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Office of the Surgeon General (US); Office on Smoking and Health (US). The Health Consequences of Smoking: A Report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention (US); 2004.

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The Health Consequences of Smoking: A Report of the Surgeon General.

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6Other Effects

Introduction

This chapter addresses evidence on smoking and health effects over a range of specific diseases and non-specific but adverse consequences. The associations reviewed appear to reflect both specific and non-specific pathways of injury by tobacco smoke. The evidence indicates that smoking should be considered not only a cause of specific diseases and conditions, but a contributing factor to nonspecific morbidity and a diminished quality of life.

Diminished Health Status

This section focuses on the question of whether cigarette smokers have poorer health in comparison with nonsmokers, beyond the already well-characterized burden of morbidity and mortality from the specific diseases caused by smoking. The hypothesis that smoking might impair health in general draws plausibility from the toxicologic richness of tobacco smoke, the well-documented systemic distribution of tobacco smoke components and metabolites, and the effects on host defenses, including the immune system. Additionally, impairment of organ function short of the level at which clinical disease is diagnosed may leave the smoker vulnerable to otherwise well-tolerated threats to health. For example, the reduction of lung function found in many smokers who do not have overt chronic obstructive pulmonary disease (COPD) may increase the risk for developing a more severe illness with a respiratory infection, or having a respiratory complication following surgery.

This section reviews studies that have addressed a number of health status indicators (Figure 6.1) including direct reports of health status or responses to an instrument that provides a health status index, and indirect indicators such as medical services utilization data. When interpreting the findings of these studies, consideration needs to be given to the potential causal pathways linking smoking to a poor health status, the assessment and measurement of health status, and the potential for biases, such as from confounding, to affect associations of smoking with these outcome measures.

Figure 6.1. A conceptual model for the relationship between cigarette smoking and diminished health status.

Figure 6.1

A conceptual model for the relationship between cigarette smoking and diminished health status.

For the diseases caused by smoking, direct causal pathways are implicit. For example, substantial evidence supports the hypothesis that smoking causes lung cancer through the direct deposition of tobacco smoke carcinogens in the respiratory tract. For some of the outcome measures considered in this section, pathways are far less certain and may be both direct and indirect. Increased absenteeism might reflect, for example, the tendency of smokers to have more severe respiratory illnesses than nonsmokers, possibly attributable to the effects of smoking on respiratory defenses or because smokers tend to have a lower level of lung function.

The outcomes considered in this section have multiple determinants. Health status itself is an integrative measure reflecting the net consequences of the many varied factors that determine health and well-being. To the extent that smokers differ from non-smokers in these factors, there is a potential for confounding to distort associations of smoking with the outcome measures. Studies show, for example, that smokers and nonsmokers differ in aspects of lifestyle and in their approaches to health care (e.g., the use of preventive services such as multiphasic testing [Oakes et al. 1974] and screening [Beaulieu et al. 1996; Edwards and Boulet 1997]). Additionally, the suite of relevant confounding factors may differ from outcome to outcome, and for some outcomes there is uncertainty as to the relevant confounding factors. Some of the individual characteristics that affect the decision to start smoking and to continue to smoke also may be determinants of risk for the outcomes considered here.

Conclusions of Previous Surgeon General’s Reports

Extensive research over time has identified cigarette smoking as a cause of specific diseases, and many reports from the Surgeon General have focused on smoking and these diseases. These reports have also addressed more general and nonspecific adverse consequences of smoking, such as increased rates of absenteeism from work or the utilization of medical services among smokers in comparison with nonsmokers. Conclusions from the reports that relate to these outcomes are listed in Table 6.1, including findings on general respiratory morbidity. Reports of increased morbidity from common and frequent viral and bacterial respiratory infections among smokers have been reviewed (U.S. Department of Health and Human Services [USDHHS] 1990) and are among the topics covered in Chapter 4 of this report. However, the overall health status of smokers compared with nonsmokers has not been comprehensively addressed in prior Surgeon General’s reports.

Table 6.1. Conclusions from previous Surgeon General’s reports concerning smoking as a cause of diminished health status and respiratory morbidity.

Table 6.1

Conclusions from previous Surgeon General’s reports concerning smoking as a cause of diminished health status and respiratory morbidity.

Biologic Basis

Cigarette smoke, inhaled through the mouth into the lungs, reaches lung airways and alveoli, where the tobacco smoke components pass into the systemic circulation (Murray 1986). The airways and alveoli themselves are exposed to the gaseous and particulate components of tobacco smoke as many of these components readily pass through the alveolar-capillary membrane into the alveolar capillaries and then circulate throughout the body. Nicotine, for example, which is among these components, reaches the brain within 10 seconds after smoke is inhaled (USDHHS 1988). It is distributed throughout the body and has been found in breast milk (Schwartz-Bickenbach et al. 1987; Schulte-Hobein et al. 1992; Golding 1997) and in cervical mucus (Prokopczyk et al. 1997). Carbon monoxide, a diffusible gas, moves from the alveoli into the capillaries where it binds tightly to the hemoglobin of the red blood cells. Benzo[a]pyrene, a well-characterized carcinogen in tobacco smoke, can be found bound to the blood cells in the epithelial cells of the airways of smokers and in their major organs. The effects of smoking on host defenses and aspects of immune function have been covered in prior reports (USDHHS 1990, 1994) and again in this report. These effects may have the consequence of increasing risks for infections, whether of the respiratory tract or other organs. However, there has been less research to date on infections beyond those of the respiratory tract. This systemic distribution of tobacco smoke components underlies the associations between smoking and disease that are well documented for many organs including cardiovascular disease, stroke, and cancers of the kidney and urinary bladder. The widespread distribution may also lead to more general effects on health.

This same systemic distribution may have non-specific effects as well, contributing to a reduction in health status. Exposure to tobacco smoke components causes smoke-specific diseases such as bladder cancer (carcinogens in urine come in contact with the bladder) and atherosclerosis, probably reflecting multiple underlying mechanisms with inflammation having a central role (Cross et al. 1999). Underlying mechanisms might include heightened oxidative stress and reduced antioxidant defenses, increased inflammatory activity, reduced host defenses against infection, and lowered reparative capacities of tissues. The evidence on these mechanisms is at varying levels of development. This section focuses on oxidative stress as an example, selected because the available literature is extensive.

Oxidative Stress

Oxidative stress refers to an increased exposure to oxidants and/or a decreased antioxidant capacity, caused by oxygen radicals that mutate DNA, promote atherosclerosis, and lead to chronic lung injury. Oxidative stress is now hypothesized to be a general mechanism underlying aging and many of the chronic diseases associated with aging, contributing to the development of cancer, cardiovascular disease, and COPD (Ames et al. 1995). Mounting evidence points to chronic oxidative stress as one mechanism whereby smoking affects health. Smoking is associated with evidence of chronic systemic inflammation, perhaps a consequence of the chronic oxidative stress experienced by the smoker (Cross et al. 1999; Hecht 1999). The oxidant load posed by cigarette smoke is substantial; the tar component is estimated to contain 1018 oxygen radicals per gram of tar and the gas component to have as many as 1015 other organic radicals per puff (Repine et al. 1997).

A number of comparisons between smokers and nonsmokers have been made with respect to measures of biomolecular oxidative damage, including oxidative injury to DNA, proteins, and lipids. A widely used assay for quantifying oxidative damage to DNA is 8-hydroxydeoxyguanosine (8-OH-dG). The assay measures hydroxyl radical-induced DNA damage at C8 of guanine (Lagorio et al. 1994), which has been linked experimentally to cigarette smoke condensate (Leanderson and Tagesson 1990). Cultured human lung cells exposed to cigarette smoke had 70 percent higher 8-OH-dG levels than unexposed cells (Leanderson and Tagesson 1992). DNA from the lung tissue of smokers had 42 percent higher 8-OH-dG levels than the DNA from nonsmokers, and 8-OH-dG concentrations increased according to the number of cigarettes smoked per day (Asami et al. 1997).

Studies comparing 8-OH-dG levels in DNA from smokers and nonsmokers are summarized in Table 6.2. In general, regardless of the biologic material, smokers tend to have greater damage. A strong dose-response association with the number of cigarettes smoked was observed in one study (Lodovici et al. 2000), but an inverse dose-response trend was observed in another (van Zeeland et al. 1999). When levels of 8-OH-dG in circulating lymphocytes were compared before and after cigarettes were smoked, Kiyosawa and colleagues (1990) observed that 8-OH-dG levels increased 54 percent after smoking. A similar but less frequently used approach to determine biomolecular oxidative damage is to assay 8-hydroxyguanine, which has been found in leukocyte DNA (Asami et al. 1997) and in urine (Suzuki et al. 1995) of smokers at concentrations at least 90 percent higher than in nonsmokers.

Table 6.2. Studies on the association between smoking and oxidative injury.

Table 6.2

Studies on the association between smoking and oxidative injury.

Oxidative damage to proteins can occur in both amino acid residues and the peptide backbone in protein, and can be assessed by assaying protein carbonyls (Reznick et al. 1992; Eiserich et al. 1995). Studies document that exposing human plasma (Reznick et al. 1992; Eiserich et al. 1995; Panda et al. 1999) or saliva (Nagler et al. 2000) to cigarette smoke increased protein carbonyl concentrations by more than 300 percent. Compared with unexposed guinea pigs, guinea pigs exposed to cigarette smoke had plasma protein carbonyl concentrations more than 30 times greater (Panda et al. 2000). In humans, protein carbonyl concentrations in 15 smokers were 61 percent higher than in 5 comparison nonsmokers (Lee et al. 1998).

Isoprostanes constitute a specific measure of lipid peroxidation and serve as good general markers of oxidative injury (Morrow and Roberts 1996). Free radicals catalyze the peroxidation of arachidonic acid to F2-isoprostanes (Morrow and Roberts 1996). Circulating (Morrow et al. 1995) and urinary (Morrow et al. 1995; Reilly et al. 1996) isoprostane levels have been shown to be markedly higher in smokers than in non-smokers (Table 6.2). Circulating (Morrow et al. 1995; Pilz et al. 2000) and urinary (Reilly et al. 1996; Pilz et al. 2000) isoprostane concentrations decreased at least 20 percent within two weeks of smoking cessation. Babies of smoking mothers had concentrations of isoprostane levels in their umbilical arteries and veins more than 110 percent higher than babies of nonsmoking mothers (Obwegeser et al. 1999).

Another widely used measure of free radical catalyzed lipid peroxidation is thiobarbituric acid reactive substances (TBARS) (Bonithon-Kopp et al. 1997). Comparisons of TBARS between smokers and nonsmokers have shown that (1) current smokers have higher TBARS levels—sometimes strikingly higher, (2) levels of TBARS rise after smoking, and (3) the influence of smoking on increased lipid peroxidation can be offset somewhat by administering the antioxidant micronutrients vitamins C and E (Table 6.2).

Antioxidant Depletion

Even as smokers are exposed to the oxidative stress of regularly inhaling cigarette smoke, substantial evidence shows that blood levels of individual antioxidant micronutrients are lower in current smokers than in nonsmokers. This association has been clearly demonstrated for vitamin C (McClean et al. 1976; Bolton-Smith et al. 1991; Ross et al. 1995; Lykkesfeldt et al. 1997) and for total and selected carotenoids including α-carotene, β-carotene, and cryptoxanthin (Aoki et al. 1987; Stryker et al. 1988; Bolton-Smith et al. 1991; Pamuk et al. 1994; Ross et al. 1995; Brady et al. 1996; Alberg et al. 2000). For vitamin C (Brook and Grimshaw 1968; Buiatti et al. 1996; Marangon et al. 1998) and several of the specific carotenoids (Comstock et al. 1988; Nierenberg et al. 1989; Buiatti et al. 1996; Marangon et al. 1998), circulating concentrations tend to decline with increasing number of cigarettes smoked.

Whether the differences in antioxidant levels across smoking categories reflect direct depletion or differing dietary intake has been controversial. If smoking directly depletes antioxidant micronutrients, the effect would presumably be acute. In fact, levels of vitamin C and selected carotenoids increased when measured in persons after 84 hours without smoking a cigarette (Brown 1996), and an experimental exposure of plasma equivalent to six puffs of cigarette smoke completely depleted the ascorbic acid present in the serum (Handelman et al. 1991; Eiserich et al. 1995). When measurements were taken at baseline and 20 minutes after smoking a cigarette, decreases in circulating micronutrient concentrations were observed (Yeung 1976).

Smoking and the Leukocyte Count

Studies show that smokers when compared with nonsmokers have generally heightened inflammation, increased white blood cell counts that remain elevated after cessation, and increased levels of other markers of inflammation such as C-reactive protein (Allen et al. 1985; Das 1985; de Maat et al. 1996; Tracy et al. 1997; Danesh et al. 1999).

The association between smoking and the leukocyte count has been extensively investigated, with numerous studies showing that current smokers have higher leukocyte counts than nonsmokers (Table 6.3). In most studies, the increase was 20 percent or more in smokers compared with nonsmokers and was present across strata of age, gender, and race. The leukocyte count increases with the number of cigarettes smoked per day and with the depth of inhalation. Similar dose-response trends were evident in other studies that did not lend themselves to inclusion in the summary tables (Petitti and Kipp 1986; Schwartz and Weiss 1991). Dose-response trends tend to be weaker when examined in relation to either pack-years1 or duration of smoking, suggesting that smoking has an immediate effect on the leukocyte count.

Table 6.3. Studies on the association between current smoking and white blood cell counts.

Table 6.3

Studies on the association between current smoking and white blood cell counts.

The findings from former smokers are consistent with both an immediate and a persistent effect of smoking. In comparisons with lifetime nonsmokers (Table 6.4), former smokers consistently have higher white blood cell counts, but the difference is smaller than that between current smokers and lifetime nonsmokers. In most of the studies, the leukocyte counts for former smokers were only about 5 percent greater than those for lifetime nonsmokers. The excess is persistent (Petitti and Kipp 1986; Schwartz and Weiss 1991; Sunyer et al. 1996), although it decreases with increasing duration of cessation, becoming closer to the average counts found in lifetime nonsmokers (Yarnell et al. 1987; Hansen et al. 1990b). A short-term (overnight) abstention from cigarettes did not strongly influence the counts (Noble and Penny 1975).

Table 6.4. Studies on the association between former smoking and white blood cell counts.

Table 6.4

Studies on the association between former smoking and white blood cell counts.

Prospective cohort studies have tracked changes in leukocyte counts in relation to changes in smoking. In a study of Kaiser Permanente enrollees in the San Francisco Bay area, the leukocyte counts increased 12 percent among those who started smoking during the follow-up, but it decreased 7 percent among smokers who had quit during the follow-up (Friedman et al. 1973). In a subsequent study that compared leukocyte counts of 9,392 persistent smokers with those of 3,825 smokers who had quit, the quitters experienced significantly higher declines (Friedman and Siegelaub 1980). In a cohort of homosexual men seronegative for human immunodeficiency virus (HIV), Sunyer and colleagues (1996) observed that decreases in smoking were followed by decreased white blood cell counts, and increases in smoking were followed by increased white blood cell counts. Furthermore, changes in white blood cell counts were proportional to changes in smoking patterns (Table 6.5).

Table 6.5. Studies on the percentage difference in white blood cell counts stratified by smoking patterns.

Table 6.5

Studies on the percentage difference in white blood cell counts stratified by smoking patterns.

These observations of inflammatory markers, particularly the leukocyte counts, are consistent with the induction of systemic chronic inflammation in smokers, perhaps reflecting the substantial oxidant load from habitual cigarette smoking. Studies of former smokers suggest that this state of inflammation does not simply reflect an acute effect. These observations support one of the mechanisms, oxidative stress, proposed as contributing to the general effects of smoking on health.

Epidemiologic Evidence

Absenteeism

Absenteeism from work is frequent and costly (Steers and Rhodes 1978); its multiple causes include individual and organizational factors (Steers and Rhodes 1978). Researchers investigating the effect of smoking on absenteeism face the challenges of controlling for potential confounding by individual-level factors such as alcoholism, and specifying how smoking could act in combination with other factors at both individual and group levels. While the literature is extensive (Table 6.6), the studies vary in the success with which these challenges have been met, partially reflecting the extent and quality of available data.

Table 6.6. Studies on the association between current smoking and absenteeism.

Table 6.6

Studies on the association between current smoking and absenteeism.

Current Smokers

In studies with varying designs conducted in diverse locations, cigarette smokers consistently have had higher rates of absenteeism than nonsmokers (Table 6.6). The evidence also indicates that the duration of sickness absences tends to be longer for smokers and smokers miss more cumulative worktime than nonsmokers. The association between smoking and absenteeism has been observed in both men and women of all ages. Sickness absences have been measured in a variety of ways, including lost worktime per unit of time, episodes of absenteeism, and the duration of absences. The finding that smoking is associated with absenteeism, regardless of the index used, documents consistency of the observed association. Although most studies were cross-sectional or retrospective in design, two were prospective cohort studies (North et al. 1993; Niedhammer et al. 1998) and another studied smoking histories in relation to work-place attendance records during the preceding nine years (Holcomb and Meigs 1972). The findings of these prospective studies confirm that smoking preceded the absenteeism. In a few studies, the association with smoking was observed primarily in men but not in women (Green et al. 1992; North et al. 1993), but in general the findings have been consistent across all of the subgroups studied. Of the 30 studies that were the sources for the data abstracted into Table 6.6, 17 studies found that absenteeism among smokers was at least 20 percent greater than among nonsmokers in all subgroups.

Two additional reports not included in the table also provide evidence of an association between smoking and absence frequency (Ferguson 1973; Donaldson et al. 1999). In a study of 516 men employed in four occupational groups in Australia, Ferguson noted that “. . .the employee with repeated absence also tended (p <0.10), more often than the resister” (employee without repeated absences) “. . .to smoke more than 15 cigarettes daily” (Ferguson 1973, p. 336). In a study of 146 lumber company employees, a tobacco use scale was not correlated (r = 0.01) with absenteeism (Donaldson et al. 1999).

In several studies summarized in Table 6.6 that assessed the relationship between current smoking and absenteeism (Athanasou 1979; Andersson and Malmgren 1986; Hawker and Holtby 1988; Bertera 1991), current smokers were compared with all nonsmokers, including former smokers. As discussed in the following section, absenteeism rates among former smokers are persistently elevated compared with those of lifetime nonsmokers. Thus, using an “unexposed” comparison category that includes former smokers along with lifetime nonsmokers will dilute associations that would be estimated when using a “pure” unexposed category consisting solely of persons who have never smoked.

In the two studies that assessed the dose-response relationship with the number of cigarettes smoked, the likelihood of being absent increased strongly with the number of cigarettes smoked per day (Lowe 1960; Holcomb and Meigs 1972). In a retrospective cohort study of 226 male factory employees in Connecticut that included eight years of follow-up, the rate of long-term absences increased 43 percent, 57 percent, and 100 percent compared with nonsmokers for those who smoked less than one pack, one pack, and more than one pack of cigarettes per day, respectively (Holcomb and Meigs 1972). In a study of more than 3,300 male General Electric employees in England, the number of days absent for medical reasons increased 11 percent, 13 percent, 26 percent, and 57 percent compared with nonsmokers for those who smoked 1 to 9, 10 to 19, 20 to 29, and 30 or more cigarettes per day, respectively (Lowe 1960).

This body of evidence shows increased absenteeism among smokers, while providing only limited information on the reasons for the absences. A significant proportion of sickness absences in smokers would be expected to be due to smoking-associated illnesses. Athanasou and colleagues (1981) hypothesized that smoking acts as a susceptibility factor, increasing the risks for other harmful occupational exposures. In one study, smoking was associated with a significantly increased likelihood of absences resulting from problems as diverse as back symptoms, digestive tract symptoms, and neck and upper limb symptoms (Dimberg et al. 1989). A recent review summarizing 38 studies showed an increased risk for back pain in smokers compared with nonsmokers in the majority of studies (Goldberg et al. 2000). In another study, absences were elevated not only for “medical reasons” but also for “other” reasons (Lowe 1960). Substantial evidence also documents that smokers are more likely than non-smokers to have on-the-job injuries (Lowe 1960; Naus et al. 1966; Reynolds et al. 1994; Forrester et al. 1996). Because smoking increases absences for a broad set of health problems, and not just specific smoking-associated illnesses, the underlying causal pathways are likely to be multiple and general, reflecting the systemic nature of the effects of smoking.

Former Smokers

The evidence is consistent that former smokers are less likely to be absent from work compared with persistent smokers. Former smokers tend to have somewhat higher absenteeism rates than persons who have never smoked (Table 6.7), but the increases are much smaller than those for current smokers. The analyses performed by Wooden and Bush (1995) with former smokers (n = 4,812) in the 1989–1990 Australian National Health Survey illustrate the seemingly paradoxic relationship between quitting smoking and absenteeism. In a multiple regression model that included both the duration of active smoking and time since quitting, the number of years that a former smoker had smoked remained a strong predictor of absenteeism, and the likelihood of absences declined gradually over time since cessation (Wooden and Bush 1995). Similarly, Manning and colleagues (1989) found differences between recent and sustained quitters, and observed considerably higher absenteeism rates for recent quitters compared with long-term quitters. These results indicate that both prior smoking history and time since quitting are factors strongly associated with absenteeism, but in opposite directions. This pattern may arise because some smokers may quit when diagnosed with an illness caused by smoking, and the recent quitters may thus already have a smoking-induced illness that predisposes them to lost worktime.

Table 6.7. Studies on the association between former smoking and absenteeism.

Table 6.7

Studies on the association between former smoking and absenteeism.

In interpreting evidence linking smoking to a diminished health status, including absenteeism, untangling the direct effects of smoking from the indirect effects is challenging, as smokers and nonsmokers may differ in potential confounding factors. Nonetheless, given the scope of the evidence available and the diversity of the populations studied, the literature does provide insights into the role of smoking as a cause of absenteeism.

With regard to confounding, alcohol use is a major factor of concern. Alcohol use has been linked to absenteeism in some studies, and smokers drink more than nonsmokers (Smith 1970; Turner 1988; Ault et al. 1991; Marmot et al. 1993; Vasse et al. 1998). Smokers are also more likely to be heavy alcohol drinkers and to use illicit substances (Merrill et al. 1999; Best et al. 2000; Brain et al. 2000; Dawson 2000), and heavy alcohol and illicit substance use, rather than cigarette smoking, could increase the likelihood of workplace absences. Studies that adjusted for alcohol consumption have generally (Hendrix and Taylor 1987; Bush and Wooden 1995; Wooden and Bush 1995), but not universally (Ault et al. 1991), found smoking to be associated with frequent absences, implying that the association of smoking with alcoholism is not due to confounding. Studies were not found that accounted for illicit substance use in assessing the association between smoking and workplace absences. Less likely is the possibility that the association between smoking and absences reflects confounding by characteristics that are linked both to smoking (see the section on “Health Status” later in this section) and to an increased risk for frequent absences. For example, women are consistently absent from work more often than men (Leigh 1983; Pines et al. 1985; Steinhardt et al. 1991). But women assume a disproportionate share of family responsibilities such as staying home with sick children, and the relative importance of smoking may therefore be less. Observations of persons with “psychosocial problems” (Leijon and Mikaelsson 1984) and anxiety/neuroses (Taylor 1968; Ferguson 1973) document increased risks for absenteeism, and if such persons are more likely to smoke, confounding is possible. Given the range of populations studied, confounding by psychosocial factors seems unlikely.

Of the relevant pathway factors leading to health-related absences, age is the primary demographic characteristic that is a potential modifying or confounding factor. Socioeconomic status, another potential confounding or modifying factor, is inherently restricted in studies within occupational groups. Age is associated with both absenteeism (Pines et al. 1985) and health status. The association between smoking and absenteeism has been observed consistently across a broad spectrum of age strata in the summarized results, implying that the association does not reflect confounding by age.

Only a few studies provide prospective data concerning absenteeism following smoking cessation; the findings suggest that smoking cessation is associated with better attendance at work. A particularly informative study conducted with employees of a North Carolina pharmaceutical company compared the attendance patterns of former smokers before and after quitting with attendance patterns of a matched group of persistent smokers (Jackson et al. 1989). In the time preceding smoking cessation by the cessation group, the persistent smokers tended to have fewer absences than the smokers who went on to stop smoking. However, during the three years following cessation, the mean number of annual sick days declined among those who quit. Absences continued to increase for persistent smokers, leading to a widening gap in absences between the two groups. The study was small, with only 70 persons participating. In a randomized trial of nine worksite smoking cessation programs, employees who were smokers at baseline had a significant reduction (p = 0.002) in self-reported sick days after stopping smoking (Jeffrey et al. 1993). In another study evaluating a workplace health promotion program that reduced smoking prevalence, the authors reported significant reductions in absenteeism for program participants but not for nonparticipants (Wood et al. 1989).

The evidence that reduced absenteeism follows cessation complements findings based on comparisons of current smokers with nonsmokers. The reduced rate after cessation supports a causal interpretation, rather than attributing the association to an indirect pathway or to confounding factors.

In summary, there is consistent evidence demonstrating that employees who are current smokers have a greater likelihood of absences from work compared with employees who have never smoked. Additional evidence is needed on dose-response trends and, more importantly, on changes in absence rates before and after smoking cessation. Other reviewers have concluded that reduced absenteeism could lead to potential savings that can be accrued from smoking cessation programs in the workplace (Kristein 1983; Warner et al. 1996).

Medical Services Utilization

Medical services utilization provides another measure of the global effects of smoking on health. The most important utilization indicators in studies on smoking can be grouped into three general categories: (1) costs, (2) outpatient visit rates, and (3) hospitalization rates. Interpreting these findings requires consideration of the many factors influencing medical services utilization. Smokers, for example, are less likely than nonsmokers to use preventive services such as screening (Beaulieu et al. 1996; Edwards and Boulet 1997). However, the high incidence of smoking-induced diseases among smokers will tend to drive their medical care needs. The socioeconomic and educational differences between smokers and nonsmokers also complicate data interpretation because of potential confounding. Comparisons of smokers within well-defined groups, such as particular workforces or health care plans, should provide unbiased comparisons.

Costs

In evaluating the relationship between smoking and medical care costs, only those studies directly addressing expenditures were considered (Table 6.8). The literature on comparative lifetime costs of medical care for smokers and nonsmokers based on assumed models and projections was not considered relevant to this chapter. Of the seven studies reviewed, six showed the medical costs of smokers to be greater by at least 15 percent in at least one subgroup. In one study of enrollees in a health maintenance organization, smokers had costs 25 percent higher than nonsmokers among those younger than 65 years of age, but few differences were observed in those age 65 years or older (Terry et al. 1998). Only the study by Vogt and Schweitzer (1985) on enrollees in Kaiser Permanente found no differences between smokers and nonsmokers.

Table 6.8. Studies on the association between current smoking and medical service costs.

Table 6.8

Studies on the association between current smoking and medical service costs.

Two studies not included in Table 6.8 are also relevant. In a population of retirees followed for one year, smoking was associated with added health care costs of more than $1,900 per year per pack of cigarettes smoked per day, after adjusting for age, gender, education, seat belt use, and alcohol consumption (Leigh and Fries 1992). In a study conducted as part of a worksite health promotion program in Birmingham, Alabama, smokers were found to have incurred more costs than nonsmokers, but the data were not presented (Weaver et al. 1998).

Outpatient Services

In several studies (Table 6.8), smokers were at least 15 percent more likely than nonsmokers to use outpatient services (Peters and Ferris 1967; Palmore 1970; Chetwynd and Rayner 1986; Freeborn et al. 1990); one study found an increased likelihood of 6 percent (Rice et al. 1986). In studies that stratified age and gender, strong associations with smoking were observed in particular groups. Male smokers were more frequent users of outpatient services than were male nonsmokers, but this difference was not found among females in one study (Oakes et al. 1974). In another study, this gender difference occurred in young but not old persons (Ashford 1973). Three studies showed only small differences in the use of outpatient services between smokers and nonsmokers (Vogt and Schweitzer 1985; Halpern and Warner 1994; Miller et al. 1999).

The frequency of outpatient visits does not appear to increase with the number of cigarettes smoked (Peters and Ferris 1967; Balarajan et al. 1985; Marsden et al. 1988). However, regardless of the number of cigarettes smoked, some studies documented a large difference in the number of visits by smokers compared with nonsmokers.

Hospitalization

In all but one of the studies considered (Terry et al. 1998), smokers had higher hospitalization rates than nonsmokers; the differences were at least 10 percent. In two other studies that stratified age and gender, one study found an association in males but not in females (Oakes et al. 1974), and the other study found an association only among younger females (Ashford 1973).

Additional studies corroborate the results summarized in Table 6.8. In a study of a cohort of retirees followed for one year, the number of packs of cigarettes smoked per day was significantly associated with the number of days hospitalized (Leigh and Fries 1992). In a study of 1,000 veterans accessing the Veterans Administration system in Connecticut, tobacco users were significantly more likely (p <0.01) than nonusers to be hospitalized, and tobacco users were significantly more likely (p<0.01) than nonusers to be hospitalized and to spend more days in the hospital (Benedetto et al. 1998). In a study of Kaiser Permanente enrollees in Oregon, Pope (1982) observed a weak, non-significant correlation between a smoking index and hospitalization rates in the youngest age group for men and women (aged <35 years), but this association was not present in the other age groups studied.

Dose-response data are available from two prospective cohort studies (Table 6.9). In the Coronary Drug Project, the five-year hospitalization rates for smokers compared with nonsmokers plateaued at the lowest smoking category, and were more compatible with a threshold relationship than with a nonthreshold dose-response relationship. However, it was unclear whether these analyses accounted for the higher mortality rates experienced by smokers relative to nonsmokers during the follow-up period (Coronary Drug Project Research Group 1976). In a two-year follow-up of smokers in the American Cancer Society Cancer Prevention Study I (CPS-I) a strong dose-response relationship was present: compared with those who smoked 1 to 9 cigarettes per day, those who smoked 10 to 19, 20 to 39, and 40 or more cigarettes per day had an increased likelihood of hospitalization during the follow-up period of 8.5 percent, 14.6 percent, and 28.0 percent, respectively (Hammond 1965). In a cross-sectional survey of U.S. military personnel that compared smokers with nonsmokers, those who smoked one-half of a pack or less, one pack, and one and one-half packs or more per day had increases in self-reported days hospitalized of 28.1 percent, 6.3 percent, and 54.7 percent, respectively (Marsden et al. 1988).

Table 6.9. Studies on the association between the amount smoked and medical service utilization rates.

Table 6.9

Studies on the association between the amount smoked and medical service utilization rates.

Former Smokers

Studies comparing the use of medical services by former smokers with lifetime nonsmokers are summarized in Table 6.10. Costs were 26 percent higher for former smokers in one study (Pronk et al. 1999), and higher for some services but not higher overall in another study (Vogt and Schweitzer 1985). In every study, former smokers were more likely than lifetime nonsmokers to use outpatient services. In a study conducted in the United Kingdom that was stratified by age and gender, smokers were more likely than non-smokers to have general practice health care providers visit their homes for an illness (Ashford 1973). The use of outpatient services by smokers remained elevated compared with that of nonsmokers long after smoking cessation (Halpern and Warner 1994). For hospitalizations the findings were mixed, with three studies showing higher rates in former smokers (Van Peenen et al. 1986; Kaplan et al. 1992; Halpern and Warner 1994). In one of these studies, however, the difference was eliminated after adjusting for age, and in two other studies there were only small differences between former smokers and lifetime nonsmokers. In another study that stratified age and gender, former smokers were more likely than lifetime nonsmokers to be hospitalized in some strata, but less likely in others, without a consistent pattern (Ashford 1973).

Table 6.10. Studies on the association between former smoking and medical services utilization costs and rates.

Table 6.10

Studies on the association between former smoking and medical services utilization costs and rates.

These studies generally have not taken into account prior smoking history and time since quitting, nor have they considered whether development of a disease led to quitting. The extent of smoking before quitting is a determinant of risk, and risks fall for many diseases as the duration of quitting lengthens. The somewhat inconsistent findings may reflect (1) the heterogeneity of former smokers in these studies and (2) analysis strategies that did not fully account for risk determinants in the former smokers. In an analysis of the 1990 National Health Interview Survey data that accounted for time since quitting, former smokers had significantly more hospital admissions until 10 years following cessation, at which point former smokers and lifetime nonsmokers had similar numbers of hospital admissions (Halpern and Warner 1994).

The clinical trials of Wagner and colleagues (1995) provide additional evidence. Two cessation trials followed participants and collected medical care utilization data. After six years of follow-up, quitters experienced reductions in outpatient visits, hospital admissions, and hospital days in both trials compared with persistent smokers. In contrast, medical care utilization continued to increase among persistent smokers: 7 to 15 percent for outpatient visits, 30 to 45 percent for hospital admissions, and 75 to 100 percent for days spent in the hospital. These divergent patterns in the use of medical care services resulted in substantially greater rates of hospitalization, hospital days, and outpatient visits for persistent smokers.

Age

Several studies suggest that smoking may have a greater impact on the youngest age groups compared with older age groups. More frequent use of outpatient (Peters and Ferris 1967; Newcomb and Bentler 1987) and inpatient (Newcomb and Bentler 1987) services among smokers than among nonsmokers has been observed even in adolescents and young adults, suggesting that the differences observed in smoking and nonsmoking older adults are not solely a result of smoking-induced diseases. In fact, in a few studies higher levels of service utilization were observed among smokers than among nonsmokers in the younger age groups, but such differences were either not present or were reversed in the oldest age groups. This pattern is evident in the cross-sectional analyses of the 1970 U.S. National Health Interview Survey data, a random sample of U.S. households in which both smoking men and smoking women had a markedly higher number of days hospitalized per year than their nonsmoking counterparts until they reached their mid-40s, at which point the differences between smokers and nonsmokers became more subtle (Weinkam et al. 1987).

In general, compared with nonsmokers, smokers tend to incur more medical costs, to see physicians more often in the outpatient setting, and to be admitted to the hospital more often. Among patients admitted to the hospital, smokers have longer lengths of stay and incur greater expenses per admission than nonsmokers. Less information is available concerning the use of medical services such as prescription drugs and emergency department visits, but increases for smokers compared with nonsmokers have also been observed with respect to these outcomes (Chetwynd and Rayner 1986; Miller et al. 1999). Although smokers use more palliative care services, as demonstrated by this review, smokers have been less likely than non-smokers to use preventive services such as multiphasic testing (Oakes et al. 1974) and screening (Beaulieu et al. 1996; Edwards and Boulet 1997).

Postoperative Complications

In comparison with nonsmokers, smokers have been hypothesized to be at a higher risk for postoperative complications because of a greater frequency of chronic diseases, impaired pulmonary reserve, altered immune responses, and impaired wound healing. Higher rates of postoperative complications in smokers could contribute to the greater costs that they incur for health care services.

Substantial clinical and experimental research has been conducted on the relevant effects of smoking on host defenses, immune responses, and wound healing. As reviewed elsewhere in this report and in a previous Surgeon General’s report (USDHHS 1990), smoking produces a range of effects on respiratory defense mechanisms that may increase the risk for postoperative pneumonia. Compromised lung function and the presence of COPD increase the risks for respiratory complications, including respiratory failure. The increased likelihood of coronary heart disease (CHD) in smokers increases the risk for cardiac events during and after surgery. In animal and clinical models, exposure to tobacco smoke and nicotine specifically impaired aspects of wound healing (Brown et al. 1986; Silcox et al. 1995; Haverstock and Mandracchia 1998; Jorgensen et al. 1998; Hollinger et al. 1999).

The literature on postoperative complications is extensive and diverse in the scope of complications associated with smoking. Table 6.11 provides evidence for lower survival rates after surgery for smokers compared with nonsmokers and suggests that this increased mortality may reflect a range of specific and nonspecific consequences of smoking, including a greater risk for postoperative complications related to the surgery. A number of reports address specific surgical complications such as flap failures, wound infections, and poor orthopedic outcomes. A similarly diverse set of reports consistently shows that smoking also increases the risk of respiratory complications.

Table 6.11. Studies on the association between smoking and complications of surgery.

Table 6.11

Studies on the association between smoking and complications of surgery.

Health Status

Comparisons of self-rated health statuses in smokers and nonsmokers provide further evidence of the global effects of smoking on health. Although self-ratings are inherently subjective, they provide direct evidence of the relationship of smoking to a diminished health status. Consonant with the complex concept of “health,” health status is itself a multidimensional construct, challenging to measure and approached with varied measurement methods, including direct questions on perceived health status and standardized scales. For example, the Short Form 36 (SF-36) is a standardized, 36-item scale that measures eight dimensions of health (Lyons et al. 1994), three of which have a direct relevance to this review: general health perceptions (five items), physical health (four items), and mental health (five items). Table 6.12 (smokers versus nonsmokers), Table 6.13 (dose-responses), and Table 6.14 (former smokers versus non-smokers) summarize the evidence. Studies were grouped according to the aspect of health status measured: symptoms/illnesses/health complaints, perceived health status (poor/good), physical function, physical status, general health status, life satisfaction/ dissatisfaction, well-being, quality of life, tiredness, and mental health. In some studies “poor” health was measured whereas in others “good” health was measured, so the anticipated directions of the effects of smoking vary with the specified outcome.

Table 6.12. Studies comparing the health status of smokers and nonsmokers.

Table 6.12

Studies comparing the health status of smokers and nonsmokers.

Table 6.13. Studies evaluating the dose-response relationship between the number of cigarettes smoked per day and health status.

Table 6.13

Studies evaluating the dose-response relationship between the number of cigarettes smoked per day and health status.

Table 6.14. Studies comparing the health status of former smokers and nonsmokers.

Table 6.14

Studies comparing the health status of former smokers and nonsmokers.

Studies with varying designs, as well as studies measuring physical health status (Table 6.12), have shown uniformly that smokers tend to rate their general health status lower than do nonsmokers. Studies that do not include sufficient data to summarize in the tables obtained similar results. A study of 558 Bank of America retirees in California comparing smokers with nonsmokers showed that smoking was strongly associated with a higher number of sick days confined to home (Leigh and Fries 1992). In an analysis of 1990 National Health Interview Survey data, the perception of health status held by current smokers was significantly lower than that held by nonsmokers (Erickson 1998). In a multiple regression analysis of data collected from approximately 18,000 men and women in Finland, which included variables for sociodemographic characteristics, family life, morbid conditions, pain, psychosocial problems, and relative weight, smoking was associated with a significantly lower perceived health status in men but not in women (Fylkesnes and Førde 1991). In a random sample of 1,200 adults in South Wales, United Kingdom, the mean score on the SF-36 general health perception scale among participants who had ever smoked was 7.8 points lower than for those who had never smoked (Lyons et al. 1994). A study using the same scale with 921 U.S. male military veterans showed that current smoking was significantly inversely correlated with good general health perceptions (Schnurr and Spiro 1999). In a telephone survey of Newfoundland residents, the likelihood of rating one’s health as good declined in proportion to the number of cigarettes smoked per day; those who had never smoked were more than four times more likely than smokers of more than 30 cigarettes per day to rate their health as good (Segovia et al. 1989). In a survey of 1,623 patients from nine medical practices in Scotland who had a history of smoking, persistent smokers rated their general health 8.0 percent lower than former smokers rated theirs on the SF-36 scale (Tillmann and Silcock 1997). Among 2,502 enrollees in an Oregon health maintenance organization, smoking was negatively correlated with general health status for both men and women, an observation that extended to measures of mental and physical health status (Pope 1982).

Smokers in at least one subgroup were at least 10 percent more likely than nonsmokers to rate their health as poor, including studies that compared self-reported chronic conditions (Balarajan et al. 1985; Halpern and Warner 1994), acute conditions (Balarajan et al. 1985), and physical symptoms (Macnee 1991; York and Hirsh 1995). An increasing number of cigarettes smoked per day was consistently associated with increased risks for symptoms or illnesses (Balarajan et al. 1985; Marsden et al. 1988; Joung et al. 1995), and with a greater likelihood of rating one’s health as poor (Joung et al. 1995; Poikolainen et al. 1996; Manderbacka et al. 1999) (Table 6.13), with differences between the highest and lowest exposure categories of about 30 percent or greater in every study that assessed dose-response trends (Table 6.13). For several measures of poor health, the differences between former smokers and lifetime nonsmokers (Table 6.14) tended to be even more striking than for comparisons between current smokers and lifetime nonsmokers, probably because of the increased likelihood of quitting among those experiencing symptoms or diagnosed with illnesses.

A few studies examined reports of fatigue or tiredness. In a survey of New Zealand women who worked at home, smokers were 71 percent more likely than nonsmokers to report frequently feeling tired for no reason (Chetwynd and Rayner 1986). In a study of retired persons in the United States, after adjusting for age, current smokers were 60 percent more likely than lifetime nonsmokers to report becoming very tired easily (Rimer et al. 1990); former smokers were 25 percent more likely than lifetime nonsmokers to report getting very tired easily (Rimer et al. 1990).

Smokers tend to rate their general level of well-being lower than do nonsmokers whether well-being is measured directly (Dennerstein et al. 1994), assessed overall as quality of life (Sippel et al. 1999), or rated by degrees of general satisfaction with life (Blair et al. 1980) (Table 6.12). Similar findings have been observed when former smokers were compared with lifetime nonsmokers (Table 6.14) (Blair et al. 1980; Sippel et al. 1999). Conversely, compared with lifetime nonsmokers, current smokers tend to rate themselves as more dissatisfied with life (Table 6.12) (Kaprio and Koskenvuo 1988), but few differences in the prevalence rates of life dissatisfaction were observed between former smokers and nonsmokers (Table 6.14) (Kaprio and Koskenvuo 1988).

With respect to mental health and well-being, smokers tend to rate themselves slightly lower on measures of mental health or mental well-being (Wakefield et al. 1995; Wooden and Bush 1995; Sippel et al. 1999). In addition, smokers are more likely than nonsmokers to have psychological symptoms such as depressed mood and phobic anxiety (Matarazzo and Saslow 1960; Macnee 1991; Schoenborn and Horm 1993). In the South Wales study, not included in the summary tables, current smokers had a mean SF-36 mental health score that was slightly but not significantly lower than that of people who had never smoked (Lyons et al. 1994). Former smokers also tend to rate themselves less favorably than do nonsmokers (Table 6.14). The differences between former smokers and lifetime nonsmokers were small with respect to mental health and well-being (Wetzler and Ursano 1988; Wooden and Bush 1995; Sippel et al. 1999), but were more marked on measures of symptoms or morbidity (Table 6.14) (Lilienfeld 1959; Lindenthal et al. 1972; Macnee 1991). A strong dose-response trend was observed between smoking frequency and depressed moods in nationally representative U.S. data from the National Health Interview Survey (Schoenborn and Horm 1993). However, dose-response trends generally did not occur for mental health measures (Table 6.13) (Lindenthal et al. 1972; Wetzler and Ursano 1988; Stansfeld et al. 1993).

Studies of physical functioning, or functional status, among elderly populations also provide relevant evidence. Although they are not a focus of this review, such studies have provided prospective evidence that cigarette smoking is associated with accelerated declines in physical function (Pinsky et al. 1987; Guralnik and Kaplan 1989; Berkman et al. 1993; Strawbridge 1993). An analysis of data from the Honolulu Heart Study showed that smoking was inversely associated with freedom from clinical illnesses, physical impairment, and cognitive impairment (Reed et al. 1998).

The evidence provides a clear indication that smokers perceive their health as poorer than nonsmokers perceive theirs. Smokers report more symptoms (including mental health symptoms) and illness episodes, feel more tired, and have lower ratings for physical health status. Compared with nonsmokers, smokers even report lower overall levels of well-being for reasons that may at least partially reflect their diminished health status. The consistent indications of a poorer health status among smokers compared with nonsmokers across numerous health status dimensions provide direct evidence that smoking is associated with a diminished health status.

Evidence Synthesis

This section reviewed evidence on smoking and a diverse but interrelated set of measures of health status. Although the measures are nonspecific and likely to be affected by factors other than smoking, there is abundant and consistent evidence that smokers generally have a poorer health status than nonsmokers. This section reviewed findings on self-reported health statuses, absenteeism, and medical services utilization rates, as well as complications of surgical care. For each of these outcomes, the weight of the evidence indicates an adverse effect from smoking. There are many studies with differing designs and a variety of populations. The strength of the association with smoking is variable across the outcome measures and across study populations, probably reflecting the nonspecificity of these measures and the differing mixes of potential confounding and modifying factors across studies. In general, there is evidence for an increasing severity of outcome measures with an increasing number of cigarettes smoked, and current smokers tend to have worse outcomes than former smokers. Studies have addressed potential confounding factors to a limited extent, depending on the availability of data on relevant factors. Given the diversity of populations, study designs, and consistency of findings, confounding alone does not seem to be a satisfactory explanation for the overall pattern of findings. A single, unifying biologic basis for the association of smoking with the outcome measures cannot be postulated, but there are many well-supported direct and indirect mechanisms that may link smoking to the adverse effects documented in this section.

Conclusions

  1. The evidence is sufficient to infer a causal relationship between smoking and diminished health status that may manifest as increased absenteeism from work and increased use of medical care services.
  2. The evidence is sufficient to infer a causal relationship between smoking and increased risks for adverse surgical outcomes related to wound healing and respiratory complications.

Implications

Although preventing the specific diseases caused by smoking has been a public health priority for a long time, cigarette smoking also causes a substantial and costly burden of nonspecific morbidity. Smokers have a poorer health status, lose more time from work, and use medical care services at a higher rate than their nonsmoking peers. These adverse effects occur among younger smokers even before the burden of smoking-induced diseases becomes apparent at middle age and older.

Loss of Bone Mass and the Risk of Fractures

In the United States, of the estimated 850,000 fractures per year in persons 65 years of age and older, nearly 300,000 are hip fractures (Apple and Hayes 1994; Centers for Disease Control and Prevention [CDC] 1996; Ray et al. 1997). Approximately 33 percent of women and 17 percent of men experience a hip fracture if they live to be 90 years old (Mazess 1982; Melton and Riggs 1987). Mortality in persons with a hip fracture is 12 to 20 percent higher than in persons without a hip fracture of similar age, race, and gender (Miller 1978; Jensen and Tondevold 1979; Weiss et al. 1983; Jensen 1984; Kenzora et al. 1984; Kreutzfeldt et al. 1984). The estimated annual costs for medical and nursing services related to hip fractures range from $7 billion to $10 billion (Ray et al. 1997). From July 1991 through June 1992, costs to Medicare for 10 types of fractures were estimated at $4.2 billion (Baron et al. 1996). Moreover, continued growth of the elderly population can be expected to dramatically increase the number of hip fractures, because hip fracture incidence rates increase exponentially with age (Melton and Riggs 1987; Melton et al. 1987). If these demographic and incidence trends continue, the number of hip fractures may well double or triple by the middle of the century (Kelsey and Hoffman 1987). With their frequency, adverse quality of life impacts, and economic costs, hip fractures are an urgent and major public health problem.

Bone mineral density (BMD) is one of the strongest indicators of the risk for a fracture. Several cohort studies have confirmed that even a single low BMD measurement is associated with the risk of a later fracture (Gärdsell et al. 1989; Hui et al. 1989; Cummings et al. 1993). For each standard deviation decrease in BMD, the estimated relative risk (RR) of fractures ranged from 1.5 to 2.6, depending on the site that was measured (Marshall et al. 1996). Therefore, discussions of the possible adverse effects from smoking on bone health should consider both BMD and fractures as outcome measures. An estimated 60 to 80 percent of the bone density variation is explained by genetic factors (Eisman 1999), leaving 20 to 40 percent of the variation attributable to nongenetic factors. Smoking is an important modifiable risk factor in both women and men.

Conclusions of Previous Surgeon General’s Reports

Harmful effects of smoking on the skeleton have been recognized for several decades but the data were not sufficient to conclude that smoking adversely affects bone mass (USDHHS 1990); however, the most recent Surgeon General’s report on women and smoking (USDHHS 2001) identified smoking as adversely affecting bone health and increasing the risks for fractures. The report concluded that smoking adversely affects bone density and increases the risks for hip fractures in postmenopausal women. Specifically, the conclusions were that (1) postmenopausal women who currently smoke have lower bone density than women who do not smoke; (2) women who currently smoke have an increased risk for hip fracture compared with women who do not smoke; and (3) the relationship among women between smoking and the risk for bone fracture at sites other than the hip is not clear (USDHHS 2001). However, because male osteoporosis also has been recognized as a considerable disease burden, the role of smoking in male bone health also deserves consideration.

Biologic Basis

Smoking has the potential for direct and indirect effects on skeletal health and the risk of fractures. Direct toxic effects of smoking on bone cells may be related to the physiologic effects of nicotine (Fang et al. 1991; Riebel et al. 1995) or possibly cadmium in tobacco smoke (Bhattacharyya et al. 1988). Indirect effects of smoking on bone cells may result from decreased intestinal calcium absorption (Krall and Dawson-Hughes 1999), reduced intake and lower levels of vitamin D (Brot et al. 1999), or alterations in the metabolism of adrenal cortical and gonadal hormones (Michnovicz et al. 1986; Khaw et al. 1988; Baron et al. 1995). These direct and indirect effects may account for the generally observed decrease in markers of bone formation such as osteocalcin in smokers compared with nonsmokers (Brot et al. 1999; Bjarnason and Christiansen 2000). Smoking might also indirectly influence bone density through reduction in body weight, since body weight tends to be lower for smokers than for nonsmokers. This weight difference may itself lead to lower bone density and an increased risk for a fracture (Kiel et al. 1987; Cummings et al. 1995). Smokers also tend to have an earlier menopause than nonsmokers, thus extending the postmenopausal period of accelerated bone mineral loss (USDHHS 2001). Finally, smokers tend to be less physically active than nonsmokers and activity level is associated with bone density and hence risk for a fracture (Gregg et al. 1998).

In several analyses involving women, the lower weight of smokers compared with nonsmokers explains part of the increased risk for low BMD associated with smoking (Bauer et al. 1993). However, there are differences in BMD and in fracture rates between smokers and nonsmokers even after adjusting for weight differences, suggesting that the weight difference alone does not explain the effects of smoking (Kiel et al. 1992, 1996; Bjarnason and Christiansen 2000). The lower weight in smokers may increase the risk of fractures, such as hip fractures, through several mechanisms: reduced soft tissue mass overlaying the trochanter, resulting in less energy absorption from a fall on the hip; reduced weight loads on the skeleton; or reduced conversion of adrenal steroids into sex steroids in adipose tissue. The antiestrogenic effect of smoking also may contribute to osteoporosis in women (Jensen et al. 1985; Jensen and Christiansen 1988), and may reduce the benefits of hormonal replacement therapy (Komulainen et al. 2000). In a Finnish trial of osteoporosis prevention, smoking was associated with a nonresponse to hormonal therapy, as assessed by changes in BMD (Komulainen et al. 2000). Less consistent evidence for a blunted response to estrogen by smoking was reported from a Danish trial (Bjarnason and Christiansen 2000). Interestingly, although estrogen appears to be a critical hormone for male skeletal health (Slemenda et al. 1997; Khosla et al. 1998), smoking does not appear to modify the association between estradiol levels and bone density in men (Amin et al. 1999). Finally, smoking may increase the risk of fractures through reductions in physical performance capacity, thereby increasing the risk for falls (Nelson et al. 1994).

Bone Density in Young Men and Women

Epidemiologic Evidence

Increasingly refined measures of BMD have become available so that current studies use direct BMD measurements. Before such direct measurements were possible BMD was assessed using radiographs, with measurements typically focused on the widths of the cortical bones in sites such as the metacarpals. Direct quantitative assessments of the amount of mineral in various skeletal sites have now become possible with the advent of single and dual photon absorptiometry, followed by refinements such as single and dual x-ray absorptiometry, quantitative computed tomography, and quantitative ultrasonography. These techniques have all been used to generate the data summarized here.

In adults at any particular age bone mass is dependent on the peak mass achieved up to that age, and subsequent losses from the peak are attributable to aging and other factors. The pace of skeletal growth is rapid during infancy, slower during childhood, accelerated during puberty, and by 20 to 30 years of age the peak skeletal mass is attained (Kroger et al. 1992; Lu et al. 1996). Gains in BMD continue into the third decade after bone growth has ceased (Recker et al. 1992). After menopause, bone loss rates accelerate compared with premenopausal rates, and these rates are sustained or increase even more with aging (Ensrud et al. 1995). Age-related losses also occur in men (Jones et al. 1994). In the context of these age-related patterns, the role of smoking in the attainment of peak bone mass is reviewed along with studies of bone density and menopausal status. A literature search was conducted using the National Library of Medicine’s PubMed system; the key words used were “bone mineral density,” “bone density,” “fracture,” “smoking,” and “cigarettes.” In addition, all references from a key meta-analysis (Law and Hackshaw 1997) were also retrieved. Studies focusing on men mainly involve older age groups. The evidence on smoking and BMD comes primarily from cross-sectional and cohort studies. The cross-sectional studies assess the cumulative consequences of smoking on BMD growth and/or decline. Cohort studies can assess changes in BMD over time. Findings of the different types of studies are presented in Tables 6.156.17.

Table 6.15. Cross-sectional studies on the association between smoking status and bone density in women.

Table 6.15

Cross-sectional studies on the association between smoking status and bone density in women.

Table 6.16. Studies on the association between smoking status and bone density in men and women published since the 1997 meta-analysis by Law and colleagues.

Table 6.16

Studies on the association between smoking status and bone density in men and women published since the 1997 meta-analysis by Law and colleagues.

Table 6.17. Cohort studies on the association between smoking status and the risk of bone loss in men and women.

Table 6.17

Cohort studies on the association between smoking status and the risk of bone loss in men and women.

Peak Bone Mass

Because BMD increases rapidly during adolescence, initiating smoking around the time of puberty might reduce peak BMD. However, the effects of smoking on the attained level of peak bone mass are uncertain because there are limited data on the skeletal effects of smoking during adolescence. Furthermore, it is possible that relatively short exposures in this age group would have little effect on bone density measurements. One prospective cohort study of children and adolescents (aged 9 to 18 years) in Finland repeatedly ascertained lifestyle factors and followed participants for 11 years, at which time they underwent bone density testing (Välimäki et al. 1994). In men, but not in women, smokers had lower BMD measurements of the hip and spine than did nonsmokers after adjusting for covariates. A cross-sectional study of 15-year-old Swedish adolescents did not find an association between smoking and total body bone mineral content (Lötborn et al. 1999). Findings were similar in a cross-sectional study of 500 children aged 4 to 20 years in the Netherlands, but only 32 were smokers (Boot et al. 1997).

Data are available from studies of premenopausal women, starting from the ages at which peak BMD is reached. A meta-analysis of cigarette smoking, BMD, and the risk for hip fractures (Law and Hackshaw 1997) identified 10 cross-sectional studies of premenopausal women (Johnell and Nilsson 1984; McCulloch et al. 1990; Mazess and Barden 1991; Daniel et al. 1992; Fehily et al. 1992; Sowers et al. 1992; Hopper and Seeman 1994; Ortego-Centeno et al. 1994; Välimäki et al. 1994; Law et al. 1997). Additional study populations included menopausal and postmenopausal women (Table 6.15). As shown in Table 6.15, the mean ages of women in the study samples ranged from 22 to 76 years. Because absolute bone density units varied among studies according to the bone site assessed and the measurement technique used, the difference between the average BMD of current smokers and nonsmokers in each of the studies was recorded as a proportion of one between-person standard deviation. In combining the studies, each bone density difference was weighted by the inverse of its variance and was age-adjusted only.

Bone densities were reported for current smokers compared with never smokers in most studies, but were reported for current compared with former and lifetime never smokers combined in a few studies. There was no evidence of a significant difference in BMD between smokers and nonsmokers in the pre-menopausal women (Figure 6.2). Two additional studies of premenopausal and postmenopausal women performed since the 1997 meta-analysis also show no significant differences in BMD between smokers and nonsmokers (Table 6.16) (Takada et al. 1997; Gregg et al. 1999); however, a study of premenopausal women from Australia did find a significantly lower BMD in female current smokers that was not found in the subgroup of female smokers who participated in sports (Jones and Scott 1999). Cross-sectional data from the Danish Osteoporosis Prevention Study showed lower BMD in current smokers compared with lifetime non-smokers in perimenopausal women (Hermann et al. 2000). It is appropriate to consider these results unadjusted for other covariates in that adjusting for one of the most important risk factors for bone density— weight—actually may mask an association. Smoking-induced weight loss may represent an intervening variable in the causal chain between smoking and bone density reduction.

Figure 6.2. Differences (95% confidence intervals), as a proportion of 1 standard deviation (SD), in bone mineral density between female smokers and nonsmokers according to age and menopausal status.

Figure 6.2

Differences (95% confidence intervals), as a proportion of 1 standard deviation (SD), in bone mineral density between female smokers and nonsmokers according to age and menopausal status. Note: Fitted regression lines are shown. The 11 open circles refer (more...)

One study from Spain assessed smoking and BMD in healthy young males (Ortego-Centeno et al. 1997). In this study, male volunteers aged 20 through 45 years were measured for BMD in the lumbar spine and proximal femur; blood biochemical markers were also assessed. BMD was significantly lower for smokers of 20 or more cigarettes per day compared with nonsmokers. In multiple regression analyses considering all smokers, smoking was not significantly associated with measures of BMD. Interpretations of these findings are limited by the cross-sectional data and the small sample size.

Smoking Cessation and Bone Mineral Density Loss

Two prospective cohort studies assessed smoking cessation and BMD in men and women (Hollenbach et al. 1993; Kiel et al. 1996). In a study in Rancho Bernardo, California, Hollenbach and colleagues (1993) found that smoking cessation later in life was beneficial for men and women in halting BMD loss at hip sites (intertrochanter, total hip, femoral neck, and trochanter) where BMD is reduced in smokers. In men, smoking cessation was followed by a reduction in the rate of loss of the spinal BMD, and women experienced a significant decrease in the rate of BMD loss at the midradius after quitting. In the Framingham study, current or former smoking (past 10 years) was not associated with a lower BMD loss at any skeletal site among women who had not taken estrogen but it was in women who had (Kiel et al. 1996). Former male smokers who had quit for less than 10 years had a lower BMD than men who had quit for 10 or more years, independent of weight, alcohol consumption, or caffeine use.

Evidence Synthesis

Smoking, even at a young age, might increase risk for osteoporosis later in life if it reduces the peak bone mass attained, thereby compromising the peak from which decline begins. Only a few studies address smoking during adolescence, and the findings in women during the premenopausal years are conflicting, are not based on large studies, and do not provide strong evidence for an effect of smoking on BMD before menopause. For males, data are scant for this age range. Although an effect of smoking on BMD is plausible, the available evidence from observational studies is limited and inconsistent.

Conclusion

  1. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and reduced bone density before menopause in women and in younger men.

Implications

The failure to demonstrate a causal relationship between smoking and bone density in young women does not detract from the basis for concern about smoking and osteoporosis in women. For women, smoking patterns established in younger years are likely to persist past menopause, and there is substantial evidence linking smoking to low bone density during menopause (see below). Future research should quantify the combined and cumulative effects of premenopausal and postmenopausal smoking on bone density. More research is needed in young men regarding the relationship between smoking and bone density.

Bone Density in Middle and Later Years of Life

Epidemiologic Evidence

In contrast to the findings for younger persons, findings of bone density studies performed in populations well beyond the years of peak bone mass demonstrate substantial differences between smokers and nonsmokers. As illustrated in Figure 6.2, based on the meta-analysis by Law and Hackshaw (1997), bone density was lower in smokers than in nonsmokers for post-menopausal women, and the difference increased linearly with age. For every 10-year increase in age, the bone density of smokers fell below that of non-smokers by approximately 2 percent of the average bone density at the time of menopause, regardless of the skeletal site that was measured.

Since the publication of this meta-analysis, there have been additional studies of smoking and bone density in postmenopausal women and in men. Of four studies that did not demonstrate an association between smoking and bone density (Cheng et al. 1999; Varenna et al. 1999; Huuskonen et al. 2000; Kim et al. 2000), two had used quantitative ultrasound to measure bone status. Seven other studies did demonstrate statistically significant associations between smoking and BMD (Table 6.16) (Brot et al. 1997; Takada et al. 1997; Vogel et al. 1997; Grainge et al. 1998; Smeets-Goevaers et al. 1998; Hagiwara and Tsumura 1999; Hermann et al. 2000).

Data from cohort studies of older men and women also implicate smoking as a significant risk factor for bone loss (Table 6.17). Of the six studies that reported smoking data (three involving women and men, two involving women only, and one involving men only) (Sowers et al. 1992; Jones et al. 1994; Vogel et al. 1997; Burger et al. 1998; Guthrie et al. 1998; Hannan et al. 2000), three documented significantly more bone loss in female smokers than in female and male nonsmokers (Sowers et al. 1992; Burger et al. 1998; Guthrie et al. 1998), and three reported higher rates of loss among male smokers than among male nonsmokers (Vogel et al. 1997; Burger et al. 1998; Hannan et al. 2000). Interpretations of several of the studies are constrained by relatively small sample sizes and limited durations of follow-up.

Evidence Synthesis

Extensive and consistent data are available on BMD and smoking for perimenopausal and postmenopausal women and for older men. Data from cohort studies, which track changes in BMD over time, as well as from cross-sectional studies provide generally consistent evidence of increased rates of loss in postmenopausal women who smoke compared with nonsmokers. Smoking cessation appears to benefit BMD since limited data indicate higher rates of BMD loss for heavier smokers. Data are more limited for men. The 2001 Surgeon General’s report (USDHHS 2001) found the evidence to be consistent for women and concluded that “Postmenopausal women who currently smoke have lower bone density than do women who do not smoke” (p. 321). There are a number of mechanisms that may underlie this finding.

Conclusions

  1. In postmenopausal women, the evidence is sufficient to infer a causal relationship between smoking and low bone density.
  2. In older men, the evidence is suggestive but not sufficient to infer a causal relationship between smoking and low bone density.

Implications

Smoking has an adverse effect on bone density in middle and later years of life; for every 10-year increase in age, the bone density of female smokers falls below that of nonsmokers by about a 0.14 standard deviation, or 2 percent of the average bone density at the time of menopause in women. Because a 1.0 standard deviation decrease in bone density doubles the risk of fracture, and because fracture incidence increases with age (Melton and Riggs 1987; Melton et al. 1987), the proportion of all fractures attributable to smoking would be expected to increase for smokers who continue smoking into older ages. Attempts to decrease smoking as early in life as possible are likely to reduce fractures that would be caused by smoking in old age.

Because bone loss is relatively small over short periods of time, studies with longer durations of follow-up and minimal avoidable losses of participants at follow-up could add important information to the understanding of how smoking contributes to bone loss. Additional information is likely to come from studies of biochemical markers of bone turnover, which might further the understanding as to mechanisms whereby smoking accelerates bone loss.

Fractures

Epidemiologic Evidence

Hip fractures, the most frequently studied fractures in relation to smoking, account for a significant proportion of the morbidity and mortality attributed to osteoporosis. The meta-analysis by Law and colleagues (1997) reviewed 19 cohort and case-control studies of the risk of hip fractures in postmenopausal women according to whether they had COPDs. The studies differed with regard to the ages of the participants, duration of follow-up, and whether former smokers were included in the smoking or nonsmoking groups. Table 6.18 shows the characteristics of each of the 19 studies, demonstrating the range of ages at the time of the fracture. For the cohort studies, the duration of follow-up ranged from three years (Forsén et al. 1994) to 26 years (Kiel et al. 1992). Figure 6.3 shows the risk of hip fractures in smokers relative to non-smokers according to age; the risks for smokers increased with increasing age. Major conclusions of the meta-analysis include (1) smoking has no material effect on bone density in premenopausal women; (2) postmenopausal bone loss is greater in smokers—an additional 0.2 percent of bone mass each year; (3) in comparisons of women who are current smokers with women who are nonsmokers, the risk of hip fracture is estimated to be 17 percent greater at 60 years of age, 41 percent greater at 70 years, 71 percent greater at 80 years, and 108 percent greater at 90 years; and (4) the estimated cumulative risk of hip fracture to 85 years of age in women is 19 percent in smokers and 12 percent in nonsmokers; to 90 years it is 37 percent and 22 percent, respectively. The data for men were much more limited but suggested similar consequences.

Table 6.18. Studies on the association between smoking and the risk of hip fractures in men and women used in the 1997 meta-analysis by Law and Hackshaw.

Table 6.18

Studies on the association between smoking and the risk of hip fractures in men and women used in the 1997 meta-analysis by Law and Hackshaw.

Figure 6.3. Relative risk (95% confidence intervals) of hip fracture in smokers compared with nonsmokers in postmenopausal women according to age.

Figure 6.3

Relative risk (95% confidence intervals) of hip fracture in smokers compared with nonsmokers in postmenopausal women according to age. Note: Each cohort study (8 solid circles) and case-control study (11 open circles) is in the same order as in Table (more...)

Since the publication of the meta-analysis by Law and colleagues (1997), some (Forsén et al. 1998; Burger et al. 1999; Kanis et al. 1999; Melhus et al. 1999; Baron et al. 2001) but not all subsequent studies of hip fracture (Fujiwara et al. 1997; Clark et al. 1998; Mussolino et al. 1998) have continued to show an association between smoking and an increased risk of hip fracture (Table 6.19). These studies have used various designs and have been carried out in diverse populations.

Table 6.19. Studies on the association between smoking and the risk of hip fractures in men and women reported since the 1997 meta-analysis by Law and Hackshaw.

Table 6.19

Studies on the association between smoking and the risk of hip fractures in men and women reported since the 1997 meta-analysis by Law and Hackshaw.

Data on the association between smoking and fractures at other sites are more limited (Table 6.20). Studies from the 1980s and early 1990s that examined fractures other than those of the hip rarely found an association with smoking, although more recent studies have demonstrated positive associations between smoking and vertebral fractures (Scane et al. 1999; Lau et al. 2000), ankle fractures (Honkanen et al. 1998), and the general categories of nonhip fractures (Jacqmin-Gadda et al. 1998) and of all fractures (Huopio et al. 2000).

Table 6.20. Studies on the association between smoking and the risk of fractures at sites other than the hip in men and women.

Table 6.20

Studies on the association between smoking and the risk of fractures at sites other than the hip in men and women.

Smoking Cessation and Hip Fractures

The association between smoking cessation and the risk of hip fractures was examined in several studies, including three prospective cohort studies with follow-up periods of 5 to 12 years (Forsén et al. 1998; Cornuz et al. 1999; Høidrup et al. 2000) and two case-control studies (La Vecchia et al. 1991; Cumming and Klineberg 1994). In men, successful smoking cessation of at least five years decreased the risk of hip fracture compared with continuing smokers (Høidrup et al. 2000), although other investigations found that this risk remained elevated for men and women smokers compared with lifetime nonsmokers (Cumming and Klineberg 1994; Forsén et al. 1998). Two studies also found no decrease in the risk for hip fractures in women after five years of smoking cessation (La Vecchia et al. 1991; Cornuz et al. 1999), and another found that no benefit from quitting for women, including premenopausal women, was observed until 10 years after cessation (adjusted RR = 0.7 [95 percent confidence interval (CI), 0.5–0.9] compared with current smokers) (Cornuz et al. 1999).

Evidence Synthesis

The evidence on smoking and fracture has been reviewed extensively in previous reports of the Surgeon General. The 1990 report considered evidence from eight case-control studies, noting that most showed an association with risk for fracture of the hip or vertebra. Five cohort studies, however, did not show a clear increase in risk and the report found the evidence to be inconclusive. Far more extensive data were available for the 2001 report, including substantially more studies of hip fracture in women. The case-control studies reviewed all indicated excess risk for hip fracture in smokers, with the RR ranging from 1.1 to 2.0. Six reports of cohort studies published subsequent to the 1990 report were also cited, all showing an increased risk for hip fracture in current smokers. The 2001 report (USDHHS 2001) concluded that “women who currently smoke have an increased risk for hip fracture compared with women who do not smoke” (p. 321).

This report extends the review of the 2001 report with additional studies and covers the evidence on men as well. The evidence consistently indicates an increased risk for women and men who smoke. Findings of some studies show a dose-response relationship between risk for hip fracture and the amount smoked. The RR tends to rise with age as would be expected, and the effect of smoking reflects sustained, additional bone loss beyond that associated with aging. The documented effects of smoking on BMD is consistent with the observational evidence on hip fracture.

For fracture sites other than the hip, the evidence has been less consistent. The 2001 Surgeon General’s report found the evidence to be unclear. This report evaluated a number of studies for other sites, also finding the evidence to be mixed and limited in scope for any particular site.

Conclusions

  1. The evidence is sufficient to infer a causal relationship between smoking and hip fractures.
  2. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and fractures at sites other than the hip.

Implications

The RR of hip fractures in smokers increases with age, and hip fracture incidence increases with age, implying that the proportion of hip fractures attributable to smoking increases with age. Smoking is one of the major causes of fracture in older persons that can be prevented. Public health interventions aimed at helping smokers quit are likely to substantially reduce the number of hip fractures. Although hip fractures carry the greatest costs and risks of mortality and morbidity, other fractures also contribute to these outcomes. Further research is necessary to quantify the risks of these other fractures in smokers.

Dental Diseases

Diseases of the teeth and their supporting structures are a major public health issue with a significant impact on personal well-being. More than $60 billion were spent on oral health care in the United States in 2000, and each year acute oral conditions result in an estimated 1.6 million missed school days and 2.4 million lost workdays. Although there have been tremendous improvements in the oral health of the U.S. public during the past several decades, oral diseases and conditions remain highly prevalent. For example, recent national data indicate that 66 percent of persons aged 12 through 17 years and 94 percent of those aged 18 years and older have experienced dental caries in their permanent teeth (USDHHS 2000).

As the oral cavity is the first part of the human anatomy to be exposed to mainstream smoke in active smokers, researchers have long hypothesized that smoking could have a deleterious effect on the teeth and their supporting structures. However, research on this association was hampered for decades by (1) lack of consensus on case definitions for some diseases; (2) difficulty in measuring oral conditions and consequent use of indices of questionable validity; (3) some incorrect assumptions about disease etiology, pathogenesis, distribution, and natural history; and (4) limited capacity for epidemiologic investigations within the dental research community. As a result, until recently the literature was sparse and findings were not definitive.

Conclusions of Previous Surgeon General’s Reports

The previous Surgeon General’s reports on smoking and health did not include dental or periodontal effects of smoking, although oral cancer and related premalignant lesions have been addressed. During the past 15 years, however, there has been a substantial amount of research on smoking and oral health, and this topic was addressed in Oral Health in America: A Report of the Surgeon General (USDHHS 2000). This section reviews the epidemiologic evidence for smoking as a causal factor for the most common forms of non-malignant oral disease; cancers of the oral cavity are covered in Chapter 2.

Periodontitis

The periodontium includes those hard and soft tissue structures that support the teeth: the gingiva, the cementum covering the root surfaces of the teeth, the periodontal ligament that attaches the tooth root surfaces to the adjacent alveolar bone supporting each tooth, and the alveolar bone. The gingiva covers the other periodontal structures and comprises attached and free gingiva. The attached gingiva extends from the bottom of the gingival sulcus to the mucogingival junction, where it is contiguous with the mucous membrane of the lip, cheek, and floor of the mouth. The free gingiva extends from the base of the gingival sulcus to the gingival margin.

In a healthy state, the gingival margin is approximately 0.5 to 2.5 mm coronal to the cemento-enamel junction (CEJ) (where the enamel on the crown of the tooth meets the root). The sulcus is 1 to 3 mm in depth and does not bleed when probed. The base of the sulcus is formed by the junctional epithelium, which joins the gingival connective tissue to the tooth surface. Healthy gingiva is usually pink in color, is well adapted to the teeth, has a stippled surface texture, and is tightly bound to the underlying alveolar bone and the roots of the teeth.

Based on the most recent classification system developed by the American Academy of Periodontology, there are at least eight categories of periodontal diseases and conditions (Armitage 1999). Of those, the two most common are gingivitis and chronic periodontitis. Gingivitis is defined as an inflammation of the gingiva in which the junctional epithelium remains on or near the enamel covering the crown of the tooth. It is characterized clinically by redness, gingival bleeding, edema or enlargement, and occasional gingival sensitivity and tenderness (Genco 1990a). Chronic periodontitis (previously called adult periodontitis) is an inflammation of the gingiva and the adjacent attachment apparatus that is characterized by loss of clinical attachment because of destruction of the periodontal ligament and loss of the adjacent supporting bone (Flemmig 1999). Clinical features of chronic periodontitis may include edema, erythema, gingival bleeding upon probing, periodontal pocketing, or suppuration.

The most common forms of both gingivitis and periodontitis involve bacterial infection. Severe forms of periodontitis often are associated with infection by specific bacteria that colonize the subgingival area (Genco 2000). Destruction of soft tissue and alveolar bone is thought to involve toxins and proteases produced by the bacteria as well as hyperresponsiveness and reactivity of various components of the immune system (e.g., the production of cytokines and prostaglandins). Smoking may play a role in the pathogenesis of periodontal diseases by altering immune function and tissue repair.

The understanding of the distribution and natural history of periodontitis has evolved over the past several decades. Previously, it was thought that virtually all persons were susceptible to severe disease if oral hygiene was inadequate. The disease was considered to progress in a linear fashion throughout life from gingivitis to periodontitis to bone loss to tooth loss, generally attacking the entire dentition and was nearly universal among adults (World Health Organization 1961). This concept was driven, in part, by epidemiologic indices that incorporated signs of both gingivitis and periodontitis, analytic methods that aggregated and averaged measurements within persons and populations, and assumptions about disease progression on the part of the early oral epidemiologists. In the current model of periodontal diseases, a small proportion of persons in most populations are considered to have severe periodontitis; periodontitis is usually preceded by gingivitis but few sites with gingivitis later develop periodontitis; periodontal tissues can undergo some degree of self-repair; and generalized forms of periodontitis are uncommon (American Academy of Periodontology 1996; Burt and Eklund 1999).

Based on current concepts of periodontitis, clinical or epidemiologic assessment of the disease involves detailed measurements of various signs of soft tissue or bone destruction at two to six sites per tooth either on all teeth or on selected teeth. Among the most common measurements is probing pocket depth (PPD), which is measured by inserting a calibrated probe into the gingival sulcus and recording the distance in millimeters from the gingival margin to the base of the gingival sulcus (if healthy) or pocket (if diseased). Because the pathogenesis of periodontitis involves destruction of the junctional epithelium at the base of the sulcus, a PPD greater than 4 mm may indicate disease (Genco 1990b). Another common parameter is the clinical attachment level (CAL), which is measured as distance in millimeters from the CEJ to the base of the gingival sulcus or pocket. It is a direct measure of the position of the periodontal epithelial attachment of a tooth relative to its ideal position at the CEJ. Many cross-sectional studies have used the terminology “loss of periodontal attachment” (LPA) to describe this same parameter, although more recent studies tend to reserve the use of the term LPA for longitudinal assessments of change in the CAL between two points in time. The longitudinal change in CAL is sometimes called relative attachment loss, particularly when computer-linked electronic periodontal probes are used to record the measurements from a fixed reference point such as a cusp tip. Examples of all of these parameters and terms are found in the epidemiologic literature on the association between smoking and periodontal destruction. Because periodontal destruction may occur without deep pocket formation, PPD alone will underestimate disease and may not be sufficient as the prime indicator of disease (Goodson 1990). Intraoral radiographs have been used to assess alveolar bone loss from periodontitis, but this approach can have low sensitivity and may underestimate true bone loss (Goodson 1990; Eickholz and Hausmann 2000; Pepelassi et al. 2000). In addition, radiography often is not logistically feasible or acceptable to examinees during large-scale field epidemiologic studies. At this time, change in the CAL is considered the prime indicator of periodontal destruction.

Biologic Basis

Microbiology

It is possible that cigarette smoking affects periodontal health by altering the quantity or composition of bacterial dental plaque. Although some studies found that smokers had more visible bacterial plaque than nonsmokers (Sheiham 1971; Bastiaan and Waite 1978; Lavstedt et al. 1982; Preber and Bergström 1985), many other studies reported no significant differences in mean plaque levels or rates of plaque accumulation (Alexander 1970; Swenson 1979; Bergström 1981, 1990; Feldman et al. 1983; Macgregor et al. 1985; Bergström and Eliasson 1987a,b; Lie et al. 1998). Cross-sectional differences in plaque levels between smokers and nonsmokers may be due to differences in oral hygiene practices rather than to smoking per se (Preber and Kant 1973; Andrews et al. 1998). However, the presence of specific bacterial species in periodontal plaque may be more important than the quantity of visible plaque and debris on the teeth in the pathogenesis of severe periodontitis (Genco 1996). Some evidence indicates that smokers may be more likely than nonsmokers to harbor specific periodontal pathogens. A study of adults exhibiting a wide range of periodontal conditions (Zambon et al. 1996) found that subgingival infection with Bacteroides forsythus was more common in current smokers even after adjusting for disease severity, with a dose-response relationship between the amount of smoking and infection. Current smokers were also more likely than former or lifetime nonsmokers to have subgingival infection with Actinobacillus actinomycetemcomitans. Consistent with those findings, a study of dental clinic patients found that plaque samples from smokers were 11 times more likely than samples from nonsmokers to test positive for one of three periodontal pathogens (Kazor et al. 1999). In a study of young adults with early-onset periodontitis (Kamma et al. 1999), 11 postulated periodontal pathogens were detected more frequently and in greater numbers in the subgingival plaque from smokers than from nonsmokers. Smoking may increase the likelihood of infection with periodontal pathogenic microorganisms even among persons with no clinical signs of disease. In a study of young adults who did not have periodontitis (Shiloah et al. 2000), smokers were 18 times more likely than nonsmokers to have at least one of eight periodontal pathogens in their sub-gingival plaque. Several studies, however, reported no differences in the plaque bacteria between smokers and nonsmokers (Preber et al. 1992; Stoltenberg et al. 1993). Additional evidence suggests that smoking may act synergistically to potentiate the effects of toxins produced by periodontal pathogenic bacteria (Sayers et al. 1999).

Immune Function

There is substantial evidence that smoking affects both localized and systemic components of the immune system, although the links between these effects and periodontal disease remain to be established. Smoking increases the number but impairs the functions of polymorphonuclear leukocytes (PMNs, or neutrophils), peripheral blood cells that represent the first line of defense against microorganisms (Noble and Penny 1975; Barbour et al. 1997). Either an impairment of the PMN’s ability to neutralize periodontal infections or an overstimulation of potentially tissue-destructive processes can lead to periodontal destruction (American Academy of Periodontology 1999). For example, smoking can impair PMN chemotaxis, phagocytosis, and oxidative burst (Eichel and Shahrik 1969; Kenney et al. 1977; Ryder et al. 1998). Impaired phagocytosis has been implicated in refractory periodontitis (MacFarlane et al. 1992). Smoking also appears to compromise the function of macrophages, which play a vital role in both humoral and cell-mediated immunity, and of B lymphocytes, the major cell type involved in the humoral immune system. Exposure to cigarette smoke also appears to have an immunosuppressive effect on T lymphocytes, which may reduce antibody response to periodontal bacteria (Barbour et al. 1997). Smokers may have a decreased production of antibodies specific to periodontal pathogens, especially IgG2 (Quinn et al. 1998). Recent evidence suggests that levels of cytokines in gingival crevicular fluid, which are secreted by mononuclear cells and are associated with collagen destruction and bone resorption, may be increased in smokers (Boström et al. 1998a,b). Furthermore, there may be a synergistic interaction between smoking and the genotype for a specific cytokine, IL-1, in the development of severe periodontitis (Kornman and di Giovine 1998).

Gingival Blood Flow and Soft Tissue Effects

It has long been hypothesized that the peripheral vasoconstrictive effect of tobacco smoke and nicotine reduces gingival blood flow and thereby impairs the delivery of oxygen and nutrients to gingival tissue. There is some evidence of reduced blood flow in gingival tissues (Clarke et al. 1981; Clarke and Shephard 1984) and reduced size and altered morphology of capillaries in oral mucosa and gingival tissues (Johnson et al. 1989) following exposure to tobacco smoke or nicotine. However, more recent evidence appears contradictory (Baab and Öberg 1987; Johnson et al. 1991). Smokers tend to exhibit less gingival bleeding than nonsmokers, even with control for bacterial plaque levels (Preber and Bergström 1985, 1986; Bergström and Preber 1986; Bergström 1990; Danielsen et al. 1990; Newbrun 1996). However, this reduced gingival bleeding may be related more to the suppression of an inflammatory response than to reduced gingival blood flow.

Nicotine can be stored in and released from periodontal fibroblasts, possibly affecting their morphology and ability to attach to root surfaces (Raulin et al. 1988; Hanes et al. 1991; James et al. 1999). In addition, nicotine may inhibit the growth of gingival fibroblasts and their production of collagen and fibronectin, components of the gingival extracellular matrix involved in the structure and attachment of gingiva (Tipton and Dabbous 1995). Thus, it is possible that smoking impairs the ability of periodontal tissues to repair damaged junctional epithelium. Smoking impairs wound healing and compromises the prognosis following surgical and nonsurgical periodontal therapy (Preber and Bergström 1990; Ah et al. 1994; Newman et al. 1994; Rosenberg and Cutler 1994; Preber et al. 1995; Tonetti et al. 1995; Grossi et al. 1996, 1997; Kaldahl et al. 1996; Kinane and Radvar 1997; Trombelli and Scabbia 1997; Boström et al. 1998b; Machtei et al. 1998; Renvert et al. 1998; Palmer et al. 1999; Papantonopoulos 1999; Söder et al. 1999). One study that employed statistical modeling of longitudinal changes in the CAL concluded that diminished capacity for repair, rather than direct tissue damage, probably was the major mechanism involved in smoking-associated periodontal destruction (Faddy et al. 2000).

Epidemiologic Evidence

Epidemiologic studies of smoking and periodontitis have employed a variety of case definitions for disease, using various combinations of PPD, CAL or LPA, and alveolar bone loss. Some studies used indices for “periodontal disease” that are no longer considered valid indicators for the prevalence of disease in populations (Burt and Eklund 1999). Other studies employed indices that originally were intended for use in population-based treatment planning and not for etiologic studies, such as the Community Periodontal Index of Treatment Needs (Ainamo et al. 1982). Some studies did not use a case definition for disease, but instead assessed mean levels of one or more clinical parameters among exposed and unexposed groups, or described the proportion of the study population that exceeded various measurement thresholds (e.g., ≥4 mm LPA). Some studies, primarily conducted before the 1970s, provided no case definition other than diagnosis by the examiner. Despite the numerous problems measuring the disease, published epidemiologic and clinical studies consistently show a moderate to strong degree of association between smoking and periodontitis.

To identify epidemiologic studies of smoking and periodontitis, the National Library of Medicine’s PubMed database was searched for English language publications from 1965–2000, using the following Medical Subject Headings (MeSH) key words: “smoking,” “tobacco,” “periodontal diseases,” and “periodontitis.” These terms also were searched as title words. The smoking and health database maintained by the Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion, CDC, was also searched using those terms as key words. Reference lists from published studies, review articles, and textbooks were examined to identify additional studies.

Tables 6.21 through 6.23 summarize the findings from 6 case-control studies, 52 cross-sectional studies, and 12 cohort studies conducted between 1959 and 2000. The case-control studies consistently found that persons with periodontitis were more likely than controls without periodontitis to be smokers, although not all studies separated current smokers from former smokers in their analyses. These studies generally controlled for potential confounders in either the selection of a control group or in their analyses. Cross-sectional studies that attempted to estimate parameters such as the odds ratio (OR) consistently reported moderate to strong degrees of association between smoking and periodontitis under a wide range of case definitions (Beck et al. 1990; Horning et al. 1992; Haber et al. 1993; Stoltenberg et al. 1993; Grossi et al. 1994, 1995; Sakki et al. 1995; Tomar et al. 1995; Ahlberg et al. 1996; Dolan et al. 1997a; Norderyd and Hugoson 1998; Shizukuishi et al. 1998; Wakai et al. 1999; Tomar and Asma 2000). Consistent with the findings from case-control and cross-sectional studies, cohort studies reported RR estimates for smoking and onset or progression of periodontitis of 1.4 to more than 10, using a wide range of outcome measures. Of the cross-sectional studies that examined the relationship separately for current smokers and former smokers, current smokers were more likely than former smokers to have periodontitis (Haber et al. 1993; Dolan et al. 1997a; Wakai et al. 1999; Tomar and Asma 2000). Two case-control studies (Haber and Kent 1992; Gelskey et al. 1998) and several cross-sectional studies (Grossi et al. 1994, 1995; Norderyd and Hugoson 1998; Wakai et al. 1999; Tomar and Asma 2000) reported a significant dose-response relationship between the number of cigarettes smoked per day and disease status. Two of these studies used cigarette-years2 or pack-years as the measure for exposure (Grossi et al. 1994, 1995), which combined quantity and duration of smoking to characterize the exposure. One study reported a significant dose-response relationship between the duration of smoking and disease risk (Tomar and Asma 2000). That study also found a significant inverse relationship between the number of years since quitting smoking and the odds of having periodontitis.

Table 6.21. Case-control studies on the association between smoking and periodontitis.

Table 6.21

Case-control studies on the association between smoking and periodontitis.

Table 6.22. Cross-sectional studies on the association between smoking and periodontitis.

Table 6.22

Cross-sectional studies on the association between smoking and periodontitis.

Table 6.23. Cohort studies on the association between smoking and periodontitis.

Table 6.23

Cohort studies on the association between smoking and periodontitis.

Nearly all other reviewed studies reported either mean measures of PPD or CAL/LPA or radiographically demonstrated alveolar bone loss by smoking status, or they reported the percentage of persons with some specified number or percentage of sites exceeding some threshold on one or more of these clinical parameters. With only one exception (Preber et al. 1980), all cross-sectional and cohort studies that measured differences in mean CAL/LPA or mean PPD found a worse periodontal status among smokers than among nonsmokers. That 1980 study (Preber et al. 1980), however, was conducted with young military recruits whose duration of smoking must have been relatively short because of their age.

Evidence Synthesis

The available epidemiologic literature is highly consistent in showing a moderate to strong association between cigarette smoking and periodontal destruction. The association is robust across a wide range of case definitions, populations, and study designs. There is also evidence of a dose-response relationship between smoking intensity and risk for periodontitis. Both number of cigarettes smoked and duration of smoking are positively associated with disease risk. The risk of periodontitis appears to decrease after smokers stop smoking, with a decreasing risk as the duration of successful cessation increases. Although only a few prospective cohort studies have been carried out, they consistently found that smokers were more likely than nonsmokers to experience the onset or progression of disease. The association cannot be explained by confounding.

The mechanisms involved in smoking-associated periodontal destruction are still not fully understood. However, available evidence supports several hypotheses. An immune mechanism is plausible because smoking affects many elements of the human immune system. The effects of smoking on local and systemic immune factors may make the smoker more susceptible to bacterial infection. In addition, substantial evidence indicates that smoking impairs the regeneration and repair of periodontal tissues. The evidence is inconsistent in suggesting that smoking quantitatively or qualitatively alters the microflora of subgingival plaque.

Conclusion

1. The evidence is sufficient to infer a causal relationship between smoking and periodontitis.

Implications

Smoking intervention should be a major component of prevention and treatment of periodontitis. A recent study (Tomar and Asma 2000) concluded that more than 50 percent of the cases of adult periodontitis in the United States are attributable to cigarette smoking. In light of this conclusion, and because more than one-half of U.S. adult smokers visit a dentist each year (Tomar et al. 1996), the dental care community has both the opportunity and the professional obligation to counsel patients who smoke to quit. The dental office may also provide an opportune setting for tobacco use prevention efforts among young people (Hovell et al. 1996). Unfortunately, a lack of awareness and inadequate skills may be barriers to further involvement by dentists and dental hygienists (Secker-Walker et al. 1994; Dolan et al. 1997b).

Further research is needed to achieve a greater understanding of the mechanisms involved in smoking-associated periodontitis. In addition, more behavioral research is needed to enhance the willingness and ability of dentists and dental hygienists to intervene in their patients’ use of tobacco and to counsel younger patients against tobacco use. Educational research should identify effective methods for training students of dentistry and dental hygiene, as well as licensed clinicians, to become competent at counseling their patients to stop using tobacco and assisting patients who want to quit (Tomar et al. 1996; Barker and Williams 1999; Cabana et al. 1999).

Dental Caries

Dental caries is an infectious, communicable, multifactorial disease in which bacterially produced acids dissolve the hard enamel surface of a tooth (Featherstone 1999). Unchecked, the bacteria may then penetrate the underlying dentin and progress into the soft pulp tissue, which is rich in blood and nerve tissue. Dental caries commonly results in loss of tooth structure and discomfort. Untreated dental caries commonly progresses to incapacitating pain and a bacterial infection that leads to pulpal necrosis, tooth extraction, and loss of dental function, and can progress to an acute systemic infection. The major etiologic factors for this disease are thought to be specific bacteria in dental plaque (particularly Streptococcus [S.] mutans and S. lactobacilli) on susceptible tooth surfaces and the availability of fermentable carbohydrates.

Most epidemiologic studies conducted during the past 60 years have used some variation of the decayed, missing (due to caries), or filled permanent teeth (DMFT) index (Klein et al. 1938) to measure the frequency of dental caries. Until the mid-1980s the proportion of the population with dental caries was rarely used to estimate disease prevalence in industrialized populations because the disease was nearly universal. The DMFT index is more a measure of disease severity than of disease prevalence; it is simply the sum of the number of permanent teeth (T) that are decayed (D), missing due to dental caries (M), or filled (F). This index, if applied to the number of coronal (i.e., enamel-covered) tooth surfaces (S), is designated the DMFS. The M component is often omitted in adult studies because of the inherent uncertainty as to why a tooth is missing. Thus, some studies report DFT or DFS scores. Other studies report the components of DMFT individually, such as DS, FS, and MS. Nearly all studies aggregate DMF data by reporting the population mean. The number of root surfaces affected by caries is almost always scored and reported separately from coronal caries, and usually is designated as RDFS or RDS (the M component is not reported for root-surface caries).

Biologic Basis

There are several hypothesized mechanisms that may underlie the association between smoking and dental caries. As discussed in the section on smoking and periodontitis, evidence is inconsistent in showing that smoking per se alters either the bacterial profile in the gingivi or the rate of formation of dental plaque (Alexander 1970; Swenson 1979; Bergström 1981, 1990; Feldman et al. 1983; Macgregor et al. 1985; Bergström and Eliasson 1987a,b; Lie et al. 1998). Differences in oral care behavior between smokers and nonsmokers provide an indirect explanation. Perhaps the most consistent explanation is that smokers tend to practice less frequent or less effective oral hygiene and plaque removal (Preber and Kant 1973; Macgregor and Rugg-Gunn 1986; Andrews et al. 1998).

Several studies concluded that smoking might lower the pH or reduce the buffering capacity of saliva (Heintze 1984; Parvinen 1984), impairing the function of saliva as a protective factor against enamel demineralization (Edgar and Higham 1996). In contrast, one review concluded that smoking increases salivary flow rate (Macgregor 1989), raising pH and increasing salivary calcium concentration (ten Cate 1996). These factors would tend to favor enamel remineralization, but benefit would come only if the flow rate increase were sustained. Another comprehensive review concluded that smoking has a minor effect on saliva flow rate and its chemical composition, at least in terms of factors thought to affect dental cariogenesis (Christen et al. 1991). In sum, an effect of smoking on salivary function does not appear to be a key mechanism in causing dental caries.

The association between smoking and root-surface caries suggested by several studies may be due, in part, to the periodontal effects of smoking. The loss of periodontal attachment and subsequent exposure of root surfaces are necessary conditions for root-surface caries to occur (Burt et al. 1986; Stamm et al. 1990). Persons who experience a loss of periodontal attachment attributable to smoking may also be at greater risk for subsequent root-surface caries.

Epidemiologic Evidence

To identify the epidemiologic studies on smoking and dental caries, the National Library of Medicine’s PubMed database was searched for English language publications from 1965–2000. The following MeSH key words were used: “smoking,” “tobacco,” “dental caries,” and “tooth demineralization.” These terms also were searched as title words. The smoking and health database maintained by CDC’s Office on Smoking and Health was also searched using the same terms as key words. Reference lists from published studies, review articles, and textbooks were sources for additional studies.

Table 6.24 summarizes 12 cross-sectional studies and 3 cohort studies published between 1952 and 1999. Most cross-sectional studies used some variation of the DMF index to measure caries prevalence; all but two (Hart et al. 1995; Tomar and Winn 1999) found that smokers experienced more coronal dental caries than nonsmokers, as measured by mean DS, DFS, DMFS, or DMFT. In general, differences between smokers and nonsmokers in mean DMFT or DMFS were small, even in studies in which the differences were reported to be “statistically significant.” The largest differences in numbers of carious lesions were reported in studies that used DMFS (Ludwick and Massler 1952; Ainamo 1971; Zitterbart et al. 1990; Axelsson et al. 1998). None of those studies, however, appeared to limit the “missing” component of DMFS to those tooth surfaces lost due to caries. Consequently, these studies may mix caries caused by smoking with the advanced periodontal destruction that can cause tooth loss in adults.

Table 6.24. Cross-sectional and cohort studies on the association between smoking and dental caries.

Table 6.24

Cross-sectional and cohort studies on the association between smoking and dental caries.

Few of the studies on the association between smoking and dental caries controlled for potential confounding factors. Although the observed association between smoking and dental caries may reflect a causal relationship, it is also possible that it reflects factors common to both smoking and the risk of dental caries. For example, in industrialized nations both dental caries (USDHHS 2000) and cigarette smoking (Giovino et al. 1995) are more prevalent among groups with lower socioeconomic status (SES) than among higher SES groups. SES is a strong correlate of factors that affect dental caries status, such as diet, use of dental services, and oral hygiene practices (USDHHS 2000). None of the studies adjusted for SES or other potential confounding factors in examining the association between smoking and dental caries. Several literature reviews do suggest that the association between smoking and dental caries may reflect the tendency for smokers to practice less effective dental hygiene and plaque removal (Macgregor 1989; Christen et al. 1991; Kassirer 1994; Andrews et al. 1998).

Few studies adjusted for other notable correlates of both smoking and dental caries in their analyses. The DMF index is a cumulative, irreversible index. As persons experience decayed or filled permanent tooth surfaces or lose teeth over their lifetimes, their DMFT or DMFS scores will increase. Therefore, DMFT and DMFS can be associated strongly with age even if age per se is not a risk factor for incidence of dental caries. Few studies, however, adjusted for age in their analyses. Several studies provided age-specific mean caries scores (Ludwick and Massler 1952; Zitterbart et al. 1990; Axelsson et al. 1998) or age-specific significance testing of differences in means (Hirsch et al. 1991), which revealed an inconsistent association between smoking and caries within age groups. In the one study that used a nationally representative sample of U.S. adults and adjusted for age and race or ethnicity, DFT and DMS were actually slightly lower among male smokers than among those who had never used tobacco (Tomar and Winn 1999).

Two studies attempted to investigate a dose-response relationship between smoking and dental caries (Ludwick and Massler 1952; Ainamo 1971). Although smokers in the highest category of cigarettes smoked per day had experienced slightly higher DMFT, DMFS, or DS than those in the lowest dose categories, the relationship was not consistent. The first study presented age-specific comparisons of mean DMFT and DMFS by the number of cigarettes smoked per day, which showed no clear pattern within age strata. The second study did not present age-stratified or age-adjusted estimates, which potentially could present difficulties in interpreting the association between a disease index that is cumulative with age and an exposure that probably was increasing with age in the study population (aged 18 through 26 years).

Smoking may be associated more with root-surface caries than with coronal caries. Two cohort studies (Ravald et al. 1993; Locker 1996) and two cross-sectional studies (Locker 1992; Tomar and Winn 1999) reported higher mean RDFS or RDS scores among smokers, but in one cohort study (Locker 1996) smoking was not found to be a significant predictor of root-surface caries in multiple logistic regression modeling.

Evidence Synthesis

Few studies have investigated the association between cigarette smoking and dental caries. The available literature is fairly consistent in suggesting that smokers may experience slightly more decayed, missing, or filled coronal tooth surfaces. In addition, smokers generally experienced more decayed or filled root surfaces than nonsmokers. However, many of the published studies did not address potential confounders of these associations. It is therefore possible that the observed associations could reflect in part the presence of other factors associated with both smoking and dental caries. Evidence for a dose-response relationship is sparse and inconsistent. Studies that examined whether quitting smoking reduced the risk of caries development were not identified.

There is little evidence for a biologic mechanism that would explain the role of smoking in the development of coronal dental caries. Methodologic considerations limit the interpretation of findings from epidemiologic studies. The few lines of investigation undertaken have been inconsistent in identifying either bacterial or salivary effects that would be expected to increase this risk.

Some evidence suggests that smoking may indirectly increase the risk for root-surface caries. The mechanism probably involves an increased exposure of root surfaces of teeth secondary to loss of periodontal attachment. This relationship may reflect the impact of smoking on periodontium and the subsequent exposure of tooth root surfaces to the oral environment.

Conclusions

  1. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and coronal dental caries.
  2. The evidence is suggestive but not sufficient to infer a causal relationship between smoking and root-surface caries.

Implications

To better characterize the relationship between cigarette smoking and dental caries, future investigations will need to control for potential confounding factors. These studies should be of the cohort design to allow for assessments of the effect of smoking on carious lesion formation and to determine whether smoking cessation reduces disease incidence. Investigations into an association between smoking and root-surface caries will need to apply indices that take into account the number of root surfaces at risk, such as the Root Caries Index (Katz 1980), or control for root surface exposure in trying to identify whether smoking acts through a direct or indirect mechanism.

The increased risk for root-surface caries may be due to smoking-associated periodontal destruction and subsequent exposure of root surfaces of teeth to the oral environment. Because of the causal relationship between smoking and periodontitis as well as with many other diseases, and because more than one-half of U.S. adult smokers visit a dentist each year, the dental care community has both the opportunity and the professional obligation to counsel patients who smoke to quit.

Erectile Dysfunction

Erectile dysfunction, defined as the persistent inability to attain and maintain penile erection adequate for satisfactory sexual performance (National Institutes of Health [NIH] Consensus Development Panel on Impotence 1993), has recently received considerable attention as a major medical issue in the United States. Additional emphasis has been given to this condition with increasing recognition of its profound impact on quality of life (Wagner et al. 2000). Epidemiologic data, though sparse, indicate its importance as a public health problem. The prevalence of erectile dysfunction in 1992 was estimated to be 18 percent among men 50 through 59 years of age according to the National Health and Social Life Survey, a United States probability sample of men and women aged 18 through 59 years (Laumann et al. 1999). Among men 40 through 70 years of age, prevalence estimates of complete erectile dysfunction during 1987–1989 exceeded 10 percent and estimates of at least mild erectile dysfunction exceeded 50 percent, according to the Massachusetts Male Aging Study (Feldman et al. 1994). Incidence estimates of erectile dysfunction during 1995–1997, derived from longitudinal results of the Massachusetts Male Aging Study, approach 26 cases per 1,000 men annually (Johannes et al. 2000).

Many conditions have been implicated as causes of erectile dysfunction, including hormonal derangement, psychogenic influences, neurologic disorders, and vascular impairment, which may all interfere with the basic physiologic mechanisms involved in penile erection. Vascular impairment, which commonly refers to disease states that hamper penile blood flow, warrants particular attention for several reasons. Most importantly, vascular diseases are commonly associated with presentations of erectile dysfunction. Objectively demonstrable erectile dysfunction has been found in patients with myocardial infarction, coronary bypass surgery, cerebral vascular accidents, peripheral vascular disease, and hypertension (Melman and Gingell 1999). Furthermore, reports of patients with vasculogenic erectile dysfunction have suggested predisposing vasculopathic risk factors, which include cigarette smoking, fatty diets, adverse serum lipid levels, hypertension, physical inactivity, and obesity (Goldstein and Hatzichristou 1994). Several large epidemiologic studies have explored the extent to which these factors impair erectile function (Feldman et al. 1994; Derby et al. 2000b; Feldman et al. 2000; Johannes et al. 2000). The results of these studies also imply that modifications of risk factors may reduce the occurrence of erectile dysfunction.

Among widespread concerns about adverse health effects associated with cigarette smoking is the growing belief that this activity adversely affects sexual health and, in particular, erectile function. It is plausible that cigarette smoking exerts atherogenic effects on penile circulation relevant to erectile function, akin to effects on coronary circulation associated with heart disease (Fried et al. 1986; Raichlen et al. 1986). Furthermore, cigarette smoking cessation may afford a preventive strategy for reducing erectile dysfunction rates. However, each of these hypotheses requires a critical examination of the evidence regarding the effects of smoking on penile erection. This chapter summarizes and evaluates current observational and experimental data linking cigarette smoking and tobacco use with erectile dysfunction, including the patho-physiologic concepts.

Conclusions of Previous Surgeon General’s Reports

This topic has received some coverage in prior Surgeon General’s reports. The 1964 report (U.S. Department of Health, Education, and Welfare [USDHEW] 1964) included a discussion on masculinity in relation to COPD. The discussion drew from an investigation that defined the “element of masculinity as indicated by external morphologic features,” and contended that “weakness of the masculine component is significantly more frequent in smokers than in nonsmokers, and most frequent in heavier smokers” (USDHEW 1964, pp. 383–4). This vaguely described element merely relates to the theme of male sexual prowess, as erectile ability or lack thereof was not directly assessed. The Advisory Committee to the Surgeon General recognized the tentative nature of the conclusions and the need for further confirmation. The 1990 report carried out a comprehensive review of sexual activity and performance, and sperm density and quality (USDHHS 1990). This review did not lead to specific conclusions, reflecting limitations of the available data and their inconsistency. This section reviews the issue of male sexual function, examining the influence of cigarette smoking on penile erection, one specific component of male sexual function.

Biologic Basis

Direct biologic evidence establishing plausible mechanisms for the effects of cigarette smoking on penile erection certainly would strengthen the premise that cigarette smoking constitutes a risk factor for erectile dysfunction. One possible mechanism is smoking-induced endothelial dysfunction of the penile vasculature. This hypothesis is supported by recent investigations into the physiology of penile erection affirming that the endothelium of the blood vessels supplying the penis, as well as that lining the lacunar spaces within the penis, releases vasoactive substances that contribute to the control of penile smooth muscle relaxation required for penile erection (Lue and Tanagho 1987).

Saenz de Tejada and colleagues (1989) probed whether smoking affects penile vasculature endothelium as part of an investigation of the consequences of diabetes mellitus on endothelial function in the penis in men with erectile dysfunction. Using isolated strips of human corpora cavernosa of the penis, the investigators compared isometric tension results from men with and without diabetes who were smokers (having at least a five pack-year history of cigarette smoking) or nonsmokers. The findings indicate that a history of smoking was not associated with a worsened impairment of endothelium-mediated relaxation responses. The study did not assess responses of tissue from smokers independently while controlling for other possible erectile dysfunction risk factors, nor did it carry out a subset analysis of responses from smokers specified to have had large amounts of cigarette smoke exposure. These limitations restrict the conclusions that can be drawn concerning the effects of smoking on endothelial function in the penis.

In a study of rats, Xie and colleagues (1997) examined the long-term effects of smoking on the endothelial synthesis of nitric oxide in the penis. Nitric oxide is now known to be the principal vasoactive mediator of penile erection (Burnett 1997). Nitric oxide is released by endothelial cells in response to direct cholinergic stimulation and in response to dynamic factors of changing penile blood flow. In the study, rats were passively exposed to cigarette smoke in 60-minute sessions once per day, five days per week, for eight weeks. Immunoblot analyses of the protein expression of endothelial nitric oxide synthase (eNOS) in penile tissue from the exposed rats did not reveal any diminution of eNOS expression compared with tissue from control rats. However, these investigators confirmed that overall nitric oxide synthase enzymatic activity (which combines neuronal and endothelial sources) and specifically the protein expression of the neuronal form of nitric oxide synthase in the penis were both markedly reduced following passive exposure to cigarette smoke in rats as compared with rats not exposed to smoke. Their findings mainly suggest that smoking selectively impairs neuronal mechanisms, in particular the neuronally based nitric oxide signal transduction pathway associated with penile erection. But the relevance of the rat model for humans is uncertain.

The investigation by Saenz de Tejada and colleagues (1989) also evaluated whether smoking affects the neurogenic mechanisms responsible for penile erection. The overall finding was that the impairment of neurogenically mediated relaxation of penile smooth muscle from smokers (combining results from men with and without diabetes) was not different from the impairment observed in nonsmokers (both men with and without diabetes). However, these conclusions have the same limitations as those concerning endothelial effects observed in this study (see above). An in vitro investigation of neuromuscular transmission in human corpus cavernosum also studied nicotine and found that the actions of this agent are both contractile and relaxant (Adaikan and Ratnam 1988). If erectile dysfunction results from exogenously administered nicotine during cigarette smoking, it may be due to the acute vasoactive modulatory effects of this agent on the penile vasculature.

Epidemiologic Evidence

Observational Data

This section explores the association between cigarette smoking, as well as other forms of tobacco use, and the occurrence of erectile dysfunction based on a review of available observational data. A literature search was conducted using the National Library of Medicine’s PubMed system and was supplemented with professional knowledge of other resources. The critical feature of the observational data is the necessary reliance on self-reporting and other subjective instruments (e.g., logs, questionnaires, and sexual function inventories) to determine tobacco exposure and erectile performance, rather than quantitative measurements of these variables. A single-item assessment (e.g., “Do you experience difficulty getting and/or maintaining an erection that is rigid enough for satisfactory sexual intercourse?”) has gained prominence particularly for population-based epidemiologic studies (Derby et al. 2000a). This assessment has been useful as a single, direct practical tool to ascertain the presence of erectile dysfunction, whereas clinical questions are impractical (Derby et al. 2000a). This data collection methodology does introduce the possibility of information bias, probably toward underreporting. Differential underreporting by smoking status would bias estimates of the effects of smoking; however, the findings do prove insightful as to its probable significance within the general population. Furthermore, aspects of compromised sexual function are fundamentally issues of a subjective nature, wherein patient self-reporting may accurately serve as the main, or even the sole, criterion for establishing the existence and severity of the problem.

Case Series

Cigarette smoking has been linked to erectile dysfunction in several clinical reports, most qualifying as observational case series. As such, they are limited by not having true comparison groups, but they are reviewed here because they are often cited and data from more formal studies are limited. Wabrek and colleagues (1983) found that approximately 50 percent of 120 men referred for evaluation and management of erectile dysfunction to a hospital-based medical sexology program were smokers, counting users of cigarettes, cigars, or pipes. Virag and colleagues (1985) confirmed a 64 percent rate of cigarette smoking, defined as tobacco use exceeding 15 cigarettes per day for at least 15 years, among 440 men referred for clinical evaluation of erectile dysfunction. Bornman and Du Plessis (1986) similarly observed a 62 percent cigarette smoking rate, based on approximately 25 cigarettes per day for more than 20 years among 300 men screened at an andrology clinic. An attempt to provide comparative information was made by Condra and colleagues (1986), who studied 178 men with erectile dysfunction referred for clinical evaluation and found that 51.4 percent were current smokers and 81 percent were current or former cigarette smokers. These rates exceeded the 38.6 percent and 58.3 percent rates, respectively, ascertained in the general population using concurrent survey data. A recently published meta-analysis of smoking prevalence in men with erectile dysfunction also included a comparative assessment that controlled for age distribution, time period, and geographic location (Tengs and Osgood 2001). This meta-analysis, which consisted of 19 clinical studies published in the last 20 years with data on current smoking, revealed that 40 percent of the combined total of 3,819 men with erectile dysfunction were current smokers compared with 20 percent of men in the general population (Tengs and Osgood 2001).

Population-Based Studies

More valid appraisals of the effects of cigarette smoking on erectile dysfunction have been obtained through cross-sectional, random surveys of a sample population (Table 6.25). The Vietnam Experience Study of 1985–1986, which surveyed 4,462 U.S. Army Vietnam-era veterans aged 31 through 49 years, found erectile dysfunction prevalence rates of 2.2 percent among nonsmokers, 2.0 percent among former smokers, and 3.7 percent among current smokers (p = 0.005). The association (OR = 1.5 [95 percent CI, 1.0–2.2]) was maintained even after adjustments for comorbidity factors including vascular disease, psychiatric problems, hormonal factors, substance abuse, marital status, race, and age (Mannino et al. 1994).

Table 6.25. Cross-sectional studies on the association between smoking and the risk of erectile dysfunction (ED).

Table 6.25

Cross-sectional studies on the association between smoking and the risk of erectile dysfunction (ED).

Additional recent studies support the direct association between cigarette smoking and erectile dysfunction. A cross-sectional study assessing the prevalence of erectile dysfunction in 2,010 men aged over 18 years in Italy in 1996–1997 showed that smoking was associated with an increased risk of the condition (Parazzini et al. 2000). Although the study was controlled for multiple variables including age, marital status, SES, and chronic diseases, it found an increased risk of erectile dysfunction for current smokers (OR = 1.7 [95 percent CI, 1.2–2.4], p <0.05) and for former smokers (OR = 1.6 [95 percent CI, 1.1–2.3], p <0.05) in comparison with lifetime nonsmokers (Parazzini et al. 2000). The Krimpen Study, a community-based study conducted in Rotterdam, the Netherlands, between 1995 and 1998 that surveyed 1,688 men aged 50 to 78 years, also confirmed that smokers professed significant erectile dysfunction (adjusted OR = 1.6 [95 percent CI, 1.1–2.3], p <0.05) to a greater extent than non-smokers (Blanker et al. 2001). A cross-sectional study of erectile dysfunction prevalence conducted in Spain in 1998–1999, consisting of 2,476 men aged 25 to 75 years, demonstrated that cigarette smoking was significantly associated with erectile dysfunction (adjusted OR = 2.5 [95 percent CI, 1.64–3.80], p <0.05) (Martin-Morales et al. 2001).

Another recent study supports the direct association between cigarette smoking and erectile dysfunction (Bacon et al. 2001). The Health Professionals Follow-up Study, a prospective cohort study of heart disease and cancer among U.S. male health professionals (Rimm et al. 1991; Ascherio et al. 1996), surveyed 34,282 men aged 53 through 90 years in 2000. The study showed an increased probability of erectile dysfunction among current smokers compared with nonsmokers (OR = 1.3 [95 percent CI, 1.1–1.6], p <0.05), while controlling for age, marital status, and chronic diseases (Bacon et al. 2001).

Evidence against an independent association between cigarette smoking and erectile dysfunction comes from the baseline phase of the Massachusetts Male Aging Study, a community-based survey conducted from 1987–1989 of 1,290 men aged 40 through 70 years living in the Boston, Massachusetts, area (Feldman et al. 1994). The probabilities of complete erectile dysfunction were 11 percent in smokers and 9.3 percent in nonsmokers, including both former smokers and those who had never smoked (p >0.20) (Feldman et al. 1994). However, the longitudinal phase of the Massachusetts Male Aging Study, extending over a nine-year median interval, showed the comorbidity-adjusted rate of incident erectile dysfunction to be significantly higher among cigarette smokers (24 percent) than nonsmokers (14 percent) (OR = 1.97 [95 percent CI, 1.07–3.63], p = 0.03) (Feldman et al. 2000). The classification of erectile dysfunction was based on an algorithm derived by the discriminant analysis of 13 questions.

Kleinman and colleagues (2000) reanalyzed the baseline data from the Massachusetts study using new methods for classifying erectile dysfunction. One method corresponded to the approach used by Feldman and colleagues (2000), based on responses from men attending a urology clinic to an original questionnaire and to an additional global question for self-rating erectile dysfunction. Another analysis was based on responses to an expanded follow-up questionnaire. Cross-sectional analyses of predictors of erectile dysfunction were carried out in the 1987–1989 baseline data. With the clinic-based method for classification, current smoking was not associated with erectile dysfunction (OR = 0.95 [95 percent CI, 0.72–1.22]) while with the study-based method it was (OR = 1.39 [95 percent CI, 1.07–1.80]).

Disease Correlates

Type of Tobacco Exposure. The prospective analysis of the Massachusetts Male Aging Study examined various types of tobacco exposures to identify associations with erectile dysfunction. The odds of incident erectile dysfunction were more than doubled both for passive exposure to cigarette smoke, if present both at home and at work (adjusted OR = 2.07 [95 percent CI, 1.04–4.13]) (p = 0.04), and for cigar smoking (adjusted OR = 2.45 [95 percent CI, 1.09–5.50]) (p = 0.03). Passive exposure at home or at work alone did not increase the odds of incident erectile dysfunction in nonsmokers, but each increment of exposure did increase the estimated likelihood of erectile dysfunction in smokers (Feldman et al. 2000).

Dose-Response. The relationship between the amount of tobacco exposure and the extent of erectile dysfunction has been subjected preliminarily to epidemiologic analyses. Several population-based studies further explored the effects of measures of exposure on erectile dysfunction. The Vietnam Experience Study did not show any relationship between the number of cigarettes smoked daily or the number of years smoked and erectile dysfunction among currently smoking veterans (Mannino et al. 1994). Similarly, the baseline phase of the population-based Massachusetts Male Aging Study did not reveal any dependence of packs per day or lifetime pack-years smoked on reported erectile dysfunction among current smokers (Feldman et al. 1994). By contrast, an Italian cross-sectional study showed an increased erectile dysfunction risk with duration of the behavior, based on an OR of 1.6 (95 percent CI, 1.1–2.3) for men smoking 20 or more years and an OR of 1.2 (95 percent CI, 1.0–2.4) for men smoking less than 20 years (Parazzini et al. 2000).

Risk Factor Covariates and Effects of Medication. The combined effects (i.e., synergistic or additive interactions) of cigarette smoking and other risk factors in the development of erectile dysfunction have been analyzed. Goldstein and colleagues (1984) examined clinical characteristics in 19 potent patients who underwent pelvic irradiation for prostate cancer, finding that 14 out of 15 who displayed diminished erectile capacity were cigarette smokers, whereas only 1 out of 4 who preserved erectile capacity was a cigarette smoker. The strong association of cigarette smoking with erectile impairment in this study led the investigators to propose a synergistic role of smoking, and conceivably other vasculopathic risk factors, with the radiation effects associated with radiation-induced erectile dysfunction (Goldstein et al. 1984). In the baseline phase of the Massachusetts Male Aging Study, Feldman and colleagues (1994) found that cigarette smoking did not constitute an independent risk factor for erectile dysfunction; however, in that same study, the association of erectile dysfunction with certain risk factors was greatly amplified in current cigarette smokers. This amplification was demonstrated for persons having erectile dysfunction with treated heart disease (from 21 percent for current nonsmokers to 56 percent for current smokers), treated hypertension (from 8.5 to 20 percent), and untreated arthritis (from 9.4 to 20 percent), and for those persons receiving various medications including cardiac drugs (from 14 to 41 percent), antihypertensive medications (from 7.5 to 21 percent), and vasodilators (from 21 to 52 percent). Similarly, in an Italian cross-sectional study, smoking increased the adjusted ORs for erectile dysfunction associated with diabetes by 13 percent and with hypertension by 39 percent (Parazzini et al. 2000).

Effects of Smoking Cessation. The hypothesis that cigarette smoking adversely affects erectile function would seemingly be strengthened by epidemiologic evidence demonstrating that smoking cessation leads to erectile function recovery. Forsberg and colleagues (1979) presented the case reports of two cigarette smokers aged 20 and 27 years with erectile dysfunction whose erectile function returned in concordance with improved penile vascular testing results following smoking cessation. Elist and colleagues (1984) determined that 8 (40 percent) out of 20 men with erectile dysfunction who had smoked one to two packs of cigarettes per day for at least 15 years recovered functional erections after abstaining from cigarette smoking for six weeks. In this study, seven responders (35 percent) were confirmed by objective testing criteria to have recovered normal erectile activity from baseline abnormal levels.

Population-based reports add additional perspectives to the premise that modifying cigarette smoking behavior affects the occurrence of erectile dysfunction. One study in this regard is the Vietnam Experience Study of 1985–1986, which determined that the prevalence of erectile dysfunction among former smokers was comparable to that among nonsmokers, and the prevalence rates were significantly lower than those found in current smokers (Mannino et al. 1994). Similarly, the longitudinal phase of the Massachusetts Male Aging Study determined that incident erectile dysfunction was no more likely among former smokers than among nonsmokers, in contrast to current smokers (Feldman et al. 2000). Results from the Health Professionals Follow-up Study also suggest that former smokers carry a lower risk of erectile dysfunction than current smokers, although this risk for former smokers still exceeds that of nonsmokers (Bacon et al. 2001).

From these population-based study results, one might further conclude that the discontinuation of smoking results in a recovery of functional erection status. However, this simple conclusion is challenged by recent results from the prospective evaluation of men participating in the Massachusetts Male Aging Study who discontinued smoking during the almost nine-year follow-up period of this study. This latter analysis found that the covariate-adjusted incidence of erectile dysfunction was not significantly reduced after smoking discontinuation (p = 0.28). Important considerations of this investigation are that the men who quit smoking had begun smoking at an early age (mean age 16.6 years) and had accumulated a high lifetime exposure to tobacco smoke before quitting (mean pack-years 39.4). The data provide a refined understanding of the effects of cigarette smoking cessation on erectile dysfunction: smoking cessation in middle age after a significant lifetime exposure to cigarette smoke may fail to modify erectile dysfunction occurrence, because long-term vascular effects of smoking conceivably persist after smoking cessation (Derby et al. 2000b).

Clinical Data

This section examines the link between tobacco exposure and erectile dysfunction based on objective clinical criteria. The erectile dysfunction specialty has developed quantitative measurements that serve as indices of erectile function, including physiologic and anatomic descriptions of the physical state of the penis. Numerous investigations have applied these methodologies to ascertain the effects of cigarette smoking and other forms of tobacco use on penile erection.

Penile Tumescence Studies

Nocturnal penile tumescence (NPT) monitoring provides a noninvasive diagnostic technique to quantify erection physiology objectively during the naturally occurring cycle of sleep-related penile erections. These spontaneous episodes of tumescence normally accompany rapid eye movement (REM) sleep and are diminished in men with presumably organic erectile dysfunction (Karacan et al. 1978; Allen and Brendler 1992). Several early investigations of the objective basis for vasculogenic erectile dysfunction applied NPT monitoring. Elist and colleagues (1984) confirmed NPT-monitored abnormalities in 20 smokers with erectile dysfunction, among whom 7 (35 percent) displayed normal NPT-monitored results after six weeks of smoking cessation. Virag and colleagues (1985) determined that smokers comprised 72 percent of patients with abnormal NPT results but only 32 percent of patients with normal NPT results. In a study of 168 men who smoked one or more packs per day (heavy smokers) and 632 men who smoked less than one pack per day (light smokers), Karacan and colleagues (1988) found that sleep-related penile erection rigidity was significantly lower at each decade of life after 30 years of age in heavy smokers compared with light smokers, and the duration of maximal tumescence was significantly lower for heavy smokers aged less than 30 years and 51 through 60 years compared with age-equivalent light smokers. In an investigation of 314 smokers with erectile dysfunction, Hirshkowitz and colleagues (1992) confirmed a significant inverse correlation between sleep-related penile erection rigidity and the number of cigarettes smoked per day (r = −0.12; p = 0.04). These investigators also showed that the duration of maximal tumescence was significantly shorter at the penile base (p ≤0.05), and the duration of detumescence (which refers to the decline from full erection to penile flaccidity) was also shorter (p = 0.06) among men who smoked 40 or more cigarettes per day compared with men who smoked 1 to 19 per day and 20 to 39 per day (p = 0.14).

Penile Vascular Hemodynamics

Impaired blood flow to the penis can be assessed using various measurement techniques. One widely used early technique to assess arterial vascular competence within the penis was the Doppler ultrasound of arterial pulsations in the flaccid, unstimulated organ. Although this method is no longer applied, the findings of these studies may still be relevant with respect to the pathogenesis of smoking-related vascular disease of the penis. With the values obtained, the penile-brachial index (PBI) can be calculated (the PBI refers to the ratio of penile to brachial systolic blood pressures). Reduced PBI values have been associated with impairment of the erectile process (Kempczinski 1979). Using this technique, Wabrek and colleagues (1983) did not find a significant association between cigarette smoking and abnormal PBI values. Virag and colleagues (1985) also did not find an independent smoking effect on PBI, although a synergistic effect was observed with smoking in combination with other arterial risk factors such as diabetes, hyperlipidemia, and hypertension. In contrast, Condra and colleagues (1986) demonstrated significantly lower PBI values among smokers than among nonsmokers. This same study also noted that the amount of time smoked correlated with abnormal PBI values: smokers with normal PBI values had smoked for a mean duration of 19.95 years while those with abnormal PBI values had smoked for a mean duration of 26.55 years. DePalma and colleagues (1987) likewise found that cigarette smoking carried a significantly higher probability of abnormal (49 percent) than normal (28 percent) vascular laboratory findings including PBI, which was not observed for age, hypertension, diabetes, or prior myocardial infarction. Hirshkowitz and colleagues (1992) confirmed consistent PBI reductions among 314 cigarette smokers with erectile dysfunction, finding significant correlations between the number of cigarettes smoked per day and the magnitude of these reductions for the left dorsal artery (r = −0.14; p = 0.01) and right cavernosal artery (r = −0.13; p = 0.03) of the penis.

The vascular evaluation of the penis has more recently employed a pharmacologic stimulus in combination with penile duplex ultrasonography to characterize the penile arteries. This application followed the discovery that a pharmacologic stimulus to induce an artificial erection provides an improved assessment of the physiologic responsiveness of these arteries over that provided during the resting state (Abber et al. 1986). Using this technique and applying a combined set of ultrasonographic parameters to establish normal vascular findings, Shabsigh and colleagues (1991) showed a consistent, nearly statistically significant difference in vascular impairment in smokers compared with nonsmokers. Kadioĝlu and colleagues (1995) also observed that penile vascular parameters were abnormal to a greater extent among smokers than among nonsmokers, although the differences were not statistically significant.

In summary, PBI testing suggests deleterious effects of smoking on the “resting state” circulation of the penis, and sonographic evaluation of the penis following pharmacostimulation additionally demonstrates apparent deleterious effects of smoking on dynamic blood flow changes in the penis.

Penile Vascular Morphology

Arteriographic studies have been conducted in patients with erectile dysfunction to characterize the vascular anatomy of the penis. Investigations have been carried out among cigarette smokers to confirm the presence and location of arteriographic lesions. Virag and colleagues (1985) calculated a 67.8 percent rate of arteriographic abnormalities among patients in whom organic erectile dysfunction had been established by NPT monitoring, of whom 86 percent were smokers. Bähren and colleagues (1988) similarly showed that 82 percent of their patient group with arteriographically proven peripheral arteriosclerotic lesions were heavy smokers. In a study by Forsberg and colleagues (1989), men with erectile dysfunction underwent screening studies of penile blood flow to identify abnormalities. Using both pharmacostimulation and angiography in 17 men, this study found significant distal penile vessel lesions; 14 (82 percent) of the men were identified as smokers. Rosen and colleagues (1991) carried out a comprehensive evaluation of penile circulation in cigarette smokers with erectile dysfunction, finding that smoking represented a significant independent risk factor in the development of atherosclerotic lesions in the internal pudendal and common penile arteries. These investigators also determined that the number of pack-years smoked was independently associated with hemodynamically significant atherosclerotic disease in the hypogastric cavernous arterial bed supplying the penis (for each 10 pack-years smoked, RR = 1.31 [95 percent CI, 1.05– 1.64]).

Histopathology

The effects of cigarette smoking on erectile tissue were investigated by Mersdorf and colleagues (1991), who confirmed degenerative tissue changes (including a decrease in smooth muscle content, sinusoidal endothelium, nerve fibers, and capillaries, and an increase in collagen density) in erectile tissue of smokers. These tissue alterations are consistent with tissue alterations seen in other vascular diseases.

Experimental Data

This section reviews experiments carried out to test the effects of cigarette smoking on erectile function (Table 6.26). These experimental approaches controlled cigarette smoking exposures and provided the possibility for a rigorous evaluation of the consequences for erectile ability. The value of the information was enhanced when experiments involved robust scientific methodology (e.g., a random allocation of people to experimental and control groups, the use of different control groups, and the application of blinding procedures to reduce bias).

Table 6.26. Experimental studies on the association between smoking and erectile dysfunction.

Table 6.26

Experimental studies on the association between smoking and erectile dysfunction.

Human Studies

Perhaps the first reported study to experimentally evaluate the hypothesized association between cigarette smoking and erectile dysfunction was performed by Gilbert and colleagues (1986), who made polygraphic recordings of penile erection responses in smokers during the viewing of erotic videos. Several aspects of this study are noteworthy: (1) the study population consisted of 42 male self-reported heterosexual cigarette smokers in good health, aged 18 through 44 years; (2) participants were assigned to high-nicotine exposure (0.9 mg nicotine per cigarette smoked), low-nicotine exposure (0.002 mg nicotine per cigarette smoked), or control (sucking on a hard mint candy) groups randomly selected and unknown to the experimenter; (3) at enrollment, a counterdemand was issued to the effect that nicotine enhanced sexual potency, to militate against contaminating hypotheses held by the participants about the effects of smoking on erections; (4) smoking abstention was required for two hours before the experiment; (5) baseline erotic videos were shown for participant acclimation; and (6) concomitant measures of cardiovascular response were obtained. The study found that smoking two, but not one, high-nicotine cigarettes significantly decreased the rate of penile diameter increase compared with the other conditions during the erectile stimulus (p < 0.001). It also determined that high-nicotine cigarettes caused significantly more vasoconstriction and heart rate increase than did low-nicotine cigarettes, which did not differ from control conditions (p < 0.001).

In another experiment undertaken to assess the acute effects of cigarette smoking exposure on penile erection, Glina and colleagues (1988) studied the interference of smoking on vasoactive drug-induced erectile responses monitored by intracavernous pressure recording. Study design features were as follows: (1) 12 chronic cigarette smokers, aged 22 through 65 years, were enrolled; (2) subjectively reported erectile function status of the participants at enrollment was not stated; (3) smoking was prohibited on test days; (4) each participant underwent pharmacostimulation consisting of intracavernous injection of 100 mg pa-paverine hydrochloride at baseline (without smoking) and one week later immediately after nicotine exposure (smoking two cigarettes containing 1.3 mg nicotine per cigarette); and (5) intracavernous pressure measurements were performed 20 minutes following pharmacostimulation by the same experimenter. The study found that all men obtained an erection by clinical judgment at baseline compared with only four (33 percent) after smoking, corresponding to a significant decrease in mean intracavernous pressures from 85.83 mm Hg at baseline to 53.50 mm Hg after smoking. As part of an earlier, larger investigation of the use of pa-paverine injections to test diagnostically for erectile dysfunction, Abber and colleagues (1986) described a similar experiment involving a chronic smoker with erectile dysfunction who displayed an acutely worsened erectile response immediately following smoking a cigarette compared with his baseline results.

In a visual depiction of the effects of cigarette smoking on arterial flow to the penis, Levine and Gerber (1990) described their pelvic arteriographic study of a 38-year-old man with a 25 pack-per-year smoking history who presented for evaluation of erectile dysfunction. Whereas a complete baseline evaluation including pelvic arteriographic studies showed no abnormalities, repeat pelvic arteriography immediately after the patient smoked two cigarettes revealed a decrease in the caliber of the entire pudendal artery and nonvisualization of the deep penile artery. The investigators suggested that acute vasospasm was responsible for the observed effects.

Further experimental evidence of the deleterious effects of cigarette smoking on erectile function was recently documented in an acute smoking cessation study by Guay and associates (1998). Ten men, 32 to 62 years of age who had at least a current 30 pack-year smoking history and were smoking one pack of cigarettes or more per day, were enrolled in a study monitoring NPT and rigidity by a home RigiScan® technique. The study required monitoring of sleep-related penile erections on two successive nights, the first night following a usual day of smoking and the second night following discontinuation of smoking for one 24-hour interval. An additional component of the study involved repeat monitoring in four men who did not smoke for one month although they were administered transdermal nicotine patches (21 mg) during this time. The study results show that erectile parameters improved to a statistically significant degree in men who had stopped smoking for 24 hours, with further observed improvements in those not smoking and wearing nicotine patches for one month. The investigators concluded that eliminating cigarette smoking improves erectile function although factors contained in cigarette smoke other than nicotine primarily exert the damaging effects.

Animal Studies

Animal models have provided another useful approach for investigating the association between cigarette smoking and erectile dysfunction. The study by Juenemann and colleagues (1987) using an in vivo canine model represents a comprehensive, well-controlled investigation that combined stimulatory and monitoring techniques relevant to the physiology of erection. The methodology involved monitoring arterial inflow, intracavernous pressure, and venous outflow of the penis during cavernous nerve stimulation of erection alone, and with regulated penile perfusion before and after acute inhalation of cigarette smoke (1.4 mg nicotine per cigarette). Following smoking exposure (one to six cigarettes), compared with nonsmoking baseline conditions, peak arterial inflow was significantly diminished, peak intracavernous pressure was significantly diminished and could not be maintained, and venous outflow was not significantly restricted. Measurable serum nicotine and cotinine levels, obtained in the dogs following smoking exposure and used as markers, were consistent with concentrations found in human smokers, whereas no changes in arterial blood gases or systemic blood pressure were observed throughout the investigation. The investigators concluded that smoking exerts a localized deleterious effect on the neurovascular mechanisms required for penile erection, with a particular impairment of the veno-occlusive mechanism associated with maintenance of penile erections.

In a rat model, Xie and colleagues (1997) evaluated the long-term effects of cigarette smoking on penile erection. The methodology involved monitoring in vivo neurostimulated erections after exposing rats to a constant influx of cigarette smoke in an enclosed cage for a 60-minute session once per day, five days per week, for eight weeks. The investigation surprisingly found increases in intracavernous pressures in smoke-exposed rats compared with controls. However, the rats exposed to cigarette smoke also developed systemic hypertension. Intracavernous pressures standardized to systemic blood pressures in rats exposed to cigarette smoke did not differ from intracavernous pressures found in controls. The investigators explained their findings on the basis of tobacco smoke-associated vasoconstriction, and they conceded that vascular damage commonly associated with long-term cigarette smoking is inappreciable in the rat model, which is resistant to atherosclerosis.

Evidence Synthesis

Available evidence indicates that cigarette smoking constitutes a risk factor for erectile dysfunction. However, the causal basis for this relationship must be carefully evaluated. With regard to the consistency of the relationship, both case series and population-based studies evaluating rates of erectile dysfunction among smokers provide support. The population-based studies afford a more accurate observational basis for this assessment than do uncontrolled case series, although the paucity of these studies hampers reaching a definitive conclusion. The strength of the relationship also rests on limited available information, but is similarly supported by observational evidence showing that a variety of tobacco exposures (including active and passive cigarette smoking and cigar smoking) is associated with erectile dysfunction. Consideration of a dose-response relationship is supported by a few observational and experimental investigations that have shown an increased risk of erectile dysfunction associated with increased exposures to cigarette smoking. The temporality of the relationship seems likely, with a few observational studies showing some evidence of erectile dysfunction following exposure to tobacco smoke. Intriguingly, preliminary observational findings demonstrate that cigarette smoking cessation apparently leads to a recovery of erectile function only if the discontinuation occurs after a limited extent of lifetime smoking.

Coherence of the relationship is supported by several biologic studies that have proposed plausible mechanisms for the deleterious effects of cigarette smoking on erections. The acute deleterious effects of smoking on erectile function result at least in part from nicotine carried in cigarette smoke. The nicotine pharmacologically induces vasospasm of penile arteries, and hence alters the dynamics of local blood flow required for penile erection. The chronic deleterious effects of smoking on erectile function result from impaired vascular physiology of the erectile tissue, as evidenced by degenerative morphologic changes in tissue of smokers. Although the exact mechanism of the impairment remains unclear, early studies in animals point to damaging effects on tissue-dependent erection regulatory factors. In sum, several lines of evidence contribute toward the inference of a causal relationship between cigarette smoking and erectile dysfunction. However, because the scope of observational and experimental evidence remains limited and incomplete, it seems reasonable to consider the evidence to be suggestive but insufficient to establish a causal relationship at this time.

Conclusion

  1. The evidence is suggestive but not sufficient to infer a causal relationship between smoking and erectile dysfunction.

Implications

The clinical studies and basic scientific research summarized in this section suggest a relationship between cigarette smoking and erectile dysfunction. A strong inference that smoking causes erectile dysfunction requires more evidence to confirm initial findings and to fill in gaps in the knowledge base. Additional observational studies of sufficient size and with well-validated outcome measures are needed. More basic scientific studies to identify biologic mechanisms for the deleterious effects of smoking on penile erections also are necessary. In the meantime, current knowledge about the problem still prompts recommendations for smoking cessation and avoidance to limit the risk of erectile dysfunction. Promoting nonsmoking to prevent erectile dysfunction seems clinically appropriate. There may be significant public health benefits by reducing morbidity rates of this increasingly recognized, widespread condition.

Eye Diseases

Diseases of the visual system, and possible subsequent visual loss, represent substantial social and economic concerns to the U.S. public. In the last three decades, Gallup polls have consistently indicated that blindness is second only to mental incapacity as the disability Americans fear most (National Advisory Eye Council [NAEC] 1998). There is ample reason for concern. An estimated 3.4 million Americans aged 40 years and older have visual impairment and 1 million of these people are legally blind. Because most vision loss results from eye disease associated with advancing age, and the “baby boom” population in the United States is aging, the public health impact of this problem is projected to double by 2030 (Prevent Blindness America 2002).

The economic consequences of eye disease for the U.S. population are huge. For example, sight-restoring cataract surgery was the most frequently performed surgical procedure among Medicare beneficiaries, at an estimated annual cost of $3.4 billion in 1991 (Steinberg et al. 1993). Altogether, the economic impact of visual disabilities and disorders was estimated at more than $38.4 billion in 1995 (NAEC 1998). Thus, substantial contributions to the social and economic welfare of the public are possible by finding and controlling the causes of these eye diseases, particularly the factors that present the opportunity to prevent the disease or loss of sight.

Conclusions of Previous Surgeon General’s Reports

Epidemiologic investigation into risk factors for eye disease did not begin in earnest until the 1970s, bolstered by the establishment of the National Eye Institute (NEI) in 1968. Reports of the Surgeon General on smoking and health published before 2001 did not include eye disease as a topic simply because there were scant data indicating that smoking was related to ocular morbidity, although a compelling biologic basis did exist for postulating such associations. At least two of the three leading causes of visual loss worldwide, cataract and age-related macular degeneration (AMD), probably are due, at least in part, to smoking.

Cataract

Cataract is the leading cause of blindness worldwide and a leading cause of visual loss in the United States (Thylefors et al. 1995; Muñoz et al. 2000). Currently, the most common and effective means of restoring vision is through surgical removal of the opacified lens and insertion of an artificial lens into the eye. According to NEI, about 1.35 million cataract operations are performed annually in the United States for Medicare beneficiaries (NAEC 1998), at an estimated cost of $3.4 billion in 1991 (Steinberg et al. 1993). If risk factors that either delay the onset or slow the progression of cataracts could be identified, major socioeconomic gains would be realized. The research findings that link cigarette smoking to cataract, specifically nuclear cataract, have identified one of the few modifiable risk factors for cataract.

The ocular lens is a normally transparent organ having a purely optical function. The lens, situated behind the pupil, focuses radiant energy on the retina to produce an image, much like the lens of a camera. The shape of the lens changes, or accommodates, in response to the distance of the viewed object to focus a sharp image onto the retina.

The transparency of the lens is a function of its peculiar characteristics. The lens itself is composed of a central core, or nucleus, of inert, protein-filled, former epithelial cells. The interior proteins are highly structured to ensure transparency. The lens grows by the constant addition of protein-filled, elongated, former epithelial cells that have differentiated into lens fibers that do not have a nucleus or other organelles. Of interest in this process is that the lens contains every fiber cell ever incorporated into it, including cells formed in the embryo stage through those formed very recently. These cells must maintain transparency throughout the life of an individual to ensure visual clarity, yet this central core is metabolically inert and cannot renew itself. Thus, the central lens is severely restricted in its ability to repair damage. The outermost layer of the lens is composed of a layer of epithelial cells, which are responsible for most of the metabolic activity of the lens. These cells are the source of new cells, as the old cells differentiate into fiber cells and are displaced toward the nucleus. These newest lens fibers make up the lens cortex, which surrounds the nucleus.

The loss of lens transparency is termed lens opacity, and lens opacification becomes increasingly common with advancing age. When the opacity becomes sufficiently dense or extensive or both so as to interfere with vision, the lens opacity is called a cataract. There are three main types of lens opacity or cataract, which are distinct in terms of risk factors, location in the lens, and epidemiologic pattern: nuclear, cortical, and posterior subcapsular lens opacity (West and Valmadrid 1995). The different types of opacities also can occur together in the lens, resulting in a “mixed” opacity.

The frequency of each type of lens opacity in the population increases with age and varies by racial or ethnic group. In one population-based study of 2,520 older Americans (West et al. 1998), aged 65 to 69 years, 32 percent of whites had nuclear, 15 percent had cortical, and 8 percent had posterior subcapsular cataract in at least one eye; comparable figures for African Americans were 20 percent, 42 percent, and 4 percent, respectively. At least 4 percent of the study participants in that age group had undergone cataract surgery as well.

Biologic Basis

Several hypotheses have been advanced to explain a possible association of smoking and cataract. Given the plethora of aromatic compounds and trace metals in cigarette smoke that are capable of damaging lens proteins, it is difficult to know which mechanism is likely to be the most important. Harding (1995) has postulated that cadmium, lead, thiocyanate, and aldehydes from cigarette smoke lead to lens damage. Investigators analyzing blood and lenses from cataract surgery patients have shown significant accumulations of cadmium in the blood and lenses of smokers compared with lenses of nonsmokers, with cadmium in lenses proportional to the amount smoked (Ramakrishnan et al. 1995; Cekic 1998).

Harding (1991) also has suggested that the damage to the lens may be from thiocyanate, which can cause carbamylation of crystallins (lens proteins) and enzymes. Smokers do have elevated thiocyanate levels in their blood, but levels in lenses have not been measured.

Others suggest that smoking may cause cataract through an indirect route, by lowering antioxidants (Taylor et al. 1995). However, the role of antioxidants in protecting against cataractogenesis still is controversial. Few studies have determined the level of anti-oxidants in the lens and the relationship between lens levels and blood or serum levels. One of the better studied antioxidants is vitamin C, which appears to be concentrated in the lens, and ocular levels of vitamin C are sensitive to plasma levels of this vitamin (Taylor et al. 1997). A review of research linking vitamin C and cataract found studies that reported a protective effect of vitamin C, an increased risk with serum levels of vitamin C, and no association at all; the conflicting results do not provide evidence of an association (West and Valmadrid 1995). In one study, smokers compared with nonsmokers had lower serum values of vitamin C, and in another, both smokers and nonsmokers had similar blood and lens levels of vitamin C (Kallner et al. 1981; Ramakrishnan et al. 1995). At present, the antioxidant pathway for lens damage from smoking requires more corroborative research.

Epidemiologic Evidence

The relevant articles for this section on eye diseases were identified initially through a search in PubMed from 1966 through 2000 by using the following search terms: “lens opacity,” “cataract,” “lens,” “nuclear lens opacity,” “cortical lens opacity,” “posterior subcapsular lens opacity,” “age-related macular degeneration,” “senile macular degeneration,” “age related maculopathy,” “choroidal neovascularization,” “drusen,” “geographic atrophy,” “atrophic macular degeneration,” “diabetic retinopathy,” “diabetic eye disease,” “glaucoma,” “intraocular pressure,” “Graves’ ophthalmopathy,” “thyroidopathy,” “eye pathology,” and “eye disease.” These terms were searched with the Boolean operator “and” followed by the terms “cigarette,” “smoking,” and “tobacco” in appropriate combinations. All articles were reviewed, and their bibliographies were reviewed for relevant articles not captured by the search strategy. The final selection of articles for citation in this section was made in consideration of the adequacy of the research or review and the relevance to the topic. The selection of eye diseases for review was based on the public health importance of the disease and the availability of research relevant to an association with smoking.

Several key methodologic issues should be addressed in any research on risk factors for cataract. First, there are different types of cataract, with largely unique risk factors for each type. Early research on risk factors often did not differentiate cataract type, making interpretation difficult because the mix of cataract types was unknown. For example, a surgical series of cataract patients is likely to be heavily weighted for posterior subcapsular cataract, whereas a population-based series will have few posterior subcapsular cataract cases. Surgical notes, or ophthalmologist notes, of the cataract type may lead to misclassification, as only the major cataract type usually is recorded. Ideally, studies on cataractogenesis would use one of several reliable, valid grading schemes for documentation of the presence and severity of lens opacity types.

The second methodologic issue is that each type of lens opacity has a different impact on the visual system. Research that defines cataract to include a visual acuity criterion effectively excludes asymptomatic, early lens changes or may include substantial numbers of persons with lens opacity not yet affecting acuity in the control group. Such research is less desirable from an etiologic standpoint.

Finally, issues of bias and confounding must be addressed with any research. Selection bias in clinic-based, case-control studies of cataract can be problematic, because controls sometimes have eye problems that may share risk factors in common with cataract. In population-based studies, patients with bilateral cataract surgery often are excluded from the analyses, because the type of cataract or date of surgery may be unknown. If the risk factor of interest drives progression of cataract, the exclusion of bilateral surgical cases will result in an underestimation of the risk. Potential confounders for the relationship of smoking and nuclear or posterior subcapsular cataract include age, race, gender, steroid use, and possibly alcohol use.

Ten epidemiologic studies reviewed have found an association between smoking and nuclear opacity and four found an association between smoking and posterior subcapsular opacity (Table 6.27). The studies reporting an association between nuclear cataract and smoking were carried out in diverse populations using different methodologies and different lens grading systems (Flaye et al. 1989; West et al. 1989a, 1995; Leske et al. 1991, 1998; Christen et al. 1992; Hankinson et al. 1992; Klein et al. 1993b; Cumming and Mitchell 1997; Hiller et al. 1997). The association with smoking generally was consistent (with most RRs ranging between 2 and 3); a dose-response relationship with the amount smoked was found. Four prospective cohort studies have found an association with smoking at baseline and subsequent risk of developing new nuclear opacities, surgery for nuclear opacities, or progression of existing nuclear opacities (Christen et al. 1992; West et al. 1995; Hiller et al. 1997; Leske et al. 1998).

Table 6.27. Studies on the association between smoking and cataracts.

Table 6.27

Studies on the association between smoking and cataracts.

Smoking has been less consistently associated with an increased risk of posterior subcapsular opacity. Two prospective cohort studies have found an increased risk, between 2.5- and 3-fold, associated with heavy smoking (smoking 20 or more cigarettes per day and smokers of 65 or more pack-years) (Christen et al. 1992; Hankinson et al. 1992). Two cross-sectional, population-based studies found a weaker association, and one reported an association only among men (Klein et al. 1993b; Cumming and Mitchell 1997). Two other population-based surveys did not find any association with posterior subcapsular cataract (Flaye et al. 1989; Hiller et al. 1997).

One limitation of population-based studies of risk factors for posterior subcapsular cataract is the rarity of that cataract type, making it difficult to acquire enough cases to precisely characterize risk. Another limitation is that posterior subcapsular cataract is highly visually disabling, and generally progresses quickly, so while it is overrepresented in surgical series it may be underrepresented in population-based studies because affected persons already have had cataract surgery (West et al. 1998). Thus, prospective cohort studies on posterior subcapsular cataract in populations are likely to provide more compelling data about the association.

The three studies that found no association between smoking and cataract deserve comment. The case-control study in India (Mohan et al. 1989) was hospital-based and relied on patients from one center. The possibility of selection bias, especially in terms of cases with vision loss and controls without vision loss and their COPDs, must be considered. The case-control study in Italy (Italian-American Cataract Study Group 1991) had a design similar to the study in India but used cases and controls from three clinics covering the population in Parma, Italy. This broader coverage reduced the possibility for selection bias. However, the recruitment rates of cases of posterior subcapsular cataract and nuclear cataract were lower than expected; the smoking data were not shown for this study, so an assessment of the power to detect an increased risk associated with smoking could not be done. The third study (Bochow et al. 1989), a case-control study of risk factors for posterior subcapsular cataract, did not evaluate the association of smoking with other cataract types. The controls included patients with nuclear cataract alone or with AMD, which may have increased the prevalence of smoking in the comparison group. Thus, the three studies that did not find an association between smoking and cataract have limitations that may have introduced bias toward the null.

There are no clinical trials of smoking cessation and determinations of either reduced risk of onset or progression of lens opacities. Six studies examined the risk in former smokers, and the data in general support a lower risk of progression or development of cataract after cessation. The mechanism is likely to be a reduction in the smoking-related dose of injurious agents to the lens rather than any reversal of the cataractogenic process. A cross-sectional survey looked in detail at time since smoking cessation and reported that cessation of 10 or more years reduces the risk of nuclear opacity (West et al. 1989a). In two large prospective cohort studies, former smokers at baseline had no increased risk of new nuclear opacities (Christen et al. 1992) or new cataract surgery (Hankinson et al. 1992). The 13-year follow-up study among male physicians of self-reported development of visually significant cataract found a lower risk among former smokers compared with current smokers (Christen et al. 2000). The prospective data are compatible with previous work showing that ongoing smoking drives progression. Other researchers who found similar risks for former smokers as for current smokers did not evaluate risk by years since cessation (Cumming and Mitchell 1997; Hiller et al. 1997). Studies of risk for cataract among smokers using low-yield cigarettes or low-tar products have not been reported.

Evidence Synthesis

Substantial evidence based on cross-sectional and prospective cohort studies now has accrued linking nuclear, and possibly posterior subcapsular, cataract to cigarette smoking. There is a dose-response relationship and evidence that former smokers have a lower risk of cataract and of progression of cataract compared with current smokers. On the basis of the epidemiologic studies, researchers now are investigating the mechanisms by which smoking may damage the lens, by using animal and lens cell culture models. The laboratory data are not yet sufficiently mature to inform the discussion of smoking and cataract, in part because there are few animal models of age-related cataract; most require an external insult to initiate the cataractogenic process. However, smokers are exposed to a number of agents that may cumulatively damage the lens, which lacks reparative capacity.

Conclusions

  1. The evidence is sufficient to infer a causal relationship between smoking and nuclear cataract.
  2. The evidence is suggestive but not sufficient to infer that smoking cessation reduces the risk of nuclear opacity.

Implications

There is moderate evidence to suggest that smoking also may be associated with an increased risk of posterior subcapsular opacities as well, but more research is needed before a causal association can be inferred for this cataract type. The difficulty the lens has in repairing damage suggests that opacification at the time of smoking cessation is likely to be irreversible. Studies of cataract in clinical trials of smoking cessation would provide more definitive evidence for any protective effect, although feasibility would be constrained by the need for large populations.

Age-Related Macular Degeneration

AMD is the leading cause of blindness in whites aged 65 years and older in the United States (Sommer et al. 1991; Muñoz et al. 2000). There currently is no well accepted treatment to prevent or halt the progression of atrophic AMD, the most common form of AMD. Treatment to halt vision loss from the less common, severe form of AMD, exudative (neovascular) AMD, often is short lived, as neovascularization (new blood vessel formation) often recurs. A recent large-scale clinical trial has provided evidence that antioxidant supplements plus zinc may delay the progression of some signs of AMD (Age-Related Eye Disease Study Research Group 2001). Otherwise, no preventive therapy for AMD is available, so considerable attention has focused on identifying risk factors for this disease.

The macula is a component of the retina at the center of the optical axis; it contains the fovea, a highly specialized area of the retina responsible for high-resolution vision. The retina consists of neural tissues, including the photoreceptors that convert energy from visible light into electrical signals sent on to the brain for processing. The photoreceptors—rods and cones— have high metabolic requirements and replace their outer segments daily. The metabolic functions of the retina are supported by the retinal pigment epithelium, which phagocytizes an estimated 2,000 outer segment membranes daily. This high rate of activity is made possible by the exchange of nutrients (and removal of waste) through the retinal blood supply, the choriocapillaris. There is a blood retinal barrier to this exchange, which is formed by both the retinal pigment epithelium and its anchor, Bruch’s membrane (lamina basalis choroideae). Thus, the complex of the retinal pigment epithelium, Bruch’s membrane, and the choriocapillaris serve as the nutritional source for the sensory retina. Changes in each of the tissues in this complex have been hypothesized to result in AMD. However, the pathogenesis of AMD, indeed the differentiation of changes in early AMD from those of normal aging, is uncertain (Sarks and Sarks 1994).

AMD is an umbrella designation for a variety of degenerative changes in the macula. The degeneration is characterized in its early stages by pigmentary disturbances and atrophic changes. The late stages of AMD are characterized by widespread atrophy of the retinal pigment epithelium, loss of photoreceptors (atrophic AMD), and, less commonly, exudative AMD. With exudative AMD, new, unstable blood vessels develop in the choroid and grow under or through the retinal pigment epithelium via breaks in Bruch’s membrane. Leakage from these neovascular membranes may lead to detachment of the retinal pigment epithelium, hemorrhage, and formation of a disciform scar. The late stages are associated with vision loss, classically loss of central vision, the part of vision responsible for activities such as reading and close work.

Morphologic changes associated with AMD include basal laminar deposits at the level of the retinal pigment epithelium, thickening of Bruch’s membrane, and drusen. Drusen are deposits of extracellular material thought to be accumulations or “garbage bags” of waste products from the retinal pigment epithelium. At least two types of drusen are recognized clinically on the basis of their appearance: small, hard drusen, which are a common feature of aging; and larger, soft drusen, which also are common with aging but are a likely risk factor for developing severe AMD. The presence of drusen in the fundus, thought to be the hallmark of early AMD, is being challenged as a marker by observations that drusen can appear and disappear over time (Bressler et al. 1995; Klein et al. 1997), that most people with large, soft drusen do not develop advanced AMD (Klein et al. 1997), and that epidemiologic patterns associated with advanced AMD are different from those for drusen-defined early AMD. This debate has relevance in evaluating the evidence for an association of smoking and early versus advanced AMD.

Biologic Basis

Of the postulated mechanisms underlying the retinal changes in AMD, three have bearing on the hypothesis that smoking is associated with AMD. The first can be characterized as oxidative stress leading to changes in the ability of the retinal pigment epithelium to phagocytize cellular products, which in turn leads to accumulations of debris that interfere with the nutrient exchange between the retinal pigment epithelium and the choriocapillaris. Oxidative stress can result from free-radical damage to proteins, lipids, and possibly, mitochondrial DNA. The stress is considered to contribute to malfunctions of the retinal pigment epithelium. The macula is a particularly likely target for oxidative stress because of the macula’s high exposure to light, high metabolic rate, and high concentrations of fatty acids. But the macula also is very rich in antioxidative, protective mechanisms, including an array of antioxidant nutrients and enzymes, as well as melanin. Smoking, through its actions on reducing plasma levels of antioxidants in addition to reducing macular pigment, is hypothesized to increase the oxidative stress on the macula by robbing it of its defenses (Hammond et al. 1996).

The second hypothesis for the pathogenesis of AMD proposes that the degradation of Bruch’s membrane, as manifested by thickening and changes in the composition, leads to interference with nutrient exchange between the retinal pigment epithelium and its blood supply. Vascular endothelial growth factor (VEGF) has been reported in the retinal pigment epithelium cells; these cells may liberate VEGF in response to the interference in nutrient exchange. Investigators are working on the role of VEGF, released in connection with hypoxia, in the pathogenesis of AMD, particularly for the neovascular type (Mousa et al. 1999). Smoking has been associated with an increase in plasma immunoreactive VEGF, at least acutely, operating likely through its ability to cause tissue hypoxia (Wasada et al. 1998).

The third hypothesis for the pathogenesis, or at least a possible contributing cause, of AMD is vascular insufficiency. Changes in the choroidal circulation may impair the ability of the retinal pigment epithelium to dispose of waste substances, leading to the accumulation of waste material. The rate and volume of blood flow through the choriocapillaris are high in response to the demands of the pigmented epithelium and the photoreceptors. Smoking has been shown to alter choroidal blood flow (Bettman et al. 1958). Smoking also affects the vasculature through platelet adhesions and hypoxia from elevated levels of carboxy-hemoglobin, which might add to the stimulation of new vessel growth.

It is likely that multiple pathways are responsible for the degenerative changes in the macula with age, and a reasonable basis exists for presuming that smoking may operate through one or more of these pathways.

Epidemiologic Evidence

Two methodologic issues add to the complexity of assessing the relationship between AMD and smoking. The first issue is that advanced, or severe, AMD mostly occurs in the very old. About 7 percent of the white population aged 75 years and older will have advanced AMD (Klein et al. 1992). The second issue is that life expectancy of smokers is less than that of non-smokers, so selective survival of smokers to even develop AMD is an issue. Together, the relatively low incidence of AMD and the low prevalence of smoking in very elderly populations diminish the power to detect associations in all but the largest studies, which is evident in the population-based studies of AMD that have low numbers of cases of severe AMD.

One way to circumvent the problem is to study the association of smoking in precursor lesions or early AMD; however, there is no uniform agreement on the clinical signs of early AMD. Many of the signs currently in use are common in the population and can be so unstable as to be almost uninformative about who will develop advanced AMD. Data are accumulating on predictors of advanced AMD, the presence of very large drusen, and the retinal area covered by drusen. In part, the difficulty of determining the relevant early signs may be due to the limitations of photographic systems to detect such changes in, for example, Bruch’s membrane; for research purposes, however, no alternative detection systems are available for accurately detecting early changes.

With these caveats in mind, the research findings to date suggest a strong likelihood that smoking is related to advanced or severe AMD, particularly exudative AMD, but there is scant evidence that smoking is related to the apparent early signs of AMD (Table 6.28). One cross-sectional, population-based study (Smith et al. 1996) found increased odds of early AMD among smokers compared with nonsmokers (OR = 1.89 [95 percent CI, 1.25–2.84]). However, two others, using identical grading methods, found no increased odds (Klein et al. 1993c; Delcourt et al. 1998). In another cross-sectional survey of fishermen who were heavy smokers, a paradoxical protective effect was seen for smoking and the odds of early AMD, primarily cases of moderate drusen (West et al. 1989b). A prospective cohort study of the risk of developing early signs of AMD found an increased risk of developing large (>250 μm) drusen among smokers compared with lifetime nonsmokers; the RR was 3.21 (95 percent CI, 1.09–9.45) among men and 2.20 (95 percent CI, 1.04– 4.66) among women. No other early sign was associated with smoking (Klein et al. 1998). The lack of association with presumed early AMD may be due to the imprecision of the signs chosen to represent early AMD, thus biasing the results toward the null. Further work on improving this classification is warranted. It is also possible that smoking is related to progression of AMD to the exudative form but not to the onset of early lesions.

Table 6.28. Studies on the association between smoking and age-related macular degeneration (AMD).

Table 6.28

Studies on the association between smoking and age-related macular degeneration (AMD).

Gender differences appear in the findings as well. In one case-control study of severe AMD, the relationship with smoking was observed in men only (Hyman et al. 1983). In one prospective cohort study in a population having primarily early AMD, progression of AMD among smokers was observed with a dose-response pattern only among men (Klein et al. 1998). A prospective cohort study of exudative AMD among men found a benefit of quitting smoking after 20 years of cessation (Christen et al. 1996), but a similar study among women found no benefit after 15 or more years of cessation (Seddon et al. 1996). There are not evident explanations for these differences, except that the significantly lower prevalences of smoking among women may reduce the power to detect associations with AMD, especially if heavy smoking is the risk-determining factor.

The strongest and most consistent association seen in the literature is the association of current smoking and risk of severe AMD, especially exudative AMD. Because several studies tended to combine atrophic and exudative AMD into “late” or “severe” AMD, it is difficult to know whether to attribute the association to either one or both, unless specified. Four case-control studies have been reported to date. A large case-control study of exudative disease (Eye Disease Case-Control Study Group 1992) found an increased OR with current and past smoking of 2.2 (95 percent CI, 1.4–3.5) and 1.5 (95 percent CI, 1.2–2.1), respectively. Three other case-control studies also found an increased risk for severe AMD in smokers, with estimated ORs between 2 and 3 (Hyman et al. 1983; Macular Photocoagulation Study Group 1986; Tamakoshi et al. 1997). Four cross-sectional, population studies found increased odds of exudative AMD among current smokers, with ORs between 1.5 and 3.6; two of the four studies found a dose-response relationship. Two of the four cross-sectional studies found increased odds of atrophic AMD with current smoking (Vinding et al. 1992; Smith et al. 1996), but the other two did not (Klein et al. 1993c; Vingerling et al. 1996). Two prospective studies found a significant association with either exudative disease or severe AMD in current heavy smokers (20 or more cigarettes per day) (Christen et al. 1996; Seddon et al. 1996). Former smokers also had an increased risk of AMD, although lower than that for current heavy smokers. Quitting more than 20 years previously appeared to decrease the risk in two cross-sectional studies (Vingerling et al. 1996; Delcourt et al. 1998), as well as in a prospective cohort study in men (Christen et al. 1996). In the prospective study in women (Seddon et al. 1996), however, quitting 15 or more years prior did not decrease the risk of severe AMD.

The data from cross-sectional studies suggest that passive smoking is not related to early or late AMD (Klein et al. 1993c; Smith et al. 1996). There are no corroborating data from animal models. Although animal models of induced retinal damage exist, no good animal models present the spectrum of features of AMD.

Evidence Synthesis

These data provide evidence that current smoking is associated with exudative AMD and possibly atrophic AMD. Dose-response relationships with the amount of smoking have been described. Maintaining smoking cessation at least 20 years decreased the risk of severe AMD and exudative AMD. The possibility that smoking is associated with the neovascular form of AMD is further bolstered by the findings from a study of ocular histoplasmosis (Ganley 1973), where neovascularization can result from the infection. In that study, smokers were twice as likely as nonsmokers to develop disciform scars. Moreover, in a clinical trial of photocoagulation to halt progression of neovascularization, smokers were more likely than nonsmokers to have recurrent neovascularization over time (Macular Photocoagulation Study Group 1986). However, smoking did not predict development of neovascularization in the previously unaffected companion eyes of the eyes with neovascularization (Macular Photocoagulation Study Group 1997).

Conclusions

  1. The evidence is suggestive but not sufficient to infer a causal relationship between current and past smoking, especially heavy smoking, with risk of exudative (neovascular) age-related macular degeneration.
  2. The evidence is suggestive but not sufficient to infer a causal relationship between smoking and atrophic age-related macular degeneration.

Implications

There is a need for more research into gender differences, dose-response relationships, and a possible threshold effect. Further research is also needed to determine the effect of smoking cessation on the risk of neovascular AMD.

Diabetic Retinopathy

Diabetic retinopathy is a serious ocular complication of diabetes associated primarily with long-term duration of diabetes and poor control in both type 1 and type 2 diseases. The retinopathy is likely the result of vascular changes occurring in the retinal circulation that feeds the inner layers of the retina. Diabetic retinopathy in the early stages (mild, non-proliferative retinopathy) is characterized by excessive permeability of the vasculature, with ballooning of the retinal capillaries to form microaneurysms, dot hemorrhages, and hard and soft exudates. Preproliferative retinopathy includes, in addition to the aforementioned features, vascular occlusion and dilation and/or venous beading. Proliferative diabetic retinopathy is characterized by new vessel growth or fibrous proliferation or both. Vitreous hemorrhage secondary to the neovascularization also may be seen. Clinically significant macular edema, the result of extensive vessel leakage, can be a feature of chronic diabetic eye disease that may occur at any stage of the process. The prevalence of diabetic retinopathy increases with duration of diabetes, and most persons with diabetes have signs after 10 years’ duration. Moreover, diabetic retinopathy is an important cause of vision loss. Although photocoagulation is an effective means of treating proliferative diabetic retinopathy, too often the retinopathy is not diagnosed at an early stage when treatment can be maximally effective.

Biologic Basis

Several investigators have postulated that smoking may contribute to the onset of diabetic retinopathy and/or drive progression of existing retinopathy through its effect on the retinal circulation (Morgado et al. 1994). If such relationships exist, one mechanism of action is likely to be hypoxia from chronic exposure to carbon monoxide, which may be toxic to retinal vasculature. Carbon monoxide also is associated with separation of arterial endothelial cells, causing edema, which also is a feature of diabetic retinopathy. Nicotine exposure increases levels of plasma vasoconstrictors, such as angiotensin and vasopressin, which have binding sites on retinal blood vessels. In addition, nicotine exposure increases platelet adhesiveness, and persons with diabetic retinopathy are more likely to have increased platelet aggregation compared with persons with diabetes but without retinopathy. Although there is a reasonable biologic basis to the hypothesis that smoking is related to diabetic retinopathy, the data suggest otherwise.

Epidemiologic Evidence

Many studies have examined the association between smoking and diabetic retinopathy (Table 6.29), and the data from several studies do not support the proposed association. The well-controlled studies, including prospective cohort studies in large populations of persons with diabetes, found no association between smoking and the amount smoked and the prevalence, incidence, or progression of diabetic retinopathy (Klein et al. 1983; Moss et al. 1991, 1996). Studies that found an association in general did not adjust for level of control of diabetes, a major risk factor for diabetic retinopathy. One study did adjust for level of control and other risk factors and found an association between smoking and a six-year progression of diabetic retinopathy (Mühlhauser et al. 1996). However, progression was defined as any progression, from onset of diabetic retinopathy to becoming blind, if proliferative diabetic retinopathy was present at baseline. There were no data shown on whether smokers tended to have worse retinopathy at baseline, but the analyses should have adjusted for baseline status of diabetic retinopathy as a risk factor for progression. When the progression was confined to the subgroup with no retinopathy at baseline, smoking was not significantly associated with either the incidence or progression of diabetic retinopathy.

Table 6.29. Studies on the association between smoking and diabetic retinopathy (DR).

Table 6.29

Studies on the association between smoking and diabetic retinopathy (DR).

Evidence Synthesis

Although smoking might plausibly worsen diabetic retinopathy, the evidence is inconsistent. The strongest studies, the prospective cohort studies, do not show an association. The level of diabetes control is a potential major confounder that has not been considered in a number of the studies.

Conclusion

  1. The evidence is suggestive of no causal relationship between smoking and the onset or progression of retinopathy in persons with diabetes.

Implication

As research on diabetes continues, possible effects of smoking should be reassessed.

Glaucoma

Glaucoma is the third leading cause of blindness worldwide (Thylefors et al. 1995). In the United States, African Americans and Hispanics are more affected than other groups. Glaucoma is a disease characterized by loss of retinal ganglion cells, probably through a variety of mechanisms. The two main types of primary glaucoma are primary open-angle glaucoma and angle closure glaucoma. The angle refers to the angle between the iris and trabecular meshwork in the anterior chamber, which if shallow or closed impedes outflow of aqueous fluid and causes a rise in pressure. There are distinct differences between the two types of glaucoma, and their distribution differs in populations. In the United States, primary open-angle glaucoma is the more common type.

Biologic Basis

There is no evident basis for proposing that smoking might predispose a person to either developing glaucoma or having more severe glaucoma. Investigators have proposed that factors that diminish perfusion of the optic nerve head with blood may be associated with glaucoma. Because smoking affects the retinal circulation (although any direct effect of smoking on the optic nerve head is unknown), several investigators have examined the association of glaucoma with smoking. However, the effects of smoking on blood flow in ocular circulation are difficult to measure, in part because studies often do not consider separating acute effects in smokers and nonsmokers from the chronic effects that result from repeated exposures. The role of smoking in altering intraocular pressure also is variable. In one study (Shephard et al. 1978), smoking (including cumulative consumption) was not associated with intraocular pressure differences.

Evidence Synthesis

The few epidemiologic studies conducted (Table 6.30) do not indicate any relationship between smoking and glaucoma. Three cross-sectional studies found no association between smoking and glaucoma (Klein et al. 1993a; Ponte et al. 1994; Leske et al. 1995), and one prospective cohort study found no increased risk of glaucomatous field loss among persons with ocular hypertension who smoked compared with those who did not smoke (Quigley et al. 1994). The association has not been evaluated in angle closure glaucoma, but there is little biologic basis for proposing such a relationship.

Table 6.30. Studies on the association between smoking and glaucoma.

Table 6.30

Studies on the association between smoking and glaucoma.

Conclusion

  1. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and glaucoma.

Implication

As further studies of glaucoma are undertaken, the role of smoking should remain under investigation.

Other Eye Diseases: Graves’ Ophthalmopathy

Several other eye diseases have been investigated for an association with smoking. Most were not reviewed for this report, however, because the data are insufficient to reach any conclusions. The one exception is an uncommon condition—Graves’ ophthalmopathy, an ocular complication of Graves’ disease.

Graves’ disease is thought to be an autoimmune disease of the thyroid. It is likely that both genetic and environmental factors are related to the risk of the disease. Among its clinical manifestations, the ophthalmologic complications appear to be related to smoking. Graves’ ophthalmopathy is characterized by proptosis (protrusion of the eyeball), diplopia (double vision), optic neuropathy, and conjunctival and peri-orbital inflammation. The pathogenesis of Graves’ ophthalmopathy is not completely understood, but it appears to involve the orbital fibroblasts that are stimulated to release glycosaminoglycans, which in turn are related to the orbital edema seen with the ocular complications. Recent data suggest an autoimmune basis for Graves’ ophthalmopathy as well (Bahn 2000).

Biologic Basis

The mechanism by which smoking may cause or aggravate Graves’ ophthalmopathy is unknown. Orbital hypoxia and effects of thiocyanate have been postulated, and other research has investigated the effect of smoke constituents on orbital fibroblast activity. Researchers investigating the role of hypoxia in muscular inflammation have found stimulation of protein synthesis and proliferation of extra-ocular, muscle-derived fibroblasts under hypoxic conditions (Metcalfe and Weetman 1994). Smoking does not appear to affect serum concentrations of proinflammatory cytokines in Graves’ disease, even among persons with ocular complications (Salvi et al. 2000).

Epidemiologic Evidence

Seven studies (Table 6.31) found an increased risk associated with smoking of developing the ophthalmologic complications of Graves’ disease (Hägg and Asplund 1987; Shine et al. 1990; Tellez et al. 1992; Prummel and Wiersinga 1993; Winsa et al. 1993; Pfeilschifter and Ziegler 1996; Bartalena et al. 1998); three found a dose-response relationship with the number of cigarettes smoked (Shine et al. 1990; Tellez et al. 1992; Pfeilschifter and Ziegler 1996). The studies, while consistent, are limited in number and the sample sizes of some are small. The severity of the ophthalmopathy was associated with smoking in two studies (Prummel and Wiersinga 1993; Winsa et al. 1993). Estimates of the OR varied between 2 and 10, depending on the control population selected. The effect of quitting smoking on Graves’ ophthalmopa-thy has not been well studied and would provide convincing evidence of a causal relationship. On the basis of the findings of the epidemiologic studies, several investigators are studying the effect of smoking on the thyroid gland and the extra-ocular, muscle-derived fibroblasts.

Table 6.31. Studies on the association between smoking and Graves’ ophthalmopathy.

Table 6.31

Studies on the association between smoking and Graves’ ophthalmopathy.

Evidence Synthesis

Although there are suggestive epidemiologic findings, the biologic basis for a role of smoking in Graves’ ophthalmopathy is unclear. The epidemiologic data are still limited, although consistent in indicating an increased risk in smokers. Dose-response is not well documented.

Conclusion

  1. The evidence is suggestive but not sufficient to infer a causal relationship between ophthalmopa-thy associated with Graves’ disease and smoking.

Implication

Data on the role of smoking cessation in preventing or lessening the severity of the ophthalmopathy would be important to understanding the relationship between Graves’ disease and smoking.

Peptic Ulcer Disease

In the early 1990s, the central role played by the bacterium Helicobacter pylori (H. pylori) in both the incidence and recurrence of peptic ulcer disease was recognized (Kuipers et al. 1995). This section reviews the evidence of an association between smoking and peptic ulcer disease in light of this new understanding of the pathogenesis of ulcer disease. Relevant articles were identified through a MEDLINE search from 1985 through June 2000 using the following terms: “ulcer and smoking and pylori” and “smoking and pylori and eradication.” A further search was performed for the years 1998 through June 2000, using the terms “ulcer and smoking” to identify any major studies that were not included in the previous Surgeon General’s report (USDHHS 2001), even though the studies had not evaluated H. pylori.

Conclusions of Previous Surgeon General’s Reports

Numerous studies have demonstrated an association between smoking and the occurrence of peptic ulcer disease. This evidence was reviewed in the 1964, 1971, and 1972 Surgeon General’s reports on smoking and health (USDHEW 1964, 1971, 1972). The 1979 report concluded that cigarette smoking was significantly associated with both the incidence and an increased risk of dying from peptic ulcer disease: “the association between smoking and peptic ulcer disease is significant enough to suggest a causal relationship” (USDHEW 1979, p. 1–23). In addition, that report concluded that there was highly suggestive evidence that smoking also retards ulcer healing. The 1990 report concluded that smokers had an increased risk of developing both duodenal and gastric ulcers, and smoking cessation reduced that risk (USDHHS 1990). That report also found that among smokers ulcer disease was more severe, duodenal ulcers were less likely to heal, and both duodenal and gastric ulcers were more likely to recur. Ulcer patients who stopped smoking, however, were found to have an improved clinical course compared with continuing smokers. Although much of this previous evidence was based largely on studies of men, the more recent Surgeon General’s report on women and smoking (USDHHS 2001) concluded that women who smoked also had an increased risk of peptic ulcer disease.

Biologic Basis

In the decades since the 1964 Surgeon General’s report, explanations of the pathogenesis of peptic ulcer disease have changed dramatically with the identification of the gastric bacterium H. pylori in a high proportion of patients with peptic ulcers (Marshall and Warren 1984). Up to 100 percent of duodenal ulcers and 70 to 90 percent of gastric ulcers are now associated with H. pylori infection (Kuipers et al. 1995). Most ulcers in persons without H. pylori infection were linked to the use of nonsteroidal anti-inflammatory drugs (NSAIDs) (Borody et al. 1991, 1992a). Other causes of peptic ulcers, although rarer, include Crohn’s disease and Zollinger-Ellison syndrome.

Normally, the gastrointestinal mucosa is protected from injury by, among other factors, a layer of mucus and the secretion of bicarbonate by gastric and duodenal epithelial cells to neutralize gastric acid. If these protective mechanisms are impaired, or if there is an increase in levels of damaging factors, then ulceration may occur.

Effects of Smoking on Gastrointestinal Physiology

The 1990 Surgeon General’s report (USDHHS 1990) reviewed the effects of cigarette smoking on aspects of human gastrointestinal physiology relevant to peptic ulcer disease. Likely mechanisms whereby smoking could promote the development of peptic ulcer disease included the potential for tobacco smoke and/or nicotine to increase maximal gastric acid output and duodenogastric reflux and to decrease alkaline pancreatic secretion and prostaglandin synthesis.

Two subsequent reviews (Endoh and Leung 1994; Eastwood 1997) evaluating the potential effects of cigarette smoke and nicotine as injurious and protective factors that could play a role in peptic ulcer formation came to similar conclusions. Data on the effects of smoking on gastric acid secretion in humans have been highly inconsistent; multiple reports found that smoking and/or nicotine variously stimulated, inhibited, or had no effect on gastric acid secretion. However, there was more consistent evidence that smoking promotes reflux of duodenal contents into the stomach, and increases production of free radicals and the release of vasopressin, a potent vasoconstrictor. Protective mechanisms consistently affected by smoking were the chronic inhibition of gastric mucus secretion, cytoprotective prostaglandin production, pancreatic and duodenal mucosal bicarbonate secretion, and a decrease in mucosal blood flow.

The mucosal protection mechanism most clearly affected by smoking is the pancreatic secretion of bicarbonate. A transient reduction in secretion is seen immediately after smoking, leading to a drop in pH in the duodenal bulb (Eastwood 1997). Acidity in the duodenal bulb appears to be the most important determinant for the development of gastric metaplasia in the duodenum, thus paving the way for duodenal colonization by H. pylori (Tytgat et al. 1993).

Results from studies evaluating mucosal blood flow among smokers and nonsmokers have been more varied, possibly because of a variation in the measurement methods. Taha and colleagues (1993) demonstrated that both gastric and duodenal mucosal blood flow were reduced in chronic NSAID users. However, after allowing for NSAID use, significantly reduced duodenal blood flow was seen only in H. pylori-positive smokers. There was no additional effect of either H. pylori infection or smoking on gastric mucosal blood flow.

Finally, some strains of H. pylori produce a vacuolating toxin that may be important in determining the virulence of the organism. This toxin induces vacuolation of HeLa cells in vitro, as does nicotine alone, but the addition of nicotine to H. pylori potentiates the vacuolating effect of the toxin (Cover et al. 1992).

In summary, studies document that smoking appears to have a multitude of effects on gastroduodenal physiology, and through a number of mechanisms it could promote peptic ulceration. These effects are, however, largely transient, and the affected physiologic measures return to normal within minutes or hours after smoking cessation (Eastwood 1997). These same studies also indicate that smoking could particularly increase the likelihood of ulceration in H. pylori-positive persons.

Smoking and Helicobacter pylori Infection

Both H. pylori infection (Malaty et al. 1992; EUROGAST Study Group 1993) and smoking (Bergen and Caporaso 1999) are more common among groups of lower SES. Cross-sectional studies that have evaluated the association between H. pylori infection and smoking in healthy volunteers consistently have reported higher infection rates in smokers (current or former) than in nonsmokers. In a study of 485 volunteers in the United States, current and former smokers were more likely to be seropositive for H. pylori than nonsmokers (among blacks, rates were 73 percent among current smokers, 85 percent among former smokers, and 61 percent among nonsmokers; and among whites, rates were 40 percent, 48 percent, and 25 percent, respectively) (Graham et al. 1991). Infection also was slightly more common among 3,496 adult smokers in Northern Ireland (65 percent among former smokers, 57 percent among smokers of fewer than 20 cigarettes, and 64 percent among smokers of 20 or more cigarettes per day compared with 53 percent among people who had never smoked) (Murray et al. 1997). Similar findings were seen in a group of 273 adults from Melbourne, Australia, among current and former smokers (45 percent and 44 percent, respectively, compared with 31 percent in people who had never smoked) (Lin et al. 1998) and among 1,064 adult heavy smokers in New Zealand (38 percent in smokers of more than 20 cigarettes per day compared with 23 percent in smokers of less than 20 cigarettes per day and nonsmokers) (Collett et al. 1999). Similar patterns have been reported in adults visiting general practitioners in Germany (Brenner et al. 1997) and in patients receiving an endoscopic examination in the United Kingdom (Bateson 1993) and Malaysia (Goh 1997).

In some of these studies, the association between H. pylori and smoking was attenuated after adjusting for other factors, including age and SES. In both developed and developing countries, H. pylori infection is believed to occur during childhood (Xia and Talley 1997), and thus it is unlikely that smoking influences the risk of initial H. pylori infection to any great extent. It is unclear whether smoking could be a risk factor for the acquisition or persistence of H. pylori infection in adulthood or if low SES is a common, more distal risk factor for both H. pylori and smoking. These variables do not, however, alter the fact that smokers are more likely than nonsmokers to be infected with H. pylori. The link between H. pylori and peptic ulcer disease is well established; thus, it is important to consider whether smoking also is a risk factor or if some or all of the observed associations between smoking and peptic ulcer disease could be due to confounding by H. pylori infection status.

Trends in Peptic Ulcer Disease

During the past several decades, rates of hospitalization for and mortality from peptic ulcer disease in the United States have declined dramatically. Using hospitalization rates from the computerized database of the U.S. Department of Veterans Affairs, El-Serag and Sonnenberg (1998) showed that although gastric ulcers accounted for 67.6 and duodenal ulcers for 168.8 out of every 10,000 hospitalizations of veterans from 1970–1974, comparable figures for 1990–1995 were 49.6 per 10,000 and 52.5 per 10,000, respectively. Similarly, using vital statistics data from CDC’s National Center for Health Statistics, these two authors showed that mortality from gastric ulcer disease had fallen from 17.4 per million per year in 1968–1972 to 7.7 per million per year in 1988–1992, with a comparable drop in mortality for duodenal ulcer disease from 19.6 to 8.4 per million per year (El-Serag and Sonnenberg 1998). However, peptic ulcer disease still is a leading cause of morbidity. In 1989, the National Health Interview Survey included a special questionnaire on digestive diseases. Among approximately 42,000 adult respondents, 10 percent reported that they had ever had a physician-diagnosed peptic ulcer, one-third of whom also reported having a new or recurring ulcer in the past 12 months (Sonnenberg and Everhart 1996). Among the 50 percent who reported the site of their ulcer, gastric and duodenal ulcers were equally common overall, although nonwhites reported gastric ulcers more frequently and duodenal ulcers less frequently than whites. When recurrent ulcers (defined as a relapse in the past 12 months of a previously diagnosed ulcer) were excluded, the incidence of new peptic ulcers in 1989 was an estimated 52.7 per 10,000 (Everhart et al. 1998). Among those respondents who specified the site of the ulcer, the incidence of gastric ulcers (17.0 per 10,000) was about three times that of duodenal ulcers (6.1 per 10,000). This finding suggests that the incidence of new duodenal ulcers may have fallen more rapidly over time than that of gastric ulcers.

A large part of the decrease in peptic ulcer rates over the last few decades in the United States has been attributed to lower smoking rates (Kurata et al. 1986), although the same pattern was not seen in the United Kingdom (Sonnenberg 1986). However, the prevalence of H. pylori infection in developed countries also is believed to have declined over a similar time period (Banatvala et al. 1993; Kosunen et al. 1997), and it is this decline, rather than falling smoking rates, that may explain some or all of the reductions in ulcer rates.

Epidemiologic Evidence

Smoking and Development of Peptic Ulcer

Studies that evaluated the relationship between tobacco smoking and the development of peptic ulcer disease repeatedly have shown an increased risk of both duodenal and gastric ulcers among smokers (USDHEW 1979; USDHHS 1990). In some studies, this risk also has been observed to increase with increasing levels of smoking. During a 149,291 person-years follow-up of a cohort of 7,624 Japanese men in Hawaii, the age-adjusted incidence of gastric and duodenal ulcers increased with increasing levels of smoking at baseline (RR among nonsmokers and smokers of less than 24, 24 through 40, and greater than 40 pack-years: 1.0, 1.5, 3.1, and 3.8 [Ptrend <0.01], respectively, for gastric ulcers and 1.0, 1.8, 2.4, and 3.3 [Ptrend <0.01], respectively, for duodenal ulcers [Kato et al. 1992]). In contrast, an analysis of self-reported ulcer history, using data from the 1989 National Health Interview Survey in the United States, suggested that smoking may be a stronger risk factor for chronic ulceration than for the development of new ulcers (Everhart et al. 1998). Although these data show a strong relation between smoking and age-standardized prevalence of chronic active ulcers (1.8 percent, 3.0 percent, 3.9 percent, and 5.3 percent among nonsmokers and smokers of <20, 20, and >20 cigarettes per day, respectively), there was no association between smoking and the incidence of new ulcers.

Helicobacter pylori, Smoking, and Peptic Ulcer

Only a few studies have considered both smoking and H. pylori infection in relation to the incidence of peptic ulcer disease (Table 6.32). These studies largely have been cross-sectional surveys of patients referred for upper gastrointestinal endoscopy using variable definitions of smoking, and rarely presenting results that distinguished between smokers with and without H. pylori infection. No studies have separately evaluated the risk of peptic ulcers in former smokers after allowing for H. pylori infection.

Table 6.32. Studies on the association between smoking and peptic ulcer disease, allowing for Helicobacter pylori (H. pylori) infection.

Table 6.32

Studies on the association between smoking and peptic ulcer disease, allowing for Helicobacter pylori (H. pylori) infection.

Four of these studies were conducted with groups receiving endoscopic examinations. Martin and colleagues (1989) found no duodenal ulcers in 47 H. pylori-negative persons although 4 of them, all of whom were taking NSAIDs, had a gastric ulcer. Among the 60 H. pylori-positive persons, peptic ulcers were significantly more common in smokers than in non-smokers. Similarly, Talamini and colleagues (1997) reported a significant association between duodenal ulcers and smoking after adjusting for H. pylori infection. In a Swiss study, smoking also appeared to be associated with an increased risk of duodenal ulcers, particularly among H. pylori-positive persons (Halter and Brignoli 1998). The lack of a single reference group in this study, however, makes comparisons with other studies difficult. In contrast, Schubert and colleagues (1993) reported no significant differences between the proportion of smokers in patients with and without ulcers and, as a consequence, did not include smoking status in their multivariable models adjusting for H. pylori. It is possible, however, that the very broad definition of smoking used in this last study may have led to very light or occasional smokers being inappropriately classified as smokers, thus masking differences between patients with and without ulcers.

Two other studies used groups of company employees. Wang and colleagues (1996) conducted a case-control study in a factory in Shanghai, China. To prevent confounding by SES and gender, data were analyzed separately for men and women, drivers and workers (lower SES), and staff (higher SES). Among male workers and drivers (304 cases and 263 controls), current smoking was associated with a significantly elevated risk of peptic ulcer disease that increased with the amount of cigarettes smoked. A similar pattern was seen for duodenal ulcer disease alone. There was only one female employee smoker, and too few former smokers to evaluate risks in those groups. Although smoking status was assessed after the development of ulcers, smoking rates were high and few workers reported having stopped smoking. It is therefore unlikely that many employees changed their smoking behavior following ulcer diagnosis.

Schlemper and colleagues (1996) conducted parallel studies in companies in Japan and the Netherlands. Men and women with verifiable ulcer disease who had not been treated with H. pylori eradication therapy were compared with those without ulcers or prior gastric surgery. After adjusting for potential confounders, researchers found that daily smoking was associated with a nonsignificant increased risk of peptic ulcer disease only in the Dutch population. In this study, the majority of ulcers had been diagnosed a median of six years before smoking data were collected, and it is possible that employees with peptic ulcer disease may have changed their smoking behaviors over time.

There is a potential for bias in any of these studies if participants altered their smoking behaviors because of ulcer symptoms or if they misreported their smoking patterns. If ulcer patients tend to stop or reduce their smoking because of symptoms, or if they systematically underreport the amount they smoke, then the true associations between smoking and ulcers could be greater than those reported. Conversely, if ulcer patients actually increase their smoking in response to ulcer symptoms or if they systematically overreport the amount they smoke, then the observed associations could exaggerate the true effect. This latter situation would seem less likely than the former.

Nonsteroidal Anti-Inflammatory Drugs, Smoking, and Peptic Ulcer

The main cause of ulcers in persons negative for H. pylori infection, at least in developed countries, is the use of NSAIDs (Borody et al. 1991, 1992a). In the 1990 Surgeon General’s report (USDHHS 1990), smoking was associated with peptic ulcer disease and acute gastric erosions in three studies of NSAID users. Since then, three more studies have evaluated the relationship between smoking and peptic ulcers in NSAID users, with conflicting results.

Hansen and colleagues (1996) compared 94 NSAID users admitted to a hospital with complications of peptic ulcers (predominantly bleeding or perforated ulcers) with 324 controls selected at random from all assumed NSAID users. Overall, cases were no more likely than controls to be smokers (44 percent and 41 percent, respectively), but after adjusting for age, gender, ulcer history, and duration of NSAID use, current smoking was associated with an almost twofold increased risk of ulcer complications (OR = 1.9 [95 percent CI, 1.0–3.6]).

In contrast, Aalykke and colleagues (1999) compared 132 current NSAID users diagnosed with bleeding peptic ulcers with 136 ulcer-free NSAID users selected from a rheumatology clinic and geriatrics department. Smokers were not at an increased risk of developing bleeding ulcers compared with controls (OR, adjusted for age, gender, ulcer history, H. pylori infection status, and NSAID dose = 0.91 [95 percent CI, 0.48–1.71]). Similarly, in a large case-control study in the United Kingdom, Weil and colleagues (2000) compared 1,121 patients diagnosed with bleeding peptic ulcers with 989 community controls. Information on H. pylori infection status was not available, but among NSAID users the risk for bleeding peptic ulcers (compared with nonsmokers who did not use NSAIDs) did not differ appreciably between current smokers (OR = 4.0 [95 percent CI, 2.9–5.5]) and non-smokers (OR = 3.6 [95 percent CI, 2.9–4.5]).

Mortality from Peptic Ulcer

Large-scale cohort studies consistently have shown that smokers are at a greater risk of dying from peptic ulcer disease than nonsmokers (USDHHS 1990). Follow-up of the U.S. Veterans Study now has been extended to 26 years, with a total of 5.4 million person-years. Smoking information was collected only at baseline. To allow for the fact that many current smokers at baseline subsequently would have stopped smoking, the analysis was restricted to people who never smoked (who were unlikely to have started smoking) and to former smokers at baseline. Former smokers had elevated risks for mortality from both duodenal ulcer disease (OR = 1.8 [95 percent CI, 1.3–2.4]) and gastric ulcer disease (1.6 [1.1–2.2]) (NIH 1997). During follow-up of the British doctors cohort, information about smoking behaviors was collected at baseline in 1951 and again in 1957, 1966, 1972, 1978, and 1990. After 40 years, mortality from peptic ulcer disease was 8 per 100,000 per year among men who had never smoked cigarettes; 12 per 100,000 per year among former smokers; and 11, 33, and 34 per 100,000 per year among current smokers of 1 to 14, 15 to 24, and 25 or more cigarettes per day, respectively (p <0.001) (Doll et al. 1994). None of these studies, however, could explore possible confounding of this association by H. pylori infection.

Effect of Smoking on Ulcer Severity

Ulcers may be more severe and complications may occur more frequently among continuing smokers (USDHHS 1990). Hasebe and colleagues (1998) compared 35 patients with deep gastric ulcers (ulceration beyond the muscularis propria) and 33 patients with shallow and intermediate depth ulcers (ulceration in submucosa and muscularis propria) in Japan. They found that patients with deep ulcers were more likely to be heavy smokers, defined as smoking 20 or more cigarettes per day, than patients with shallower ulcers (81 percent versus 55 percent, p <0.05). However, patients with deep ulcers also were significantly more likely to drink alcohol on a daily basis (40 percent versus 27 percent, p <0.05) and to have H. pylori infections (97 percent versus 79 percent, p <0.01), so it is possible that these differences could explain some or all of the associations with smoking.

Smoking and Peptic Ulcer Complications

Svanes and colleagues (1997) compared patients diagnosed with perforated peptic ulcers with population controls (90 percent response rate) in Norway. Analyses of smoking were restricted to cases (36 gastric perforation and 73 duodenal perforation) and controls (n = 4,270) aged 15 through 74 years because smoking was rare in older patients. After adjusting for age and gender, the risk of perforated ulcers in current smokers increased significantly with the number of cigarettes smoked per day. The ORs were 7.3 (95 percent CI, 4.0–18.1) for smokers of 1 to 9 cigarettes per day, 8.7 (95 percent CI, 5.5–14.4) for smokers of 10 to 19 cigarettes per day, and 11.2 (95 percent CI, 6.3–27.5) for smokers of 20 or more cigarettes per day (p <0.001) compared with people who had never smoked. The risk among former smokers was no greater than that among those who had never smoked (OR = 0.8 [95 percent CI, 0.2–2.2]). Smokers were less likely than nonsmokers to have used NSAIDs or other ulcerogenic drugs. Thus, variation in NSAID use could not explain the relationship with smoking. The high alcohol consumption, however, which was significantly more common among current smokers (25 percent versus 4 percent among nonsmokers), could possibly explain some of the strong associations between smoking and perforated ulcers. H. pylori infection was not assessed, but among the cases, 87 percent of smokers and 96 percent of nonsmokers reported previous “ulcer dyspepsia,” suggesting that infection rates probably were high in both groups.

Lanas and colleagues (1997) conducted a similar study in Spain, comparing 76 patients with gastrointestinal perforation (including 31 with duodenal ulcers and 28 with gastric ulcers) with matched hospital and community controls. After adjusting for the use of NSAIDs and alcohol and histories of ulcers and arthritis, smoking was again associated with a significantly increased risk of perforated ulcers (p = 0.003). In Italy, Labenz and colleagues (1999) compared 72 patients admitted with bleeding peptic ulcers with matched hospital controls. After adjusting for H. pylori infection status, NSAID use, and alcohol intake, smoking was associated with a nonsignificant 40 percent increased risk of bleeding ulcers (OR = 1.4 [95 percent CI, 0.5–3.6]).

In the large case-control study conducted by Weil and colleagues (2000) in the United Kingdom, overall current smoking was associated with a 60 percent increased risk of bleeding peptic ulcers (OR = 1.6 [95 percent CI, 1.2–2.0]). This risk appeared to differ, however, between users and nonusers of NSAIDs. Among NSAID nonusers, smoking was associated with an almost twofold increased risk of bleeding ulcers (OR = 1.9 [95 percent CI, 1.4–2.4]). In contrast, the risk for peptic ulcers in NSAID users did not differ appreciably between current and nonsmokers as described above.

Effect of Smoking on Ulcer Healing and Recurrence

Ulcer Healing

Many studies have shown that smoking adversely affects healing of duodenal ulcers by acid-reducing agents (Lam 1990; USDHHS 1990). It does not appear, however, to have the same adverse effect on healing by other agents, including sucralfate (Lam 1991) or colloidal bismuth subcitrate (Lam 1991; Lambert 1991). In a meta-analysis, data from six studies of sucralfate were combined, giving overall healing rates of 78 percent among 301 smokers and 78 percent among 272 nonsmokers (Lam 1991). In the same analysis, data also were pooled from three studies of colloidal bismuth subcitrate, giving healing rates of 82 percent among 55 smokers and 76 percent among 38 nonsmokers. Less consistent results were reported for the effects of smoking on gastric ulcer healing, although studies evaluating the benefits of smoking cessation have suggested that ulcer patients who stop smoking do better than patients who continue to smoke (USDHHS 1990).

Rates of ulcer healing are significantly higher (Hentschel et al. 1993; Labenz and Börsch 1994) and recurrence rates significantly lower (Rauws and Tytgat 1995) among patients with ulcers (gastric or duodenal) who received H. pylori eradication therapy, which now is the recommended treatment for patients with H. pylori infection (NIH 1997). The combined effects of smoking and H. pylori eradication on ulcer healing in the short term have not been directly evaluated; however, in three studies of ulcer patients treated with H. pylori eradication therapy, there were no significant differences in ulcer healing rates between smokers and nonsmokers (O’Connor et al. 1995; Bardhan et al. 1997; Kadayifçi and Simsek 1997). O’Connor and colleagues (1995) reported healing rates for gastric and duodenal ulcers of 83 percent for smokers compared with 92 percent for nonsmokers (p = 0.3); the H. pylori eradication rate also was slightly lower among smokers (83 percent versus 94 percent, p = 0.2), possibly explaining the slightly different healing rates. Bardhan and colleagues (1997) reported duodenal ulcer healing in 96 percent of smokers compared with 94 percent of nonsmokers (p = 0.6), whereas rates of H. pylori eradication were slightly higher for nonsmokers (77 percent versus 71 percent, p = 0.5). Kadayifçi and Simsek (1997) reported duodenal ulcer healing in 82 percent and 83 percent of heavy (more than 20 cigarettes per day) and mild (1 to 20 cigarettes per day) smokers, respectively, compared with 85 percent of nonsmokers (p = 0.9). In this study, H. pylori eradication rates were slightly higher for nonsmokers (68 percent versus 66 percent among mild and 59 percent among heavy smokers). These reports suggest that ulcer healing rates are high in patients treated with H. pylori eradication therapy, regardless of their smoking status.

Duodenal Ulcer Recurrence

In studies comparing duodenal ulcer recurrence rates for smokers and nonsmokers before the introduction of H. pylori eradication therapy, higher relapse rates consistently were reported for smokers (USDHHS 1990). However, ulcers rarely, if ever, recur in patients who remain free of H. pylori, regardless of their smoking status. George and colleagues (1990) observed no recurrence of duodenal ulcers among 71 patients (31 current and 12 former smokers, and 28 lifetime non-smokers) whose ulcers had healed, whose H. pylori had been eradicated, and who remained free of H. pylori during the four years they were followed. In an Australian study, 197 patients successfully treated for H. pylori-positive duodenal ulcers had their infections eradicated and their ulcers cured. They then were followed for 12 to 73 months (Borody et al. 1992b). There was no recurrence of H. pylori or duodenal ulcers among the groups of 80 current smokers (smoking 5 to 40 cigarettes per day), 38 former smokers (who gave up smoking during follow-up or up to 20 years earlier), and 79 patients who had never smoked. In the Netherlands, Van Der Hulst and colleagues (1997) also found no recurrences in 141 duodenal ulcer patients whose ulcers had been cured and who had been treated successfully for H. pylori infection; they remained free of infection during nine years of follow-up. In Greece, there was no recurrence of duodenal ulcers during 12 to 72 months of follow-up in 141 patients who remained H. pylori negative, regardless of their smoking status; there were seven recurrences (six in smokers) among 24 patients (unknown number of smokers) who became reinfected with H. pylori (Archimandritis et al. 1999).

Although other authors have documented low ulcer recurrence rates in patients whose H. pylori infection was eradicated, ulcer recurrence commonly is associated with either reinfection with H. pylori (Bayerdörffer et al. 1993) or NSAID use (Chen et al. 1999). Furthermore, recurrence rates have not varied between smokers and nonsmokers. A study in Hong Kong followed patients for 10 to 18 months who had been successfully treated for H. pylori infection and whose duodenal ulcers had healed (Chan et al. 1997). The authors documented two recurrences (2.9 percent, both H. pylori negative) among 68 smokers (≥10 cigarettes per day) and four recurrences (2.1 percent, three H. pylori negative) among 188 persons who had never smoked or were former smokers. The study concluded that smoking did not influence ulcer recurrence after H. pylori eradication.

Patients treated for H. pylori-positive duodenal ulcers in a multicenter study (Canada, Ireland, United Kingdom, and United States) were followed for six months (Bardhan et al. 1997). All patients had healed ulcers, but H. pylori was eradicated in only 77 percent of nonsmokers and 71 percent of smokers. Ulcers recurred in 22 percent of 118 smokers and 16 percent of 117 nonsmokers (p = 0.32). The slightly higher rate seen in smokers could be a result of the slightly lower H. pylori eradication rate for this group. Recurrence rates in this study among patients who apparently remained free of H. pylori during follow-up were an unusually high 12 percent (<6 percent in three of the centers) for both smokers and nonsmokers.

In summary, smoking does not appear to affect duodenal ulcer recurrence rates in patients whose H. pylori infection has been eradicated. Among those who remain H. pylori positive, smoking may increase the risk of relapse, although no good data support or refute this possible association.

Gastric Ulcer Recurrence

A similar pattern is seen for H. pylori-positive gastric ulcers, which also rarely recur after successful H. pylori eradication therapy in the absence of NSAID use (Labenz and Börsch 1994). There were no relapses of gastric ulcers in 45 patients who remained H. pylori negative during 10 years of follow-up (Van Der Hulst et al. 1997). Chan and colleagues (1997) observed one recurrence of gastric ulcer accompanied by the reappearance of H. pylori in 15 smokers and no recurrences in 16 nonsmokers followed for up to 18 months after H. pylori eradication and successful ulcer healing.

These data suggest that for both gastric and duodenal ulcers, the main predictor of successful ulcer healing with no recurrence is H. pylori infection status. If smoking has any effect on the healing or recurrence of ulcers, it is therefore likely to be through an effect on the process of H. pylori eradication.

Smoking and Helicobacter pylori Eradication

A number of studies have evaluated the effects of smoking on H. pylori eradication. Results of studies that included more than 50 participants and presented separate eradication rates for smokers and nonsmokers are shown in Table 6.33. (Because three other studies [Fraser et al. 1996; Harris et al. 1996; Georgopoulos et al. 2000] simply reported that smoking was not significantly associated with eradication without presenting eradication rates, it is not possible to tell if there were nonsignificant differences between smokers and nonsmokers.) Although the definition of smoking in these studies often is unclear, and a range of different drug combinations was used to treat the infections, a fairly consistent pattern of lower eradication rates is seen in groups defined as smokers.

Table 6.33. Studies on Helicobacter pylori (H. pylori) eradication rates among smokers and nonsmokers.

Table 6.33

Studies on Helicobacter pylori (H. pylori) eradication rates among smokers and nonsmokers.

Other factors known to be strongly predictive of H. pylori eradication are compliance with therapy (Graham et al. 1992; Cutler and Schubert 1993; Labenz et al. 1994) and the prevalence of metronidazole resistance (O’Riordan et al. 1990). Although some studies have reported poorer compliance among smokers (Unge et al. 1993), others have found similarly high compliance rates between smokers and nonsmokers (O’Connor et al. 1995; Bardhan et al. 1997; Kamada et al. 1999). In a logistic regression model also adjusting for therapy duration and omeprazole pretreatment, Labenz and colleagues (1994) found both lack of compliance (OR = 74.72 [95% CI, 24.17–205.51]) and smoking (OR = 2.75 [95% CI, 1.56–4.86]) to be independent risk factors for treatment failure. Witteman and colleagues (1993) found that metronidazole resistance developed more readily in smokers following therapy with bismuth and metronidazole after allowing for variations in compliance (p = 0.01). However, poorer eradication rates in smokers also are seen with regimens that do not contain this class of drug. Therefore, it seems unlikely that the lower eradication rates for smokers can be attributed to either poorer compliance or an increase in metronidazole resistance. It has been suggested that smoking may adversely affect eradication by increasing acid output or by decreasing gastric blood flow, thereby reducing drug delivery to the gastric mucosa, but little evidence supports either of these hypotheses.

Evidence Synthesis

Incidence of Peptic Ulcer

Many studies have reported strong and significant associations between smoking and peptic ulcer disease. Only six studies, however, have allowed for the effects of H. pylori infection when evaluating this association. Three of those studies reported significantly increased risks of ulcer disease in smokers after adjusting for H. pylori infection; in each study, the majority (80 to 90 percent) of ulcer patients were H. pylori positive (Wang et al. 1996; Talamini et al. 1997; Halter and Brignoli 1998). A fourth study reported a significant association between smoking and ulcers only among H. pylori-positive persons (Martin et al. 1989). The remaining two studies (Schubert et al. 1993; Schlemper et al. 1996) reported little or no association, but the classification of smoking status in these studies is potentially unreliable.

Cigarette smoking has a number of effects on gastroduodenal physiology that could lead to the development of peptic ulceration, and evidence suggests that some of these effects may be potentiated in H. pylori-positive persons. Taken together, these data strongly suggest a causal relationship between smoking and the development of peptic ulcers, at least in H. pylori-positive persons. There is insufficient evidence to evaluate the relation between smoking and peptic ulcers in those who are H. pylori negative. Conflicting and inadequate data link smoking to ulcer occurrence in NSAID users and it is not possible to evaluate an independent effect for smoking in the development of NSAID-induced peptic ulcers.

There is evidence to suggest that after adjusting for NSAID use, smoking may be associated with an increased risk of peptic ulcer complications, including perforation and bleeding. Data from the most recent study (Weil et al. 2000), however, suggest that this effect may be restricted to nonusers of NSAIDs.

The effects of smoking cessation on ulcer risk have not been evaluated in the context of H. pylori infection. However, the transient nature of many of the physiologic effects of smoking suggests that an excess risk may be restricted to current smokers.

Ulcer Healing and Recurrence

Healing and recurring H. pylori-positive ulcers are closely associated with eradication and recurrence of the infection. The evidence strongly suggests that if H. pylori is eradicated, smoking has no effect on either the healing or recurrence of ulcers. There is, however, evidence to suggest that H. pylori eradication therapy is somewhat less successful for current smokers. There are no good data to evaluate the effects of smoking on the recurrence of ulcers associated with H. pylori infection when long-term H. pylori eradication fails, or on the treatment and recurrence of ulcers in persons negative for H. pylori infection.

Conclusions

  1. The evidence is sufficient to infer a causal relationship between smoking and peptic ulcer disease in persons who are Helicobacter pylori positive.
  2. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and peptic ulcer disease in nonsteroidal anti-inflammatory drug users or in those who are Helicobacter pylori negative.
  3. The evidence is suggestive but not sufficient to infer a causal relationship between smoking and risk of peptic ulcer complications, although this effect might be restricted to nonusers of non-steroidal anti-inflammatory drugs.
  4. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and the treatment and recurrence of Helicobacter pylori-negative ulcers.

Implications

The prevalence of H. pylori has declined in developed countries (Banatvala et al. 1993; Kosunen et al. 1997) and, as a result, the proportion of patients with H. pylori-negative ulcers will increase, making them an important group to study. Also, an increasing number of H. pylori-negative ulcers may not be attributable to NSAID use or other established causes of ulcers (Jyotheeswaran et al. 1998). The rarity of ulcer recurrence when H. pylori is eradicated, regardless of smoking status, suggests that smoking is not an important factor in the initial development or recurrence of ulcers among persons who are H. pylori negative. However, this topic has not been well investigated, largely because of the paucity of such ulcers, and is likely to be an important area for future research.

Because the main effects of smoking on gastrointestinal physiology appear to be short-lived, it is likely that smoking cessation will both reduce ulcer occurrence in those persons who are H. pylori positive and improve the chances of eradication in patients (with or without ulcers) treated for H. pylori infection. Even if eradication is successful, it seems unlikely that a continuation of smoking will influence the course of peptic ulcer disease.

Conclusions

Diminished Health Status

1. The evidence is sufficient to infer a causal relationship between smoking and diminished health status that may manifest as increased absenteeism from work and increased use of medical care services.

2. The evidence is sufficient to infer a causal relationship between smoking and increased risks for adverse surgical outcomes related to wound healing and respiratory complications.

Loss of Bone Mass and the Risk of Fractures

3. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and reduced bone density before menopause in women and in younger men.

4. In postmenopausal women, the evidence is sufficient to infer a causal relationship between smoking and low bone density.

5. In older men, the evidence is suggestive but not sufficient to infer a causal relationship between smoking and low bone density.

6. The evidence is sufficient to infer a causal relationship between smoking and hip fractures.

7. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and fractures at sites other than the hip.

Dental Diseases

8. The evidence is sufficient to infer a causal relationship between smoking and periodontitis.

9. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and coronal dental caries.

10. The evidence is suggestive but not sufficient to infer a causal relationship between smoking and root-surface caries.

Erectile Dysfunction

11. The evidence is suggestive but not sufficient to infer a causal relationship between smoking and erectile dysfunction.

Eye Diseases

12. The evidence is sufficient to infer a causal relationship between smoking and nuclear cataract.

13. The evidence is suggestive but not sufficient to infer that smoking cessation reduces the risk of nuclear opacity.

14. The evidence is suggestive but not sufficient to infer a causal relationship between current and past smoking, especially heavy smoking, with risk of exudative (neovascular) age-related macular degeneration.

15. The evidence is suggestive but not sufficient to infer a causal relationship between smoking and atrophic age-related macular degeneration.

16. The evidence is suggestive of no causal relationship between smoking and the onset or progression of retinopathy in persons with diabetes.

17. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and glaucoma.

18. The evidence is suggestive but not sufficient to infer a causal relationship between ophthalmopathy associated with Graves’ disease and smoking.

Peptic Ulcer Disease

19. The evidence is sufficient to infer a causal relationship between smoking and peptic ulcer disease in persons who are Helicobacter pylori positive.

20. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and peptic ulcer disease in nonsteroidal anti-inflammatory drug users or in those who are Helicobacter pylori negative.

21. The evidence is suggestive but not sufficient to infer a causal relationship between smoking and risk of peptic ulcer complications, although this effect might be restricted to nonusers of non-steroidal anti-inflammatory drugs.

22. The evidence is inadequate to infer the presence or absence of a causal relationship between smoking and the treatment and recurrence of Helicobacter pylori-negative ulcers.

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Footnotes

1

Pack-years = The number of years of smoking multiplied by the number of packs of cigarettes smoked per day.

2

Cigarette-years = The number of years of smoking multiplied by the number of cigarettes smoked per day.

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