## Print version ISSN 0102-311XOn-line version ISSN 1678-4464

### Cad. Saúde Pública vol.35 no.8 Rio de Janeiro  2019  Epub Aug 29, 2019

#### http://dx.doi.org/10.1590/0102-311x00129118

ARTICLE

Burden of smoking in Brazil and potential benefit of increasing taxes on cigarettes for the economy and for reducing morbidity and mortality

1 Instituto Nacional de Saúde da Mulher, da Criança e do Adolescente Fernandes Figueira, Fundação Oswaldo Cruz, Rio de Janeiro, Brasil.

2 Instituto de Efectividad Clínica y Sanitaria, Buenos Aires, Argentina.

3 Instituto de Medicina Social, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brasil.

4 School of Health and Related Research, University of Sheffield, Sheffield, U.K.

ABSTRACT

The prevalence of smoking in Brazil has decreased considerably in recent decades, but the country still has a high burden of disease associated with this risk factor. The study aimed to estimate the burden of mortality, morbidity, and costs for society associated with smoking in 2015 and the potential impact on health outcomes and the economy based on price increases for cigarettes through taxes. Two models were developed: the first is a mathematical model based on a probabilistic microsimulation of thousands of individuals using hypothetical cohorts that considered the natural history, costs, and quality of life of these individuals. The second is a tax model applied to estimate the economic benefit and health outcomes in different price increase scenarios in 10 years. Smoking was responsible for 156,337 deaths, 4.2 million years of potential life lost, 229,071 acute myocardial infarctions, 59,509 strokes, and 77,500 cancer diagnoses. The total cost was BRL 56.9 billion (USD 14.7 billion), with 70% corresponding to the direct cost associated with healthcare and the rest to indirect cost due to lost productivity from premature death and disability. A 50% increase in cigarette prices would avoid 136,482 deaths, 507,451 cases of cardiovascular diseases, 64,382 cases of cancer, and 100,365 cases of stroke. The estimated economic benefit would be BRL 97.9 billion (USD 25.5 billion). In conclusion, the burden of disease and economic losses associated with smoking is high in Brazil, and tax increases are capable of averting deaths, illness, and costs to society.

Keywords: Tobacco Use Disorder; Cost of Ilness; Costs and Cost Analysis

RESUMO

A prevalência do tabagismo no Brasil reduziu sobremaneira nas últimas décadas, mas o país ainda tem uma elevada carga de doença associada a este fator de risco. O objetivo deste trabalho foi estimar a carga de mortalidade, morbidade e custos para a sociedade associada ao tabagismo em 2015 e o potencial impacto gerado em desfechos de saúde e para a economia a partir do aumento de preços dos cigarros por meio de impostos. Foram desenvolvidos dois modelos: o primeiro é um modelo matemático baseado em uma microssimulação probabilística de milhares de indivíduos usando-se coortes hipotéticas que considerou a história natural, custos e a qualidade de vida destes indivíduos. O segundo é um modelo de impostos aplicado para estimar o benefício econômico e em desfechos de saúde de diferentes cenários de aumento de preços em 10 anos. O tabagismo foi responsável por 156.337 mortes, 4,2 milhões de anos de vida perdidos, 229.071 infartos agudos do miocárdio, 59.509 acidentes vasculares cerebrais e 77.500 diagnósticos de câncer. O custo total foi de R$56,9 bilhões, dos quais 70% corresponderam ao custo direto associado à assistência à saúde e o restante ao custo indireto devido à perda de produtividade por morte prematura e incapacidade. Um aumento de 50% do preço do cigarro evitaria 136.482 mortes, 507.451 casos de doenças cardiovasculares, 64.382 de casos de câncer e 100.365 acidentes vasculares cerebrais. O benefício econômico estimado seria de R$ 97,9 bilhões. Concluiu-se que a carga da doença e econômica associada ao tabagismo é elevada no Brasil e o aumento de impostos é capaz de evitar mortes, adoecimento e custos para a sociedade.

Palavras-chave: Tabagismo; Efeitos Psicossociais da Doença; Custos e Análise de Custo

RESUMEN

La prevalencia del tabaquismo en Brasil se redujo sobremanera en las últimas décadas, pero el país todavía cuenta con una elevada carga de enfermedad asociada a este factor de riesgo. El objetivo de este trabajo fue estimar la carga de mortalidad, morbilidad y costes para la sociedad, asociada al tabaquismo en 2015, y el impacto potencial generado en los desenlaces de salud y para la economía a partir del aumento de precios del tabaco a través de impuestos. Se desarrollaron dos modelos: el primero es un modelo matemático, basado en una microsimulación probabilística de millares de individuos, a través de cohortes hipotéticas, que consideró la historia natural, costes y calidad de vida de esos individuos. El segundo se trata de un modelo de impuestos aplicado para estimar el beneficio económico y en desenlaces de salud de diferentes escenarios con el aumento de precios durante 10 años. El tabaquismo fue responsable de 156.337 muertes, 4,2 millones de años de vida perdidos, 229.071 infartos agudos de miocardio, 59.509 accidentes vasculares cerebrales y 77.500 diagnósticos de cáncer. El coste total fue de BRL 56,9 billones (USD 14,7 billones), de los cuales un 70% correspondieron al coste directo asociado a la asistencia a la salud y lo restante al coste indirecto, debido a la pérdida de productividad por muerte prematura e incapacidad. Un aumento de un 50% del precio del tabaco evitaría 136.482 muertes, 507.451 casos de enfermedades cardiovasculares, 64.382 de casos de cáncer y 100.365 accidentes vasculares cerebrales. El beneficio económico estimado sería de BRL 97,9 billones (USD 25,5 billones). Se concluyó que la carga de la enfermedad y económica asociada al tabaquismo es elevada en Brasil y el aumento de impuestos es capaz de evitar muertes, enfermedad y costes para la sociedad.

Palabras-clave: Tabaquismo; Costo de Enfermedad; Costos y Análisis de Costo

Introduction

There are 1.1 billion smokers in the world, and four out of five live in low- and middle-income countries 1. Smoking is the leading risk factor for death from chronic noncommunicable diseases, accounting for 6 million deaths a year 2. A total of 603 thousand deaths a year are attributable to passive smoking, 28% of which in children 3. This risk factor is associated 75% of cases of chronic obstructive pulmonary disease (COPD) and 22% and 10% of deaths in adults from cancer and cardiovascular diseases, respectively 2. Recent epidemiological evidence also indicates that other diseases such as breast and prostate cancer and vascular disorders of the gastrointestinal tract are partly attributable to smoking 4.

The total global cost reaches USD 1.4 trillion per year, or 1.8% of the global Gross Domestic Product (GDP) 5. Approximately 40% of these losses occur in low- and middle-income countries. Four of the five BRICS countries - Brazil, Russia, India, and China -, account for 25% of the global cost attributable to smoking 5. From the health sector’s perspective, the cost of care represents 15% of total expenditures in some countries, and in seven Latin American countries alone it is the equivalent of 8.3% 6.

Smoking is the third leading risk factor for death and quality-adjusted years of life lost in South American countries 7. It is associated with a reduction in productivity and heavy expenses for families, factors that contribute to the exacerbation of poverty. The loss of productivity is the result of premature death, which occurs before the individual retires, and also indirectly, with the reduction in productivity due to the chronic diseases associated with smoking 8.

Brazil has an outstanding position in the global scenario with its National Tobacco Control Policy, which incorporates the guidelines of the World Health Organization Framework Convention on Tobacco Control (WHO-FCTC), ratified by Brazil more than 10 years ago (Decree n. 5,658 of 2006). Although Brazil was one of the world leaders in the number of smokers, from 1990 to 2015 it was also one of the countries that showed a significant reduction in smoking prevalence among both men and women (56.5% and 55.8%, respectively) 9. These strides are important, but data from 2011 showed that the burden of disease associated with smoking is still high, with some 147 thousand deaths and 2.69 million years of life potential lost per year, in addition to generating an annual cost to the health system of BRL 23.37 billion (USD 6.1 billion) 10.

The objectives of this study were to estimate the burden of disease and economic burden associated with smoking in Brazil in 2015 and to predict the economic and health benefits from increasing excise taxes on cigarettes in a 10-year scenario.

Materials and methods

The study used two models: (i) a model of the burden of disease associated with smoking, which allowed estimating the impact in terms of morbidity, mortality, and cost to society and (ii) an excise tax model to measure how price increases would avoid deaths, illness, and costs to society based on different scenarios of cigarette price increases in 10 years. We also estimated the government’s increase in tax revenue resulting from the excise tax increases.

Model of burden of disease associated with smoking

This is a mathematical model with first-order Monte Carlo microsimulation using a probabilistic simulation of each individual to incorporate the natural history, direct and indirect costs, and loss of quality of life associated with the main tobacco-related diseases. The model has been validated in various countries, as shown by previous studies 10,11,12. The selected diseases were: ischemic and non-ischemic cardiac diseases, COPD, pneumonia and influenza, stroke, and the following types of cancer: lung, mouth and pharynx, esophagus, stomach, pancreas, kidneys and renal pelvis, larynx, uterine cervix, and myeloid leukemia. The model’s methodological development and coding of the diseases by the 10th revision of the International Classification of Diseases (ICD-10) have been presented in detail in previous studies 10,13. The model was programmed in Excel (https://products.office.com/) with macros in visual basic.

Initially, for each individual from a hypothetical cohort of non-smokers, we calculated, by age and sex, the baseline risk of occurrence of acute and chronic events that could be related to the disease, its progression or death, and the direct costs (healthcare) and indirect costs (productivity lost to premature death and disability). Individuals were followed in six hypothetical cohorts in which we estimated, in annual cycles, each event’s risk of occurrence, according to demographic characteristics and smoking status (non-smoker, smoker, or former smoker), clinical conditions, and risk equations 10,11,13.

Due to the lack of information of good quality on the population incidence of the target diseases, a method was determined backed by data from the Brazilian Mortality Information System (SIM. http://datasus.gov.br) for 2015. This option has been adopted in economic and epidemiological models 14,15,16,17,18,19 and allows estimating the absolute risks by age and sex for acute or chronic events. It is acknowledged internationally that national statistics underestimate mortality from COPD 20,21, so the estimates for COPD risk, incidence, and progression were taken from the international literature 20,22. Case-fatality was estimated from hospitalizations in the Brazilian Hospital Information System of the Brazilian Unified National Health System (SIH/SUS. http://www.datasus.gov.br). Although the etiology of pneumonia and influenza is infectious, the inclusion of both is justified by evidence of increased risk in smokers suffering severe episodes of exacerbation and higher mortality when compared to non-smokers.

The model captured the outcomes’ frequency to the extent that each individual could present no events or multiple events, since acute events and chronic conditions were not mutually exclusive. We also calculated years of potential life lost (YPLL), with two components - YPLL due to premature morality (YPLL-PM) and YPLL due to reduced quality of life (YLL-QL), the direct and indirect costs associated with tobacco-related diseases. Since the model did not include a direct estimate of the effects of passive smoking and perinatal diseases (low birthweight, low birth stature, respiratory distress syndrome, and sudden infant death syndrome), we used an approximation based on the literature to calculate mortality. The additional burden from these causes was 13.6% in males and 12% in females 23.

Calibration, internal consistency, and validation of the model of burden of disease associated with smoking

The following methodological steps were performed: internal consistency to identify errors related to the incorporation of data and the model’s programming syntax in the software; calibration to ensure reproducibility of the results in relation to the incidence and mortality indicators; and external validation, in which the model’s results were validated via comparison with epidemiological and clinical studies that did not use the same data sources to estimate the risk equations. This process allowed verifying the model’s reliability. For calibration specifically, we selected all the mortality rates except for mortality from COPD, since it is underestimated in national statistics. The results by age and sex were compared to rates presented in national statistics, and we proceeded to the analysis of deviations. The mean rates of events simulated by the model that were within +/- 10% of the mean reference rate of events (national statistics and databases) were considered acceptable. In case of larger deviations, the risk equation for this specific event was modified (the case-fatality and survival values varied in the +/- 15% range) to provide for a better fit in the results.

Data collection

The parameters used in the model were backed by Brazil’s demographic structure and by the individual risk of death by cause, age, and sex, and the prevalence of smoking based on smoking status 24. The demographic data were obtained via projection of the population to 2015 by the Brazilian Institute of Geography and Statistics (IBGE. Projeção da população brasileira por sexo e idade: 2000-2060. https://www.ibge.gov.br/estatisticas-novoportal/sociais/populacao/9109-projecao-da-populacao.html?=&t=o-que-e, accessed on 20/Apr/2016), considering each individual in the cohorts by sex and age from 35 to 100 years. Overall population mortality and disease-, age-, and sex-specific mortality were incorporated into the estimated risk of death 10,13. The following adjustments were made to the data from the SIM: (i) correction of the under-recording of deaths by application of the adjustment factor for coverage of deaths 25; (ii) imputation of missing values for age and sex, replaced respectively by median age and the most frequent sex calculated by considering the records with the same underlying cause; and (iii) redistribution of garbage codes and ill-defined causes that did not allow the precise classification of cause of death for the diseases included in the model (Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz. Projeto Carga de Doença. http://www4.ensp.fiocruz.br/projetos/carga/downloads1.htm, accessed on 05/Apr/2017).

The relative risks of developing each disease in smokers and former smokers compared to non-smokers were obtained from the Cancer Prevention Study II (CPS-II) 26. Case-fatality was calculated by the model for certain conditions such as acute myocardial infarction (AMI), angina pectoris, and stroke and compared to the available national statistics for ischemic coronary disease or cerebrovascular diseases. By dividing the data on deaths grouped according to ICD-10 codes by the Brazilian population, it was possible to obtain the absolute mortality risk by cause, sex, and age. For the cancer case-fatality rates, we obtained data on specific prognoses by type of cancer, age, and sex using Globocan 19,27. Due to the unavailability of hospitalizations by sex, age, and ICD-10 in Brazil’s supplementary health system (private plans), a correction was performed in the data from the SIH/SUS in order to include all hospitalizations in 2015 in the country 28.

Estimated burden of disease associated with smoking

The burden was estimated by analysis of differences in the occurrence of acute and chronic events, deaths, and costs between the results predicted by the model, according to current data on smoking prevalence 24, and the results predicted for a cohort of non-smokers. Estimated burden of disease was expressed in YPLL in population terms, through two components: YPLL-PM and YPLL-QL. YPLL-PM were calculated via a standardized methodology 29 and measures of state-of-health utility were used for each disease to estimate the YPLL-QL.

Cost calculation

We adopted society’s perspective, including the direct cost of care and the indirect cost associated with loss of productivity due to premature death and disability. Costs are shown in Brazilian Reais (BRL) for 2015, with no adjustment for inflation.

A 5% annual discount rate was applied for all the health outcomes and for the costs 30. The discount was necessary in order for these results estimated over the years to express present values.

Direct cost

We estimated the mean unit cost per disease to the SUS (public) and the supplementary health sector (private) through the micro-costing and cost-per-procedure technique. This cost was incorporated into the model, which simulated the likelihood of occurrence of the events over the individual’s life to estimate the total cost of care. The Delphi technique was used, consulting specialists in oncology, cardiology, pulmonology, and neurology to identify and quantify the health resources. The costs items included: medical consultations, tests, hospitalizations, and surgical and non-surgical procedures.

To assess the resources for the SUS, we consulted: (i) Management System for Table of Procedures, Medicines, and Orthoses, Prostheses, and Special Materials (SIGTAP. http://sigtap.datasus.gov.br/tabela-unificada/app/sec/inicio.jsp, accessed on 20/Sep/2017); (ii) Database on Prices in Health (BPS. http://aplicacao.saude.gov.br/bps/login.jsf, accessed on 22/Sep/2016); and (iii) Chamber for Regulation of the Pharmaceuticals Market (CMED. http://portal.anvisa.gov.br/cmed, accessed on 25/Sep/2016). We also reviewed the reports on approval of incorporation of technologies by the SUS by the National Committee for Health Technology Incorporation since 2011 (CONITEC. http://conitec.gov.br/, accessed on 04/Oct/2016). The cost of cancer of the larynx and cancer of the esophagus for the SUS was obtained in the literature 31. The procedures tables for the national health insurance market and the Brazilian Hierarchical Classification of Medical Procedures published by the Brazilian Medical Association (CBHPM. https://amb.org.br/cbhpm/, accessed on 30/Sep/2017) were consulted to calculate the costs to the supplementary health system.

Indirect cost

The theory of human capital was used to estimate the cost from premature death and disability 32,33. We assumed that the value for society of the loss of productivity can be measured as the current values of the individuals’ lost work time, according to their market wages, and to which was assigned a productivity equal to a worker’s marginal productivity in a perfectly competitive market 34.

Presenteeism was used to estimate the disability’s cost, a concept that refers to the decrease in work productivity when an individual is reincorporated into work after the disease. The decrease in productivity as a consequence of the illness can be expressed as a shorter workday and lower level of production per hour of work, or both 35.

The current value of a person’s future income depends on their life expectancy, participation in the labor market, and income from work. The human capital value of an individual of a given sex and age is the current value of this income in the future, according to the actuarial formula of the value of a statistical life (VSL):

VSL=j=iExprobalive*Wages*1+g1+rEx-i (Equation 1)

In which prob(alive) is the probability that an individual will be alive the next year (Instituto Brasileiro de Geografia e Estatística. Projeção da população brasileira por sexo e idade: 2000-2060. https://www.ibge.gov.br/estatisticas-novoportal/sociais/populacao/9109-projecao-da-populacao.html?=&t=o-que-e, accessed on 20/Apr/2016); wages is an estimate of the individual’s annual income from work 36; and the last term considers two parameters assumed as constants: a growth rate over time in income from work (parameter g), the premise of which is that this growth is equal to the mean annual growth rate for Brazil’s per capita GDP, or 2.25% per annum, from 1960 to 2015 (World Bank. http://data.worldbank.org/indicator/), and a 5% discount factor for future income (parameter r). Calculation of the VSL associated with an individual of a given sex and age is the sum of the products for each age.

It was necessary to adopt alternative models for the reduction of work productivity 35,37,38 using an indirect estimation criterion: it was assumed that individuals’ work productivity decreased due to smoking at the same proportion as the reduction of quality of life attributed to it 16. We also estimated the probability of an individual surviving from year t to year t + 1 according to the life table by age and sex in 2015, published by the IBGE (http:www.ibge.gov.br, accessed on 18/Mar/2017).

The Mincer 39,40 equation was applied to estimate mean annual income (referring to the term wages in Equation 1) by sex and age based on maximum schooling attainment, labor market experience (approximated by age and age-squared), and geographic location:

"ln"Wage=α+βage+γage2+δlevelschooling1++θlevelschooling8+φurban+ε (Equation 2)

In which ln(wages) is the natural logarithm of the wages received for the individual’s principal work activity, age and age 2 seek to approximate work experience, level schooling 1,... level schooling 8 represent the different levels of schooling attained, urban is the variable that indicates whether the individual lives in an urban or rural area, and ε represents the model’s error term, which assumes meeting the classical assumptions. To calculate the equation, the ordinary least squares method was applied and the data were obtained from the Brazilian National Household Sample Survey (PNAD 2015) 36. The analyses were performed with Stata, version 14.1 (https://www.stata.com).

Excise tax model

This model was based on the application of percentage increases in cigarette prices. Prevalence of smoking obtained with this increase was calculated as:

Prevalencepost=Prevalencepre+(Ed*%P*Ip*Prevalencepre) (Equation 3)

In which: Prevalence post is the prevalence of smoking after the price increase; Prevalence pre is the prevalence of smoking before the price increase; E d is the price elasticity of demand 41; Δ%P is the percentage variation of price; and I p is the proportion of variation in tobacco consumption that impacts the prevalence of smokers.

We calculated the expected impact on health outcomes, drawing on the Brazilian national context to define three price increase scenarios: short-, medium-, and long-term. The basi case for comparison was estimated by the unification of the three scenarios, and the results were accumulated for 10 years. We assumed linear evolution from the short-term scenario to the medium-term scenario in a five-year period, and then to the long-term scenario, from year 6 to year 10 12. Based on these estimates of change in the prevalence and redistribution involved in the proportion of smokers, former smokers, and non-smokers in the population, we focused on the estimate of the expected burden of tobacco-related diseases in the country based on these new conditions, according to the same method adopted to estimate the underlying burden of disease. The impact on health outcomes was calculated as the observed difference between the two estimates of deaths, occurrence of events, years of potential life lost, disability, and direct and indirect costs.

Impact on tax revenue

The expected variation in revenue in the different scenarios of cigarette sales price increases was estimated by 42:

%R=%consumption* %price/%tax (Equation 4)

In which: Δ%R is the percentage variation in revenue; Δ% consumption is the expected percentage variation in consumption from the increase in sales price; Δ% price represents the percentage variation in the consumer sales price; and %tax is the proportion of the consumer sales price corresponding to the tax.

Impact on health outcomes and the economy

Three scenarios of price increases for cigarettes, through taxes, were proposed (25%, 50%, and 75%) over the course of 10 years. Impacts on health outcomes are expressed as the decrease in prevalence and thus in deaths, cases of tobacco-related diseases, and averted costs. Impacts on the economy are expressed as the total economic benefit calculated by the sum of the averted direct and indirect costs and the additional tax revenue due to the price increase. The results are presented in BRL for 2015.

Results

Calibration and validation

The mean event rate for each parameter was within plus-or-minus 10% of the rates found in the national statistics, which guaranteed excellent internal validation. Assessment of the correlation between the observed and expected results produced R2 values between 0.700 and 0.999 (perfect fit = 1), indicating high correlation. External validation was performed by comparison of the model’s results with published epidemiological studies (that were not used as data sources in this study). A favorable correlation was observed between the model’s predicted values and those observed in the selected references (Figure 1).

Deaths and events attributable to smoking

The model estimated 558,789 deaths in 2015, of which 156,337 (28%) were attributable to smoking and which corresponded to 12.6% of total deaths in the country (1,239,810). The proportion of attributable deaths was highest for COPD (74%) and lung cancer (78%). Cerebrovascular accident (stroke) and AMI corresponded to 13% and 18% of the total, respectively. Passive smoking and perinatal causes totaled 18,093 deaths per year. A total of 77,500 cases of cancer were diagnosed, of which 26,850 were lung cancer. There were 1,103,423 acute and chronic events, of which 378,594 (34%) cases of COPD, 229,071 (21%) of AMI, and 59,509 (5%) of stroke (Table 1).

Table 1 Deaths, acute and chronic events, and years of potential life lost due to premature deaths attributable to smoking. Brazil, 2015.

Disease Total of deaths (A) * Deaths attributable to smoking
Men (B) Women (C) Total (D = B + C) % (D/A)
n n % n % n
Total 558,789 106,729 100 49,608 100 156,337 28
AMI 130,312 16,791 16 6,397 13 23,188 18
Ischemic heart disease (except AMI) 32,293 3,545 3 1,462 3 5,007 16
Cardiovascular disease (non-ischemic causes) 59,944 5,182 5 1,622 3 6,804 11
Stroke 80,857 6,493 6 4,319 9 10,812 13
Cancer of lung 30,519 16,077 15 7,686 15 23,763 78
Pneumonia 85,442 7,954 7 2,946 6 10,900 13
COPD 41,924 17,891 17 13,229 27 31,120 74
Cancer of mouth and pharynx 10,269 3,845 4 2,036 4 5,881 57
Cancer of esophagus 10,597 5,695 5 1,195 2 6,890 65
Cancer of stomach 16,770 2,846 3 533 1 3,379 20
Cancer de pancreas 10,846 1,149 1 1,058 2 2,207 20
Cancer of kidneys and renal pelvis 3,295 754 1 53 0 807 24
Cancer of larynx 4,796 3,433 3 397 1 3,830 80
Myeloid leukemia 11,116 1,237 1 325 1 1,562 14
Cancer of bladder 3,720 1,060 1 296 1 1,356 36
Cancer of uterine cervix 7,996 - - 739 1 739 9
Passive smoking and other causes 18,092 12,777 12 5,315 11 18,093 100
Disease Total of deaths (A) * Acute and chronic events attributable to smoking
Men (B) Women (C) Total (D = B + C) % (D/A)
n n % n % n
Total 3,825,406 706,321 - 397,102 - 1,103,423 29
AMI 905,532 169,439 30 59,632 18 229,071 25
Ischemic heart disease (except AMI) 1,102,307 154,317 26 87,279 18 241,595 22
Cardiovascular disease (non-ischemic causes) 59,944 5,182 5 1,622 3 6,804 11
Stroke 385,523 35,641 18 23,869 13 59,509 15
Cancer of lung 34,313 18,702 87 8,148 64 26,850 78
Pneumonia 705,548 78,483 20 42,669 13 121,152 17
COPD 557,944 214,351 73 164,243 63 378,594 68
Cancer of mouth and pharynx 24,813 10,279 73 4,347 41 14,626 59
Cancer of esophagus 12,260 6,496 70 1,418 48 7,914 65
Cancer of stomach 23,611 3,968 26 770 9 5,738 20
Cancer de pancreas 11,199 1,189 23 1,097 19 2,287 20
Cancer of kidneys and renal pelvis 6,914 1,552 37 108 4 1,660 24
Cancer of larynx 8,591 6,290 82 581 67 6,871 80
Myeloid leukemia 16,458 1,878 21 480 6 2,358 14
Cancer of bladder 11,896 3,736 44 778 23 4,513 38
Cancer of uterine cervix 18,496 - - 1,683 9 1,683 100
Passive smoking and other causes - - - - - - -
Disease Years of potential life lost due to premature deaths attributable to smoking **
Men Women Total
n n n %
Total 1,046,516 542,074 1,588,590 100
AMI 204,654 80,864 285,318 18
Ischemic heart disease (except AMI) 40,177 17,312 57,489 9
Cardiovascular disease (non-ischemic causes) 56,994 19,063 76,057 4
Stroke 80,642 61,945 142,587 5
Cancer of lung 172,761 94,978 267,739 6
Pneumonia 71,454 30,578 102,032 21
COPD 181,735 152,742 334,477 17
Cancer of mouth and pharynx 48,513 26,683 75,196 5
Cancer of esophagus 68,194 14,290 82,484 5
Cancer of stomach 31,485 6,511 37,966 2
Cancer de pancreas 13,756 12,949 26,705 2
Cancer of kidneys and renal pelvis 9,104 718 9,822 1
Cancer of larynx 41,129 4,963 46,092 3
Myeloid leukemia 15,132 4,332 19,464 1
Cancer of bladder 10,786 3,457 14,243 1
Cancer of uterine cervix - 10,689 10,689 1
Passive smoking and other causes - - - -

AMI: acute myocardial infection; COPD: chronic obstrutive pulmonary disease.

* Totals are not attributable to smoking;

** With application of 5% discount.

Years of potential life lost

The years of life lost, expressed as YPLL, totaled 4,203,389, resulting from 71.7% of YPLL-PM for both sexes. Of this total, 64% of YPLL-PM occurred in males. Most of the YPLL-PM were attributed to ischemic cardiovascular diseases (27.1%), COPD (20%), and lung cancer (16%). Life expectancy in female smokers is 6.71 years shorter than for non-smokers, while the difference between former smokers and non-smokers is 2.45 years. Male smokers and former smokers lose 6.12 and 2.66 years of life, respectively, when compared to non-smokers.

Costs

The direct cost of healthcare for diseases not attributed to smoking was BRL 96,724,046,812. The cost (from society’s perspective) attributable to smoking totaled BRL 56,898,155,567, and the direct cost accounted for 70% (BRL 39,404,319,965). COPD (BRL 15.990.182.776), cardiac diseases (BRL 10,264.380,964), lung cancer (BRL 2,285,584,843), and stroke (BRL 2,174,230,523) accounted for 78% of this cost. The costs of passive smoking and perinatal causes totaled BRL 4,542,046,307 (Table 2). The indirect cost was BRL 19,744,770,789, of which BRL 9,751,467,172 due to premature death and BRL 9,993,303,617 due to disability (Table 3).

Table 2 Total direct costs and costs attributed to smoking, by sex, for Brazilian Unified National Health System (SUS) and supplementary health, in Brazilian Reais (BRL). Brazil, 2015.

Diseases Cost
Men Women Total attributable to smoking (men + women)
Total * Attributable to smoking Total * Attributable to smoking
Cardiac deseases 26,710,814,513 7,099,459,424 19,139,483,274 3,164,921,540 10,264,380,964
Stroke 6,567,735,100 1,251,024,227 6,432,148,992 923,206,296 2,174,230,523
COPD 11,991,177,002 9,170,718,873 10,481,665,204 6,819,463,903 15,990,182,776
Pneumonia 466,538,203 94,626,804 384,141,825 51,445,899 146,072,702
Cancer of lung 1,877,966,347 1,630,924,926 1,023,252,825 654,659,917 2,285,584,843
Other types of cancer 6,902,454,354 3,164,087,473 4,746,669,814 837,734,377 4,001,821,850
Passive smoking and other causes - 3,047,874,475 - 1,494,171,832 4,542,046,307
Total 54,516,685,354 25,458,716,202 42,207,361,277 13,945,603,762 39,404,319,956

COPD: chronic obstrutive pulmonary disease.

* Total cost of diseases estimated by the model.

Table 3 Indirect cost attributable to smoking, by sex, in Brazilian Reais (BRL). Brazil, 2015.

Indirect cost Men Women Total * %
Premature death 8,318,500,168 1,432,967,004 9,751,467,172 49
Disability 7,617,250,799 2,376,052,818 9,993,303,617 51
Total 15,935,750,967 3,809,019,822 19,744,770,789 100

* Without discount.

Expected effects of cigarette sales price increases by increasing taxes

In 10 years, the impact produced by increases in cigarette prices expressed in economic benefits would vary from BRL 55.1 billion (price increase of 25%) to BRL 128.8 billion (increase of 75%). With a 50% price increase, the number of averted deaths would vary from 68,241 to 204,723. Averted cardiac diseases and strokes would total 507,451 and 100,365 cases, respectively. For cancer, the projection would be 64,382 averted cases (Table 4).

Table 4 Total benefit in averted health outcomes, averted costs to society, and additional tax revenue based on cigarette price increase scenarios in 10 years, Brazil.

Scenarios *
25% 50% 75%
Health outcomes
Averted deaths 68,241 136,482 204,723
Averted cardiac diseases 253,725 507,451 761,176
Averted stroke 50,182 100,365 150,547
Averted cancer cases 32,192 64,382 96,575
Averted costs to society
Direct (BRL billion) - A 16.3 32.5 48.8
Averted losses in productivity (BRL billion) - B 10.0 20.0 30.0
Tax revenue
Increase in excise tax revenue (BRL billion) - C 28.8 45.4 50
Total economic benefit (A+B+C) 55.1 97.9 128.8

* Amounts represent the percentage increase in retail cigarette sales prices due to excise tax increases.

Discussion

This study expanded the results published in 2011 10 by estimating indirect costs and developing a cigarette excise tax model. There were 156,337 deaths in 2015, or 6.3% more than in 2011 10. Factors that could explain this increase would be a difference in smoking prevalence between age groups and the 11% population growth from 2007 to 2015, the year of the first and current estimates, respectively (IBGE. http://www.ibge.gov.br, accessed on 15/Mar/2017).

Cardiac diseases, COPD, lung cancer, and stroke accounted for 65% of the deaths, maintaining the same tendency as in 2011 10. However, deaths from AMI and stroke were reduced by some 4% and 40%, respectively, also in comparison to 2011, which corroborates the downward trend in mortality from cardiovascular diseases in Brazil 43. The burden of disease was concentrated in males, with 68% of all deaths and 64% of all events. However, our results showed a reduction in the burden among men when compared to 2011, with a decline of 12% and 8% in deaths and events, respectively 10. Prevalence of smoking dropped considerably from 2008 to 2013 in both sexes, and although Brazilian men smoke more than Brazilian women 44, the reduction in prevalence and thus in the burden in men indicates an important convergence of these two indicators.

Measures to reduce exposure to second-hand smoke are a reality in Brazil (Law n. 12,546 of 2011), but before 2011 there was an increase in deaths and in the direct cost related to passive smoking and perinatal diseases (7% and 69%, respectively) 10. In newborns, the consequences of second-hand smoke include reduction in weight, stature, and head circumference 45. Thus, protective measures for non-smokers must be enforced routinely in all environments.

In recent years, Brazil has adopted a policy of increasing excise taxes on cigarettes. In 2011, an ad valorem tax rate entered into force for cigarettes, currently set at 66.7%, besides a policy of minimum prices per pack 46,47. Our results demonstrate the benefits generated for tax revenue (an increase of up to BRL 50 billion in 10 years). It is an effective measure, as demonstrated in Brazilian and international studies 41,48, contributing to the expansion of fiscal space and favoring public investments. The success with the price and excise tax policy in avoiding costs, mortality, and morbidity also assumes the joint involvement of government areas in health, the economy, and law enforcement due to the volume of the illegal cigarette market in Brazil.

The cost of disease not attributed to smoking was significant, reaching BRL 96.7 billion per year. The estimates of burden and costs of chronic diseases at the national level in adults are scarce, and the current study is intended to support policymakers and researchers in chronic diseases by providing data on the problem’s magnitude in Brazil. The direct cost attributable to smoking increased by 70% from 2011 to 2015, which could be explained by the incorporation of new technologies both in the SUS (CONITEC. http://conitec.gov.br/decisões-sobre-incorporacoes, accessed on 11/Sep/2016) and in the private supplementary health system (ANS. http://ans.gov.br, accessed on 11/Sep/2016). The indirect cost accounted for 30% of the total cost. Since this was the first such estimate in Brazil, we suggest that indirect costs should be incorporated into future studies, given their magnitude, as already observed in other countries 23,49,50,51.

Due to methodological issues, comparison of the findings with other studies is limited. Still, the results in other countries are similar to ours, presenting a heavy burden for the economy. In Europe, smoking compromises 2.5% of the annual GDP, reaching 0.55% in China 52. In the USA and Canada, smoking accounts for losses of 3% in the GDP, compared to 1% in the other countries of the Americas 2. In Brazil, the loss was 0.7% of the GDP, and tax revenue from the tobacco industry reached BRL 13 billion in 2015 46, that is, 23% of the total cost of BRL 56.89 billion. On this point, article 19 of the WHO-FCTC which deals with criminal and civil liability, raises the possibility of compensation for damages, which has already been enforced through court action in the United States 53.

The results proved robust, based on the process of calibration and validation, guaranteeing the reproducibility of the model’s results. But some limitations should be addressed. The literature points to friction cost 54, the Washington panel approach 33, and the theory of human capital 35,36 as the principal methods for calculating indirect cost. The theory of human capital may overestimate costs, especially when compared to friction costs, whose calculation is more complex 34. However, this approach was applied due to the availability of local data, the concepts’ simplicity and that of the associated calculations, and because it is also the preferred method in the guidelines for economic evaluation in Brazil 30. Another limitation was the correction of hospitalizations for the supplementary health system (private) based on a single adjustment factor 28, which was necessary given the insufficiency of data based on the ICD-10. This was the solution adopted in order for calculations of case-fatality and direct cost to be performed comprehensively. Finally, the results may be underestimated, since an association with smoking has been established for a broader set of diseases than those included in the current burden-of-disease model 4.

Cost-effective measures should be intensified in order to avoid deaths and illness from smoking, and in consequence, generating benefits for Brazilian society. The costs for society reflect an important opportunity cost, and compensation for damages is a timely topic for the debate on the tobacco control agenda. The resulting resources can be invested in the full implementation of the Framework Convention on Tobacco Control, but they should not be limited only to this purpose, since other public policies can also benefit from this compensation.

Acknowledgments

The authors wish to thank the Brazilian National Cancer Institute José Alencar Gomes da Silva and the International Development Research Centre.

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Received: July 03, 2018; Revised: November 08, 2018; Accepted: February 14, 2019

Correspondence M. Pinto Instituto Nacional de Saúde da Mulher, da Criança e do Adolescente Fernandes Figueira, Fundação Oswaldo Cruz. Av. Rui Barbosa 716, Rio de Janeiro, RJ 22250-020, Brasil. mftpinto@gmail.com

Contributors

M. Pinto participated in the collection and analysis of epidemiological data and cost data and writing and final approval of the article. A. Bardach, A. Palacios and A. Pichon-Riviere contributed in the collection and analysis of epidemiological data and cost data, development of the models, and writing and final approval of the article. A. Biz participated in the collection and analysis of epidemiological data and cost data and writing and final approval of the article. A. Alcaraz, B. Rodriguez and F. Augustovski contributed in the collection and analysis of epidemiological data and cost data, development of the models, and writing and final approval of the article.

Additional informations

ORCID: Marcia Pinto (0000-0001-7568-5014); Ariel Bardach (0000-0003-4437-0073); Alfredo Palacios (0000-0001-7684-0880); Aline Biz (0000-0002-6923-4556); Andrea Alcaraz (0000-0002-4260-8239); Belen Rodriguez (0000-0002-4497-8022); Federico Augustovski (0000-0002-2914-5022); Andres Pichon-Riviere (0000-0001-6052-025X).

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