Dataset Information

ENDS retailers and marketing near university campuses with and without tobacco-free policies.

ABSTRACT: Introduction:This study characterizes the retail environment for Electronic Nicotine Delivery Systems (ENDS) near public universities in California, assesses marketing in the first random sample of ENDS retailers, and compares ENDS retailer density and retail marketing near campuses with and without tobacco-free policies. Methods:Two data sources were used to construct a sampling frame of possible ENDS retailers, which were mapped within 1 to 4 miles of the 33 University of California and California State University campuses. To assess retailer density, a telephone survey of possible ENDS retailers (n=1186) determined which sold e-cigarettes or e-liquids (completion rate=72.9%). To assess retail marketing, trained data collectors completed observations in a random sample (n=438, M=13.3 stores per campus, SD=11.2) in fall 2015. Results:In a telephone survey, 59.1% of retailers reported selling e-cigarettes or e-liquids. Half of the campuses had 10 or more ENDS retailers nearby. Most ENDS retailers were convenience stores (42.5%), and more were head shops (8.4%) than smoke shops (6.8%) or vape shops (6.2%). Nearly half (43.6%) of ENDS retailers sold products marketed as zero-nicotine and 13.9% sold NRT. ENDS advertising was visible in 72.1% and on the exterior of 28.1% of retailers. However, the presence of exterior advertising for ENDS was significantly lower near campuses with established tobacco-free policies than campuses with recent or no tobacco-free policies (OR=0.45, 95% CI=0.22, 0.94). Conclusions:The large number of tobacco retailers that sell ENDS near colleges suggests a need for better monitoring and regulations of ENDS availability and marketing. The widespread availability of zero-nicotine products suggests a need to examine whether nicotine-free products are as advertised and safe to use. Longitudinal research is needed to understand how retail marketing for ENDS responds to change in tobacco-free policies at nearby campuses.

SUBMITTER: Barker DC

PROVIDER: S-EPMC6342456 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

ENDS retailers and marketing near university campuses with and without tobacco-free policies.

Barker Dianne C DC Schleicher Nina C NC Ababseh Kimberly K Johnson Trent O TO Henriksen Lisa L

Tobacco induced diseases 20181001

<h4>Introduction</h4>This study characterizes the retail environment for Electronic Nicotine Delivery Systems (ENDS) near public universities in California, assesses marketing in the first random sample of ENDS retailers, and compares ENDS retailer density and retail marketing near campuses with and without tobacco-free policies.<h4>Methods</h4>Two data sources were used to construct a sampling frame of possible ENDS retailers, which were mapped within 1 to 4 miles of the 33 University of Califo ...[more]

PMID: 30687532

Similar Datasets

Project description:IntroductionPrevious studies have found that tobacco retailers cluster near schools. However, all retail outlets may be located near each other and near schools due to existing infrastructure and zoning policies. We assessed whether tobacco retailers cluster near schools in the United States more than expected when accounting for existing retail locations.Aims and methodsWe identified 322 056 probable tobacco retailers, 95 110 public schools, and more than 3.8 million businesses comparable to tobacco retailers in land use and business type. We created 500 simulated tobacco retailer datasets by randomly selecting from the larger list of businesses. For each simulated dataset, we calculated the distance from schools to the nearest tobacco retailer (proximity) and the count of tobacco retailers within 800 m of schools (density). Observed proximity and density values were compared to 95% coverage intervals from the 500 simulations. We stratified analyses by urbanicity, percentage of students in the free and reduced-priced lunch program (FRLP), and percentage of Hispanic/Latino, non-Hispanic Black, and non-Hispanic white students.ResultsTobacco retailers were closer to schools in rural areas, cities, and towns and more dense around schools in rural areas, cities, and suburbs compared to random locations in potential retail space. Schools with more students receiving FRLP had higher density than expected while schools with fewer students receiving FRLP had lower density than expected. Within rural areas, clustering did not vary across sociodemographic groups. Within non-rural areas, there were inequities in clustering by racial, ethnic, and socioeconomic school composition.ConclusionsTobacco retailers cluster near schools after accounting for existing business patterns. There are inequities in clustering by sociodemographic school composition.ImplicationsThis study provides compelling evidence that tobacco retailers cluster near US public schools and that there are racial, ethnic, and socioeconomic inequities in clustering, even when accounting for overall retail location patterns. Given that public schools tend to reflect neighborhood demographics, policies to limit tobacco retailers near schools may reduce both school-based and neighborhood-based inequities.

Project description:BackgroundSchool tobacco policies (STPs) that aim to achieve a tobacco-free environment require consistent enforcement by school staff. However, little is known about why staff choose whether or not to enforce STPs. Therefore, we investigated staff members' responses to STPs that determine enforcement. Furthermore, we examined how these responses depend on contextual factors at the individual, interpersonal, school, implementation, and national levels.MethodsWe performed a realist review (RR), which synthesizes existing primary evidence into a programme theory demonstrating key causal pathways through Context-Mechanism-Outcome configurations (CMOs). These CMOs link contextual factors to outcomes (i.e. staff enforcement) by explaining the underlying generative mechanisms (i.e. staff members' cognitive, psychosocial, and behavioural responses). A systematic literature search for the period 2000-2016 was performed using Academic Search Premier, PsycInfo, and MEDLINE. Forty English-language articles were identified for the synthesis.ResultsOur programme theory demonstrated three CMOs: when contextual factors make staff members experience STP enforcement as part of their professional role and duties, it may lead to staff members showing responsibility for STP enforcement (CMO1); when contextual factors make staff members feel their contribution is leading to positive outcomes, it may lead to staff members showing motivation to enforce STPs (CMO2), and when contextual factors make staff members feel that they are able to deal with students' responses, it may lead to staff members showing confidence in STP enforcement (CMO3). Moreover, the programme theory provided more precise insights into what contextual factors contribute to triggering the individual mechanisms and the consequent outcomes.ConclusionsBy applying a realist approach, we have been able to detect three CMOs explaining staff members' STP enforcement. The findings provide useful insights explaining how stakeholders can support staff members' STP enforcement and consequently improve the impact of STPs on adolescent smoking.

Project description:ObjectivesUniversities are exploring strategies to mitigate the spread of COVID-19 prior to reopening their campuses. National guidelines do not currently recommend testing students prior to campus arrival. However, the impact of presemester testing has not been studied.DesignDynamic SARS-CoV-2 transmission models are used to explore the effects of three presemester testing interventions.InterventionsTesting of students 0, 1 and 2 times prior to campus arrival.Primary outcomesNumber of active infections and time until isolation bed capacity is reached.SettingWe set on-campus and off-campus populations to 7500 and 17?500 students, respectively. We assumed 2% prevalence of active cases at the semester start, and that one-third of infected students will be detected and isolated throughout the semester. Isolation bed capacity was set at 500. We varied disease transmission rates (R0=1.5, 2, 3, 4) to represent the effectiveness of mitigation strategies throughout the semester.ResultsWithout presemester screening, peak number of active infections ranged from 4114 under effective mitigation strategies (R0=1.5) to 10?481 under ineffective mitigation strategies (R0=4), and exhausted isolation bed capacity within 10 (R 0 =4) to 25 days (R0=1.5). Mandating at least one test prior to campus arrival delayed the timing and reduced the size of the peak, while delaying the time until isolation bed capacity was reached. Testing twice in conjunction with effective mitigation strategies (R0=1.5) was the only scenario that did not exhaust isolation bed capacity during the semester.ConclusionsPresemester screening is necessary to avert early and large surges of active COVID-19 infections. Therefore, we recommend testing within 1?week prior to and on campus return. While this strategy is sufficient for delaying the timing of the peak outbreak, presemester testing would need to be implemented in conjunction with effective mitigation strategies to significantly reduce outbreak size and preserve isolation bed capacity.

Dataset Information

ENDS retailers and marketing near university campuses with and without tobacco-free policies.

Publications

ENDS retailers and marketing near university campuses with and without tobacco-free policies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets