This study identifies and analyzes X (formerly Twitter) posts related to 14 e-cigarette use prevention campaigns from 2014 to 2020, assessing message volume, content, sources, potential reach and engagement. Using supervised machine learning, we classified 618,965 tweets, finding 43% contained opposition messaging. Two regional campaigns received the highest levels of opposition, with over 99% of related tweets classified as opposition. However, prevention/neutral messages exhibited 92% higher potential reach than opposition messages. Geolocation analysis suggested that regional campaigns may have struggled to focus their impact within targeted jurisdictions. These findings illustrate the dual role of social media as both an amplifier of prevention messages and a platform for oppositional narratives, underscoring the need for public health practitioners to develop adaptive strategies to address misinformation and enhance the impact of digital campaigns.

Tobacco content on Twitter (X) generally opposes regulation. Although a near real-time data source of the public’s response to prominent events heightens the allure of extrapolating public sentiment from Twitter content, tobacco policy sentiment on the platform may be more indicative of industry-affiliated top users. We examined 2 years of tobacco policy discussion on Twitter (X) at the user level ( N = 3,159,807 posts) from September 2019 to July 2021. We sampled the 100 most followed, amplified (retweets), influential (H index), and connected (betweenness centrality) users at three different time periods: pre-COVID (September 2019 to February 2020), COVID lockdown (March 2020 to March 2021), and post vaccine rollout (April to July 2021) to characterize top users. The Louvain method was used to partition users into communities based on retweet behavior. The 100 most amplified users received between 48% and 71% of all retweets across time periods, with e-cigarette advocates dominating the most amplified (64.7%), influential (38.4%) and connected users (42.1%). The vast majority of interaction took place in communities dominated by e-cigarette advocates, but only reaching 2.5% to 8.2% of users. We identified 58 tobacco policy top users who had 1,000 or more total retweets and were among the top 100 for any of our influence metrics at more than one time period. Among top users, 50 were e-cigarette advocates, and 24 had quantifiable ties to the tobacco industry. Practitioners and researchers should be wary of mischaracterizing industry public relations on social media as public sentiment.

Introduction: Prior research on the effects of social media promotion of tobacco products has predominantly relied on survey-based self-report measures of marketing exposure, which potentially introduce endogeneity, recall, and selection biases. New approaches can enhance measurement and help better understand the effects of exposure to tobacco-related messages in a dynamic social media marketing environment. We used geolocation-specific tweet rate as an exogenous indicator of exposure to smokeless tobacco (ST)-related content and employed this measure to examine the influence of social media marketing on ST sales. Aims and Methods: Autoregressive error models were used to analyze the association between the ST-relevant tweet rate (aggregated by 4-week period from February 12, 2017 to June 26, 2021 and scaled by population density) and logarithmic ST unit sales across time by product type (newer, snus, conventional) in the United States, accounting for autocorrelated errors. Interrupted time series approach was used to control for policy change effects. Results: ST product category-related tweet rates were associated with ST unit sales of newer and conventional products, controlling for price, relevant policy events, and the coronavirus disease 2019 (COVID-19) pandemic. On average, 100-unit increase in the number of newer ST-related tweets was associated with 14% increase in unit sales (RR = 1.14; p = .01); 100-unit increase in conventional ST tweets was associated with similar to 1% increase in unit sales (p = .04). Average price was negatively associated with the unit sales. Conclusions: Study findings reveal that ST social media tweet rate was related to increased ST consumption and illustrate the utility of exogenous measures in conceptualizing and assessing effects in the complex media environment. Implications: Tobacco control initiatives should include efforts to monitor the role of social media in promoting tobacco use. Surveillance of social media platforms is critical to monitor emerging tobacco product-related marketing strategies and promotional content reach. Exogenous measures of potential exposure to social media messages can supplement survey data to study media effects on tobacco consumption.

Background E-cigarette promotion on social media coincided with the rapid growth of e-cigarette use among American youth, particularly with the increased JUUL pod vaporiser use. We examined commercial JUUL-related messages on Instagram to identify marketing appeals used to target users along the continuum of e-cigarette use; we mapped the appeals to existing theoretical marketing frameworks to better understand industry strategies. Methods Hashtag-based keyword rules were used to collect JUUL-related posts from the Instagram application programming interface, 1 March–13 November 2018. Posts were classified as commercial or non-commercial. A combination of machine learning methods, keyword algorithms and human coding were used to characterise message themes in commercial posts. Results Keyword filters captured 50 817 relevant posts and 41% were commercial. Among commercial posts, 91% contained recruitment/trial-based appeals (eg, combustible tobacco cessation; product sampling; giveaways) and 71% featured reinforcement/addiction-related appeals (eg, loyalty programmes). None of the commercial messages contained e-cigarette cessation-related appeals and less than 25% mentioned quitting combustible tobacco as a recruitment appeal. Conclusions Instagram posts featuring e-cigarette related marketing can increase exposure to persuasive messages encouraging e-cigarette trial and use particularly among susceptible youth. Stronger regulations are needed to prevent exposure to social media marketing among young social media users.

Background Social media discussion tends to follow news about proposed or enacted government policies. Thus, digital discourse surveillance may be an effective and unobtrusive way of understanding industry and public response to policies and regulations, including in the domain of tobacco control. Recently, the US Food and Drug Administration restricted sales of flavoured cartridge and disposable vape products. Historically, the tobacco industry used modification of product characteristics, labelling or packaging to work around flavour restrictions. We aimed to characterise strategies used by nicotine product manufacturers and vendors to promote flavoured products on Instagram and to identify policy workaround tactics. Methods Keyword rules were used to collect flavoured electronic cigarette-related Instagram posts from CrowdTangle, from 1 January 2019 to 31 December 2021. Posts were coded for commercial content and promotional strategies using a combination of machine learning methods, keyword algorithms and human coding. Additional exploratory analyses were conducted to identify major discussion themes. Non-English posts were excluded from the analyses. Results Keyword filters captured 113 393 relevant posts from 391 unique accounts, with 46 076 posts referencing flavour promotion (40.6%) and 2124 (2%) posts mentioning alternatives to restricted flavoured products or strategies to evade flavour sales restrictions. Promotional messages featured non-characterising flavour references, ‘off-brand’ product substitutes, promotion of new flavoured product technologies, innovation, do-it-yourself appeals, global promotion, international delivery and encouraged flavoured product stockpiling. In addition, promotion of refillable devices, e-juice, tank systems and ‘box mod’ vaporizers was present. Conclusion Social media surveillance can enhance our understanding of public health needs and policy compliance, as well as inform strategies to prevent policy evasion. Examining evolving industry tactics to promote flavoured products in response to regulatory changes can help authorities and practitioners assess policy effectiveness and inform future design and implementation approaches.

Objective: To examine conversations among JUUL users on Reddit related to restrictions on flavored ENDS and the shifting policy landscape. Methods: Posts and comments (n = 166,169) between May 2019 and May 2020 on the subreddit r/JUUL were scraped using pushshift.io API. Keyword filters were used to identify texts discussing flavored ENDS products (n = 33,884 texts). These were further narrowed down to texts discussing flavor policy workaround strategies (n = 7429) and N-gram analysis was performed. Finally, findings from the N-gram analysis were triangulated through qualitative review of a separate sample of texts (n = 488) from the flavor policy-related posts and comments. Results: Overall activity on the subreddit r/JUUL peaked around the time of the EVALI outbreak (September 2019) and when FDA issued guidance restricting flavored ENDS product sales (January 2020). The N-gram analysis revealed an active discussion of banned products one can “still get” or “JUUL compatible” alternatives, including specific brands, brick and mortar locations, and specific flavors. Ten dominant themes emerged from the qualitative review, with some posts containing more than one theme. Conclusion: Many users turned to Reddit for information related to the shifting regulatory landscape concerning flavored ENDS. Discussions focused on both legal alternatives to banned products as well as illegal means of acquiring JUUL pods, including residual retail supply, online, and mail vendors.

Social media are an important marketing platform for emerging tobacco products. Heated tobacco products (HTPs) have been introduced in a limited number of local test markets in the United States as potentially reduced-exposure tobacco products. HTPs can be used to heat tobacco as well as marijuana. However, due to growing digital media promotion of these products, it is possible that public knowledge and purchasing opportunities extend beyond test markets. Research on HTP social media promotion is sparse. The objective of the present study is to assess the amount and characterize the content of HTP-related messages on Twitter. We used keyword rules to collect HTP-related posts from the Twitter Historical Powertrack from 1 August 2016 to 31 July 2021. Posts were coded for type (organic, commercial), promotional strategies (e.g., discounts, event promotion), and marijuana co-use mentions using a combination of machine learning methods and human coding. Keyword filters captured 121,012 relevant tweets posted over the period of data collection, with 46,013 (38.02%) tweets featuring commercial content. Findings revealed that there was a two-fold increase in the monthly volume of messages from August 2016 to July 2021. The proportion of organic tweets increased from 29% of all tweets in August 2016 to 73.5% in July 2021. Approximately 20.6% of tweets included mentions of marijuana, and 5,243 posts (4.3%) contained links to online retailers. Promotional tweets featured event promotion, discounts, reduced harm appeals, and fashion appeals. Tobacco control and substance use prevention initiatives should include efforts to monitor the role of social media in promoting organic word-of-mouth and normalizing novel tobacco products.

Background: Tobacco use is the single most preventable cause of cardiovascular disease mortality and morbidity. However, evidence on associations of tobacco/nicotine and cannabis use and COVID-19 infection and severity among youth is limited. It is also unclear if associations between tobacco and cannabis use with COVID-19 are similar to other acute respiratory infections (ARIs). Methods: We used data from Fall-2020 and Spring-2021 ACHA-NCHA surveys. Multivariable multinomial and binary logistic regression models were used to estimate the odds of COVID-19 infection/severity and other ARIs by tobacco/nicotine product or cannabis use within last 3 months. Results: Of 69,868 students ages 18-24, 70% were female, 0.7% with COVID-19 confirmed-severe, 5% confirmed-moderate, 8% confirmed-mild/asymptomatic, 23% with any ARIs, 18% using any tobacco/nicotine products, and 16% using cannabis. With multiple adjustments, users of only e-cigarettes, only other tobacco products, or dual/poly products (vs. non-users) were nearly 2 times more likely to have COVID-19 (vs. confirmed-negative). A similar pattern of associations was observed for tobacco/nicotine product use and ARIs. Cannabis use had no association with COVID-19 infection, but cannabis users had 8% higher odds of ARIs than non-users. Of 9,380 COVID-19 confirmed students, no association of tobacco/nicotine product use with COVID-19 severity was observed, but cannabis users had 17% higher odds of severe/moderate (vs. mild/asymptomatic) symptoms than non-users. Conclusion: Aong US college students, e-cigarette or dual/poly-product users are more likely to have COVID-19 and other acute respiratory infections. Cannabis users were more likely to have more severe COVID-19 symptoms than non-users; they were also more likely to have other acute respiratory infections.

Background There is a lot of misinformation about a potential protective role of nicotine against COVID-19 spread on Twitter despite significant evidence to the contrary. We need to examine the role of vape advocates in the dissemination of such information through the lens of the gatewatching framework, which posits that top users can amplify and exert a disproportionate influence over the dissemination of certain content through curating, sharing, or, in the case of Twitter, retweeting it, serving more as a vector for misinformation rather than the source. Objective This research examines the Twitter discourse at the intersection of COVID-19 and tobacco (1) to identify the extent to which the most outspoken contributors to this conversation self-identify as vaping advocates and (2) to understand how and to what extent these vape advocates serve as gatewatchers through disseminating content about a therapeutic role of tobacco, nicotine, or vaping against COVID-19. Methods Tweets about tobacco, nicotine, or vaping and COVID-19 (N=1,420,271) posted during the first 9 months of the pandemic (January-September 2020) were identified from within a larger corpus of tobacco-related tweets using validated keyword filters. The top posters (ie, tweeters and retweeters) were identified and characterized, along with the most shared Uniform Resource Locators (URLs), most used hashtags, and the 1000 most retweeted posts. Finally, we examined the role of both top users and vape advocates in retweeting the most retweeted posts about the therapeutic role of nicotine, tobacco, or vaping against COVID-19. Results Vape advocates comprised between 49.7% (n=81) of top 163 and 88% (n=22) of top 25 users discussing COVID-19 and tobacco on Twitter. Content about the ability of tobacco, nicotine, or vaping to treat or prevent COVID-19 was disseminated broadly, accounting for 22.5% (n=57) of the most shared URLs and 10% (n=107) of the most retweeted tweets. Finally, among top users, retweets comprised an average of 78.6% of the posts from vape advocates compared to 53.1% from others (z=3.34, P<.001). Vape advocates were also more likely to retweet the top tweeted posts about a therapeutic role of nicotine, with 63% (n=51) of vape advocates retweeting at least 1 post compared to 40.3% (n=29) of other top users (z=2.80, P=.01). Conclusions Provaping users dominated discussions of tobacco use during the COVID-19 pandemic on Twitter and were instrumental in disseminating the most retweeted posts about a potential therapeutic role of tobacco use against the virus. Subsequent research is needed to better understand the extent of this influence and how to mitigate the influence of vape advocates over the broader narrative of tobacco regulation on Twitter.

In today's complex media environment, does media coverage influence youth and young adults' (YYA) tobacco use and intentions? We conceptualize the "public communication environment" and effect mediators, then ask whether over time variation in exogenously measured tobacco media coverage from mass and social media sources predicts daily YYA cigarette smoking intentions measured in a rolling nationally representative phone survey (N = 11,847 on 1,147 days between May 2014 and June 2017). Past week anti-tobacco and pro-tobacco content from Twitter, newspapers, broadcast news, Associated Press, and web blogs made coherent scales (thetas = 0.77 and 0.79). Opportunities for exposure to anti-tobacco content in the past week predicted lower intentions to smoke (Odds ratio [OR] = 0.95, p < .05, 95% confidence interval [CI] = 0.91-1.00). The effect was stronger among current smokers than among nonsmokers (interaction OR = 0.88, p < .05, 95% CI = 0.77-1.00). These findings support specific effects of anti-tobacco media coverage and illustrate a productive general approach to conceptualizing and assessing effects in the complex media environment.

Twitter is an important avenue through which tobacco regulation evolves in the public consciousness. That said, prior research has identified the spread of mis and dis-information regarding tobacco products on Twitter and a possibly disproportionate influence of e-cigarette advocates on the platform taking an anti-regulatory stance. To examine the most influential users discussing tobacco regulation on Twitter. We used a keyword filter (F1 = .91) to identify N=3,159,807 tobacco-policy tweets by n=58,369 users from the full corpus of tobacco-related content between the vaping-associated lung injury outbreak starting in August 2019, continuing through the period before (period 1), during (period 2), and after pandemic stay-at-home orders (period 3), and through the months following vaccination rollout, up to July 2021. Top users by retweets and sustained influence (H index) were identified and coded. Total posts and retweets received were heavily concentrated among the top 100 users at each of three time periods. The top 100 most retweeted users posted 8.5%, 21.4% and 34.6% of all original tweets during periods 1, 2 and 3, respectively and 56%, 48%, and 70% of all retweets. The 100 users with the top H index posted 8.3% of all content, 17.5%, and 27.3% with those posts accounting for 23.1%, 37.5%, and 16.9% of all retweets received during each period respectively. After coding user profiles, e-cigarette advocates comprised 44.5% (n=146) of top H index unique users across all three time periods. While both the number of posts and number of users discussing tobacco policy on Twitter declined sharply with the onset of the COVID-19 pandemic, e-cigarette advocates continued to dominate both top 100 retweet and top 100 H index groups revealing the strong influence of anti-tobacco regulation advocates on Twitter.

This study used semantic network analysis to investigate the themes of JUUL electronic cigarette-related messages on Instagram posted by three account types (commercial, vape community, and organic users) and explore the function of hashtags in the JUUL-related discourse across these groups. Posts were collected from 1 March 2018 to 15 May 2018. We conducted network analyses for each user group, with separate analyses to examine texts with and without inclusion of hashtags. Network statistics determined which words occurred most frequently, which words co-occurred or clustered together, and what communication function hashtags perform. Analyses of message content with hashtags included revealed that the largest cluster of terms by account type was brand promotion (commercial), brand engagement (community), and youth social use of JUUL and other substances, such as marijuana (organic users). On removal of hashtags, the largest cluster for each group was online and offline retailer promotion (commercial), JUUL promotion or shares of existing promotional content (community), and youth social use (organic users). Commercial accounts used hashtags to increase brand visibility and engage with vape communities present on Instagram. Community accounts served as discursive intermediaries between commercial accounts and organic users, fostering organic user engagement with brands. Social media serve as an extension of real-life peer groups among youth and young adults. Community accounts, which likely have greater credibility among users compared to commercial accounts, may help enhance the effects of targeted promotion and normalize vaping comprehensive regulation of commercial digital tobacco marketing is necessary to reduce the amount of commercial content youth and other consumers are exposed to through overt commercial and influential community accounts.

Studies reporting clinical symptoms related to electronic nicotine delivery systems (ENDS) usage, especially types of devices and e-liquids, are sparse. The sample included 1,432 current ENDS users, ages 18-64, from a nationwide online survey conducted in 2016. ENDS use included device types, nicotine content, flavors, and eliquid used. Outcomes included any e-cigarette, or vaping, product use-associated lung injury (EVALI)-like symptoms (e.g., cough, shortness of breath, nausea) as well as any clinical symptoms. Of the sample, 50% were female, 23% non-Hispanic (NH) White, 23% NH Black, 54% Hispanic, 18% aged 18-24, 17% LGBTQ, 41% with <$50 K income, 55% 1 + any symptoms, and 33% 1 + any EVALI-like symptoms. Cough and nausea were most prevalent among EVALI-like symptoms (27% and 7.3%, respectively). The proportion having any EVALI-like symptoms was higher in the following groups: younger, Hispanic, current smokers, and current other product users. With multiple adjustments, participants who used refillable devices, varied nicotine content, used flavored products, or made their own e-liquids were more likely to have clinical symptoms than their counterparts. For example, the odds (95% CI) of having 1 + EVALI-like symptoms in participants who used refillable devices with e-liquid pour or e-liquid cartridge replacement were 1.70 (1.13, 2.56) and 1.95 (1.27, 2.99), respectively, compared to the non-refillable group. Use of products (devices and e-liquids) that can be altered and flavored products are associated with higher odds of having clinical symptoms, including EVALI-like symptoms.

ObjectiveAs a remedy to committing fraud and violating civil racketeering laws, in November 2017, four major tobacco companies were court-ordered to develop and disseminate corrective statements regarding smoking health risks using mass media channels. We aimed to describe the nature, timing, reach of and exposure to the court-mandated tobacco industry corrective advertising campaign on social, broadcast and print media.MethodsData from social, print and broadcast media were used to measure potential exposure to corrective messages. Keyword rules were used to collect campaign-related posts from the Twitter Firehose between November 2017 and January 2018. Data were analysed using a combination of machine learning, keyword algorithms and human coding. Posts were categorised by source (commercial/institutional, organic) and content type (eg, sentiment). Analysis of social media data was triangulated with ratings data for television advertising and print advertising expenditure data.ResultsKeyword filters retrieved 13 846 tweets posted by 9232 unique users. The majority of tweets were posted by institutional/commercial sources including news organisations, bots and tobacco control-related accounts and contained links to news and public health-related websites. Approximately 60% of campaign-related tweets were posted during the first week of campaign launch. Household exposure to the televised corrective advertisements averaged 0.56 ads per month.DiscussionThe corrective campaign failed to generate social media engagement. The size and timing of the advertising buys were not consistent with strategies effective in generating high sustained impact and audience reach, particularly among youth.

Public health organizations are increasingly turning to social media as a channel for health campaign dissemination, as these platforms can provide access to “hidden” or at-risk audiences such as populations of color and youth. However, few studies systematically assess the effects of such campaigns in a competitive communication environment characterized by an influx of sophisticated tobacco product marketing. The objective of the current study is to investigate how content and source features of Twitter messages about truth® campaigns influence their popularity, support, and reach. Keyword rules were used to collect tweets related to each of the six campaigns from the Twitter Firehose posted between August 2014 and June 2016. Data were analyzed using a combination of supervised and unsupervised machine learning, keyword algorithms, and human coding. Tweets were categorized by source type (direct or truth®-owned social influencer; non-influencer). Tweet content was coded and classified for valence and campaign references (branded vs. non-branded or organic content). Message reach was calculated by source type and message type. Keyword filters captured 308,216 tweets posted by 225,912 Twitter users. Findings revealed that campaigns that utilized social influencers as message sources generated more campaign-branded and sharable content (e.g., campaign hashtags) and greater volume of tweets per day and reach per day. Influential users posted fewer organic messages and more branded/sharable content, generating greater reach compared to non-influencers. Oppositional messages decreased over time. Harnessing cultural elements endemic to social media, such as popular content creators (influencers) and messages (memes), is a promising strategy for improving health campaign interest and engagement.

Background. The prevalence of e-cigarette use among youth is rising and may be associated with perceptions of health risks for these products. We examined how demographic factors and socioeconomic status (SES) are correlated with the perceived health risks of e-cigarette product contents among youth. Method. Data were from a national online survey of youth aged 13 to 18 between August and October 2017, weighted to be representative of the overall U.S. population in age, sex, race/ethnicity, and region. Survey analysis procedures were used. Results. Of 1,549 e-cigarette users and 1,451 never-e-cigarette users, 20.9% were Hispanic, 13.7% Black, 21.7% LGBTQ (lesbian/gay/bisexual/transgender/queer), and 49.3% in low-income families. With adjustment for e-cigarette use status, perceived health risks of nicotine and toxins/chemicals in e-cigarettes significantly differed by gender, race, sexual orientation, and SES (ps < .05). For example, adjusted odds of perceiving harm from nicotine were 60% higher in girls versus boys, 34% lower in non-Hispanic Blacks versus non-Hispanic Whites, 33% lower in urban versus suburban residents, 40% higher in LGBTQ versus straight-identifying individuals, and 28% lower in low-income versus high-income families. Lower parental education level also was associated with children's lower health risk perception of e-cigarette product contents. Conclusions. For youth, the perceived health risks of e-cigarette product contents were associated with demographics, sexual orientation, and SES. The findings may have relevance for developing communication and education strategies addressing specific youth audiences, especially those in vulnerable groups. These strategies could improve awareness among youth concerning the health risks of e-cigarettes, helping to prevent or reduce e-cigarette uptake and continued use.

Introduction: Comprehensive studies regarding clinical symptoms related to electronic nicotine delivery systems (ENDS) usage are sparse. Methods: The sample included 1,432 current ENDS users, ages 18-64, drawn from a national online survey conducted in 2016. A quota sampling method was used for key demographic characteristics such as age, gender, and race/ethnicity. ENDS use included types of devices, flavors, and knowledge of e-liquid used. Outcomes included any E-cigarette or Vaping use-Associated Lung Injury (EVALI)-like symptoms (e.g., cough, shortness of breath, nausea) and any clinical symptoms (see Table footnotes). Results: Of the sample, 50% were female, 23% non-Hispanic (NH) White, 23% NH Black, 54% Hispanic, 18% aged 18-24, 17% LGBTQ, 41% with <$50K income, 55% 1+ any symptoms, and 33% 1+ any EVALI-like symptoms. Cough and nausea were most prevalent among EVALI-like symptoms (27% and 7.3%, respectively). The proportion of having any EVALI-like symptoms was higher in the following groups: younger, Hispanic, current smokers, and current other product users. With multiple adjustments (see Table footnotes), those who used refillable devices, varied nicotine content, flavored products or made their own e-liquids were more likely to have clinical symptoms than their counterparts. For example, the odds (95% CI) of having 1+ EVALI-like symptoms in those who used refillable devices with e-liquid pour or with e-liquid cartridge replacement were 1.70 (1.13, 2.56) and 1.95 (1.27, 2.99), respectively, compared to the non-refillable group (see Table). It should be noted that those who used non-refillable devices were also more likely not to know the nicotine content in their e-liquid. However, their use pattern seemed stable: They tended to use only one brand, one type of device, and non-flavored e-liquid (results not tabulated). Conclusions: ENDS use was significantly associated with the odds of having clinical symptoms, including EVALI-like symptoms.

Background: The prevalence of e-cigarette use among youth is on the rise and may be associated with adolescents’ limited knowledge of the health effects of these products. We examined how demographics and socioeconomic status (SES) are correlated with the perceived health risks of e-cigarettes among youth. Methods: Data from a national online survey of youth aged 13-18 in 2017, weighted to be representative of the overall U.S. population in age, sex, race, ethnicity, and region were analyzed. Differences in perceived health risks of nicotine and other chemicals provided by vaping were addressed with respect to the demographics and SES of the participants, taking into account their e-cigarette use status. Results: Among 3,174 participants, 56.5% were female, 19.3% Hispanics and 14.7% non-Hispanic Blacks. Indicators of low SES [family receiving public assistance (PA) or participating in free school lunch program] were seen in 50.2%. With adjustment for e-cigarette use status in multivariable regression models, perceived health risks from the contents of e-cigarettes differed by gender, age, place of residence, and SES status. For example, the odds of perceiving harm from nicotine in e-cigarette products was 1.6 times higher in girls than in boys; the same odds was lower by 27% for those in families receiving government PA compared to those in families that did not. A parent’s education level also significantly influenced their child’s perception of the harm of the contents of e-cigarette products ( see Figure ). Conclusions: For youth, the perceived health risks of nicotine, toxins or chemicals in e-cigarette products were significantly different by age, gender, race/ethnicity, and SES. The findings may have relevance for developing communications and education strategies targeting specific youth audiences, especially those in vulnerable groups. These strategies could improve awareness among youth concerning the health effects of e-cigarettes, helping to prevent or reduce e-cigarette use.

Exposure to media content can shape public opinions about tobacco. Accurately describing content is a first step to showing such effects. Historically, content analyses have hand-coded tobacco-focused texts from a few media sources which ignored passing mention coverage and social media sources, and could not reliably capture over-time variation. By using a combination of crowd-sourced and automated coding, we labeled the population of all e-cigarette and other tobacco-related (including cigarettes, hookah, cigars, etc.) 'long-form texts' (focused and passing coverage, in mass media and website articles) and social media items (tweets and YouTube videos) collected May 2014-June 2017 for four tobacco control themes. Automated coding of theme coverage met thresholds for item-level precision and recall, event validation, and weekly-level reliability for most sources, except YouTube. Health, Policy, Addiction and Youth themes were frequent in e-cigarette long-form focused coverage (44%-68%), but not in long-form passing coverage (5%-22%). These themes were less frequent in other tobacco coverage (long-form focused (13-32%) and passing coverage (4-11%)). Themes were infrequent in both e-cigarette (1-3%) and other tobacco tweets (2-4%). Findings demonstrate that passing e-cigarette and other tobacco long-form coverage and social media sources paint different pictures of theme coverage than focused long-form coverage. Automated coding also allowed us to code the amount of data required to estimate reliable weekly theme coverage over three years. E-cigarette theme coverage showed much more week-to-week variation than did other tobacco coverage. Automated coding allows accurate descriptions of theme coverage in passing mentions, social media, and trends in weekly theme coverage.

Background: Decreasing total cholesterol (TC) and increasing high-density lipoprotein cholesterol (HDL-C) levels have been observed over the past several decades in the US population. It is not clear if the obesity epidemic has mitigated these favorable changes. Hypothesis: Associations between birth cohort and TC and HDL-C levels are partially attenuated by body mass index (BMI). Methods: We examined differences in TC and HDL-C levels across US birth cohorts born between 1930-1998 from the National Health and Nutrition Examination Surveys (NHANES) exam cycles 1999-2016, and the impact of body mass index (BMI) on these differences. A series of 10-year birth cohorts were constructed (1930-1998). Survey-weighted multivariable-adjusted linear regression models were used. Results: Among 40,273 participants, 50% were women and 22% non-Hispanic Blacks. After adjustment for age, sex, race, and lipid-lowering medication use, (and age 2 for the TC model), population mean TC decreased by 5.15 mg/dL and mean HDL-C increased by 1.34 mg/dL for each more recent birth cohort (all P<.001) ( Table ). There was an interaction between age and birth cohort for TC, with greater decreases with aging; for example, the mean of TC was 4.14, 6.48, and 8.83 mmHg lower for each more recent birth cohorts at the age of 30, 50, and 70, respectively. BMI was positively associated with TC and negatively associated with HDL-C. However, BMI only slightly influenced the association of birth cohort with TC (2%), but it strongly influenced the birth cohort effect on HDL-C (31%). Conclusion: More recent birth cohorts had lower TC levels and higher HDL-C levels than older birth cohorts in the US. These favorable birth cohort effects were partially compromised by BMI. Research into the environmental and behavioral differences between 20 th century US birth cohorts is needed to support future efforts to reduce the prevalence of dyslipidemia.