Few studies to date have characterized daily exclusive e-cigarette users, device characteristics, and use behaviors. This study describes daily e-cigarette user characteristics, and assesses the ...association between user behaviors and demographics.
From 2015-2017, 100 daily exclusive e-cigarette users and 50 non-users were recruited in Maryland, USA. Sociodemographic characteristics, health status, e-cigarette/tobacco use behaviors, device characteristics, and reasons for e-cigarette use were collected by interview. Chi-squared tests (categorical variables), Student's t-test (continuous variables), and linear regressions were used to assess relationships between variables.
Most daily exclusive e-cigarette users were men, White, former smokers, used MODs/tanks, and vaped on average 365 puffs/day (SD: 720). A third of users first vaped within 5 minutes of waking in the morning, and 56% vaped throughout the day. E-liquid consumption ranged from 5-240 mL/week (median: 32.5), with nicotine concentration 0-24 mg/mL (median: 3). E-cigarette users were more likely to report wheezing/whistling and hypertension than controls, although the finding was not statistically significant after adjustment. Less than half planned to quit vaping.
Daily e-cigarette users between 2015-2017 most commonly vaped MOD/tank devices. Being male and of lower education was associated with higher usage. Daily users with no intention to quit may be at risk for increased exposure to emissions from e-cigarettes that include inorganic (metals) and organic (e.g. acrolein, formaldehyde) compounds with known toxic effects, particularly to the lung. Further research is needed to characterize the long-term health effects of daily e-cigarette use.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Lung cancer is one of the most commonly diagnosed cancers and the leading cause of cancer-related death worldwide. Although smoking is the primary cause of the cancer, lung cancer is also commonly ...diagnosed in people who have never smoked. Currently, the proportion of people who have never smoked diagnosed with lung cancer is increasing. Despite this alarming trend, this population is ineligible for lung screening. With the increasing proportion of people who have never smoked among lung cancer cases, there is a pressing need to develop prediction models to identify high-risk people who have never smoked and include them in lung cancer screening programs. Thus, our systematic review is intended to provide a comprehensive summary of the evidence on existing risk prediction models for lung cancer in people who have never smoked.
Electronic searches will be conducted in MEDLINE (Ovid), Embase (Ovid), Web of Science Core Collection (Clarivate Analytics), Scopus, and Europe PMC and Open-Access Theses and Dissertations databases. Two reviewers will independently perform title and abstract screening, full-text review, and data extraction using the Covidence review platform. Data extraction will be performed based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS). The risk of bias will be evaluated independently by two reviewers using the Prediction model Risk-of-Bias Assessment Tool (PROBAST) tool. If a sufficient number of studies are identified to have externally validated the same prediction model, we will combine model performance measures to evaluate the model's average predictive accuracy (e.g., calibration, discrimination) across diverse settings and populations and explore sources of heterogeneity.
The results of the review will identify risk prediction models for lung cancer in people who have never smoked. These will be useful for researchers planning to develop novel prediction models, and for clinical practitioners and policy makers seeking guidance for clinical decision-making and the formulation of future lung cancer screening strategies for people who have never smoked.
This protocol has been registered in PROSPERO under the registration number CRD42023483824.
Electronic cigarettes (e-cigarettes) have become popular, in part because they are perceived as a safer alternative to tobacco cigarettes. An increasing number of studies, however, have found toxic ...metals/metalloids in e-cigarette emissions.
We summarized the evidence on metal/metalloid levels in e-cigarette liquid (e-liquid), aerosols, and biosamples of e-cigarette users across e-cigarette device systems to evaluate metal/metalloid exposure levels for e-cigarette users and the potential implications on health outcomes.
We searched PubMed/TOXLINE, Embase®, and Web of Science for studies on metals/metalloids in e-liquid, e-cigarette aerosols, and biosamples of e-cigarette users. For metal/metalloid levels in e-liquid and aerosol samples, we collected the mean and standard deviation (SD) if these values were reported, derived mean and SD by using automated software to infer them if data were reported in a figure, or calculated the overall mean (mean ± SD) if data were reported only for separate groups. Metal/metalloid levels in e-liquids and aerosols were converted and reported in micrograms per kilogram and nanograms per puff, respectively, for easy comparison.
We identified 24 studies on metals/metalloids in e-liquid, e-cigarette aerosols, and human biosamples of e-cigarette users. Metal/metalloid levels, including aluminum, antimony, arsenic, cadmium, cobalt, chromium, copper, iron, lead, manganese, nickel, selenium, tin, and zinc, were present in e-cigarette samples in the studies reviewed. Twelve studies reported metal/metalloid levels in e-liquids (bottles, cartridges, open wick, and tank), 12 studies reported metal/metalloid levels in e-cigarette aerosols (from cig-a-like and tank devices), and 4 studies reported metal/metalloid levels in human biosamples (urine, saliva, serum, and blood) of e-cigarette users. Metal/metalloid levels showed substantial heterogeneity depending on sample type, source of e-liquid, and device type. Metal/metalloid levels in e-liquid from cartridges or tank/open wicks were higher than those from bottles, possibly due to coil contact. Most metal/metalloid levels found in biosamples of e-cigarette users were similar or higher than levels found in biosamples of conventional cigarette users, and even higher than those found in biosamples of cigar users.
E-cigarettes are a potential source of exposure to metals/metalloids. Differences in collection methods and puffing regimes likely contribute to the variability in metal/metalloid levels across studies, making comparison across studies difficult. Standardized protocols for the quantification of metal/metalloid levels from e-cigarette samples are needed. https://doi.org/10.1289/EHP5686.
Full text
Available for:
CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
PDF
