Objective To estimate the economic burden of diseases and deaths attributable to bidi smoking in India for persons aged 30–69 years.
Methods The National Sample Survey data on healthcare expenditures, data on bidi smoking prevalence from the Global Adult Tobacco Survey and relative risks of all-cause mortality from bidi smoking are used to estimate the economic burden of diseases and deaths attributable to bidi smoking in India using a prevalence-based attributable-risk approach. Costs are estimated under the following heads: (1) direct medical expenditure of treating diseases; (2) indirect morbidity costs and (3) indirect mortality costs of premature deaths.
Findings The total economic costs attributable to bidi smoking from all diseases and deaths in India in the year 2017 for persons aged 30–69 years amount to INR805.5 billion (US$12.4 billion), of which 20.9% is direct and 79.1% is indirect cost. Men bear 93.7% of the total costs.
Conclusion The total annual economic costs of bidi smoking amount to approximately 0.5% of India’s gross domestic product, while the excise tax revenue from bidi is only half a per cent of its economic costs. The direct medical costs of bidi smoking amount to 2.24% of total health expenditure. Since the poor bear a disproportionately large share of the economic costs of bidi smoking, the unregulated use of bidi would potentially push more households in India, which incur heavy out-of-pocket expenditures on healthcare, into poverty.
- low/middle income country
- non-cigarette tobacco products
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Bidi is the second most commonly used tobacco product in India with about 72 million people aged 15 years or more using it regularly in 2017.1 Although current bidi smoking prevalence among adults declined from 9.2% in 2009–20102 to 7.7% in 2016–2017, its continued consumption could impose significant costs. Bidi contains about 0.15–0.5 g of bidi tobacco per stick, which is only one-fifth to two-thirds of the amount of tobacco in western-style cigarettes.3 Yet, the concentration of nicotine in bidi is significantly higher than that in cigarettes, and bidi’s relatively low combustibility forces smokers to inhale more deeply, resulting in greater delivery of carbon monoxide, nicotine and other components of tobacco smoke compared with cigarettes.4 Bidi smoking is a causal risk factor for many types of cancers, including cancer of the mouth, pharynx, larynx, oesophagus and lungs,5 and increases the risk of chronic bronchitis, tuberculosis and respiratory diseases.5 6
Despite the health consequences of bidi smoking, tax treatment of bidi in India has been liberal compared with other tobacco products. The total tax burden—tax as percentage of retail price—on bidi was approximately 16% before introduction of the Goods and Services Tax (GST) in July 2017.7 GST subsumed excise and value added tax, although the national calamity contingent duty (NCCD) continued to apply. GST also introduced a cess—known as compensation cess to compensate the state governments for any revenue shortfall for a period of 5 years—on all tobacco products except bidi. The total tax burden—GST + NCCD + compensation cess—on cigarettes and smokeless tobacco (SLT) is estimated to be 53% and 60%, respectively, under GST, while it is only 22% on bidi.7 This historical discrepancy in tax rates has made bidi much cheaper than cigarettes, outselling the latter by a ratio of 4.3:1 as estimated from the Global Adult Tobacco Survey (GATS), 2016–2017.1 Moreover, while current cigarette smoking prevalence among adults is 4%, it is 7.7% for bidi.1
Given bidi’s popularity in India, it is important to highlight the enormous costs bidi smoking imposes on smokers and on their families and the nation. A study8 by the Ministry of Health, Government of India in collaboration with WHO estimated that the total direct and indirect costs attributable to tobacco use from all diseases in India in 2011 was INR1045 billion—1.16% of the gross domestic product (GDP). This study, however, did not give a breakdown of costs for bidi. No previous study has ever estimated the economic costs of bidi smoking in India.
This study uses several data sources. The 71st round of the National Sample Survey (NSS) in 2014—Social Consumption in India: (Health)9—is used to estimate healthcare expenditures. This nationally representative survey collected data on utilisation and expenditure with respect to private and public healthcare services—inpatient hospitalisation during the 365 days prior to the date of interview and outpatient visits during the 15 days prior to interview—from 36 480 rural and 29 452 urban households. Expenditures on medicines, surgeon fees, laboratory tests, transportation, lodging, loss of household income incurred during illness episodes were recorded. These allow one to compute average expenditures under different categories. The GATS-2016–20171 is used to estimate bidi smoking prevalence. GATS is a nationally representative household survey of persons ≥15 years across all 30 states of India and two union territories and uses a multistage sampling design. A total of 74 037 individual interviews were conducted with a response rate of 93%. The 68th round NSS,10 a nationally representative household survey on employment and unemployment, is used to estimate labour force participation rate (LFPR) and average wages. Besides these, data from census of India,11 Sample Registration System,12 WHO life tables for India,13 Reserve Bank of India,14 rural–urban combined Consumer Price Indices (CPIs)15 and published literature on all-cause mortality risks from bidi smoking16 are used for estimating different cost components.
This study estimates the economic burden of bidi smoking for all diseases and deaths together using all-cause mortality risk due to bidi smoking. A disease-specific approach is not feasible due to the unavailability of relative risks of mortality (RR) for bidi smoking for individual diseases. Three major types of costs are considered: (1) direct medical expenditure of treating diseases, including cost of medicine, surgeon fees, bed charges and costs of diagnostic tests and patient transportation; (2) indirect morbidity costs, including non-medical expenditures such as transportation and lodging charges for caregivers and loss of household income during hospitalisation or outpatient visits and (3) indirect mortality costs of premature deaths attributable to bidi smoking.
A prevalence-based attributable-risk approach is used for estimating the direct medical costs and the indirect morbidity costs.17 18 The human capital approach19 20 is used to estimate the costs of premature mortality, and the expected value of loss of future productivity caused by premature deaths attributable to bidi smoking is estimated. Costs are estimated separately for males and females ages 30–69, because the RR for bidi smoking is available for this age group only. The main effects of smoking on mortality occur after age 25 and assignment of underlying causes of death is less reliable for persons above 69 years.16 Cost estimates are converted to 2017 prices using CPI15 with 2012 as the base year. The detailed methodology is described below.
Estimation of bidi smoking-attributable fraction
The bidi smoking-attributable fraction (SAF) is the proportion of expenditure on healthcare, morbidity and mortality attributable to bidi smoking, estimated using an epidemiological formula18:
Subscript g indicates gender. P and RR denote the prevalence of ever-bidi smoking (defined as current + former use prevalence) and the RR of all-cause mortality for bidi smoking compared with never smokers (of any smoked tobacco products), respectively. To estimate the indirect mortality costs, SAFs are estimated by gender and 5-year age groupings. The estimated SAFs are multiplied with each cost measure to arrive at the bidi smoking-attributable costs.
GATS asked respondents the following questions on bidi smoking: ‘Do you currently smoke tobacco (bidi, in this case) on a daily basis, less than daily or not at all?’ Those who answered ‘not at all’ were asked a follow-up question: ‘In the past, have you smoked tobacco on a daily basis, less than daily or not at all?’ While the answers to these questions gave a direct measure of current bidi smoking prevalence, it did not give a direct measure of former bidi smoking prevalence, as the follow-up question was for all smoking. To estimate former bidi smoking, the proportion of current bidi smoking in current smoking is estimated and multiplied the same with the former smoking, assuming that same proportion will hold for former bidi smoking prevalence too. This method is followed for each 5-year age and gender subgroup as well as for the combined 30–69 age group by gender. The prevalence of ever-smoking of bidi had to be used in the calculation of SAF, since the RRs used in this study were estimated using comparisons of ever-bidi smokers vis-à-vis never smokers. The RR for bidi smoking for the age group 30–69—male (1.6, 95% CI 1.5 to 1.7) and female (2.2, 95% CI 1.9 to 2.5)—is directly obtained from a nationally representative case–control study on smoking and deaths in India.16
The NSS data on health expenditures report that public sector providers service approximately 42% and 32% of inpatient hospitalisation and 28% and 21% of outpatient visits in rural and urban areas, respectively. Since institutional expenses are not adequately reflected in subsidised services from most public service providers, the ailment-specific average expenditure for each of the ailments from private providers was computed and imputed to those receiving treatment from public providers. Average expenditures for all ailments combined are estimated after these imputations. Pregnancy-related expenditures incurred, if any, are not counted while estimating the averages.
Direct medical costs
Bidi smoking-attributable direct healthcare expenditures (BDE) are estimated by multiplying the SAF with the corresponding direct healthcare expenditures (DE):
where subscript g indicates gender. EIP is the average expenditure per inpatient hospitalisation, NIP is the average number of inpatient hospitalisations per person (averaged over the full subgroup) in 365 days, EOP is the average expenditure per outpatient visit and NOP is the average number of outpatient visits per persons for 15 days prior to the date of interview. EIP, in turn, is computed from expenditures on doctor fees, medicines, diagnostic tests, bed charges, other medical expenses and patient transportation, as obtained directly from the survey. Similarly, EOP is computed from expenditures on similar items (except bed charges) for outpatient visits. The 15-day average values for outpatient expenditures are multiplied by 24.33 to convert them to annual values. N is the population in the age group 30–69 in 2017 obtained from population projections by the census.11
Indirect morbidity costs
Bidi smoking-attributable indirect morbidity costs (BIE) are estimated by multiplying the SAF with the corresponding indirect morbidity costs (ie):
TIP and TOP are the average expenditure on transportation and lodging charges for caregivers per inpatient hospitalisation and outpatient visit, respectively, estimated from the 71st round NSS. These expenditures were given under a single head in the survey. YIP and YOP are the income loss to the whole household due to inpatient hospitalisation and outpatient visits, respectively. However, the loss of household income is directly reported for outpatient visits only, and in order to compute the same for inpatient hospitalisation, the average daily wages and LFPR are estimated from the 68th round NSS.10 Then, YIP is computed as, YIP=(average duration of inpatient hospitalisation)x(LFPR)x(average wages). NIP is the average number of hospitalisations per person (averaged over the full subgroup) in 365 days and NOP is the average number of outpatient visits per person for 15 days prior to the date of interview. The 15-day average values were converted to annual values as before.
Sampling weights are used to estimate average expenditures in equations (2) and (3), so that the estimated averages could be used as nationally representative. All estimated averages are statistically significant at 95% CI.
Premature mortality costs
Estimating the bidi smoking-attributable costs of premature mortality involved two steps: (1) estimating the total number of premature deaths attributable to bidi smoking and (2) estimating the expected present value of future productivity lost for each of those deaths. The product of (1) and (2) gives the bidi smoking-attributable premature mortality costs.
To estimate the total number of premature deaths attributable to bidi smoking, all-cause deaths attributable to bidi smoking stratified by gender and 5-year age groups are estimated by multiplying the SAFs with the corresponding number of deaths in each age group obtained from the Sample Registration System.12 To estimate the expected present value of future productivity lost from bidi smoking-attributable deaths, the present value of foregone lifetime earnings (PVLE) for each person at age of death is estimated. The PVLE is estimated by gender and 5-year age groupings based on an approach20 which took into account life expectancy by gender and 5-year age groupings, LFPR, current pattern of earnings at successive ages, and a discount rate to convert a stream of future earnings into its present value. An empirically estimated social discount rate of 3.6%—a simple average of two social discount rates (2% and 5.2%) estimated for India21 22—is used to convert the stream of future earnings into its present value. To account for potential growth in future earnings, an annual average productivity growth rate of 7.3% was assumed, which is the geometric mean of the 10 years of annual GDP growth rates from 2007–2008 to 2016–2017 in India.14
Table 1 presents the prevalence of ever-bidi smoking and the estimated SAF for the age group 30–69 by gender, as estimated from equation 1. The estimated SAF implies that bidi smoking is responsible for about 12.8 in every 100 deaths among men aged 30–69 years. The same SAF is also applied to the expenditures estimates. For example, bidi smoking is responsible for INR12.8 out of every INR100 spent on treatment for men aged 30–69 years. For women in this age group, only INR2.5 of every INR100 spent is attributed to bidi smoking. There is considerable variation in the SAF across men and women because the ever-bidi smoking prevalence is about 24.5% among men aged 30–69 years, but only about 2.1% among women in the same age group.
Table 2 shows the estimated total costs along with their different components for the age group 30–69. The total direct and indirect costs attributable to bidi smoking in this age group amount to INR805.5 billion (US$12.4 billion) or INR1588 per capita in 2017. Direct medical costs amount to INR168.7 billion (US$2.6 billion), contributing 20.9% of the total costs. Indirect costs constituted a major proportion, contributing 79.1% of the total costs at INR636.8 billion (US$9.8 billion). About 389 000 deaths were attributable to bidi smoking in 2017 and the cost of premature mortality was substantial (INR527.4 billion), constituting 65.5% of total costs and 82.8% of indirect costs. This shows that family members bear an enormous economic burden due to the premature death of a bidi smoker, resulting in loss of future wage incomes for the whole family. Indirect morbidity costs consisting of non-medical expenditures such as transportation and lodging charges for caregivers and loss of household income during hospitalisation and outpatient visits account for as much as 17.2% of the total indirect costs and amount to INR109.4 billion (US$1.7 billion). The total economic costs attributable to bidi smoking are disproportionately shared by men, who account for 93.7% of the total costs, largely owing to the fact that the prevalence of bidi smoking among men in the 30–69 age group is nearly 12 times higher compared with women.
To put these estimates in context, table 3 compares them with certain outcome indicators. The excise tax revenue from bidi in the year 2016–2017 amounted to INR4.17 billion or half a per cent of the economic costs of bidi smoking. The direct medical cost of bidi smoking amounted to 2.2% of total private and public health expenditures in the FY 2016–2017. The total economic costs of bidi amounted to approximately 0.5% of India’s GDP.
This study, for the first time, estimates the economic costs of bidi smoking in India and finds that the total annual economic costs for persons aged 30–69 amounted to INR805.5 billion (US$12.4 billion) in 2017. The direct medical costs accounted for 21% (INR168.7 billion) of total costs. In comparison, the total economic costs attributable to smoking alone for the age group 35–69 was INR 811.2 billion (US$12.5 billion) in India in 2011.8 An earlier estimate for the year 2004 had estimated the economic costs of smoking (excluding premature mortality costs) to be US$1.3 billion.23 There are no estimates of economic costs of bidi smoking specifically with which to compare the present estimates. While both previous estimates used a disease-specific approach to estimate the costs, the present study uses an all-cause mortality approach. Moreover, while the earlier studies estimated costs for the 35–69 age group, the present study estimates costs for 30–69 age group and uses updated health expenditures, prevalence and population data.
The huge healthcare burden attributable to bidi smoking in India has several implications. The share of out-of-pocket healthcare spending in total household spending is about 6.8% in India24 and roughly 18% of Indian households face catastrophic expenditures due to healthcare costs.25 Diseases associated with bidi smoking add to this, potentially pushing more people into poverty. In India, over 63 million people are pushed into poverty every year due to healthcare costs and about 15 million are pushed into poverty due to spending on tobacco and associated health expenditures.26 Expenditure on tobacco also crowds out expenditure on food and education in India, especially among the poor.27 Given that bidi smoking in India is more prevalent among lower SES groups than the rest, it is likely that much of the bidi-related illnesses and associated economic costs would also be higher among the poor. Thus, high spending on bidi coupled with associated healthcare burden can thrust bidi smokers into a vicious circle of smoking, ill health and poverty. The economic costs of bidi smoking also reflect an important gender dimension, with 93.7% costs accounted for by men. Yet, an entire household shares the consequent toll on household income.
Considering the enormous costs bidi smoking imposes and given that bidi accounts for approximately 81% of smoked tobacco in India as estimated from GATS,1 tobacco taxation policies must more effectively target bidi smoking in the interest of public health. Arguments such as ‘bidi industry generates high employment’ and ‘bidi taxes are regressive’ are often highlighted. These arguments, however, are not tenable. For example, bidi smoking prevalence among illiterate adult men in India is about 29.4% and that among adults with secondary and above education is 4.7%.1 However, lower SES groups are relatively price sensitive. The own-price elasticity for bidi is estimated to be −0.43 among low-income households, while it is −0.08 among high-income households in India.28 Hence, a tax hike on bidi will result in relatively larger consumption reduction among the poor than the rich, mitigating possible tax regressivity.
The employment claims about the bidi industry are largely inflated. According to GOI, about 4.8 million workers registered under labour welfare organisations are engaged in the bidi industry.29 However, it is unclear if these are full-time employees. Published literature indicates that the bidi industry employs about 3.4 million full-time workers, comprising only 0.7% of the employment in all sectors combined.30 In fact, 95% of bidi production in India is concentrated in 10 states and there are only two states, West Bengal and Jharkhand, where full-time bidi employment constitutes 2%–2.5% of total employment in all sectors. In all other states, it is well below 1%.30 Moreover, studies show that bidi workers are largely exploited by the industry.31 Total compensation offered to bidi workers constitutes only 0.38% of compensation to workers in unorganised manufacturing, although the bidi industry contributes 11% to unorganised manufacturing employment.30 The government should tax bidi on a par with other tobacco products and, if needed, take measures to rehabilitate the few workers employed in the bidi sector, although it is quite likely that the market would find its own ways to absorb those workers in the long run.
The GST legislation implemented in 2017 was an opportunity to make tobacco taxes uniform and raise taxes on bidi. However, the total tax burden on bidi under GST remains less than half of that on cigarettes or SLT products.7 To make taxes uniform for all tobacco products, the compensation cess currently applied to cigarettes and SLT should be applied to bidi as well. This would also help communicate the important public health message that all tobacco products are equally harmful. Additionally, the GST exemption for manufacturers with a taxable supply of less than INR2 million should not be applied to sin goods such as bidi. The smaller producer exemption during the pre-GST regimen resulted in splitting of manufacturing facilities by larger manufacturers to smaller units to avoid paying taxes.32 With an average price of INR15 per pack of 25 bidi sticks, the new INR2 million exemption in GST would translate to approximately 3.3 million bidi sticks per manufacturer and, as a result, would shrink the tax base on bidi under GST, instead of increasing it as originally intended. As these exempted bidi sticks are still subject to the GST through the wholesale distribution channel where the turnover is likely more than INR2 million, the negative impact of the exemption on revenue might be reduced.
These estimated costs attributed to bidi smoking are likely conservative for several reasons. First, the reported income lost to households due to hospitalisation and outpatient visits may underestimate the true productivity loss, as casual labourers, self-employed or unemployed may not report loss of income. Second, LFPR for women in India is low compared with men, which can lead to the underestimation of the attributable premature mortality costs that take into account foregone earnings. Third, the estimated direct medical costs would only represent the costs of those who sought medical care which can be relatively low in India, where healthcare utilisation is abysmally low,33 especially among the lower socio economic status groups, due to lack of financial resources and access to healthcare.
This study has limitations. First, RR is used to estimate costs from attributable morbidity even though the risks of morbidity and mortality from bidi smoking need not be the same. However, previous studies34–36 have widely used this approach. Second, former bidi smoking prevalence is estimated from the former all-smoking prevalence, with the assumption that the proportion of former bidi smoking prevalence in total former smoking prevalence is the same as the proportion of current bidi smoking prevalence in current all-smoking prevalence. To the extent this assumption does not hold, the estimate of SAF may be biased.
This study estimates the annual economic costs of bidi smoking for the age group 30–69 to be INR805.5 billion (US$12.4 billion) in 2017 or 0.5% of GDP. An earlier study30 estimated the annual economic output of bidi employment to be INR38 billion in 2014, which translates to approximately INR43 billion (US$0.66 billion) in 2017 if adjusted for inflation. Bidi smoking is a severe threat to the public health and national exchequer. Despite overwhelming evidence on the effectiveness of taxing tobacco products,37 taxation as a tool to regulate bidi smoking has been highly underutilised in India. It has been alleged that political clout by the bidi industry is hindering higher taxation on bidi.38 Certainly, there is an economic rationale for increased taxation on bidi as this study demonstrates.
Allowing bidi consumption to continue unhindered would make income distribution even more regressive, as the poor will continue to bear a disproportionately large share of economic costs from bidi smoking due to their higher bidi smoking prevalence. Moreover, it could become a major resource drag on the national exchequer by way of increased economic costs. The present tax burden of about 22% on bidi should be increased to WHO-recommended rate of 75%.
What this paper adds
What is already known on this subject
Bidi is the second most commonly used tobacco product in India with about 72 million people aged 15 years or more using it regularly in 2017. Yet, the tax treatment of tobacco products in India—even under the recently rolled out Goods and Services Tax—is quite favourable to bidi, which is largely used by lower SES.
What important gaps in knowledge exist on this topic
There is no estimate of the actual economic costs of bidi smoking in India or elsewhere. Such estimates are necessary to inform public policy, especially on the taxation of bidi on a par with other equally harmful tobacco products.
What this paper adds
This paper finds that the total annual economic costs of bidi smoking amount to 0.5% of India’s gross domestic product and its direct medical costs amount to 2.24% of total health expenditure. Since the poor bear a disproportionately large share of the economic costs of bidi smoking the unregulated use of bidi would be a major resource drag on the national exchequer.
Contributors RMJ is the sole author of this study.
Funding The Campaign for Tobacco-Free Kids.
Competing interests None declared.
Patient consent Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
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