Dataset Information

Potential revenue from taxing e-cigarettes and comparison of annual costs of daily e-cigarette use versus daily cigarette smoking among South African adults.

ABSTRACT:

Introduction

To inform policy making under the proposed The Control of Tobacco and Electronic Delivery Systems Bill, we compared annual costs of using e-cigarettes versus cigarettes, and estimated revenue from e-cigarette taxation.

Methods

We extracted e-cigarette retail prices from 231 South African e-cigarette vendor websites. We compared annual costs associated with daily cigarette smoking (self-reports from daily smokers in the 2018 South African Social Attitudes Survey, SASAS) versus daily e-cigarette use (based on cumulative costs of consumables plus device costs). We estimated revenue from excise tax if e-cigarettes were taxed at 75% (the rate proposed by the government) and 37.5% (half of the government's proposal as a hypothetical scenario) of the cigarette excise rate. We applied the different rates to e-cigarette consumption in 2018 SASAS and projected for 2021.

Results

Mean annual cost associated with daily use was ZAR 6693 (US$460.32, based on an exchange rate of about 69 US$ to 1000 ZAR) for manufactured cigarettes; for e-cigarettes, this ranged from ZAR 8574.69/year (with price minimizing strategies) to ZAR 19780.83/year (retail products exclusively). Expected revenue from e-cigarette excise tax at 75% of the cigarette tax rate was up to ZAR 2.20 billion (95% CI: 0.96-3.44). If taxed at 37.5% of the cigarette tax rate - half of the government's proposed rate - the projected revenue was up to ZAR 1.10 billion (95% CI: 0.48-1.72). Of the projected revenue from e-cigarette excise tax at 75% of the cigarette rate, the portion attributable to hardware (device and batteries) was 61% (ZAR 1.35 billion), while the portion attributable to e-liquid was 39% (ZAR 0.86 billion).

Conclusions

Calculated daily costs were higher for e-cigarettes than cigarettes. We recommend an e-cigarette excise tax. The government's proposed tax rate may reduce youth e-cigarette access, while allowing adult smokers wishing to switch exclusively to e-cigarettes to reduce their tobacco-related harm.

SUBMITTER: Agaku IT

PROVIDER: S-EPMC7842579 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Potential revenue from taxing e-cigarettes and comparison of annual costs of daily e-cigarette use versus daily cigarette smoking among South African adults.

Agaku Israel T IT Egbe Catherine O CO Ayo-Yusuf Olalekan A OA

Tobacco induced diseases 20210129

<h4>Introduction</h4>To inform policy making under the proposed <i>The Control of Tobacco and Electronic Delivery Systems Bill</i>, we compared annual costs of using e-cigarettes versus cigarettes, and estimated revenue from e-cigarette taxation.<h4>Methods</h4>We extracted e-cigarette retail prices from 231 South African e-cigarette vendor websites. We compared annual costs associated with daily cigarette smoking (self-reports from daily smokers in the 2018 South African Social Attitudes Survey ...[more]

PMID: 33542679

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Project description:BackgroundCigarette smoking is an established cause of preventable death and often initiated during adolescence. We estimated the short- and long-term costs of cigarette smoking among currently smoking adolescents in Nigeria.MethodsA cross-sectional survey among adolescents in Oyo state, Nigeria and a review of mortality records of patients managed for lung cancer in a tertiary facility in Ibadan, Nigeria were conducted. Short-term costs estimated were: (a) average weekly costs of purchasing cigarettes by currently smoking adolescents, and (b) costs of managing at least an episode of chronic cough occurring within 12 months of the survey. Long-term costs were limited to: (a) life-time expenditure on purchasing cigarettes, and (b) direct medical and non-medical (transportation) costs of managing lung cancer. Long-term costs were first projected to the approximate year when the adolescents (mean age:16.0 ± 1.8 years) might be diagnosed with lung cancer based on the average age at presentation with symptoms of lung cancer obtained from the records (59.8 years), and then discounted to 2020 prices. This was estimated as 44 years from the base year (2020). Costs were reported in 2020 prices in Nigerian Naira (NGN) and US dollar (USD) equivalent using the Central Bank of Nigeria, June 2020 exchange rate of USD 1: NGN 360.50.ResultsApproximately 3.8% of the adolescents were current cigarette smokers. Average weekly expenditure on cigarettes was NGN 306.82 ± 5.74 (USD 0.85 ± 0.02). About 26% had experienced at least an episode of chronic cough which cost them an average of NGN 1226.81 ± 6.18 (USD 3.40 ± 0.02) to manage. Total future costs of cigarette smoking in 2020 prices for the 43 adolescents who were current smokers in the event that they develop lung cancer were approximately NGN 175.7 million (USD 487.3 thousand), NGN 871.8 million (USD 2.4 million) and NGN 4.6 trillion (USD 12.7 million) at assumed annual inflation rates of 10%, 15%, and 20% respectively and discount rate of 4.25%.ConclusionThe estimated economic costs of smoking were very high. Efforts to prevent smoking initiation among adolescents in our study area should be intensified. Interventions to subsidize the medical cost of health-related consequences of cigarette smoking are also required, especially as treatment costs are currently largely borne out-of-pocket.Supplementary informationThe online version contains supplementary material available at 10.1007/s10389-021-01644-5.

Project description:A total of 2453 smokers were interviewed in townships over two rounds of data collection. Townships are low-income, urban areas characterised by overpopulation, poor service delivery, crime, and poor socioeconomic outcomes. Township residents typically live in poverty. Data were collected from six townships in four of South Africa's nine provinces, namely Gauteng (Eldorado Park and Ivory Park), Western Cape (Khayelitsha and Mitchell's Plain), Free State (Thabong) and KwaZulu-Natal (Umlazi). These townships were chosen to represent both the geographical and racial spread of low socioeconomic areas in South Africa. Round 1 data (n = 1260) were collected from October to November 2017, and round 2 data (n = 1193) were collected from July to August 2018. The sample includes two of South Africa's four population groups: African and mixed race (locally referred to as "Coloured", which describes people of mixed Khoisan, Malay, European, and black African ancestry). Since few Whites and Asians live in townships, they were not sampled. Households were selected via a random walk through each township. One smoker per household was interviewed (if a household contained at least one available smoker). We aimed to interview 200 adult smokers (aged 18+ years) per township per round. If a household had more than one smoker, a random selection determined which smoker to interview. Respondents were asked about their most recent cigarette purchase, specifically packaging type (single stick, pack, or carton), number of items purchased, brand, type of outlet where the cigarettes were bought, and the total amount paid for cigarettes. Respondents were also asked about other tobacco use in the household, and about their perceptions regarding illegal cigarettes. Socioeconomic and demographic information was collected at the individual and household level. The data has been used to estimate illicit trade (https://tobaccocontrol.bmj.com/content/early/2020/03/10/tobaccocontrol-2019-055136.info), and to analyse the determinants of smoking intensity (https://www.sciencedirect.com/science/article/pii/S2211335520300590).

Project description:IntroductionThere is increasing recognition that non-daily cigarette smoking is common in early adulthood but less is known about its stability over time, or what influences transitions to heavier or nonsmoking. We examined the stability of non-daily smoking in a sample of young adults, and tested whether social and cognitive factors predicted transitions to other smoking patterns over time.Aims and methodsParticipants were 579 young adults (18-24 years old at enrollment, 52% male) who were non-daily and never-daily cigarette smokers and California residents. Participants completed 13 waves of assessment over 3 years. We used descriptive statistics to evaluate the frequency of consistent abstinence, defined as no cigarette use at two consecutive waves and no cigarette use at any subsequent waves. Cox and logistic regression were used to test predictors of consistent abstinence.ResultsWe found that 55% of participants smoked intermittently throughout the study, while 43% were consistently abstinent by the end of the study; few transitioned to daily smoking. Stopping smoking was associated with having fewer smoking friends, smoking less in social situations, having lower positive reinforcement expectancies for smoking, and having stronger intent to quit. Post hoc analyses indicated those who stopped smoking tended to report reductions in positive reinforcement expectancies and increased intent to quit in the 6 months before stopping.ConclusionsFindings suggest a substantial minority of young adult non-daily smokers may stop on their own, but that the majority continue smoking and may require intervention. Interventions for this population should address social motives and reinforcement expectancies.ImplicationsThe majority of young adults who are non-daily cigarette smokers appear to maintain this habit over an extended period and may require intervention. Interventions that focus on reducing expectancies for positive effects of and social motives for cigarette use and on increasing intent to quit smoking may be most effective.

Dataset Information

Potential revenue from taxing e-cigarettes and comparison of annual costs of daily e-cigarette use versus daily cigarette smoking among South African adults.

Introduction

Methods

Results

Conclusions

Publications

Potential revenue from taxing e-cigarettes and comparison of annual costs of daily e-cigarette use versus daily cigarette smoking among South African adults.

Similar Datasets

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