Rates of adverse events and related risk factors following e-cigarette use.

BACKGROUND: E-cigarettes have emerged as popular products, especially for younger populations. However, concerns regarding health effects exist and there is a notable gap in understanding the prevalence and nature of adverse events. This study aims to examine the rate of adverse events in individuals who use e-cigarettes in a large sample. METHODS: A cross-sectional survey was conducted with a sample of 4695 current and former e-cigarette users with a median age of 34 years. The survey collected data on e-cigarette use, adverse events experienced, product characteristics, related behaviors, sociodemographic factors and presence of medical comorbidities. Statistical analyses were conducted using Pearson's chi-squared tests and logistic regression. RESULTS: A total of 78.9% of respondents reported experiencing an adverse event within 6 h of using a vaping device, with the most common events being headache, anxiety and coughing. Product characteristics and related behaviors significantly influenced the risk of adverse events. There were also sociodemographic disparities, with Hispanic respondents and those with at least college-level education reporting higher rates of adverse events. CONCLUSIONS: Our study found a high rate of adverse events among e-cigarette users. We identified that certain e-cigarette product characteristics, behaviors and medical comorbidities significantly increased the risk of these events.

Identification and Characterization of Illegal Sales of Cannabis and Nicotine Delivery Products on Telegram Messaging Platform.

INTRODUCTION: Unregulated and potentially illegal sales of tobacco, nicotine, and cannabis products have been detected on various social media platforms, e-commerce sites, online retailers, and the dark web. New end-to-end encrypted messaging services are popular among online users and present opportunities for marketing, trading, and selling of these products. The purpose of this study was to identify and characterize tobacco, nicotine, and cannabis selling activity on the messaging platform Telegram. METHODS: The study was conducted in three phases: (1) identifying keywords related to tobacco, nicotine, and cannabis products for purposes of detecting Telegram groups and channel messages; (2) automated data collection from public Telegram groups; and (3) manual annotation and classification of messages engaged in marketing and selling products to consumers. RESULTS: Four keywords were identified ("Nicotine," "Vape," "Cannabis," and "Smoke") that yielded 20 Telegram groups with 262 506 active subscribers. Total volume of channel messages was 43 963 unique messages that included 3094 (7.04%) marketing/selling messages. The most commonly sold products in these groups were cannabis-derived products (83.25%, n = 2576), followed by tobacco/nicotine-derived products (6.46%, n = 200), and other illicit drugs (0.77%, n = 24). A variety of marketing tactics and a mix of seller accounts were observed, though most appeared to be individual suppliers. CONCLUSIONS: Telegram is an online messaging application that allows for custom group creation and global connectivity, but also includes unregulated activities associated with the sale of cannabis and nicotine delivery products. Greater attention is needed to conduct monitoring and enforcement on these emerging platforms for unregulated and potentially illegal cannabis and nicotine product sales direct-to-consumer. IMPLICATIONS: Based on study results, Telegram represents an emerging platform that enables a robust cannabis and nicotine-selling marketplace. As local, state, and national tobacco control regulations continue to advance sales restrictions and bans at the retail level, easily accessible and unregulated Internet-based channels must be further assessed to ensure that they do not act as conduits for exposure and access to unregulated or illegal cannabis and nicotine products.

Assessing the Impact of the Massachusetts Temporary Flavor Ban on Licensed Tobacco Retailers.

Introduction: In 2019, the state of Massachusetts signed into law the first statewide sales restrictions of flavored ENDS/tobacco products for both physical and online shops in response to a previous executive order to curb E-Cigarette, or Vaping Product, Use Associated Lung Injury (EVALI) cases that were surging throughout the nation. Methodology: This study obtained licensure data from the Massachusetts Department of Revenue, to observe the changes in retail licensure comparing the pre ban (October 2018-August 2019) and post ban periods (October 2020- August 2021). A series of linear regression tests were conducted on both periods using census tract data to explore potential associations with sociodemographic covariates, including median age, median household income, and population proportion by gender, age, and race/ethnicity groups. Results: Analysis of the Massachusetts post-ban period (October 2020-August 2021) found that new tobacco retail licenses issued decreased by 52.9% (n = 968) when compared to the pre-ban period (October 2018-August 2019) of 1831. A significant positive association was discovered between change in new retailer count and proportion male population (2.48 ± 1.05, P = .018) as well as proportion Hispanic population (1.19 ± .25, P < .001) at the census tract level. Conclusion/Discussion: Our analysis indicates that, following the temporary MA flavor sales ban, the total number of licenses decreased, though decreases were more pronounced for new licenses when compared to continuing licenses. Higher increases in new tobacco retailer density were significantly associated with concentration of male and Hispanic populations.

Tobacco/nicotine dependence as a risk factor for substance use disorders and related mental health conditions among cancer patients.

BACKGROUND: Cancer patients often face multiple comorbidities and are at risk for various mental health conditions and substance use disorders. Tobacco/nicotine dependence (TND) is a known risk factor for poor health outcomes and has been associated with psychiatric disorders including substance use disorder. However, the specific relationship between TND and the risk of substance use disorder and mental health conditions among cancer patients remains underexplored. This study aimed to assess the association between TND and the risk of comorbid conditions among cancer patients. METHODS: Data were obtained from a database of electronic health records for patients from the University of California health system. The odds for every condition among cancer patients with TND were calculated and compared with those for cancer patients without TND. ORs were adjusted for gender, ethnicity, and race. RESULTS: Three thousand seven hundred and ninety-one cancer patients with TND had 252,619 total conditions, and 51,711 cancer patients without TND had 2,310,880 conditions. After adjusting for confounders, the condition for which TND most exacerbated risk was psychoactive substance-induced organic anxiety disorder (OR = 16.3, p < 0.001). This appeared consistent with the second, third, and fifth most-exacerbated conditions: stimulant use disorder (OR = 12.8, p < 0.001), cocaine induced mental disorder (OR = 11.0, p < 0.001), and cocaine use disorder (OR = 11.0, p < 0.001). Different conditions exacerbated by TND include acute alcoholic intoxication (OR = 11.4, p < 0.001), opioid use disorder (OR = 7.6, p < 0.001), schizoaffective disorder (OR = 7.4, p < 0.001), and cannabis use disorder (OR = 6.3, p < 0.001). CONCLUSIONS: Our findings reveal a strong association between TND and an increased risk of substance use disorder and mental health conditions among cancer patients. Specifically, cancer patients with TND were at an elevated risk for psychoactive substance-induced organic anxiety disorder, stimulant use disorder, and cocaine-related disorders. Additionally, TND was associated with an increased risk of acute alcoholic intoxication, opioid use disorder, schizoaffective disorder, and cannabis use disorder. These findings underscore the need for comprehensive screening and interventions to address TND and comorbid conditions among cancer patients.

Assessing Characteristics and Compliance of Online Delta-8 Tetrahydrocannabinol Product Sellers.

Introduction: The debate over the legal status of many cannabis- and hemp-derived products, including delta-8 tetrahydrocannabinol (THC), is in question. Although low concentrations of delta-8 THC are legal at the Federal level, many states have implemented their own regulations to both allow and restrict its use and sale. Of concern, sellers with unknown legal credentials have appeared online and are actively selling this product. Materials and Methods: We characterized the marketing, sale, and compliance of online delta-8 THC sellers using (1) data collected from the Twitter Application Programming Interface with delta-8 THC-related keywords; (2) unsupervised topic modeling using the Biterm Topic Model to identify clusters of tweets involved in marketing and selling; (3) inductive coding to identify marketing and selling characteristics; and (4) web forensics and simulated shopping to determine compliance with state restrictions for delta-8 THC sales. Results: In total, 110 unique hyperlinks associated with 7085 tweets that included marketing and selling activity for delta-8 THC were collected. From these links, we conducted simulated purchasing in January 2021 to identify compliant and noncompliant websites. Among the vendors, age verification was not found in over half of websites (59, 53.63%); 60 (54.55%) did not report a physical address; and 74 (65.45%) sold delta-8 products direct-to-consumer. Sixty-seven (90.54%) of detected vendors shipped delta-8 products to addresses in states that prohibit sales. Forty-three (64.18%) of Internet Protocol addresses were located within the United States; all others were international. Conclusion: Our analysis suggests that online storefronts are illegally selling and shipping cannabinoid derivatives to U.S. consumers. Further research is needed to understand downstream health and regulatory impacts from this unregulated access.

Examining the association between California tobacco licensed retail density and public support or opposition to state anti-tobacco legislation.

INTRODUCTION: The state of California has enacted progressive anti-tobacco policies, including Proposition 56 in 2016. In response, the alternative and emerging tobacco product (ATP) industry has increased its political activity. This study explores the association between the proportion of people voting against Proposition 56 and tobacco/ATP retail density. METHODS: We conducted a retrospective analysis using data on licensed California tobacco retailers, which were then cross-referenced for categorization using Yelp. Proportion voting against Proposition 56 was obtained from the Secretary of State's website. A series of linear regression tests were performed between population-normalized retailer density and voting proportion at the county level before and after adjusting for covariates such as age, gender, race/ethnicity and median household income. RESULTS: The total number of licensed tobacco retailers increased by 29.31% from 2015 to 2019. Association between proportion voting against Proposition 56 and retail density was significant during voting and during periods of policy implementation and post-implementation (2016-2018) for non-specialized tobacco retailers. For specialized/ATP retailers, significance was only detected during the post-implementation period (2018-2019) after normalization. Proportion voting against Proposition 56 was also a significant predictor of increase in total number of non-specific (ß=0.48, p=0.008) as well as specialized tobacco and/or ATP retail storefronts (ß=0.21, p=0.001) from 2016 to 2018. CONCLUSIONS: This study provides initial evidence of the association between tobacco retail density and voting patterns for anti-tobacco policy. Future research should examine the role of tobacco retail density on variation in local support for state tobacco control initiatives, including tailoring outreach to specific voting census blocks in communities with heavy retail presence.

Estimating County-Level Overdose Rates Using Opioid-Related Twitter Data: Interdisciplinary Infodemiology Study.

BACKGROUND: There were an estimated 100,306 drug overdose deaths between April 2020 and April 2021, a three-quarter increase from the prior 12-month period. There is an approximate 6-month reporting lag for provisional counts of drug overdose deaths from the National Vital Statistics System, and the highest level of geospatial resolution is at the state level. By contrast, public social media data are available close to real-time and are often accessible with precise coordinates. OBJECTIVE: The purpose of this study is to assess whether county-level overdose mortality burden could be estimated using opioid-related Twitter data. METHODS: International Classification of Diseases (ICD) codes for poisoning or exposure to overdose at the county level were obtained from CDC WONDER. Demographics were collected from the American Community Survey. The Twitter Application Programming Interface was used to obtain tweets that contained any of the 36 terms with drug names. An unsupervised classification approach was used for clustering tweets. Population-normalized variables and polynomial population-normalized variables were produced. Furthermore, z scores of the Getis Ord Gi clustering statistic were produced, and both these scores and their polynomial counterparts were explored in regression modeling of county-level overdose mortality burden. A series of linear regression models were used for predictive modeling to explore the interpretability of the analytical output. RESULTS: Modeling overdose mortality with normalized demographic variables alone explained only 7.4% of the variability in county-level overdose mortality, whereas this was approximately doubled by the use of specific demographic and Twitter data covariates based on a backward selection approach. The highest adjusted R2 and lowest AIC (Akaike Info Criterion) were obtained for the model with normalized demographic variables, normalized z scores from geospatial analyses, and normalized topic counts (adjusted R2=0.133, AIC=8546.8). The z scores of the Getis Ord Gi statistic appeared to have improved utility over population-normalization alone. In this model, median age, female population, and tweets about web-based drug sales were positively associated with opioid mortality. Asian race and Hispanic ethnicity were significantly negatively associated with county-level burdens of overdose mortality. CONCLUSIONS: Social media data, when transformed using certain statistical approaches, may add utility to the goal of producing closer to real-time county-level estimates of overdose mortality. Prediction of opioid-related outcomes can be advanced to inform prevention and treatment decisions. This interdisciplinary approach can facilitate evidence-based funding decisions for various substance use disorder prevention and treatment programs.

Predictors of Time to Coronavirus Disease 2019 Infection in the National Basketball Association: A Retrospective Case-Control Study.

A case-control study was conducted between 1 December 2021 and 31 January 2022 to identify factors, which increase risk for coronavirus disease 2019 (COVID-19) among athletes in the National Basketball Association (NBA). Behavioral factors and stadium attendance significantly decreased time to COVID-19 infection, but local COVID-19 rates were not associated in a multivariable model.

Longitudinal analysis of tobacco and vape retail density in California.

INTRODUCTION: Tobacco retailer density may be associated with greater youth initiation and reduced success during quit attempts; however, the extent to which tobacco retailer density has changed overtime across multiple categories of retailers has not been reported. METHODS: Data on licensed tobacco retailers within California from 2015-2019 were obtained from the California Department of Tax and Fee Administration. Store type was categorized by automated cross-referencing with Yelp. Geolocations were aggregated at county level for analyzing longitudinal trends in changes in tobacco retail density including demographic characteristics. RESULTS: The number of active CA tobacco retailer licenses increased from 19825 in 2015 to 25635 in 2019. The highest percent increase in tobacco retailer licenses (9.1%) was observed in 2017. The number of specialized tobacco stores was highest in Los Angeles, San Diego, and Riverside counties. We observed a significant increase in the number of active licenses for non-specialized and specialized tobacco stores, both overall and after controlling for the size of populations within each region. Time was a statistically significant predictor for the number of active licenses for only non-specialized stores, after adjusting for covariates. Regional volume of retailers was positively associated with higher proportion of women, lower median household income, and higher proportion of Hispanic residents. CONCLUSIONS: Monitoring the changes in tobacco retail density and associated sociodemographic factors over time can help to identify communities at higher risk for tobacco and nicotine product exposure and access, and its associated health disparities.

Content and trend analysis of user-generated nicotine sickness tweets: A retrospective infoveillance study.

INTRODUCTION: Exposure to pro-tobacco and electronic nicotine delivery system (ENDS) social media content can lead to overconsumption, increasing the likelihood of nicotine poisoning. This study aims to examine trends and characteristics of nicotine sickness content on Twitter between 2018-2020. METHODS: Tweets were collected retrospectively from the Twitter Academic Research Application Programming Interface (API) stream filtered for keywords: 'nic sick', 'nicsick', 'vape sick', 'vapesick' between 2018-2020. Collected tweets were manually annotated to identify suspected user-generated reports of nicotine sickness and related themes using an inductive coding approach. The Augmented Dickey-Fuller (ADF) test was used to assess stationarity in the monthly variation of the volume of tweets between 2018-2020. RESULTS: A total of 5651 tweets contained nicotine sickness-related keywords and 18.29% (n=1034) tweets reported one or more suspected nicotine sickness symptoms of varied severity. These tweets were also grouped into five related categories including firsthand and secondhand reports of symptoms, intentional overconsumption of nicotine products, users expressing intention to quit after 'nic sick' symptoms, mention of nicotine product type/brand name that they consumed while 'nic sick', and users discussing symptoms associated with nicotine withdrawal following cessation attempts. The volume of tweets reporting suspected nicotine sickness appeared to increase throughout the study period, except between February and April 2020. Stationarity in the volume of 'nicsick' tweets between 2018-2020 was not statistically significant (ADF= -0.32, p=0.98) indicating a change in the volume of tweets. CONCLUSIONS: Results point to the need for alternative forms of adverse event surveillance and reporting, to appropriately capture the growing health burden of vaping. Infoveillance approaches on social media platforms can help to assess the volume and characteristics of user-generated content discussing suspected nicotine poisoning, which may not be reported to poison control centers. Increasing volume of user-reported nicotine sickness and intentional overconsumption of nicotine in twitter posts represent a concerning trend associated with ENDS-related adverse events and poisoning.

Content Analysis of Nicotine Poisoning (Nic Sick) Videos on TikTok: Retrospective Observational Infodemiology Study.

BACKGROUND: TikTok is a microvideo social media platform currently experiencing rapid growth and with 60% of its monthly users between the ages of 16 and 24 years. Increased exposure to e-cigarette content on social media may influence patterns of use, including the risk of overconsumption and possible nicotine poisoning, when users engage in trending challenges online. However, there is limited research assessing the characteristics of nicotine poisoning-related content posted on social media. OBJECTIVE: We aimed to assess the characteristics of content on TikTok that is associated with a popular nicotine poisoning-related hashtag. METHODS: We collected TikTok posts associated with the hashtag #nicsick, using a Python programming package (Selenium) and used an inductive coding approach to analyze video content and characteristics of interest. Videos were manually annotated to generate a codebook of the nicotine sickness-related themes. Statistical analysis was used to compare user engagement characteristics and video length in content with and without active nicotine sickness TikTok topics. RESULTS: A total of 132 TikTok videos associated with the hashtag #nicsick were manually coded, with 52.3% (69/132) identified as discussing firsthand and secondhand reports of suspected nicotine poisoning symptoms and experiences. More than one-third of nicotine poisoning-related content (26/69, 37.68%) portrayed active vaping by users, which included content with vaping behavior such as vaping tricks and overconsumption, and 43% (30/69) of recorded users self-reported experiencing nicotine sickness, poisoning, or adverse events such as vomiting following nicotine consumption. The average follower count of users posting content related to nicotine sickness was significantly higher than that for users posting content unrelated to nicotine sickness (W=2350.5, P=.03). CONCLUSIONS: TikTok users openly discuss experiences, both firsthand and secondhand, with nicotine adverse events via the #nicsick hashtag including reports of overconsumption resulting in sickness. These study results suggest that there is a need to assess the utility of digital surveillance on emerging social media platforms for vaping adverse events, particularly on sites popular among youth and young adults. As vaping product use-patterns continue to evolve, digital adverse event detection likely represents an important tool to supplement traditional methods of public health surveillance (such as poison control center prevalence numbers).

Characterizing California licensure status and tobacco user experience with adverse events using Yelp data.

Various tobacco vendors, including alternative tobacco product sellers, are listed on the popular crowdsourced business listing platform Yelp. Yelp is used to rate and choose tobacco, electronic nicotine delivery systems (ENDS) goods/services and includes self-reporting of user experiences with shops and products. We cross-referenced California Department of Tax and Fee Administration (CDTFA) licensed tobacco, vape, and head shop retail stores with publicly available Yelp business listings to identify licensed and unlicensed stores in California. We extracted metadata associated with store accounts and analyzed user comments and ratings for discussion of tobacco-related complaints and adverse events. We detected a total of 3,717 shops that were categorized as tobacco/vape/head shops on Yelp and by cross-referencing with CDTFA data, licensed businesses accounted for 49.5% (n = 1,841), licensed individual retailers 31.6% (n = 1,174), and suspected unlicensed storefronts 18.9% (n = 702). Businesses and individuals with a state tobacco retail license received a higher average rating from Yelp users (3.86 out of 5) compared to unlicensed shops (3.57) (p < 0.001). Additionally, 4,682 unique comments about licensed businesses, 1,535 unique comments about individual retailers, and 560 unique comments about unlicensed vendors were reviewed, with themes including discussion about defective and counterfeit products and adverse events including coughing, difficulty breathing and reports of hospitalization detected. In contrast, comments about licensed stores predominantly discussed customer service issues. Close to one-fifth of tobacco, vape and/or head shops reviewed on Yelp were not in CDTFA's licensure database. Overall self-reported tobacco user experiences appeared to differ in content and severity based on whether an establishment was licensed. These results have the potential to identify unauthorized stores and adverse events associated with their tobacco and vaping products or services.

Association of tobacco retailer count with smoking population versus vaping population in California (2019).

BACKGROUND: Access to tobacco products, including vape products, from local brick-and-mortar stores influences the exposure, uptake, and use of these products in local communities. METHODS: Licensed tobacco retailers in California were classified as specialized tobacco/vape stores or non-specialized stores by obtaining categories published on Yelp. California smoking and vaping prevalence data were obtained from the 500 cities project and ESRI community analyst tool respectively. A series of simple linear regression tests were performed, at the zip code level, between the retailer count in each store category and smoking/vaping population. The Getis-Ord Gi* and Anselin Local Moran's I statistics were used for characterization of tobacco retail density hotspots and cold spots. RESULTS: The association between CA smoking/vaping population and number of tobacco retailers was statistically significant for all store categories. Variability in smoking population was best explained by variability in non-specialized storefronts(R2=0.84). Spatial variability in tobacco-only storefronts explained the least proportion of variability in the overall smoking population. Similar results were obtained specific to vaping population, although the proportion of population explained by variability in the number of non-specialized storefronts was comparatively lower(R2=0.80). CONCLUSIONS: Localities with greater numbers of non-specialized tobacco retailers had higher rates of smoking/vaping populations, and this association was much stronger for localities with greater numbers of specialized retailers. Non-specialized storefronts may represent convenient access points for nicotine products, while specialized storefronts may represent critical access points for initiation. Hence, regulations that address the entirety of the tobacco/vaping retail environment by limiting widespread access from non-specialized stores and reducing appeal generated by specialized retailers should be incorporated in future tobacco regulatory science and policymaking.

Google shopping queries for vaping products, JUUL and IQOS during the E-cigarette, or Vaping, product use Associated Lung Injury (EVALI) outbreak.

OBJECTIVES: To assess whether the late 2019 US outbreak of pulmonary disease linked to vaping ('E-cigarette, or Vaping, product use Associated Lung Injury' (EVALI)) impacted online shopping queries for vaping products and the Philip Morris 'IQO' brand of heated tobacco. METHODS: We tracked online shopping queries for vape(s), JUUL and IQOS by analysing rates of Google queries indicative of shopping (eg, buy IQOS) after news of the outbreak was first reported (the week of 29 July 2019) until hospitalisations ceased (the week of 16 February 2020). We compared observed rates of shopping during the outbreak to counterfactual expected rates that were predicted using an autoregressive iterative moving average model fit to queries from 1 January 2014 to the week of 21 July 2019. RESULTS: During the outbreak, vape shopping queries were 34% (95% CI 30% to 38%) lower than expected and JUUL shopping queries were 39% (95% CI 34% to 45%) lower than expected, translating into about 7.2 and 1.0 million fewer searches. IQOS shopping queries were 58% (95% prediction interval (PI): 34-87) higher than expected, translating into 35 000 more searches. Moreover, IQOS shopping queries reached a historic high the week they were discussed as a potentially safe alternative to vaping (the week of 29 September 2019), when they were 382% (95% PI: 219-881) above expected rates for the week. CONCLUSIONS: These results suggest that unplanned events, such as the EVALI outbreak, can provoke changes in the epidemiology of product usage. Tobacco companies should be prohibited from using events such as disease outbreaks to position their products as less harmful without prior approval.

Inductive Characterization of ENDS-Associated Adverse Events Among California Young Adults.

Introduction: Previous studies have identified numerous adverse events experienced with the use of ENDS or E-cigarettes. However, much remains unknown about adverse event frequency, duration, and response experienced by users. The purpose of this study was to inductively characterize ENDS-attributed adverse events among young adults. Methods: Sixteen focus groups were held with 114 young adults (aged 18-29 years) who have reported lifetime ENDS use in April 2021. Discussion topics included current and previous tobacco, nicotine, and cannabis use; specific symptoms and frequency and duration of and response to symptoms of ENDS-attributed adverse events; and the impact of other conditions such as COVID-19 on ENDS use. Data were inductively analyzed using a team-based approach. Results: More than 40 ENDS-attributed adverse events were reported in focus groups among approximately three quarters of all study participants, with headache, coughing, lightheadedness, nausea, dry or sore throat, and dizziness the most common. In general, adverse events were transient, with most resolving in a few hours, although some tended to last for longer. The frequency of adverse events varied most between every time ENDS were used and when someone vaped excessively. Finally, behavioral responses varied by adverse events, with difficulty in breathing, chest pain, and lung discomfort more likely to result in quitting permanently. Conclusions: Overall, the results of this study show that not only do adverse events vary greatly, but they also vary across multiple dimensions of user experience.

Campus Smoking Policies and Smoking-Related Twitter Posts Originating From California Public Universities: Retrospective Study.

BACKGROUND: The number of colleges and universities with smoke- or tobacco-free campus policies has been increasing. The effects of campus smoking policies on overall sentiment, particularly among young adult populations, are more difficult to assess owing to the changing tobacco and e-cigarette product landscape and differential attitudes toward policy implementation and enforcement. OBJECTIVE: The goal of the study was to retrospectively assess the campus climate toward tobacco use by comparing tweets from California universities with and those without smoke- or tobacco-free campus policies. METHODS: Geolocated Twitter posts from 2015 were collected using the Twitter public application programming interface in combination with cloud computing services on Amazon Web Services. Posts were filtered for tobacco products and behavior-related keywords. A total of 42,877,339 posts were collected from 2015, with 2837 originating from a University of California or California State University system campus, and 758 of these manually verified as being about smoking. Chi-square tests were conducted to determine if there were significant differences in tweet user sentiments between campuses that were smoke- or tobacco-free (all University of California campuses and California State University, Fullerton) compared to those that were not. A separate content analysis of tweets included in chi-square tests was conducted to identify major themes by campus smoking policy status. RESULTS: The percentage of positive sentiment tweets toward tobacco use was higher on campuses without a smoke- or tobacco-free campus policy than on campuses with a smoke- or tobacco-free campus policy (76.7% vs 66.4%, P=.03). Higher positive sentiment on campuses without a smoke- or tobacco-free campus policy may have been driven by general comments about one's own smoking behavior and comments about smoking as a general behavior. Positive sentiment tweets originating from campuses without a smoke- or tobacco-free policy had greater variation in tweet type, which may have also contributed to differences in sentiment among universities. CONCLUSIONS: Our study introduces preliminary data suggesting that campus smoke- and tobacco-free policies are associated with a reduction in positive sentiment toward smoking. However, continued expressions and intentions to smoke and reports of one's own smoking among Twitter users suggest a need for more research to better understand the dynamics between implementation of smoke- and tobacco-free policies and resulting tobacco behavioral sentiment.

Could age increase the strength of inverse association between ultraviolet B exposure and colorectal cancer?

BACKGROUND: Vitamin D has been identified as a potential protective factor in the development of colorectal cancer (CRC). We expect to see a stronger association of ultraviolet B (UVB) exposure and CRC crude rates with increasing age since chronic vitamin D deficiency leads to sustained molecular changes that increase cancer risk. The DINOMIT (disjunction, initiation, natural selection, overgrowth, metastasis, involution, and transition) model postulates various stages of cancer development due to vitamin D deficiency and the associated latency period. The purpose of this study is to examine this age-dependent inverse relationship globally. METHODS: In this ecological study, a series of linear and polynomial regression tests were performed between country-specific UVB estimates adjusted for cloud cover and crude incidence rates of CRC for different age groups. Multiple linear regression was used to investigate the association between crude incidence rates of colorectal cancer and UVB estimate adjusting for urbanization, skin pigmentation, smoking, animal consumption, per capita GDP, and life expectancy. Statistical analysis was followed by geospatial visualization by producing choropleth maps. RESULTS: The inverse relationship between UVB exposure and CRC crude rates was stronger in older age groups at the country level. Quadratic curve fitting was preferred, and these models were statistically significant for all age groups. The inverse association between crude incidence rates of CRC and UVB exposure was statistically significant for age groups above 45 years, after controlling for covariates. CONCLUSION: The age-dependent inverse association between UVB exposure and incidence of colorectal cancer exhibits a greater effect size among older age groups in global analyses. Studying the effect of chronic vitamin D deficiency on colorectal cancer etiology will help in understanding the necessity for population-wide screening programs for vitamin D deficiency, especially in regions with inadequate UVB exposure. Further studies are required to assess the need for adequate public health programs such as selective supplementation and food fortification.

Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine Learning.

Background: Suicide and substance use disorder (SUD) pose serious public health challenges among young adults in the United States. Increasing social media use among these populations can be leveraged as an alternative method to detect characteristics of suicide-related topics and behavior among substance users. Objective: To detect and characterize suicide and self-harm related conversations co-occurring with SUD posts and comments on the popular social media platform Instagram. Methods: This study used big data and machine learning approaches to collect and classify Instagram posts containing 632 controlled substance-related hashtags. Posts were first classified for online drug diversion topics and then filtered to detect suicide and mental health discussions. Posts and comments were then manually annotated for SUD and mental health co-occurring themes. Associations between these characteristics were tested using the Chi-square test. Results: We detected 719 Instagram posts/comments that included user-generated discussions about suicide, substance use and/or mental health. Posts self-reporting SUD and mental health topics were also more likely to discuss suicide compared to those that did not discuss SUD and mental health topics, respectively (p < 0.001). Major themes observed included concurrent discussions of suicide ideation and attempts and low self-esteem. Conclusions: Our study results provide preliminary evidence of social media discussions about suicide and mental health among those with SUD. This co-occurrence represents a key health risk factor on a platform heavily utilized by young adults. Further studies are required to analyze specific patterns of suicide and self-harm ideations for the purposes of designing future suicide prevention campaigns through digital channels.

A geospatial analysis of age disparities in resolute localities of tobacco and vaping-specific storefronts in California.

INTRODUCTION: Concomitant with the popularization of vaping, vape shops have dramatically proliferated over the past years. This study assesses whether vape storefronts in California are significantly associated with density of different age groups, and whether this differs between tobacco storefronts or non-specific tobacco retailers. METHODS: Addresses for licensed tobacco retailers were obtained from the California Department of Tax and Fee Administration. Business names and addresses were used to obtain store categories cross-referenced from Yelp. Using a cross-sectional ecological design, stores categorized as 'Vape Shop' or 'Tobacco Shop' were geolocated and compared with age-related variables from the American Community Survey. Regression was conducted in R to determine relationships between age group concentration, in ventiles, and proportion of tracts with tobacco-specific or vape-specific stores. Geospatial visualization was conducted using ArcGIS. RESULTS: We found 848 vape shops, 820 tobacco shops, 419 categorized as both, and 20320 retailers with neither category. Overall, 1800 tobacco and/or vape shops were categorized in 1557 of California's 23194 census tracts. A positive linear association was found between ventiles of two age categories, 20-24 and 25-34 years, and proportion of tracts with vape-specific or tobacco-specific shops separately. CONCLUSIONS: Positive associations were found for ages 20-34 years but not for other ages, suggesting vape shops are strategically located in areas populated by young adults. Location-based targeting increases access, thereby increasing proportion of tobacco users, and could be a critical factor in e-cigarette uptake and use. Further study to identify additional age-related demographic characteristics among clientele of tobacco storefronts is warranted.

Characterizing Self-Reported Tobacco, Vaping, and Marijuana-Related Tweets Geolocated for California College Campuses.

Introduction: College-aged youth are active on social media yet smoking-related social media engagement in these populations has not been thoroughly investigated. We sought to conduct an exploratory infoveillance study focused on geolocated data to characterize smoking-related tweets originating from California 4-year colleges on Twitter. Methods: Tweets from 2015 to 2019 with geospatial coordinates in CA college campuses containing smoking-related keywords were collected from the Twitter API stream and manually annotated for discussions about smoking product type, sentiment, and behavior. Results: Out of all tweets detected with smoking-related behavior, 46.7% related to tobacco use, 50.0% to marijuana, and 7.3% to vaping. Of these tweets, 46.1% reported first-person use or second-hand observation of smoking behavior. Out of 962 tweets with user sentiment, the majority (67.6%) were positive, ranging from 55.0% for California State University, Long Beach to 95.8% for California State University, Los Angeles. Discussion: We detected reporting of first- and second-hand smoking behavior on CA college campuses representing possible violation of campus smoking bans. The majority of tweets expressed positive sentiment about smoking behaviors, though there was appreciable variability between college campuses. This suggests that anti-smoking outreach should be tailored to the unique student populations of these college communities. Conclusion: Among tweets about smoking from California colleges, high levels of positive sentiment suggest that the campus climate may be less receptive to anti-smoking messages or adherence to campus smoking bans. Further research should investigate the degree to which this varies by campuses over time and following implementation of bans including validating using other sources of data.