Tobacco Documents Online

I SAMMIEC II Smoking-Attiibutable Mortality, Morbidity,-and Econom.i: Costs Computer Software _ and - Documzntation Project Staff 40 James M, -Shultz, M.S., Ph.D. - Department of Epidemiology and Public Health University of Msami School of Medicine 1029 N.W. 15th Street (R~69) Miami, Florida 33136 (3J5) 347-6972 - - Thomas E. Novotny, M.D. ChieL Program- Services Activity _ Office on Smoking and Health Center nter for Chronic hronic Disease Prevention and Health Promotion - Centers for Disease Control Public Health Service U.S. Department of Health and Human Services Rochville; Maryland 201i57_ (301) 443-1575 Dorothy P. Rice, M.S., Sc.D. (Hon.) -- Department of-Social and Behaviorai Sciences School of Nursing - University of California San-Francisao, California 94143 The authors wish to aclmowledge- the editorial and production assistance provided by HCR and- iu staH, including Donna Grande, Project Director, and William Thomas, Jr., Information Support Coordinator.

A ., , SAMMEC II Smoking-Attributable Mortality, Morbidlty,_ s€nd Ec°onomic Costs Computer Software and Documentation Module 2: t1'fethodology -and Conceptual Issues James M. ShtlYta, M.S., Ph.D. Thomas E Novotny, M.D. Dorothy P. Rice, M:S.,- Sc.D. (Hon.) Prepared for. __ - - Otfiee on Smoking and Health Center for Chronic Disease Prevention and IIleeltb Promotion Centers for Disease Control Public Health Service - US. Departenent of Health and Human Services October O40

SAAMIEC II 1Vf odule 2: Iviethodology-ard Conceptual Issues Table of Contents Page Chapter 1: Ile Disease Impact of Cigarette Smoking _ 1 -Chapter s:- Smoking-Attributrble Disease Impact Estimation Rationale - - - 3 Data for the Group Under Study - 3 Epidemiologic Measures 4 Economic Cost-of-Illness lvieasures 4 The Role of Computer Software 5 Chapt.er 3: Smokirtg-Attribntable Desease Impact Estimation: Conceptual Issues - 7 ibe Scope of the Calculations 7 Interpretation and Use of the Estimates - 9 Disease Impact Estimation as a Health Policy Intervention 10 Conceptual Issues for Cost-0f-Ill.•g= Studies -_ - - - 10 Estimation ls.sues for Cost-of-Illness Studies - - 12 Chapter 4: Sretoking-Attributable Cost-of-fllness Studies: Review of the :aterature 17 Cost-of-fllness Studies - 17 Cost-0s i lness Guidelines - - 17 National Calculations of Economic Gosts-Attributable-to Smcldn; United States 18 Natioaal Calculations of Economic Costs Attributable to Smoking: Other Gouutriea - 20 State Calculations of Econosnic Costs Attrshutable to Cigarette Smoking 20 Economic Costs to the Individual Annbutarbie to Cigarette Smoking 21_ Cost Offsets: Extended Iafe Expectancy for Nonsmokers- and Former Smokers 22 Summary - - - 22 L J./ CG't QD b.I Xh

0 j Chapter S: I'be Disease Impact Measures_ - 23 Definitions of Smoking-Related Disease Impact Measures 23 Chapter 6: Smoking-Related Diagnoses - Chapter- 7: Smohng-Attributable Fractions 27 - (,hapter 8: Calculation of Smoking-Attributable Mortality 31 - Smoking-Attributable Mottality. An Over-view= 31 - Estimation of Smo1~`ng-Attributable Mortality - 31 Comments on Smoking-Attributable Mortality-Related Measurm 31 Smoldng :4?trtbutable Mortality Rates 32 Chapter 9: Calculation of Smoking-Attributable Years of PotentW bife Lost 33 Smoking :Attributable Years of Poter~tial -Life Lost:- An Overview 33 Fstimation of Smc~g-Attr,~uta.bl euta.ble Years of Potential Life Lost 33 Smoldng-Attnbuta-ble Years of Potential Life Lost_ Rates - 33 Chapter 10: Calculation of Smolcing-At-t:ibutable Indirect Mortality Costs 37 Smoldng-Attn'but~kle Indirect Mortality Costs: An Overview 37 Estimation oi Smoking-Attributable Indirect Mortality Costs -- Smoking-Attributable Indirect Mortality Cost Rates - 37 38 lK.N Chapter 11: Calctraat:an of Srnoking-Attributable Diaect Health-Care Costs _ 41 - Smolr:og-Atta-ibutable Direct Coats: An Overview ' 41 Estimation of Smoking-Attributable pirw Health-Care Costs - 41 Chapter 12: - Calculation of Stnoking-Attributable Indirect Morbidity Costs 43 = Costs: Ap Overview ble indirect Morbidit but Smola Att 45 y ng- ri a Estimation of Smoltir.g-Attnbutable Indirect Morbidity Codts_ -- - -- 45 Iteferences - - 49

Chapter _ I The Di-sease_ Iznpact of C:gaa ett=e Smoking Cigarette smoking is the chie& single preventable cause of premature mortality in the Unit~ States (U.S. Deparu~ent of Health and ]`Ier~man Services, 1986). A series of reports by t.he Surgeon General on tb E- health consequences of smoking has documented the contribution of _ cigarette smoking to deaths e.aused by cancers (USDHHS, 19182), cardiovascular diseases - (USDHHS, _ 1983), and chronic obstructive pu!ffionarq diseasm (USDFi..~i,S, 1984). From these three reports, national smoking=attnbutab1= mortality was estimated at 350,000 deaths in 1980 (equivalent to 17% of total national mortality). Other estimates of mortality attnbutable to cigarette smoking have-been reported, including-27Q,C00 deaths for 1980 (l~ce et_aL, 1986), 314,000 deaths- for 1982 (Office of Technology Assessment, 1985), 320,000 deaths for 1984 (Centers for Disease Control, 1987) and 390,000 deaths for 1985 (L3SDH~iS, 1989). On average, each smoker_ who dies ftom-a smoking-related disease forfeits 15 years- of life compared with his or her- nonsmaking counterparts (.Varner,-1987). -Morbidity rates are higher for-cigarette smo-kers- throughout their life, particularly from respiratory diseases,- than for persons who have never smoked. - Moreover, both ac the workrite and at home, passivcsmoking (the inhalation of sidestream emissions from cigarettes smoked by co-workers or family members) -increases the risk for lung cancer, coronary l±eart- diseau, and respiratory disease am ong nonsmokers= (LJSDHHS, 1986). In the United States,- direct medical costs #or the detection, treatment, and rehabilitation of persons with smoking=attribu3ablc clinical diseases have- be-en estimated to exceed S23 billion _ annually (1984 dollars, Rice et al., 1986). Indirecc morbidity costs, defined as the costs for excessive 3ick leave days and disability days for smoldng-linlced illnesses, are regarded as a negative productiviry-facsor estimated to -total $9 billion-annually. Indirect mortaiiry costs, defined as the economic value of forfeited futurc :.arnmgs for persons who die prematurely from smoldng-relatecl causes,- are-valued -at -$2 1 btllion annually: Tae- total of these three cost measures (S53 billion) is -equivalznt to 7% of total national direct costs of illness plus 1~0 of illness-associated indirect costs. Not included in this estimate are the psychosocial oosts associated with smoking-related disease& These data provide compellang reasons for the active promotion of nonsmoDdr_g. Such activities include health education among youth for primary prevention of smoking°, smoking cessation programs for persons addicted-to zigarettes; economic disincentives to smoking; and-regulatory controls on the production, marketing, and sale of-tobacco products. "I-be development of smoking-control policies and educational programs relies heavily on State, local, and corporate decision-makers. For each jurisdiction, the following questions can be -- asked: 'How many people die from smoking-caused illness?' 'How much- is smoking costing tu?' 'What would be our return on- investment for a nonsmoldng initiative?' For each question, the concept of cost includes both tangible -and intangile costs. Answers to some of I

these questions are .~s~le frotF.~ existing data sou~. •3uribg the past decadc, incrcasingly sophisticated methods have been applied to estimate the eeonomic costs of smoking (Luce and Schweitzer, 1978; Forbes and 'fbompson, 1983; Rice and 1-Iodgson, 198?; Oster et aL, 1984; O6ce of iechnology Assessment, 1985; Rice et a3., 1986). - - 'Disease impact estimation' is used here as-an expression for the process of quantifying a health problem from several vantage- points, including -morbidity, mortality, and economic costs. The combination of epidemiologic estimates of the human costs of smola.ng-(mQrbidity and mortality) with indicators -of sn;oking-attrib_ utable econorn:c-costr provides a comprehensive-pictung of d.isaase impact. Although= disease impact estimation methods have been used with national data, we of these methods -vvith local data ha-s been technologicall~y d.ifficult. _ As a=r~ul~ thc-h~nesota - Department of He~~h (IyIDPl~ developed mici•ocomputer software for estimating amol4ng- attributable disease impact (Sbultz, 1986a, 1988). Ile- software evolved during development of a statewide smoleng-;ontrol plan _(INIDK-1984; Dean et aV, 1985, 1985), -the passing of-oon= smoldng legislation (Shultz et a! , 1986), and the implementation of the program atic phase of the plan (the kii.an_esotd -Nonsm~okdbg Initiative). 'Ile- software-was named SAMMEC _ (Smoking-Attnbutablc Mortality, Morbidity, and Economic Costs). - SAMMEC was used_ to produce a national estimate of sraoking-attri'cutable mortaiity and yeztrs of potential li:e iost-for 1984 (CDC, 1987). In additiQn, -State-speciFic calculations -for -198r were performed-by State-based_CLC-personnel and State employees in all 50 States, Puerto Rico, and Washington, D.C. (C7 C, 1988). These data are pubiished in=the 1990 bicnnial status report to- Congress pi=oduccd by the O~'i~ on Smoking and Health ,USDF€HS, 1~). - SAMMEC was also -Used-to develop disease impact estimates for other nations, including Austraua, France, the People's FcepubhC of China, and-selected provinces in Canada (Health Department of Western Australia, 1937;-Hi_11 and Giron,-1982+World Banlt,_ in press; Collishaw and Myera, 1.984). ~ Tbe current and -expected disease irnpact of Eigarette_ smoking for less developed countries (LDCs) has- not been-adequately quantified (Ltwit, 1988). Smoking prevalence rates, on which predictions of smolcng-attn-butable disease depend, are increasing in many LJ>CL- 4lthough - smo;<ing-attnbutable d:sea_se in;pact cstunation is important for LDCs, calculation procedures L the lack of mortality, and software tools su ch as SAIvsNEC _P may be inappropr'-ate because of prevalence, and -econdmic datd in these countries. -- - SAMMEC II is the second phase of SA,'+INffiC applicatiori,s. - SnMRMC II is a new software product-that improves on the 5nethodology of its predecessor and sccornmodates additional types of health data. OD _ VI AD -- - ~ ~ !-a 2 7~ Q #N1

- - Chapter Smoking-Attributable Disease Impact Estimation ~~. the tobacco industry (Schelling, 1987; Warner, 1 RadonskA formidable cass against tobacco use has -been made by estimating the disease burden of cigarette smolang (IJ.S. -Department-of Health, Education, and Welfare, 1979). .is burden has- tieen quant~ed in te~s -of smo~ng-~t~'btstable mortality, years of pot.ential ;ife iost (YPLL), excess medical care, =and e;cess disability (Rice et aL Economic measures belp define-the impact of cigarette-smolcing on health-care syitems-snd on the productivity of the population (Shulta, 1985a; Office of 'f'echnology Assessment, 1995; Rice et aL, 1986). Estimates of smoking-attributable econotn.ic costs are useful for developing health policy and for planning smoking-control initiatives. - In additiona cost ertimates may help -- polieyaFakers make decision-, about- tobacco-control activities (Shulu and Moen, -19$6; St,ultz et al.,-1986,_Smitl:i et aL, 1990). - Previous -smolting-related disease impact studies do not descn'be al! dimensions of smoking and disease. For ez:ampie, the pain and- sufi'enng, decreased quality of life, and related- Psychosocial - aspects o, physical illness are not- measured- (Abt, 1975; HHodgson and- Meiners, 1979). Prevalence-based =t-o; -t7iness calculatioas do not account for economic factors such as Social Secutitv disbursements, pension claims, changes in the demand for bealtb- specialties related to the treatment of smoh~g-associated illness,- and the,"empl-oy3nent by or monetary dividends from Data for the Group Under Study Five -sets_ of data are necessary for computing disease impact measures: mortality data,_smokiDg prevalence rates, b+eaith-care cost data, earnings data, and populatioa data.- These data are available -for all States and for some large municipalities. Outside the United States, the quality and availability of these data vary considerably. State-specific smoldng-prevalence rate data are available for States p$rticipating in_tbe telephone-based Behavioral Risk Factor Surveillance System (Bft.) conducted by the Centers for Disease Control (CDC) (Remington et al., 1985; CDC, 1989a j. The BR~'SS provides comparable data for all participating States. Tle Office on Smoking and Health used smoking prevalence data-from the Current Population Survey (CPS) in its State-specife calculations for 19&5 (Marcus et al., 1989). State-speciflc CPS data for 1989 are now avai7able. Estimates of direct bealtb-care costs attributed to smoking require an estimate of total personal health-care expenditures for the prevention, diagnosis, treatment, and rehabilitation of all i7lnes3es for the group under study (Hodgson, 1983; FRice et aL, 1986). In the United States, health-care cost estimates used in SAJvIIv€EC II may be available fiom State health agencies, the 'A

Health Care Financing Admiaistration (Levit, 1985; Lazenby, 19W, or university-based health services researchesa. For comparabdity among States,-co3ts can be prorated using national personal health-care expezsditures compiled by the Health Care-Financing f5dministrationfor five cost centera: hospita izz-tion, physicians' fee's,-nursing home fees, medications, and other professional servicm Epidemialogic Measures The pivotal calculation in di;easeim impact estimation isthe att-rsnutable-risk, or'smoking= anttbutable frac€ion' ~el~, 1987). This measure, -de~ne + as the maximal proportion of casc~ of a disease causally=liaed to cigarette smoking, is a function of two otber-- measures: current and former smoking prevalence rates and relative risks (Lilienfeld and Menfeld, 1M,-Walter,- 19i6). Diagnosis-specific rela - tive risks for smolcing-related diseases, -defined as the ratia of mortality- -among current or former smokers to that of never -smokers, have been developed -from several large prospective studies-of-smoking and mortality (Hammond, 1966; Kahn, 1966;-Doll and - Peto, 1976; Cederlof ec aL, 1977; Doll et aL, 1980; Stellrnan and-Garfinkel; 1985; U.S. Department of-Healtn and =Human Ser•~is.r.s, 1989). Relative risk estimates for smoking diffzr by sex and study population (USDHEW, 1979; ??SDHHS, 1989): Relative rWa are typically lower for former smokers than for current smokers; for former smokers, relative risks decrease as the number ofyears after cessation increases. However, age-specific relative r-isk estimates are not avai7abl-e for most smoldng-related diagnose& S?tlvD:ffi-C H software benefits hrom-the inclusion of updated _relative risk estimates derived from the most recent American Cancer Society data, the Cancer Prevention-Study lY (CPS-I~) (USDHI:S, 1989). These.-relativerislt- estimates are based on a fou3-year follo°•a-up study (1982 -to 1986)of 1.2 million entrants of the CPS-IL For smoking-related-diagnoses in the CFS-H, the relative risks-yvere calculated by - comparing the age-adjusted mortalit•j rates for current -and former smcrkers- with those of never smokers. For a specific population, the smoking-attributable fraction may be an overestimation or an underestimation- if the physiological ,and behavioral sharacteristics of the populat;otk are not comparable to those of the- study populations -from which the relative risk measures were - derived. Use of smo--lring prevalence rates for the current year also may result in an under- estr,mate of smoking-attn'butable diseaseand-death. Overall smoking prevalence rates are lower in recent years_ than in the- previous 30 years (fJSDHHS, 1989), and the burden of most chronic diseases linked to- smoking, such as cancer and obstructive -pulmonary-disease, reflects previous decades of higher smoking prevalence. Economic Cost-of-Rlness Measures- Health economics measures calculated by SA1viN.EC II also use a prevalence-based method- ology (Rice et al, 1986) that estimates the current annual costs of the lifetime smoking = behavior of persons who receive medical treatment, are absent-fromwork,-os succumb to smoking-induced Wness during the year under study (Scheiling, 19S7). Grossly aggregated

) econom,ic data on health-care costs do not permit diagnosis=;pecific estirtmatrs.. Personal health - expenditure data are typically sum- mariaed-by type of cost (e.g., bospital costs, m_edi6ation costs) and only occasionally by disease catepa:y- (H9dgson and Kopsseirc, 19£~4',.' Data are incomplete for patterns- of morbidity and patterns of inedieal use by disease status. The National Center - for Health Statistics has documented excess rates of hospitalization and use of physician services for smokers compared with never smokers (Rice et aL, 1986). However, a study of medical use, by smoking status, for participants in the Kaiser-Peririane8te health plan indicated that rates of outpatient service -utilization did not differ between current smokers and persons who had never smoked; smokers were less likely to seek preventive medical services (Vogt and Schweitzer, i98"Z). Availability s~d ac~i.*aey of estimates of total person$1 health-care crpenditures also vary by State. Ile entire array of health econoaics data, as well as its completeness and accuracy, may -v°ary considerably in other nations. Tae Role of Computer Softva:+g Spreadsheet soft-waPZ=incorporates both epidemiologic and ealth_eco:iorni~ data (Shultz, 1985b, 1986a, 1988; Sbuliz~ Rice, and Ir:odesoz:, 1986). - Calculati~ i~nr can be reproduced rapidly and accurately. Standardized software can generate reports spccific to populations- under study and provide comparable estimates for similar populations. Ho•vever, unercical use of disease irnpact data produced by SAN'wfEC II may lead to- misinterpretation or overinterpreta:ion_ of findings. 'rhese Iimitations_ ~re discussed later-in-this docun:ent. - 39 - -- - CJY CX' ~ ~ N ~ 5 O

r Chapter 3 S-rnoking-Attributable Disease Impact Estimation:_ Conceptua=l Iss-ues The Scope of tbe- Calculations Tbe disease impact calculations dcscribed here include direct health-care costs, indirect mortality costs, and indirect morbidity costs. These thre_e types of costs are routinely u3ed by the National Center for-Health Statistics-to defirle the costs of illness (Hodgson, 1983; Hodgson and Meiners, 1979, 1982). '1'ney do not _represent all economic interactions. Sever~l important questions about compensating economic effects-are presented below. - ."_. _"y (1j -Ane smoi'dng-atzributable dir_ect medical costs a net liabi;liry to society? Warner (1987) notes that calculations-by Rice and colleagues (19S6) focus on the readily measurable, tangible zosts-of smoking. ':bese calculations regard smoking-attributable direct medical costs as a liability. Warner notes-that, from a purely economic viewpoint, health-care expenditures attnbutable to cigarette-smoking also represent tobacco-related jobs-created and incomes paid to workers. Another perspective is that the provision of medical eare services for coping witlr the consequences of cigarette smoking requires that society forego alternative goods and-services (an argumcnt used by Berry and Boland, 1977, against alcohol abuse). Rice and colleagues (1986) state: On average, current and -former smokers use more medical care ... than persons who have never smoked. Although a smoker may suffer from smoking-induced illness and require medical care, the cost of treatment may be borne, at least in part, by others. This occurs, _for example, when medical care for smoking-related diseases is paid by health insurance funded by premiums from both other smokers and nonsmokers, or by public expenditures such as Medicare and Medicaid. [2] Do smokers generate larger lifetimt medical cosir than do n6nsmokes? Lewit (1983) suggests that movement toward a tobacco-free society may reduce heaJth-care costs. Conversely, a Swiss study indicated that higher annual medical costs for smokers were offset by the longer lifetime of medical utilization by nonsmokers (Lzu and Schaub, 1983, 1985): Lifetime medical costs per individual were_found to be-equal for smokers and nonsmokers. Wareer (1987) discusses the offsetting effects of longer life expectancy for nonsmokers, which leads to a delay, but not necessarily a reduction, in lifetime health-care expenditures:- ..t it is clear that, in financial terms, all smking-related health-care xats do not represent a pure social burden. At least some of these costs would be offset by the later health-care costs associated with a tobacco-free society, even xi CA OD .~ CD ipa

recogr.izing that the latter would have to be d iscounted to re0ect their later occurrenx. In addition, Schelling (1987) statea: Careful estimates have not been done for t.be-United States, but it seems-a reasonable guess -that the bealth-eare costs that are obviated by premature deaths attnbutable to tmolang are-at least the order of magnitude of the bealth~are _ costs attnbutable to fatal smoking-induced illness. These are reasonable- arguments- but they are not based on -data from-definitive studies that examine medical utilization by smoking status in old age. Deferred M8ess and compression _ of - morbidity in advanced ages may be the outcome-of lifelong nonsmoking and hygienic behaviors. Excess morbidity from smoking is latown to extend throughout the lifespan (Hermanson et aL, 1988). [3] Do nonsmokrrs -rost more than smak= in ScciaB S¢curity and pen.sion-cldi:rrts? Warner (1987) notes that extended longevity for a 3obacco-free society would also increase the number of people livi.ng well into retirement and increase the burden on -pension plans and Social Security. ScSelling (1987) showed this by a simple -numerical exercise and then- - concluded that 'people who smoke and-die 15 years early- are net _financial benefactors to the - rest of society, by living most of a normal productive-tax-paying life and dying before they can - claim their retirement benefits.' However, Social Security-and pension claims are regarded by economists as transfers, or purely financial transactions, in contrast to expenditures for goods or services (Scbellang, 1987). Rce and colleagues-~19fi6) state: Social Security, _pensions and disability and_ sickness payments to _ill stnokers subsidized by non3mokers (and smokers who do not sufyer tU bealth_et~`,ects), and payments forgone to smokers who die prematurely to the benefit of nonsmokers are also payments which transfer controt over- the -use of resources -from_ one segment of society to another. Iley do not represent the monetary value of resource lbsses caused by smoking and are not benefits or costs to society as a whole .:.These transfer pa;!ments-can be important economic values in the social decision-making process and assist in determining the societal response to smoking activities. Although each of these authors makes an accurate economic statement, all recognize that the valuation of human life- a.nd health extends far beyond economics. [4] WhQt if the ACt economic i7npOd of C3gQrme SlnokGng? A broader analysis by Schepiing ;1957) and Warner (19$7) fulfills an important need identified _ in a review of the economic literature on_cosu of smoking (Shultz, 19RSa=). :a Warner's (1987) depiction of health and-economic outcomes-of a=tobacco-frce society, the net economic impact of a tobacco-f;ee society is desenbed as unclear. Econometric modeling studies bave suggested that, in the absence of extensions in-the age-of retirement and mechanisms for financial support

of the retired pcpulation, movement toward a nonsmoking society may be recessionary in the long term (Richter and Gori, 1980). Shifting and partially- offsetting economic effects may occur during the next several decades while smoking rates dec!ine. - At this -titne, however, a tobacco-free society has not been achieved, and the economic burden associated with disease due_ to_ lifetime tobacco use is real and calculable. The net economic etlect of cigarette smoking in the future is_ speculati+e. Interpretation -and-iJse of the Fstimates Smoking-attrybutable disease impact estimates should be described sn-scienti6c, government, and public foeums- as a z;ustee of _related measures that assess the health and economic conse- _ queacea of cigarette smok:ng. It is appropriate to apply the data_ as general benchmarla; they do not represent precise point estimates. With SANLAEC II, these multiple measures are -- tadored to local conditions and experience, but they do not account for all health and economic eHects. Tbe generation of e:itimates of the disease impact of-smoking may be accompanied by- uncritical use of the data. Warner (1987) as3at7s the dogmatic and uninformed use of emnomic- calcuiations by antitobacco activists: - .. the esseniiai question is not the precise magnitude of the social costs, but rather their qualitative meaning. As they are used by some antitobacco activists and legslatorla lobby~ng to restrict tobacco use, their intended implication is clear. tobacco use is imposing an economic burden on society thst is avoidable; smokers are imposing costs or nor,smokers _. Smoldng is costly in terms of productivity losses. The per person-lifetime medical costs for smokers may be greater than (Izwit, 1983), equal to (Leu and Schaub, 19$?), or less than (Schelling, 1987) that for nonsmokers. However, whether smokers cost nonsmokers money, or vice versa, is unresolvui. The public re.spo= -to the epidemic of smoking-related diseases involves individual behavioral change and modificacion of the e~nvi,ronment= Smokitsg-attnbuiable disease impact estimates are developed in a pubU health context in which a value is placed on- living healthfully to full life eapectanry; in this crznteatt, cigarette smoking is perceived as a threat to the collective health of society. As with other scientific statements, particularly those r eleased under the aegis of a national- or State health agency, disease impact estimates are a form of argument and have a political as well as a scientific basis. The technology of SA1:IIvMC II software enhancea tbe credibility and perceived authority of disease impact estimates.

We alert rr.~earchera-and- policymakera to the possible misuse of SAIvV~IEC II disease impact estimates by misinterpretation,-overinterprctation, failure to appropriately qualify the findings, or overartension of the authority of these data. Disease Impact Estimatioy as a Health Policy Interveatiog Smoking-attributable disease impact estimates may al3o be used to support regulatory and economic interventions (Sbultz et al., 1986). Economic incentives and disincentives dit•ectly reinforce healtb-related behaviors and Muence the-environmetlL For example, increa= in cigarette excise taxes provide direct economic disincentives to smoking; by repeatedly increasing cigarette prices in excess of inflation rates, the increasing share of disposable income resluired- to-mai$tain-thesmokibg habit may cause smokers to reduce=consumgtion or may reinforce a prior decision to quit. Most importantly, such increases may discourage some adolescents with limited financial reso:uces from-smoking (hcwit, Coate, and Crrossman, 19$1).- Excise tax proceeds-may also provide a funding source for nonsmoking programs. Disease impact - ` estimation has in fact been used in the justification of excise tax legislation (Shultz et aL, 1986). Nonsmoking legislation (tobacco excise tax incre ases, clean air act legislation, and appropriations- for nonsmoking programs) provides an incentive for behavioral change (i.e.; the perception that nonsmoking is endorsed by government as beneficial for its citizens) in addition to the specific provisions of the legislation itseL`. Tbus, -disease impact estimation is an intervention that can influence decision-making by public health professionals formulating a-nonsmoking plan, by legislators considering the merits of nonsmoking legislation, by employers charged with decreasing corporate health expenditures, _ and by-bealtb program managers directing= nonsmohir,g programs (Minnesota Department of I'iealth, 1987). Conceptual Issues for Cost-of-Illness Studies Prevalenee•Based Approach. -Prevalence-based cost-of-illoess (COI) methods estimate tae_ direct and indirect econom:c burden incurred in a period (the base period)- as_ a result of the prevalence of 'dssease_ in the-current year. included are the rosts in the base year or in any time prior to the base year. Prevalence c osts measure the value of resources used or lost during a spzci; ed period, regardless of the time of disease onset. 'Ibe present discounted _ value of future losses due to mortality are also calculated. The conventional methodology attributes future losses to the year in which the death occurs. Most cost-of-diness studies employ this approach, and it is-used here. Human Capital Valuation of Llfe_ Economists use different approaches for valuing human life. One is the human capital approach, refined by Rice, Hodgson, and Kopstein (19&5); the second is the wilingcess-to-pay approach, first proposed by Schelling (1968) and Kishan (1971). Tle human capital approach has been selected for SAN>;:~iEC IL In this approach, an individual's value to society is his or her production potentiaL If markets are functioning well. individuals will be paid a wage equal to the value of the output they produce. Thus, the value 10

of a person to sos-iety- can be measured by his or her earnings, and the economic value of G.fe would then be- the future earnings stream.- This stream of earnings is discounted by using a discount rate that reflects the tradeoff between the value of a dollar today and a dollar tomorrow. op~ The human capital approach is the most commonly used approach for valuing human life (Itice, Hodgson, and ICopstein, 1985). It has the advantage of relying on data that are readdy avai7able. It is relatively easy to apply and is- useful for answering questions about the economic burden of a disease for a specific period (e.g, strokes in 1985) and for analyzang cost-benefit (e.g., determining tho-czst savings of a specffic procedure or intervention program that reduces tllness andlor improves survival rates~ Studies that tue the human capital approach estimate the direct and indirect costs of specific categories ofiZlaesseL - Direct costs are those for which payments are tnade; and indirect costs are those for which resources are losL Estimates of direct costs are-usually straigbtforwarri They include txpenditares for medical care, including hospital and nursing home care, services of medical professionals, drugs, and appliances. The measurement of=indarect costs ipvolves- the estimation of the value of human Ufe, =which raises conceptual anddata -issues. This measurement uses presenF discounted values of -earaings by age and sex - The measure of output loss is earnir3gs; adjusted for wage supplements. This valuation relies on the assumption that earnings reflect productivity. Common practice imputes a value to bousehold- work performed by men and women and adds this value to earnings to - obtain a composite m=e=an present lifetime earnings by age and sex - The human capital approach has some disadvantages Because it values life by using market earnings, it yields very low values for children and the retired elderly. It also undervalues life if labor market imperfections exist. Also, wages do not reflect t.Fue abUities. For example, women and minorities are often paid a lower wage than white men are in comparable jobs. 'Ilus, men are more highly valued than womeh, white pcrsons more than black persons, and middle-aged people more than the young and elderly. In addition, some individuals may-have low productivity as a result of -a particular sllness. Ideally, one would ldce to- adjust earnings for such factors as race-and sex discriminatioa- and W health.- In practice,-this is extretnely difficult to do. Psychosocial costs, such as pain and-suffering,- are -components of the burden of illness omitted from the human capital computation of indirect costs. The human capital methodology does measure an important component of the cost of disease, and it should be evaluated on bow well it does :o. Morbidity destr,oys -labor, a valuable- economic resource, by causing persons to lose time and effectiveness from work and other productive activities, pushing them out of the labor force completely, or bringing about premature death.- Disease thus creates an- undeniable loss to individuals and to society, and it is this loss that the human capital approach attempts to meaazure (Hodgson and Meiners, 1982). 11

Estimation Issues for Cost-of=Dirtess Studies - In principle, COI studies use standard procedures for estimating direct -and iodirect costs. -'Ibe specific-estimating orocedures;-howeyer, vary according to the particular d.isease and tbe- available sources of data. Several issues related to cost estimation are discussed below. These include valuing psycbosocial costs, reduced productivity, household services, earnings, nonmarket use of resources, discount ratet, transfer payments; costs versus charges, and nonhealtb sector costs. Psychosocial Costs. IIlness and disease are rcsponsble for a wide variety of-deteriontions in the quality of life-th.at are frequently referzed- to as psychosocial costs. Victims of illness and - disease, families of victims, and those who render care may all be affected. V'ictims may suffer disfigurement, disability, and the pa~n and grief of impending death. 'bey- and those around them may be forced-`'tnto economic dependence and social isolation, relocation, and other undesired changes ~ life plans ( Hodgson and. Meiners, 1982). Tbe combination of financial -strain and psycbosoc-lal problems can be_esgecially devastating. Some psycbosocial cb3ts, such as tbe- inluence of mortality on-the famt7y and its life cycle can be measured (World HealtF Organization, 1976;-Feichtinger and Hansluwka, 1977). In addition. consequences-of disiewe resulting iii dissolution of carriage, widowhood, and orphanbood- (Preston; 1974), and tbe-impact of changes in residence and loss of jobs ean-be measured. To a large extent, however, tbe-methodology for estimating psychosocial costsis-yrt to be -_ developed. Measures are required for the- impact of sickness on a persoa's sense of well=being, _ and on the well-being- of- his or her family and associates. Indicators must reflect reducrd- self-esteem, emotional problems, pain and suffering caused by loss of body parts, disability, social isolation, economic depcndence, impending death, and otherwise reduced qttaiity of life that often accompanies a di-sease- (Hodgson and Meiners, 1982' ; The difficulty-of quantifying psychosocial costs cause them-to be omitted from COI estimates,Constructing quality -of-life indicators and relating them to measures- of health status are major problems. In additicsn, integrating nonmonetary-informatiot: on quality of life with-dollar estimates for direct abd indirect eeonomic costs is- extremely difl•icult- VaL'dsting Household Services. Marketplace- earnings_ underestimate the loss resulting from women's Llnesse~s because some women are not in-the labor force. Men who are hon;ernatcers- are also not in the labor force. Tfne value of household work must, therefore, be added to earnings. Walker and Gauger (1980) produced the most frequently used estimate of-the v°alue of primary and secondary household production. Tbey z:sed data from-tirne and motion studies of bousekeeper€, multiplied by the relevant market wages- for various services- performed, to - estimate the cost of replacing a housekeeper's time with person-hours from the labor force. Valuation-was done on a task-by-ta-sk-basis. :be value of housekeeping services for women not in the labor force acd- for employed men and women were estimated. More recently, Peskin (1984~ used a somewhat different estimation technique. Za~e Walker and Gauger, Peskin calculated the mean time input for men and women who keep house and 12 ~ ~ ~ b~+ CG #ik

valued the specific tasks by using the pre i.ing wage rate for such tasla.- The -data were-then analyzed by using regression so that-controls for socioeconom-ic and demographic factors could be Qadc. Other studies of the- value of household production have been conducted, but each has its limitations.- Using tbe Walker and Gauger data as a basis, Brody (1975) produced estimates of the value of household production by full-time female homemakers. Brody ignored the household production of men and women engaged in market work. Murphy (1982)-calculated per person annual values of household work, based on the -hours _of work given by survey - respondents, and calculated national-averagas for men and women by controlling for differences between the sample distribution and_ population distribution for age, sM education, and urban_ residence. Howtvei}-Murphy did- not control for labor force participation, marriage, and household size. A recent unpublished review of these and other studies by Kenney (1987) conciuded that the Peskin estimates seem- to be the best available. Earnings. In cost-of-islnes.s studies, the appropriate measure of output loss for individuals is earnings, and the usual-measure-of expected earnings is_the ar:nual-mean earnings by age_and_ sea, adjusted for-wage supplements, such as employer contributions for social insurazl;.e, private pensions, and welfare funds. Rice, Hodge-nn, and Kopstein ;1985) used crors-sectio>3a1 prof•iles of mean earnings by age and sex to estirnate lifetime earnings. In- applying these data, they - assumed that the future pattern of earnings for-an average individual within a sex group will follow_ the pattem rzported--by the Bureau of Census during a base year. This model recognizes that the average individual can expect his or her earnings to increase with age and experience. - Tbe economic assumption behii€d the use- of earnings as a measure of the value of foregone output is_that individuals are paid the value of their marginal product. Because some subgTOUps- are discriminated ag -ainst in employment, actual earnings may be less than the value of -output. Tbus, mortality costs-for diseases that-primatily affect women and- blacks may be under- estimated. -'The indirect costsefor diseases =that affect a-population with above average productivity wil} alsa be underestimated if mean earnings are used to_ measure foregone output. T`ne use of_mean earnings for people who suffer from diseases that affect certain socioeconomic groups may be -incdrrect.- Perhaps it would bc-useful to caiculate human capital ti-alues by orc:upatioa and_ level-of education. Human capital values rrould be more accurate for some_ groups which_could be important, for example, for estimating COI related -to occupational exposure. But for tiiseases-not related to occupation or level of education, values for broadly defined groups, such as men and women at a given age~ may be all that are required. Further, while age, race, and -ses:-can generally -be-deteraiined for- persons with -a given disease (such as cancer), information=on-education and occupation are-not readily available (Hodgson and Meiners, 1982). Nonmarket Use of Resources. Whde- the health-care system can meet some needs of patients with chronic- disz~, -a large share _of the burden of -caring for such patients falls on relatives, friends, and- community volunteers who receive- no reatuneration_ for their essential services. When measuring the amount of resources that society devotes to health and long-term care, we generally confine ourselves to the dollar value of services purchased in the market- place, such as nursing home care and home health services. Tlc size of the informal care

network-can, however, affect the leve: of health expenditures. if individuals become unable or unwilling to devote time and resources to-carring for family and friends, many of the services provided informally might have to be_pnrchased. If the availab>7ity of informal_ caregivers vras_ reduced because of reduced ia~y size or increased participation in the labor €orce by women, we-might welf experience an increase in expenditures for nursing-homes or home health care (Paringer,-1985). Few studies, however, have examined the issues and -estimated the -=ts of informal care services, such as household chores, personal care taslss,- and accompanying the impaired person to the doctor's office.= _ Diseonnt Rates_ The calculation of the present value of expected lifetime earnings taises questions - about discounting and choosing the appropriate discount -rate. From the economist's viewpoint, the arithmetic sum -of lifetime earnings- overstates the present economic value of an individual's earring power. IDeterffiining -the present- value_ of the future earniogs stream is the correct way to mew uae_ eaonoanic-value-over_a period of time; discounting cenveru a aream of earnings into its_ pre3ent value. Economists agree that-compar•ison of streams of earnings over varying tirnespans should employ the process of discounting and that the benefits_ of public projects for which COI- estimates are used should be disoouuted at the social-rate of time prefer-ence.- This rate correctly states society's preference for present-versus future -ccr.sumption.- Unfortunately, -tht social rate of - time-preference is unobservable, and the actual value is uncertain. Hodgson _and-Meiners- (1982) discuss the discount hate in-detaD and recommend that investigators use at least 2,-and preferablY-3, discouac_rates ranging from 2Selp-to 209c. 'Ile higher the discount rate, the lower the present value of sa given stream =of earnings. With a high discount rate, earnings far into the future-yield -a relatively small present value. Conversely, lowering the_ discount rate increases the present value of futu.*e_ earnings. PoGqimakers must know whether cost estimates are appreciably affected by alternative discount rates. -COI estisnates from two studies for the same base period, whether for the same illness or not, can only be meaningfully cgmpared when the same- discount rates are used __ Consamption. _ Some researchers have- questioned whether the- cost of morbidity and mortality due to illness is an individual's output or an individual's output minus his or her consumption (Weisbrod, 1961). Most studies_are concerned with tht COI to society. _'Ibe individual, not just the output be oF she contributes in excess of eonsumption,-is- valued-by-society. Economists today getieraL'y agree that consumption should not be deducted Xisban, 1971). Costs versus Char ges. For measuring Airect-costs, charge data are more frequently used than cost data, despite the fact that charges do not necessanPly reflect resource use. For example, hospitals often charge less than cost for some services (e.g., maternity beds) and substantially more than cost for others (e.g., laboratory tests). Charge data are generally more accessible than cost data; most services have fee schedules (except for services of volunteers, famlily members, and friends). Some institutions (such as hospitals) have cost-to-charge ratios that can be used to approximate costs from charge data, but such a ratio is unavailable for many other services, such as physicians or home health care. 14 Qy

If charge data for some services- are converted to -: osts and others are not, totaf cost -calculation will be inaccurate because of the mixture of data in different units. Factors such as -reimburse- ment methods can-affect the detcrmination-of-costs, as illustrated by the implecnentation of Diagnostic Related-Groups under Medi,:are. - Jv€ost researchers use charge data in cost studies because of its accessi'bilitk and the lack of proven alternatives. Transfer Payments.__ 'Jsing- the human capital method, costs of illness and disease ais the value of reaourcas ;med and resQurcev lost due to morbidity and mor.ality. Direct and indirect costs are losses -that_v+ould not occur if illness and disease were reduceil. Transfers shift control over the use of- resources; they _take _ resourees frota one segment of society and give them to another. Transfers may alter-the allocation of resources among competing ends but-r~rre not a use of resources ia and of the-mseh~es (Hodgson and ?ricinzrs,-1a82). Transfer payments,-such as public aid and disability payments, and-saxea are not costs of illness and disease and- shoold not be added to direct and indirect economic costs. Taxes will already have been counscd in- indirect costs, and transfer payments are smnply a reallocation of income from one individual (e.g., the wage earner) to another (e.g~, the disablcd j. Although these transfers are a cost to the .uage-earner_ in the for-m of a reduction in dispo.sabld income, hiv or her loss is another's gain, and the net cost to 3ociety-in terms- of resources used (and thus, - unavailable for other us----) is zero, except for cosi.; inmirre_d in-opeiating the system that affects the transfers.- Tle addition of transfer payments to direct and indirect costs of Mness would result in double- counting. 15

Chapter 4 Smoking-Attributable Cost-of-fjlness- Studies: Review of the Literature Cost-of-Illness Studies -- Fstimation of smoking-related _econamic costs is _ based on the prevalen-ce_-based methodologies for estimating the cost of illness (COi} lbe-earliest attempts to estimate-national hea3th-care expenses date frore about-1950, and the metbodolog,y-was formalized and upgraded by Pice and _ colleagues tbrough-.multiFple itsrations during the last three decades (Rice,- 1966; CCooper and _ -ttice, 1976; Hodgson and K,op3tein, 1984;-Rice, Hodgson; and iCnpstein, 19&5). - - Cost-cif-Illness GttideUnes COI calculations are aggregated at the level of major -diagraostic categories and include estimates of both direct mea:ca: care costs and indirect costs. - Direct costs are the ~ts af inedicai-care for the prevention and diagnosis of disease and the treatment and rehabilitation of persons with disease. Direct cos;s include personal health expenditures in eight cost centers: hospital care, physicians' services, dentists' services, other professional- services, drugs, eyeglasses and appliances, nursing home care,-and other per3ozFal health care. Direct costs also include support (or nonpersonal) costs for research, public -health astiities, medical faci~.itie s.ities construction, and program administration. Indirect costs result from output lost because of ces.sation or reduction-of productivity due to_ death or disability. Tbe typical measure of indirect costs is lost income. Calculations of -indirect costs typically account for age- and sex-speciific life expectan,:ier patterns of earnings at different ages, labor force participation rates, and the imputed value of housekeeping services. Two types of indirect-aoats are distinguished Indirect mortality costs are the costs of lost income and productivity for persons who die prematurely from t7lnesrs, Indirect morbidity costs are the costs of lost income and productivity for persons who are disabled by di=aease- Systematic COI guidelines were defined by the Pub!ic Health Service Task Force on Cost of fllnes.s Studies (Hodgson and Meiners, 1979). 'Tbe guidelines identify five categories of costs originating from diseases and-otber medical conditions: (1) direct costs of medical care, (2) indirect costs resulting from losses of output due to -morbidity and premature mortality, (3) nonhealtb sector direct and indirect costs, (4) 3ocial costs and decreased quality of life, and (5) rippling effects of cost increases throughout the economy. ibe-consensus developed by-the Task Force indicated that C9I studies should, at a minimum, include direct and indirect-health sector costs. SA-.iNVvMd II software calculates smoking- attributable direct and indirect health -_ sector costL 17 t1~ ~

National Calculations of Economic Costs Attributable to Smoking:- United Swes Early work by Hedrick (1971) estimated smoking-related costs for the United States at SS3 billion, an aggregate figure including direct health-care costs pius morbidity and fire costs. This figure was crudely derived frona-a Canadian study by mult6plying Canadian costs by a factor of 10, tbe-ratio of the respective gross national products. Ibe earliest esti.-aates-of smoking- related costs were critiqued by Luce and Schweitzer (1978)-wbo noted tbe imprecise analytical basis of these figureL Tbe three -estimates -cited by these authors were those of-Soper (1472) of SS.3 billion-(1966 dollars), which included both direct-and indirect cgats and used the Canadian data from Hedrick's study; WMIa.ms -and Justus (1974) of 54.~3 bilfion (1970 dollars) in d.irect- health-care ~ts; and Walker (1974) -of ~11-5 bdlion (1974 dollars, in tiirect hath- care- COts. Luce and Schweitzer calculated tbe-tu'sset of costs attributable to smolr.ing by using worldwide percentages of all° circulatory; neoplastiq and respiratory diseases attributLle to smoking (based on Boden, 1976) and applying 19172 cost estimates to_tbem (Cooper and Rice, 1976). -Adjusted- _ to 1975 dollars, the estimate was S25.9 bi7lion;-this total included $73 billion in direct costs, $123 billion in indirect mortabty costs (the cost of income lost due to prdmaturt death), $5.9 billion in indirect morbidity costs (the cost of income lost due to disability from nonfatal smoking-related disease), and $0.2 billion -in cigarZ tte-ibuited- fire losses. In -a subsequent article- (Luce and Schweitzer, 1978), the -same-miethodology-was used- and inflated to-1976 dolla.z: which produced an -zstimatz of $27,5- billioa.- Woife (1977) ,produced a smoking cost estimate of $-18.9 billion (1976-dollars), a figure that - included- $7.1 billion- in- direct health-care costs, $7.7 billion in indirect mortality costs, and $4.1 billion in indirect morbidity eosts. Kristein (1977) calculated the cost of bea`y-cigarette smoking- (a _pack or more per day) by- using -tvwo strategies. First, using estimates of excess medical use, excess absenteeism, and premature mortality, lr:ristein estimated smoking-related costs at S203 bMom (19?5--dollars); thic-included direct costs of 55.2-b:;lion, indirect mortality costs of $12.0 billion, and indirect morbidity costs of $3.1 billion. He validated this estimate against a separate calculation by- applying smoking-attributable fractions for- respwatory; circulatory, and neoplastic diseases to Cooper's and Rice's (1976) cost=data- to produce an estimate of $20.8 billion. Kristein ard-Grove (197&) translated these large-dol]ar figures into colloquial terms: each cigarette was respoasible-for 135--: enis in direct medical_ -costf- and-3.15 cents in gross national product loss (1978 dollars), the equivalent of 90 cents per pack sold. In the preface to the Surgeon General's landmark report on smoking and health (U.S. Department of-H-ealtl, Education, and Welfare3 1979), former Health and Human Services Secretary Joseph Califano cited -figures for-smolang-related costs at 15 billion to $8 billion in medical care expenditures_and S12 billion to 318 billion in- lost- productivity, lost wases,- and absenteeism. Warner (1983)-inflated the l,uce=and Schweitzer (1977) estimate to 1983 dollars and estimated a total smoking-related cost o€ g49 billion - $15 billion from medical care resourres and $34 billion from productivity losses. -'Ihese figures were placed in context $200 per capita annual social cost of smoking and more than $100 in excess health insurance and-taxe< per working adult. 18-

National smoking-atuributable cost estimates we-re enhanced by Rice and Hodgson (1983) who used 1980- national COI data (Hodgson and Kopstein, 19$4; Rice, Hodgson<_ amd-1Cppstein, 19$S). Rice used these 1980 data to estimate- smoldng- costs to the -nation. 'Ihe method improved upon the scheme of Luce and-Schweitzer by using sexspeci[jc sff,olang-attnbutable- risks for- individual dBcase codesand then summing stnok;ng-attrtbutable deaths across all - diseases witl~ a di=agnoati~ category. The mortality ratio (str.oking-attn''~utabte deaths to tot~f deaths) for each diagnostic category-wa-s used-as a multipliec to determine smoking-attributable costs for the categorY. Costs of smoking-attributable disease in 1980 were estimated to total $422 billion. This in.cluded_an estimated $16.1 billion from direct healt._h-care costs (73%-of the national total of 5219.4 billion). Thiv alsio included $19.2 billiot;_ in indirect mortality costs and 56.9 btllion =ftotnt-indirect morbidity costs. 'Ibe Office of 'I'echnology Ammsnent (OTA) (1985) calculated smoking-attnbutabie costs by using the method of,Doll and Peto (1981) appued to American Cancer Society dat,a_fro€n the 1960s and 1970s for= -one mlion Americans. OTA staff consulted with aa expert-committee of - health economists at;d- epidemiolog~sta in order to develop a consensus meth-odology for performing these computations. In 1985 ddollars, the middle estimate for direct health-care costs was $22 billion, indirect lost productivity costs were $43 billion, and total costs were $65 bilbon. The confidence inter°~al was yery large, and the range for- total stno~cing-attributable costs was from $38 b'L~-lion to $95 billion. National direct costs were equivalent to 5.72 per pack sold (1985 dollars), and inn-direct costs were equal to $1.45 per pach for a total of 5217 per pack (@TA 19$S).- This study also estimated smoking=attribvtable raortality at 314,0M deaths in 1951 or 5,300,000 year -of potential life lost (1,200,000 years prior to age 65). 1be metbodol4g,v for costs of smoking has-been -furtber advanced by Rice and colleagues (Rice et aL, 1985). These -inyestigators estimated loss of life attributable to cigarette smoking at 270,000 deaths per -yyar, the eguivaleut of 3,900,000 years of potential life lost.- S€uoking- attnbutable indirect mortaliry costs were calculated the same vvay _ as in the carlies report (Rice and`Hodgson, 193.3), which yiclder -an estimatz of S 16.8 billion in 1980 dollars (fewer smoidng-related diagnboses were included in the 1985 paper). Direct health-c$re costs were calculated by an entirely new strategy based on indices of_reparfed medical care utilizatio-n- computed from i;JatiOnai- Health Interview Survev INsIIS) data. This approach eliminated severx6l-major weaknesses in-eariier approaches 9vbere stnoking-attribu€able-coss-were estimatecd based on propor4ionase mortality due to cigarette smoking (d~tcussed in Shultz, 1995a). Using ratios-of hospital da}~ and physician visits for ever smokers to never smokers, these investigators produced an estimate of 5;4.4 bdlion in direct medical care costs due to smoking. Estimates w-ere based on neoplastic, circulatory, and respiratory diseases only. F;nally, data from the NHIS for work-loss days, -disability day=~ and the percentage of the population unable to work due to disabling dlness-wer-e used in a similar fashion to the direct cost method to estimate smoking-attributabie ibdirect tnorbidity=c6sts at $7.4 billion. - Relative rates of disability and work loss for ever sm-okers and never smokers were used to calculate the smoking-attributable fraction of these costs. Thus-€he total estimate of smoldng-attri'butable-casts summed to 538.6 b0on (1980 dollar3) C1T Q') 19_ aF T~

National Catculations of Economic Costs Attrfbutable-to Smokinp: = Other Countries A Canadian study conducted by Forbes and Thompson (1983) estimated smokin-g-linked_disease costs during a lifetime, including--tbe costs of fetal complications and e-hLdhbod-orposure to passive smokdng. Direct cost estima"- were-e-quivalent to 15% of male and 10% of female per capita health-costs in Canada. The-authors used -a methodoiogybascd ot:- morbidity ratioos for dise.astes-related to smoking-at each of six eras of the lil'espan. They constructed a hypothetical nonsmoking population and determined the _excsas inpatient hospital utalization for cigarette smokers. Annual emw sm- oking-related costs were-equiv,augnt to S36-per male and $29 per- _ -female (39&U dollars)z Indirect costs rvere not estimated. A second Canadian study (Collishaw and Myer€, 1984) mam^ined ea~ smoldng-l.'nked di-n= costs by cost oentzr,-3tsch- as hospitalization,-:ather-than by diagnosis sategory. These authors also included indirect costs and-property losses from cigarette-ignitcd fires. Total costs - attn'butabie to smoking exceeded-17Q9' of the gross consumer expenditure for tobacco products. Conversely, a Syviss study (Leu and Schaub, 1983) indicated that-higher annual costs of medical utilLution by smokers were compensated by the ionge_r lifetime_ of medical utilil'uation by- __ nonsmokers. Nonsmokers Gve longe-r- (a life- expectancy increase of 4.1 years at birth) but- use medical services 6e;a04y in their last years of afe.- Becau.se-of these reciprocal effects, lifctiane _ medical costs per- individual were -indistinguishabl_e between smokers and nonsmokc:s. These investigators modeled the concept that smokers-are at increased risk due to behavioral factors other than cigafctte'smoking per se, This study did not estimate the indirect costa- associated with- smoking, a substantial figure based on the -decrement in life expectancy. - - State Calcnlatlons=of E:ronomic-Costs- Attributable to Cigarette Smoking =- CJI methodology has been -adapted to State-level calculations of the costs of smoking. -Follo~ving Rice aridliodgson (1983), the smaking-attr~utable costs to the State of Minnesota were originally calculated in 1984 (Minnesota Department of Health, 1984; Dean et aL, 1985). In 1983 dollars,- cigarette smoking cost Minnesota S.S2- per pack sold in direct medical cosu and an additional S.66 per pack sold in indirect mortality costs. Cady (1983} estimated - -- - smking-attnbutablt• direct costs to be $1.10 per pack sold for Ivf a~achusetts. Following the - Minnesota methodology, calculations for the State of Washington estianated-sm~oldng-related direct costs at 5.78 per pack sold in 1981 (Pauloa,i, 19g4). - Corresponding figures for the State of Florida were 5:6i per-pack in direct costs and $1.02 per pack in indirect costs (Sacks, 1985). Medical care costs attributable to cigarette smaking were estimated at S27Q nu"Iiori for the State of Kentucky, representing 8% of total direct costs (Hinds, 14$E~ 1be-State of Colorado and New York City were the-first State and local governments to use microcomputer spreadsheets -for=computiQg State`smoking costs based on-tbe revised -_ methodology of Rice and colleagues (Rice et aL 1985). Both used the first version of the Nfinnesota-spreadsheets (Shultz, 19SSb), the immediate predecessor of SAMNMC software. Colorado estimates (1.gS2 dollars) were S2SS million for direct costs (S.66 per pack) and S4S7 nu7Iion for indirect coats (S1.2b per pack) (Colorado Department of Health, 1986). For New York City, estimates of the average annual dsease- impact of smoking based on data for 1983 ` ~ ~ ~ ~ ~

through 1985 indic~ted that more- than 11,000 New York City residents die each year from smoking-attnbutable-disesse` for an- associated loss of 170,t>00 years of potential life. The price tag (1994 dollars) was estimated at S1.0 billion in-medicaj-care co3tsF '41.0 billion ;a indirect mortality costs, and- $480 mdlioe in indirect morbidity costs (ShUltz, -1986b). -ar-d distributed by the SHMUAEC softw-are-(Shulti, 1986a) was completed im August 1986 lvfianesota Oepartmoht of Health in the fall of 1~-to-seversl users. North Dakota vaas one of the first States to compde a r~,oort=by using SA,'~*~C calculations-~v€cOortough et al., 1986). New York State followed suit (Smith et a1, 1990). In 4997, the Office or: Smoking_ and Health (OSH) distributed SAM.~fEC to ttll 3t,' States, - Puerto Rico, add thd_Distai:t of ~lur~oia. A series of State te_oorrs r~nsd epidemioiogy newsletter articles on-thm State calculations has-oppeared, The States includeAlabama (Alabama Department-of Public Health, 1987) , DDelaware (BreukelmM-Zeit:z, Novotny, 1488),- Maine (Maine Bureau of Health, -1988), Massachusetts (Shulu and Oonnolly, 1989), Puerto Rico (Dietz et aL, -in press), Teras (Texas Department of Health, 1987), Yerr•tont (VerMont __ Departmenr of Health, 1987), Washington (Ooldbaurn et aL,-19fi9), and Wyoming ;'~Vyonis:g Division of ~eal-th and Medical Services, 1988). OSH compiled Statc -by-State data into a chapter of its biennial report to Congress CJ.S,Departineat-of Health ard Humau Setvicet, 1990)' The aggregated State costs were as- follows: direct morbidity, 523.6 billion; -iridirect- morbidity,- 510.2 billion; and indirect mortality, 3i7.$ billion. Total smoking-attributable costs were estimated at $52.3 bdlioa for 1955. ~_ Econoriie Costs to the Individual Attributable to Cigarette Smoking -Tbe costs of smokin~ over the li.`etin<e of an individual ca;~ be estimated. ":'tiis prospective, - incidence-based approach is singularly suited for estir--jating the impact of primary ireveetion efforts (Hartunian et al., 1y"-30). An analytical_s~,dy by Oster and colleagues (Oster et al., 1984) represents- the most sophisticated applicatioa of this method4logy to the- costs of c;$arette_ smoking. Our-estimates- of the costs 4f sm-olcing are -expectedi values in a statistical or mathematical- sense.- "Ibey represent the likely average oatcome of a game of health roulette tha3 evegy smoker zither- kstowingly_ or unkno,*ingly plays._= These estimates represent an am ount-that -eve" smoker should ecpect- to km _ Of course, a smoker who is lucky enough not to develop a serious -Mness ovee_ his or her lifetime wil;-not bear signi5cant costs as a result=of smoking. Alternatively, a smoker who does eventually develop a- serious disease will incur costs far in excess of those that arc expected en average. Tbese investigators exams,ed-the major disrases related to smoking:- coronary heart disease, lung can: er, and chronic obstructive lung-disea.se. = Smokers had a higher risk ®f d~-veloping any one of these diseases in any given year than nonsmokers did. Medical costs for-treatment of these-diseases and the -lost income from death or long-tec~n disa3ility were estimated. From these calculations, Oster and colleagues -estimated the expected lifetime- cos ts of smoking to- the individual, by amount smoked, in present-valued dollars for persons of different- ages. 21

Cost Offsets: Extended Life- Expectancy for Nonsmokers and Former Smokers Calculations by _ Richter -and Gori j1980) challenge bealtb-professionals committed to-smoking controL -Using-ecoc-omettic models, these researchers found that successful smoldng control and ;ucz=ful health promotion wW produce positive economic outcomes in the short run. But ultimately, if no policy changes are made in the-age of retirement and =in -the mechanisms for -tbe fina,ncial supponof the :etired population, tbe effect of smoking control could be -- recessionary: iJnde; th.i.s theory, Social Security and pen=ion plans as prrsently eoststituted could not easily support-an increase in QIdEr retired adults with an extended life expectat:,. These issues have been extensively reviewed by noted authorities in the field (Rice et al., 1986; Warner, 1987; Scbeaing,,1937). -A more extended discussion has bee.n =presente€i in G'hapter 2 of this voluma_ Summat7 The short history of costs -of smoking analyses=:s marked by di-verse-approac6es of increasing sophisti-; ation. Computer software for performing stnolcing-attr:3utable- disease impact estimates has been used by several ;urisdictions throughout the world. Use of this-software has - acceler ated improvements in -metb-odology, bealth data systems, and software- tools.- _ Air

k Cttapfer S - The Disease Impact Measures Table 5A presents the measures of smoling-attrtbutabie -diseas4 impact -calcu!ated by SAMMEC 13 softwate. Table SA Smolsing-Related Disease Impact Measures SAMWC U SoPiwa€e - Epidemiologic Measnres-_ A. Smoldng-atYributable fractions (SAFs) B. Mortality-related measures 1. Smoking-attributable mortality 2 Smkiag-attributable years of potential life lost (YPLL) - 3. Age-adjusted smoking-att:,butab!e mortality rates 4. Age-adjusted smoking-attributable YPLL rates Health Economics M-easnres A. Direct health-carc costs 1. Hospiw costs 3. - Physician fees - 3. Nursing home costs 4. Medication costs 5. Other professional services- B. Mortality (indirect mortality costs) C Morbidity (indirect morbidity costs) D. Tota,l and per capita smolang-attributable costs Definitions of Smolang-Related Disease Impact Measures Smoking-Attributable Fractions: The mardmal proportion of deaths or-c.asep of disease causally related to cigaietm smoking. - According to Last (1988), 'the attributable fractiorn among the population is the proportion by which the incidence rate of the outcome in the entire population would be reduced if expasure were eliminated' 23

Smoldne4ttributable Mortality: For each smoking-related diagnos;s, smoldng-attributable mortality is computed as foliows: [1Vurnber of Deaths z.Sr4.9 for each 5-year age group for males and fema;es. User-supplied- mortality dats are incorporated into _the-calculation. SmldnZ-Attributabie Years of Potential Lift Iost This -measure includes person-years of life lost, either to a 3peciGc age (65 or 7S) ) or to full life expectancy, for all deaths attrnbutable to cigarette smoldnj: User-supplied mortality data are ~corporated-into-the calculation (Centera for Disease Control, 19V). -You can select the desired YPLL measure and supply life expectancy data specific to the group -under study: For eacbh diagnosis, smoking-related YPLL are calculated' as fo;lows:- Weathu i -SAF x YPL-L] fbr each 5,eaa-age-group for males=and-for - females. Age-adjusted smo]dng-att-Fbutable mortality and YPLL rates are the rates of these 2 measures per 100,000 persons in the population-under bonsideratiom Age adjustment for the direct method -is performed in SA?ANi"tC H by using several standard populations: These rates permit comparisons of -the smoicing-attributab;e-tr:ortality-and -Y'' LL, among populations, such as those of individual States._- - - Direct Health-Carg Costs: Direct health-care costs are the costs for the-prevention and -- detection of srnolanj-relatrri diseases -and injuries, and for the treatment and r€babltation of smokers. Direct costs are typ;colly categoraed into primary cosi centers: hospitalization, - _ physicians' se:-Aces,-medication ccsts, nursing home costs, and ot6er professional services. SAMMEC II software estimates these costs-by using SAFs for annual bospital-days and annual - physician visits =applied to-estimated Ss.ate-level-_health-care costs for the treatment of persons with neopiastic, cardiovascular, and-respiratory dis-eases,.- Iadirstct Mortality {:osts: Indirect mortality costs are calculated as the foregone wages and salaries for pertons who-die prematurely from smoking-related causes. -'r.'he present value of future earnings by-sex and 5-year age group has been previously calculated for several-discount rates (Tkice et al., 1990). You can select the discount rate for the present value of -future - earnings.- For each diagnosis, smaldng-rel.ated indirect mortality costs are- calculated as follows: [Deaths X W x Lil'etiw -Earm:ngs] for each-S-year s~e group for males and for females. The estimate.of forfeited= lifetime earnings is the present_ value of -future earnings. User-supplied mortality data are- incorporated into the z;alculation.= Indireet Morbidity Costs: lndirect morbidity costs are thd costs of lost earnings and _ productivity for persons disabled by smoking-related chronic diseases. SA.*ANZC 11 softfvare estimates these costs by using-SAFs for work-loss days and bed-disabrti'ty days applied to estimated State-leve:l earnings, and it includes an imputed vaiue-for housekeeping services. _ Total and Per t:api3a Costs: 1'otai costs are the sum of direct health-care costs, indirect mortality costsa and indirect morbidity cosis-_Tttese estimates are presented by sex for ages 35 ~ to 64 and 65 or over. These summary costs are -also- apportioned to t6e population to develop ~i an estimate of per capita costs.- ~ A3 - 4 24

- Chapter 6 Smo1c.ing-Related -Diagttoses Epidemiologic studies have demonstrated_that cigarette smoking is a-prirma:y risk factor for a variety of disewes. Cur;ent smokers are at increased risk for multiple diseases, primarily in three diagnostic categories: -neoplastrs,-respir ator; disease3; a©d -cardiavascu:ar disaaw& Former smokers aw also at elevated risk when compared with never stnokers. The U.S. Sa:rgeon-General's r=ports provide detailed literature-reviews that summarize the epidenxiblogic evidence lialong cigarette smoking to tnultiple-cancers (J.S. Department of Health and Human Services, 1982), cardiovascular diseases (USDWAS, 1983), and respiratory disea_ses (USDHiS; 1984). The 1989 report presented detailed background iafo.*ma:6on on several relative risk estimates for smoking-related diseases (IdSDHiSs 1989). Because of the availability of these upertly researEhed-fcviewa, a thot••ongh-review of the epiderniologic literaware is not provided in this docurdent = The prevalence-based methodology used in SF~iME^ II software permits the inclusion of many- smoking-related° diagnoses. In SA?aMC II, you can expand -or contract the set- of diagnoses used in the calculation procedures'Ihe default diagnosis set loaded into SAAMIC U at - -start-up is derived primarily frotn-the 1989 Report of-tbe Surgeon General (USDHHS, 1989) (Table 6A). The default diagnosis- set- also includes several perinatal conditions linked to maternal smoking (MIcIntosh, 1984). - SAMMEC II- perunits the inclruion- of four such conditions '~ that have pa_*ticularly strong assa,-iations- with smoking (short -gestatiob and- lav birth weight, respiratory distress-sVadrome; respirator-, conditions of the newborn, and sudden infant death syndrome); McIntosh includes other diagnoses irn his analysis. Diagnoses in Table 6A-are designated by codes from the International ClassifFcation of ` Diseases, 9th Revision, Clinical Modit cyation. Based on the conventi ;ns in the literature on the disease outcomes related to smoking, a smoking-related diagnosis may be a single code or a range of codes.

Table 6A SmaltWg-Related Diagtsosis Set ICD.9-CM Code - L Adults: Male and female 3S to 8S # .gem old - - - Infestjoas Diseases 010-012 Gardlovascsdar Diseases - - 410-414 - -_ - - 380-398, 4u1-484; 415-417, 4?Q-429-- 430-438 440-44$ -_ _- - - - Respirstor7 Diseases- - 490-492, 496 480-487, 493 In inries 890-899 IL Cbtlda*_n: Male and female < 1 year old -Perfnatal Condations - 765 769 770 Signs and SJmptoms.- 798.0 Lo = _, - Diagnoses Respiratory tuberculosi3 Lip, onal cavity, pharymx Esophagus p`ancreac - Larynx , Trachea, lung, bronchus Cetv° uteri Urinary bladder Kidney, other- nriaa-ry CA-ronary heart disea.ce Other heart diseaie Cerebrovascular disease --Other arurial disease - - - Chron-Ac obstructive pulmonary disease Other respiratory disease - Burn deaths Short gestadon/low birth weight Respiratory distress syndrome Respiratory conditions of the newborn Sudden infant death syndrome AR

1 Chapter 7 Smokirtg=Atttibutabie- Fractions The critical calculation in SA1vL1viEC II is the smoking-attributable fraction (S.~ for each smoking-related--diag=s. 'Ibe SAF is the masimaa proportion of disease c-a3es-or deaths causally linked to cigarette smokang. Calculation of the SAF-requires two other measures: diagnosis -speci5c relative risk estimates a.od- smoking prevalence rates. The formula for-talculating SAFs is de*ived from the attrtbutable risk formula (L lieafeld and Li7ienfeld, MO). P (RR-1) - Attributable risk ~ P(F,~-~)+1 where p: -Frevalense of the risk factor RR: relative risk of disease due to exposure-to the risk factor The relative risk is the ratio of the rates of illness or death for exposed persons compared with those for nonexposed persons. For a smoldng-linked diagnosis, the relative risk is the ratio of - the mortality rate for current or former smokers- compared with that for never smokers: Mortslity rate for current or former smokers ~..., ._w~...~. _ Relat3ve risk - Mortality rate for never smokers- In SPJvQA-E-C II, sex-specific relative risks for current and -former smokers are those reported in the 1989 Surgeon General's Report (U.S. Department of Health and Human Services; 1989) (Table 7A). An expanded form of the-attnbutable risk forrttul4 accounts for the different levels of exposure for current srnokers and former smokers as indicated by separate-prevalence rates and relative risk estimates. ':lis formula is used in SAWMEC 1:1 to calculate the total SAF of mortality by- sec for each diagnoss=for the population under study. IP. + P:(RRJ + P3(R?)J - 1 Smoking-attributable fractioQ = where pr percentage of never smokers in group under study p,: - percentage of current smokers in group under study pz: percentage of former smokers in group under study (p, + P,(P-Rj + P3(RRJ) - 27

t?l2,: relative risk of death for current smokers compared with that of never smokers R.R_: relative risk of death for former smokers compared with that of never smokers S.~M]vfE%-- II permits the user to supply the smoking prevalence rates for current and former smokers (p in the SAF equ3tion) that are specific to the group_ under study. Prevalence rates for all races in the United States are available at start-up (TI able 7B). 28

- Tab1e 7A Relative Risk Estimates ICD-9-CM Code Olag_goaea Males Cr.~rrent Smoker Former Smoker Current Smoker Females - Former Smoker NEOPLASMS - 140-149 LiP,-ori€l cavity, phar;nz 27.4g 8.80 5.59 2.88 150 - Esophagus 7.60 =.83 10-25 3.16 157 Paacrez 2.14 1.12 Z33 1.78 161 ;.2.-7111 10.48 5.24 17.78 11.88 162 'i rach ea, lung, bronchus 22..36 9.36 11.94 4.69 180 Cervix uteri NA NA 2.14 1.94 18$ Urinary bladder 2.86 1.90 2-SS 1.85 189 Kidney, other urinary 2.95 -1.95 1.41 1.16 CARDIOVASCUTAR DISEASES - 3905-398 Rbeurnatic -heart d_isea.;e 1.85 132 _ 1.69 1.16 401-404 Hypertension 1.85 1.32 1.64 1.16 410-414 Lscbemic heart disease Ages 35 to 64 2.81 1.75 3.00 1.43 Ages 65 f 1.62 1.29 1.60 1.29 ~ 415-417 Pulmonary heart disea-se 1.85 1.32 1.69 1.i6 420-429 Cardiac arrest/otber heart 1.85 132 1.69 1.16 - 430-438 Cerebrovascular disease Ages 35 to 64 - 3.67 138 4.80 1.41 _ - Ages 65+ 1.94 1.27 1.47 1.01 440 Atherosclerosis 4.06 2..33 - 3.00 134 441 Aortic aneurysm 4.06 2.33 3.00 1.34 442-448 Other artenal disease 4.06 2.33 3.00 134 RESPIRATORY DISEASES 010-012 ltespi.ratory tuberculosis 1.99 1_55 2.18 1.38 48J-487 Pneumonia, 'Laluer.ra 1.99 1_% 2.18 138 490-492 -Bronehitis, emphysema 9.65 &75 10.47 7.04- 493 -A3thma 1.99 1.56 2.18 138 496 Chrosic airways obstruction 9.65 8<76 10.47 - 7.04 PERINATAL CONI3MONS• 765 - Short gestation/low birth weight 1.76 1.76 769 Respiratory distress syndrome 1.76 1.76 770 Respiratory wndatior+s-newborn 1.76 1.76 798.0 Sudden infant death syndrome 1.50 1S0 OTHER CONDITYONS 890-R99 Burn deaths m t9 ° Deaths among infants <i year old. - " Smoleing-attnbutable burn deaths detertnined from injury surveillance -studies.- m

Table _7B - - Smoking Prevalence Rates LiAited -States, AII Races, 198% Maies- - - Fi msles Age= G:oup Current Smoker Foamer - - Smoker- _ _ Current Former Smoker - - ° -Smokp 33 ta-54 - 34.5 34.9 29.0 20.2 GS aud ova 17.2 - 53.4 13.7 -19.8 18 to-d4 (Fcatales of Childbeari;,g Age) - 29.5 Sourrwa 19; Alatiot.a; t?sslLbiatESView Survey. OM-a a5 Smokin= and F1eaIt4 anp?6lMW drm Akio,

Chapter 8 Calculation of -Smoking-Attributable Mortality Smoking-Attributable Mortality: An Overview The most- recent- estimate of smoldng-attr'batable mortality was presented in the Surgeon General's 1989 report (U.S. Department of Health and Human Services, 1989). In 1985, -- 330,000 deaths were associated with 10 specific smoldng-related diagaoses. When other chronic diseases, fire-caused deaths, deaths due to passive smoking, and infant deaths caused - by maternal smoking were included, the total was 390,000 -deaths for 1985. The relative risks used in these calculations are those now used in SAMMFC II. Estimation of -Smoking-A"ributabCe MortaL'ty - Calculation of smoldng-attrbutable mortality requires current and former smoking prevalence rates for adults 35 years of age or older and for women of childbearing age (18 to 44 years). A.fttr you enter these prevalence rate data and tbe-mortality data for the smoking-related diagnoses, SAMAHwC II can estimate smolcing-attributable mortality. For each smoking-related- diagnosis, number of deaths (by sex) occurring within a 5-year age category are multiplied by the smoldng-attnbutable fraction (SAF) for that diagnosis, age category, and sex - - Smoking-attributable mor'ality = Number of deaths x- SAF Total smoking-attributable mortality is then calculated as the sum of smolung-attributable deaths for all age groups and diagnoses-for both sexes combined. - Comments on Smoking-Attributable Mortality-Related Measures - The priunary -L'mitation in the existing methodolr,gy is the use of a single SAF for mortality - among all age groups. Mortality data are available by age of death and may be readily summarized into 5-year age groups. However, accurate smoking prevalence rates are usually - not available by 5-year age groups. -Most often, a single summary rate or two separate rates (35 to 64 and 65 or over) are available. In addition, for- most diagnoses -related to smoking, - age-specific relative risks are not available. The SAF is calculated by using prevalence rate estimates and relative rysks; typically, the end result is that a single SAF value is multiplied by deaths across all age groups. -- -- For most diagnoses, relative risks associated with smoking remain stable across age groups. - For- such diagnoses, applying a single SAF estimate to all age categories is not problematic. In -~ contrast, for coronary heart disease (CHD) and cerebrovascular disease (CVD), relative risks -rb decline with age, approaching 1.0 (the value indicating no excess risk) for deaths after age 65 ~ r.~ 31 - ~

(USDHHS, 1983). Current.smoker prevalence rates also decline with age. -'~tce.u risks for - CHD and CVD decline rapidly after smoking cessation. These findings of relative risks and prevalence rates decreasing with age indicate that the SAF also declines with age. In contrast, - taottality from CHD and CVID increases with age, and about tttree-fourths of deaths from these conditions oecur after age 65. - Thus, wriile number of deaths from CHD and CVD increases rapidly after age 65, the proportion of these deaths attributable to smoking drops markedly ., SPF led to an within this age brackeL In past calculations, applying a single suttim. ry overestimate of smolang-attr3butable deaths from CHD and CVD. - 'Ibe calculations presented in the Surgeon General's 1989 report (and lience, in SA~vi~C U) account for different age group-speci6c risks for CHD and CVD: For CI~-and -CVI), SAI~MC 1I calculares-separate Sf~'s for ages 35 to 64 and 65 or over, by using d-iEl:erent- values for preva7ence`rates- and relative risks. This procedure largely corrects for- previous - overestimation. - - - - Smok.ing-Attributable ?v1o-ptality Rates- - To calculate stnoking-attnbutable mortality rates, population data for the group under study are needed. Using computed numbers of smoking-attributable deaths for the group under study and the population data you supply, SAIvINMC Il produces age=adjustet.+ smoking-attributable mortality rates per 100,000 persons. SAMMEC U allowz you to select race-specific U.S. population data as the standard population. Alternatively, you can enter population data for another reference popiaation.---Calculation of age-adjusted rates permits comparisons between groups. Age-adjustment corrects for any differences in age distnbution between the groups-so that the comparison can be made as if the two groups had the -sarne age structure. ~ Vt ~ CD N 32 1~+ CJ1

Chapter 9 Calculation of Smoking=Attribu tabir= Years of Potential Life Lost - Smokiag-Attributable Years of Potential Life Lost: An OYerview - In addition to -causing excess mortality, cigarette smoking is associated with premature loss of life. Snoldng causes more premature deaths than any other health-risk behavior in the United States (R'arner, 19K; Centers for Disease_f:ontrol,_1988): One epidemiologic measure that is sensitive to both numbers of deaths and prematurity of death is years of potential life iost- (YPLL). A thorough description of the use of this- measure has been provided (CDC, 198b).- Estimation of Smoking-Attributable Years of Putential-Life Lost Loss of Isfe can be measured in terms of years of life lost prior to a particular age (typically. age 65 or 75) or prior to full life expectancy. Smoking-attributable''PLL is the suar of years of life lost for deaths attnbhted to smoldng for all diagnoses related to-smoking. For each smoldng-resated diagnosis, deaths (by sex and 5-year age group) are multiplied by the YPLL for each _5-year age group. This product is then multiplied by the smolang-attnbutable fraction (SAF) for the diagnosis: Satoking-attributable- YPLL = Deaths x.SAF x YPLL Summing across age categories provides the sex-specific-estimate of smoking-attributable YPLL for the diagnosis. Total smoking-attnbutable YPLL is-the sum of smolang-attnbutable Y-PLL- across age groups an_d across diagnoses for both sexes combined. With SAMNMC II, you can select YPLL -pr ior to age 65, YYPLL prior to-age 75, or YPLL prior to full life expectancy (Tables 9A-9C). If you citoose YPLL prior to full life expectancy, you can select sex-specific US. life expectancies foF whites, blacks, nonwhites, or all races combined. Or, you can supply life exx_c+tanry-data specific to the group under study. - Smoking-Attributab;le Years of Potential Life Lost Rates - SAIvflv1EC Il calculates age-specific and- age-adjusted rates of YPLIL to allow comparison among populations. Population data for the group under study are required to produce these rate estimates. Using computed numbers of smolring-attnbutable deaths and the selected- YPLL values, SAMDviEC II computes age-adjusted rates of smoldng-attributable YPLL - 33

Table 9A Years of Potential Life Lost Prior To Age 65 and Age 7S 5tears logt Ynrs IOst &e at death t0 aQe 6S t0 aec 75 0-4 - -62 72 S-9 57 67 10-14 52 - 62 lS-19 - - - 47 - - 57 20-24 42 52 25-29 - - - - 37 _ - 47- - 30-34 _ 32 - 42 33-39 27 -- - 37 - 40-M - - - 22 - - 32 - 45-49 17 27 50-54 - - 12 _ - 22 SS-59= - - -7 - - - 17 6414 2 12 65-69 0 7 7t1-74 0 2 75-79 - - 0 0 804u 0 - - 0 85+ 0 0 Table 9B - Years of Potentia; Life Relnaitling Relative to Life Expectancy: Males United States, 1985 Age at death All races - - Whites Nonwhites Blacks- 0-4- - 70.1 -- -70J -- 663 64.7 5-9 65.3 653 61.7 59.9 10-14 60.3 60.9 - S6.b 35.0 15-19 =- SSS 56.1 51.9 - 50.2 20•24 =- - 309 51.4 - 473 45.6 25-29 463 46.8 42.d 41 ; 30-34 41.7 422 3t.4 363 35-39 = 37.1 37.5 - - 34.1 - 326 40-44 92S 32.9 30.0 2" 4549 2a1 - 21;.4 26.0 24.7 50-54 2'3.9 24.2 222 21.1 s5-59 - - 20.1 -- 201 182 17.! 60-" 16.5 16.6 15.7 149 65-69 133 133 13,0 123 70-74 -- 10.5 - 10.5 103 9.9 75-79 -, -31 - - i.0 - - 93 79 a0." - - 6.1 6.0- 63 6.2 85+ 11 5.1 - 5.9 5.7 Swe.: M.uoa.t Caws fer !4.h! Suewn t1 K - - - - 34 %]

Table 9C Years of Potential-Life Remainin= Relative to Life F.xpectattcy: Females United States, 1985 Age at death k!1 eaoa WWtes Nogfr:aJus Blacks 0-4 77.0 77.4 74.1 73.E 3-9 72.1 72.5 69.3 64.0 1Q14 672 67.6 64.4 63.1 15-19 62.3 627 59.5 3s2 20-24 57.4 57.8 34.6 53.4 25-29 316 33.0 49.11 48.6 30-34 47.7 4a.1 45.1 43.9 35-39 42.9 433 40.4 393 40-" 362 383 35.9 34.8 - 13•49 33 .6 33.9 313 30.4 30-54 . ~ y ~.1 29.4 27.3 26.3 33-39 24.9 25.0 23.3 223 60-64 20B 21.0 19.7 19.0 63-69 17.1 172 16.3 15.7 70=74 13.6 13.6 13 , 2 12.7 75-79 10.5 103 20.4 10.0 80-Frl 7.7 7.7 S.0 7,S 10f 6.4 - 6.4 7.0 6.9 fs~ Naoy Ce"ur 6or HskD Ursun 14Y ~ - OD _ AI OD 35

Chapter 10 - - Calculation of SmoIsing-Attributable- f ndirect Mortality Costs- Smoking-Attributable Indirect Mortality Costs: Ab-Overview L;direct_ mortality costs are the estimated costs-of lost income and productivity resulting from premature death due to-smoltzng-related -disease and injury. For persons who die prematurely, all future earnings are forfeited. Using tbe_ human capital methodology, this loss of income is estimated as the present value of future earnings. This loss is attnbuted to the year of death. As the -economiE analog of the years of potential life lost (YP? L) measure, the indirect mortality cost estimate incorporates both the number of deaths and number-of premature _ deaths due to smoking-related causes. Rather than assessing this loss of life- in terrns of person-years, indirect mortality costs translate_ death statistics- into future earnings losses, a conservative estimate of productivity losses. A future stream of earnings is calculated as the sum of future a: nual earnings prior to retirement, assuming a one percent annual increase in product'rrity-->tnd- the annual inflation rate. _ Ile present value of future earnings (PVFE) is calculated the same way, but each term is discounted at 4 to 10 percent to account for -assumptions about the ti¢e value of money (see ~ discussion of discount rates on page 14). You can select from 3 discount rates: 4, 6, and 10 4 V id i ~ k i bl T l lO OC l i he o ta nto cons erat es aon mean earn r.gs, - e percent ( ab es - n t ta A,l ), a u~ wage supplements, labor fcrce participation rates, and an imputed value for household work for both males and females. Estimation of Smoldng-Attributable Indirect Mortality Costs For each smoking-related diagnosis, deaths (by sm and 5-year age group) are multiplied by the corresponding PVFE value. TW.s product is then multiplied by the smoking-attr.'butable fraction (SAF) for the diagnosis: Smoking-attributable indirect mortality costs- = Deaths x SAF x FVFE Summing across age categories provides- the sex-specific estimate of smoking-attributable lifetime earnings losses (indirect mortality costs) for the -diagnosis. The total smoldng-attnbutable indirect mortality cost is the sum of this cbst measure for age groups and diagnoses for both sexes combined. Indirect mortality costs and YPZ.L are similarly computed. . ~ Cti GD .~ tA 37 t~ CD

Smoking-Attributable Indirect Mortality Cost .ates SANDAEC II calculates age-specific and age-adjusted rates of indirect mortalmy costs to permit .omparisom- among populatiolm Populatiou data for the group under study are required to produce these rate estimates. Age-adjusted rates-are computed by using the direct method (Llienfeld and Lilier.feld, 1980). - - - Table 10A Present Value of Future Earnings (1~i83--I5iscount Rate 44g1 - Males Fzma!es <1 - S 421.235 - S 341.S74 l-4 - - 454~1" : 36638E - 5-9 -519,459- - 42?,790 10-14 - 602,092 467.S57 15-19 689,576 532,141 2O-24 745,680 - 575,461 25-29 - - 749,695 556,019 30-34 717,630 513,796 35-39 `- 653,4" 454,d97 40-" 561,016 38e,555 4549 - - - - 450,453 319,279 30-54 - 331,4-76 249,422 55-59 - 213,719 1a1.13-1 60-64 - - - - 108.680 - 117,333 6sr69 - 42,II79 67,3" 70-74 19.176 96,593 = 75-79 - - - - 9383 15,647 -a044 - 4,69e 9.164 aS * 1.4t2 2.311 w~ aiar. Rakon .n3 tanm.w . rlm eesI 4"

Table lOB Present Value of Future Earnings (1985-Discount Rate: 6%) - Age Males Females sl S 206,631 s 173,739 14 - 236,117 1%.515 S-9 293,977 344.559 10-14 374,790 311,673 15-19 46a,7d2 384,026 9D-2t 541,021 4iS,e04 25-29 S64.5,6 424,963 30-34 563,043 402.176 35-39 _ 532.289 36/.333 4044 471,190 319,090 4549 389,462 268.529 50-54 29e,645- 214,826 55-59 - 194.$78 159,614 60-64 101,0@5 _ )05.2ri 63-69 39,713 61,103 70-74 17,BQ'2 33374 75-79 8,789 17.531 8044 4.457 8,655 35+ 1,406 2,237 3ov~ Riec Rs+®.n trd C1mme~ ~ro ~~ Table 10C Present Value of Future Earnings 1985--Discount Rate: 10% Age - - Males Females <1 S- 60,AC6 S 53,d31 73,494 66,797 s-9 1u,042 ssXs 10-14 170,371- 130,622 15-19 2551,439 217,161 20-24 324Xs 264.94s 25-29 363,750 3;7.57a 30-34 3$1,607 2i2,561 33-39 377,522 255.422 40 -.. - 350,066 230,617 4349 302,591 20a= WS4 299,410 1WS16 SS-S9 165,416 12E,3r0 60d1 _ W714 i7,2?b dS~9 34.679 51,510 70-74 131"1 2t3,792 75-79 70r. 15IM S4&t 4,037 7,773 aS+ 1,344 2.155 Rom RA,.R .r o.W..Q 39

Chapter 11 Calculation of Srboi€ingaAttribettab9e - Direct Health-Care Costs Smold.ng Attribtttable Direct Dealth-Care Costs: An Dverview Smoking-attn3utable--dii-ect emts are exTendit{rres for the prevention, diagnosis, and treatment of smoking-related diseases and medical conditions. Direct costs include personal health expenditures for hospitaliation, outpatient clinical care, nursing home care, home health care, services of primary physicians and specialists, services of nonphysician health practitioners, and medication. Direct costs also include support or nonpersonal cosu for program administration, research, public health activities, and construction of medical facilities. Estimation of Smo;n g-Attributable Direct-Health-Care Costs The SAMI•rfEC-D user supplies gross cost estimates for total personal health expenditures and for five component cost centers: hospitalization, physician services, medication, nursing home care, and other-professional services. The methodolog•y used in SAMINEC i_ follows Rice and colleagues (1986). ';bese investigators used two morbidity indicators, annual hospital-days and annual physician visits, available- from National Health :nterviev: Survey kIv'HIS) data by smoking status. Rate ratios were computed as the ratio of annual hospital days (or physician visits) for ever smokers (current-and former smokers)_to annual hospital days-(or physician visits) for never smokers. These rate ratios serve as relative risk estimates in the standard population attnbutabie-risk formula. - Only diseases falling into the broad categories of neoplastic, circulatory, and respiratory illness were included in the calculations flf relative risk for smokers. The smoi&g-attnbutable fraction (SAF) was computed by using the relative risk estimates -and smoking prevalence rates as fol]ows (Lilienfeld and-Lilienfeld, 1980): P Attributable risk ~ p (RR-1) + I where: p: - prevalence -of the- risk factor RR: risk ratio (relative risk) for ever smokers compared w3th newr-smokers To estimate smoking-attributable direct cosu; the SAF was multiplied- by the estimated direct costs for the combination of neoplastic, circulatory, and respiratory diseates for the group under study. CJ1 41 .~ N 9

For SAM vr rEC 11, a-refinement of the above -tret5odology was-used to establish the fraction of medical care and disability attributable to smoking. Tlue-steps involve-d-in the calculation of smoking-attnbutable direct costs are summarized beiow: (1) Reported rate- s of short-term hospitalization and risiu to a physician in the last 12 months for current smokers, former smokers, and never srrtoke3 were calculated using data from the 1987 NHIS (unpublished data, Office on Smoking and Health). Only persons 35 years-ofd or older-who- bad conditions in-tbe categories of neoplastic disease, cardiovascular disea,;e; or respiratory dise3se were included. (2)- Rates of =hospitalization -and physician- visits-for current smokers and former smokers -relative to those for -never smoi€ers, were- calculated. Rstativ_ e-rate estimates less than 1.0 for some age and sex strata-('Table 11A) were set to 1.0 in SANLVXC II. We assumed that cigarette use would n-ever-be protectlvt for health care utilization. [Note: A relative- rate of l:0 indicates no excess utilization.) (3) For the calculation of SAFs for the cost centers- of nursing home care and other professional services, the -relative -rates for hospital care-were used. For the SAFs for medication costs, the relative rates of physician- visits weie- used. (4) The relative rates of utdiiation for all five cost centers for current and fo-rmer- smokers are used with -prevalence- data for current and former smokers to -calculate the SAF values for hospital costs and physician visits. 'lhe_ expanded aunbutable risk formula is-as- foiiowa: - [p, + P,(RRJ + P:()ZRI)l -_ Smoldng-attributable fraction = --_- - - IP-, + PI(RJZJ + P:(RRJ) i where: p: percentage of never smokers in group ubder study p,: percentage of current smokers in group under study pr percentage of former smokers in group under study RR,: ielative rate of-utilization for current smokers compared with-that of never-smokers RR2: relative rate of utilization- for former smokers ccrupared- with that of never smokers To calculate direct costs for the group under study, cost center-speci6c expenditures are necessary for SAM1viEC II. - When ali- 50 States performed SAIvNMC calculations in 1SS8, the OSH_ prflvided data for 1985. -'Ihese data were obtained by adjusting to 1985 (OSH, 1990) the State specific data reported- for 1982 by -the Health Care Financing-Ad.rainist-ration (HC7rA) (Levif, 1985). National data for 1985 were-used for this- ad;tutrnent (Lazenby, 1986). The calculation is summarized as follovs: - OD Cft fb .~ Go 42 N W

198~ 39as - State cost Tlational-cost centrr figure center fbgure- -198S State-specific - x a State ~ cost center 1982 1985 population figure National cost- = U.S. population center figure -A simBar -procedure will use 1987 health-care expenditure tata for the United Statm as published by HCFA_(Let3ch, 1988) -to produce State-specific economic data. These data arc a~~able -frotn the OSH for each State and are included in the documentation manual for ~ S~viHC IL For-other jurbsdiztioss-(suc~h as counties), the State.spc~b cosu!r.an be converted into a State per capita-cost and then multiplied by the population of the luriusdiction. Updated State-specific cost -data will be-awagabie from-HCFA periodically. These data are reported -in the quarterly journal, Hearih -C4re Finans•ing-Revi..~w. Table 11R Relative Rates of Hospital Days Per 100 Persons and _ Physician Visits -Per 100 Persons = By Smoking Status - -Males - Females - Both Sexes 35-64 S5+ 3Sd.4- - 65+ 35-64 65+ Hospital days per 100 persons Never smokei-st 42-6 155.9 64.1 125.0 56.3 133.5 Former smokers 82.0 -1915 73.6 - 168_3 78.8 186.6 Current -smokers 84.3 - 11339 -69.7 76.2 77.3 M. 7 Relative rate (current)- 1.98 - 1.18 - L09 0.61 1.37 0.96 Relative rate (former) 1.93 1.23 1.15 1.35 1.37 - 1.40 Pbysician- visits per 100 persons Never smokers 323.7 454.2 421.2 5$3.4 386.8 547.8 Former smokers 370.5 501.4 529:3 - 671.1 432.0 559.1 Current smokers 3'+7.2 456.0 463.8 428.0 418.4 441.4 Relative rate (current) 1.17 1.00 1.10 0.74 1.08 0.81_ Relative rate (forn:er, - 1.14 1.10 1.26 1.15 1.12 1.02 43

Chapter 12 Calculition of Smo1cin g-AttributablE = Indirect Morbidity Costs- - _ Sariokiug-Attributstble Indirect Morbidit~y Costs: An ©vervieer Indirect =morbidity costs are the estimated costs of -lost income and produr-&4ity for persons who are sick or disabled frrn: smoking-attriDutable-diseascs:, Rice and col,'eagues have stated= the- _ following (1986): Morbidity_ costs consist of the productivity losses to society, as measured by - wages, salaries, and supplements, resulting from days lost from work among the currently employed, persons unable to work-ber,auu of Mness-and disability, persons institutionalized for health reasons, and the imputed value of -- housekeepiog services of women who are unable to keep house because of- -- hlness or disability. Estfmation of Sr;t-oking-Atfribatable Indirect I1fos bidity Costs- ~. The methodology-usyd in-S4ivaZC U follovmRic:- and colleagues (1986). These investigators ' 1 used two mosbidity indi"cators,-worY-loss dayt and bed disability d~;~, $vadable from National Health Interview Survey (NHIS) data by smoking status. Rate ratios were computed as the ratio of annual work ;oss days (or bed disability days)-for ever smokers (current and former smokers) to work-loss days (or-bed disability days) -for r:ever-smokerg. These risk ratios served as relative risk estimates. The smoking-attnbutable fraction (SAF; was computed using the relative risk estimates and ever smoker prevalence rates as 1ollows (lyilicnfcld and Iilien#ead, ' 1980): p (RR-1) Attributable risk `_ p (F.li!-1) + -1 where: p:- prevalence of the risk factor RR: risk ratio (relative -risk) for ever smokers compared to never smokers SAYs~ for work-loss (bed disability) days vwere-anultiplied by the total estimated work-loas-days to develop an estimate of smoking-attributable work-loss days; this estimate *-as then multiplied by earnings to estimate smoking-attnbutabld morbidity costs. Because of the lack of comparable data on morbidity costs by disease category for individual States, SAMMEC software estimated these costs as a proportion of total econornic costs for each State based on the proportion estimated for the nation by Rice and colleagues (1986). 45

With SAJvPvffiC I, you can enter population data-, earnings data, and labor force participation rate data to determine mean per capita income according to the following formula: ~ Meaa per capitst income t ((wages +- supplements) x (ntirrtber of full-time employed ~rson~)J ~ (.S x-(vmges + supplements) x (number ot-part-tirne employed persons)]}t (number of persons in the population) Indirect morbidity costs are_cQmptrted as-follovrs: _ = Smoking-attribtrtable indirect morbidity costs Disability days x SAF x mean per capita- incorne This calculation is- sm-specific. The SAFs for worlC-loss days and bed disability days were calculated acc?rding to the metbodoingy of Rice and colleagues (19986), modibed to accommodate sepa<rate- relative rates- of disablity for current-and -former smokert. -'fbe-steps in the calculation process are f ummarized belo`v: (1) The work-loss days per 100 currently employed persons and bed-disability days per 100 women keeping house (combined) were calculated for current smolCers, former smokem, andnever smokers who responded to the 1987 I~"1S. Only persons 35 or older who reported illness due to cardiovascular disease, neoplastic disease; or - respiratory disease were- included in the calculations(2) Number of persons unable to wcirk= or keep house per 1,000 persons was -calculated for current smokers, form er smokers, and never smokers who responded to the 1987 _ NHIS. (3) Relative -rates-of disability for current sr;aokers and former smokers compared with never smokers were calculated (Table 1?A). (4) The relative rates of d'uability for current smokers and former smokers compared with never swokers-were used with-the prevalence of current smoking and former smoldng to calculate t15e-SAF of total disability days reported by persons with cardiovascular; neoplastic, and respiratory disease. The expanded attributable risk formula is-used in these calculations: (P. + PJRRJ + PARR0) • 1 Smoking-attributable fraction = -- 1P. + P,(RRJ + Pa(RRJ] 46

r i Wbere:- p,: percentage of never smokers in group under study p,: percentage of current- smokers in group under study pp percentage of former smokers in group under study - -- -- - RR,: relative rate of disabdity for current smokers compared with tt at of never smokers IR3: relative rate of disability for former smokers compared with that of never smokers (5) Total smoldng-attnbutable person-days of disability were anuitipGed by the gross earnings data to obtain an estimate of smoking-attributable indirect morbidity costs. Table 1?.A Relatiye Rales foP Work-Loss I)ays Pe.--100 Employed Persons and - - Bed-Disability Days Per -100 Females Keeping-House by Srnokir.g Status - hi_ ales - Feaiaies Botb sexes 35-64 65+ 35-64 65+ 35-64 6S+ Nemer smokers ?37.8 239.9 495.9 673.1 407.1 6324 Former smokers 287.1 S 17.3 5422 785.5 392-2 691.0 Current smokers 346.7 749.0 631.0 730.0 489.0 734.0 Relative rate (CUfreAt) 1.46- 3.12 -1.27 -1.0$- 1.20 1.16 Relative rate (former) 1.21 216 -- 1.09 1.17 0.96 1.09 47

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