METHODS: A search for economic evaluation studies was conducted from inception to 30 September 2022, on PubMed, Embase, Cost-Effectiveness Analysis (CEA) Registry by Tufts Medical Centre, EconLit and the NHS Economic Evaluation Database (NHS EED). Eligible studies were included if they were (1) conducted among adults ages 18 years old and older who were smokers attempting to quit for the first time; (2) compared varenicline to behaviour support with bupropion or NRT, behaviour support alone and unaided cessation; and (3) performed a CEA or cost-utility analysis. The INBs were calculated and pooled across studies stratified by country income level and study perspective using the random-effects model. Statistical heterogeneity between studies was assessed using the I2 statistic and Cochrane Q statistic.
RESULTS: Of the 1433 identified studies, 18 studies were included in our review. Our findings from healthcare system/payer perspective suggested that the use of varenicline is statistically significantly cost-effective compared with bupropion (pooled INB, $830.75 [95% confidence interval, $208.23, $1453.28]), NRTs ($636.16 [$192.48, $1079.84]) and unaided cessation ($4212.35 [$1755.79, $6668.92]) in high-income countries. Similarly, varenicline is also found to be cost-effective compared to bupropion ($2706.27 [$1284.44, $4128.11]), NRTs ($3310.01 [$1781.53, $4838.50]) and behavioural support alone ($5438.22 [$4105.99, $6770.46]) in low- and middle-income countries.
CONCLUSION: Varenicline is cost-effective as a smoking cessation aid when compared with behavioural support with bupropion or nicotine replacement therapies and behavioural support alone in both high-income countries and low- and middle-income countries, from the healthcare system/payer perspective in adult smokers who attempt to quit for the first time.
OBJECTIVE: To analyze the total and risk-attributable burden of lip and oral cavity cancer (LOC) and other pharyngeal cancer (OPC) for 204 countries and territories and by Socio-demographic Index (SDI) using 2019 Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study estimates.
EVIDENCE REVIEW: The incidence, mortality, and disability-adjusted life years (DALYs) due to LOC and OPC from 1990 to 2019 were estimated using GBD 2019 methods. The GBD 2019 comparative risk assessment framework was used to estimate the proportion of deaths and DALYs for LOC and OPC attributable to smoking, tobacco, and alcohol consumption in 2019.
FINDINGS: In 2019, 370 000 (95% uncertainty interval [UI], 338 000-401 000) cases and 199 000 (95% UI, 181 000-217 000) deaths for LOC and 167 000 (95% UI, 153 000-180 000) cases and 114 000 (95% UI, 103 000-126 000) deaths for OPC were estimated to occur globally, contributing 5.5 million (95% UI, 5.0-6.0 million) and 3.2 million (95% UI, 2.9-3.6 million) DALYs, respectively. From 1990 to 2019, low-middle and low SDI regions consistently showed the highest age-standardized mortality rates due to LOC and OPC, while the high SDI strata exhibited age-standardized incidence rates decreasing for LOC and increasing for OPC. Globally in 2019, smoking had the greatest contribution to risk-attributable OPC deaths for both sexes (55.8% [95% UI, 49.2%-62.0%] of all OPC deaths in male individuals and 17.4% [95% UI, 13.8%-21.2%] of all OPC deaths in female individuals). Smoking and alcohol both contributed to substantial LOC deaths globally among male individuals (42.3% [95% UI, 35.2%-48.6%] and 40.2% [95% UI, 33.3%-46.8%] of all risk-attributable cancer deaths, respectively), while chewing tobacco contributed to the greatest attributable LOC deaths among female individuals (27.6% [95% UI, 21.5%-33.8%]), driven by high risk-attributable burden in South and Southeast Asia.
CONCLUSIONS AND RELEVANCE: In this systematic analysis, disparities in LOC and OPC burden existed across the SDI spectrum, and a considerable percentage of burden was attributable to tobacco and alcohol use. These estimates can contribute to an understanding of the distribution and disparities in LOC and OPC burden globally and support cancer control planning efforts.
METHODS: Data came from the 2020 ITC Malaysia Survey, a web-based survey of a nationally representative sample of adults who smoked (n=1047) aged 18 and older. They were asked on ever heard of, ever used, and currently using HTPs, and their reasons for using HTPs.
RESULTS: Overall, 25.4% (n= 324; 95% CI:22.3%-28.7%) of Malaysians who smoked reported ever used HTPs with 6.7% (n=85; 95% CI:22.3%-28.7%) were using them daily and 8.1% (n=110; 95% CI:6.4% -10.2%) were using HTPs non-daily. Most of them (57.2%) who dual use were of aged 25-39 and 97.3% were males. Among those who smoked daily, almost half (49.3%) were also using HTP daily. Among those who used HTPs daily and non-daily, curiosity (84.2%, 95% CI:78.4%-90.0%), taste (83.2%, 95% CI:77.3%-89.1%), and appealing technology (78.5%, 95% CI:71.3%-85.6%) were the most reported reasons. Among those who used HTPs daily, curiosity was the top reason (87.9%, 95% CI:78.9%-93.4%), while among non-daily, taste good was the top reason (81.9%, 95% CI:71.9%-88.8%).
CONCLUSIONS: The very high use of HTPs among Malaysians who smoked requires continued public health surveillance that can inform the regulation of these novel tobacco products.
METHODS: Country-wise aggregate data from the Global Health Professions Student Survey on 'current cigarette smoking' (smoking cigarettes on 1 or more days during the past 30 days), and 'current use of tobacco products other than cigarettes' (chewing tobacco, snuff, bidis, cigars or pipes, 1 or more days during the past 30 days) were analysed. For each WHO region, we estimated mean prevalence rates of tobacco use weighted by the population of the sampling frame and aggregate proportions for 'health professionals' role' and 'cessation training' indicators using 'metaprop' command on Stata V.11.
RESULTS: A total of 107 527 student health professionals participated in 236 surveys done in four health profession disciplines spanning 70 countries with response rates ranging from 40% to 100%. Overall, prevalence of smoking was highest in European countries (20% medical and 40% dental students) and the Americas (13% pharmacy to 23% dental students). Other tobacco use was higher in eastern Mediterranean (10%-23%) and European countries (7%-13%). In most WHO regions, ≥70% of the students agreed that health professionals are role models, and have a role in advising about smoking cessation to their patients and the public. Only ≤33% of all student health professionals in most WHO regions (except 80% dental students in the Eastern Mediterranean region) had received formal training on smoking cessation approaches and ≥80% of all students agreed that they should receive formal cessation training.
CONCLUSIONS: Tobacco control should take place together with medical educators to discourage tobacco use among student health professionals and implement an integrated smoking cessation training into health professions' curricula.
SETTING: Adults interviewed during house-to-house surveys.
PARTICIPANTS: Women (15-45 years) and men (15-49 years) surveyed in four Nepal Demographic and Health Surveys done in 2001, 2006, 2011 and 2016.
OUTCOME MEASURE: Current tobacco use (in any form).
RESULTS: The prevalence of tobacco use for men declined from 66% in 2001 to 55% in 2016, and declined from 29% to 8.4% among women. Across both education and wealth quintiles for both men and women, the prevalence of tobacco use generally declines with increasing education or wealth. We found persistently larger absolute inequalities by education than by wealth among men. Among women we also found larger educational than wealth-related gradients, but both declined over time. For men, the Slope Index of Inequality (SII) for education was larger than for wealth (44% vs 26% in 2001) and changed very little over time. For women, the SII for both education and wealth were similar in magnitude to men, but decreased substantially between 2001 and 2016 (from 44% to 16% for education; from 37% to 16% for wealth). Women had a larger relative index of inequality than men for both education (6.5 vs 2.0 in 2001) and wealth (4.8 vs 1.5 in 2001), and relative inequality increased between 2001 and 2016 for women (from 6.5 to 16.0 for education; from 4.8 to 12.0 for wealth).
CONCLUSION: Increasing relative inequalities indicates suboptimal reduction in tobacco use among the vulnerable groups suggesting that they should be targeted to improve tobacco control.
METHODS: The socioeconomic trends in smoking were analyzed using data from cross-sectional National Health and Morbidity Surveys for the years 1996, 2006, and 2011. Household per capita income was used as a measure of socioeconomic position. As a measure of inequality, the concentration index that quantified the degree of socioeconomic inequality in a health outcome was computed. Smoking was assessed in current and former smokers. The study population was examined by gender, region, and age group.
RESULTS: This study found a trend of an increasingly higher smoking prevalence among the poor and higher cessation rates among the rich. With the exception of younger women in Peninsular Malaysia, the socioeconomic gradient in current smoking is concentrated among the poor. For former smokers, especially men, distributions across the years were mostly concentrated among the rich.
CONCLUSION: It is important to ensure that health policies, programs, and interventions consider the potential impact of the socioeconomic patterning in smoking on equity in health.
IMPLICATIONS: Findings on the socioeconomic gradient in smoking and cessation from Malaysia across a period of rapid economic development will contribute to addressing the paucity of knowledge on the socioeconomic gradient of smoking and cessation in other progressing LMICs. This study provides evidence from an upper-middle-income country, of an increasing trend of smoking among the poor and an increasing trend of cessation rates among the rich, particularly for men. We found opposing trends for younger adult women in the more developed, Peninsular Malaysia. More rich young women were found to have taken up smoking compared to socioeconomically less advantaged young women.
METHODS: A nationally representative survey was employed in 900 elementary, junior high, and senior high schools that were located in 60 regions or 24 provinces of Indonesia. Each school's compliance with SFZ parameters was measured using a closed-ended questionnaire. The dataset was analyzed using frequency distribution, while the chi-square was performed to analyze the measurement effect of each parameter for SFZ compliance.
RESULTS: Java Island is the region with the largest proportion of school units (10%) studied in this study, and the largest group of the schools are high schools (36.1%). In terms of SFZ compliance, 413 (45.9%) of schools had perfect compliance scores of 8, followed by 183 schools (20.3%) with a score of 7 and 107 (11.9%) with a score of 6. It was found that parameter 5, namely cigarette butts found in the school environment, had the largest proportion when a school did not apply SFZ. Cigarette butts were found in 261 (29.0%) schools. Cigarette butts found in schools contributed 7.8 times to not applying SFZ compared to schools where no cigarette cutters were found.
CONCLUSION: Although the SFZ compliance rate in Indonesian schools is 66.2% at least on 7 of 8 existed parameters, this means most of schools still aren't fully complying with the regulations for SFZs. This recent evidence will help decisionmakers to enforce tobacco control, particularly among youth, which form the pillar of national development.
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MATERIALS AND METHODS: Two thousand seven hundred students were randomly selected by proportional stratified sampling. Analyses on 1,736 non-smoking students revealed that prevalence of adolescents susceptible to smoking was 16.3%.
RESULTS: Male gender (aOR=2.05, 95%CI= 1.23-3.39), poor academic achievement (aOR 1.60, 95%CI 1.05-2.44), ever-smoker (aOR 2.17, 95%CI 1.37-3.44) and having a smoking friend (aOR 1.76, 95%CI 1.10-2.83) were associated with susceptibility to smoking, while having the perception that smoking prohibition in school was strictly enforced (aOR 0.55, 95%CI 0.32-0.94), and had never seen friends smoking in a school compound (aOR 0.59, 95%CI 0.37-0.96) were considered protective factors
CONCLUSIONS: These results indicate that follow-up programmes need to capitalise on the modifiable factors related to susceptibility to smoking by getting all stakeholders to be actively involved to stamp out smoking initiation among adolescents.
MATERIALS AND METHODS: Data were collected in two waves from a cohort of 2,552 adolescents aged 12-13 years old studying in 15 secondary schools based in Kinta, Perak. A multistage sampling method was used to select the schools and a self-administered structured questionnaire was applied to help categorize the participants into five different smoking stages. Nonsmokers were divided into never smokers and susceptible never smokers. Ever-smokers were categorized as experimenters, current smokers or ex-smokers.
RESULTS: Among the participants 46.8% were Malay, 33.5% Chinese and 17.1% Indians. At baseline, we had 85.3% non-smokers and 14.6% ever smokers. Incidence of adverse transition among all our participants was 24.1%, with a higher value among male participants (16.8%). A higher proportion of susceptible never smokers and experimenters progressed to current smoking stage compared to never smokers.
CONCLUSIONS: This study highlights the changes and patterns of adverse transition among adolescents. Male adolescents, those who are susceptible to smoking and those who had already tried experimenting with cigarettes have a higher chance of escalating to a higher smoking stage.