Variation in smoking attributable all-cause mortality across municipalities in Belgium, 2018: application of a Bayesian approach for small area estimations.

BACKGROUND: Smoking is one of the leading causes of preventable mortality and morbidity worldwide, with the European Region having the highest prevalence of tobacco smoking among adults compared to other WHO regions. The Belgian Health Interview Survey (BHIS) provides a reliable source of national and regional estimates of smoking prevalence; however, currently there are no estimates at a smaller geographical resolution such as the municipality scale in Belgium. This hinders the estimation of the spatial distribution of smoking attributable mortality at small geographical scale (i.e., number of deaths that can be attributed to tobacco). The objective of this study was to obtain estimates of smoking prevalence in each Belgian municipality using BHIS and calculate smoking attributable mortality at municipality level. METHODS: Data of participants aged 15 + on smoking behavior, age, gender, educational level and municipality of residence were obtained from the BHIS 2018. A Bayesian hierarchical Besag-York-Mollie (BYM) model was used to model the logit transformation of the design-based Horvitz-Thompson direct prevalence estimates. Municipality-level variables obtained from Statbel, the Belgian statistical office, were used as auxiliary variables in the model. Model parameters were estimated using Integrated Nested Laplace Approximation (INLA). Deviance Information Criterion (DIC) and Conditional Predictive Ordinate (CPO) were computed to assess model fit. Population attributable fractions (PAF) were computed using the estimated prevalence of smoking in each of the 589 Belgian municipalities and relative risks obtained from published meta-analyses. Smoking attributable mortality was calculated by multiplying PAF with age-gender standardized and stratified number of deaths in each municipality. RESULTS: BHIS 2018 data included 7,829 respondents from 154 municipalities. Smoothed estimates for current smoking ranged between 11% [Credible Interval 3;23] and 27% [21;34] per municipality, and for former smoking between 4% [0;14] and 34% [21;47]. Estimates of smoking attributable mortality constituted between 10% [7;15] and 47% [34;59] of total number of deaths per municipality. CONCLUSIONS: Within-country variation in smoking and smoking attributable mortality was observed. Computed estimates should inform local public health prevention campaigns as well as contribute to explaining the regional differences in mortality.

Can smoking prevalence explain COVID-19 indicators (cases, mortality, and recovery)? A comparative study in OECD countries.

There are many risk factors associated with the spread of the COVID-19 pandemic, including low wind speed, fossil fuel energy production, air pollution, and smoking. Several studies argue that smoking is not a risk factor for COVID-19 morbidity among males or any other sub-group. The study aims to analyze the following research questions: (1) can smoking prevalence explain COVID-19 indicators (cases, mortality, and recovery)? Are these relationships monotonically increasing or decreasing? In an attempt to test the counter-intuitive possibility of a non-linear relationship, the proposed empirical model relaxes the assumption of monotonic change by applying the quadratic design and testing which one of the two competing models (quadratic or linear) better fits the data. Findings suggest more complex relationships between corona indices and prevalence of smoking than previously thought. These patterns might be explained by several conditions such as the attenuation of hypercytokinemia for mild levels of smoking prevalence compared with non-smokers, elevated social distancing of smokers in countries with lower smoking prevalence, and unidentified factors that should be examined in future research.

The Negative Impact of Tobacco Smoking on Health-Related Quality of Life among Saudi Adolescents During the COVID-19 Pandemic.

OBJECTIVE: This study aimed to evaluate the impact of cigarette smoking and health-related quality of life among Saudi secondary vocational students during the COVID-19 pandemic. METHODS: A convenience sample of 328 answered a web-based self-administered questionnaire based on the Youth Risky Behavior Monitoring System (YRBSS) plus the Short Form 12 (SF-12) were included in the study. The target population included all Saudi students enrolled at the Secondary Industrial Institute in Dammam, Saudi Arabia, during December 2020 and February 2021. RESULTS: Out of the total of 328 male participants, representing a response rate of 38.59%, the highest percentage of respondents were in the first year (45.4%), the mean age of the participants was 17.73 years with a standard deviation (SD) of 1.85 years. The prevalence of current smokers, past smokers, and never smokers accounted for 30.2%, 21.3%, and 48.5%, respectively. First-year students reported relatively high levels of smoking prevalence and low physical scores of health-related quality of life (HRQoL). The overall mean of HRQoL of current smokers, past smokers, and never smokers accounted for 58.60, 58.38, and 63.66, respectively. In addition, current smokers reported a relatively low physical score of HRQoL 55.73. CONCLUSION: This is the first report to explore the impact of smoking on HRQoL of Secondary Industrial Institute students in Saudi Arabia during the COVID-19 pandemic. The results indicate that smoking has a negative impact on the quality of life of vocational students. Therefore, a health strategies plan may be developed to improve the quality of life for vocational students in Saudi Arabia. OBJECTIVE: This study aimed to evaluate the impact of cigarette smoking and health-related quality of life among Saudi secondary vocational students during the COVID-19 pandemic. METHODS: A convenience sample of 328 answered a web-based self-administered questionnaire based on the Youth Risky Behavior Monitoring System (YRBSS) plus the Short Form 12 (SF-12) were included in the study. The target population included all Saudi students enrolled at the Secondary Industrial Institute in Dammam, Saudi Arabia, during December 2020 and February 2021. RESULTS: Out of the total of 328 male participants, representing a response rate of 38.59%, the highest percentage of respondents were in the first year (45.4%), the mean age of the participants was 17.73 years with a standard deviation (SD) of 1.85 years. The prevalence of current smokers, past smokers, and never smokers accounted for 30.2%, 21.3%, and 48.5%, respectively. First-year students reported relatively high levels of smoking prevalence and low physical scores of health-related quality of life (HRQoL). The overall mean of HRQoL of current smokers, past smokers, and never smokers accounted for 58.60, 58.38, and 63.66, respectively. In addition, current smokers reported a relatively low physical score of HRQoL 55.73. CONCLUSION: This is the first report to explore the impact of smoking on HRQoL of Secondary Industrial Institute students in Saudi Arabia during the COVID-19 pandemic. The results indicate that smoking has a negative impact on the quality of life of vocational students. Therefore, a health strategies plan may be developed to improve the quality of life for vocational students in Saudi Arabia.

Association of teleworking and smoking behavior of U.S. wage and salary workers.

INTRODUCTION: The COVID-19 pandemic has led to a major shift in workspace from office to home. This report examined how telecommuting is related to smoking behavior of wage and salary workers. METHODS: Self-reported smoking behavior of 1,390 U.S. wage and salary workers aged 16-64 years from the Tobacco Use Supplement of the Current Population Survey 2018/19 were linked to the 2018 American Time Use Survey. Weighted multivariate logistic regression predicting smoking probability and generalized linear regression predicting smoking intensity were used for analysis. RESULTS: Almost a fifth (19%) of wage and salary workers reported working from home and over a half (52%) reported working in telecommuting amenable occupations. Nearly 12% were current smokers, smoking 14.7 cigarettes daily on average. Compared to their counterparts, smoking prevalence (percentage points) was lower among those employed in telecommuting amenable occupations (-0.52, p < .001 for all; 0.01, p = .862 for men; -2.40, p < .001 for women) and who worked more frequently from home (-0.21, p < .001 for all; -0.76, p < .001 for men; -0.03, p = .045 for women). Smoking intensity (cigarettes per day) was lower among those employed in telecommuting amenable occupations (-3.39, p = .03 for all; -0.36, p = .90 for men; -4.30, p = .21 for women). We found no statistically significant association between smoking intensity and telecommuting frequency. CONCLUSIONS: The lower likelihood of smoking and lower level of smoking intensity among telecommuting wage and salary workers suggests the need for proactive efforts to address the potential exacerbation in occupation-related smoking disparities between occupations that are and are not amenable to telecommuting.