained from vital 

statistics data and certificates of live birth

Mean birth weight (SD) and difference in 

mean birth weight:

•

•

•

•

•

Nonsmokers: 3,340 g (558 g) (reference)

Quit smoking before pregnancy: 3,339 g 

(557 g),-1 g

Quit smoking, first trimester: 3,280 g 

(590 g), -60 g

Quit smoking, second trimester: 3,072 g 

(763 g), -268 g

Continued smoking: 3,090 g (542), -250 g

Results not adjusted for 

potential confounders 

Statistical testing 

not reported

Did not account for alcohol 

or substance use

Grzeskowiak et 

al. (2015)

• Retrospective cohort study

• n = 7,658

• 2000–2005

• South Australia

• Nonsmokers

• Quit smoking during pregnancy

• Continued smoking: Smoked 

during pregnancy

• Smoking status not further defined

• Smoking history based on self-reports 

ascertained at first prenatal care visit

Mean birth weight (SD) and difference in 

mean birth weight:

•

•

Nonsmokers: 3,410 g (610 g)(reference) 

Quit smoking: 3,408 g (608 g)(-2 g) 

• Continuing smokers 3,155 g (628 g), 

-255 g, p <0.001 

Results not adjusted for 

potential confounders

Did not account for alcohol 

or substance use

Yan and 

Groothuis 

(2015)

•

•

•

•

•

•

Population-based 

cohort study

Singleton pregnancies

Excluded women with 

chronic diseases

n = 11,131

2000–2001

United Kingdom

•

•

•

•

•

Nonsmokers: Not defined

Quit smoking before pregnancy 

(timing of cessation not specified)

Quit smoking during pregnancy 

(month of cessation noted)

Continued smoking: Smoked beyond 

7 months’ gestation

Smoking history based on self-reports

ascertained when infants were

9 months old

Mean unadjusted birth weight (SD) and 

difference in mean birthweight:

•

•

•

•

•

•

•

•

•

•

•

•

•

Nonsmokers 3,452 g (551 g)

Quit smoking before pregnancy: -8 g

Quit smoking month 1: -5 g

Quit smoking month 2: -5 g

Quit smoking month 3: -9 g

Quit smoking month 4: -143 g, p <0.05

Quit smoking month 5: -170 g, p <0.05

Quit smoking month 6: -184 g 

Quit smoking month 7: -215 g, p <0.05

Continued smoking: -245 g, p <0.05

Quit smoking trimester 1: -5 g

Quit smoking trimester 2: -159 g, p <0.05

Continued smoking: -245 g, p <0.05

Results adjusted for birth 

year/quarter of infant, 

maternal weight, height, 

income, prenatal care 

initiation, alcohol use, 

maternal employment 

status, home satisfaction, 

religion affiliation, and 

racist or religion-based 

insults in living area

Did not account for 

substance use

Table 4.32 Continued

A Report of the Surgeon General

356 Chapter 4
Study Design/population Exposure groups/how determined Estimate of effects Comments

Hayes et al. 

(2016)

• Quasi-experimental, 

historical cohort of 

smoking cessation 

intervention trial

• Excluded deliveries of 

infants <1,500 g

• n = 652

• 2004–2005

• Ireland

• Quit smoking before enrollment: 

Smoked when became pregnant, quit 

before first study visit, and did not 

resume smoking

• Quit smoking after enrollment: Smoked 

at time of first study visit but quit by third 

study visit (combined with “attempted

to quit” for adjusted analysis)

• Attempted to quit: Attempted to quit at 

first or second study visit but resumed 

at one or more visits (combined with 

“quit smoking after enrollment” for 

adjusted analysis)

• Continued smoking: Smoked at the time 

of all three study visits

• Smoking status based on self-reports 

and validated with urine cotinine levels 

at second study visit (did not describe 

how cotinine levels were used in the 

analysis), and ascertained at three visits 

(12–18 weeks’ gestation, 28–32 weeks’ 

gestation, and within 1 week of delivery)

Median birth weight and difference in 

mean birth weight (95% CI):

• Quit smoking before enrollment: 3,600 g, 

3,595 g (reference)

• Quit smoking after enrollment: 3,340 g, 

p = 0.07

• Attempted to quit: 3,450 g, p = 0.13

• Continued smoking: 3,260 g, 3,269 g,

-326 g (-483– -17), p < 0.01

Difference in mean adjusted birth weight 

(95% CI):

• All: 

– Continued smoking (reference) 

– Quit smoking before enrollment: 

+288 g (153–423 g) 

– Quit smoking after enrollment or 

attempted to quit: +147 g (50–244 g) 

• Preterm: 

– Continued smoking (reference) 

– Quit smoking before enrollment: +67 g 

(-272–407 g) 

– Quit smoking after enrollment or 

attempted to quit: +181 g (-236–600 g) 

• Term: 

– Continued smoking (reference) 

– Quit smoking before enrollment: 

+327 g (183–472 g) 

– Quit smoking after enrollment or 

attempted to quit: +146 g (46–246 g) 

Randomized cessation trial 

and thus no comparison 

group of never smokers

Results adjusted for other 

smokers in the household, 

gestational age at delivery, 

and sex of infant

Did not account for alcohol 

or substance use

Table 4.32 Continued

The Health Benefits of Smoking Cessation 357
Study Design/population Exposure groups/how determined Estimate of effects Comments

Suzuki et al. 

(2016)

(continues on 

next page)

•

•

•

•

• J

Population-based 

cohort study

Singleton pregnancies

n = 7,734

2011–2014

apan

•

•

•

•

•

Nonsmokers: Never smoked

Quit smoking before pregnancy: 

Not further defined

Quit smoking during early pregnancy: 

Not further defined

Continued smoking: Currently smoking 

at time in which study questionnaire 

was administered

Smoking status based on self-reports 

collected in second trimester

Mean birth weights (SD) and difference in 

mean birth weight:

•

•

•

•

Nonsmokers: 3,015 g (427 g) (reference)

Quit smoking before pregnancy: 3,029 g 

(408 g), +14 g

Quit smoking during early pregnancy: 

3,011 g (444 g), -4 g

Continued smoking: 2,873 g (423 g),

-142 g

Mean adjusted birth weights (SE) and 

difference in mean adjusted birth weight 

by sex of newborn:

• Female:

–

–

–

–

Nonsmokers: 3,018 g (16 g) (reference)

Quit smoking before pregnancy: 

3,030 g (18 g), +12 g, p = 0.7

Quit smoking during early pregnancy: 

2,979 g (21 g), -39 g, p = 0.06

Continued smoking: 2,894 (28 g),

-124 g, p <0.001

• Male:

–

–

-

–

–

Nonsmokers: 3,096 g (17 g) (reference)

Quit before pregnancy: 3,089 g (18 g),

7 g, p = 0.9

Quit during early pregnancy: 3,068 g 

(20 g),-28 g, p = 0.2

Continued smoking: 2,960 g (27 g),

-136 g, p <0.001

• Term births—Female:

–

–

–

–

Nonsmokers: 3,056 g (16 g) (reference)

Quit before pregnancy: 3,069 g (19 g),

+13, p = 0.6

Quit during early pregnancy: 3,021 g 

(21 g),-35 g, p = 0.1

Continued smoking: 2,928 g (28 g),

-128 g, p <0.001

Results adjusted for 

partner’s smoking status, 

income, birth order, 

pregnancy complications 

(hypertension, diabetes), 

pre-pregnancy weight, 

gestational weight 

gain, maternal age, and 

gestational age

Results stratified by term/

preterm delivery

Did not account for alcohol 

or substance use

Table 4.32 Continued

A Report of the Surgeon General

358 Chapter 4
Study Design/population Exposure groups/how determined Estimate of effects Comments

(continued from 

previous page) 

Suzuki et al. 

(2016)

— — •

–

–

–

–

Term births—Male:

Nonsmokers 3,142 g (18 g) (reference)

Quit before pregnancy: 3,134 g (19 g),

+8 g, p = 0.9

Quit during early pregnancy: 3,110 g 

(21 g),-32 g, p = 0.2

Continued smoking: 3,005 g (28 g),

-137 g, p <0.001

—

Wallace et al. 

(2017)

(reanalysis 

of Blatt et al. 

[2015])

• Population-based 

retrospective cohort study 

using Ohio certificates of 

live birth

• Singleton pregnancies

• Excluded congenital 

malformations

• All participants had 

at least one previous 

preterm delivery

• n = 36,432

• 2006–2012

• Ohio

• Nonsmoker: Did not smoke during 

3 months before pregnancy or during 

pregnancy

• Quit smoking by first trimester: Smoked 

during 3 months before pregnancy

but not during pregnancy

• Quit by second trimester: Smoked 

during first trimester but not during 

second and third trimesters

• Quit by third trimester: Smoked 

during second trimester but not during 

third trimester

• Continued smoking: Smoked during 

all three trimesters

• Smoking status obtained from U.S. 

certificates of live birth

Mean birth weight (SD) and difference in 

birth weight:

• Nonsmokers: 2,964 g (764 g) (reference)

• Quit smoking by first trimester: 2,951 g 

(745 g), -13 g

• Quit smoking by second trimester: 

2,841 g (819 g), -123 g

• Quit smoking by third trimester: 

2,343 g (1,061 g), -621 g

• Continued smoking: 2,743 g (667 g),

-221 g

• All comparisons significant at p <0.01

Results not adjusted for 

confounders

Did not account for alcohol 

or substance use

Table 4.32 Continued

The Health Benefits of Smoking Cessation 359

Notes: BMI = body mass index; CI = confidence interval; CO = carbon monoxide; g = grams; kg = kilograms; ng/mL = nanograms per milliliter; SD = standard deviation; 

SE = standard error.
A Report of the Surgeon General

360 Chapter 4

221 and 303 g in the conventional analysis for light and 

heavy smokers, respectively. Also, in the sibling analysis, 

cessation was associated with a reduction in birth weight 

of 29 g (95% CI, -42 to -16) for light smokers compared 

with nonsmokers, but it was not associated with a significant reduction in birth weight in heavy smokers (-1  g; 

95% CI, -46–44). By comparison, using nonsibling controls, babies of light smokers who quit had a reduction 

in birth weight of 47 g (95% CI, -55 to -40), while heavy 

smokers who quit had a reduction of 79 g (95% CI, -100 to 

-58) compared with nonsmokers during pregnancy. 

Several of the studies published since the 1990 and 

2004 Surgeon General’s reports examined the specific 

timing of tobacco smoke exposure and fetal growth. Yan 

and Groothuis (2015), who examined birth outcomes in 

more than 11,000  women and 2,000  smokers by gestational month of cessation through month 7, found little 

effect of smoking on birth weight in the first 3 months of 

pregnancy but increasing effects for every month women 

smoked after that. Estimates of the effect of smoking on 

birth weight were adjusted for several socioeconomic 

factors and alcohol use but not for gestational age, and 

they were statistically significant for months 4, 5, and 7. 

However, cessation status was not biochemically validated. 

Elsewhere, Blatt and colleagues (2015) examined cessation 

in a cohort of more than 900,000 births by trimester in a 

study using Ohio birth certificate data. Those researchers 

found a greater reduction in birth weight in quitters compared with nonsmokers over time (-60 g for smoking in 

the first trimester only, -268 g for smoking in the second 

trimester) but no further reduction for smoking through 

the third trimester (-250 g). The results were not adjusted 

for potential confounders or for gestational age, however, 

and there was no biochemical validation of cessation. All 

comparisons were statistically significant. 

Two studies examined smoking patterns across pregnancies and, thus, focused on cessation between pregnancies rather than on cessation during pregnancies. Abrevaya 

(2008) found that, after stratifying results by age, both 

the younger (18–24 years of age) and older (25–30 years 

of age) groups of continuing smokers had babies with 

lower mean birth weights compared with quitters, even 

after adjusting for multiple potential confounders (-134 g 

and -115  g, respectively) (Abrevaya 2008). In Sweden, 

Johansson and colleagues (2009) assessed smoking status 

during antenatal care for mothers having two live births, 

comparing the outcomes of the second pregnancy within 

exposure groups with those for the first pregnancy, and 

found increases in birth weight of the babies of quitters 

(233 g) and nonsmokers (173 g) that exceeded the increase 

in continuing smokers (119 g). An important limitation 

of study designs that examine outcomes across consecutive pregnancies is that the smoking exposure categories 

are often simplified (e.g., assessing smoking at only one 

time point for each pregnancy). If the timing of cessation 

(such as during pregnancy rather than before pregnancy, 

or during a specific trimester of pregnancy) affects infant 

birth weight, the effect may not be detected in studies with 

limited assessment of smoking exposure. 

Summary of the Evidence. Since the 2004 Surgeon 

General’s report confirmed that smoking cessation eliminates much of the reduction in birth weight caused by 

maternal smoking (USDHHS 2004), numerous studies 

have assessed the relationships between smoking and 

smoking cessation and fetal growth. Many studies adjusted 

for multiple confounders, and some included biochemical validation of quit status. The evidence is sufficient to 

infer that smoking cessation during pregnancy reduces 

the effects of smoking on birth weight and gestationalage adjusted birth weight. Depending on the timing of 

cessation, the birth weight of infants of women who quit 

smoking before or in early pregnancy approached or met 

that of nonsmokers in many studies. The evidence is inadequate to infer the exact gestational age before which cessation should occur to eliminate the effects of smoking 

on birth weight or gestational-age adjusted birth weight. 

Small for Gestational Age

In addition to gestational age–adjusted birth weight 

or birth weight in term infants, the designation of SGA 

(a birth weight ≤10th  percentile for gestational age) or 

the infant’s SGA status can be used as an indicator of fetal 

growth. SGA is a less sensitive measure of fetal growth 

than gestational age–adjusted birth weight, but it is 

strongly associated with increased morbidity and mortality 

(Pallotto and Kilbride 2006; Katz et al. 2013). The association between smoking-related reduction in birth weight 

and infant mortality has been studied in detail, as reviewed 

in the 2014 Surgeon General’s report (USDHHS 2014).

Table 4.33 presents studies published after the year 

2000 that addressed smoking cessation and SGA infants. 

Twenty-two studies were identified. Definitions for SGA 

included, by percentile of birth weight, less than the 

2.5th, 3rd, 5th, and 10th percentiles; they also included 

greater than 2 standard deviations (SD) below the mean. 

All of the studies but one (Grzeskowiak et  al. 2015) 

included adjustments for potential confounders; three 

also adjusted for alcohol consumption but not substance 

use (McCowan et al. 2009; Bakker et al. 2011; Tong et al. 

2017); and two addressed both alcohol consumption and 

substance use (Erickson and Arbour 2012; Murphy et al. 

2013). Two studies examined smoking status across two 

consecutive pregnancies (Okah et al. 2007; Kvalvik et al. 

2017), and 20 examined cessation with respect to single 

pregnancies. Of those 20  studies, 19  compared infants 

of women who quit smoking with those of nonsmokers 
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Mitchell et al. 

(2002)

•

•

•

•

•

Case-control

Term births without 

congenital anomalies

n = 1,714

1995–1997

New Zealand

•

•

•

•

•

•

•

Nonsmokers: Never smoked cigarettes 

regularly, or did not smoke during

12 months before pregnancy or 

during pregnancy

Quit smoking before pregnancy: Smoked 

during 12 months before pregnancy but 

not during pregnancy

Quit smoking during pregnancy

Continued smoking during pregnancy, 

increased amount

Continued smoking during pregnancy, 

decreased amount

Continued smoking during pregnancy, 

amount did not change

Smoking status based on self-reports 

obtained from a postpartum interview

<10th percentile for sex Unadjusted and adjusted ORs for SGA 

(95% CI):

•

•

Nonsmokers (reference)

Quit smoking before pregnancy:

–

–

Unadjusted: 0.83 (0.55–1.27)

Adjusted: 1.03 (0.64–1.64)

• Quit smoking during pregnancy:

–

–

Unadjusted: 1.13 (0.73–1.75)

Adjusted: 1.14 (0.68–1.91)

• Continued smoking during pregnancy, 

increased amount:

–

–

Unadjusted: 1.94 (1.02–3.67)

Adjusted: 2.07 (0.97–4.42)

• Continued smoking during pregnancy, 

decreased amount:

–

–

Unadjusted: 2.56 (1.86–3.52)

Adjusted: 3.23 (2.14–4.86)

• Continued smoking during pregnancy, 

amount did not change:

–

–

Unadjusted: 3.35 (1.98–5.66)

Adjusted: 4.88 (2.66–8.94)

Results adjusted for 

maternal education, 

occupation, marital status, 

ethnicity, parity, age, 

age at first pregnancy, 

height, pre-pregnancy 

weight, hypertension, 

and marijuana use

England et al. 

(2007)

• Randomized trial for 

preeclampsia prevention

• n = 4,289

• 1992–1995

• United States

• Nonsmokers: Never smoked regularly

• Quit before pregnancy: Quit before last 

menstrual period and validated with 

cotinine mid-pregnancy

• Quit during pregnancy: Quit after last 

menstrual period and validated with 

cotinine mid-pregnancy

• Quit before or during pregnancy: 

Quit groups from two previous 

categories combined

• Continued smoking: Smoking at 

study enrollment

• Smoking status based on selfreports obtained at study enrollment

(13–21 weeks’ gestation) in 2007 study

• Quit status validated with urine cotinine 

concentration obtained mid-pregnancy 

(mean: 28 weeks’ gestation)

≤10th percentile for 

race, sex, and parity

Unadjusted and adjusted OR (95% CI):

• Nonsmoker (reference)

• Quit before or during pregnancy:

– Unadjusted: 1.0 (0.7–1.4)

– Adjusted: 1.0 (0.7–1.5)

• Continued smoking:

– Unadjusted: 1.9 (1.5–2.4)

– Adjusted: 2.0 (1.6, 2.7)

Results adjusted for 

maternal BMI and 

study center

Did not account for 

alcohol or substance use

Table 4.33 Studies on smoking cessation and small for gestational age infants

The Health Benefits of Smoking Cessation 361
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Okah et al. 

(2007)

• Population-based 

retrospective cohort 

study using certificates 

of live births in Missouri

•

•

•

•

First and second 

singleton live births

n = 5,107

1994–2003

Missouri

•

•

•

•

•

Nonsmokers: Smoked during neither 

pregnancy 

Smoked during first but not during 

second pregnancy

Smoked during second but not 

during first pregnancy

Smoked during both pregnancies

Smoking history ascertained from vital 

statistics data and certificates of live 

births, which used one question on 

tobacco use during pregnancy (yes/no)

<10th percentile for 

gestational age 

Adjusted OR for SGA in second pregnancy 

(95% CI):

•

•

•

•

Nonsmoker (reference)

Smoked during first but not during second 

pregnancy: 1.31 (0.65–2.65)

Smoked during second but not during 

first pregnancy: 1.83 (1.19–2.82)

Smoked during both pregnancies: 

2.80 (2.00–3.93)

Results adjusted for 

maternal age, race, and 

medical risk for SGA

Did not account for 

alcohol or substance use

Pipkin (2008) • Prospective cohort

study of the genetics 

of preeclampsia

• Singleton pregnancies 

with moderate to 

severe preeclampsia

• n = 1,001

• Years: Not reported

• United Kingdom

• Nonsmoker: Never smoked

• Quit smoking: Quit before first antenatal 

visit but quit time not reported

• Continued smoking: Smoking at the 

time of antenatal booking

• Smoking status based on self-reports 

obtained at antenatal booking

<3rd percentile for 

gestational age

Percentage SGA and adjusted OR for SGA 

(95% CI):

• Nonsmoker: 27.9% (reference)

• Quit smoking: 37.5%

• Continued smoking: 46.1%; 2.20 (1.41–3.44)

Results adjusted for 

maternal parity and BMI 

and sex of the infant

McCowan

et al. (2009) 

•

•

•

•

Prospective cohort study

n = 2,504

2004–2007

New Zealand and 

Australia

•

•

•

•

Nonsmoker: Did not smoke during 

pregnancy

Quit smoking: Smoked during pregnancy 

but quit before being interviewed at

15 weeks’ gestation

Continued smoking: Smoking at 

15 weeks’ gestation

Smoking status based on self-reports 

ascertained at 15 weeks’ gestation

SGA birth weight 

<10th customized 

centile

Adjusted OR (95% CI):

•

•

•

Nonsmoker (reference)

Quit smoking: 1.06 (0.67–1.68)

Continued smoking: 1.76 (1.03–3.02)

Results adjusted for 

maternal age; ethnicity; 

marital status; employment 

status; BMI; bleeding 

during pregnancy; folic 

acid use; multivitamin use; 

alcohol use at 15 weeks’ 

gestation; and scores 

for depression, stress, 

or anxiety 

Did not account for 

substance use

Table 4.33 Continued

A Report of the Surgeon General

362 Chapter 4
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Polakowski

et al. (2009)

• Population-based

retrospective cohort 

using certificates 

live births

• Singleton pregnancies 

>28 weeks’ gestation

• n = 915,441

• 2005

• Multiple sites in the 

United States

• Nonsmoker: Did not smoke during any

trimester of pregnancy

• Quit smoking, first trimester: Smoked 

during first trimester but not during 

second and third trimesters

• Quit smoking, second trimester: Smoked 

during second trimester but not during 

third trimester

• Continued smoking: Smoked during all 

three trimesters

• Excluded women who did not fit any of 

the categories above

• Smoking history ascertained from vital 

statistics data and certificates of live births

Birth weight <10th

percentile weight for 

gestational age 

Adjusted OR for SGA (95% CI):

• Term (≥37 completed weeks):

– Continued smoking (reference)

– Nonsmokers: 0.41 (0.40–0.42)

– Quit smoking, first trimester:

0.45 (0.42–0.48)

– Quit smoking, second trimester:

0.59 (0.54–0.64)

• Preterm (28–36 completed weeks):

– Continued smoking (reference)

– Nonsmokers: 0.45 (0.42–0.47)

– Quit smoking, first trimester:

0.47 (0.40–0.55)

– Quit smoking, second trimester:

0.88 (0.72–1.08)

Results adjusted for

maternal age, race/

ethnicity, marital status,

education, late entry into 

prenatal care, and history 

of preterm delivery 

Did not account for 

alcohol or substance use

Vardavas 

et al. (2010)

•

•

•

•

•

Population-based, 

prospective cohort study 

Singleton pregnancies 

n = 1,400 

2007–2008 

Crete, Greece 

•

•

•

•

Nonsmoker: Did not smoke from 3 months 

before pregnancy through pregnancy

Quit smoking: Stopped smoking 

sometime between 3 months before 

pregnancy and 12 weeks’ gestation.

Continued smoking: Smoking at 12 weeks’ 

gestation

Smoking status based on self-reports 

obtained at enrollment and during

second and third trimesters

Birthweight <10th 

percentile for 

gestational age

Unadjusted OR for SGA (95% CI):

•

•

•

Nonsmoker (reference)

Quit smoking: 0.73 (0.34–1.59)

Continued smoker: 2.36 (1.42–3.93)

Adjusted OR for SGA (95% CI):

•

•

•

Nonsmoker (reference)

Quit smoking: 0.74 (0.34–1.62)

Continued smoker: 2.63 (1.55–4.49)

Results adjusted for 

origin, parity, maternal 

education, and age and 

sex of the infant

Did not account for 

alcohol or substance use

Bakker et al. 

(2011)

• Population-based, 

prospective cohort study

• n = 5389

• 2001–2005

• Netherlands

• Nonsmokers: Did not smoke during 

pregnancy

• Quit smoking, first trimester: Smoked 

only during first trimester

• Quit smoking, second trimester: Smoked 

during second trimester (combined with 

“continued smoking” for this analysis)

• Continued smoking: smoked during third 

trimester (combined with “quit smoking, 

second trimester” for this analysis)

• Smoking status based on self-reports 

obtained in each trimester of pregnancy

Birth weight <5th

percentile for 

gestational age

Adjusted OR for SGA (95% CI):

• Nonsmokers (reference)

• Quit smoking: 1.17 (0.73–1.88)

• Continued smoking 2.11 (1.55–2.88)

Results adjusted for 

maternal age, BMI, height, 

education, ethnicity, parity, 

alcohol consumption, 

caffeine intake, folic acid 

intake, maternal stress, 

gestational age at birth; 

and sex of the fetus 

Did not account for 

substance use

Table 4.33 Continued

The Health Benefits of Smoking Cessation 363
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Baba et al. 

(2012)

•

•

•

•

•

Population-based cohort 

study based on Swedish 

Medical Birth Register

Singleton pregnancies

n = 846,411

1999–2010

Sweden

•

•

•

•

•

•

Nonusers: Did not use snuff or smoke 

cigarettes before pregnancy or during 

early pregnancy (≤15 weeks’ gestation)

Quit smoking, early: Smoked before 

pregnancy but quit during early pregnancy

Continued smoking, early: Smoked 

before and during early pregnancy 

(based on first assessment of smoking 

status at ≤15 weeks’ gestation)

Quit smoking, late: Smoked during early 

pregnancy but not during late pregnancy 

(based on assessment of smoking status 

at ≤15 weeks’ gestation and 30–32 weeks’ 

gestation)

Continued smoking: Smoked during 

early and late pregnancy

Smoking status based on self-reports 

assessed at first antenatal visit (typically 

≤15 weeks’ gestation) and again in 

late pregnancy (typically 30–32 weeks’ 

gestation)

Birth weight >2 SD 

below the mean for 

gestational age using 

sex-specific growth 

curves

Unadjusted and adjusted OR for SGA 

(95% CI):

• Based on early assessment: 

–

–

Nonuser (reference)

Quit smoking, early:





Unadjusted: 1.17 (1.11–1.24)

Adjusted: 1.03 (0.98–1.09)

– Continued smoking, early:





Unadjusted: 2.69 (2.58–2.80)

Adjusted: 2.55 (2.43–2.67)

• Based on late assessment:

–

–

Nonuser (reference)

Quit smoking, late:





Unadjusted: 2.01 (1.83–2.21)

Adjusted: 1.82 (1.65–2.01)

– Continued smoking, late:





Unadjusted: 3.18 (3.01–3.36)

Adjusted: 3.21 (3.02–3.40)

Adjusted OR for preterm SGA and term SGA 

(95% CI):

•

•

Nonuser (reference)

Quit smoking, early:

–

–

Preterm SGA: 0.86 (0.76–0.98)

Term SGA: 1.07 (1.01–1.14)

• Continued smoking, early:

–

–

Preterm SGA: 1.85 (1.67–2.06)

Term SGA: 2.76 (2.62–2.91)

Results adjusted for 

maternal age, parity, 

education, early pregnancy 

BMI, cohabitation, height, 

pregestational diabetes, 

and essential hypertension

Did not account for 

alcohol or substance use

Bickerstaff 

et al. (2012)

• Retrospective cohort

• n = 30,524

• 1997–2006

• Australia

• Nonsmokers: Never smoked or quit

>12 months before booking

• Quit smoking: Smoked during 12 months 

before booking but quit before booking

• Continuing smokers: Currently smoking 

at booking

• Smoking status based on routinely 

collected clinical data

<10th and <3rd 

percentiles using 

customized centiles 

for Australian 

ethnicities

Adjusted OR for SGA (95% CI):

• 10th percentile:

– Continuing smokers vs. nonsmokers: 

2.26 (2.08–2.47)

– Quit smoking vs. continuing smokers: 

0.43 (0.33–0.57)

• 3rd percentile:

– Continuing smokers vs. nonsmokers: 

2.41 (2.14–2.73)

– Quit smoking vs. continuing smokers: 

0.46 (0.31–0.68)

Results adjusted for 

plurality, previous 

pregnancy complications, 

parity, and ethnicity

Did not account for 

alcohol or substance use

Table 4.33 Continued

A Report of the Surgeon General

364 Chapter 4
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Erickson 

and Arbour 

(2012)

•

•

•

•

•

Population-based, 

retrospective cohort 

study using the 

British Columbia 

Perinatal Registry

Singleton pregnancies

n = 233,891

2001–2006

British Columbia, 

Canada

•

•

•

Nonsmokers: Never smoked

Quit smoking: Not further defined, 

timing not specified

Continued smoking: Smoking at 

first prenatal visit, subgrouped by 

smoking intensity:

–

–

–

Light: 1–4 cigarettes/day

Moderate: 5–9 cigarettes/day

Heavy: ≥10 cigarettes/day

• Smoking history based on self-reports 

typically ascertained at the first prenatal 

visit (12–18 weeks’ gestation)

Birth weight <3rd and

<10th percentiles for 

gestational age

Adjusted OR for SGA (95% CI):

• 3rd percentile:

–

–

–

Nonsmokers (reference)

Quit smoking: 0.86 (0.72–1.03)

Continued smoking:







Light: 1.33 (1.11–1.60)

Moderate: 1.82 (1.51–2.20)

Heavy: 2.37 (2.06–2.72)

• 10th percentile:

–

–

–

Nonsmokers (reference)

Quit smoking: 0.84 (0.76–0.92)

Continued smoking:







Light: 1.24 (1.12–2.72)

Moderate: 1.74 (1.57–1.93)

Heavy: 2.14 (1.98–2.32)

Results adjusted for 

maternal age, parity, 

prenatal care visits, 

diabetes, hypertension, 

pre-pregnancy weight, 

presence of a partner, 

alcohol and drug use, 

and sex of the infant

Miyake et al. 

(2013)

• Retrospective 

cohort study

• n = 1,565

• 2007–2008

• Japan

• Nonsmoker: Did not smoke during 

pregnancy

• Quit smoking, first trimester: Smoked 

only during first trimester

• Quit smoking, second or third trimester: 

Smoked during the second or third 

trimester but not throughout pregnancy

• Continued smoking: Smoked throughout 

pregnancy

• Smoking status for each trimester of 

pregnancy based on self-reports obtained 

after delivery

Birth weight <10th 

percentile for 

gestational age

Adjusted OR for SGA (95% CI):

• Nonsmoker (reference)

• Quit smoking, first trimester:

– Overall: 0.53 (0.13–1.49)

– Male infants: 1.02 (0.16–3.81)

– Female infants: 0.24 (0.01–1.22)

• Quit smoking, second or third trimester:

– Overall: 1.93 (0.55–5.27)

– Male infants: 1.67 (0.08–11.08)

– Female infants: 2.14 (0.48–6.92)

• Continued smoking:

– Overall: 2.87 (1.11–6.56)

– Male infants: 4.21 (1.26–12.14)

– Female infants: 1.51 (0.23–5.96)

Results adjusted for region 

of residence; number of 

children; family structure; 

maternal age, education, 

employment, alcohol 

consumption, and BMI; 

gestational age at birth; 

and sex of the infant

Did not account for 

substance use

Table 4.33 Continued

The Health Benefits of Smoking Cessation 365
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Murphy et 

al. (2013)

•

•

•

•

•

Prospective cohort study

Singleton pregnancies

n = 1,216

2010–2011

Ireland

•

•

•

•

•

Nonsmoker: Not defined

Quit smoking: Smoked during 6 months 

before pregnancy but quit by first 

prenatal visit

Continued smoking: Smoked during 

6 months before pregnancy, at first

prenatal visit, and during third trimester

Smoking status based on self-reports 

obtained at enrollment and in third 

trimester

Birth weight <10th

percentile, corrected 

for maternal height 

and weight, parity, 

infant sex, ethnicity, 

and gestation

OR for SGA (95% CI):

•

•

Nonsmoker (reference)

Quit smoking:

–

–

Unadjusted: 0.81 (0.46–1.40)

Adjusted: 1.05 (0.58–1.89)

• Continued smoking:

–

–

Unadjusted: 2.09 (1.27–3.44),

Adjusted: 1.39 (1.06–1.84)

Birth weight adjusted for

maternal age, nationality, 

unplanned pregnancy, 

private healthcare, alcohol 

use, and illicit drug use

Rode et al. 

(2013)

• Prospective cohort study

• Singleton, term 

pregnancies

• n = 1,774

• 1996–1999

• Denmark

• Nonsmokers: Not defined

• Quit smoking: Quit immediately before 

or during pregnancy

• Continued smoking: Not defined.

• Smoking status based on self-reports 

assessed at 12–18 weeks’ and 37 weeks’ 

gestation and 1 year postpartum

• Salivary cotinine obtained in a subgroup 

at 16 and 37 weeks’ gestation

Birth weight <10th 

percentile for 

gestational age

OR for SGA (95% CI):

• Nonsmokers (reference)

• Quit smoking:

– Unadjusted: 1.1 (0.7–1.7)

– Adjusted: 1.0 (0.6–1.6)

• Continued smoking:

– Unadjusted: 3.5 (2.4–4.9)

– Adjusted: 3.6 (2.5–5.2)

Birth weight adjusted 

for pre-pregnancy BMI, 

preeclampsia, and parity

Salivary cotinine for 

subgroup reported but 

not integrated into 

main analysis

Did not account for 

alcohol or substance use

Meghea et al. 

(2014) 

•

•

•

•

Prospective cohort study

n = 474

2008–2009

Romania

•

•

•

•

Nonsmokers: Not smoking when learned 

they were pregnant

Quit smoking: Quit upon learning of 

pregnancy

Continued smoking: Smoking at time 

of study interview (gestational age 

not reported)

Smoking history based on self-reports 

obtained at study enrollment (gestational 

age not reported)

Birth weight <10th 

percentile for 

gestational age

Adjusted OR for SGA (95% CI):

•

•

•

Nonsmokers (reference)

Quit smoking: 2.16 (1.05–4.43)

Continued smoking: 1.79 (0.74–4.32)

Results adjusted for 

stress, depressive 

symptoms, maternal age

>35 years old, education, 

rural residence, marital 

status, and nulliparity

Did not account for 

alcohol or substance use 

Table 4.33 Continued

A Report of the Surgeon General

366 Chapter 4
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Räisänen 

et al. (2014)

• Population-based 

study based on Finnish 

Medical Birth Register

• Singleton pregnancies, 

live or stillborn after

22 weeks’ gestation 

• n = 1,164,953

• 1991–2010

• Finland

• Nonsmokers:Not further defined 

• Quit smoking: Quit smoking during

first trimester 

• Continued smoking: Smoked after 

first trimester

• Smoking history ascertained from the

Finnish Medical Birth Register 

Birth weight >2 SD 

below sex- and parityspecific means for 

gestational age

OR for SGA (95% CI):

• Nonsmokers (reference)

• Quit smoking:

– Unadjusted 1.33 (1.26–1.41)

– Adjusted: 1.16 (1.09–1.23)

• Continued smoking:

– Unadjusted: 2.38 (2.33–2.44)

– Adjusted: 2.47 (2.41–2.53)

Results adjusted for 

maternal age, parity, 

socioeconomic status, 

and sex of the infant

Did not account for 

alcohol or substance use

Suzuki et al. 

(2014)

•

•

•

•

•

Prospective cohort study

Singleton pregnancies

n = 2,663

1991–2006

Japan

•

•

•

•

•

moker: Never smoked

Quit smoking before pregnancy: 

Not further defined

Quit smoking, first trimester

Continued smoking: Smoked after first 

trimester

Smoking history based on self-reports 

obtained in early pregnancy (usually 

first trimester)

Birth weight <10th 

percentile using sexspecific growth curves 

for infants in Japan

Adjusted OR for SGA (95% CI):

• Boys:

–

–

–

–

Nonsmokers (reference)

Quit smoking before pregnancy: 

1.2 (0.5–3.2)

Quit smoking, first trimester: 

1.0 (0.5–2.1)

Continued smoking: 3.2 (1.7–6.2)

• Girls:

–

–

–

–

Nonsmokers (reference)

Quit smoking before pregnancy: 

0.5 (0.1–1.5)

Quit smoking, first trimester: 

1.1 (0.6–2.0)

Continued smoking: 2.5 (1.3–5.2)

Results adjusted for 

maternal age and BMI

Did not account for 

alcohol or substance use

Blatt et al. 

(2015)

• Population-based 

retrospective cohort 

study using certificates 

of live births in Ohio

• n = 927,424

• 2006–2012

• Ohio

• Nonsmoker: Did not smoke during 

3 months before pregnancy or during 

pregnancy

•

•

Quit before pregnancy: Smoked during 

3 months before pregnancy but not 

during pregnancy 

Quit first trimester: Smoked only during

first trimester

• Quit second trimester: Smoked during 

first and second trimesters but not third 

trimester

• Continued smoking: Smoked throughout 

pregnancy

• Smoking history ascertained from vital 

statistics data and certificates of live births

Birthweight <10th and 

<5th percentiles for 

gestational age

Adjusted OR for SGA (95% CI):

• <10th percentile:

– Nonsmoker (reference)

– Quit first trimester: 1.19 (1.13–1.24)

– Quit second trimester: 1.67 (1.57–1.78)

– Continued smoking: 2.26 (2.22–2.31)

• <5th percentile:

– Nonsmoker (reference)

– Quit first trimester: 1.25 (1.17–1.33)

– Quit second trimester: 1.83 (1.68–1.99)

– Continued smoking: 2.44 (2.37–2.51)

Results adjusted for 

maternal age, race, 

education, marital status, 

hypertension, diabetes, 

and BMI

Did not account for 

alcohol or substance use

Table 4.33 Continued

The Health Benefits of Smoking Cessation 367
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Grzeskowiak 

et al. (2015)

•

•

•

•

Retrospective 

cohort study

n = 7,658

2000–2005

South Australia

•

•

•

•

•

Nonsmokers

Quit smoking

Continued smoking

Smoking status not further defined

Smoking history based on self-reports 

ascertained at antenatal booking

Birth weight <10th 

percentile for 

gestational age by 

sex of the infant and 

maternal height and 

parity

Percentage SGA:

•

•

•

Nonsmokers: 7.1% (reference) 

Quit smoking: 8.1%, p = 0.81

Continued smoking: 15.3%, p <0.001

Results not adjusted for 

potential confounders

Did not account for 

alcohol or substance use

Kvalvik et al. 

(2017)

• Population-based 

retrospective cohort 

study using the Medical 

Birth Registry of Norway

• First and second births

• n = 118,355

• 1999–2014

• Norway

• Nonsmoker: Did not smoke at the end of

either pregnancy

• Daily smoker/quit smoking: Smoked daily 

at end of first pregnancy but not smoking

at end of second pregnancy

• Nonsmoker/daily smoker: Not smoking 

at end of first pregnancy but smoked 

daily at end of second pregnancy

• Daily smoker/daily smoker: Smoked daily 

at end of both pregnancies

• Did not describe how smoking status 

was ascertained

Birth weight <10th and

<2.5th percentile for 

gestational age by sex

RR for SGA at second pregnancy (95% CI):

• <10th percentile:

– Nonsmoker (reference)

– Daily smoker/quit smoking:

 Unadjusted: 1.5 (1.3–1.6)

 Adjusted: 1.5 (1.3–1.7)

– Nonsmoker/daily smoker:

 Unadjusted: 2.1 (1.8–2.5)

 Adjusted: 2.1 (1.8–2.5)

– Daily smoker/daily smoker:

 Unadjusted: 2.9 (2.7–3.1)

 Adjusted: 2.9 (2.7–3.1)

• < 2.5th percentile:

– Nonsmoker (reference)

– Daily smoker/quit smoking:

 Unadjusted: 1.5 (1.1–2.0)

 Adjusted: 1.5 (1.1–2.0)

– Nonsmoker/daily smoker:

 Unadjusted: 3.2 (2.4–4.3)

 Adjusted: 3.1 (2.3–4.2)

– Daily smoker/daily smoker:

 Unadjusted: 4.0 (3.4–4.7)

 Adjusted: 3.9 (3.3–4.6)

Results adjusted for 

maternal age, marital 

status, and year of 

first birth

Did not account for 

alcohol or substance use

Table 4.33 Continued

A Report of the Surgeon General

368 Chapter 4
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Tong et al. 

(2017)

• Population-based 

retrospective 

cohort study

• n = 88,933 

• 2009–2011 

• United States 

•

•

•

•

•

•

•

•

Nonsmoker: Did not smoke during

3 months before pregnancy or during 

last 3 months of pregnancy

Quit smoking: Smoked during 3 months 

before pregnancy but not during last

3 months of pregnancy

Continued smoking, nondaily: Smoked 

during 3 months before pregnancy and

<1 cigarette/day during last 3 months 

of pregnancy

Continued smoking, daily: Smoked 

during 3 months before pregnancy and 

smoked ≥1 cigarette/day during last

3 months of pregnancy

Smoking status based on survey 

administered postpartum

≤10th percentile birth 

weight for gestational 

age by sex and race

Prevalence ratio for SGA (95% CI):

•

•

Nonsmoker (reference)

Quit smoking:

–

–

Unadjusted: 1.0 (0.9–1.1)

Adjusted: 0.9 (0.9–1.0)

• Continued smoking:

– Nondaily:





Unadjusted: 1.6 (1.3–1.9)

Adjusted: 1.4 (1.1–1.8)

– Daily:





Unadjusted: 2.2 (2.0–2.4)

Adjusted: 2.0 (1.9–2.2)

Results adjusted for 

maternal age, parity, 

education, marital 

status, BMI, trimester 

of entry into prenatal 

care, and alcohol use 

during pregnancy

Did not account for 

substance use

Table 4.33 Continued

The Health Benefits of Smoking Cessation 369

Notes: BMI = body mass index; CI = confidence interval; OR = odds ratio; RR = risk ratio; SD = standard deviation; SGA = small for gestational age.
A Report of the Surgeon General

370 Chapter 4

(Mitchell et  al. 2002; England et  al. 2007; Pipkin 2008; 

Andersen et  al. 2009; McCowan et  al. 2009; Polakowski 

et al. 2009; Vardavas et al. 2010; Bakker et al. 2011; Baba 

et al. 2012; Erickson and Arbour 2012; Miyake et al. 2013; 

Murphy et al. 2013; Rode et al. 2013; Meghea et al. 2014; 

Räisänen et al. 2014; Suzuki et al. 2014; Blatt et al. 2015; 

Grzeskowiak et  al. 2015; Tong et  al. 2017), and 1  study 

compared them with the infants of continuing smokers 

(Bickerstaff et al. 2012). In general, these 20 studies found 

that women who continued to smoke past early pregnancy 

had an elevated risk of SGA delivery and that cessation 

attenuated or eliminated this excess risk. 

Seven of the 20  studies examined a combinedexposure variable of cessation before pregnancy with cessation during early pregnancy, and thus could not isolate 

the effects of cessation by timeframe (before and after 

conception) (England et  al. 2007; Andersen et  al. 2009; 

Vardavas et al. 2010; Bickerstaff et al. 2012; Murphy et al. 

2013; Rode et al. 2013; Tong et al. 2017). Six of these seven 

studies found no difference in SGA risk in quitters compared with nonsmokers (England et  al. 2007; Andersen 

et al. 2009; Vardavas et al. 2010; Murphy et al. 2013; Rode 

et al. 2013; Tong et al. 2017), while one (Bickerstaff et al. 

2012) found a significant decrease in risk among quitters 

compared with continuing smokers (aOR = 0.43; 95% CI, 

0.33–0.57). In 2 of the 20 studies, the timing of cessation 

with respect to conception was not described (Pipkin 2008; 

Erickson and Arbour 2012). Pipkin and colleagues (2008) 

did not perform any testing for statistical significance; and 

Erickson and Arbour (2012) found no increased risk of SGA 

among infants of quitters. Six of the 20 studies included 

assessment of smoking status in late pregnancy (typically 

in the third trimester) (Mitchell et al. 2002; Bakker et al. 

2011; Baba et al. 2012; Rode et al. 2013; Blatt et al. 2015; 

Tong et al. 2017), thus reducing any potential contribution of unidentified relapse. Of these studies, five found no 

significant increase in risk of SGA infants among quitters 

whose status was verified in late pregnancy, and one (Baba 

et al. 2013) found an increased risk for late, but not early, 

quitters. One of the six studies assessed timing by trimester 

(Blatt et al. 2015) and found significant increases in risk 

in both early quitters (smoked in first trimester only) and 

later quitters (smoked in first and second trimesters only) 

(aOR = 1.19; 95% CI, 1.13–1.24, and 1.67; 95% CI, 1.57–

1.78, respectively) when compared with nonsmokers. One 

study included biochemical validation of smoking cessation (Rode et al. 2013) and combined preconception and 

early-pregnancy quitters. The study found no increase for 

SGA risk in quitters when compared with nonsmokers. 

Of the two studies that examined smoking cessation 

across consecutive pregnancies, one found no increased 

risk of SGA in babies of women who quit by the second 

pregnancy compared with women who did not smoke in 

either pregnancy (Okah et al. 2007), and the other found 

a significant increase for SGA in quitters compared with 

women who did not smoke during either pregnancy 

(Kvalvik et al. 2017). However, the basis for the different 

findings is not clear. Both studies were population based, 

used an SGA definition of less than 10th percentile, and 

relied on self-reported smoking status, and both adjusted 

for several potential confounders (for maternal age, race, 

and medical risk factors for SGA, and for maternal age, 

marital status, and year of first birth, respectively). The 

two studies were conducted in different countries (United 

States and Norway, respectively), however, and although 

Okah and colleagues (2007) categorized smoking status as 

positive or negative for each pregnancy, Kvalvick and colleagues (2017) specifically assessed smoking status at the 

end of each pregnancy. 

Summary of the Evidence. Since the 2004 Surgeon 

General’s report confirmed that smoking cessation eliminates much of the reduction in birth weight caused by 

maternal smoking (USDHHS 2004), numerous studies 

have assessed the relationships between smoking and 

smoking cessation and SGA, and most have adjusted for 

multiple confounders. The evidence is sufficient to infer 

that smoking cessation before or during early pregnancy 

reduces the risk of SGA birth compared with continued 

smoking. The evidence is suggestive but not sufficient to 

infer that the risk of an SGA birth in women who quit 

smoking before or during early pregnancy does not differ 

from that for nonsmokers. The evidence is inadequate 

to determine the gestational age before which smoking 

cessation should occur to eliminate the effects of smoking 

on risk of SGA. 

Preterm Delivery

Delivery before 37  completed weeks’ gestation 

is a leading cause of neonatal morbidity and mortality 

(March of Dimes et al. 2012; Menon 2012; Blencowe et al. 

2013; Katz et al. 2013), and this problem affects approximately 15 million births per year globally (World Health 

Organization 2017) and nearly 10% of births in the United 

States (Martin et al. 2017). Preterm delivery can be medically indicated (about two-thirds of all preterm deliveries) 

or spontaneous (about one-third of preterm deliveries). 

Spontaneous preterm delivery encompasses preterm 

labor, premature rupture of membranes, and spontaneous 

fetal loss. Medically indicated preterm delivery can be 

the outcome of numerous maternal and fetal conditions, 

including maternal chronic diseases, such as hypertension or diabetes, and pregnancy complications, such as 

preeclampsia, GDM, or abnormal placentation (Purisch 

and Gyamfi-Bannerman 2017). Numerous risk factors 

for spontaneous preterm delivery have been identified, 

including prior spontaneous preterm delivery, intrauterine 
The Health Benefits of Smoking Cessation 371

Smoking Cessation

infections, shortened cervix, multifetal pregnancy, fetal 

abnormalities, uterine anomalies, Black race, interpregnancy interval less than 18  months, low socioeconomic 

status, low gestational weight gain, poor nutrition status, 

and advanced maternal age (Conde-Agudelo et  al. 2006; 

USDHHS 2010; Purisch and Gyamfi-Bannerman 2017). 

The 1990 Surgeon General’s report identified a 

reduced risk of preterm delivery among women who 

quit smoking before or during pregnancy relative to continuing smokers, but the report found insufficient evidence to draw conclusions about the effects of smoking 

cessation on both preterm delivery and gestational duration (USDHHS 1990). The 2004 Surgeon General’s report 

found a causal relationship between maternal smoking 

and preterm delivery (gestational age <37  weeks) and 

shorter gestational duration (number of days or weeks of 

pregnancy) (USDHHS 2004). The 2010 Surgeon General’s 

report reviewed mechanisms hypothesized to explain 

the increased risk of preterm delivery among smokers, 

including increased risk of genitourinary tract infections, 

alterations in vaginal flora and localized immunosuppression, alterations in cervical cytokine profiles, reductions in maternal zinc levels, dysregulation of the fetal 

immune system, and alterations in myometrial contractility (USDHHS 2010). 

Twenty-five studies published in 2000 or later that 

examined smoking cessation and preterm delivery were 

identified (Table  4.34). Two studies (Abrevaya 2008; 

Mohsin and Jalaludin 2008) examined cessation across two 

consecutive pregnancies, and 23  examined cessation in 

single pregnancies (Hrubá and Kachlik 2000; Vogazianos 

et al. 2005; McCowan et al. 2009; Polakowski et al. 2009; 

Anderka et  al. 2010; Vardavas et  al. 2010; Bakker et  al. 

2011; Baba et  al. 2012; Bickerstaff et  al. 2012; Erickson 

and Arbour 2012; Batech et al. 2013; Miyake et al. 2013; 

Murphy et  al. 2013; Meghea et  al. 2014; Räisänen et  al. 

2014; Bailey 2015; Smith et al. 2015; Yan and Groothuis 

2015; Dahlin et al. 2016; Moore et al. 2016; Suzuki et al. 

2016; Tong et al. 2017; Wallace et al. 2017). All but three 

studies (Hrubá and Kachlik 2000; Vogazianos et al. 2005; 

Suzuki et  al. 2016) adjusted for at least some potential 

confounders, and five addressed alcohol consumption 

(McCowan et  al. 2009; Bakker et  al. 2011; Miyake et  al. 

2013; Yan and Groothuis 2015; Tong et  al. 2017), while 

three addressed both alcohol and substance use (Erickson 

and Arbour 2012; Bailey 2015; Smith et al. 2015). 

Of the 23 studies examining individual pregnancies, 

8  classified exposure combining cessation before pregnancy with cessation during early pregnancy and, thus, 

could not estimate the effect of cessation after conception 

(Hrubá and Kachlik 2000; Anderka et al. 2010; Vardavas 

et al. 2010; Baba et al. 2012; Bickerstaff et al. 2012; Murphy 

et al. 2013; Dahlin et al. 2016; Tong et al. 2017). Of these 

eight studies, five compared quitters with nonsmokers and 

found no statistically significant difference in risk between 

the two groups (Vardavas et  al. 2010; Baba et  al. 2012; 

Murphy et al. 2013; Dahlin et al. 2016; Tong et al. 2017). 

Bickerstaff and colleagues (2012) compared quitters with 

continuing smokers and found no difference in risk. Six 

of the 23 studies examined cessation before conception; 

4 compared quitters with nonsmokers (Vogazianos et al. 

2005; Smith et al. 2015; Yan and Groothuis 2015; Moore 

et al. 2016). Three of the four found no significant differences in preterm deliveries (Vogazianos et al. 2005; Smith 

et  al. 2015; Yan and Groothuis 2015), and one found a 

slightly reduced risk in quitters (Moore et al. 2016). One 

study compared women who quit before pregnancy with 

continuing smokers and found a significantly reduced risk 

of preterm delivery (Batech et  al. 2013); and one study 

reported percentages of preterm infants for nonsmokers 

and women who quit before pregnancy (5.0% and 5.8%, 

respectively), as well as for other cessation groups, but 

adjustment for confounding was not performed, and only 

an overall chi-square test result was reported (Suzuki 

et al. 2016).

Twelve of the 23 studies examined cessation during 

pregnancy (McCowan et al. 2009; Polakowski et al. 2009; 

Bakker et al. 2011; Miyake et al. 2013; Meghea et al. 2014; 

Räisänen et al. 2014; Bailey 2015; Smith et al. 2015; Yan 

and Groothuis 2015; Moore et al. 2016; Suzuki et al. 2016; 

Wallace et al. 2017); of those, 7 found no statistically significant increase in the risk of preterm delivery in quitters 

compared with nonsmokers (McCowan et al. 2009; Bakker 

et al. 2011; Miyake et al. 2013; Meghea et al. 2014; Räisänen 

et al. 2014; Smith et al. 2015; Yan and Groothuis 2015). 

Moore and colleagues (2016) and Wallace and colleagues 

(2017) used data from state certificates of live birth in 

Ohio, and both found an increased risk of preterm delivery 

in those who quit late in pregnancy, but not in those who 

quit early in the pregnancy compared with nonsmokers. 

Using a large sample of more than 900,000 births, Moore 

and colleagues (2016) found an increase in risk among 

second-trimester quitters (aOR  =  1.70; 95%  CI, 1.60–

1.80) but not in earlier quitters (first trimester) compared 

with those who were nonsmokers. Wallace and colleagues 

(2017) found an increased risk in third-trimester quitters 

(aOR = 1.81; 95% CI, 1.48–2.21) but not in second- or firsttrimester quitters compared with nonsmokers. One study 

found a significant difference across smoking categories 

overall, but women who quit during pregnancy were not 

compared directly with other groups (Suzuki et al. 2016). 

In another study using a large sample of 900,000 births, 

significant reductions in the risk of preterm delivery were 

found among first- and second-trimester quitters compared with continuing smokers (aOR  =  0.69; 95%  CI, 

0.65–0.74 and aOR = 0.87; 95% CI, 0.79–0.96, respectively) 
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Hrubá and

Kachlik 

(2000)

•

•

•

•

•

Retrospective, clinicbased study

Term, singleton 

deliveries

n = 1,147

Years of data collection 

not reported

Czech Republic

•

•

•

•

•

Nonsmoker: Never smoked

Quit smoking: Smoked but quit before

pregnancy or during first trimester

Continued smoking: Smoked throughout 

pregnancy either daily or occasionally

Smoking status based on self-reports 

from interviews conducted shortly 

after delivery

Findings stratified by exposure to 

environmental tobacco smoke

≤36 weeks’ gestation Percentage preterm delivery:

•

•

Continued smoking: 10.0%

No exposure to environmental tobacco smoke:

–

–

–

Nonsmoker: 6.5%

Quit smoking: 6.3%

Continued smoking: 10.0%

• Exposure to environmental tobacco smoke:

–

–

Nonsmoker: 9.4%

Quit smoking: 4.8%

Results not adjusted for

potential confounders

No statistical testing 

reported

Did not account for 

alcohol or substance use

Vogazianos 

et al. (2005)

• Population-based, 

retrospective cohort 

study

• n = 59,014

• 1990–1996

• Cyprus

• Nonsmokers: Did not smoke before or 

during pregnancy

• Quit smoking: Smoked before but not 

during pregnancy

• Continued smoking: Smoked before 

and during pregnancy

• Not clear how many women quit 

smoking during pregnancy and how 

they were categorized

• Smoking status based on maternal 

self-reports obtained during 

physician interviews

<38 weeks’ gestation OR for preterm delivery (95% CI):

• Nonsmokers (reference)

• Quit smoking: 1.02 (0.73–1.43)

• Continued smoking: 2.58 (2.05–3.25)

Results not adjusted for 

potential confounders

Did not account for 

alcohol or substance use

Abrevaya 

et al. (2008)

•

•

•

•

•

•

Population-based, 

retrospective cohort 

study using linked 

certificates of live 

births in Michigan

First and second 

pregnancies in which 

women smoked during 

the first pregnancy

n = 14,731

n = 8,044

1989–2004

Michigan

•

•

•

Quit smoking between pregnancies: 

Smoked during first pregnancy but not 

during second pregnancy

Continued smoking: Smoked during first 

and second pregnancies

Smoking status based on smoking history 

collected from certificates of live births, 

which used one question on tobacco use 

during pregnancy (yes/no)

<37 weeks’ gestation Adjusted OR for preterm delivery (95% CI):

•

•

Quit smoking between pregnancies (reference)

Continued smoking:

–

–

18–24 years of age: 1.04 (0.89–1.22)

25–30 years of age: 1.12 (0.89–1.40)

Results adjusted for 

maternal race, education, 

income, population, 

interpregnancy interval, 

and year of birth; trimester

of first prenatal visit; 

number of prenatal visits; 

presence of father’s name 

on birth certificate; 

and first-birth value 

of the outcome

Did not account for 

alcohol or substance use

Table 4.34 Studies on smoking cessation and preterm delivery

A Report of the Surgeon General

372 Chapter 4
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Mohsin and 

Jalaludin 

(2008)

• Population-based 

retrospective 

cohort study

• Consecutive 

singleton births

• n = 244,480

• 1994–2004

• Australia

• Nonsmoker: Did not smoke during 

either pregnancy

• Quit smoking between pregnancies:

• Smoked during first pregnancy but not 

during second pregnancy

• Resumed smoking between pregnancies:

• Smoked during second pregnancy but 

not during first pregnancy

• Continued smoking: Smoked during 

first and second pregnancies 

• Smoking status based on self-reports

<37 weeks’ gestation Adjusted OR for preterm delivery at second 

pregnancy (95% CI):

• Nonsmoker (reference)

• Quit smoking between pregnancies:

1.41 (1.29–1.55)

• Resumed smoking between pregnancies:

1.43 (1.37–1.60)

• Continued smoking: 1.89 (1.8–1.99)

Results adjusted for 

interpregnancy interval 

and other factors not 

explicitly

McCowan 

et al. (2009)

•

•

•

•

•

Prospective cohort 

study designed to 

develop screening

tests for pregnancy 

complications

2004–2007

n = 2,504

New Zealand

and Australia

•

•

•

•

Nonsmokers (did not smoke during 

pregnancy)

Quit smoking: Smoked during pregnancy 

but quit before the study interview

(~15 weeks’ gestation)

Continued smoking: Smoking at time of 

study interview (~15 weeks’ gestation)

Smoking status based on self-reports 

ascertained at 15 weeks’ gestation

Spontaneous preterm 

labor or preterm, 

premature rupture of 

membranes resulting 

in a preterm delivery at 

<37 weeks’ gestation

Adjusted OR for spontaneous preterm 

delivery (95% CI):

•

•

•

Nonsmokers (reference)

Quit smoking: 1.03 (0.49–2.18)

Continued smoking: 3.21 (1.42–7.23)

Results adjusted for 

demographic factors 

(maternal age, ethnicity, 

marital status, employment 

status, and BMI) and clinical 

risk factors (bleeding during 

pregnancy; folic acid use; 

multivitamin use; alcohol 

use at 15 weeks’ gestation; 

and scores for depression, 

stress, or anxiety) 

Did not account for 

substance use 

Polakowski 

et al. (2009)

• Population-based 

retrospective 

cohort study 

• Singleton deliveries, 

≥28 weeks’ gestation

• n = 915,441 

• 2005 

•United States (11 states) 

Preterm delivery 

28–≤37 weeks’ 

gestation based on 

last menstrual period, 

unless implausible 

(then based on 

clinical estimate)

Adjusted OR for preterm delivery (95% CI):

• Preterm, non-SGA:

– Continued smoking (reference)

– Nonsmokers: 0.72 (0.70–0.74)

– Quit first trimester: 0.69 (0.65–0.74)

– Quit second trimester 0.87 (0.79–0.96)

• Preterm, SGA:

– Continued smoking (reference)

– Nonsmokers: 0.45 (0.42–0.47)

– Quit first trimester: 0.47 (0.40–0.55)

– Quit second trimester: 0.88 (0.72–1.08)

Results adjusted for 

maternal age, race/

ethnicity, marital status, 

education, late entry into 

prenatal care, and history 

of preterm delivery 

Did not account for 

alcohol or substance use

• Nonsmoker: Smoked zero cigarettes in 

alltrimesters of pregnancy 

• Quit first trimester: Smoked during first 

trimester but not during second and 

third trimesters 

• Quit second trimester: Smoked during 

second trimester but not during third 

trimester 

• Continued smoking: Smoked during all 

three trimesters 

• Excluded women who did not fit in any 

of these categories 

• Smoking status based on certificates of 

live births 

Table 4.34 Continued

The Health Benefits of Smoking Cessation 373
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Anderka et al. 

(2010)

•

•

•

•

Population-based, casecontrol study

n = 4,667

1997–2003

United States

•

•

•

•

•

•

Nonsmoker: Did not smoke during

3 months before conception or during 

any trimester of pregnancy

Quit smoking: Smoked preconception 

but not during any trimester of 

pregnancy, smoked in first trimester 

but not in second or third trimesters, 

or smoked in second trimester but not 

in third trimester

Continued smoking: Smoked during 

all three trimesters

Smoking status based on maternal

self-reports obtained during interviews 

conducted 6 weeks–24 months 

postpartum

<37 weeks’ gestation Percentage and adjusted OR for preterm 

delivery (95% CI):

•

•

•

Nonsmoker 7.6% (reference)

Quit smoking: 8.0%, adjusted OR not reported

Continued smoking: 11.5%, 1.59 (1.13–2.25)

Results adjusted for 

maternal age, race/

ethnicity, education, 

and birthplace

Did not account for 

alcohol or substance use

Vardavas 

et al. (2010)

• Population-based, 

prospective cohort study

• Singleton pregnancies

• 2007–2008

• n = 1,400

• Greece

• Nonsmokers: Did not smoke during 

3 months before pregnancy

• Quit smoking: Smoked within 3 months 

before pregnancy and/or during

the first 12 weeks of pregnancy but 

(quit by the time of study interview 

~12 weeks’ gestation)

• Continued smoking: Smoked during 

3 months before pregnancy, during 

first 12 weeks of pregnancy, and

• at the time of the study interview 

(~12 weeks’ gestation)

• Smoking status based on selfreports ascertained at approximately 

12 weeks’ gestation

<37 weeks’ gestation OR for preterm delivery (95% CI):

• Nonsmokers (reference)

• Quit smoking:

– Unadjusted: 0.86 (0.54–1.38)

– Adjusted: 0.90 (0.56–1.46)

• Continued smoking:

– Unadjusted: 1.22 (0.82–1.83)

– Adjusted: 1.28 (0.84–1.94)

Results adjusted for 

origin, parity, maternal 

education and age, and 

sex of the infant

Did not account for 

alcohol or substance use

Table 4.34 Continued

A Report of the Surgeon General

374 Chapter 4
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Bakker et al. 

(2011)

•

•

•

•

Population-based 

cohort study

2001–2005

n = 5,389

Netherlands

•

•

•

•

•

Nonsmokers: Did not smoke during 

pregnancy

Quit smoking, first trimester: Smoked 

only during first trimester (combined 

with “quit smoking, second and third 

trimesters” for analysis)

Quit smoking, second trimester: Smoked 

during second trimester (combined with 

“quit smoking, first and third trimesters” 

for analysis)

Continued smoking: Smoked during third 

trimester (combined with “quit smoking, 

first and second trimesters” for analysis)

Smoking status based on self-reports 

obtained during each trimester

<37 weeks’ gestation Adjusted OR for preterm delivery (95% CI):

•

•

•

Nonsmoker (reference)

Quit smoking, first trimester: 0.66 (0.37−1.17)

Continued smoking: 1.25 (0.88–1.78)

Results adjusted for 

maternal age, BMI, 

height, education, 

ethnicity, parity, alcohol 

consumption, caffeine 

intake, folic acid intake, 

and stress; gestational 

age at birth; and sex of 

the fetus

Did not account for 

substance use

Table 4.34 Continued

The Health Benefits of Smoking Cessation 375
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Baba et al. 

(2012)

• Population-based 

retrospective cohort 

study using the Swedish 

Medical Birth Register

• n = 776,836

• 1999–2009

• Sweden

• Nonsmoker: Did not smoke during 

3 months before pregnancy or before 

registration for antenatal care

• Quit smoking: Smoked during 3 months 

before pregnancy but quit by registration 

for antenatal care

• Continued smoking: Smoking at 

registration for antenatal care

• Smoking status based on self-reports 

assessed at first antenatal visit (typically 

≤15 weeks’ gestation)

• Overall preterm 

delivery: <37 weeks’ 

gestation

• Very preterm 

delivery: <32 weeks’ 

gestation

• Moderate preterm 

delivery: 32–36 

weeks’ gestation

• Spontaneous 

preterm delivery: 

Spontaneous onset 

oflabor and preterm 

premature rupture

• Induced preterm 

delivery: Vaginally 

induced onset of

labor and cesarean 

delivery before the 

onset of labor

OR for preterm delivery (95% CI): 

• Nonsmoker (reference)

• Quit smoking:

– Unadjusted:

 <37 weeks: 1.02 (0.99–1.06)

 <32 weeks: 1.04 (0.94–1.15)

 32–36 weeks: 1.02 (0.98–1.06)

– Adjusted:

 <37 weeks: 0.90 (0.87–0.94)

 <32 weeks: 0.91 (0.82–1.01)

 32–36 weeks: 0.90 (0.86–0.94)

– Spontaneous preterm delivery: 0.92 

(0.88–0.96)

– Induced preterm delivery: 0.86 (0.79–0.92)

• Continued smoking:

– Unadjusted:

 <37 weeks: 1.43 (1.38–1.48)

 <32 weeks: 1.84 (1.69–2.00)

 32–36 weeks: 1.37 (1.32–1.41)

– Adjusted:

 <37 weeks: 1.30 (1.25–1.36)

 <32 weeks: 1.68 (1.52–1.84)

 32–36 weeks: 1.25 (1.20–1.30)

– Spontaneous preterm delivery: 1.32 

(1.26–1.38)

– Induced preterm delivery: 1.20 (1.12–1.29)

Results adjusted for BMI in 

early pregnancy, maternal 

age, parity, education, 

and cohabitation 

Did not account for 

alcohol or substance use

Bickerstaff 

et al. (2012)

•

•

•

•

Retrospective 

cohort study

1997–2006

n = 30,524

Australia

•

•

•

•

•

Nonsmoker: Never smoked or quit

>12 months before booking

Quit smoking: Smoked during 12 months 

before booking but quit before booking

Continued smoking: Currently smoking 

at booking

Smoking status based on routinely 

collected clinical data

<37 weeks’ gestation Percentage with preterm delivery:

•

•

•

Nonsmoker: 9.7%

Quit smoking: 12.7%

Continued smoking: 12.9%

Adjusted OR for preterm delivery (95% CI):

•

•

Continued smoking vs. nonsmoker: 

1.42 (1.28–1.59)

Quit smoking vs. continued smoking: 

0.92 (0.69–1.23)

Results adjusted for 

plurality, previous 

pregnancy complications, 

parity, and ethnicity

Did not account for 

alcohol or substance use

Table 4.34 Continued

A Report of the Surgeon General

376 Chapter 4
 

 

 

 

Study Design/population Exposure groups/how determined Outcome definition Findings Comments 

Yan and 

Groothuis 

(2015) 

• Population-based 

cohort study 

• Singleton pregnancies 

• Excluded women with 

chronic diseases 

• n = 11,131 

• 2000–2001 

• United Kingdom 

• Nonsmokers: Not defined 

• Quit smoking before pregnancy:

Timing of cessation not specified 

• Quit smoking during pregnancy

(month of cessation noted) 

• Continued smoking: Quit during

third trimester or did not quit 

• Smoking history based on selfreports ascertained when infants were

9 months old 

<37 weeks’ gestation,

based on gestational 

age estimated by

research team 

Difference in percentage of preterm delivery: 

• Nonsmokers (reference) 

• Quit smoking before pregnancy: +0.8% 

• Quit smoking, first trimester: +0.1%, 

p = 0.8 

• Quit smoking, second trimester: 2.8%, 

p = 0.08 

• Continued smoking: +2.9%, p <0.01 

Adjusted for birth year/

quarter of infant and

maternal weight, height,

income, initiation of 

prenatal care, alcohol 

use, employment status, 

home satisfaction, religion 

affiliation, and racist or 

religion-based insults in 

living area 

Did not account for 

substance use 

Dahlin et al. 

(2016) 

• 

• n = 1,371,274

• 

• Sweden 

Population-based,

retrospective cohort

study using the Swedish 

Medical Birth Register

1999–2012 

• Nonsmokers: No antenatal tobacco use 

• Quit smoking: Smoked during 3 months

before pregnancy but quit by the first 

antenatal visit 

• Continued smoking: Smoked ≥1 cigarette/

day at the time of the first antenatal visit 

• Smoking status based on self-reports 

derived from the Swedish Medical 

Birth Register 

• Extreme preterm

delivery: <28 weeks’ 

gestation 

• Very preterm

delivery: 28–31 

weeks’ gestation 

• Moderate preterm 

delivery: 32–36 

weeks’ gestation 

OR for preterm delivery (95% CI):

• Nonsmokers (reference) 

• Quit smoking: 

– Unadjusted preterm delivery: 

 Extreme: 1.12 (0.97–1.29) 

 Very: 1.03 (0.93–1.13) 

 Moderate: 1.05 (1.02–1.08) 

– Adjusted preterm delivery: 

 Extreme: 1.02 (0.88–1.18) 

 Very: 0.92 (0.83–1.02) 

 Moderate: 0.94 (0.91–1.01) 

• Continued smoking: 

– Unadjusted preterm delivery: 

 Extreme: 1.87 (1.64–2.12) 

 Very: 1.68 (1.54–1.83) 

 Moderate: 1.39 (1.34–1.43) 

– Adjusted preterm delivery: 

 Extreme: 1.74 (1.51–1.99) 

 Very: 1.52 (1.38–1.67) 

 Moderate: 1.27 (1.23–1.31) 

Results adjusted for

maternal age, parity, 

cohabitation with 

father, country of birth, 

education, and BMI 

Did not account for 

alcohol or substance use 

Table 4.34 Continued

The Health Benefits of Smoking Cessation 377
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Murphy et al. 

(2013)

•

•

•

•

•

Prospective cohort study

Singleton pregnancies

n = 1,216

2010–2011

Dublin, Ireland

•

•

•

•

Nonsmoker: Not defined

Quit smoking: Smoked during 6 months

before pregnancy but quit by first 

prenatal visit

Continued smoking: Smoked during 

6 months before pregnancy, and 

smoking at first prenatal visit and 

during third trimester

Smoking status based on self-reports 

obtained at enrollment and during

third trimester

<37 weeks’ gestation Crude and adjusted OR for preterm delivery 

(95% CI):

•

•

Nonsmokers (reference)

Quit smoking:

–

–

Crude: 1.14 (0.51–2.56)

Adjusted: 1.68 (0.51–5.63)

• Continued smoking:

–

–

Crude: 1.25 (0.51–3.10)

Adjusted: 1.09 (0.86–1.75)

Birth weight adjusted 

for maternal age, BMI, 

nationality, unplanned 

pregnancy, private 

healthcare, alcohol use, 

and illicit drug use

Meghea et al. 

(2014)

• Prospective cohort study

• n = 474

• 2008–2009

• Romania

• Nonsmokers: Not smoking when 

learned of pregnancy

• Quit smoking: Quit upon learning 

of pregnancy

• Continued smoking: Smoking at time 

of study interview (gestational age 

not reported)

• Smoking history based on selfreports obtained at study enrollment 

(gestational age not reported)

<37 weeks’ gestation Odds ratio for preterm delivery (95% CI):

• Nonsmokers (reference)

• Quit smoking: 1.41 (0.59–3.37)

• Continued smoking: 1.29 (0.46–3.67)

Results adjusted for 

stress, depressive 

symptoms, maternal age

>35 years old, education, 

rural residence, marital 

status, and nulliparity

Did not account for 

alcohol or substance use

Räisänen

et al. (2014)

•

•

•

•

•

Population-based 

retrospective cohort 

using Finnish Medical 

Birth Register

Singleton deliveries, 

live or stillborn after 

22 weeks’ gestation

n = 1,164,953

1991–2010

Finland

•

•

•

•

Nonsmokers: Not further defined

Quit smoking: Quit smoking during 

first trimester

Continued smoking: Smoked after 

first trimester

Smoking history based on self-reports 

ascertained from the Finnish Medical 

Birth Register

<37 weeks’ gestation Adjusted OR (95% CI):

•

•

Nonsmokers (reference)

Quit smoking:

–

–

Unadjusted: 1.04 (0.98–1.10)

Adjusted: 1.01 (0.95–1.07)

• Continuing smokers:

–

–

Unadjusted: 1.35 (1.31–1.38)

Adjusted: 1.39 (1.36–1.43)

Results adjusted for 

maternal age, parity, 

socioeconomic status, 

and sex of the infant

Did not account for 

alcohol or substance use

Table 4.34 Continued

A Report of the Surgeon General

378 Chapter 4
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Bailey (2015) • Randomized clinical 

trial of smoking 

cessation intervention

• 2008–2012

• n = 1,486

• Tennessee

• Quit smoking: Smoked at first prenatal 

visit but quit by third trimester

• Continued smoking: Smoked at first 

prenatal visit and still smoking during 

third trimester

• Smoking history based on self-reports 

obtained at first prenatal visit

• Quit status ascertained during third 

trimester by exhaled CO and urine 

cotinine and by self-report at delivery

Preterm delivery not 

defined

Percentage preterm delivery (95% CI):

• Quit smoking: 9.8%

• Continued smoking: 13.8%

• p = 0.089

Randomized cessation trial 

and thus no comparison 

group of never smokers

Results adjusted for 

maternal age, education, 

marital status, insurance 

status, and marijuana use

Examined maternal race, 

previous pregnancies, 

live deliveries, and alcohol 

use, but they were not 

significant in the model

Smith et al. 

(2015)

•

•

•

•

Population-based casecohort study

n = 1,887

2009–2010

United Kingdom

•

•

•

•

•

l

l

l

l

Nonsmoker: Did not smoke during 

preconception or early (1–13 weeks) or 

ate (14–32 weeks) during pregnancy

Quit smoking before pregnancy: Smoked 

preconception but not during early or 

ate pregnancy

Quit smoking, first trimester: Smoked 

during early pregnancy but not during 

ate pregnancy

Continued smoking: Smoked during 

ate pregnancy

Smoking status based on self-reports 

obtained from maternal interview 

conducted shortly after delivery

32–36 weeks’ gestation Adjusted RR for preterm delivery (95% CI):

•

•

•

•

Nonsmokers (reference)

Quit smoking before pregnancy: 

0.93 (0.72–1.20)

Quit smoking, first trimester: 

1.12 (0.76–1.66)

Continued smoking: 1.38 (1.04–1.84)

Results adjusted for 

maternal age, ethnicity, 

BMI, education level, 

and lifestyle factors 

(recreational drug and 

alcohol use, dietary 

practices, and folic 

acid supplements)

Table 4.34 Continued

The Health Benefits of Smoking Cessation 379
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Yan and

Groothuis

(2015)

• Population-based

cohort study

• Singleton pregnancies

• Excluded women with

chronic diseases

• n = 11,131

• 2000–2001

• United Kingdom

• Nonsmokers: Not defined

• Quit smoking before pregnancy:

Timing of cessation not specified

• Quit smoking during pregnancy

(month of cessation noted)

• Continued smoking: Quit during 

third trimester or did not quit

• Smoking history based on selfreports ascertained when infants were 

9 months old

<37 weeks’ gestation,

based on gestational 

age estimated by

research team

Difference in percentage of preterm delivery:

• Nonsmokers (reference)

• Quit smoking before pregnancy: +0.8%

• Quit smoking, first trimester: +0.1%,

p = 0.8

• Quit smoking, second trimester: 2.8%, 

p = 0.08

• Continued smoking: +2.9%, p <0.01

Adjusted for birth year/

quarter of infant and

maternal weight, height,

income, initiation of 

prenatal care, alcohol 

use, employment status, 

home satisfaction, religion 

affiliation, and racist or 

religion-based insults in 

living area

Did not account for

substance use

Dahlin et al.

(2016)

•

•

•

•

Population-based,

retrospective cohort 

study using the Swedish 

Medical Birth Register

n = 1,371,274

1999–2012

Sweden

•

•

•

•

Nonsmokers: No antenatal tobacco use

Quit smoking: Smoked during 3 months 

before pregnancy but quit by the first 

antenatal visit

Continued smoking: Smoked ≥1 cigarette/

day at the time of the first antenatal visit

Smoking status based on self-reports 

derived from the Swedish Medical 

Birth Register

•

•

•

Extreme preterm

delivery: <28 weeks’ 

gestation

Very preterm 

delivery: 28–31 

weeks’ gestation

Moderate preterm 

delivery: 32–36 

weeks’ gestation

OR for preterm delivery (95% CI):

•

•

Nonsmokers (reference)

Quit smoking:

– Unadjusted preterm delivery:







Extreme: 1.12 (0.97–1.29)

Very: 1.03 (0.93–1.13)

Moderate: 1.05 (1.02–1.08)

– Adjusted preterm delivery:







Extreme: 1.02 (0.88–1.18)

Very: 0.92 (0.83–1.02)

Moderate: 0.94 (0.91–1.01)

• Continued smoking:

– Unadjusted preterm delivery:







Extreme: 1.87 (1.64–2.12)

Very: 1.68 (1.54–1.83)

Moderate: 1.39 (1.34–1.43)

– Adjusted preterm delivery:







Extreme: 1.74 (1.51–1.99)

Very: 1.52 (1.38–1.67)

Moderate: 1.27 (1.23–1.31)

Results adjusted for

maternal age, parity, 

cohabitation with 

father, country of birth, 

education, and BMI

Did not account for 

alcohol or substance use

Table 4.34 Continued

A Report of the Surgeon General

380 Chapter 4
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Moore et al. 

(2016)

(continues on 

next page)

• Population-based,

retrospective cohort

using certificates oflive

 births in Ohio 

• Singleton births without

congenital anomalies 

• n = 913,757 

• 2006–2012 

• Ohio 

• Nonsmoker: Did not smoke during 

3 months before pregnancy

• Quit smoking before pregnancy: Smoked 

during 3 months before pregnancy but 

not during first trimester

• Quit smoking, first trimester: Smoked 

during first trimester but not during 

second and third trimesters

• Quit smoking, second trimester: Smoked 

during second trimester but not during 

third trimester

• Continued smoking: Smoked during all 

three trimesters

• Smoking status obtained from Ohio 

certificates of live birth

• Overall preterm 

delivery: <37 weeks’ 

gestation based 

on clinician’s 

best estimate of 

gestational age 

• Extreme preterm 

delivery:20–27weeks’ 

gestation 

• Preterm delivery: 

28–36weeks’ 

gestation

• Spontaneous 

preterm delivery: 

Not medically 

indicated

• Indicated preterm 

delivery:Births 

complicated by 

intrauterine 

growth restriction, 

preeclampsia, or 

eclampsia following 

induction of labor

Adjusted OR for preterm delivery (95% CI):

• Overall:

– Nonsmoker (reference)

– Quit smoking before pregnancy: 0.91 (0.88–

0.94)

– Quit smoking, first trimester: 1.02 (0.98–

1.07)

– Quit smoking, second trimester: 1.70 (1.60–

1.80)

– Continued smoking: 1.21 (1.19–1.24)

• Extreme preterm:

– Nonsmoker (reference)

– Quit smoking before pregnancy: 0.87 (0.77–

0.98)

– Quit smoking, first trimester: 1.20 (1.03–

1.40)

– Quit smoking, second trimester: Not 

applicable

– Continued smoking: 0.90 (0.83–0.97)

• Preterm:

– Nonsmoker (reference)

– Quit smoking before pregnancy: 0.91 (0.88–

0.94)

– Quit smoking, first trimester: 1.01 (0.96–

1.05)

– Quit smoking, second trimester: 1.46 

(1.37−1.55)

– Continued smoking: 1.24 (1.21–1.26)

Results adjusted for 

maternal race, education, 

age, Medicaid, marital 

status, and parity

Table 4.34 Continued

The Health Benefits of Smoking Cessation 381
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

(continued 

from previous 

page)

Moore et al. 

(2016)

(continues on 

next page)

— — — Indicated preterm delivery (95% CI):

• Overall:

–

–

–

–

–

Nonsmoker (reference)

Quit smoking before pregnancy: 

0.92 (0.87–0.97)

Quit smoking, first trimester: 

1.01 (0.94–1.09)

Quit smoking, second trimester: 

1.78 (1.62–1.96)

Continued smoking: 1.22 (1.18–1.26)

• Extreme preterm:

–

–

–

–

–

Nonsmoker (reference)

Quit smoking before pregnancy: 

0.85 (0.78–0.93)

Quit smoking, first trimester: 

0.93 (0.82–1.05)

Quit smoking, second trimester: 

Not applicable

Continued smoking: 0.73 (0.69–0.78)

• Preterm:

–

–

–

–

–

Nonsmoker (reference)

Quit smoking before pregnancy: 

0.91 (0.87–0.96)

Quit smoking, first trimester: 

0.99 (0.92–1.07)

Quit smoking, second trimester: 

1.66 (1.51–1.83)

Continued smoking: 1.18 (1.14–1.22)

— 

Table 4.34 Continued

A Report of the Surgeon General

382 Chapter 4
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

(continued 

from previous 

page)

Moore et al. 

(2016)

— — — Spontaneous preterm delivery (95% CI):

• Overall:

Nonsmoker (reference)

Quit smoking before pregnancy: 

0.90 (0.87–0.93)

Quit smoking, first trimester: 

1.03 (0.97–1.08)

Quit smoking, second trimester: 

1.65 (1.54–1.77)

Continued smoking: 1.20 (1.17–1.22)

–

–

–

–

–

• Extreme preterm:

Nonsmoker (reference)

Quit smoking before pregnancy:

0.88 (0.77–1.02)

Quit smoking, first trimester: 

1.20 (1.00–1.43)

Quit smoking, second trimester: 

Not applicable

Continued smoking: 0.93 (0.84–1.02)

–

–

–

–

–

• Preterm:

Nonsmoker (reference)

Quit smoking before pregnancy: 

0.90 (0.87–0.94)

Quit smoking, first trimester: 

1.02 (0.96–1.08)

Quit smoking, second trimester:

1.37 (1.26–1.48)

Continued smoking: 1.25 (1.22–1.28)

–

–

–

–

–

— 

Suzuki et al. 

(2016)

•

•

•

•

•

Population-based, 

cohort study

Singleton pregnancies

n = 7734

2011–2014

Japan

•

•

•

•

•

Nonsmokers: Never smoked

Quit smoking before pregnancy: 

Not further defined

Quit smoking during early pregnancy: 

Not further defined

Continued smoking: Currently

smoking at time study questionnaire 

was administered

Smoking status based on self-reports 

collected during second trimester

Preterm delivery 

not defined

Percentage preterm delivery:

•

•

•

•

•

Nonsmoker: 5.0%

Quit smoking before pregnancy: 5.8%

Quit smoking during early pregnancy: 5.6%

Continued smoking: 8.9%

Chi-square test p = 0.008

Results not adjusted for 

potential confounders 

Did not account for 

alcohol or substance use 

Table 4.34 Continued

The Health Benefits of Smoking Cessation 383
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Wallace et al. 

(2017)

• Population-based, 

retrospective cohort 

study using certificates 

of live births in Ohio

• Singleton pregnancies

• Excluded congenital 

malformations

• All participants had 

at least one previous 

preterm delivery

• 2006–2012

• n = 36,432

• Ohio

Nonsmoker: Did not smoke during 

3 months before pregnancy

Quit smoking by first trimester: Smoked 

during 3 months before pregnancy but 

not during first trimester

Quit by second trimester: Smoked 

during first trimester but not during 

second or third trimesters

Quit by third trimester: Smoked 

during second trimester but not during 

third trimester 

Continued smoking: Smoked during 

all three trimesters 

Smoking status obtained from Ohio 

certificates of live birth 

<37 weeks’ gestation Adjusted OR for preterm delivery (95% CI):

Nonsmokers (reference)

•

•

•

•

•

•

Quit smoking by first trimester: 

0.97 (0.86–1.09)

Quit smoking by second trimester: 

1.10 (0.93–1.29)

Quit smoking by third trimester: 

1.81 (1.48–2.21)

Continued smoking: 1.14 (1.07–1.22)

•

•

•

•

•

Results adjusted for 

maternal race, marital 

status, and Medicaid 

enrollment

Tong et al. 

(2017)

•

•

•

•

Did not account for 

alcohol or substance use

Population-based, 

retrospective 

cohort study

n = 88,933

2009–2011

United States

•

•

•

•

Nonsmoker: Did not smoke during 

past 2 years and did not smoke during 

3 months before pregnancy 

Quit smoking: Smoked during 3 months 

before pregnancy but not during last 

3 months of pregnancy 

Continued smoking, nondaily: Smoked 

during 3 months before pregnancy and 

smoked <1 cigarette/day inlast 3 months 

of pregnancy 

Continuedsmoking, daily: Smoked 

during 3 months before pregnancy and 

smoked ≥1 cigarette/day during last

3 months of pregnancy 

<37 weeks’ gestation 

based on clinical 

estimate of gestation 

from birth certificates

Crude and adjusted prevalence ratio for 

preterm delivery (95% CI):

•

•

Nonsmoker (reference)

Quit smoking:

–

–

–

–

–

Crude: 1.0 (0.9–1.1)

Adjusted: 1.0 (0.9–1.1)

Continued smoking, nondaily:

Crude: 1.0 (0.8–1.3)

Adjusted: 1.0 (0.8–1.2)

• Continued smoking, daily:

–

–

Crude 1.3: (1.2–1.4)

Adjusted: 1.3 (1.2–1.4)

Prevalence ratios adjusted 

for maternal age, parity, 

education, marital status, 

BMI, trimester of entry into 

prenatal care, and alcohol 

use during pregnancy

Did not account for 

substance use

Table 4.34 Continued

A Report of the Surgeon General

384 Chapter 4

Notes: BMI = body mass index; CI = confidence interval; CO = carbon monoxide; OR = odds ratio; RR = risk ratio; SGA = small for gestational age.
The Health Benefits of Smoking Cessation 385

Smoking Cessation

(Polakowski et al. 2009), and in a smaller study, no significant difference was found between quitters and continuing smokers (Bailey 2015). Three studies were not 

sufficiently large to examine cessation during pregnancy, 

and the CIs were wide (McCowan et al. 2009; Miyake et al. 

2013; Meghea et al. 2014). 

In one of the 23  studies examining individual 

pregnancies, the timing of cessation was not described 

(Erickson and Arbour 2012); in that study, a modest but 

significant increase in risk was found among quitters compared with nonsmokers (aOR = 1.18; 95% CI, 1.08–1.28). 

Only 1 of the 23 studies included biochemical validation of 

smoking status (Bailey 2015); that study was a randomized 

clinical trial of a smoking cessation intervention (n = 1,486 

who received the intervention vs. 461 who received usual 

care) in which no statistically significant difference was 

found in the risk of preterm delivery among women in 

the intervention group between women who quit smoking 

during pregnancy and continuing smokers (13.8% among 

continuing smokers and 9.8% among quitters [p = 0.09]).

Of the two studies that examined cessation across 

pregnancies, one found an increased risk of preterm 

delivery in the second pregnancy in women who quit 

between pregnancies versus those who did not smoke 

in either (aOR  =  1.41; 95%  CI, 1.29–1.55) (Mohsin and 

Jalaludin 2008), and the other found no difference in the 

risk of preterm delivery during the second pregnancy for 

women who quit between pregnancies compared with 

those who smoked during both pregnancies (Abrevaya 

2008). As was previously discussed, examining outcomes 

across pregnancies can be limited by an oversimplification of exposure categories, but this design can reduce the 

contributions of confounding from environmental and 

genetic factors. If smoking cessation during pregnancy 

affects the risk of preterm delivery, then the effect could 

be missed using this method.

Summary of the Evidence. Since the 2004 Surgeon 

General’s report found a causal relationship between 

maternal smoking and preterm delivery (gestational age 

<37  weeks) and shorter gestational duration (USDHHS 

2004), numerous studies have assessed the relationships 

between smoking cessation before and/or during pregnancy and preterm delivery, and most have adjusted for 

multiple confounders. Most of these studies compared the 

risk of preterm delivery in quitters to that in nonsmokers, 

while fewer studies directly compared the risk in quitters 

to that in continuing smokers. The majority of studies 

that compared quitters and nonsmokers found no difference in risk of preterm delivery, and studies that compared 

quitters and continuing smokers reported mixed results 

(all  reported lower risk in quitters compared with continuing smokers overall, but not all findings were significant). There were limited data with which to assess the role 

of timing of cessation for risk of preterm delivery, but the 

largest studies that examined trimester-specific cessation 

reported that earlier cessation produces greater benefits 

for risk of preterm delivery than later cessation. The evidence is suggestive but not sufficient to infer that the risk 

of preterm delivery in women who quit smoking before or 

during early pregnancy does not differ from that of nonsmokers. The evidence is suggestive but not sufficient to 

infer that women who quit smoking before conception or 

during early pregnancy have a reduced risk of preterm 

delivery compared with women who continue to smoke.

Stillbirth, Perinatal Mortality, 

and Infant Mortality

Stillbirth (typically defined as a fetal death after 

28  weeks’ gestation), perinatal mortality (stillbirths and 

deaths in the first week of life), and infant mortality (neonatal [death in the first month of life] and postnatal [death 

from 1 month to 1 year of life]) have all been associated 

with prenatal exposure to tobacco in previous Surgeon 

General’s reports. The 1990 Surgeon General’s report on 

smoking cessation presented evidence that women who 

quit smoking are at lower risk of perinatal mortality relative to continuing smokers, although the studies were 

too few to be conclusive (USDHHS 1990). No conclusions 

were drawn about the relationship between smoking cessation and infant mortality. The 2004 and 2014 Surgeon 

General’s reports concluded that infants of smokers are at 

higher risk of stillbirth, perinatal mortality, and neonatal 

mortality than infants of nonsmokers (USDHHS 2004, 

2014). Overall, these reports did not review the effects 

of cessation on these risks. The 2004 Surgeon General’s 

report also found that smoking during or after pregnancy 

increases the risk of sudden infant death syndrome, but 

this outcome was not reviewed in this report due to the 

lack of studies directly assessing the consequences of 

smoking cessation on sudden infant death syndrome 

(USDHHS 2004).

Stillbirth, perinatal, and infant mortality are multifactorial in etiology, and many of their causal factors 

are also causally associated with smoking. For example, 

smoking is causally associated with preterm delivery, 

PPROM, placenta previa, and placental abruption—all 

of which contribute to perinatal and neonatal mortality; 

and preterm delivery accounts for more than one-third of 

infant deaths (Matthews et al. 2015). Therefore, the effects 

of cessation on those pathways would likely translate 

into beneficial effects on more distal outcomes. In addition, approximately half of perinatal deaths in the United 

States are stillbirths, and half are deaths in the first week 
A Report of the Surgeon General

386 Chapter 4

of life. Therefore, effects of smoking cessation on stillbirth 

or deaths in the first week of life likely also affect rates 

of perinatal mortality. The relationship between smoking 

and fetal growth was explored in depth in the 2014 

Surgeon General’s report (USDHHS 2014). Briefly, when 

the distributions of birth weight for the infants of smokers 

and their corresponding mortality rates are examined, 

infants of smokers have higher mortality than those of 

nonsmokers at every birth weight when each population is 

adjusted to its own z-scale for birth weight (Wilcox 2001). 

Thus, maternal smoking affects infant mortality independently of its effects on birth weight. Infants of nonsmokers 

are less likely to be born with low birth weight than those 

of smokers, but when they are, the underlying etiologies 

are associated with higher mortality (Wilcox 2001).

Stillbirth

Five studies published after 2000 were identified 

that examined smoking cessation and stillbirth; four 

examined cessation with respect to individual pregnancies 

(Wisborg et al. 2001; Erickson and Arbour 2012; Räisänen 

et al. 2014; Bjørnholt et al. 2016), and one examined cessation across two consecutive pregnancies (Högberg and 

Cnattingius 2007) (Table  4.35). All four studies examining cessation with respect to individual pregnancies 

included adjustment for at least some confounders, and 

two included adjustment for alcohol use or for alcohol 

and other substance use (Wisborg et  al. 2001; Erickson 

and Arbour 2012). Three studies relied on data from registries (Erickson and Arbour 2012; Räisänen et al. 2014; 

Bjørnholt et al. 2016), and none included biochemical validation of cessation status. Two studies examined women 

who quit smoking during early pregnancy (Räisänen 

et  al. 2014; Bjørnholt et  al. 2016), and one (Wisborg 

et  al. 2001) assessed smoking status in late pregnancy 

(30 weeks). No studies examined both the effects of quitting early versus quitting late in pregnancy. Three studies 

found no increased risk of stillbirth among women who 

quit smoking during early pregnancy compared with 

nonsmokers (Wisborg et  al. 2001; Räisänen et  al. 2014; 

Bjørnholt et  al. 2016), and one found increased risk in 

quitters but not in continuing smokers (Erickson and 

Arbour 2012). This last study, however, did not address 

the timing of cessation in quitters with respect to pregnancy, and smoking status was ascertained only at the 

first prenatal visit, making it possible that some former 

smokers had relapsed by the end of pregnancy compared 

with women who smoked in neither pregnancy. However, 

the risk of stillbirth in the second pregnancy was significantly elevated among women who smoked during 

both pregnancies. 

In the study that examined cessation across consecutive pregnancies (Högberg and Cnattingius 2007), 

a large, population-based study using data from the 

Swedish Medical Birth Register, women who smoked 

during the first pregnancy but not during the second 

pregnancy did not have an increased risk of stillbirth in 

the second pregnancy. 

Summary of the Evidence

Since the 2004 and 2014 Surgeon General’s reports 

found that infants of smokers are at higher risk of stillbirth 

than infants of nonsmokers (USDHHS 2004, 2014), several studies have examined the effects of smoking cessation on the risk of stillbirth, and findings have been mixed. 

These studies were limited by a lack of biochemical validation and inconsistent assessment of the timing of cessation during preconception and gestation. Consequently, 

the evidence is inadequate to infer that smoking cessation 

during pregnancy reduces the risk of stillbirth compared 

with continued smoking. 

Perinatal Mortality

Two studies published after 2000 were identified 

that examined smoking cessation and perinatal mortality (Bickerstaff et  al. 2012; Bailey 2015) (Table  4.36). 

Bickerstaff and colleagues (2012) examined risk in a retrospective cohort study of Australian women who had quit 

smoking in the year before pregnancy or after becoming 

pregnant but before the first antenatal visit, while Bailey 

(2015) examined risk in women participating in a randomized smoking cessation trial in the state of Tennessee 

who smoked during the first trimester of pregnancy but 

had quit by the third trimester. These two studies relied on 

self-reported tobacco use and adjusted for several potential 

confounders. Both studies found a reduction in the risk of 

perinatal mortality in quitters compared with continuing 

smokers, with findings from Bailey (2015) reaching statistical significance. Neither study compared quitters with 

nonsmokers.

Summary of the Evidence

Since the 2004 and 2014 Surgeon General’s reports 

concluded that children of smokers are at higher risk of 

perinatal mortality than children of nonsmokers (USDHHS 

2004, 2014), few studies have addressed smoking cessation and perinatal mortality. The evidence is inadequate to 

determine whether cessation before or during pregnancy 

reduces the risk of perinatal mortality compared with 

continued smoking.

Infant Mortality

Three studies published later than 2000 were identified that examined smoking cessation and infant death 
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Wisborg et al. 

(2001)

•

•

•

•

•

Prospective cohort study

Singleton pregnancies

n = 25,102

1989–1996

Denmark

•

•

•

•

Nonsmokers: Not smoking at time of 

either antenatal interview

Quit smoking: Stopped smoking by 

second antenatal interview

Continued smoking: Smoking ≥1 

cigarette/day at both antenatal interviews

Smoking status ascertained from 

maternal interviews conducted before

first antenatal visit (typically 16 weeks’ 

gestation) and before the 30-week 

antenatal visit

Death of a fetus at

or after 28 weeks’ 

gestation

Crude and adjusted ORfor stillbirth 

(95% CI): 

•

•

Nonsmokers (reference)

Quit smoking:

–

–

Unadjusted: 0.9 (0.5–1.9)

Adjusted: 0.9 (0.5–1.9)

• Continued smoking:

–

–

Unadjusted: 2.0 (1.4–2.9)

Adjusted: 1.9 (1.3–2.9)

Results adjusted for parity; 

maternal age, education, 

employment, caffeine and 

alcohol intake, weight, 

and height; and sex of 

the infant

Did not account for 

substance use

Högberg and 

Cnattingius 

(2007)

• Population-based 

cohort study

• First and second 

singleton births

• n = 526,691

• 1983–2001

• Sweden

•

•

Nonsmokers:Not smoking daily at 

time offirst antenatal visit 

Moderate smoker: Smoking 

1–9 cigarettes/day at time of first 

antenatal visit 

• Heavy smoker: Smoking ≥10 cigarettes/

day at time of first antenatal visit

• Quit smoking: Not smoking in 

second pregnancy

• Smoking history ascertained from 

medical birth registry, which included 

smoking status collected at first antenatal 

visit (typically <15 weeks’ gestation)

Fetal death after at 

least 28 completed 

weeks’ gestation

Crude and adjusted ORfor stillbirth in 

spregnancy (95% CI): econd 

• Nonsmoker both pregnancies (reference)

• Nonsmoker/moderate smoker:

– Unadjusted: 0.85 (0.54–1.32)

– Adjusted: 0.82 (0.52–1.30)

• Nonsmoker/heavy smoker:

– Unadjusted: 1.09 (0.49–2.45)

– Adjusted: 0.92 (0.38–2.22)

• Moderate smoker/nonsmoker (quit smoking):

– Unadjusted: 1.17 (0.91–1.50)

– Adjusted: 1.11 (0.85–1.44)

• Moderate smoker/moderate smoker:

– Unadjusted: 1.15 (0.92–1.43)

– Adjusted: 1.16 (0.92–1.46)

• Moderate smoker/heavy smoker:

– Unadjusted: 1.64 (1.21–2.23)

– Adjusted: 1.56 (1.13–2.16)

• Heavy smoker/nonsmoker (quit smoking):

– Unadjusted: 0.88 (0.51–1.51)

– Adjusted: 0.67 (0.36–1.26)

• Heavy smoker/moderate smoker:

– Unadjusted: 1.50 (1.09–2.06)

– Adjusted: 1.41 (1.01–1.96)

• Heavy smoker/heavy smoker:

– Unadjusted: 1.70 (1.32–2.19)

– Adjusted: 1.55 (1.17–2.04)

Results adjusted for 

maternal age, education, 

cohabitation with the 

father, mother’s country 

of birth, interpregnancy 

interval, stillbirth in first 

pregnancy, and year of 

second delivery

Did not account for 

alcohol or substance use

Table 4.35 Studies on smoking cessation and stillbirth

The Health Benefits of Smoking Cessation 387
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Erickson 

and Arbour 

(2012)

•

•

•

•

•

Population-based

retrospective cohort 

study using the 

British Columbia 

Perinatal Database 

Registry

Singleton deliveries

n = 233,891

2001–2006

British Columbia, 

Canada

•

•

•

•

•

•

•

Nonsmoker: Never smoked

Quit smoking: Former smoker (time of 

cessation in former smokers with respect 

to pregnancy was not available)

Continued smoking: Current smoker 

at time of smoking status assessment

Light: 1–4 cigarettes/day

Moderate: 5–9 cigarettes/day

Heavy: ≥10 cigarettes/day

Smoking history based on self-reports 

typically ascertained at first prenatal visit

Fetal death ≥20 weeks’

gestation or >500 g

Adjusted OR for stillbirth (95% CI):

•

•

•

Nonsmoker (reference)

Quit smoking: 1.43 (1.03–2.00)

Continued smoking

–

–

–

Light: 1.08 (0.67–1.72)

Moderate: 1.19 (0.71–1.97)

Heavy: 1.40 (0.97–2.03)

Results adjusted for

parity; prenatal care 

visits; maternal age, 

diabetes, hypertension, 

pre-pregnancy weight, 

and alcohol and drug use; 

presence of a partner; 

and sex of the infant

Räisänen

et al. (2014)

• Population-based 

retrospective cohort 

using Finnish Medical 

Birth Register

• Singleton deliveries, 

live or stillborn after 

22 weeks’ gestation

• 1991–2010

• n = 1,164,953

• Finland

• Nonsmokers: Not further defined

• Quit smoking: Quit smoking during 

first trimester 

• Continued smoking: Smoked after 

first trimester

• Smoking history based on self-reports 

ascertained from the Finnish Medical 

Birth Register

• Details on when and how data were 

collected were not reported

Stillbirth definition 

not provided

OR for stillbirth (95% CI):

• Reference (nonsmokers)

• Quit smoking:

– Unadjusted: 0.70 (0.60–0.81)

– Adjusted: 1.07 (0.92–1.26)

• Continued smoking:

– Unadjusted: 1.03 (0.97–1.10)

– Adjusted: 1.13 (1.06–1.20)

Results adjusted for 

maternal age, parity, 

socioeconomic status, 

and sex of the infant

Did not account for 

alcohol or substance use

Bjørnholt 

et al. (2016)

•

•

•

•

•

Population-based cohort 

study using the Danish 

Medical Birth Register

Singleton births

n = 841,228

1997–2010

Denmark

•

•

•

•

Nonsmoker: Did not smoke 

during pregnancy 

Quit smoking: Quit during first trimester 

or early in second trimester 

Continued smoking: Still smoking 

at time offirst antenatal visit 

Smoking status ascertained from 

maternal interviews at first antenatal 

visit (13–15 weeks’ gestation) 

•

•

•

1997–2004: 

Fetal death after 

28 completed 

weeks’ gestation 

2004–2010: 

Fetal death after 

22 completed 

weeks’ gestation 

Stillbirth further 

categorized as 

antepartum 

(before delivery) 

or intrapartum 

(during delivery) 

Adjusted OR for stillbirth (95% CI):

• All:

–

–

–

Nonsmoker (reference)

Quit smoking: 1.03 (0.80–1.32)

Continued smoking: 1.47 (1.35–1.62)

• Antepartum:

–

–

–

Nonsmoker (reference)

Quit smoking: 0.83 (0.61–1.13)

Continued smoking: 1.45 (1.31–1.61)

• Intrapartum:

–

–

–

Nonsmoker (reference)

Quit smoking: 1.94 (1.10–3.41)

Continued smoking: 1.47 (1.12–1.92)

Results adjusted for year of 

delivery, maternal age, and 

marital or partner status

Table 4.35 Continued

A Report of the Surgeon General

388 Chapter 4

Notes: CI = confidence interval; OR = odds ratio.
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Bickerstaff 

et al. (2012)

•

•

•

•

Retrospective 

cohort study

1997–2006

n = 30,524 

Australia

•

•

•

•

Nonsmoker: Never smoked or quit

>12 months before booking

Quit smoking: Smoked during 12 months

before booking but quit before booking

Continued smoking: Currently smoking

at booking

Smoking status based on routinely

collected clinical data at antenatal booking 

Stillbirths and neonatal 

deaths during delivery 

hospitalization

Adjusted OR for perinatal mortality (95% CI):

•

•

Continued smoking vs. nonsmoker:

1.36 (0.99–1.87)

Quit smoking vs. continued smoking:

0.78 (0.28–2.16)

Results adjusted for 

plurality, previous 

pregnancy complications, 

parity, and ethnicity 

Did not account for 

alcohol or substance use 

Bailey 

(2015)

• Randomized clinical

trial of smoking

cessation intervention

• n = 1,486

• 2008–2012

• Tennessee

• Quit smoking: Smoked at first prenatal 

visit but quit by third trimester

• Continued smoking: Smoked at first

prenatal visit and still smoking during

third trimester

• Smoking history based on self-reports 

obtained at first prenatal visit

• Quit status ascertained during third

trimester by exhaled CO and urine

cotinine and by self-reports at delivery

Fetal or neonatal 

demise not defined

Percentage perinatal deaths: 

• Quit smoking: 0.2%

• Continued smoking: 1.0%

• p = 0.046

Randomized cessation trial 

and thus no comparison 

group of never smokers

Results adjusted for 

maternal age, education, 

marital status, insurance 

status, and marijuana use

Examined alcohol use, 

but not significantin 

the model 

Notes: CI = confidence interval; CO = carbon monoxide; OR = odds ratio.

Table 4.36 Studies on smoking cessation and perinatal mortality

The Health Benefits of Smoking Cessation 389
A Report of the Surgeon General

390 Chapter 4

(Table 4.37). One study examined cessation with respect 

to individual pregnancies (Wisborg et al. 2001), and two 

examined cessation across two consecutive pregnancies 

(Abrevaya 2008; Johansson et al. 2009). All three studies 

relied on self-reported smoking status and adjusted for 

multiple potential confounders, with one also adjusting 

for alcohol use (Wisborg et al. 2001), but none adjusted 

for substance use. In a prospective cohort study of Danish 

women, Wisborg and colleagues (2001) found that, compared with women who did not smoke at all during pregnancy, women who smoked during pregnancy but quit by 

the time of the first antenatal interview (around 16 weeks’ 

gestation) had no significant increase in the risk of infant 

death (aOR = 1.0; 95% CI, 0.5–1.9). Johansson and colleagues, who examined smoking status at the first antenatal visit in two consecutive pregnancies, found no 

increase in infant mortality for the second pregnancy 

among women who were light smokers in the first 

pregnancy but had quit by the second pregnancy compared with women who did not smoke in either pregnancy (aOR = 1.0; 95% CI, 0.8–1.5). This study, however, 

found increased risk in women who were heavy smokers 

in the first pregnancy and quit by the second pregnancy 

(aOR  =  1.4; 95%  CI, 1.0–2.0). Similarly, heavy smokers 

who smoked only in the second pregnancy had a significantly increased risk of infant mortality for that pregnancy 

(aOR = 1.8; 95% CI, 1.0–2.9). In the third study, Abrevaya 

and colleagues (2008) found no significant difference in 

the risk of infant mortality during the second pregnancy 

in women who smoked during the first but not the second 

pregnancy compared with women who smoked during 

both pregnancies. Comparisons between women who quit 

smoking by the second pregnancy and women who did not 

smoke in either pregnancy were not reported.

Summary of the Evidence

Since the 2004 Surgeon General’s report (USDHHS 

2004), few studies have addressed smoking cessation and 

infant mortality, and findings have been mixed. The evidence is inadequate to infer that women who quit smoking 

before or during early pregnancy have reduced risk for 

infant mortality compared with continuing smokers.

Female Reproductive Health

Fertility

“Infertility” is defined as the inability to achieve pregnancy following 12 months of regular, unprotected sexual 

intercourse (Practice Committee of American Society for 

Reproductive Medicine [PCASRM] 2013), while “fecundity” refers to the biologic ability to conceive. Subfertility 

is any form of reduced fertility in couples trying to conceive. Up to 15% of couples have some form of infertility 

(Thoma et al. 2013), approximately half of which is related 

to female causes, 30% to male causes, and 20% to both 

male and female causes (Kovac et al. 2015). Women can 

have primary infertility (inability to conceive and no previous pregnancies), or secondary infertility (inability to 

conceive following a previous pregnancy). The PCASRM 

(2012) has estimated that 13% of infertility may be attributable to smoking.

Several pathways involved in reproduction could 

be targets of toxicants in cigarette smoke that adversely 

affect fertility (Dechanet et al. 2011; Marom-Haham and 

Shulman 2016). Cigarette smoking could affect folliculogenesis by inhibiting the growth of follicles or the maturation of oocytes. Possible mechanisms include abnormal 

oxidative stress, increased apoptosis, abnormal cross 

talk between oocytes and granulosa cells by inhibition 

of gap-junction formation between cells, or impairment 

of oocyte nuclear function by damaging DNA or interfering with meiosis. In addition, compounds in cigarette 

smoke could disrupt steroidogenesis, leading to alterations of estrogens and/or androgens in the follicular environment. Cigarette smoke, through its proangiogenic or 

antiangiogenic properties, could affect the early development of the embryo. Additionally, cigarette smoke could 

target the oviduct (by acting on its adhesive properties, 

ciliary activity, or muscular contractions) or the endometrium (by impairing endometrial proliferation or maturation, or by causing aberrant regulation of angiogenesis). 

Finally, tobacco smoke could cause vascular impairment 

in the uterine arteries or could affect myometrial contractility, which could adversely affect implantation (Dechanet 

et al. 2011; Marom-Haham and Shulman 2016).

The 1990 Surgeon General’s report found evidence 

that cessation before attempted conception restored 

the fertility of former smokers to that of never smokers 

(Baird and Wilcox 1985; Daling et  al. 1985; Howe et  al. 

1985; USDHHS 1990). The 2001 Surgeon General’s report 

reviewed conception delay and infertility and found that 

although active smoking was associated with conception 

delay, the effect appeared to be reversible, as several studies 

observed similar conception rates for former and never 

smokers (USDHHS 2001). The report noted that smoking 

was consistently associated with impaired fertility in both 

case-control and cohort studies, and some studies found 

evidence of a dose-response relationship. Former smokers 

appeared to have little excess risk of impaired fertility. The 

report also concluded that smokers are at increased risk of 

primary and secondary infertility, but it did not draw conclusions about smoking cessation (USDHHS 2001). 

The 2004 Surgeon General’s report reviewed studies 

of smoking and fertility in women and found consistent 
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Wisborg et al. 

(2001)

•

•

•

•

•

Prospective cohort study

Singleton pregnancies

n = 25,102

1989–1996 

Denmark

•

•

•

•

Nonsmokers: Not smoking at time of 

either antenatal interview

Quit smoking: Smoked during pregnancy 

but quit by first antenatal interview

Continued smoking: Smoked ≥1 cigarette/

day at first antenatal interview

Smoking status ascertained from 

maternal interviews conducted before 

first antenatal visit (typically 16 weeks’ 

gestation) and before the 30-week 

antenatal visit

Death of a liveborn 

infant before 1 year 

of age

Crude and adjusted OR for infant mortality

(95% CI):





Nonsmokers (reference)

Quit smoking:

– Unadjusted: 1.0 (0.5–1.9)

– Adjusted: 0.9 (0.5–1.9)

Results adjusted for parity; 

maternal age, education, 

employment, caffeine and 

alcohol intake, weight, 

and height; and sex of 

the infant

Did not account for 

substance use

Abrevaya

et al. (2008)

• Population-based, 

retrospective cohort 

study using Michiganlinked certificates of 

live births

• First and second 

pregnancies in which 

women smoked during 

the first pregnancy

n = 14,731 (18–24 years 

of age)

n = 8,044 (25–30 years 

of age)

• 1989–2004

• Michigan

•

•

• Quit smoking: Smoked during first 

pregnancy but not during second 

pregnancy

• Continued smoking during both 

pregnancies: Smoked during first and 

second pregnancies

• Smoking status based on smoking history 

collected from certificates of live birth, 

which used one question on tobacco use 

during pregnancy (yes/no)

Death of a liveborn 

infant within 1 year 

of birth

Adjusted OR for infant mortality (95% CI):

 Quit smoking (reference)

 Continued smoking during both pregnancies:

– 18–24 years of age: 1.07 (0.71–1.61)

– 25–30 years of age: 0.67 (0.28–1.62)

Results adjusted for 

maternal race, education, 

income, population, 

interpregnancy interval, 

year of birth, trimester 

of first prenatal visit, 

presence of father’s name 

on birth certificate, 

number of prenatal visits, 

and first-birth value of 

the outcome

Did not account for 

alcohol or substance use

Table 4.37 Studies on smoking cessation and infant mortality

The Health Benefits of Smoking Cessation 391
Study Design/population Exposure groups/how determined Outcome definition Findings Comments

Johansson 

et al. 

(2009)

•

•

•

•

Births from the Swedish 

Birth Register

First and second 

singleton pregnancies

n = 555,046

Sweden

•

•

•

•

•

Nonsmokers: Not smoking at first 

antenatal visit in either pregnancy

Quit smoking: Smoked at first antenatal 

visit of first pregnancy but not at first 

antenatal visit of second pregnancy

Relapsed: Did not smoke at first antenatal 

visit of first pregnancy but smoked at first 

antenatal visit of second pregnancy

Continued smoking: Smoked at first 

antenatal visit of both pregnancies:

– Light smoker: 1–9 cigarettes/day

– Heavy smoker: ≥10 cigarettes/day

Smoking status based on maternal selfreports obtained at first antenatal visit 

and on Swedish Birth Register

Death during the 

first year of life in a 

liveborn infant from

second pregnancy, born

≥22 weeks’ gestation

Adjusted OR for infant mortality after second 

pregnancy (95% CI):

•

•

Nonsmoker (reference)

Quit smoking:

–

–

Light smoker, first pregnancy: 

1.0 (0.8–1.5)

Heavy smoker, first pregnancy: 

1.4 (1.0–2.0)

• Relapsed:

–

–

Light smoker, second pregnancy: 

1.1 (0.8–1.5)

Heavy smoker, second pregnancy: 

1.8 (1.0–2.9)

• Continued smoking (results attenuated when 

also adjusted for gestational age and placental 

abruption; remained significant for all but 

light/light smokers):

–

–

–

–

Light/light: 1.3 (1.1–1.6)

Heavy/light: 1.5 (1.1–1.9)

Light/heavy: 1.7 (1.3–2.2)

Heavy/heavy: 2.0 (1.7–2.4)

Results adjusted for 

maternal age, education, 

country of birth, 

interpregnancy interval, 

and year of delivery

Did not account for 

alcohol or substance use

Table 4.37 Continued

A Report of the Surgeon General

392 Chapter 4

Notes: CI = confidence interval; OR = odds ratio.
The Health Benefits of Smoking Cessation 393

Smoking Cessation

evidence that smoking reduces fecundity and increases 

the risk of primary infertility, with some evidence presented of a dose-response relationship with the number 

of cigarettes smoked. The report concluded that a causal 

relationship exists between smoking and reduced fertility 

in women, but it did not draw conclusions related to cessation (USDHHS 2004). The 2010 Surgeon General’s report 

provided an updated review of smoking and fertility in 

women, including a meta-analysis of 12 studies that calculated an overall OR of 1.6 (95% CI, 1.3–1.9) for infertility 

versus nonsmokers (Augood et al. 1998). Earlier, a metaanalysis of data from seven studies of in vitro fertilization 

(IVF) patients indicated a significant reduction in conceptions per cycle in smokers compared with nonsmokers 

(OR  =  0.57; 95%  CI, 0.42–0.78) (Hughes and Brennan 

1996). A subsequent review of 22  studies reported that 

19 found evidence of adverse effects of smoking on female 

reproduction (Wilks and Hay 2004). 

Since 2000, two papers have examined smoking cessation and fertility in women. In a study of 569 women who 

became pregnant without infertility treatment, Munafò 

and colleagues (2002) found that women who smoked in 

the year before conception took approximately 2 months 

longer to conceive than women who quit at least a year 

before conception. In multivariable models that adjusted 

for age, weight, lifetime use of oral contraceptives, alcohol 

consumption, and vigorous exercise, the number of packyears of smoking was not associated with time to conception among former smokers (p = 0.093), but the number 

of cigarettes smoked per day was associated with increased 

time to conception among women who smoked during 

the period in which they were trying to conceive.

Radin and colleagues (2014) examined the association between fecundability (the probability of becoming 

pregnant in a single menstrual cycle), duration of active 

smoking, and smoking cessation in a prospective cohort 

of women in Denmark who were 18–40 years of age. The 

women were followed for up to 12 cycles after beginning to 

attempt conception. Overall, former smokers, occasional 

smokers, and regular smokers did not differ in fecundability from never smokers in models that adjusted for 

age, partner smoking, passive smoking, and the number of 

cycles at risk (adjusted fecundability ratios [aFRs] = 0.99, 

1.11, and 0.89, respectively). Former smokers with at 

least 10 pack-years of smoking, however, had significantly 

reduced fecundability (aFR = 0.74). 

Summary of the Evidence

The current review confirms findings of previous 

Surgeon General’s reports that support a causal association between smoking and reduced fertility (USDHHS 

2001, 2004). Although past reports of the Surgeon General 

found a causal association between smoking and reduced 

fertility and suggestive evidence of restored fertility after 

smoking cessation, studies published since 2000 do not 

provide sufficient evidence to build upon the findings of 

the previous reports. Recent evidence is inadequate to further elucidate the association between smoking cessation 

or the timing of cessation and attempted conception and 

improved fecundability. The evidence is inadequate to elucidate the association between smoking cessation or the 

timing of cessation and fertility or fecundity.

Age at Menopause

The age of natural menopause is defined as the age 

menses cease for 12 consecutive months with no obvious 

cause, such as pregnancy or lactation, and it may be an 

important predictor of subsequent morbidity and mortality. The risks of cardiovascular disease and osteoporosis 

are higher for women with earlier menopause, but their 

risk of breast cancer is reduced (Gold 2011). Age at menopause was found to be associated with increased all-cause 

mortality when women with natural menopause before 

40 years of age were compared with those who experienced 

menopause at 50 years of age or older (Gold 2011). Earlier, 

a large international study of women from 11 countries 

found the median age at menopause to be 50 years (range: 

49–52 years across the countries) (Morabia and Costanza 

1998). Factors associated with earlier menopause in epidemiologic studies include non-White race, low socioeconomic status, nulliparity, never using oral contraceptives, 

and lower weight (Gold 2011). Mechanisms contributing 

to an effect of smoking on age at menopause could involve 

genetics, environmental exposures, hormonal pathways, 

and health status (Gold et al. 2001, 2011; He and Murabito 

2014; Sapre and Thakur 2014; Schoenaker et al. 2014). 

The 1990 Surgeon General’s report noted that cigarette smoking has consistently been associated with earlier menopause in epidemiologic studies (USDHHS 1990). 

The report found that smokers experience menopause 

1 to 2 years earlier than nonsmokers and that the consistency of study findings and evidence for a dose-response 

relationship supported a causal association. The report 

also noted that the age of menopause in former smokers 

appeared to be closer to that in never smokers than in 

current smokers, suggesting that the effects of smoking 

on age at menopause may be at least partially reversible 

(USDHHS 1990). The data at that time were found to be 

limited, however, with few studies examining the duration 

of cessation or lifetime tobacco exposure.

The 2001 Surgeon General’s report found that 

smoking was consistently associated with a 1-  to 2-year 

decrease in age at natural menopause and concluded 

that smokers have a younger age at natural menopause 

than nonsmokers (USDHHS 2001). Possible mechanisms addressed in that report included exposure of the 
A Report of the Surgeon General

394 Chapter 4

ovaries to toxic components in tobacco smoke (animal 

studies suggest that tobacco smoke may cause follicular 

atresia) and the effects of nicotine on the metabolism of 

sex hormones. Although the report did not draw conclusions on smoking cessation, it did summarize studies that 

included former smokers (USDHHS 2001); those studies 

had mixed results. 

Just over a decade after the 2001 Surgeon General’s 

report, a meta-analysis of 11  papers published between 

1997 and 2009 (comprising about 50,000 women) found 

that smoking was significantly associated in all the studies 

with earlier age at natural menopause (Sun et al. 2012). 

After adjustment for heterogeneity, the OR for onset of 

earlier menopause was 0.67  (95%  CI, 0.61–0.73), and 

menopause was estimated to take place an average of 

approximately 1  year earlier in smokers compared with 

nonsmokers. Results from some of the studies supported 

the notion that the timing of menopause may be dependent on the amount of cigarettes smoked and/or the duration of smoking. Kinney and colleagues (2006) analyzed 

longitudinal data from almost 500 women and found that 

a change in age of menopause was observed only among 

active smokers who smoked more than 14  cigarettes 

per day or who had accumulated at least 20 pack-years. 

Those authors found no association between menopause 

and previous smoking, even among women who had 

smoked more than 14  cigarettes per day, smoked more 

than 10 pack-years, or who had quit smoking within the 

past decade (Kinney et  al. 2006). Similarly, Blanck and 

colleagues (2004) found that in a study of 874  women, 

menopause came earliest among current smokers who 

started smoking in their teens, smoked at least 20 cigarettes per day, smoked for 10 to 19 years, or had at least 

10 pack-years. Former smokers and never smokers did not 

differ in time to menopause, however, even after adjusting 

for number of term pregnancies and education (Blanck 

et al. 2004). 

In a study of more than 5,500 women, Van Asselt and 

colleagues (2004) found that although there was a significant association between current smoking and earlier age 

of menopause (rate ratio = 1.41; 95% CI, 1.32–1.50), there 

was no association with former smoking (rate ratio = 0.95; 

95% CI, 0.89–1.02). The latter was true regardless of the 

number of years since cessation. In a more recent study 

of more than 2,000  women, Mikkelsen and colleagues 

(2007) found that—after adjusting for marital status, education level, social participation, health status, and coffee 

consumption—women who stopped smoking more than 

10 years before menopause were significantly less likely to 

have an early menopause (<45 years of age) (aOR = 0.13; 

95%  CI, 0.05–0.36) than women who were current 

smokers (aOR = 1.59; 95% CI, 1.11–2.28). Finally, in one 

of the few longitudinal studies of smoking status and 

menopause, Hayatbakhsh and colleagues (2012) followed 

more than 3,500 Australian women and found that women 

smoking at the 21-year follow-up were 61% more likely to 

experience menopause before 45 years of age than women 

who had never smoked (adjusted hazard ratio [HR] = 1.61; 

95%  CI, 1.27–2.04), even after adjusting for education, 

ethnicity, BMI, use of oral contraceptives, and gravidity. 

Those who quit smoking before the 14-year follow-up 

assessment had a risk of early menopause that was the 

same as that of never smokers, while those who quit later 

(between 14 and 21 years of follow-up) may have been at 

increased risk (HR  =  1.36; 95%  CI, 0.89–2.07). Among 

those smoking at the 14-year follow-up, only smoking 

more than 20 cigarettes per day was significantly associated with early menopause. 

Menopause is associated with the exhaustion of the 

ovarian follicular pool (Vermeulen 1993; Hacker et  al. 

2015), and it has been hypothesized that smoking could 

alter the timing of menopause by hastening the decline of 

ovarian reserves. Evidence for this pathway (Richardson 

et al. 2014) includes studies demonstrating an increased 

concentration of follicular-stimulating hormone (FSH) 

in smokers compared with nonsmokers (Cooper et  al. 

1995) and a reduced number of oocytes retrieved in IVF 

cycles in smokers compared with nonsmokers (Zenzes 

et al. 1997; El-Nemr et al. 1998; Fuentes et al. 2010). The 

mechanisms underlying the potential effects of tobacco 

smoke on ovarian reserves are not well understood, but 

they could include direct effects on gametes or effects on 

ovarian vascularization (Richardson et al. 2014). A mechanism involving depletion of ovarian reserves would likely 

result in an irreversible effect on age at menopause. 

It has also been hypothesized that antiestrogenic 

effects of environmental toxicants, such as those found 

in tobacco smoke, could contribute to earlier age at 

menopause (Gu et al. 2013). Potential pathways include 

inhibition of estrogen biosynthesis, induction of the 

2-hydroxylation pathway, and competitive binding of 

estrogen receptors or sex hormone-binding globulin 

(Baron et al. 1990). Gu and colleagues (2013), who used 

luteal phase urine samples from 603  premenopausal 

women in the Nurses’ Health Study  II to study specific 

pathways, found lower total estrogen and estrogen metabolites and parent estrogens in current smokers compared 

with never smokers (with statistically significant differences for estradiol), suggesting that cigarette smoking 

reduces the biosynthesis of estrogen and induces estrogen 

metabolism. No differences were seen in levels of individual estrogen metabolites, metabolic pathway groups, 

or  pathway ratios between never and former smokers 

(most of whom had quit more than 5 years earlier), suggesting that the effects of smoking on estrogen biosynthesis may be reversible. The authors were unable to 
The Health Benefits of Smoking Cessation 395

Smoking Cessation

examine whether components of tobacco smoke bind 

estrogen receptors or sex hormone-binding globulin.

Summary of the Evidence

The 2001 Surgeon General’s report found that 

“[w]omen smokers have a younger age at natural menopause than do nonsmokers and may experience more 

menopausal symptoms” (USDHHS 2001, p.  14). Several 

papers published since the 2001 report provide additional evidence that active smoking results in earlier age 

at menopause. Several of these recent papers also examined risk in former smokers and found no evidence of earlier age at menopause, suggesting that the mechanisms 

through which smoking affects age at menopause are at 

least partially reversible. However, uncertainty remains 

regarding the role of the duration and amount of smoking 

in former smokers, and these variables were categorized 

differently across studies. Therefore, the evidence is suggestive but not sufficient to conclude that cessation 

reduces the risk of earlier menopause compared with continued smoking, and uncertainty remains regarding the 

contributions to the risk of earlier menopause of age at 

cessation, the number of years smoked, the number of 

cigarettes smoked per day, and the number of pack-years 

smoked in former smokers. 

Male Reproductive Health

Fertility and Sperm Quality

The 1990 Surgeon General’s report found few 

studies about sperm quality after smoking cessation, and 

those studies had serious limitations (USDHHS 1990). 

The 2004 Surgeon General’s report concluded that the 

evidence was inadequate to infer the presence or absence 

of a causal relationship between active smoking and sperm 

quality, but the evidence did suggest that smokers have 

decreased semen volume and increased abnormal morphologic forms (USDHHS 2004). The clinical relevance of 

these findings, however, was uncertain. The 2010 Surgeon 

General’s report, which also reviewed sperm quality and 

male fertility, noted that studies conducted after the 2004 

report strengthened the evidence that smoking affects 

semen quality and fertility (USDHHS 2010). The 2010 

report reviewed potential mechanisms, including alterations in the hormonal milieu, effects on the sperm plasma 

membrane, and damage to DNA and/or chromosomes in 

sperm. The report also noted that (a) studies designed to 

address the timing of exposure in relation to the maturation of sperm cells had not been conducted and (b)  the 

effects of tobacco smoke on spermatogonial stem cells 

could cause long-term effects that could persist after 

smoking cessation, while effects on both epididymal sperm 

and mature sperm could be reversible (USDHHS 2010). 

The report also noted that studies examining hormone 

levels in male smokers and nonsmokers found inconsistent results and variation in how obesity was considered (obesity is associated with the conversion of androgens to estrogen) and in the type of circulating hormones 

studied (free or bioavailable levels). The report found consistent evidence linking smoking in men to chromosomal 

changes and DNA damage in sperm, which affects male 

fertility, pregnancy viability, and anomalies in offspring. 

Among the studies published after the 2010 Surgeon 

General’s report was a meta-analysis of 20  studies comprising more than 5,800 men, with the authors’ finding 

that cigarette smoking was associated with reduced sperm 

count, lower motility, and changes in morphology (Sharma 

et al. 2016). Elsewhere, in a small study of 136 men that 

excluded those with known infertility, levels of testosterone, luteinizing hormone, and prolactin were higher in 

smokers (≥5 cigarettes/day) than never smokers, but there 

were no differences in these measures between former 

smokers and never smokers (Blanco-Munoz et al. 2012). 

In another study, Santos and colleagues (2011) evaluated 

sperm quality after participation in a 3-month smoking 

cessation program. A man in the study had smoked about 

30 cigarettes per day for about 13 years and had secondary 

infertility. The monitoring found an improvement in his 

sperm count (from 28.6  to 72.2  million/ejaculate) and 

motility (32.7% to 78.8%) but no changes in sperm DNA 

fragmentation, number of germinal cells, or morphology. 

In addition, the percentage of sperm tails increased with 

tyrosine-phosphorylated proteins and the number of rapid 

spermatozoa recuperated after an enrichment technique, 

suggesting that the transduction signals necessary for 

proper motility and capacitation were improved. Finally, 

a study of rats found that both the motility and amount 

of sperm decreased significantly with exposure to nicotine, and that this was accompanied by reduced fertility; 

declines were ameliorated by the cessation of nicotine 

exposure in the male rats (Oyeyipo et al. 2011). 

Summary of the Evidence

Little new evidence published since the 2010 

Surgeon General’s report has addressed whether the 

effects of smoking on male fertility and sperm quality are 

reversible with cessation. Therefore, the evidence is inadequate to determine whether smoking cessation reduces 

the effects of smoking on male fertility and sperm quality. 

Erectile Dysfunction

“Erectile dysfunction” (ED) is defined as the persistent inability of a male to attain and maintain an erection 
A Report of the Surgeon General

396 Chapter 4

adequate for satisfactory sexual performance (National 

Institutes of Health Consensus Development Panel on 

Impotence 1993). Using data from the National Health 

and Nutrition Examination Survey of 2001–2002, Selvin 

and colleagues (2007) estimated that 18.4% of U.S. men 

20 years of age or older had ED, or 18 million nationwide. 

Globally, 322 million men may be affected by the year 2025. 

The 1990 Surgeon General’s report found that 

smoking may be associated with impaired male sexual performance, but because the data were limited, no conclusions could be drawn regarding the relationships between 

smoking cessation and sexual performance or the surrogate 

penile brachial index, which is calculated as the systolic 

blood pressure in the penis divided by the systolic blood 

pressure in the arm (USDHHS 1990). The 2014 Surgeon 

General’s report found the evidence sufficient to infer a 

causal relationship between smoking and ED. This conclusion was on the basis of consistent findings of smoking as a 

risk factor for ED across both cross-sectional and prospective population-based cohort studies. These studies confirmed the appropriate temporality of the association and 

evidence of a dose-response relationship between the magnitude of the risk and the level of exposure. Potential mechanisms were also reviewed in the 2014 Surgeon General’s 

report and included the effects of nicotine on the dynamics 

of blood flow required for erection (nicotine induces vasospasm in the penile arteries); formation of atherosclerotic lesions in the penile arteries; degenerative changes 

in the penile tissue, such as decreases in smooth muscle, 

sinusoidal endothelium, nerve fibers and capillaries, and 

increased collagen density; reduced endothelium-derived 

production of nitric oxide in the vasculature of the penis; 

adverse effects on vascular medial elastic fibers; and oxidative injury due to the production of superoxide radicals in 

the cavernosal smooth muscle cells (USDHHS 2014).

The 2014 Surgeon General’s report also addressed 

smoking cessation, although that report did not draw 

related conclusions. The report reviewed selected 

results from two population-based studies (the Vietnam 

Experience Study of 1985–1986 and the prospective 

Massachusetts Male Aging Study) against findings that 

smoking cessation leads to recovery of erectile function (Mannino et al. 1994; Feldman et al. 2000; USDHHS 

2014). However, the Massachusetts Male Aging Study, 

which followed quitters for nearly 9 years, did not show 

evidence that the incidence of ED was reduced after cessation (Feldman et  al. 2000). In that study, however, 

participants had started smoking at an early age (mean 

age:  16.6  years) and had a substantial lifetime exposure 

(mean pack-years: 39.4), so that results could not be generalized to populations with lower levels of tobacco exposure (Feldman et al. 2000). Notably, a separate analysis of 

the Massachusetts Male Aging Study found that cessation 

appeared to protect against the progression of ED but had 

little effect on remission (Travison et al. 2007). 

Experimental studies of the acute effects of shortterm smoking cessation reviewed in the 2014 Surgeon 

General’s report show that cessation may result in 

improvements in erectile function. For example, Glina 

and colleagues (1988), who monitored intracavernous 

pressure after pharmacologic stimulation in 12 smokers 

on a day of abstinence and after smoking two cigarettes, 

found that all participants obtained an erection on days 

of abstinence, but only four smokers did so on days of 

smoking cigarettes (Glina et  al. 1988). Later, Sighinolfi 

and colleagues (2007), who studied 20  chronic smokers 

with ED using penile color Doppler ultrasonography after 

pharmacostimulation at baseline and after 24 to 36 hours 

of abstinence from smoking, also achieved positive results. 

At baseline, 50% of these smokers had abnormal peak systolic velocity and 75% had abnormal end diastolic velocity, 

but at 24 to 36 hours, none had abnormal peak systolic 

velocity and just 15% had abnormal end diastolic velocity. 

Finally, in a sample of 10  current, long-term smokers, 

cessation for 24  hours significantly improved nocturnal 

penile tumescence and rigidity (Guay et al. 1998).

Table 4.38 presents seven cross-sectional studies of 

risk of ED in former smokers that were not reviewed in the 

2014 Surgeon General’s report. Six of the seven studies 

found a higher prevalence of ED among both former and 

continuing smokers (range in aOR for former smokers 

relative to never smokers: 1.3–2.15) (Bortolotti et al. 2001; 

Mirone et al. 2002; Safarinejad 2003; Austoni et al. 2005; 

Chew et al. 2009), but the associations for both former and 

current smokers did not reach significance in one study 

(Shiri et al. 2005). One study reported an aOR of less than 

1.0 for former smokers (Lam et al. 2006), but this result 

was not statistically significant. 

In a study of 1,580 men, Chew and colleagues (2009) 

found that both former and current smokers were at 

higher risk of ED compared with never smokers (overall 

aOR = 1.3 and 1.6, respectively, adjusted for age and symptomatic cardiovascular disease, including hypertension, 

ischemic heart disease, peripheral arterial disease, and 

stroke), but by age group, associations between former 

or current smoking and ED were significant only among 

men 50  years of age and older. Similarly, in a study of 

2,010 men, Mirone and colleagues (2002) found that current smokers and former smokers had similar aORs for ED 

(1.7 and 1.6, respectively, adjusted for age and education); 

those researchers also found that smoking for more than 

20 years increased the odds of ED compared with smoking 

for 20 years or less (aOR = 1.6 and 1.2, respectively). The 

increased risk was limited to current and former smokers 

without chronic medical conditions (aOR  =  1.7–2.4 for 

current smokers without medical conditions, 0.4–1.2 for 
Studya Design/population Reference Results: Adjusted OR (95% CI) Comments

Bortolotti et ak,

(2001)

•

•

•

•

•

Cross-sectional

Men with diabetes

n = 9,670

1996

Italy

Never smokers 



Former smokers: 1.5 (1.3–1.6)b

Current smokers: 1.4 (1.3–1.6)b

Former smoker if quit more 

than 1 year before survey; 

adjusted for age

Mirone et al. 

(2002)

• Cross-sectional

• n = 2,010

• 1996–1997

• Italy

Never smokers  Former smokers: 1.6 (1.1–2.3)b

 Current smokers: 1.7 (1.2–2.4)b

Former smoker if quit 

more than 1 year before 

survey; adjusted for age 

and education

Safarinejad 

(2003)

•

•

•

•

• I

Population-based, cross-sectional

Men 20–70 years of age

n = 2,444

Year: Not reported

ran

Never smokers 



Former smokers: 2.15 (1.38–3.1)b

Current smokers: 2.41 (1.52–3.30)b

Adjusted for age

Austoni et al. 

(2005)

• Cross-sectional

• Men attending free andrologic 

consultations

• n = 16,724

• 2001–2002

• Italy

Never smokers  Former smokers:

– Overall: 1.3 (1.2–1.5)b

– Smoked <10 years: 1.0 (0.6–1.7)

– Smoked 10–20 years: 1.2 (0.8–1.8)

– Smoked >20 years: 2.0 (1.3–2.0)b

 Current smokers:

– <10 cigarettes/day: 1.0 (0.9–1.2)

– ≥10 cigarettes/day: 1.4 (1.2–1.5)b

– Smoked <10 years: 1.1 (0.7–1.6)

– Smoked 10–20 years: 1.7 (1.2–2.3)b

– Smoked >20 years: 1.6 (1.3–2.0)b

Former smoker if quit 

more than 1 year before 

survey; adjusted for age, 

marital status, education, 

BMI, physical activity, 

and chronic diseases

Shiri et al. 

(2005)

•

•

•

•

•

Population-based, cross-sectional 

analysis within prospective cohort

Men 50, 60, or 70 years of age in 1994

n = 1,442

1994

Finland

Never smokers 



Former smokers: 1.3 (0.9–1.8)

Current smokers: 1.4 (0.9–2.2)

Adjusted for age, education, 

marital status, and alcohol 

consumption

Lam et al. 

(2006)

• Population-based, cross-sectional

• Men 31–60 years of age

• n = 819

• 2001

• Hong Kong

Never smokers  Former smokers: 0.93 (0.60–1.45)

 Current smokers:

– <20 cigarettes/day: 1.02 (0.69–1.51)

– ≥20 cigarettes/day: 1.47 (1.00–2.16)b

Erectile dysfunction defined 

as sexual dissatisfaction 

and/or erectile difficulty; 

adjusted for age

Table 4.38 Studies on smoking cessation and erectile dysfunction 

The Health Benefits of Smoking Cessation 397
Studya Design/population Reference Results: Adjusted OR (95% CI) Comments

Chew et al. 

(2009)

•

•

•

•

Population-based, cross-sectional

n = 1,580

2001–2002

Australia

Never smokers  Former smokers:

–

–

–

–

–

–

Overall: 1.33 (0.95–1.87)

Quit ≤5 years: 1.22 (0.67–2.22)

Quit 6–10 years: 2.26 (1.09–4.70)b

Quit >10 years: 1.32 (0.92–1.89)

<50 years of age: 1.18 (0.61–2.31)

≥50 years of age: 2.56 (1.42–4.58)b

 Current smokers:

–

–

–

–

–

–

Overall: 1.57 (1.02–2.42)b

1–10 cigarettes/day: 1.30 (0.69–2.44)

11–20 cigarettes/day: 1.69 (0.79–3.64)

>20 cigarettes/day: 1.57 (0.74–3.34)

<50 years of age: 0.82 (0.40–1.69)

≥50 years of age: 1.47 (0.99–2.18)

Adjusted for age and 

symptomatic cardiovascular 

disease, including 

hypertension, ischemic 

heart disease, peripheral 

arterial disease, and stroke

Table 4.38 Continued

A Report of the Surgeon General

398 Chapter 4

Notes: BMI = body mass index; CI = confidence interval; OR = odds ratio. aMeasure of association adjusted for covariate(s).

bp <0.05.
The Health Benefits of Smoking Cessation 399

Smoking Cessation

current smokers with medical conditions; and aOR = 1.4–

1.7 for former smokers without medical conditions, 0.4–

1.2 for former smokers with medical conditions). Among 

former smokers, the risk of ED was not clearly associated 

with the number of years since cessation. 

In a large study with more than 16,000 participants, 

Austoni and colleagues (2005) found associations between 

smoking and ED that were similar for current smokers 

smoking more than 10  cigarettes per day and former 

smokers compared with never smokers (aOR = 1.4; 95% CI, 

1.2–1.5, and aOR  =  1.3; 95%  CI, 1.2–1.5, respectively, 

adjusted for age, marital status, education, BMI, physical 

activity, and chronic diseases). There was no increased risk 

for men who smoked 10 or fewer cigarettes per day, but 

the risk of ED increased with duration of smoking for both 

current and former smokers. When stratified by the presence or absence of medical conditions (hypertension, cardiovascular disease, diabetes, and hypercholesterolemia), 

aORs were similar for those with and without each condition in former smokers, and all associations were significant except for former smokers with hypercholesterolemia 

(aOR = 1.2; 95% CI, 0.9–1.6). Earlier, in a sample of nearly 

10,000 men with diabetes, Bortolotti and colleagues (2001) 

found that both former smokers and current smokers had 

a higher risk of ED relative to never smokers (aOR = 1.5; 

95% CI, 1.3–1.6 and aOR = 1.4; 95% CI, 1.3–1.6, respectively, results adjusted for age). Increased time since cessation was not clearly associated with reduced risk of ED 

among former smokers. 

In a prospective study of more than 1,400  men 

50–75 years of age, Shiri and colleagues (2005) observed 

elevated but nonsignificant aORs for ED among former 

and current smokers at baseline (1.3; 95% CI, 0.9–1.8, and 

1.4; 95% CI, 0.9–2.2, respectively, adjusted for age, education, marital status, and alcohol consumption) but did 

not find a dose-response relationship in current smokers 

with duration of smoking or in former smokers with the 

number of years of smoking (not shown in table). In a 

follow-up survey conducted 5  years later, spontaneous 

recovery was not significantly associated with being a 

former smoker (aOR = 0.7; 95% CI, 0.3–1.3). When the 

sample was limited to men without ED at baseline in 1994, 

smokers who developed vascular disease by 1999 had a 

3-fold greater risk of developing ED by 2004 (adjusted

incidence density ratio = 3.1; 95% CI, 1.3–7.5; covariates

included age, education, marital status, diabetes, depression, BMI, and alcohol consumption) compared with men

who never smoked and did not develop vascular disease

(men included in the final model were not specified) (Shiri

et al. 2006). In contrast, smokers who did not develop vascular disease did not have an increased risk of ED. Former

smokers were not at increased risk for ED, independent of

vascular disease. Finally, in a prospective study of almost

300  smokers seeking smoking cessation services who 

reported having symptoms of ED with onset more than 

5 years after initiating smoking, Pourmand and colleagues 

(2004) found that at 1-year follow-up, ED status improved 

by at least one grade in 25% of former smokers but 

such improvement was not observed among continuing 

smokers (results of statistical testing not presented). 

Summary of the Evidence

Cross-sectional studies consistently found that 

former smokers had an increased prevalence of ED relative to never smokers, and in some instances, prevalence 

was similar to that of current smokers. In contrast, results 

of prospective studies were mixed, with some showing no 

increased risk of ED in former smokers compared with never 

smokers, and others showing increased risk. Experimental 

studies of short-term cessation suggest that such cessation 

is associated with acute improvements in erectile function. 

Limited data suggest that smoking contributes to ED at 

least in part through its effects on the risk of vascular disease. Smoking likely has both reversible (such as nicotineinduced vasospasm of penile arteries) and irreversible (such 

as degenerative tissue changes) effects on erectile function, 

complicating interpretation of data across different study 

designs. Changes in risk of ED by duration or intensity of 

smoking could further complicate the interpretation of 

data. Therefore, the evidence is inadequate to determine 

whether smoking cessation reduces the risk of ED compared with continued smoking. The evidence is suggestive 

but not sufficient to conclude that former smokers are at 

increased risk of ED compared with never smokers.

Synthesis of the Evidence

Smoking has diverse adverse effects on the reproductive health of females and males. This review has 

found numerous health benefits of cessation for women 

and their fetuses and newborns. For males, evidence of 

the reproductive health benefits (e.g.,  enhancing sperm 

quality and functionality, avoiding erectile dysfunction) of 

cessation is more limited. 

Conclusions

1. The evidence is sufficient to infer that smoking cessation by pregnant women benefits their health and

that of their fetuses and newborns.

2. The evidence is inadequate to infer that smoking

cessation before or during early pregnancy reduces
A Report of the Surgeon General

400 Chapter 4

the risk of placental abruption compared with continued smoking. 

3. The evidence is inadequate to infer that smoking 

cessation before or during pregnancy reduces the 

risk of placenta previa compared with continued 

smoking.

4. The evidence is inadequate to infer that smoking 

cessation before or during pregnancy reduces the 

risk of premature rupture of the membranes compared with continued smoking. 

5. The evidence is inadequate to infer that smoking 

during early or mid-pregnancy alone, and not during 

late pregnancy, is associated with a reduced risk of 

preeclampsia. 

6. The evidence is sufficient to infer that women who 

quit smoking before or during pregnancy gain more 

weight during gestation than those who continue 

to smoke. 

7. The evidence is suggestive but not sufficient to infer 

that women who quit smoking before or during 

pregnancy gain more weight during gestation than 

nonsmokers.

8. The evidence is inadequate to infer that smoking 

cessation during pregnancy increases the risk of 

gestational diabetes. 

9. The evidence is sufficient to infer that smoking 

cessation during pregnancy reduces the effects of 

smoking on fetal growth and that quitting smoking 

early in pregnancy eliminates the adverse effects of 

smoking on fetal growth. 

10. The evidence is inadequate to determine the gestational age before which smoking cessation should 

occur to eliminate the effects of smoking on fetal 

growth. 

11. The evidence is sufficient to infer that smoking cessation before or during early pregnancy reduces the 

risk for a small-for-gestational-age birth compared 

with continued smoking. 

12. The evidence is suggestive but not sufficient to infer 

that women who quit smoking before conception or 

during early pregnancy have a reduced risk of preterm delivery compared with women who continue 

to smoke. 

13. The evidence is suggestive but not sufficient to infer 

that the risk of preterm delivery in women who quit 

smoking before or during early pregnancy does not 

differ from that of nonsmokers. 

14. The evidence is inadequate to infer that smoking cessation during pregnancy reduces the risk of stillbirth. 

15. The evidence is inadequate to infer that smoking 

cessation during pregnancy reduces the risk of perinatal mortality among smokers. 

16. The evidence is inadequate to infer that women who 

quit smoking before or during early pregnancy have 

a reduced risk for infant mortality compared with 

continued smokers.

17. The evidence is inadequate to infer an association 

between smoking cessation, the timing of cessation, 

and female fertility or fecundity.

18. The evidence is suggestive but not sufficient to infer 

that smoking cessation reduces the risk of earlier age 

at menopause compared with continued smoking.

19. The evidence is inadequate to infer that smoking 

cessation reduces the effects of smoking on male 

fertility and sperm quality.

20. The evidence is suggestive but not sufficient to infer 

that former smokers are at increased risk of erectile 

dysfunction compared with never smokers. 

21. The evidence is inadequate to infer that smoking 

cessation reduces the risk of erectile dysfunction 

compared with continued smoking.

Implications

As with previous reports, the evidence presented in 

this section reaffirms that cigarette smoking cessation 

before and during pregnancy reduces the adverse effects 

of smoking on fetal growth, including risk for being small 

for gestational age and low birth weight. The timing of the 

cessation and its beneficial effects are consistent with fetal 

growth patterns, which accelerate during the third trimester; thus, quitting early in pregnancy obviates the birth 

weight reduction that results from smoking throughout 

pregnancy. The evidence also suggests that smoking cessation may reduce the risk of other adverse outcomes, 

including placental abruption, preterm delivery, stillbirth, 

and early menopause. If smoking cessation reduces the 
The Health Benefits of Smoking Cessation 401

Smoking Cessation

risk of such pregnancy complications as placental abruption and preterm delivery, then reductions in such downstream outcomes as stillbirths and perinatal and neonatal 

mortality would also be expected. More research on the 

timing of cessation with respect to pregnancy onset is 

needed to determine how to maximize improvements in 

pregnancy outcomes for women and infants.

Prenatal smoking cessation has substantial health 

benefits for mothers and offspring, but the evidence summarized in this section also provides some support that 

selected adverse outcomes might also be increased with 

smoking cessation. For example, increased gestational 

weight gain associated with cessation could potentially 

increase the percentage of women who exceed recommended gestational weight gain and experience associated complications, while simultaneously reducing the 

percentage of women with inadequate weight gain. 

Potential unintended consequences, such as excess weight 

gain, should be considered when implementing smoking 

cessation interventions for pregnant women. Such interventions could, for example, incorporate weight management programs for at-risk women. 

The evidence related to cessation and reduced fertility in men and women remains mixed and inconclusive, 

and our understanding of the mechanism(s) underlying 

these effects is limited, especially for women. Further 

research is needed to determine whether and when in the 

life course cessation of smoking needs to occur to benefit female and male fertility. Such evidence is needed so 

that the appropriate information can be communicated 

to patients and providers so that interventions can be 

tailored accordingly.
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