6. Research in the present decade has established that involuntary smoking is a cause
of disease, including lung cancer, in healthy nonsmokers, and that the children of
parents who smoke have an increased frequency of respiratory infections and
  symptoms.
7. In 1964. tobacco use was considered habituating. A substantial body of evidence
accumulated since then. and summarized in the 1988 Surgeon General's Report,
has established that cigarettes and other forms of tobacco are addicting. Given
the prevalence of smoking, tobacco use is the Nation's most widespread form of
drug dependency.
8. Studies dating from the 1950s have consistently documented the benefits of smok-
ing cessation for smokers in all age groups.
9. Recent evidence, including that presented in this 1989 Report of the Surgeon
General. documents that cigarette smoking is a cause of cerebrovascular disease
(stroke) and is associated with cancer of the uterine cervix.

Part II. The Physicochemical Nature of Tobacco

1. The estimated number of compounds in tobacco smoke exceeds 4,000, including
many that are pharmacologically active, toxic, mutagenic. and carcinogenic.
2. Forty-three carcinogens have been identified in tobacco smoke.
3. Carcinogenic tobacco-specific nitrosamines are found in high concentrations in
  smokeless tobacco.

101


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II6


CHAPTER 3

CHANGES IN SMOKING-ATTRIBUTABLE
         MORTALITY

II7


CONTENTS

Introduction  ....................................................... 121

A Twenty-Year Perspective: 1965-85 .................................. 122

The Concept of Attributable Risk  ...................................... 122
Mathematics of Attributable Risk  .................................... 123
Illustrative Calculation: Smoking and Lung Cancer in Women  ............ 125
Uncertainties in Attributable Risk  .................................... 127
   Aggregation Bias Versus Statistical Precision  ..................... 127
   Age-Standardization  ......................................... 127
   Potential Biases in Applying the Results of Prospective
    Studies to the General Population  ............................ 128
    Uncertamties in Exposure  .................................... 129
    Errors in the Classification of Causes of Death  .................... 130
Previous Estimates of Attributable Risk from Cigarette Smoking   .......... 130

Populations at Risk: 1965 and 1985   ................................... 132
Cigarette Smoking and Other Forms of Tobacco Use  .................... 133
Older Cohorts of Cigarette Smokers  .................................. 134
Overlapping Populations at Risk  ..................................... 136
Changes in the Cigarette Product  .................................... 138
Other Changes in the Cigarette Smoking Population  ..................... 139
Those Smokers Most at Risk in 1985 Were Also Smokers in 1965  .......... 140
Cancer Prevention Study I and Cancer Prevention Study II  ................. 140
Nonsmokers' Death Rates  .......................................... 141
Current Cigarette Smokers' Death Rates: Lung Cancer  .................. 143
Current Cigarette Smokers' Death Rates: Coronary Heart Disease  ......... 144
Current Cigarette Smokers' Death Rates: Chronic Obstructive
  PulmonaryDisease ............................................ ..14 6
Estimated Relative Risks from CPS-I and CPS-II  ....................... 146
Endocrine and Sex-Related Cancers in Women  ......................... 152
Summary ........................................................ 152

Smoking-Attributable Mortality in the United States, 1965 and 1985  . . . . . . . . . 153

Conclusions  ....................................................... 161

References ...................................................... ..16 2

119


Introduction

In 1938, Raymond Pearl reported elevated death rates among white males who
smoked tobacco, especially those aged 30 to 60 years (Pearl 1938). Pearl's study of
6,800 subjects revealed the increase in mortality risk to be highest among heavy
smokers. In 1954, Hammond and Horn reported on the 20-month followup of their
prospective study of 188,000 white men, aged 50 to 69 years (Hammond and Horn
1954). Death rates were highest among men who smoked cigarettes but not other tobac-
co products, and increased with the amount of cigarette use. Overall, the number of
deaths among cigarette smokers was 52 percent greater than would be expected from
nonsmokers' mortality rates. Most of the increased mortality could be attributed to
deaths from cancer and especially from coronary heart disease (CHD).

In 1964, the Advisory Committee to the Surgeon General reviewed seven prospec-
tive studies of smoking and mortality, encompassing over 1.7 million entrants. For the
1.1 million male enrollees, the overall mortality ratio, defined as the observed number
of deaths in current cigarette smokers divided by the number expected from
nonsmokers' rates, was 1.68. "For all seven studies," the Committee stated, "coronary
artery disease is the chief contributor to the excess number of deaths of cigarette
smokers over nonsmokers, with lung cancer uniformly in second place. For all seven
studies combined, coronary artery disease (with a mortality ratio of 1.7) accounts for
45 percent of the excess deaths among cigarette smokers, whereas lung cancer (with a
ratio of 10.8) accounts for 16 percent" (US PHS 1964, p. 30).

In 1979, the Surgeon General described cigarette smoking as "the single most impor-
tant preventable environmental factor contributing to illness, disability and death in the
United States" (US DHEW 1979, p. vii). The 1982 Surgeon General's Report, citing
an analysis by Doll and Peto (198 l), estimated that for the year 1978, tobacco use caused
122,000 cancer deaths in men and women (US DHHS 1982). For 1982, the estimate
for smoking-caused cancers was 129,000 (US DHHS 1982). The 1983 Surgeon
General's Report estimated that 170,000 Americans died annually from CHD caused
by cigarette smoking (US DHHS 1983). "During 1965-1977," the Report noted, "there
were an estimated 2.8 million premature deaths from heart disease, primarily CHD, in
American men and women attributable to the use of tobacco" (US DHHS 1983, p. 66).

The 1984 Report estimated that 80 to 90 percent of the 62,000 deaths from chronic
obstructive lung disease (COLD), referred to later in this discussion as chronic obstruc-
tive pulmonary disease (COPD), in the United States in 1983 were attributable to
cigarette smoking (US DHHS 1984). "Over 50,000 of the COLD deaths can therefore
be considered preventable and premature since these individuals would not have died
of COLD if they had not smoked" (US DHHS 1984, p. ii). In 1987, the Economic
Report of the President stated, "Smoking presents the largest single source of health
risk in America" (U.S. President 1987, p. 184).

This Chapter further delineates the mortality consequences of cigarette smoking in
the United States. Deaths attributable to cigarette smoking are reported for two
benchmark years-1965 and 1985. The Chapter focuses on the health consequences
of smoking for current and former cigarette smokers. Deaths of nonsmokers caused by
environmental tobacco smoke (National Research Council 1986;US DHHS1988a) and

121


deaths from cigarette-related fires (Consumer Product Safety Commission 1987; Bot-
kin 1988) are not discussed, nor are the morbidity consequences of cigarette smoking
(US DHEW 1979; Rice et al. 1986).

A Twenty-Year Perspective: 1965-85

The two-decade interval, 1965-1985, was selected primarily for reasons of data
availability. The year 1985 was the most recent one for which complete, nationwide,
cause-specific mortality statistics were available from the National Center for Health
Statistics (NCHS). Moreover, in both 1965 and 1985, questions on cigarette use were
appended to the National Health Interview Survey (NHIS), a nationally representative,
face-to-face interview survey that has been conducted annually by NCHS (Massey et
al., 1987; NCHS 1986). In particular, 1985 was the most recent full year for which
complete population-weighted data from the NHIS were available (see Chapter 5).

In addition, the years 1965 and 1985 represented the approximate midpoints of two
large-scale prospective surveys of smoking and mortality among men and women in
the United States, both sponsored by the American Cancer Society. In the first of these
two prospective studies (Garfinkel 198Oa,b, 1981; Hammond 1961, 1964a,b, 1966,
1968,1969,1972; HammondandGarfinkel1961,1964,1966,1968,1969,1975;Ham-
mond et al. 1976; Hammond and Seidman 1980; Lew and Garfinkell984,1988), about
1 million persons were followed from 1959 through 1972. In the second study (Gar-
finkel 1985; Stellman and Garfinkel 1986; Stellman, Boffetta, Garfinkel 19X8), about
1.2 million participants were followed from 1982 through 1988. The two studies will
be referred to, respectively, as "Cancer Prevention Study I (CPS-I)" and "Cancer
Prevention Study II (CPS-II)." In particular, this Chapter will present unpublished,
preliminary results from the 4-year followup (1982-86) of CPS-II.

The theory, mathematics, limitations, and other methodological issues concerning
the calculations of smoking-attributable mortality are described in the next section, The
results of the analysis follow thereafter. Readers interested primarily in those results
may proceed directly to the Section entitled "Populations at Risk:  1965 and 1985."

The Concept of Attributable Risk

In 1953, Levin estimated that 62 to 92 percent of all male lung cancers were "at-
tributable to cigarette smoking" (Levin 1953). Levitt's computations addressed the
general problem: How many cases of a disease in a given population can be explained
by the presence of a particular hazardous agent or a particular personal trait? Put dif-
ferently, how many cases would have been avoided but for the presence of the agent or
the trait (Doll and Peto 198 I )?

In principle, the answer requires an experiment whereby disease rates are measured
before and after the complete elimination of the hazardous agent or particular trait from
the population of interest. Since this type of experiment is usually impractical, the most
widely used approach is to estimate disease rates in representative sample populations
of exposed and unexposed persons. The results are then extrapolated to the population
of interest.

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The phrase "cases attributable to agent A" is often used interchangeably with "cases
caused by agent A." The latter term is meaningful so long as it is recognized that
"caused" refers to an entire population rather than to any single, predetermined mem-
ber of the population. Thus, the scientific validity of an estimate that 1,000 lives would
be saved by the removal of some hazardous agent does not hinge upon naming the
names of the people to be saved.

The population-based notion of causation is especially important for chronic diseases
with multiple causes. Agent A, for example, may promote or enhance the disease-caus-
ing effect of agent B. A case-by-case analysis of afflicted individuals may never iden-
tify agent A as the primary cause in a single instance. Yet its elimination might sub-
stantially reduce disease incidence in the population under study.

Moreover, the concept of attributable risk generally requires a timeframe. In an as-
sessment of the effects of removing a hazardous agent, a researcher could ask how many
cases of a specific disease could be avoided in a specified time period, such as 1 year.
When the disease has multiple causes, this quantity may differ from the number of cases
of the disease that may eventually be avoided. By specifying a timeframe, the re-
searcher inquires not whether such cases could be completely prevented, but whether
their premature occurrence could be avoided.

For many diseases, death rates are more accessible and reliable than disease rates.
Accordingly, computations of "attributable deaths" from a disease have been used in
place of "attributable cases" of the disease. Because death from one cause or another
is inevitable, such computations necessarily refer to a specific time period during which
premature mortality may have been prevented.

Mathematics of Attributable Risk

Let dl and do, respectively, denote the incidence rates (in terms of new cases per unit
time) of a particular disease among two sample cohorts-one exposed to a hazardous
agent, the other unexposed. The two samples are assumed not to differ materially in
any other respect, so that both would experience disease incidence do in the absence of
exposure. Accordingly, the difference dl-do measures the increase in disease in-
cidence, or absolute risk, due to the agent. Moreover, the unitless ratio r = dl/do, termed
the relative risk, measures the degree to which the hazardous exposure multiplies the
baseline incidence rate. It is often employed as a measure of the epidemiologic and
biological significance of an observed association between an agent and a particular
disease (Lilienfeld and Lilienfeld 1980; US DHEW 1979).

In the exposed cohort, the proportion of disease cases attributable to the hazardous
agent is thus equal to s=(dl-do)dl (which equals (r-1)/r). This quantity has been
variously termed the assigned share or probability of causation or attributable propor-
tion of risk among the exposed (Bond 1981; Oftedal, Magnus, Hvinden 1968; Black
and Lilienfeld 1984; National Research Council 1984; Cox 1987).

For some hazardous agents, such as cigarette smoke, the disease incidence rates dl
and do and the relative risk r have been estimated directly from prospective longitudinal
studies of exposed and unexposed cohorts. Alternatively, retrospective case-control
studies do not provide estimates of dl and do but yield a close approximation to the rela-

123


tive risk I' when incidence of the disease is low (Cornfield 195 1). Both types of studies
provide estimates of the assigned share S.

The estimate of relative risk I', derived from epidemiologic studies, is then applied to
the population of interest. Let p denote the proportion of exposed persons in the sub-
ject population, estimated independently from survey data. Then the quantity f =
pr/fp(r-I )+I] is the fraction of all cases of the disease (in a given time interval) that
occurs among exposed persons in the subject population. This is sometimes called the
"case fraction" (Miettinen 1974). Moreover, if fractionfof all cases occurs among ex-
posed persons. and if fraction s of such exposed cases is attributable to the hazardous
agent, then the fraction of all cases attributable to the agent is a =fs. From the defini-
tions off'and s, the quantity a can be expressed as
                  p (r-1)
                   a=    p (r-l) + 1            (1)

This is Levin's measure of attributable risk, also termed etiologic fraction (Miettinen
1974), attributable fraction (CDC 1987b), and population-attributable risk (MacMahon
and Pugh 1970). When a is expressed in percentage terms, it is often termed percent
attributable risk or population-attributable risk percentage.
Equation (1) shows how the attributable risk a depends upon both the relative risk r
and the proportion exposed p. Thus, an agent may be significant in the causation of
disease among exposed persons so that its relative risk Y greatly exceeds I. Yet that
agent may cause a small proportion of all cases of the disease because exposure rates
p are low. Conversely, an agent that is widely prevalent (with large p) may contribute
substantially to the total number of cases, even when its relative risk r is close to unity.
As a consequence of equation ( !). the logistic transformation of a is

log 2  =
  (l-cr)   log p + log (r-l)

where log denotes the natural logarithm. Equation (2) provides a convenient method
of decomposing the uncertainty in the attributable risk a into two components-uncer-
tainty in the proportion exposed p and uncertainty in the relative risk r.
Levin's measure of attributable risk can be generalized to cases where there are mul-
tiple levels of exposure, multiple causative agents, or confounding or stratifying vari-
ables, or when an agent can prevent a disease (Walter 1976; Miettinen 1974). In the
case of multiple levels of exposure. it is convenient to let dk denote the incidence rate
and rk = dkldo denote the relative risk for the k-th exposure level. Similarly, let pk
denote the proportion of the subject population exposed at the k-th level. Then Sk =
(a--l)/rk is the assigned share among cases exposed at the k-th level. Likewise, the
quantity b==pkrk/lXwk (11-l ) + 1 ],where xk denotes summation over exposure levels,
is the fraction of all cases occurring among persons exposed at the k-th level. The
generalized formula for attributable risk becomes xkfk sk, which can be expressed as
                LWk (h-l)
                   a=   &$k(rk--J)+l           (3)

Let D denote the total number of cases of disease in the population of interest in a
given time interval. Then A = aD is the estimated number of cases in the interval that

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are attributable to the agent. The quantity A is sometimes called "attributable cases."
When relative risks or exposure rates vary by age, sex, or other stratifying variables.
then separate estimates of A can be made for each combination of variables.

When there are multiple causative agents, attributable risks can be computed for each
agent separately and for combined exposures. Thus, if agents X and Y both have a
causal role in the development of a particular disease, then the relative risk for agent X
may depend upon the presence or absence of exposure to agent Y. When X and Y act
synergistically, some portion of the total risk attributable to X will reflect the combined
contribution of X and Y. For example, indoor exposure to radon has recently been es-
timated to account for about 13.300 lung cancer deaths annually in the United States
(Lubin and Boice 1988). Radon exposure and cigarette smoking interact synergistical-
ly in causing lung cancer (National Research Council 1988). Of the estimated 13,000
deaths attributable to radon exposure, about I I ,fKKl would be due to the combined ef-
fect of smoking and radon, while about 2,000 would reflect radon exposure in non-
smokers (Lubin and Boice 1988).

Illustrative Calculation: Smoking and Lung Cancer in Women

Table 1 provides a detailed illustrative application of Levin's method to female deaths
from lung cancer in the United States during 1985. The population of female smokers
has been divided into ten exposure levels: five categories of current cigarette smokers
based on the number consumed per day; and five categories of former cigarette smokers
based on the length of time since quitting. For each exposure category, the upper panel
shows the estimated prevalence pk, derived from the 1985 NHIS. Also given are es-
timates of relative risk rk derived from the 4-year followup (1982-86) of the second
American Cancer Society prospective study (Garfinkel and Stellman 1988). At each
exposure level, the upper panel also shows the assigned share sk and the case fraction
fk.

The computations are summarized in the lower panel of Table 1. For both current
and former smokers, as well as for all females at risk, the estimated prevalences p rep-
resent the corresponding sums I& pk over the prevalence rates Pk in the individual sub-
categories. The case fractionsf likewise represent sums of individual fractionsfk, while
the attributable risks a are derived from the corresponding sums & st&. Attributable
deaths A are derived from the products aD, where D = 38,687 lung cancer deaths among
adult females in 1985.

Table I shows that almost two-thirds of all female lung cancer deaths occurred among
women who currently smoke one pack or more daily or who have quit smoking within
the last 5 years. Nine out of ten lung cancer deaths occurred in women with any his-
tory of regular cigarette use. Cigarette smoking accounted for an estimated 82 percent
of lung cancer deaths in women, or 3 1,600 deaths in 1985. About 9,300 (or 29 percent)
of the 3 I ,600 female lung cancer deaths that were caused by smoking occurred among
former smokers.

Both the prevalence rates and the relative risks in Table 1 are subject to sampling
variability. By a formula analogous to equation (2), a standard error for the logistic
transformation of a can be derived. Under the assumption that D has no sampling