Physiological Effects of Electronic Cigarette: A Systematic Review and Meta-Analysis

Importance: Electronic cigarettes (e-cigs) are widely used devices that were initially created to aid in smoking cessation. However, their acute physiological effects are unclear and there have been a number of e-cig and vaping acute lung injury (EVALI) events recently reported. Objective: To conduct a systematic review and meta-analysis of studies assessing the immediate physiological effects, i.e., cardiovascular, respiratory or blood-based responses, of acute e-cig usage in humans. Data Sources: PubMed, Web of Science, Cochrane and Scopus databases were searched for published articles until 20th May 2020. Study Selection: English or French peer-reviewed articles measuring at least one physiological parameter before and after using an e-cig. Data extraction and synthesis: The study followed PRISMA guidelines and assessed article quality using the Downs and Black checklist. Independent extraction was conducted by two reviewers. Data were pooled using random effect models. Sensitivity analysis and meta-regression was performed to explore heterogeneity. Main outcomes: Systolic and diastolic blood pressure, heart rate, augmentation index (AIx75), fraction of exhaled nitric oxide (FeNO), and spirometry were the most frequently assessed parameters and were, therefore, chosen for meta-analyses. Results: Of 17102 articles screened, 37 articles were included for the qualitative synthesis, and 23 articles (800 patients) were included in the meta-analysis. Acute use of nicotine e-cig was associated with increased heart rate (SMD=0.51; 95%CI 0.34-0.68), systolic blood pressure (SMD=0.33; 95%CI 0.13 -0.52), diastolic blood pressure (SMD=0.50; 95%CI 0.26-0.73), and augmentation index AIx75 (SMD=0.580; 95%CI 0.220- 0.941), along with a decrease in FeNO (SMD=-0.327; 95%CI -0.599 – -0.055). E-cig exposure wasn't associated with significant changes in any spirometry measure. Conclusions and Relevance: Acute use of nicotine e-cigs was associated with significant cardiovascular and respiratory responses. Despite being considered safe, these devices have a physiological impact that needs to be further explored especially in term of its long-term consequences

Attitudes towards vaccines and intention to vaccinate against COVID-19: a cross-sectional analysis - implications for public health communications in Australia

Objective To examine SARS-CoV-2 vaccine confidence, attitudes and intentions in Australian adults as part of the iCARE Study. Design and setting Cross-sectional online survey conducted when free COVID-19 vaccinations first became available in Australia in February 2021. Participants Total of 1166 Australians from general population aged 18-90 years (mean 52, SD of 19). Main outcome measures Primary outcome: responses to question € If a vaccine for COVID-19 were available today, what is the likelihood that you would get vaccinated?'. Secondary outcome: analyses of putative drivers of uptake, including vaccine confidence, socioeconomic status and sources of trust, derived from multiple survey questions. Results Seventy-eight per cent reported being likely to receive a SARS-CoV-2 vaccine. Higher SARS-CoV-2 vaccine intentions were associated with: increasing age (OR: 2.01 (95% CI 1.77 to 2.77)), being male (1.37 (95% CI 1.08 to 1.72)), residing in least disadvantaged area quintile (2.27 (95% CI 1.53 to 3.37)) and a self-perceived high risk of getting COVID-19 (1.52 (95% CI 1.08 to 2.14)). However, 72% did not believe they were at a high risk of getting COVID-19. Findings regarding vaccines in general were similar except there were no sex differences. For both the SARS-CoV-2 vaccine and vaccines in general, there were no differences in intentions to vaccinate as a function of education level, perceived income level and rurality. Knowing that the vaccine is safe and effective and that getting vaccinated will protect others, trusting the company that made it and vaccination recommended by a doctor were reported to influence a large proportion of the study cohort to uptake the SARS-CoV-2 vaccine. Seventy-eight per cent reported the intent to continue engaging in virus-protecting behaviours (mask wearing, social distancing, etc) postvaccine. Conclusions Most Australians are likely to receive a SARS-CoV-2 vaccine. Key influencing factors identified (eg, knowing vaccine is safe and effective, and doctor's recommendation to get vaccinated) can inform public health messaging to enhance vaccination rates

How well do covariates perform when adjusting for sampling bias in online COVID-19 research? Insights from multiverse analyses

: COVID-19 research has relied heavily on convenience-based samples, which-though often necessary-are susceptible to important sampling biases. We begin with a theoretical overview and introduction to the dynamics that underlie sampling bias. We then empirically examine sampling bias in online COVID-19 surveys and evaluate the degree to which common statistical adjustments for demographic covariates successfully attenuate such bias. This registered study analysed responses to identical questions from three convenience and three largely representative samples (total N = 13,731) collected online in Canada within the International COVID-19 Awareness and Responses Evaluation Study ( www.icarestudy.com ). We compared samples on 11 behavioural and psychological outcomes (e.g., adherence to COVID-19 prevention measures, vaccine intentions) across three time points and employed multiverse-style analyses to examine how 512 combinations of demographic covariates (e.g., sex, age, education, income, ethnicity) impacted sampling discrepancies on these outcomes. Significant discrepancies emerged between samples on 73% of outcomes. Participants in the convenience samples held more positive thoughts towards and engaged in more COVID-19 prevention behaviours. Covariates attenuated sampling differences in only 55% of cases and increased differences in 45%. No covariate performed reliably well. Our results suggest that online convenience samples may display more positive dispositions towards COVID-19 prevention behaviours being studied than would samples drawn using more representative means. Adjusting results for demographic covariates frequently increased rather than decreased bias, suggesting that researchers should be cautious when interpreting adjusted findings. Using multiverse-style analyses as extended sensitivity analyses is recommended.COVID-19 research has relied heavily on convenience-based samples, which-though often necessary-are susceptible to important sampling biases. We begin with a theoretical overview and introduction to the dynamics that underlie sampling bias. We then empirically examine sampling bias in online COVID-19 surveys and evaluate the degree to which common statistical adjustments for demographic covariates successfully attenuate such bias. This registered study analysed responses to identical questions from three convenience and three largely representative samples (total N = 13,731) collected online in Canada within the International COVID-19 Awareness and Responses Evaluation Study (www.icarestudy.com). We compared samples on 11 behavioural and psychological outcomes (e.g., adherence to COVID-19 prevention measures, vaccine intentions) across three time points and employed multiverse-style analyses to examine how 512 combinations of demographic covariates (e.g., sex, age, education, income, ethnicity) impacted sampling discrepancies on these outcomes. Significant discrepancies emerged between samples on 73% of outcomes. Participants in the convenience samples held more positive thoughts towards and engaged in more COVID-19 prevention behaviours. Covariates attenuated sampling differences in only 55% of cases and increased differences in 45%. No covariate performed reliably well. Our results suggest that online convenience samples may display more positive dispositions towards COVID-19 prevention behaviours being studied than would samples drawn using more representative means. Adjusting results for demographic covariates frequently increased rather than decreased bias, suggesting that researchers should be cautious when interpreting adjusted findings. Using multiverse-style analyses as extended sensitivity analyses is recommended