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. DRArZ (S/9185) DO NOT QUOTE, CITE, OR REPRODUCE hospitaliza~ions than nonsmokers (DHHS, 1979). R/ce and Hodgson are now conducting an analysis of r_he da~a collected in the 1979 Health Interview survey. Their preliminary analysis finds thac compared to persons who have never smoked, current and former smokers report more days of restricted activity, bed disability, and work loss. According ~o ~hese data, smokers also use more medical services. They repor~ about 12 percent more physician visits and 22 percent more hospital days for each I00 persons per year (Thomas Hodgson, personal communication, 1985). Ashford conducted a large survey of the use of medical services in ~he city of Exeter in the United Kingdom. They found ~hat up co about the age of 60, male smokers consistently had more contacts wi~h ~helr doctors r_han did nonsmokers. The amount of ~he difference varied by age group, but t~pically was about 25 percent more than for nonsmokers. Above ~he age of 60, however, the nonsmokers ~ended ~o use more medical services. In part, ~his was believed to occur because by ~hat age many of the smokers have already died. For hospital services, the smokers had a higher average length of stay in r~he hospital ~handld the non-smokers (Ashford, 1973). VogU and Schweitzer used data collec~ed from the computer system of ~he Oregon re~ion of the Kaiser-Permanente Medical Care Program. They observed ~hat smokers used 20 percent more inpatien~ services ~han never smokers, but chat this difference "did not quite reach s~auisuical significance." Smokers aged A5-6A did have siEnifican~ly more hospital discharges for influenza and respiratory infections than did never smokers. In responses ~o a survey question, smokers' assessments of their personal heal~h were worse than the assessment of never smokers. Finally, they found that the never smokers used i0

..... ( ( DRAFT (519185) DO NOT QUOTE, CITE, OR REPKODUCE m~re outpatient, preventive medical services ~han did smokers, and were more liekly to use outpatient medical care for minor illnesses (Vogu & Schweiczer, 19s4). 0TA'S ESTI~fATES The following discussion outlines OTA's methods for estimating the smoking-related mortality, ~he llfe-years lost, the direct and indirect social costs of smoking, ~he health care costs of smoking, and r~he costs incurred by Medicare and Medicaid for smoking-related disease. The discussion focuses on ~he accompanying tables, which show 0TA's calculations in detail7. Smoking-related MortaliT7 • Table 1 presents previous estimates of the percentage of mortality in different disease categories chat have been related to smoking. Some of ~hese categories are less clearly associated with smoking than o~her categories. In par~ ~his is because for some ~here are important factors that may confound the associations between smoking and disease. ~or example, smokers also tend to be relatively heavy drinkers of alcoholic beverages. Thus an apparent excess of disease in smokers may not be because of the use of tobacco, but due 7The detail is presented, not to overwhelm the reader, but to allow her/him co retrace each step of ~he calculations. For ~he same reason, most of the mortalit7 estimates presented in ~he ~ables have only been rounded to the nearest whole number. These calculations are no~ nearly this accurate, but further rounding has not been made in order to allow readers to duplicate OTA's methods. ii

,° DRAF (519/85) DO NOT QUOTE, CITE, OR REPRODUCE Co r.he consumption of alcohol. Smokers as a group have a higher incidence of cirrhosis of ~he liver and ulcers. This excess of liver cirrhosis is probably due Uo consumption of alcohol. Ulcers may be independently associated wluh smoking, but for ~his analysis, both cirrhosis and ulcers will be excluded. Women who smoke during pregnancy also tend Co have a higher rate of miscarriase and ~he babies born alive weigh less than r_he average for r_he babies of nonsmokers. There is also some evidence that children of smokers have more episodes of respiratory illness than do children of nonsmokers. Burning cigaretues also s~aru fires--fires that take an estimaUed 2,500 lives each year. Finally, nonsmokers who are exposed to cigarette smoke ("passive smokins") may have an increased risk of disease compared to people nou exposed to tobacco smoke. For simplicity, however, these cauegories will be excluded from ~his analysis. Instead, OTA has focused on the three major categories of smoking- related disease--cancers, cardiovascular disease, and respiratory system disease. These accoun~ for ~he vast majoriUy of smoking-rela~ed deaths. Cancer Deaths Table 3 presents r/Re calculation of the number of deaths in 1982 for" ~he cancer sites most clearly associated with smoking: the respiratory system; lip, oral cavil, and pharyr~; esophagus, pancreas, and bladder. The me~hod is identical Uo the method used by Doll and Peto to generate their estimate r.hat about 30 percent of cancer deaths in the U.S. in 1978 were associated wir.h smokin~ (Doll & Peto, 1981).8 .........._..__ 8Doll and Peto prepared their estimates under contract to OTA. Their report was the basis for part of the OTA assessment of Technologies for Dererminin~ 12 &n o

(5/9/85) ( DO NOT QUOTE, CITE, OR REPRODUCE Their method used the mortalit7 rates for nonsmokers from the large American Cancer Soclet7 (ACS) study (often referred to as ~he "25-state s~udy" or r.he "million person s~udy"). The age-specific mortality rates (from Garfinkle, 1980) are r~hen applied to the number of people in age and sex specific population Eroups. Multiplying the t~vo leads to an estimate of the "expected" number of deaths r~hat would have occurred in a given year if everyone had r~he mortalit-y experience of ~he nonsmokers in the ACS s~udy. This "expected" number is ~hen subtracted from the number of deaths that ac~ually occurred. The difference is attributed to smoking. The number of deaths for each t~/pe of cancer is taken directly from the Vital Scatlstics data published by the National Center for Health Statistics (NCHS). The NCHS data are based on ~he information about the "underlying" cause of death supplied on dearth certificates by physicians. The las~ column is r.he "attributable risk," the percen~ of r.he deaths in ~hau category ~hat can be attributed to smoking. It is calculated by dividing r.he number of "excess" deaths by ~he total number of dear.hs in that particular age or sex grouping. In addition to the five major sites, Doll and Peto also attributed a relatively small number of cancers at other specified sites to smoking. These include some sites ~hau may be associated with tobacco, such as kidney cancers, and o~hers that may include some misdiagnosed cancers (for example, some "stomach" and "liver" cancers may be misdia~nosed pancreatic cancers). Doll and Peuo included 5,000 male and 1,000 female cancer deaths for these Cancer Risks from the Environment. The Doll and Peuo report itself was later published in the Journal of the National Cancer Institute and republished as a book by Oxford University Press. 13

DRAZT (5/9/85) DO NOT QUOTE, CITE, OR REPRODUCE or-her si~es. The figures of 5,000 and 1,000 are also used for OTA's estimates. They also included a share of ~he cancers reported To NCHS wlthou~ information on r~he specific site. The fraculon of male and female cancers ~ha~ had been esuima~ed for the specified si~es was then applied to the total number from unspecified slues. Doll and Peso made one adjus~menu to ~he non- smokers' mor~alit-y rates from ~he ACS study. To allow for r~he possibiliuy ~ha~ ~he nonsmokers in ~he ACS s~udy were less exposed uo alcohol or o~her causes of upper respiratory or digestive system cancers r~han were nonsmokers in ~he enulre U.S. populauion, ~hey doubled the number of deaths from cancers of ~he mouuh, pharyruc, larynx, and esophagus expecUed in non-smokers. This adjusrmenu has been made for ~hese si~es in Table 3. Table 4 ~o~als uhe resulus of ~e calculauions in Table 5. Overall, abouu 32 percen~ of all cancer dear.hs in 1982 are a~ribu~ed to smoking, compared ~o 30 percen~ in 1978. Fort-y-four percenU of cancer mortali~ in men is relaued uo smoking, and abouu 18 percenU of female cancer moruali~y. There are siEnificanu age differences in the auuribu~able risks for cancer. Fifuy percent of male cancer deaths under ~he age of 65 are related to smoking, compared uo A1 percenu of male cancer deaths over age 65. Similarly, for women, 23 percenu of deaths under age 65 and 15 percenu of those over 65 are a~ributed to smoking. To construc~ a lower bound estimate of the smoking-relaUed autribuuable risk for cancers, OTA assumed ~hau only lung cancers are associated with smoking. In addition, uo accoun~ for ocher possible causes of lung cancer ~hau ACS subjects may nou have been exposed ~o (such as certain occupational 14 O

\ 6 DRAFT (5191S5) <. DO NOT QUOTE, CITE, OR REPRODUCE exposures, such as to asbestos), ~he non-smoker rates from the ACS study were doubled. The resulting attributable risk estimates for cancer are still large--33 percent for males under 65, 27 percent for males 65 and over, 15 percent for females under 65, and 8 percent for females 65 and over. This certainly overstates sets too low a lower bound for the estimates of cancer risks. However, the resultinE estimate of smoking-related dearths is still very large--about 89,000 deaths or 21 percent of all U.S. cancer deaths. The highest reported estimate for smoking-related attributable risk for cancer is 38 percent (Doll & Peto, 1981, based on tables prepared by Enstrom). An upper bound can be constructed from this estimate. If the 58 percent figure is increased to ~0 percent to allow for the increasing share of cancers due to smoking over time, ~his upper bound represents a 25 percent increase over r_he OTA attributable risk estimate of 32 percent. If this is assumed to apply equally to all age and sex groups, then the upper bound estimates are: 63 percent and 51 percent for men under and over 65, and 29 and 19 percent for women under and over 65. These lower and upper bounds are used in the calculation of smoking-related costs in Table 16. Chronic Obstructive Lung D~sease Deaths Table 5 presents r_he calculations of attributable risk for chronic obstructive lung disease. These include emphysema and chronic bronchitis. The attributable risks are calculated using the method employed for cancer deaths. The published results of the ACS study (Hammond, 1966) provide age- specific death rates only for emphysema. 15

DP, ArZ (5191S5) < C DO NOT QUOTE, CITE, OR REPRODUCE The races for nonsmokers for emphysema from r/%e ACS s~udy were doubled before ~hey were applied to ~he count of ~he U.S. population by age and sex in 1982. This allows for deaths from o~her forms of chronic obstructive lung disease ~hat are related tosmoking r~hat were not included under the coding "emphysema." In addition, this doubling allows for the probability that the ACS population did not have large numbers of people wir/% significant occupational exposures (such as to asbestos, silica, coal dust, cotton dust); exposures that lead to or_her forms of chronic lung disease. Finally, ~he actual dear/is reported by NCHS were reduced by I0 percent, r-he approximate number of dear/%s due to asthma that are also included in this cause of dear-h classification. Thus, about 87 percent of chronic obstructive lung disease deaths appears to be related to smoking. Table 6 presents the total number of deaths coded as related to t/Re respiratory system. These include pneumonia, and influenza, as well as chronic obstructive lung disease. While the approximately A6,000 smoking-related deaths from chronic obstructive lung disease represent about 87 percent of all chronic obstructive lung disease deaths, r-hey account for about ~3 percent of all deaths from respiratory system disease. In contrast to smoking-related cancer deaths, the attributable risk for male respiratory system dear/Rs is lower for r/Rose under 65 than it is for r_hose 65 and over. The attributable risk for men over 65 is A9 percent, while for those under 65 it is about AO percent. For women, however, the reverse is true. Forty-four percent of respiratory system disease deaths for women under 65 are attributed to smoking, compared to about 34 percent of respiratory system dear/Rs for women over 65. 16 G8

DP, (SlglSS) DO NOT QUOTE, CITE, OR REPRODUCE An important assumption is ~ha~ uhe death races for non-smokers from ~he ACS study can be applied co the U.S. population. Aside from smoking, ~he only or_her siEnificanC cause of chronic lung disease is occupational exposure. The ACS population may noU have included very many people with these exposures. To allow for ~his, the races from the ACS s~udy were doubled for OTA's esclmace ~hac about 87 percenu of chronic funE disease is associated with smoking. Even if the ACS races are ~ripled, the resultinE auuribucable risk estimate is 81 percent. Zf, on the ocher hand, the races from the AC3 s~udy are increased by only 50 percent (co allow for smoking-related funE disease no~ reporued as emphysema), the attributable risk is 90 percent. There is evidence thau smokers have an increased risk of dying of pneumonia and influenza, buU because of the epidemic nature of influenza, ic is difficult co estimate precisely the smoking-related fracuion for any one year. Thus, even though some of ~hese deaths are related Co smoking, they have been excluded from this estimate of the number of deaths associated with smoking. For uhe cosu analysis presenued below, however, an acuribucable risk estimate for pneumonia and influenza mor~aliuy has been used Co develop an upper limit Co the range of attributable risk estimates for all respirauory system disease. Rice and Hodgson aUuribuued abouu 20 percenU of male and 30 percent of female deauhs from pneumonia and influenza to smoking. Adding 20 percenu of pneumonia/influenza mortality to the Table 6 values of 39.9 percent (under 65) and A9.3 percenu (65 and over) yield upper bound esuimaues of A8 percenu and 59 percenu. For females, adding 30 percenu of pneumonia/influenza mor~alit-y yields upper bound estimates of 57 (under 65) and ~ percenu (65 and 17

• b DRA ' (5191S5) ( ( DO NOT QUOTE, CITE, OK REPRODUCE over). Lower bound estimates were constructed by simply (and somewhat arbitrarily) subCracn/aE 20 and 30 percent from ~he estimates in Table 6. resulting range of attributable risk estimates is used in Table 16 for calculating smoking-rela~ed healr/% care costs. The Caudiovascular Disease Deaths Cardiovascular disease includes bor.hhearu disease and strokes. The latter is less clearly linked to smoking ~han the former. In addition, even in ~he studies ~hat have linked it to smoking, it appears ~hat only in younger age groups (specifically, those under r/Re age of 65) do smokers have siEniflcan~ excess risk of cerebrovascular mortality. ~stlmates Usln~ Rates Sot Non-smokers. Epidemiologic studies have clearly linked smoking with ischemic heart disease. Death from ischemlc heart disease arises from a myocardial infarction, the most common form of fatal "heart attack." Heart disease rates have been declining over r/Re last 2 decades. Thus, r/Re heart disease death rates from the ACS study cannon be used directly to generate an "expected" number of cases. Mortality from all cardiovascular disease has been falling for the last 20-30 years--for heart disease rates began falling in the mid-sixties, while for strokes the decline began in r/Re 1950s. It is generally believed that these declines represent the results of a combination of factors, including improvements in diet, decreases in ~he prevalence of smoking, and changes in medical care, such as improved control of hi,h blood pressure, the use of intensive care units and coronary artery bypass surgery. However, the relative importance of these factors is still a ma~ter of debate (see Goldman 18 O

DO NOT QUOTE, CITE, OE REPRODUCE & Cook, 198A; Pell & Fayerweacher, 1985; ~alker, 1983; Kleinman, eC el., 1979; Kennel, 1982; Scallones, 1980). Because of the quantitative uncertaint-y in portion of the decline in cardiovascular mortality =hac can be attributed to the reduction in smoking, a range of adjustments is used here. Goldman and Cook have attributed 2& percenU of the decline in coronary hear~ disease death races co reductions in smoking. In Table 7, =he non-smoker death races for coronary hear= disease from the ACS study have been adjusted by I00%, 75%, and 50% of the overall percentage decline in the years following =he 1963 followup of =he ACS study. Seventy-flve percenu approximates the Goldman and Cook esuimace thaC 2A percent of the decline is due to reduced smoklng--a change thac would noc affect the rates for non-smokers. This is bounded by adjustments chat assume thac non-smokers experienced, either I00 percent or 50 percent of the decline in overall cardiovascular mortality races.9 Table 8 presents similar calculations using data from =he Framingham Hear~ Study. Because of =he care oaken in diagnosis of disease and reporting of informaclon on cause of death for =he subjects of =his suudy, the rates for the different subcacegories of deaths due co circulatory system disease do noC directly correspond co national raues. However, the races for all cardiovascular disease are comparable. Thus in Table 8 the races for all 91C should be noted Chac these calculations for hear= disease only include persons up co the age of 85. The ACS s=udy did uoc publish hear= disease rates for those over 85. However, as will be discussed later in =his paper, mortality ratios for smokers (compared co non-smokers) decline wizh advancing years as non-smokers eventually die of hear= disease. For example, =he mortality ratio for chose aged 75-8A is 1.2. Thus =he implici= assumption uhau no one over =he age of 85 dies of smoking-rela=ed hear= disease undersua=es these es=ima=es, but probably no= =o any great ex=enc. 19