Close
About
FAQ
Home
Collections
Login
USC Login
Register
0
Selected
Invert selection
Deselect all
Deselect all
Click here to refresh results
Click here to refresh results
USC
/
Digital Library
/
University of Southern California Dissertations and Theses
/
Examining the built and online environments to understand cannabis and e-cigarette availability, marketing, and product use in Southern California
(USC Thesis Other)
Examining the built and online environments to understand cannabis and e-cigarette availability, marketing, and product use in Southern California
PDF
Download
Share
Open document
Flip pages
Contact Us
Contact Us
Copy asset link
Request this asset
Transcript (if available)
Content
EXAMINING THE BUILT AND ONLINE ENVIRONMENTS TO UNDERSTAND
CANNABIS AND E-CIGARETTE AVAILABILITY, MARKETING, AND PRODUCT USE
IN SOUTHERN CALIFORNIA
by
Patricia Escobedo, M.A.
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PREVENTIVE MEDICINE (HEALTH BEHAVIOR RESEARCH))
December 2021
Copyright 2021 Patricia Escobedo, M.A.
ii
Acknowledgments
I want to thank my advisor and dissertation chair, Dr. Lourdes Baezconde-Garbanati, for all her
support, guidance, and advocacy during my doctoral program. It has been an honor to learn from
her as a researcher, professor, advocate, advisor, and mother. I would also like to thank Dr. Jon-
Patrick Allem for his mentorship and for allowing me to serve as a research assistant in his lab
this past year. I would like to thank all my incredible committee members: Drs. Jennifer Unger,
Steve Sussman, Jon-Patrick Allem, and Robert Vos. Thank you all for your time, knowledge,
guidance, and thoughtful feedback on my dissertation project.
I would also like to thank Joshua, Eva, and Ellie for their love and patience, my parents
for their unconditional support, and my big brothers and sister for inspiring me to pursue higher
education and graduate school. Mi éxito es tu éxito.
iii
Table of Contents
Acknowledgments………………………………………………………………………..................……...ii
List of Tables ………………..…………………………………………………………………….…...….vi
List of Figures……………………...………………………………………………………..……....……vii
Abstract……………………...………………………………………………………..……....………….viii
Introduction…………………...………………………………………………………………..……...……1
Study 1: Examining the spatial distribution and clustering of vape and cannabis retailers in Southern
California…………………...……………………………………………..……………………...15
Introduction…………………...………………………………………………..…….…..15
Methods ………………….………………………………………..………………....…..20
Results ……………………………………………………………..…………….…..…..28
Discussion…………………...……………………………...……..…………………......34
Limitations…………………...………………………………...………...................……41
Study 2: Content analysis of Instagram posts by cannabis retailers in Southern California: implications for
cannabis use, prevention, and regulation …………………...………..……………………..……45
Introduction …………………...…………………………………………………...…….45
Methods ……………………...…………………………………………………...……...49
Results ……………………...……………………………………………….…...……....52
Discussion …………………...………………………………………………….…..…...53
Limitations …………………...…………………………………………………...……..60
Study 3: The associations between recall of music videos with e-cigarette promotion, engagement with
music videos with e-cigarette promotion and e-cigarette use among young adults in
California………………………………………………………………………………………....65
Introduction …………………...…………………………………………………..……..65
Methods …………………...……………………………………………….…..….……..68
Results …………………………………………………………………………………...71
Discussion …………………...……………………………………….………..….……..75
Limitations …………………...…………………………………………………...……..81
Overall Conclusions………..…………………...…………………………………………………..……..82
References…………………...……………………..…………………………………………..….……....85
vi
List of Tables
Table 1. Population characteristics of census tracts in Los Angeles
by retailer type and density level, 2019…………………………………………….....…………31
Table 2. Comparing population characteristics across low and high
retailer density neighborhoods in Los Angeles, 2019………………………………...….………33
Table 3. Descriptive statistics of themes associated with cannabis
retailer Instagram posts………………………………………………………………..…….…...53
Table 4. Sample Characteristics……………………………………..………………..….….…...74
Table 5. Adjusted and weighted regression analyses of recall
and engagement with music videos featuring e-cigarettes ………..………………….…….…....75
vii
List of Figures
Figure 1. Theoretical Model ……………………………………………………………….……10
Figure 2. Theoretical Framework for Study 1 …………………………………….……….……11
Figure 3. Theoretical Framework for Study 2 …………………………………………….….…12
Figure 4. Theoretical Framework for Study 3 …………………………………………….….…13
Figure 5. Mean retailer density in Los Angeles
by retailer type, 2019.…………………………………………………………..……………..…30
Figure 6. Images representative of cannabis retailer marketing themes………….……….…..…62
viii
Abstract
The aims of the three papers are to examine the marketing strategies of e-cigarette and
cannabis retailers by examining two key distribution channels: retailer storefronts and digital
media platforms. Study 1 built on the growing body of research that has examined tobacco
retailer density and neighborhood socio-demographics by examining the spatial distribution of
vape shops and cannabis retailers in Los Angeles, California. This study described the current
methodological problems commonly found among research examining retailer density and
demonstrated a different approach using spatial analytic techniques to examine and measure
demographic characteristics of retailer clusters. Study 2 examined how cannabis retailers in Los
Angeles market their products on social media sites like Instagram, which allows users of all
ages to follow retailer accounts, view and like images without health warnings or age
verification. Study 2 builds on Study 1 by examining the social media marketing strategies of
cannabis retailers in Los Angeles identified in Study 1. Finally, study 3 extended the research on
e-cigarette product placement in popular media by measuring active recall of e-cigarette
marketing exposure in music videos and engagement with music videos featuring e-cigarette
marketing, rather than passive exposure alone among young adults in California. This approach
allows for a more nuanced examination of how impactful product placement can be on popular
media platforms among young adult populations. Each study represents a different source of e-
cigarette or cannabis product marketing exposure. Though each source is distinct, these
exposures in the built and online environments are cumulative and can influence social norms,
personal perceptions, and intentions to use. All three study findings indicate that demographic
characteristics may influence the intensity or degree of marketing exposure to retailer storefronts,
social media marketing, and consumption of popular music videos featuring e-cigarette
ix
promotion and imagery. Retailer storefronts, social media marketing, and product placement in
popular media can serve as a visual cue that triggers substance-related thoughts, desires, and
urges, which in turn can influence substance use behaviors. Collectively, Study 1, Study 2, and
Study 3 move forward the literature on e-cigarette and cannabis availability and marketing
exposure among priority and vulnerable populations.
1
Introduction
Electronic cigarette (e-cigarette) and cannabis products represent relatively new,
overlapping, and emerging product markets. Since entering the United States (U.S.) marketplace
in 2007, e-cigarette products have evolved, from disposable e-cigarettes designed to look like
combustible cigarettes (e.g., “cigalikes”), to prefilled or refillable pod mod devices (e.g., JUUL)
compatible with prefilled pod cartridges containing nicotine or THC (the main psychoactive
chemical in cannabis) (CDC, n.d.). Sales of e-cigarettes in the U.S. increased 122.2% from 2014
to 2020, indicating significant market growth over the past decade (Ali et al., 2020). Legalized
cannabis markets are also growing in the U.S. Colorado, and Washington were the first U.S.
states to legalize recreational cannabis sales in 2012 (NCSL, 2021). However, recreational
cannabis is now legal in 19 U.S. states, including California, with the country’s largest legal
cannabis economy at $3.5 billion (NCSL, 2021; Yakowicz, 2021). U.S. sales of legalized
cannabis grew to $17.5 billion in 2020, a 46% increase from 2019 (Yakowicz, 2021). In addition,
polysubstance use of e-cigarettes and cannabis is common, especially among priority populations
like adolescents and young adults (McDonald et al., 2016). Polysubstance users reported using
the same vape device for both nicotine and cannabis and visited cannabis retailers and vape
shops to purchase nicotine and cannabis concentrates (McDonald et al., 2016). Given these
growing and overlapping product markets, it is critical to examine the marketing strategies of e-
cigarette and cannabis retailers by examining two key distribution channels: retailer storefronts
and digital media platforms (e.g., social media and music videos).
Retailers and businesses use marketing strategies to increase and maintain their competitive
advantage, requiring a value-creating strategy that competing businesses cannot employ as
effectively (Varadaraian & Jayachandran, 1999). Physical storefronts and digital media platforms
2
are important distribution channels for e-cigarette and cannabis industry marketing strategies.
Physical storefronts serve as an important source of e-cigarette and cannabis products (Schiff et
al., 2020; Zhu et al., 2019). Storefronts allow retailers to increase their competitive advantage
through advertising (store interior and store exterior, billboards) and price-related promotions
(e.g., coupons, multi-pack promotions, discounts) at the point of sale (Chaloupka et al., 2002).
Digital media platforms like social media sites allow retailers and businesses to reach current and
potential customers by showcasing products, product prices, promotions, and discounts, raising
brand awareness, promoting events, and disseminating marketing messages online to users
(Moreno et al., 2018). Music videos have also become an important marketing channel for e-
cigarette companies. Companies like KandyPens and Mig Vapor have utilized product placement
of e-cigarette and vaping products in popular music videos, viewed on interactive and engaging
platforms like YouTube (Escobedo et al., 2021). E-cigarette and cannabis use among priority
populations is on the rise, and e-cigarette and cannabis marketing exposure is associated with
substance use, greater intention to use, and more positive expectancies regarding use (D’Amico
et al., 2018; Majmundar et al., 2021). Therefore more research on these key distribution channels
is needed.
During the past decade, use of electronic cigarettes and cannabis has increased markedly in
the U.S. Among high school students in the U.S., current e-cigarette use increased from 1.5% in
2011 to 20.8% in 2018 (Cullen et al., 2018). Among adults 18 to 24 years of age, current use of
e-cigarettes increased from 5.2% in 2017 to 7.6% in 2018, a significant increase, while use
among adults 25-44 years of age plateaued and use declined among adults 45 years and older
(Dai & Leventhal, 2019). Among adolescents and adults in the U.S., non-Hispanic Whites,
compared to Hispanic/Latino, Black, and Asian Americans, have the highest rates of e-cigarette
3
ever use and e-cigarette past month use (Villarroel, Cha, Vahratian, 2020: Wang et al., 2019).
Cannabis use has also increased among priority populations. The legalization of cannabis
through state-level medical cannabis and adult recreational use laws has increased the
availability of cannabis products in the United States (Leung et al., 2018). Among adolescents,
past-month cannabis use has plateaued in recent years (ranging from 6.5% to 7% from 2015-
2018). However past-month cannabis use among young adults increased significantly from
19.8% (6.9 million users) in 2015 to 22.1% (7.5 million users) in 2018 (SAMHSA, 2019).
Among adults 26 years of age and older, past-month use of cannabis products increased from
6.5% to 8.6% (SAMHSA, 2019). Among adolescents (12-17 years of age), cannabis use was
highest among Black and Native American populations (17.2%), compared to Hispanic/Latino
(16.5%), Non-Hispanic Whites (16.1%), and Asian Americans (5.8%) (SAMHSA, 2020).
Cannabis use among young adults (18-25 years of age) was highest among Non-Hispanic Whites
(55.6%), compared to Native American (51.7%), Black (49.1%) Hispanic/Latino (48%), and
Asian American (30.3%) populations (SAMHSA, 2020).
Given the increase in e-cigarette and cannabis use among priority populations, examining
which communities have higher concentrations of e-cigarette and cannabis retailers is an
important public health issue. Retailers who specialize in the sale of e-cigarette products are
commonly known as vape shops. Previous research on tobacco retailers found that higher
tobacco retailer density is associated with a higher percentage of ethnic minority residents and
lower-income residents (Laws et al., 2002; Hyland et al., 2003; Schneider et al.; 2005; Peterson
et al., 2001; Rodriguez et al., 2013). In addition, several studies found positive associations
between tobacco retailer density and cigarette use among youth and adult residents (Peterson et
al., 2005; Reid et al., 2005). While there is an established body of research examining retailer
4
tobacco retailer density, few studies have examined the spatial distribution and clustering of vape
and cannabis retailers. There is a lack of research using spatial methods to identify statistically
significant vape and cannabis retailer clusters and cluster characteristics in the United States
(Agaku et al., 2021). Research by Dai and colleagues (2017) found that higher vape shop density
is associated with greater proportions of ethnic minority residents and higher poverty levels at
the national level. A 2020 study in California found that neighborhoods with cannabis retailers
had higher proportions of ethnic minority residents and residents living below the poverty line
(Unger et al., 2020). In addition, neighborhoods with only unlicensed cannabis retailers had
higher proportions of ethnic minority residents and lower proportions of non-Hispanic White
residents
To our knowledge, no study has examined the spatial distribution and clustering of vape
and cannabis retailers across the same geographic area in one study. Research on e-cigarette and
cannabis retailer density is needed, especially in states like California. Over the past decade,
there has been a proliferation of vape shops in Western states (Ayers et al., 2016; Van Dam,
2019), and in 2019, the state of California had the largest legal cannabis market in the world,
reporting over $3.1 billion in legal sales (McGreevy, 2019a). However, illicit cannabis sales in
California were estimated to reach $8.7 billion in 2019 (McGreevy, 2019a). Despite legalized
sales and recreational use in California, unlicensed cannabis sales may continue to surpass legal
sales given the costs of growing and selling cannabis as a licensed retailer under state cannabis
regulations (McGreevy, 2019a). Though recreational cannabis use was approved by 57% of
California voters, around 76% of cities and 69% of counties in California banned the retail sale
of cannabis (McGreevy, 2019b). Licensed cannabis businesses can deliver cannabis to any
physical address in the state of California, however as of August 2020, over 20 local
5
governments (e.g., Riverside, Beverly Hills, Arcadia, Temecula, and Palmdale) have filed
lawsuits against the state to ban delivery in local governments that banned retail sales (Blood,
2020). Given that cigarette use and tobacco-related diseases tend to concentrate among lower-
income populations (Campaign for Tobacco Free Kids, 2020), and tobacco retailer density is
associated with ethnic minority residents, it is significant to examine whether vape and cannabis
retailers are concentrated in communities at higher risk for health disparities.
In addition, given the increased use of e-cigarette and cannabis products, it is critical to
examine marketing strategies used by e-cigarette and cannabis retailers on popular media
platforms, especially platforms popular among youth and young adults (e.g., social media, music
videos). In states like California, cannabis marketing on television, radio, print, or digital
communications are only allowed when 71.6% or more of the audience is assumed to be at least
21 years of age (California Legislative Information, 2016a). However, the most common source
of cannabis marketing is social media (Rup, Goodman & Hammond, 2020). Cannabis retailers in
California and other states have established an online presence by using social media sites like
Instagram to showcase their products, raise brand awareness, promote events, and disseminate
marketing messages to current and potential customers, often without age restrictions and health
warnings (Moreno et al., 2018). California law restricts cannabis marketing on social media,
however little information exists about how cannabis marketing accounts are regulated on social
media. Legal cannabis retailers report social media accounts being permanently shut down on
Instagram for violating advertising restrictions (Bourque, 2019), however, it is not clear how
state agencies or social media sites enforce cannabis marketing regulations online. Given the lack
of regulatory enforcement, research is needed to document and describe cannabis retailer
6
marketing practices on social media sites like Instagram to understand how marketing exposure
may impact use behaviors among priority populations.
A recent longitudinal study found that adolescents with greater exposure to cannabis
advertising were more likely to report cannabis use, have greater intention to use in the future,
and have more positive expectancies about cannabis use (D’Amico et al., 2018). In addition, in
states with legalized cannabis use, exposure to cannabis marketing on social media was
associated with a greater likelihood of cannabis use (Whitehill et al., 2020). Also, +youth who
liked or followed a cannabis business on at least one social media platform were five times more
likely to have used cannabis in the past year (Trangenstein et al., 2019).
It is also critical to examine e-cigarette marketing strategies used in popular media
platforms like music videos. The multi-state Master Settlement Agreement (MSA) of 1998
restricted paid tobacco product placement in television, music videos, and motion pictures (Truth
Initiative, n.d.). However, the MSA only applies to the cigarette and smokeless tobacco
companies that signed the agreement and does not apply to new tobacco companies or emerging
tobacco products like e-cigarettes and vape pens. The MSA also does not apply to online
marketing, such as e-cigarette or vape brand websites or social media content, which do not
always require age verification or health warnings (Escobedo et al., 2018). As a result, in music
videos, e-cigarette product placement (e.g., scenes with visible branding, a visible logo, branded
merchandise, or gear such as a branded hat or shirt) is currently unrestricted. Music videos
featuring vape pen product placement, such as the 2019 video “I’m the One” by DJ Khaled, have
been reviewed over 1.4 billion times on YouTube (Allem, 2017a). This video featured 8.5
seconds of vape pen product placement and imagery, which allows the video to deliver over 5.6
7
billion impressions (1.3 billion views x 4 scenes) of e-cigarette product placement and use
without warning statements or age verification.
Though research on e-cigarette product promotion in music videos is limited, studies on
combustible tobacco products found that exposure to product placement on film is associated
with greater cigarette use (Sargent et al., 2001). In addition, on-screen tobacco use by celebrities
and other prominent figures is associated with positive views about smoking, intention to smoke
and cigarette use (Tickle et al., 2001; Dal Cin et al., 2007). E-cigarette marketing exposure was
associated with a greater likelihood of ever and current use of e-cigarettes and increased
susceptibility to use among non-e-cigarette users (Mantey et al., 2016). Research on engagement
with e-cigarette marketing by Hebert et al. (2017) found that adolescents who were susceptible to
and reported lifetime or current use of tobacco and e-cigarettes were more likely to engage with
tobacco and e-cigarette related content on social media.
A recent study found that young adults exposed to e-cigarette product placement or
imagery in music videos were more likely to report lifetime and past-month e-cigarette use
(Majmundar et al., 2021). In addition, higher levels of exposure versus no exposure was
associated with lifetime and past-month e-cigarette use (Majmundar et al., 2021). Participants in
the study were provided a list of music videos featuring e-cigarette product placement and asked
to indicate which videos they had watched, also known as priming. This is like previous research
which measured how many adolescents had watched sampled music videos featuring e-cigarette
use (Cranwell et al., 2015). While these studies measured the level of exposure to music videos
with e-cigarettes, no study to our knowledge has examined the level of awareness or recall of
music videos featuring e-cigarettes or engagement with music videos featuring e-cigarettes.
8
Given the increase in vape and cannabis use, it is important to examine the spatial
distribution and clustering of vape and cannabis retailers in areas like the City of Los Angeles,
given the proliferation of vape and cannabis retailers in California over the past decade (Ayers et
al., 2016; Van Dam, 2019). A growing body of research on tobacco retailers found that higher
tobacco retailer density was associated with greater proportions of ethnic minority and lower-
income residents, however, few studies have used spatial methods to identify retailer clusters in
the United States. It is also important to examine how cannabis retailers use popular social media
platforms like Instagram to market and advertise products to users of all ages. In California,
cannabis marketing on digital media is allowed if most of the audience is assumed to be at least
21 years of age. However, the most common source of cannabis marketing exposure was social
media (Rup et al., 2020). Social media as a marketing channel represents a public health issue as
exposure to, and interaction with cannabis marketing through social media was associated with
greater cannabis use (Whitehill et al., 2020; Trangenstein et al., 2019). Little information exists
about how cannabis content on social media is regulated and how retailers advertise cannabis
products to social media users. Therefore, more research examining social media marketing
strategies by cannabis retailers is needed. While the MSA restricts tobacco product placement in
television, movies and music videos, these restrictions do not apply to e-cigarette products,
resulting in e-cigarette product placement in music videos with over 1.3 billion views (Allem et
al., 2017a). E-cigarette marketing exposure is associated with greater use and increased
susceptibility to use (Mantey et al., 2016). However, few studies examine recall of and
engagement with e-cigarette promotions and imagery in popular music videos.
In response, this dissertation project addressed these gaps in the literature by
investigating in three different but interrelated studies: 1) examine the spatial distribution and
9
clustering of vape and cannabis retailers in Los Angeles, 2) analyzing Instagram posts among
cannabis retailers with storefronts in Los Angeles, and 3) examining the associations between
recall of and engagement with music videos featuring e-cigarette product placement or imagery
and e-cigarette use among young adults in California.
Theoretical Framework
The aims of the three papers are to understand how marketing through two key
distribution channels: retailer storefronts and digital media platforms, can impact beliefs and
attitudes toward substance use, which in turn, may influence vaping and cannabis use behaviors
among vulnerable and priority populations with greater product availability and greater
marketing exposure. The processes by which cannabis and tobacco marketing impacts beliefs,
attitudes, and use behaviors is complex, but is conceptualized using the United States Institute of
Medicine’s determinants of population health model, which is adapted from Dahlgren and
Whitehead (IOM, 2003; Dahlgren & Whitehead, 1991) (Figure 1). This model includes five
interacting levels: 1) innate individual traits (age, sex, race, and biological factors) and the
biology of disease, 2) individual behaviors (e.g., smoking, substance use, exercise, diet), 3)
social, family and community networks, 4) living and working conditions (e.g., socioeconomic
status, natural and built environment), and 5) broad social, economic, cultural, health and
environmental conditions and policies at local, state, national and levels (e.g., cultural values,
sociopolitical shifts in government). The built environment includes housing, transportation, and
other elements of city planning.
The IOM model proposes that understanding and improving population health requires an
understanding of determinants of health and the ecological nature of health. This model
demonstrates how multiple determinants of population health interact to influence population
10
health outcomes. For example, social, cultural, and environmental conditions and policies (level
5) influence and shape working and living conditions (level 4) as well as behavioral and
biological determinants of health (levels 1-2).
Figure 1.
Theoretical Model: U.S. Institute of Medicine’s determinants of population health model
Within the context of Study 1, neighborhood socioeconomic status, neighborhood
sociopolitical capital, e-cigarette and cannabis legalization, retailer zoning laws, as well as
tobacco and cannabis retailer policies at the state and local level (level 5) influence the location
of retailers in the Los Angeles area (level 4). If e-cigarette and cannabis retailers are clustered in
vulnerable communities, greater availability of these products may influence social norms among
peer and family networks within the communities (level 3), which in turn may influence e-
cigarette and cannabis use behaviors (level 2), which vary by race/ethnicity (level 1). In addition,
neighborhood socioeconomic status, neighborhood sociopolitical capital, cannabis retailer
11
policies, regulatory enforcement of retailer cannabis laws and policies, and zoning laws (level 5)
influence the location and density of unlicensed cannabis retailers in the Los Angeles area (level
4). If unlicensed cannabis retailers are clustered in vulnerable communities, and these retailers
are not in compliance with city and state retailer policies, these communities may be exposed to
greater levels of cannabis products (regulated and unregulated), marketing, promotions, and
advertising, which may influence social norms among peer and family networks within the
communities (level 3), which in turn may influence cannabis use behaviors (level 2), which vary
by race/ethnicity (level 1). The theoretical model for Study 1 is presented in Figure 2.
Figure 2
Theoretical Framework for Study 1
Within the context of study 2, neighborhood socioeconomic status, neighborhood
sociopolitical capital, cannabis retailer policies, regulatory enforcement of retailer cannabis laws
and policies, and shifting cultural values (level 5) influence the location and licensing status of
cannabis retailers in the Los Angeles area, as well as cannabis retailer business practices in the
built and online environment (level 4). If the online retailer environment allows community
12
members of all ages to view product menus, advertising, marketing activities and directs users of
all ages to licensed and unlicensed retailer stores in their communities, greater exposure, and
availability to these products may influence social norms among peer and family networks at the
community level (level 3), which in turn may influence cannabis use behaviors (level 2), which
vary by race/ethnicity (level 1) (Figure 3).
Figure 3
Theoretical Framework for Study 2
Within the context of study 3, federal and local regulation (or lack thereof) of e-cigarette
product placement across media platforms in the United States (level 5) may influence the extent
of e-cigarette product placement in music videos (level 4). If the digital media environment
allows users to view and engage with music videos featuring e-cigarette product placement,
greater exposure, and engagement with these music videos may influence social norms at the
community level (level 3), which in turn may influence individual e-cigarette use behaviors
(level 2) (Figure 4).
13
Figure 4
Theoretical Framework for Study 3
Study 1 built on the growing body of research that has examined tobacco retailer density
and neighborhood socio-demographics by examining the spatial distribution of vape shops and
cannabis retailers in Los Angeles, California. This study geocoded and produced maps of vape
and cannabis retailers in the city and used spatial methods to identify statistically significant vape
and cannabis retailer clusters. Demographic characteristics from the American Community
Survey (ACS) 2015-2019 5-year estimates were examined among neighborhoods in retailer
clusters. Study findings can be used to inform future surveillance and public health campaigns
and policy regarding retailer zoning laws.
Study 2 builds on Study 1 by describing the social media marketing content of cannabis
retailers identified in Study 1 to understand how retailers in Los Angeles use Instagram as a
marketing channel. Study 2 conducted a content analysis of cannabis retailer content posted on
Instagram to summarize the image and text data and reported the underlying themes in the data.
The themes identified in this study can inform the design of media campaigns that aim to counter
cannabis marketing on Instagram, especially among youth and young adults.
14
Study 2 described the marketing content of cannabis retailers and the potential
implications of marketing exposure. However, Study 3 moves beyond marketing exposure to
measure unprimed recall of e-cigarette marketing in music videos and engagement with music
videos featuring e-cigarette marketing and examines whether recall of marketing exposure is
associated with e-cigarette use. For example, companies like KandyPens promote their vape pen
devices using product placement in music videos, which can be used with nicotine and cannabis
e-liquid solutions.
15
Study 1
Examining the spatial distribution and clustering of vape and cannabis retailers in
Southern California
Introduction
Research over the past two decades has established that higher tobacco retailer density is
associated with greater proportions of ethnic minority and lower-income residents in the United
States (U.S.) (Rodriguez et al., 2013; Laws et al., 2002; Schneider et al., 2005; Peterson et al.,
2011; Hyland et al., 2003). However, research on vape and cannabis retailer spatial distribution
is needed, especially in states like California, given the proliferation of vape shops in Western
states (Ayers et al., 2016; Van Dam, 2019) and the recent legalization of adult-use cannabis in
2018 (California Cannabis Portal, 2021). In addition, research indicates that Southern California
and Los Angeles County have the greatest proportion of unlicensed cannabis retailers in
California (Unger et al., 2020). Therefore, it is important to examine whether cannabis retailers,
both licensed cannabis retailers (LC) and unlicensed cannabis retailers (ULC), are concentrated
in neighborhoods at higher risk for adverse health outcomes. The current study examined the
spatial distribution and clustering of vape and cannabis retailers in Los Angeles and examined
demographic characteristics among neighborhoods in retailer clusters. Study findings can
provide a better understanding of the physical environments that may influence health behaviors
and health outcomes, can help inform future surveillance and public health campaigns and
policy regarding retailer concentration limits.
There is a paucity of research using spatial methods to examine vape and cannabis
retailer density in the United States (Agaku et al., 2021). This is concerning as a study examining
the spatial distribution of vape shops in South Africa found that proximity to vape shops was
16
associated with lifetime e-cigarette use among adults ages 18-19 (Agaku et al., 2021). Most
studies measuring tobacco and vape shop density do so by counting the number of vape shops
per census tract of a given study area (Dai et al., 2017). However, this method does not allow us
to explore whether cannabis retailers are distributed evenly throughout a census tract or if
retailers are located on the same city block. It is also possible that a cluster of retailers may be
separated into different census tracts when calculating density by census tract boundaries.
Moreover, aggregating spatial data into census tracts leads to the Modifiable Areal Unit Problem
(MAUP) (O’Sullivan & Unwin, 2010). MAUP arises when aggregation units, such as census
tracts, are arbitrarily drawn for the spatial phenomena being examined (i.e., retailer storefront
locations). Census tracts are small geographic entities with boundaries drawn to follow
permanent features (e.g., streets, highways, rivers) in such a way that the average population is
about 4,000 people (U.S. Census, n.d.). However, tracts vary widely in size and shape. Two
different aggregation schemes applied to the same set of spatial data points may result in
different patterns and statistical results. To address MAUP related issues, distances between all
data points can be calculated to examine the point pattern. Point pattern analysis is used to
quantify the pattern and distribution of point data and to determine whether data points are
evenly distributed throughout the study area or whether there is clustering of data points in the
study area. More research is needed that moves beyond simply counting the number of retailers
in a census tract and focuses more on using spatial analysis methods to understand how retailers
are distributed across geographic areas.
Research examining retailer clusters is needed, as previous research on vape shops
focused on vape shop closure, vape shop marketing activities, vape shop handling of e-liquids, as
well as attitudes, perceptions, and behaviors of vape shop retailers (Allem et al., 2015; Garcia et
17
al., 2016a; Garcia et al., 2016b; Galimov et al., 2020a; Sussman & Barker, 2017). Existing
research on vape shop locations at the national level indicates that higher vape shop density was
associated with greater proportions of Hispanic and Asian American residents and higher poverty
levels (Dai et al., 2017). In addition, a study by Bostean et al. (2018) of Orange County,
California, found that census tracts with vape shops versus no vape shops were more likely to
have Latino residents, higher poverty levels, lower educational outcomes, and higher tobacco
retailer density. These findings indicate a growing health inequity, as tobacco retailer density,
cigarette use, and tobacco-related diseases tend to be concentrated among lower-income
populations (Campaign for Tobacco Free Kids, 2020). Given the existing tobacco-related health
disparities faced by lower-income communities, it is important to examine the characteristics of
neighborhoods located within vape shop clusters.
In addition, research on vape shops may be limited by how vape shop retailers are
defined. Several studies on vape shop characteristics (Garcia et al., 2016b; Galstyan et al., 2019;
Sussman et al., 2014; Sussman et al., 2016) define vape shops as retailers that exclusively sell e-
cigarettes, vaping products, and related accessories (Lee et al., 2018). However, studies on vape
shop density included vape shops that sell other smoking products and accessories (e.g., hookah
pipes, bongs) (Giovenco, 2018) and included other types of retailers (e.g., convenience stores,
markets) known to sell e-cigarette products (Berg et al., 2020b). Defining vape shops as retailers
that exclusively sell e-cigarette and vaping products has served as a meaningful way to
operationalize retailers over the past decade, however vape shops are beginning to sell products
and e-liquid solutions that contain cannabidiol (CBD) and tetrahydrocannabinol (THC) (Kong et
al., 2017a; Berg et al., 2021; Berg et al., 2020a). Given that the U.S. Food and Drug
Administration (FDA) defines a vape shop as a retailer that can sell a variety of tobacco
18
products, including e-cigarette devices (e.g., e-cigars, e-hookahs, vape pens, personal vaporizers,
e-pipes), e-cigarette components or parts, or e-liquids for personal consumption (FDA, 2016),
research on vape shop location should include vape shops that sell other tobacco, CBD or THC
products and accessories.
Like vape shop research, few studies have used spatial statistical methods to examine the
presence of cannabis retailer clusters in the United States (Agaku et al., 2021). A 2020 study in
California found that neighborhoods with cannabis retailers had higher proportions of ethnic
minority residents and residents living below the poverty line (Unger et al., 2020). In contrast,
neighborhoods with only ULC retailers were found to have higher proportions of ethnic minority
residents and lower proportions of Non-Hispanic White (NHW) residents (Unger et al., 2020). In
Los Angeles, after the 2013 approval of Proposition D, which set zoning restrictions and limited
the number of medical marijuana dispensaries (MMD’s), MMD’s were more likely to open up in
communities with higher proportions of African-American residents (Thomas & Freisthler,
2017). A 2016 study exploring medical marijuana dispensaries and neighborhood characteristics
in Los Angeles found a positive relationship between higher dispensary density and percent of
Hispanic residents (Thomas & Freisthler, 2016). A study across 39 California cities found that
communities with higher rates of poverty and alcohol outlets were at increased odds of having an
MMD (Morrison et al., 2014). In addition, a study examining cannabis abuse or cannabis
dependence hospitalizations per zip code using a Bayesian space-time misalignment Poisson
model from 2001 to 2012 found greater medical marijuana dispensary density and lower median
household income was associated with greater rates of cannabis-related hospitalizations in
California (Mair et al., 2015). Marijuana dispensary density was measured by calculating the
number of dispensaries per square mile in each zip code, and cannabis abuse and dependence
19
were found to occur more frequently in lower-income areas (Mair et al., 2015). Living in areas
with greater cannabis retailer density was associated with more frequent cannabis use during the
past more and more positive expectations about cannabis use (Shih et al., 2019). Availability
theory suggests that this new market of legalized cannabis will increase cannabis use among the
local community beyond the illicit sales they would replace (Stockwell & Gruenwald, 2004).
More research examining the spatial distribution and clustering of LC and ULC retailers is
needed in California, as the state had the largest legal cannabis market in the U.S. in 2019
(McGreevy, 2019a).
Information about the location and density of ULC retailers in Los Angeles is limited.
The California Bureau of Cannabis Control (BCC) and the Los Angeles Department of Cannabis
Regulation (DCR) have not publicly released data or listings related to ULC retailers within city
limits (Queally & Welsh, 2019). In May 2019, a report using the online directory Weedmaps
found 365 cannabis retailers located inside Los Angeles city limits, of which 220 (60%) were not
listed on the city’s list of LC retailers (Queally & Welsh, 2019). Examining ULC retailer density
is an important public health issue, given that ULC retailers may sell e-liquids and pods
containing THC and nicotine solutions associated with severe pulmonary disease (Schier et al.,
2019). In addition, cannabis products sold by ULC retailers may contain toxic pesticides, toxic
metals (e.g., lead, copper, arsenic compounds), and residual solvents (Craven et al., 2019).
California requires that LC retailers test cannabis products for the presence of over 60 pesticides,
potentially reducing exposure to chemicals contaminants that are well-documented as being
carcinogenic, neurotoxic, and associated with a range of birth defects (Craven et al., 2019).
No study to our knowledge has examined the spatial distribution of vape and cannabis
retailers to analyze demographic characteristics of retailer clusters. This study builds on existing
20
research by using spatial point pattern analyses to identify the presence and location of vape and
cannabis retailer clusters in Los Angeles. Demographic characteristics from the American
Community Survey (ACS) 2015-2019 5-year estimates were examined in neighborhoods with
low retailer density and neighborhoods in retailer clusters. Study findings can be used to inform
future surveillance and public health campaigns and policy regarding retailer concentration
limits.
Hypothesis: Compared to neighborhoods with lower retailer density, neighborhoods in vape and
cannabis retailer clusters will have greater proportions of ethnic minority residents, greater
proportions of foreign-born residents, and greater proportions of lower-income residents.
Methods
To examine the spatial and clustering patterns of vape and cannabis retailers, we gathered
data on vape and cannabis retailers with storefronts in the city of Los Angeles using popular
online directories, online search engines, and state retailer licensing lists. Demographic
characteristics of neighborhoods with low retail density were compared to neighborhoods in
retailer clusters (high retailer density). For this study, a neighborhood was defined as the area
within a census tract boundary.
Vape Shop Retailers
Though the FDA regulates tobacco products (including e-cigarette products), there is no
federal registry of vape shop storefronts. Some states, like California, do not differentiate
between vape shops and other tobacco retailers on state tobacco retailer licensing lists (Public
Health Law Center, 2019). In June 2016, California state law expanded the definition of a
tobacco product for licensing purposes to include electronic cigarettes, vape pen/vaporizers, e-
liquids, vaporizers and e-hookah, and any tobacco product component, part, or accessory
21
(CDTFA, n.d.). In 2019, a list of retailers licensed to sell tobacco products was obtained from the
California Department of Tax and Fee Administration (CDTFA). The CDTFA list does not
differentiate between tobacco and vape shop retailers, and no publicly available database of vape
shop retailers in California exists. Therefore, to identify vape shops in Los Angeles, we used
online directories such as Yelp, which has been used in previous studies (Sussman et al., 2014;
Sussman et al., 2016; Burbank, Thrul & Ling, 2016; Dai, Hao & Catley, 2017), Google, and
Smokeshops (smokeshops.com). Using the search terms “vape shop,” “vape storefront,” “vape
store,” we searched these online directories for retailers with a zip code within Los Angeles city
limits (LAHD, 2007). Online directories like Yelp, Smokeshops, and Google allow retailers to
categorize and label their business as a “vape shop,” “head shop,” “tobacco shop,” “smoke
shop,” or “vaporizer store.”
Retailers can list their businesses with multiple labels to reflect the variety of products
sold. If a retailer was labeled as a “vape shop” or “vaporizer store,” coders reviewed the retailer
listing or retailer website to check if any vape products were sold. If the coder was unable to
determine if vaping products were sold based on information provided online, they called the
retailer and asked if vaping products were sold on-site. For the purposes of this study, a vape
shop was defined as 1) retailer with a physical storefront, 2) storefront located within Los
Angeles, 3) retailer sold any vaping products (disposal device, e-cigarette, vape pen or pen-like,
rechargeable device, Mod or mech-mod rechargeable device, Box Mod, JUUL, other pod mod or
another type of electronic nicotine device) and identified as a vape shop, tobacco shop or smoke
shop, 4) retailer sells products to the public (not a manufacturer, wholesaler), and 5) retailer was
not listed as “permanently closed” on Yelp or Google. If a retailer was listed as closed, the
business was called or emailed to confirm if the store was open. If the retailer did not respond,
22
the storefront was coded as closed. If a retailer was found to sell vape products and meet
inclusion criteria, store address, contact information, and retailer website links were recorded.
Licensed Cannabis Retailers
Cannabis retailers were identified using publicly available information online to allow for
future updating of the cannabis retailer database. Publicly available lists of LC retailers were
obtained from the state of California Bureau of Cannabis Control (BCC) and Los Angeles
Department of Cannabis Regulation (DCR). For this study, a LC retailer was defined as 1)
retailer with a physical storefront, 2) storefront located within Los Angeles, 3) retailer is listed on
BCC and DCR cannabis licensing lists, and 4) retailer was not listed as “permanently closed” on
Yelp or Google. An online search was conducted to determine if each retail storefront was still
operating (open) or closed (shut down permanently). First, the name of each retail storefront was
entered into the Google search engine (Google.com). Several storefronts had identical names as
the same company owned them (e.g., Medmen); however, each storefront address was
independently verified. If search results featured links to Yelp (yelp.com), Weedmaps
(weedmaps.com), or Google Reviews, these websites were examined first. Research by
Pendersen et al. (2018) found that using both Weedmaps and Yelp provided the most accurate
and updated information about the operation status and location of medical marijuana
dispensaries (Pedersen et al., 2018). Weedmaps does not indicate whether a retailer has closed.
However, Yelp and Google Reviews allow users to report closed businesses. If a retailer was
listed as closed, the business was called or emailed to confirm if the store was open. If the
retailer did not respond, the storefront was coded as closed. For all storefronts identified as being
open, business name, storefront address, license information, contact information, and retailer
social media links (e.g., Instagram, Facebook, Twitter, Snapchat) were recorded.
23
Unlicensed Cannabis Retailers
To identify ULC retailers, a list of all cannabis retailers on Weedmaps with a storefront in
Los Angeles was obtained from the Weedmaps website in April 2019 (n = 399). All cannabis
retailers with a state and city license were removed from the Weedmaps list. For this study, a
ULC retailer was defined as 1) retailer with a physical storefront, 2) storefront located within Los
Angeles, 3) retailer is not listed on BCC and DCR cannabis licensing lists, and 4) retailer was not
listed as “permanently closed” on Yelp or Google. To determine if each retail storefront was still
operating (open) or closed (shut down permanently), an online search was conducted using the
Weedmaps list. First, the name of each ULC retailer was entered into the Google search engine
(Google.com). Each storefront address was independently verified. If search results featured
links to business listings on Yelp (yelp.com), or Google Reviews, these websites were examined
first. If a retailer was listed as closed, the business was called or emailed to confirm if the store
was open. If the retailer did not respond, the storefront was coded as closed. For all storefronts
identified as being open, business name, storefront address, license information, contact
information, and retailer social media links (e.g., Instagram, Facebook, Twitter, Snapchat) were
recorded.
Given that Weedmaps was facing pressure to remove ULC retailers during our data
collection period (Staggs, 2019), we conducted a separate online search for ULC retailers using
Yelp, Google, and other online cannabis directories that allow ULC retailers to advertise
(Smokeshops.com, Craigslist, Potguide, Muncheez, Leafbuyer, Wheresweed). Using the search
terms “cannabis shop,” “cannabis storefront,” “cannabis retailer,” “weed shop,” we searched for
ULC storefronts located within Los Angeles city limits (LAHD, 2007). If a ULC retailer was
listed as closed, the business was called or emailed to confirm if the store was open. If the
24
retailer did not respond, the storefront was coded as closed. For all storefronts identified as being
open, business name, storefront address, contact information, and retailer social media links
(e.g., Instagram, Facebook, Twitter, Snapchat) were recorded.
Data were collected from April 2019 to December 2019. During data collection, 68 vape
shops, 193 LC retailers, and 331 ULC retailers were identified. For all retailers, if the business
address could not be verified online or by contacting retailers, the retailer was listed as “can’t
verify.” Data were cleaned by removing duplicates and any retailers coded as “closed” or “can’t
verify” was removed, resulting in 4.6% (n = 9) of LC retailers and 21.1% (n = 70) ULC retailers
being removed from the sample.
Data Preparation
The analytic sample consisted of 68 vape shops, 184 LC retailers, and 261 ULC cannabis
retailers. Vape and cannabis retailer addresses were geocoded and mapped using ArcMap and
ArcGIS World Geocoding Service. Among the 68 vape shop retailers, 99% (n = 67) of the
records matched a street address within Los Angeles city boundaries. Among the 184 LC
retailers, 99% (n = 183) of the records matched a street address within Los Angeles city
boundaries. Among the 261 ULC retailers, 88% (n = 231) of the records matched a street address
within Los Angeles city boundaries. Several of the ULC retailer addresses were described as
being in Los Angeles, however geocoding in ArcGIS revealed they were in surrounding cities,
such as East Los Angeles, Huntington Park, and Compton. For this study, geocoded datapoints
and census tract boundaries were projected to California State Plane Coordinate System (SPCS)
NAD 83 StatePlane California V FIPS 0405 (U.S. Feet). The final analytic sample included 481
retailers.
25
TIGER/Line shapefiles for the 2015-2019 American Community Survey (ACS) census
tracts were obtained from the U.S. Census website, and census tracts located in or intersecting
Los Angeles city boundaries (n = 997) were retained. Among the census tracts included in the
analytic sample, six census tracts intersected city boundaries. For each of these tracts, the
percentage of the tract located within the city of Los Angeles was calculated using ArcGIS
ArcMap (version 10.7.1) tabulate intersection tool, and the percentages ranged from 43.83% to
90.27%.
Analysis Plan
To examine vape shop, LC retailer and ULC cannabis retailer point patterns, the kernel
density (KD) tool in ArcMap was used to transform point data into a continuous surface of
density estimates (O’Sullivan & Unwin, 2010). To conduct a KD estimation function, a
smoothed quartic curve surface is fitted over each data point (Esri, n.d.). The surface value is
highest at the point and declines with increasing distance from the point, reaching zero at the
search radius (Esri, n.d.). The resulting KD maps indicate which neighborhoods in Los Angeles
have retailer “hotspots” by mapping density values. The search radius for all KD analyses was
2.5 miles, representing a 5 to 10-minute drive (Unger et al., 2020). Given that KD values could
vary across a census tract, a mean KD value for each tract was calculated using the zonal
statistics as table tool in ArcMap. Mean density value tables were then joined with their
corresponding census tract shapefile.
To create a choropleth map of mean KD values, the mean KD values were classified. To
classify mean KD values for data visualization and census tract level analyses, the values were
separated into four classes, with lower mean KD values representing lower retailer density and
higher mean KD values representing higher retailer density. Preliminary analysis revealed mean
26
KD values for all retailer types were positively skewed. Given that the data was skewed, nested
means classification was selected to use a method specific to the data and mathematically
straightforward. Data classification aims to maximize between-class differences and minimize
within-class differences, therefore the number of census tracts within each class varied. To
calculate the four classes, the mean of all mean density values, µ, was calculated, and a class
break is placed at µ, separating the data into two classes: values below the mean and values
above the mean. Data were further classified by calculating the mean of these two classes and
inserting a class break at the mean below µ and the mean above µ. Group 1 (all values from zero
to the first class break), Group 2 (all values from the first class break to µ), Group 3 (all values
from µ to third class break), and Group 4 (all values from third class break to the maximum
value). Census tracts in Group 1 are called the low density group, census tracts in Groups 2 and 3
are called the medium density group, and census tracts in Group 4 are called the high density or
cluster group. A map with the KD raster output and a choropleth map of mean density values
were computed separately for each retailer type.
Demographic data were obtained from the ACS 2015-2019 5-year estimate. Using
ArcMap, demographic characteristics were joined with their corresponding census tract for all
census tracts in Los Angeles (n = 997). The percentage of each ACS demographic variable, as
well as the corresponding margin of error (MOE) and coefficient of variation (CV) was
calculated for all census tracts in Los Angeles. Unlike the decennial census, the ACS five-year
estimates are based on survey data from a portion of the total population and subject to sampling
error. The MOE measures the magnitude of sampling error, and the CV measures the relative
amount of sampling error associated with a sample estimate. A smaller CV indicates that the
standard error is small relative to the estimate, signifying the estimate is close to the population
27
value, while a larger CV indicates that the estimate has a large amount of sampling error and
may not be reliable. To calculate race/ethnicity, we calculated percent Hispanic, percent NHW,
percent Black or African American, and percent Asian American. To calculate Nativity, we
calculated the percent of foreign-born residents per tract. To calculate Low Income, we created a
dichotomous variable that categorized census tracts as lower-income (1 = median household
incomes at or below $49,713), or higher income (0 = median household income at or above
$49,714). The income limit of $49,713 was selected as it represents 80% of the median
household income for Los Angeles County (Md = $62,142) based on the ACS 2015-2019 5-year
estimate (HCD, 2020). This measure is based on the income limits by the U.S. Department of
Housing and Urban Development (HUD) which define families as “low-income” if family
income does not exceed 80% of the median family income for the local area (HCD, 2020; HUD,
2019).
To compare race/ethnicity in low versus high density groups, the average percent of each
race/ethnicity variable was calculated for all tracts. To compare Nativity in low versus high
density groups, the average percent of foreign-born residents was calculated for all tracts. To
compare low income neighborhoods in low versus high density groups, the percent of census
tracts coded as low income was calculated for all tracts. A two-sample t-test compared the
average percentage for all race/ethnicity variables across low density and cluster groups, and the
average percent of foreign-born residents across low density and cluster groups. We reported
demographic mean estimates, mean differences, t-test, and p-values for all analyses by retailer
type. A two-sample test of proportions compared the percentage of lower-income neighborhoods
in low versus high density groups. We reported mean estimates, mean differences, z-test and p-
28
value by retailer type. A level of significance of α ≤ 0.05 was used in all statistical analyses.
Statistical analyses were conducted in Stata 15.
Results
Descriptive Statistics
Table 1 shows population characteristics for all neighborhoods in Los Angeles and
population characteristics for neighborhoods with low density, medium density, and retailer
clusters by retailer type, as well as the MOE and CV for race/ethnicity and foreign-born ACS
estimates. For all census tracts in Los Angeles, the mean percent of Hispanic residents was
47.76% (the largest ethnic/racial group in the city). In comparison, the mean percent of NHW
residents was 29.31%, the mean percent of African American residents was 8.60%, the mean
percent of Asian American residents was 11.79%, the mean percent of foreign-born residents
was 36.73%, and 38% categorized as lower income. In Los Angeles, 38.11% of census tracts had
low vape shop density, 16.85% were in a vape shop cluster, 30.89% had low LC density and
16.70% were in a LC retailer cluster, 38.31% had low ULC retailer density, and 15.24% were in
an ULC retailer cluster.
Density Values
Mean density values were calculated for all census tracts in Los Angeles, classified into
four groups and mapped separately for vape shops, LC retailers, and ULC retailers (Figure 1).
The four colors noted in Figure 5 represent census tracts with low retailer density (pink), census
tracts with medium retailer density (light and dark orange), and census tracts with high
density/clustering (red). Among retailers, ULC retailers had the highest mean density value (M =
0.75), followed by LC retailers (M = 0.44) and vape shops (M = 0.21). Three colors represent
29
storefront retailer locations for vape shops (blue), LC retailers (green) and ULC retailers
(yellow), and blue lines represent the freeway systems within Los Angeles.
30
Figure 5
Mean retailer density in Los Angeles by retailer type, 2019.
30
31
Table 1
Population characteristics of census tracts in Los Angeles by retailer type and density level, 2019.
Census
tracts
non-Hispanic
white
Hispanic African
American
Asian
American
Foreign-born % Low
Income
n
(%)
Mean
Est.
(%)
MOE
(%)
Mean
Est.
(%)
MOE
(%)
Mean
Est.
(%)
MOE
(%)
Mean
Est.
(%)
MOE
(%)
Mean
Est.
(%)
MOE
(%)
(%)
City of Los Angeles 997 100 29.31 4.49 47.76 6.81 8.60 4.20 11.79 4.07 36.74 7.24 38.01
Vape Shops (n = 68)
Low Density 380 38.11 22.26 3.98 55.43 6.19 12.17 4.25 8.15 3.27 33.99 5.73 37.37
Medium Density 449 45.03 35.57 4.89 42.85 6.76 6.47 3.38 12.20 4.04 36.13 5.94 30.29
High Density (clusters) 168 16.85 28.37 4.58 43.72 7.11 6.28 3.35 18.87 4.66 44.51 5.92 60.12
Licensed Cannabis (n = 183)
Low Density 308 30.89 23.97 4.36 52.33 6.65 10.27 4.27 11.33 3.94 34.33 5.67 34.42
Medium Density 522 52.35 29.60 4.30 47.22 6.68 7.87 3.34 12.70 3.83 38.44 5.88 39.27
High Density (clusters) 167 16.70 38.14 5.31 41.14 6.37 7.85 3.78 9.79 3.80 35.80 7.63 40.72
Unlicensed Cannabis (n = 231)
Low Density 382 38.31 43.51 5.73 37.22 6.13 4.34 3.72 11.81 4.24 32.06 5.90 14.40
Medium Density 463 46.43 25.34 4.26 50.86 6.79 9.60 3.52 11.80 3.87 37.96 5.87 41.25
High Density (clusters) 152 15.24 6.14 2.10 64.55 7.34 16.16 4.20 11.75 2.85 44.64 5.68 87.50
Notes: Est = Estimate, MOE = margin of error, Coefficient of Variation (CV) for non-Hispanic White ranged from 3.73 to 91.19, CV for Hispanic ranged from 2.28 to 100.13,
CV for African American race ranged from 6.62 to 607.9, CV for Asian American range from 4.58 to 197.57, CV for foreign-born ranged from 5.56 to 121.58.
31
32
Vape Shops
Compared to neighborhoods with low retailer density, neighborhoods with high retailer
density had significantly higher proportions of NHW (22.26% vs. 28.37%), Asian American
(8.15% vs. 18.8%), and foreign-born (33.9% vs. 44.5%) residents (Table 2). In contrast,
compared to neighborhoods with low retailer density, neighborhoods with high retailer density
had significantly lower proportions of Hispanic (55.4% vs. 43.7%) and African American
(12.1% vs. 6.2%) residents. Compared to neighborhoods with low retailer density,
neighborhoods with high retailer density had significantly higher proportions of low-income
residents (37.3% vs. 60.1%).
Licensed Cannabis Retailers
Compared to neighborhoods with low retailer density, neighborhoods in LC retailer
clusters had significantly higher proportions of NHW residents (23.97% vs. 38.14%) and
significantly lower proportions of Hispanic residents (52.3% vs 41.1%). The proportion of
African Americans, Asian Americans, and low-income residents did not differ significantly
between low density and LC retailer cluster neighborhoods.
Unlicensed Cannabis Retailers
Compared to neighborhoods with low retailer density, neighborhoods in ULC retailer
clusters had significantly higher proportions of Hispanic (37.2% vs. 64.5%), African American
(4.34% vs. 16.1%), and foreign-born (32% vs. 44.6%) residents. In contrast, compared to
neighborhoods with low retailer density, neighborhoods in ULC retailer clusters had significantly
lower proportions of NHW residents (43.51% vs. 6.14%). Compared to neighborhoods with low
retailer density, neighborhoods in ULC retailer clusters had significantly higher proportions of
33
lower income residents (14.3% vs. 87.5%). The proportion of Asian Americans residents did not
differ significantly between low density and ULC retailer cluster neighborhoods.
Table 2
Comparing population characteristics across low and high retailer density neighborhoods by retailer
type in Los Angeles, 2019.
Low Density High Density (Clusters)
census
tracts
(n)
M
%
SD
census
tracts
(n)
M
%
SD
Δ delta
low to high
t
p
Vape Shops (n = 68)
non-Hispanic white 376 22.26 27.03 168 28.37 23.0 +6.11 -2.54 0.01
Hispanic 376 55.43 30.75 168 43.72 24.53 -11.07 4.35 <.001
African American 376 12.17 16.68 168 6.28 5.80 -5.89 4.45 <.001
Asian American 376 8.15 9.31 168 18.87 15.48 +10.71 -9.98 <.001
Foreign-born 376 33.99 10.69 168 44.51 13.63 +10.51 -9.70 <.001
Licensed Cannabis (n = 183)
non-Hispanic white 304 23.97 26.63 167 38.14 25.47 +14.16 -5.60 <.001
Hispanic 304 52.33 28.37 167 41.14 29.42 -11.18 4.03 <.001
African American 304 10.27 14.85 167 7.85 8.05 -2.42 1.95 0.05
Asian American 304 11.33 11.38 167 9.79 9.92 -1.54 1.47 0.14
Foreign-born 304 34.33 12.05 167 35.80 12.44 +1.46 -1.24 0.21
Unlicensed Cannabis (n = 231)
non-Hispanic white 378 43.51 27.28 152 6.14 8.77 -37.36 16.53 <.001
Hispanic 378 37.22 28.46 152 64.55 23.64 +27.32 -10.47 <.001
African American 378 4.34 4.94 152 16.16 16.75 +11.81 -12.43 <.001
Asian American 378 11.81 9.10 152 11.75 16.60 -.060 0.05 0.95
Foreign-born 378 32.06 11.73 152 44.64 12.89 +12.58 -10.84 <.001
Low Density High Density (Clusters)
census
tracts
(n)
M
SE
census
tracts
(n)
M
SE
Δ delta
low to high
z
p
Vape Shops (n = 68)
% Low Income 380 .373 .024 168 .601 .037 +22.7% -4.94 <.001*
Licensed Cannabis (n = 183)
% Low Income 308 .344 .027 167 .407 .038 +6.3% -1.36 0.17
Unlicensed Cannabis (n = 231)
% Low Income 382 .143 .017 152 .875 .026 +73.1% -15.96 <.001*
34
Discussion
To our knowledge, this is the first study to examine the spatial distribution of vape, LC,
and ULC cannabis retailers in California. By examining the spatial distribution and clustering of
three different retailer types in Los Angeles, California, the largest city in California and second-
largest city in the U.S., this study provides novel information about census tract level
characteristics associated with vape shops and cannabis retailers. Our study found significantly
higher proportions of low-income, Asian American, NHW, and foreign-born populations in vape
shop clusters compared to neighborhoods with low vape shop density. We found significantly
higher proportions of NHW residents in LC clusters compared to neighborhoods with low LC
density and found significantly higher proportions of lower-income, Hispanic, African
American, and foreign-born populations in ULC clusters compared to neighborhoods with low
ULC density. Our study reveals several notable findings that confirm and add to the limited
research examining vape and cannabis retailer concentration and sociodemographic disparities.
In Los Angeles County, in 2019, the lifetime use of e-cigarettes was highest among NHW
(12.8%), followed by Asian Americans (8.9%), Hispanic/Latinos (6.1%), and African Americans
(5.8%) (Du et al., 2019). Our study findings are in line with county-level e-cigarette use
behaviors, as we found significantly higher populations of NHW and Asian American residents
among vape shop clusters compared to neighborhoods with low vape shop density. We also
found significantly lower populations of Hispanic and African American populations in vape
shop clusters compared to neighborhoods with low vape density. Our findings are also consistent
with a study in New Jersey which found that census tracts with at least one vape shop had higher
proportions of NHW residents and lower proportions of African American residents (Giovenco
et al., 2016). However, most research examining the associations between higher vape shop
35
density and demographic characteristics is mixed and varies by the study region. Research in
Orange County, California, found that census tracts with at least one vape shop had significantly
higher percentages of Hispanic and Asian American residents (Bostean, Sanchez & Lippert,
2018). Research at the national level also found that higher vape shop density was associated
with higher proportions of Hispanic and Asian American residents but was not associated with
NHW residents (Dai et al., 2017). Mixed findings may be a result of how density is measured. In
addition, the location of vape shop storefronts may be driven by local customer demand and
retailers seeking out storefronts in areas with more affordable rent.
Our study found higher proportions of foreign-born and low-income residents in vape
shop clusters compared to neighborhoods with low vape shop density. These findings are
consistent with previous studies (Dai et al., 2017; Bostean, Sanchez & Lippert, 2018) and
research by the CDC showing that low-income adults are more likely to use e-cigarette products
compared to higher income adults (CDC, 2020b). Moreover, research by Escobedo et al. (2019)
found that e-cigarettes were more likely to be sold and advertised in lower-income NHW
communities compared to other ethnic groups. Escobedo et al. (2019) also found that exterior e-
cigarette advertising was most common among tobacco retailers in NHW and African American
communities, even though e-cigarette use among African Americans is low in Los Angeles and
at the national level (CDC, 2020b; Du et al., 2019). Our study found that African Americans
were the ethnic group least likely to live in vape shop clusters. Future research should explore if
e-cigarette marketing via the retail environment and exterior advertisements.
Unlike traditional tobacco product advertising, targeted e-cigarette advertising may be
perceived as a harm reduction strategy. More vape shops in low-income communities may be
beneficial as tobacco retailer density, cigarette use, and tobacco-related diseases tend to be
36
concentrated among lower-income populations (Campaign for Tobacco Free Kids, 2020).
However, the role of e-cigarette products as a smoking cessation device is controversial. A 2021
review of randomized clinical trials showed that providing adult smokers with e-cigarette devices
was associated with greater levels of smoking cessation (Wang et al., 2021). In contrast, a
longitudinal study among adolescents showed that e-cigarette use among non-susceptible never-
smokers predicted combustible cigarette use (Aleyan, Cole & Qian, 2018). Thus, e-cigarette
devices may attract adolescents who would otherwise be unlikely to initiate combustible
cigarette use. While the perception of vape shops as a positive presence in a community is
debatable, greater concentrations of vape shops may increase e-cigarette and combustible
cigarette use among youth and young adults.
Vape shops are popular sources of e-cigarette products for youth and young adults. A
2018 study among adolescents in Los Angeles County found that 61% of respondents reported
purchasing e-cigarettes from a vape shop (Zhu et al., 2019). In addition, among e-cigarette users
18 to 20 years of age living in California, most purchased e-cigarettes products at vape shops,
compared to gas stations, convenience stores, the internet, or other sources (Schiff et al., 2020).
These findings are concerning as a 2019 study in California found that nearly 50% of tobacco
and vape shops did not verify the age of underage decoys attempting to buy vaping products
(Roeseler et al., 2019). The rise in e-cigarette use among priority populations (Cullen et al.,
2018; Dai & Leventhal, 2019) is an important public health issue, given that one pod of popular
vaping products like JUUL contains roughly the same amount of nicotine as 20 cigarettes (Truth
Initiative, 2019b). The high blood levels of nicotine in e-cigarette users are likely to cause
physiological changes in nicotinic acetylcholine receptors in the brain, increasing future nicotine
dependence (HHS, 2016). In addition, previous research indicates that the aerosol emitted from
37
e-cigarette devices contains particulate matter containing carcinogenic chemicals, heavy metals,
and silicate nanoparticles found in combustible cigarettes (Chapman, 2015). Recent research on
e-cigarette flavored pods like JUUL determined the chemical constituents present in various
flavors and found that the constituents induced oxidative stress, inflammation, epithelial barrier
dysfunction, and DNA damage in lung cells (Muthumalage et al., 2019). This is concerning
given that oxidative stress and inflammation responses in the lungs make smokers and vapers
more susceptible to viral and bacterial infections like COVID-19 (Kaur et al., 2020). Identifying
vape retailer clusters in Los Angeles is critical as vape shops are an important source of e-
cigarette and vape products for several priority populations.
Consistent with previous research (Unger et al., 2020), we found larger populations of
NHW residents in LC clusters compared to neighborhoods in ULC clusters. While 38% of
residents in LC clusters were NHW, only 6.1% of residents in ULC clusters were NHW. In
addition, like Unger et al. (2020), we found larger populations of low-income residents in ULC
clusters (87.5%) compared to LC clusters (40.7%). Our findings that ULC clusters had larger
Hispanic and African American populations compared to LC clusters are also consistent with a
report examining LC and ULC retailer density in LA County (Nicholas et al., 2019). While
previous research examined race/ethnicity and income characteristics of cannabis retailers, our
study is the first to examine the percentage of foreign-born populations among LC and ULC
retailer clusters. Los Angeles has a substantial foreign-born population (36.7%), making it an
ideal area to examine how foreign-born populations vary by retailer type and density groups.
Given that 44.6% of residents in ULC clusters are foreign-born, our findings indicate a need for
culturally and linguistically tailored cannabis educational campaigns in neighborhoods with
greater exposure to ULC storefronts.
38
Our findings on ULC retailers signifies a critical public health inequity, as certain
demographic groups are disproportionally exposed to greater levels of unlicensed cannabis
products. In states like California, legal cannabis products can only be purchased at a cannabis
retailer licensed by the state (California Legislative Information, 2016b). LC retailers must also
adhere to state regulations related to cannabis manufacturing, packaging, labeling, and zoning
restrictions, as well as product testing and advertising and marketing restrictions (California
Legislative Information, 2016b). For example, a LC retailer may only sell cannabis products,
cannabis accessories, and licensees’ branded merchandise or promotional materials and are
prohibited from selling cigarettes and other tobacco products (BCC, 2019). LC retailers cannot
package cannabis goods, may only receive cannabis products from a licensed distributor, and all
cannabis products must comply with packaging and labeling requirements and regulations (BCC,
2019). LC retailers must also verify the age and identification of all customers before granting
customers access to the retail area (BCC, 2019). Licensed cannabis retail storefronts can only be
located outside of a 700-foot radius of pre-established sensitive locations (e.g., public park,
public library, alcoholism or drug abuse recovery or treatment facility, day care center) and other
zoning restrictions (Los Angeles Municipal Code, 2017b). To apply for one of the limited
numbers of retailer cannabis licenses from the BCC, applicants must meet serval prerequisites
which include compliance with the California Environmental Quality Act, obtaining a Sellers
Permit from the California Department of Tax and Fee Administration (CDTFA), as well as a
$5,000 bond payable to the State of California (BCC, 2020a). Retailers are required to pay $1000
to submit a license application, and annual state licensing fees vary based on expected gross
revenue for the 12-month licensing period and can range from $2500 (for stores expecting to
make $500k or less) to $96,000 (for stores expecting to make more than 7.5 million) (2020b).
39
The inability for new businesses to apply for licensure, significant licensing fees, business taxes,
and sales taxes may be contributing to the growth or continuation of ULC retailers in Los
Angeles. While the city of Los Angeles monitors the location of LC retailers and provides maps
of LC retailer locations, little was known about the location and density of ULC retailers. The
City of Los Angeles municipal code limits the number of cannabis retailers based on 2016 ACS
population data such that there should only be one LC retailer per 10,000 residents to prevent
‘undue concentration’ in neighborhoods (Los Angeles Municipal Code, 2017a). However, ULC
retailers can grow, manufacture, and sell unregulated cannabis products to consumers through
retail storefronts that are not in compliance with city or state cannabis policy.
Understanding which demographic groups have greater exposure and availability to
cannabis products is an important step as cannabis product use varies by ethnicity and age group.
A study examining changes in cannabis use among high school students from 2005 to 2015
found that African American and Latino students reported an increase in use during the past
decade, while NHW students did not show an increase in use during this time (Keyes et al.,
2017). In addition, an increase in cannabis use among African American high school students
was greater in states with legalized medical marijuana (Keyes et al., 2017). Past-month cannabis
use among young adults increased significantly from 19.8% (6.9 million users) in 2015 to 22.1%
(7.5 million users) in 2018 (HHS, 2019). In addition, rates of cannabis use disorder peak at age
18 (Vasilenko, Evans-Polce & Lanza, 2017). While rates of cannabis use disorder generally
decline across adulthood, rates of cannabis use disorder are higher for Black individuals
compared to NHW and Latino individuals (Vasilenko, Evans-Polce & Lanza, 2017). This
difference indicates that cannabis use may lead to more negative consequences for Black
individuals compared to other groups.
40
In addition, greater availability and advertising of cannabis products may influence
perceptions, attitudes, and beliefs about cannabis products, which in turn may influence use
behaviors. These effects may be even more profound among populations living in LC and ULC
retailer clusters. Furthermore, greater access to cannabis products within lower income, ethnic
communities may exacerbate already existing health disparities (Dai, Hao & Catley, 2017;
Rodriguez et al., 2013; Thorton et al., 2016). Public health officials and policymakers can use
findings from this study to design and implement tailored intervention and prevention programs
aimed at tobacco and cannabis use among residents living in neighborhoods with vape and
cannabis retailer clusters. Study findings should also be disseminated to community-based
organizations focusing on substance use prevention and treatment. Findings can be used in
educational campaigns to educate residents living in areas with higher retailer concentration
about the adverse health outcomes associated with tobacco and cannabis use and educate
residents about the health risks associated with using unlicensed cannabis products. The findings
from this study can also inform policy and tobacco and cannabis control enforcement efforts
aimed at limiting tobacco and cannabis retailer density in Los Angeles. Future research should
examine populations of youth and young adults among vape, LC and ULC clusters in Los
Angeles, as well as examine the proximity of youth-friendly locations (e.g., schools, parks,
libraries) and other vulnerable locations (e.g., colleges, substance abuse treatment centers) to
retailer clusters. In addition, to validate our definition of vape shops, future research should
examine how e-cigarette users and non-users define and classify vape shops by showing
participants photos of vape and tobacco retailers with 50% of merchandise consisting of e-
cigarette products or accessories, retailers with 25% of merchandise consisting of e-cigarette
41
products, and retailers with 10% of merchandise consisting e-cigarette products or accessories to
understand how different groups classify vape and tobacco retailers.
Limitations
The data on ULC retailers were limited to those identified on popular online directories.
While previous research found that using both Weedmaps and Yelp provided the most accurate
and updated information about the operation status and location of medical marijuana
dispensaries (Pederson, 2018), Weedmaps was facing pressure from state officials to remove
ULC retailers during our data collection period. Therefore, a separate online search for ULC
retailers was conducted using Yelp, Google, and other online cannabis directories that allow
ULC retailers to advertise. However, it is still possible that this study did not include ULC
retailers who did not advertise on these websites.
Data collection was conducted in 2019, more than a year after the legalization of adult-use
cannabis. Therefore, the data presented will only represent the cannabis retail environment at the
time of data collection. The total number of LC retailers will fluctuate as existing retailers close
and new licenses are issued by the Los Angeles Department of Cannabis Regulation. In addition,
the total number of ULC retailers will fluctuate as new businesses open and existing businesses
close, some in response to enforcement efforts by city officials. Future research should examine
the attitudes, perceptions, and beliefs of ULC retailers regarding cannabis regulation and the
cannabis licensure process to understand which factors (e.g., applications costs, distrust of
government) may discourage retailers from pursuing a state or city cannabis license.
In addition, the data presented will only represent the vape shop retail environment at the
time of data collection. The total number of vape shops will fluctuate over time as existing
retailers close and new retailers open. For example, previous research on vape shops in Southern
42
California (Kong et al., 2017b) found that of the 72 vape shops surveyed during 2014, 22% (n =
16) closed by 2015. Findings about vape and cannabis retailer density in Los Angeles may not
generalize to other areas. It is also important to note that data collection was completed before
the state of California issued coronavirus (COVID-19) stay-at-home orders, which went into
effect on March 19, 2020. Stay-at-home orders required non-essential businesses to remain
closed or to operate at limited capacity depending on county-level COVID-19 positivity rates or
health equity metrics until June 2021. While licensed cannabis businesses were categorized as
essential businesses on March 21, 2020, tobacco or vape retailers were not considered essential
businesses (Romero, 2020). Future research should examine the spatial distribution of vape and
cannabis retailers after COVID-19 stay-at-home orders were phased out in June 2021 to examine
whether the spatial distribution of vape and cannabis retailers changed over time in response to
state and county level health mandates.
The range of CV values for ACS race/ethnicity and foreign-born estimates for census tracts
in Los Angeles ranged from a low of 2.28 (Hispanic) to a high of 607.9 (African American),
indicating that some estimates may not be reliable. An ACS estimate with a CV greater than 15%
is considered unreliable therefore, results should be interpreted with caution (U.S. Census, 2009).
In addition, given the high CV values among the ACS data, the ACS values were not analyzed as
continuous explanatory variables, limiting the type of statistical analyses that could be used.
Also, in the difference of means testing, the reported p values may not be reliable if several tracts
in given means had unreliably high coefficients of variation. Future research should group
together or aggregate census tracts until CV values fall below the 15% threshold. The mean
value for each ACS demographic variable, as well as the MOE and CV, was calculated at the
census tract level in this study and mean values at the census tract level were used in the
43
analyses. However, future research should calculate the descriptive statistics, the MOE and CV
values, and conduct statistical analyses using the actual counts of residents in each census tract,
which would allow us to aggregate the actual counts of residents when grouping or aggregating
census tracts. The MOE and CV values would then be adjusted for each count in each tract,
allowing for a more accurate analysis.
Future research should consider analyzing demographic data from the 2020 U.S. Census. It
is important to note that the 2020 U.S. Census data was collected during the coronavirus
(COVID-19) pandemic, which may have impacted 2020 Census data quality (Pew Research
Center, 2020). Data quality research and data quality metrics such as the Census Bureau
Demographic Analysis provided by the U.S. Census Bureau should be examined prior to the use
of 2020 U.S. Census data to assess data accuracy (Pew Research Center, 2020).
Conclusion
To our knowledge, this is the first study to examine the spatial distribution and clustering
of vape, LC, and ULC retailers. We identified 68 vape shops, 183 LC retailers, and 231 ULC
retailers in Los Angeles, calculated the kernel density estimation for each retailer type, and
calculated the mean density value for all census tracts in Los Angeles (N = 997) based on kernel
density scores. Our study found significantly higher proportions of low-income, Asian American,
NHW, and foreign-born populations in vape shop clusters compared to neighborhoods with low
vape shop density. We also found significantly higher proportions of NHW residents in LC
clusters compared to neighborhoods with low LC cannabis density, however, we observed
significantly higher proportions of lower-income, Hispanic, African American, and foreign-born
populations in ULC clusters compared to neighborhoods with low ULC retailer density. Our
study reveals several notable findings that confirm and add to the limited research examining
44
vape and cannabis retailer concentration and sociodemographic disparities. Findings can help
target tobacco and cannabis control enforcement efforts, help target health campaigns about e-
cigarette and cannabis use, and inform future policies on undue concentration and zoning laws
that can limit tobacco and cannabis retailer density.
45
1 Study 2
Content analysis of Instagram posts by cannabis retailers in Southern California:
implications for cannabis use, prevention, and regulation
Introduction
One of the most common sources of cannabis marketing exposure is social media (Rup,
Goodman & Hammond, 2020). However, little information exists about how cannabis
advertisements are regulated on social media sites by state or local agencies (Bourque, 2019).
The lack of regulation and enforcement allows cannabis retailers to establish an online presence
by using social media to showcase products, raise brand awareness, promote events, and
disseminate marketing messages to current and potential customers, often without age
restrictions and health warnings (Moreno et al., 2018). Therefore, it is critical to examine
marketing practices used by cannabis retailers on social media sites, especially sites popular
among adolescents and young adults such as Instagram. Currently, only one study has analyzed
cannabis retailer marketing content on social media (Jenkins et al., 2021). The lack of research
on marketing practices used by cannabis retailers is concerning as exposure to cannabis
marketing may contribute to cannabis use behaviors among adolescents and other priority
populations (D’Amico et al., 2018; Whitehill et al., 2020). In addition, identifying and describing
retailer marketing messages is important for the design of counter messaging directed at
underage cannabis use, and future surveillance and enforcement efforts (Cavazos-Rehg et al.,
2016; Jenkins et al., 2021).
Currently, 19 states have legalized adult-use cannabis (NCSL, 2021). As more states
continue to legalize cannabis use, social media (e.g., Instagram, Twitter) is emerging as an
important platform to capture and document the context in which people use and market
46
cannabis products (Allem et al., 2020; Majmundar et al., 2016). This is problematic as 85% of
teens ages 13-17 reported having at least one social media account (Ballard, 2019), and 45% of
teens reported using the internet almost constantly, a stark increase from 24% of teens in 2014-
2015 (Anderson & Jiang, 2018). Among adults, social media use is highest among younger
adults (18 to 29 years of age) (Pew Research Center, 2019). Social media data can capture user-
generated images and text, which can be analyzed to inform public health and policy
(Eysenbach, 2011). Instagram is one of the most used social sites among youth and adults.
Among teens, 72% reported using Instagram (Anderson & Jiang, 2018). Among young adults
aged 18 to 24 years, 75% reported using Instagram, and 42% of adults reported visiting
Instagram several times a day (Perrin & Anderson, 2018). Instagram allows its users to take or
upload photos, edit photos, and provide each photo with an accompanying caption on its
platform. Instagram users can make their accounts public (anyone online can view) or private
(only approved users can view account content). Instagram, which is owned by Facebook,
prohibits individuals, retailers, or companies from advertising, promoting, or selling cannabis
products, even if the retailer or user is in a state with legalized cannabis use (Instagram, 2021). In
addition, cannabis retailers are not allowed to provide contact information (e.g., phone number,
email, street address) for their business (Instagram, 2021). However, given the lack of active
enforcement of these restrictions by Instagram and external regulatory agencies, cannabis
retailers can use their social media accounts to send followers of all ages updates when they post
on its platform (Moreno et al., 2018).
In states like California, cannabis advertising or marketing on television, radio, print, or
digital communications can only be displayed if 71.6% of the audience is assumed to be at least
21 years of age (California Legislative Information, 2016a). However, among U.S. states with
47
legalized cannabis, social media was one of the most common sources of cannabis marketing
reported by adolescents and adults and was a more popular source of cannabis marketing than
other websites, emails, or print media (Rup, Goodman & Hammond, 2020). Exposure to
cannabis marketing on social media is a public health concern as a recent longitudinal study
found that adolescents with greater exposure to cannabis advertising were more likely to report
cannabis use, greater intention to use in the future, and more positive expectancies about
cannabis use (D’Amico et al., 2018). In states with legalized cannabis, exposure to cannabis
marketing on social media was associated with a greater likelihood of cannabis use (Whitehill et
al., 2020). What is more, adolescents who liked or followed a cannabis business on at least one
social media platform were five times more likely to have used cannabis in the past year
(Trangenstein et al., 2019). More research examining marketing messages and themes on social
media is needed to understand how marketing exposure may impact use, especially among
adolescents and young adults.
Existing research examining how cannabis is discussed and advertised on social media
focuses mostly on how users and cannabis companies or brands discuss and market cannabis
products. Previous research on Twitter found that most posts about cannabis use from May 2018
to December 2018 were related to cannabis initiation, the use of cannabis for health and medical
issues, buying and selling of cannabis, cannabis concentrates, craving cannabis, and
polysubstance use (Allem, Escobedo & Dharmapuri, 2020). Research by Cavazos-Rehg et al.
(2016) identified and content analyzed posts with cannabis-related hashtags on Instagram from
November to December 2014. Posts showing cannabis buds and leaves were most common,
followed by images of cannabis concentrates, cannabis use, and cannabis-related advertisements
(Cavazos-Rehg et al., 2016). More recently, a study by Jenkins et al. (2021) examined marketing
48
content from June 2017 to May 2018 for 14 cannabis retailers located in Alaska, Oregon,
Colorado, and Washington on Facebook and Instagram using a cyber-ethnographic approach
(Jenkins et al., 2021). Researchers examined retailer social media posts and completed in-depth
observational field notes, which were analyzed for common themes. The predominant theme
observed was the normalization of cannabis, while subthemes included broad appeal and specific
targeting of audiences (Jenkins et al., 2021). However, this study did not include social media
marketing content from California cannabis retailers as cannabis was legalized during the data
collection period. Examining cannabis retailer marketing content in California is critical;
however, no study to date has examined social media marketing content among California
cannabis retailers. In 2020, California had the largest legal cannabis market in the country,
reporting over $4.4 billion in sales, an increase of 57% from 2019 (Bartlett, 2021), and an illicit
cannabis market estimated to have reached $8.7 billion in 2019 (McGreevy, 2019a).
Additionally, the city of Los Angeles is estimated to be California’s largest and most profitable
legal cannabis market (Queally & Welsh, 2019). More research on the social media marketing
strategies of California based cannabis retailers is needed given the state’s growing cannabis
marketplace.
While cannabis products are often marketed as medicinal and natural products, many
health claims are unsubstantiated (National Academies of Sciences, Engineering, and Medicine,
2017). There is evidence suggesting that pharmaceuticals containing cannabinoids like CBD and
THC may be effective in treating epilepsy, nausea, and vomiting associated with chemotherapy
and appetite loss and weight loss associated with HIV/AIDS (NCCIH, 2019). However, more
research on other health conditions such as anxiety, PTSD, sleep problems is needed to
understand how cannabis impacts symptoms (NCCIH, 2019). Despite the need for more research
49
on cannabis health claims, cannabis retailers in states with legalized cannabis make claims that
cannabis products can be used to treat various health conditions like depression, anxiety, and
pain when marketing products to consumers (Bierut et al., 2017). While most states like
California prohibit advertisements with deceptive, false, or unsubstantiated claims about the
health effects of cannabis products, research examining compliance with state cannabis
advertising laws online is limited.
To examine marketing strategies among cannabis retailers on Instagram, this study
analyzed Instagram posts among cannabis retailers with storefronts in Los Angeles. To our
knowledge, this is the first study to examine social media marketing content among cannabis
retailers in California. This study conducted a content analysis of cannabis retailer content posted
on Instagram to summarize the image and text data and report the underlying themes in the data.
Methods
Data Collection
Publicly available lists of licensed cannabis retailers were obtained from the state of
California Bureau of Cannabis Control (BCC) and the Los Angeles Department of Cannabis
Regulation (DCR). For this study, a licensed cannabis retailer was defined as 1) retailer with a
physical storefront, 2) storefront located within Los Angeles, 3) retailer is listed on BCC and
DCR cannabis licensing lists, and 4) retailer was not listed as “permanently closed” on Yelp or
Google. Retailers who met these inclusion criteria were identified and verified in an online
search, and the retailer's Instagram account for each storefront was recorded.
To identify unlicensed cannabis retailers, a list of all cannabis retailers on Weedmaps with
a storefront in Los Angeles was obtained from the Weedmaps website in April 2019. In addition,
an online search for unlicensed retailers who were not listed on Weedmaps was conducted from
50
August 2019 to December 2019. For this study, an unlicensed cannabis retailer was defined as 1)
retailer with a physical storefront, 2) storefront located within Los Angeles, 3) retailer is not
listed on BCC and DCR cannabis licensing lists, and 4) retailer was not listed as “permanently
closed” on Yelp or Google. Retailers who met these inclusion criteria were identified and
verified in an online search. The storefront address and Instagram account for each retailer were
recorded (see Study 1 for more detail about cannabis retailer data collection).
In February 2020, using the list of licensed and unlicensed cannabis retailers, Instagram
account names were double verified. On March 14, 2020, all publicly available data for retailer
Instagram accounts (n = 111) were scraped (electronically copied from the internet), resulting in
25,155 posts. Data for each Instagram account included: account bios, images, videos, and the
accompanying caption. Data from private or inactive Instagram accounts were not collected. This
study sampled 10% of posts per Instagram account, yielding (n = 2500) posts to analyze.
Coding Procedure
In line with research using Instagram data (Allem et al., 2017b, Allem et al., 2017c), two
investigators worked together to become familiar with the posts, then generated a coding frame
and identified 16 common themes. The goal was to summarize the image-based and text-based
data and report the underlying themes in the posts. The primary themes identified were as
follows: (1) Cannabis plant/flower: images of whole leaves removed form plant, dried flower,
package or container of cannabis flower (2) Electronic products: statements about or images of
vape pens, vape cartridges, and pods, (3) Concentrates: statements about or images of shatter
(brittle, glass-like cannabis extract), budder (smooth consistency like butter or cake frosting),
badder (consistency similar to sauce), crumble (texture falls apart or crumbles when handled),
sugar (viscous, grainy and wet), sauce (sticky, liquid consistency), crystalline (resembles coarse
51
sugar), distillate (translucent oil), rosin/resin (viscous substance), kief (collection of loose
cannabis trichomes), (4) Joints: statements about or images of pre-rolled cannabis joints, (5)
other cannabis products: statements about or images of other cannabis products such as
cannabis-infused edibles (including drinks), lotions, tinctures, oils, soap, or patches, (6)
Accessories: statements about or images of accessories typically used to administer cannabis
products such as bongs and bowls for smoking cannabis flower, dab rings or oil rigs for smoking
dense cannabis concentrates, grinders (used to break up cannabis buds), rolling paper for making
joints, or lighters, (7) Product Use: cannabis product being held, person blowing smoke, (8)
Flavors: any flavored product mentioned in the caption or any visible label or product in an
image listing a flavor name, including citrus, blueberry (flavored products did not include
cannabis strains, colors, or descriptors), (9) Health Claims: any statement about cannabis or
cannabis products being used to treat or cure specific health issues or symptoms, (10) Product
Normalization: cannabis products placed with everyday accessories (e.g. watches, sunglasses,
laptops, books), (11) Sex Appeal: person wearing revealing clothing, person posing suggestively
with product, (12) Social (e.g. groups of people, events), (13) Product Safety: any statements
about health warnings, side effects, how to use product safely, dosage recommendations, (14)
Legal Age to Purchase or Use: any statement or image about the legal age to purchase or use
cannabis products in California (21+), (15) User Experience: any mention of psychoactive
effects (e.g., “head high” or “body high”), physical effects (e.g., “energizing”, “increased
focused”), social effects (e.g., “increases creativity”), taste, sensory profile or product quality,
(16) Promotions: any mention of discounted prices and special promotions such as buy one get
one free, and free giveaways, and (17) Other: any marketing theme not mentioned in previous
themes (e.g., posts of smoke but no product visible, inspirational quotes, memes).
52
Analysis Plan
Two investigators coded posts (n = 200) to determine reliability. Investigators selected all
themes that applied to an individual post. For example, if a post featured cannabis flower and a
vape pen, it would be coded for both Cannabis plant/flower and Electronic products. Percent
agreements for all 17 themes ranged from 84% to 100%. Disagreements were resolved by
discussion between the two coders. Two investigators then coded 1250 posts (images and
accompanying text) each for a total of 2500 posts. Descriptive statistics for the primary themes
were calculated.
Results
The analytic sample (n = 2500 posts) originated from 111 unique Instagram accounts.
Among the sample, the earliest post was from August 2, 2013. Among the sample, 83.6% of
posts consisted of a single image (n = 2,090), 8.4% of posts consisted of a single video (n = 210),
while 8% consisted of slideshows (i.e., more than one image or video per post) (n = 200). The
average number of themes per post was 1.59, the average number of likes per post was 238.86
(Mdn = 56). The average number of comments per post was 5.47 (Mdn = 2). Among posts with
videos, the average number of views per post was 916.30 (Mdn = 210.50).
Among the 2500 posts, 917 (36.69%) featured cannabis plant/flower (Table 3), 347
(13.89%) featured electronic products, 339 (13.57%) featured concentrates, 259 (10.36%)
featured cannabis joints, 383 (15.33%) featured other cannabis products, 130 (5.20%) featured
accessories, 132 (5.28%) featured product use, 379 (15.17%) featured flavors, 93 (3.72%)
featured health claims, 29 (1.16%) featured product normalization, 54 (2.16%) featured sex
appeal, 32 (1.28%), were social themed, 48 (1.92%) featured product safety, 223 (8.92%)
featured user experience, 30 (1.20%) featured legal age to purchase, 261 (10.44%) featured
53
promotions, and 321 (12.85%) were other. Images representative of themes is provided in Figure
6.
Table 3
Descriptive statistics of themes associated with cannabis retailer Instagram posts
Category % N
Primary Theme (n = 2500 posts)
Cannabis plant/flowers 36.69 917
Electronic cannabis products 13.89 347
Cannabis concentrates 13.57 339
Cannabis joints 10.36 259
Other cannabis products 15.33 383
Accessories 5.20 130
Product use 5.28 132
Flavors 15.17 379
Health claims 3.72 93
Product normalization 1.16 29
Sex appeal 2.16 54
Social 1.28 32
Product safety 1.92 48
User experience 8.92 223
Legal age to purchase 1.20 30
Promotions 10.44 261
Other 12.85 321
Discussion
This study is one of the largest Instagram studies to date to focus on cannabis retailer
content, describing 2500 posts from 111 retailer storefronts located in Los Angeles. This study
found that cannabis retailer posts to Instagram often displayed themes related to cannabis flowers
and plants, flavors, electronic cannabis products, cannabis concentrates, other cannabis products,
and promotions. A key finding of this study is that cannabis retailers with public accounts on
Instagram can disseminate a variety of pro-cannabis marketing messages to users of all ages,
often without health warnings or age verification.
In line with previous research (Cavazos-Rehg et al., 2016), posts showing cannabis
plants/flower were most common, and posts showing cannabis concentrates were also commonly
54
observed. Depictions of cannabis plants/flower as well as cannabis concentrates on Instagram
may influence perceptions about cannabis as well as influence cannabis use behaviors, especially
among those most likely to use social media and cannabis: adolescents and young adults (Yu et
al., 2020). Depictions of cannabis products and cannabis use on Instagram can normalize
cannabis use behaviors on social media sites (Roditis et al., 2016). In addition, a longitudinal
study by D’Amico and colleagues (2018) found that adolescents with greater exposure to
cannabis advertising on social media were more likely to report cannabis use, intention to use,
and more positive expectancies about cannabis use. Cannabis use during adolescence can impact
thinking, memory and learning, and while researchers are still understanding how long these
effects last, it is hypothesized that some changes may be permanent (NIDA, n.d.). The perception
that regular cannabis use is not risky has increased markedly among high school students, from
2.7% in 1991 to 21.39% in 2015 (Sarvet et al., 2019). While the perceived risk of cannabis use
has decreased, cannabis potency has increased significantly over the past decade. Using samples
obtained from the U.S. Drug Enforcement Administration (DEA), the mean THC concentration
in cannabis flower has increased from 9.75% in 2009 to 14.88% in 2018 (ElSohly et al., 2021).
Rising THC concentration among cannabis concentrates is particularly alarming, as mean THC
levels increased from 6.7% in 2008 to 55.7% in 2017 (Chandra et al., 2019), and some retailers
claim to sell concentrates with THC concentrates between 70% and 90% (Subritzky, Pettigrew &
Lenton, 2016). Short-term effects of cannabis use include impaired body movement, impaired
memory, altered sense of time, and changes in mood (NIDA, n.d.). However, taking higher doses
of THC can increase the probability of experiencing hallucinations, delusions, and even
psychosis (among regular users of high potency products) (NIDA, n.d.). While not lethal,
overdoses are common when using cannabis products with high TCH levels (Barrus et al., 2016)
55
and may potentially lead to motor vehicle accidents, falls, or poisoning (CDC, 2018). Despite the
high potency of cannabis products being sold today, only 1.92% of cannabis retailer posts in our
sample mentioned product safety, which included recommended dosage, and only 1.20% of
posts mentioned the legal ages to purchase cannabis in California. Given the promotion of
potentially high potency cannabis products on Instagram to users of all ages, it is critical for
public health professionals and policymakers to counter these pro-cannabis messages with
evidence-based information about the risks of cannabis use, especially high potency products, on
social media sites like Instagram.
This study also found that Instagram posts featuring other cannabis products, electronic
cannabis products, and cannabis concentrates were more common than posts about cannabis
joints, which suggests a growing demand for ‘alternative’ cannabis products. Research in
Washington state found that while cannabis flower products make up most sales in the legal
retail market, sales of cannabis concentrates for inhalation (i.e., resin, vaporizer cartridges, and
solid concentrates) and cannabis-infused edibles have increased since 2014 (Smart et al., 2017).
The increasing supply of cannabis concentrates in the retail market may be a result of more
advanced methods of extraction, decreased enforcement in states with legalized cannabis and
market segmentation strategies (Olsen & Smith, 2020; Subritzky, Pettigrew & Lenton, 2016).
Among a national sample of cannabis users, those who preferred vaping reported that doing so
was healthier, more satisfying and a more positive experience compared to smoking (Lee et al.,
2016). Additionally, we observed Instagram posts featuring cannabis related health claims,
which have also been observed on other social media sites like Twitter (Allem. Escobedo,
Dharmapuri, 2020), Facebook, Reddit (Shi et al., 2019), and Weedmaps (Bierut et al., 2017).
While the number of posts featuring health claims was modest, this is still an important finding
56
as states like California prohibit advertisements with unsubstantiated claims about the health
effects of cannabis products. Many health claims observed in the current study were
unsubstantiated. These claims may have offline consequences if unsubstantiated claims influence
perceptions about cannabis product safety or if cannabis products are used in place of other
evidence-based treatments. Counter messages can assert that many health claims about cannabis
products are unsubstantiated, and public education campaigns could attempt to identify
misinformation and circulate evidence-based information across popular social media sites.
Like previous research on cannabis-related posts to Instagram (Cavazos-Rehg et al., 2016;
Jenkins et al., 2021), cannabis product use, product normalization, and promotions were
commonly observed. Many cannabis companies are using the platform to normalize and
destigmatize cannabis as an innocuous, uncontroversial, and legal commodity by showing
cannabis product use in everyday situations (at the beach, on a hike, in bed), as well as showing
products and packages being placed besides cell phones, makeup, handbags, and sunglasses, to
establish that cannabis products are comparable to other everyday possessions (Asquith, 2021).
Social media posts are often designed by cannabis brands to encourage user engagement
(Asquith, 2021). For example, several promotional posts observed in the current study
encouraged users to comment, to mention a retailers Instagram account name or hashtag in their
own personal posts, or to mention the Instagram post at the point of sale to receive a discount or
giveaway. The use of promotions (discounts, sales, contests, and giveaways) by cannabis
retailers on Instagram is problematic as previous research found that tobacco coupons and
discounts encouraged and sustained smoking behaviors, particularly among lower-income
populations (Choi et al., 2019). In addition, a literature review by DiFranza et al. (2006) found
evidence of a causal relationship between exposure to tobacco promotions and initiation of
57
tobacco use among youth. Furthermore, DiFranza et al. (2006) found a dose-response
relationship such that greater exposure was associated with greater risk of initiation and that risk
increased across diverse populations and with exposure to different types of promotions. These
findings are concerning as recent research indicates that exposure to cannabis marketing on
social media is associated with cannabis use and youth who engage with cannabis businesses
online (by following or liking retailer accounts and posts) are five times more likely to have use
cannabis in the past year (Whitehill et al., 2020, Trangenstein et al., 2019).
Other themes observed that may appeal to potential customers included flavors, user
experience, sex appeal, and social situations. These themes have also been observed on tobacco
and e-cigarette online marketing brand websites (Escobedo et al., 2018, Escobedo et al., 2020;
Majmundar et al., 2020). For decades, the tobacco industry has employed a variety of marketing
strategies with themes that focus on social prominence, and sexual attraction, strategies which
previous research found was associated with an increase in smoking behaviors among youth and
young adults (Pierce & Gilpin, 1995; Biener & Siegel, 2000; Rigotti, Moran & Wechsler, 2005;
NCI, 2008; Rath et al., 2020). The association between flavors and tobacco use are well
documented in the literature, and a recent study on adolescent cannabis and tobacco users found
that nearly half (48.1%) used a flavored combustible cannabis product (Werts et al., 2021). In
comparison, 58% used a flavored aerosolized cannabis product (Werts et al., 2021). This study
also found that the most popular flavors among adolescents using combustible and vaped
cannabis were fruit and other sweet flavors (candy, dessert) (Werts et al., 2021). These findings
indicate a potential public health concern, as previous research found that adolescents associated
flavored tobacco products as being less harmful and reported being more interested in trying
flavored tobacco products than unflavored tobacco products (Chaffee et al., 2020; Kowitt et al.,
58
2017). Though more research is needed, adolescents may also be more likely to experiment with
flavored cannabis products and potentially view them as less harmful, especially if they perceive
cannabis as a “natural” product. Given that the current study found that 15% of posts by cannabis
retailers featured flavored products, potential restrictions on flavored cannabis products may help
limit youth appeal.
Understanding the prevalence of health-related claims about cannabis consumption made
by retailers is important given that California cannabis regulation states that cannabis retailers
are prohibited from publishing advertising containing any health-related statement that is untrue
or misleading (California Legislative Information, 2016a). There is evidence suggesting that
pharmaceuticals containing cannabinoids like CBD and THC may be effective in treating
epilepsy, nausea, and vomiting associated with chemotherapy and appetite loss and weight loss
associated with HIV/AIDS, and some evidence that cannabis and cannabinoids can help with
chronic pain and multiple sclerosis symptoms, however more research on other health conditions
(e.g., anxiety, PTSD, sleep problems) is needed to understand how cannabis impacts symptoms
(NCCIH, 2019). Counter messages can assert that many health claims about cannabis products
are unsubstantiated. Public education campaigns could attempt to identify misinformation and
circulate evidence-based information across popular social media sites.
This is the first study to our knowledge to focus on Instagram posts of cannabis retailers in
California, where cannabis marketing is restricted to media channels where at least 71.6% of the
audience is assumed to be 21 years of age or older. Cannabis advertising and sales are also
prohibited on Instagram. However, in March 2020, we obtained over 23,000 Instagram posts
from over 111 active cannabis retailers accounts, demonstrating that cannabis advertising
restrictions by Instagram and the state of California are not being enforced. Advertising
59
restrictions are intended to prevent youth exposure to cannabis marketing. However, unregulated
social media sites provide cannabis retailers with a relatively inexpensive marketing medium that
can reach millions of potential users of all ages. Instagram users can like and repost cannabis
retailer content on their own personal accounts. Therefore cannabis marketing content can
unintentionally reach adolescent and young adult users or other users who have not actively
sought out cannabis-related content on the site. Local governments should consider filing
lawsuits against cannabis companies and retailers who engage in youth-targeted marketing. In
2021, the Los Angeles City Attorney secured a court ruling in a lawsuit against the California
based Kandypens e-cigarette company for marketing vaping devices and accessories to youth
through social media marketing on Instagram and YouTube and through product placement in
popular music videos with artists who have substantial youth followings, such as DJ Khaled and
Justin Bieber (Escobedo et al., 2021; Los Angeles City Attorney, 2021). The court order
prohibits Kandypens from engaging in youth-targeted marketing, requires compliance with
California tobacco laws and payment of $1.2 million for past violations. Having state or local
officials file lawsuits against individual cannabis companies and retailers located in California
who are in violation of California law may be an effective enforcement strategy and force
companies to comply with state laws that aim to reduce youth exposure to cannabis advertising.
This study aimed to examine the prevalence of a wide range of marketing themes,
however, future research should consider aggregating marketing themes that cluster together to
assess whether there are larger central themes in the dataset.
Limitations
The study was limited to Instagram accounts of cannabis retailers located in the City of
Los Angeles, and results may not generalize to cannabis retailers located in other regions of the
60
United States. Findings from this study may not generalize to other social media platforms, and
cannabis retailer marketing on other social media platforms should be explored in future
research. This study collected posts from August 3, 2013, to March 14, 2020, and findings may
not generalize to other time periods. While Instagram is a popular social media site among youth
and young adults, the present study did not determine the demographics of Instagram users
following cannabis retailer Instagram accounts. Instagram also does not provide a count of how
many people view a particular post; therefore, the reach of posts or number of impressions was
not reported. This study did not have access to Instagram data from private retailer accounts.
However, it is expected that most retailers would have a public account given that they are using
the platform a to reach as many new and existing customers as possible.
Conclusions
This study examined 2500 cannabis retailer posts to Instagram to describe marketing
themes used on social media sites. All 16 themes, including cannabis plants/flowers, flavors,
electronic cannabis products, cannabis concentrates, other cannabis products, product use, user
experience, health claims and promotions, were observed. These results indicate a growing
public health issue as cannabis retailers are using a variety of marketing strategies to reach
cannabis users and potential users on a social media platform utilized primarily by youth and
young adults. Public health professionals and policymakers must counter these pro-cannabis
messages with evidence-based information about the risks of cannabis use, especially high
potency products. In addition, U.S. states with legalized cannabis do not allow youth-targeted
cannabis marketing. Therefore local and state governments should consider using court orders to
target retailers and companies who are engaging in cannabis advertising on Instagram in
violation of state and local cannabis control laws. Future research should examine the impact of
61
viewing cannabis retailer marketing online to identify any possible offline consequences such as
cannabis related attitudes and beliefs, susceptibility to cannabis use, as well as cannabis us
behaviors or increase in use, especially among adolescents and young adults.
62
Figure 6
Demonstrates 17 images or text representative of cannabis retailer marketing themes
1) Cannabis plant/flowers
2) Electornic Cannabis Products
3) Cannabis Concentrates
4) Cannabis joints
5) Other Cannabis Products
6) Accessories
63
7) Product Use
8) Flavors
9) Health Claims
10) Product Normalization
11) Sex Appeal
12) Social
64
13) Product Safety
14) User Experience
15) Legal age to purchase
16) Promotions
17) Other
Note: For ethical and copyright reasons the Instagram posts analyzed in this study were not used in this
figure. Stock images were selected that accureately represented the respecitve themes.
65
Study 3
The associations between recall of music videos with e-cigarette promotion,
engagement with music videos with e-cigarette promotion, and e-cigarette use among
young adults in California
Introduction
Among young adults 18 to 24 years of age, use of electronic cigarettes (e-cigarettes, vape
pen devices) every day or some days increased from 5.1% in 2014 to 7.6% in 2018, while use
among adults 25 years of age or older has declined or plateaued (Dai & Leventhal, 2018). E-
cigarette use or vaping is associated with an increased risk of progression to combustible
cigarettes among young adults (Soneji et al., 2017) and acute lung injury (CDC, 2020a). E-
cigarette devices have evolved to facilitate the use of multiple substances (i.e., with nicotine and
cannabis e-liquid solutions (Majmundar et al., 2020) which may increase their abuse liability or
appeal to young adults.
In addition to unique product features that may appeal to young adults, for decades, the
tobacco industry has employed promotional practices that target adolescents, and young adults,
including, product placement (e.g., scenes with visible branding, a visible logo, branded
merchandise, or gear such as a branded hat or shirt) in television and film, and advertising in
print media with themes that focus on social prominence, success and sexual attraction; these
promotional strategies were found to be associated with an increase in smoking behaviors among
youth and young adults (Pierce & Gilpin, 1995; Biener & Siegel, 2000; Dalton et al., 2003;
Rigotti, Moran & Wechsler, 2005; NCI, 2008; Rath et al., 2020). Previous research found that
exposure to smoking and tobacco product placement in movies was associated with increased
awareness of products, the increased appeal of products, increased perceptions of product
66
benefits, as well as product initiation and regular use of tobacco products among youth (Dal Cin
et al., 2007; Heatherton & Sargent, 2009; Sargent et al., 2005; Sargent, Tanski & Gibson, 2007;
Song et al., 2007; Collins et al., 2019).
Actions have been taken to curb promotional practices that target young people. For
example, the multi-state Master Settlement Agreement (MSA) of 1998 restricted paid tobacco
product placement in television, music videos, and motion pictures (Truth Initiative, n.d.).
However, the MSA only applies to the cigarette and smokeless tobacco companies that signed
the agreement and does not apply to new tobacco companies or to emerging tobacco products
like e-cigarettes and vape pens. Given the lack of e-cigarette-related marketing restrictions, e-
cigarette companies have partnered with producers of music videos and musical artists popular
among young adults to promote their products. For example, KandyPens, which produces open
system pod mod vape pens, vaporizers, dab rings, vape accessories, and branded merchandise,
lists on their brand website (kandypens.com) links to 81 music videos featuring product
placement and product use.
The music video titled “I’m the One” by DJ Khaled included four scenes of e-cigarette
product placement and imagery, which totaled 8.5 seconds of screen time for KandyPens (Allem
et al., 2017a). Today, this video has been viewed over 1.5 billion times on YouTube (Allem et
al., 2017a). Given this number of views, “I’m the One” had the potential to deliver 6 billion
impressions (1.5 billion views x 4 scenes) of e-cigarette product placement and use. In a separate
example, the music video “No Brainer” by DJ Khaled contained scenes of female models using
KandyPens products, exhaling aerosol clouds, as well as scenes with KandyPens product
packaging (Escobedo et al., 2020a). Artist DJ Kahled was also shown using a KandyPens device
and exhaling an aerosol cloud toward the camera.
67
Until recently, product placement in music videos was unrestricted. However, given the
growing concern about youth e-cigarette use, local governments have begun filing lawsuits
against companies like KandyPens. For example, in 2021, the city attorney of Los Angeles
secured a court ruling against KandyPens for marketing vaping devices and accessories to youth
through product placement in music videos and social media posts (Escobedo et al., 2021; Los
Angeles City Attorney, 2021). The court order prohibits KandyPens from using any youth-
targeting marketing strategies, requires the company to comply with California tobacco laws, and
requires payment for past violations. While this court ruling is a start, more comprehensive
policies are needed to curb e-cigarette promotional practices aimed at young adults.
Reducing youth and young adults’ exposure to product placement in music videos is
particularly important. Evidence suggests that young adults exposed to any e-cigarette product
placement or imagery in popular music videos were more likely to report lifetime and past-
month e-cigarette use. It was also found that the degree of music exposure matters as participants
with greater levels of exposure was more likely to report lifetime and past-month e-cigarette use
compared to those with no exposure (Majmundar et al., 2021). Similar findings have been found
among adolescent populations (Cranwell et al., 2015). While these studies measured the level of
exposure to music videos with e-cigarette product placement and imagery, no study to our
knowledge has examined the degree of recall of music videos featuring e-cigarette product
placement or imagery without providing a list of music videos. In other words, the degree of
impact or impression of this marketing strategy has only been measured by asking participants to
accurately recall a music video in general. To build the case that this type of marketing strategy
is memorable for the viewer and worthy of further policy, research examining whether
participants can recall viewership of product placement without a list of song titles is warranted.
68
The current study will address these gaps in the literature by examining the association
between recall of e-cigarette product promotion and imagery and e-cigarette use and the
association between engagement such music videos and e-cigarette use. By describing the
associations between music video recall, engagement and e-cigarette use, findings from this
study can inform future policies on marketing restrictions in music videos and other popular
media.
Hypothesis 1: Recall of music videos featuring e-cigarette promotion or imagery will be
positively associated with e-cigarette product use among young adults.
Hypothesis 2: Self-reported engagement with music videos featuring e-cigarette products
placement or imagery will be positively associated with e-cigarette product use among young
adults.
Methods
Participants and procedures
Young adults (18 to 24 years of age) living in California completed a survey between
August 19, 2019, to October 17, 2019 (administered by YouGov PLC). Respondents (n=1500)
were recruited using a stratified sampling procedure. The sampling frame was constructed from
the 2016 American Community Survey (ACS) 1-year sample with selection within strata by
weighted sampling with replacements. Respondents were then matched to the sampling frame on
gender, age, race, and education, which resulted in a sample of 1500 participants. Propensity
scores were used to weigh the matched cases to the sampling frame. The study was approved by
the University of Southern California Institutional Review Board. All participants provided
written informed consent.
Explanatory variables
69
Recall of e-cigarette promotion. To measure the level of awareness of e-cigarette
promotion or imagery in music videos, participants were asked, “Do you remember watching
music videos that promote e-cigarettes?” For the purposes of this survey, ‘promote’ was defined
as publicizing a product to make people aware of the characteristics of a product, including the
brand and logo, creating interest in a product and persuading others to buy it” with response
options “Yes” or “No.” Participants who responded “Yes” to this question were asked to list the
name of the video and/or artist.
Recall of e-cigarette imagery. Participants who did not recall watching a music video
promoting e-cigarettes were then asked, “Do you remember watching music videos that showed
e-cigarette products, brands, logos, or devices?” with response options “Yes,” “No.” Participants
who responded “Yes” to this question were then asked to list the name of the video and/or artist.
Recall of e-cigarette promotion or imagery was operationalized using a dichotomous variable (1
= recalled at least one music video, 0 = no recall).
Music video engagement. To assess the relationship between music video engagement
and e-cigarette product use, if participants responded Yes to the recall of e-cigarette promotion
or recall or e-cigarette imagery measures above, they were then asked if in the past six months,
they had done any of the following for at least one of the music videos: 1) liked, 2) followed, 3)
commented on, 4) shared, 5) watched, or 6) re-watched music video or 7) none of the above.
Participants were asked to check all that applied. Music video engagement was operationalized
using a dichotomous variable (“1” = any engagement, “0” = no engagement ).
Outcome measures
E-cigarette product use. To examine e-cigarette use, all participants were asked about
lifetime, past six month and past-month e-cigarette use. Participants were asked, “Have you ever
70
used any of the following electronic nicotine devices?” and provided a list of electronic products:
disposal device, vape pen or pen-like, rechargeable device (such as eGO or small startup kit),
Mod or mech-mod rechargeable device, Box Mod, JUUL, other pod mod or another type of
electronic nicotine device. Response options for each product were “Yes,” “No,” and “I don’t
know.” Participants who responded Yes to any lifetime product use were asked, “During the past
six months, have you used any of the following electronic nicotine devices?” and provided the
same list of electronic products. Participants who responded Yes to any six-month product use
were then asked, “During the past 30 days, have you used any of the following electronic
nicotine devices?” and provided the same list of electronic products. Response options for each
product were “Yes,” “No,” and “I don’t know.”
Lifetime use of e-cigarette products was operationalized using a dichotomous variable
(“1” = ever use of at least one e-cigarette product, “0” = zero e-cigarette use). Past-month use of
e-cigarette products was operationalized using a dichotomous variable (1= use of any e-cigarette
product during the past 30 days, 0 = no e-cigarette use during the past 30 days, or no lifetime use
of e-cigarettes). Responses for any outcome measures indicating “I don’t know” were coded as
missing (Majmundar et al., 2021).
Covariates
Demographic covariates include age, gender (female, male, and other), race-ethnicity
(Asian, African American, Hispanic/Latino, Non-Hispanic White, and other), education (some
college or more, high school graduate or no high school), employment (employed full-time or
part-time, student or other) and household income based on California’s median household
income (less than or equal to $70,000 per year, more than $70,000 per year and income not
disclosed).
71
Participants were also asked, “Have you ever used any of the following tobacco products,
even one or two puffs?” and were provided a list of tobacco products (cigarettes, cigars,
cigarillos or little cigars, hookahs, chewing tobacco, snuff or dip, pipe tobacco or other
products). Response options for each product were “Yes,” “No,” and “I don’t know.” Lifetime
use of tobacco products was operationalized using a dichotomous variable (“1” = any use of at
least one tobacco product, “0” = zero tobacco use). Responses indicating “I don’t know” were
coded as missing. Lifetime use of tobacco products was adapted from the Population Assessment
of Tobacco Health (PATH) (NIH, n.d.).
Analytic approach
Of the 1,500 participants, those who did not pass a data quality check (i.e., those who
reported watching three or more fake music videos consisting of fictional artists and song titles)
were removed from the sample (n = 160). Separate logistic regression models assessed the
relationship between 1) recall of e-cigarette promotion or imagery in music videos and lifetime
and past-month e-cigarette use and 2) music video engagement and lifetime and past-month e-
cigarette use. All analyses were weighted and included all covariates. We reported weighted
demographic estimates, the odds ratios, 95% confidence intervals, and p-values associated with
each outcome variable. A level of significance of α ≤ 0.05 was used in all statistical analyses.
Analyses were conducted in Stata 15.
Results
Sample Demographics
Weighted demographic estimates are described here (see Table 4 for weighted and
unweighted sample estimates). Among the sample, the average age of participants was 21.08
years, and the sample had a higher proportion of respondents between 21 and 24 years of age
72
(57.14%) compared to respondents 18 to 20 years of age (42.86%). Among participants, 47.05%
were female, 41.4% were male, and 3.5% reported other gender identities or preferred not to say.
Most participants (64.70%) reported having some college education, while 35.30% had a high
school degree or less. More participants were Hispanic or Latino (44.54%), 32.21% were non-
Hispanic White, 11.19% were Asian, 5.21% were Black or African American, and 6.75% were
of other ethnicities. Most participants were currently employed (42.33%), while 36.30% were
students, and 21.37% were categorized as being unemployed or other. Most participants had a
family income less than or equal to $70,000 (62.69%), 24.11% had a family income higher than
$70,000, and 13.20% preferred not to disclose income. Nearly half of participants (49.63%)
reported ever use of tobacco products.
For the variable recall of e-cigarette promotion or imagery, 408 (30.4%) of participants
reported recalling a video, 932 (69.5%) did not recall a video with e-cigarette promotion, and
there was no missing data. Among the 408 participants who did recall a music video, 291
(71.3%) engaged with music videos and, 117 (28.6%) did not engage.
For lifetime e-cigarette use (N = 1340), 752 (54.2%) participants reported lifetime use, 582
(43.4%) participants reported no lifetime use and 31 (2.3%) had missing data. Among those with
valid lifetime e-cigarette data (N = 1309), 20 participants were missing data for lifetime tobacco
use. For past month e-cigarette use (N = 1340), 380 (28.3%) participants reported past-month e-
cigarette use, 952 (71%) reported no past-month e-cigarette use and 8 (0.6%) participants had
missing data. Among those with valid past-month e-cigarette data (N = 1332), 25 participants
were missing data for lifetime tobacco use.
Recall of e-cigarette promotion or imagery and music video engagement
73
Of the participants who recalled e-cigarette promotion or imagery, 167 (40%) listed an
artist and/or song title. Adjusted logistic regression models revealed that participants who
reported recall of e-cigarette promotion or imagery were more likely to report lifetime use of e-
cigarettes (odds ratio [OR]: 1.53; 95% CI, 1.03 to 2.28). However, recall was not significantly
associated with past-month e-cigarette use (Table 5). Among participants who recalled e-
cigarette promotion or imagery (n = 480), participants who engaged with music videos were
more likely to report past-month use of e-cigarettes (OR: 2.06; 95% CI, 1.03 to 4.13), however
engaging with music videos was not significantly associated with lifetime use of e-cigarettes.
74
Table 4
Sample Characteristics
Characteristic (n =1340) Raw, N (%) Weighted, N
(%)
Age
18- 20 years 563 (42.01) 574.25 (42.86)
21 years and over 777(57.99) 765.74 (57.14)
Gender
Female 738 (55.07) 630.41 (47.05)
Male 555 (41.42) 666.39 (49.73)
Other 47 (3.51) 43.17 (3.22)
Education
Some college educated or more 867 (64.70) 786.88 (58.72)
High school graduate or less 473 (35.30) 553.11 (41.28)
Race/Ethnicity
Asian 170 (12.69) 149.90 (11.19)
African American 92 (6.87) 69.83 (5.21)
Hispanic or Latino 484 (36.12) 596.81 (44.54)
White (non-Hispanic) 480 (35.82) 432.98 (32.31)
Other 114 (8.51) 90.46 (6.75)
Employment
Employed 577 (43.06) 567.20 (42.33)
Student 486 (36.27) 486.42 (36.30)
Other 277 (20.67) 286.37 (21.37)
Family income
Less than or equal to $70k 815 (60.82) 840.04 (62.69)
Greater than $70k 336 (25.07) 323.09 (24.11)
Not disclosed 189 (14.10) 176.85 (13.20)
Tobacco product ever use
Yes 669 (49.93) 664.98 (49.63)
No 645 (48.13) 652.62 (48.70)
I don’t know/missing 26 (1.94) 22.39 (1.67)
Recalled e-cigarette promotion or imagery in music video
Yes 408 (30.45) 412.98 (30.82)
No 932 (69.55) 927.01 (69.18)
Participants who recalled music
videos with e-cigarettes (n = 408)
Raw, N (%) Weighted, N
(%)
Engagement with music video
Yes 291 (71.32) 292.56 (71.71)
No 117 (28.68) 115.43 (28.29)
75
Table 5
Adjusted and Weighted Regression Analyses of Recall and Engagement with Music Videos Featuring E-
cigarettes
Recall of e-cigarette promotion and imagery
OR [95% CI] p
Lifetime use (n = 1298) 1.53 [1.03, 2.28] 0.03*
Past-month use (n = 1307) 1.20 [.855, 1.69] 0.28
Engagement among those who recalled videos
featuring e-cigarettes
OR [95% CI] p
Lifetime use (n = 394) .874 [.381, 2.00] 0.75
Past-month use (n = 397) 2.06 [1.03, 4.13] 0.04*
Note: *p<0.05, differences in sample sizes between lifetime use and past-month use is due to missing
tobacco product ever use data. Participants with missing data were dropped from the analysis.
Discussion
To our knowledge, this is the first study to examine whether unprimed recall of e-cigarette
promotion or imagery in music videos and engagement with music videos featuring e-cigarette
promotion or imagery was associated with e-cigarette product use. We measured active recall of
e-cigarette marketing exposure and engagement with music video content rather than passive
exposure alone, which allows for a more nuanced appreciation for how impactful and memorable
this promotional strategy is among young adults.
Like previous research (Majmundar et at., 2021), our findings suggest that viewing any
music video promoting or featuring e-cigarettes was associated with e-cigarette use.
Furthermore, any engagement with music videos promoting or featuring e-cigarettes was
associated with past-month e-cigarette use among young adults in California. Findings from this
study indicate that recall of and engagement with music videos featuring e-cigarettes is linked to
an increased likelihood of current e-cigarette use among a high-risk population.
76
By describing the association between recall of e-cigarettes in music videos, music video
engagement, and e-cigarette use, this study addresses a critical gap in the literature. Previous
research examining e-cigarette products in music videos measured the prevalence of e-cigarette
products, the number of music video views, and whether adolescents in the United Kingdom had
watched music videos featuring e-cigarettes (Knutzen et al., 2018; Cranwell et al., 2015). These
studies did not include a sample of participants from the United States, did not sample young
adults, did not ask participants to actively recognize or recall e-cigarette marketing in music
videos or how they engaged with music videos featuring e-cigarettes. Young adults in the United
States represent a priority population as they are at the highest risk for substance use and use of
e-cigarettes among young adults has increased during the past decade (Soneji et al., 2017).
Previous research examined how engagement with pro-tobacco marketing and media can impact
tobacco use (Wellmen et al., 2006). However, little was known about how engagement with e-
cigarette marketing impacted e-cigarette use until now. The current study indicates that
interacting with music videos featuring e-cigarettes may lead to greater e-cigarette use, which is
a critical finding as music videos are often watched online using social media platforms like
YouTube, a website most popular among adults 18-29 years of age (Auxier & Anderson, 2021).
Since 2010, all but one of the most viewed videos on YouTube have been official music
videos, indicating that the platform is an important source of music video content for young
adults (Statista, 2021). YouTube allows users to not only watch music videos on demand but
allows users to rate videos, as well as share, save, follow, and comment on videos. YouTube also
provides a video description, which has been used by some musical artists to promote e-cigarette
product placement in music videos. For example, as of August 2021, the description of the music
video “Krippy Kush (Remix)” by Farruko, Nicki Minaj, and Travis Scott begins with a statement
77
informing the viewers that “the vaporizer used in this Krippy video provided by Mig Vapor vape
pen, see it here” followed by a link taking users to an external Mig Vapor website (YouTube,
2017). These types of marketing strategies are concerning as most music videos and music video
descriptions on YouTube do not feature any type of age verification or health warnings.
Research on implicit cognition suggests that seeing a particular cue (e.g., watching
someone use an e-cigarette or cigarette imagery) can trigger a pattern of activation in memory,
such that behavioral concepts like e-cigarette or tobacco use become strongly activated and
accessible (Stacy et al., 1996). Increased activation and increased accessibility of these
behavioral concepts may influence substance-related thoughts, desires, and urges (Stacy et al.,
1996). Additionally, thinking about a certain outcome, such as partying and socializing with
friends, may likely stimulate a certain pattern of activation in memory and cause the individual to
recall certain concepts (e.g., consuming alcohol, smoking, or vaping) that they associate with the
outcome. Socialization and party lifestyle are marketing themes commonly observed on e-
cigarette and tobacco brand websites (Escobedo et al., 2018), and image/lifestyle/sociability
(e.g., wealth, ostentatious lifestyle, partying with friends) was the most common music video
theme among popular music videos in 2018 (Escobedo et al., 2021). E-cigarette product
placement or imagery in music videos featuring parties and grandiose lifestyles may lead viewers
to associate the brand or product use with certain outcomes (e.g., partying, socializing) and
perceptions (e.g., e-cigarette use as a status symbol, appealing or sexy). Given that music videos
featuring e-cigarettes are commonly viewed on interactive social media sites, it is critical that
tobacco control agencies increase usage of interactive and engaging content that counters e-
cigarette marketing messaging employed in music videos.
78
Research on engagement with e-cigarette marketing by Hebert et al. (2017) found that
adolescents who were susceptible to and reported lifetime or current use of tobacco and e-
cigarettes were more likely to engage with tobacco and e-cigarette related content on social
media sites like Facebook, Instagram, and YouTube (Hebert et al., 2017). Interacting with
website features allows users to become cognitively absorbed in the site, and interaction itself
can lead to more positive perceptions of website messaging, even without active processing of
the message itself (Oh & Sundar, 2015). Among young adult smokers, observing someone use an
e-cigarette product served as a smoking cue and increased the desire for e-cigarettes and
combustible cigarettes (Vena et al., 2020). Also, on-screen tobacco use by popular celebrities
was associated with positive perceptions about smoking, intention to smoke, and actual cigarette
use (Tickle et al., 2001; Dal Cin et al., 2007). Previous research on recall of tobacco advertising
on the internet found that recall was highest among young adults and current smokers reported
high levels of recall (Hrywna et al., 2007). Additionally, a meta-analysis by Wellman et al.
(2006) found that highly engaging tobacco marketing and media, compared to less engaging
marketing and media, was more effective at promoting tobacco use.
Findings from the current study can also inform restrictions on e-cigarette imagery and
marketing on popular social media sites (e.g., Facebook, YouTube). Sites like Facebook and
Instagram announced in 2019 that they would no longer allow users known as “influencers” to
promote vaping or tobacco products through paid partnerships with tobacco and e-cigarette
companies (Graham, 2019). Facebook banned advertisements promoting vaping and tobacco
products. However, tobacco and vape companies were able to promote products through paid
product placements on user accounts. While social media companies have policies in place to
restrict content, it is unclear to what extent policies are being enforced. Findings from the current
79
study could encourage websites like YouTube to ban music videos that feature e-cigarette
product placement. Currently, videos on YouTube with tobacco or vaping content are allowed on
the site but are not “suitable for advertising” (Tobacco Business, 2019). YouTube could also use
study findings to categorize music videos featuring e-cigarette product placement and imagery as
age-restricted content (YouTube, n.d.), which would require that users sign in and verify that
they are 18 years of age. Vape pen companies like KandyPens have official YouTube accounts
that feature promotional videos which require users to acknowledge that the video they are about
to watch “…may be inappropriate for some users”. YouTube or individual record companies
may also consider placing FDA tobacco product warning statements featuring Surgeon General’s
Warnings (e.g., smoking causes lung cancer, heart disease, emphysema and may complicate
pregnancy) in music videos featuring tobacco and e-cigarette imagery and product placement
(FDA, 2018).
Furthermore, findings from the current study can inform federal, state, and local
regulations on e-cigarette marketing practices. Since 2016, the U.S Food and Drug
Administration (FDA) was granted regulatory authority over e-cigarette products, which
included regulatory authority over the advertising, promotion, and sale of e-cigarette products
(FDA, 2020). Study findings can provide support for more stringent marketing restrictions and
federal enforcement of e-cigarette imagery and product use in music videos, television, movies,
and other media platforms popular among adolescents and young adults. The 1998 MSA
prohibits tobacco product placement in movies, television, and music videos, but it does not
apply to e-cigarette products (Truth Initiative, n.d.). Given the absence of federal marketing
restrictions on e-cigarettes, enforcement at the state or city level may be an effective strategy
against youth-targeted marketing. Like the lawsuit filed against KandyPens by the Los Angeles
80
city attorney, findings from this study should motivate more local district attorneys or state
attorney general’s offices to investigate and restrict the promotional practices of e-cigarettes
companies. Having state or city officials file lawsuits against individual e-cigarette companies in
violation of local tobacco marketing laws may deter other e-cigarette companies from engaging
in youth-targeting marketing and product placement.
Given the overall lack of e-cigarette marketing restrictions and enforcement, the
appearance of e-cigarettes and vape products in popular media like music videos is on the rise
(Knutzen, Moran & Soneji, 2018). This is concerning as e-cigarette marketing exposure was
associated with e-cigarette use among youth, and among youth who had never used e-cigarettes,
exposure to e-cigarette marketing through the internet, print media, retail, and television/movies
was significantly associated with susceptibility to e-cigarette use (Mantey et al., 2016). Passive
exposure to e-cigarette use has been found to generalize as a smoking cue among smokers (Vena
et al., 2020). Watching another person use an e-cigarette product increased an observer’s urge to
smoke and desire for cigarettes and e-cigarette products (Vena et al., 2020). Exposure to e-
cigarette marketing can impact vaping, and music videos have been reported to be a potential
source of exposure to e-cigarette products among young adults (Cranwell et al., 2015; Allem et
al., 2017a; Knutzen et al., 2018).
Engagement with music video content online is also popular among adolescents
(Lindsay, 2017). On social media sites like YouTube, users can watch, like, follow, comment on,
and share music video content with other users on the internet (Khan, 2017). According to the
Pew Research Center, in 2018, use of YouTube was higher among adults ages 18-29 compared
to adults 30 years of age and older (Perrin & Anderson, 2019). YouTube receives 30 million
unique visitors per month between the ages of 18 to 24 (Blattberg, 2015), and since 2010, several
81
of the most viewed videos on YouTube have been official music videos (Tankovska, 2021).
Furthermore, individuals can modify and manipulate music video content available online to
create screenshots, memes, or GIFs that can be shared online, which may lead to more people
watching the original music video content (Lindsay, 2017).
Future longitudinal research is needed to examine the temporal relationship between
engagement with media content and e-cigarette use behaviors. However, there is evidence that
the presence of e-cigarettes in popular music videos may serve as a vaping or smoking cue.
Future research should also continue to explore all potential sources of e-cigarette and vaping
exposure among youth and adults. Recent research found that programs on streaming services
like Netflix featured more smoking imagery than shows on broadcast/cable television (Truth
Initiative, 2019a), and tobacco content was observed among 42% of video games participants
reported playing (Truth Initiative, 2016; Truth Initiative, 2019a). Music videos, and other
popular media, should also be considered when assessing e-cigarette and tobacco marketing
exposure among priority populations. This study could not determine a causal relationship
between exposure to product placement or imagery in music videos and e-cigarette product use.
However, this is an area of future research. Future research should validate the open-ended
responses provided by participants who report recall of music videos with e-cigarette promotion
or imagery to determine recall accuracy.
Limitations
Limitations of this study include reliance on self-reported data to determine recall,
engagement with music videos, and substance use. All study measures relied on self-report and
may be subject to recall bias. The music video engagement measures used in the present study
may not be an exhaustive measure of engagement. This study was limited to young adults in
82
California and may not generalize to young adult populations outside of California. The survey
data was collected from a 4-week period (August 19, 2019, to October 17, 2019) and may not
extend to data collected from other points in time.
Conclusions
This study examined the association between self-reported engagement with music
videos featuring e-cigarettes and e-cigarette product use. Findings indicate that e-cigarette
promotion or imagery recall was associated with lifetime e-cigarette use, and any engagement
with music videos promoting or featuring e-cigarettes was associated with past-month e-cigarette
use among young adults in California. These results indicate a significant public health issue as
social media platforms that allow users to interact with music video content (e.g., YouTube) are
most popular among youth and young adults. In addition, given the lack of restrictions on e-
cigarette marketing practices, findings from this study should be used to inform future policies
restricting e-cigarette product placement in music videos and other media platforms popular
among youth and young adults.
Overall Conclusions
The aims of the three papers are to understand who is exposed to e-cigarette and cannabis
retailers in the built environment and how exposure to e-cigarettes and cannabis products in the
online retailer environment can impact beliefs and attitudes toward e-cigarette and cannabis use,
which in turn, may influence use behaviors among vulnerable and priority populations. Study 1
built on the limited body of research examining the spatial distribution and clustering of vape
and cannabis retailers. This study described the current methodological problems commonly
found among research examining retailer density and demonstrated a different approach using
spatial analytic techniques to examine and measure demographic characteristics of retailer
83
clusters. Findings indicate that in Los Angeles, racial/ethnicity and nativity characteristics of
neighborhoods in retailer clusters vary by retailer type and that vape and unlicensed retailer
clusters are more likely to be in lower income neighborhoods with populations at higher risks of
tobacco use, tobacco-related diseases, and other adverse health outcomes. Our study revealed
several notable findings that confirm and add to the limited research examining vape and
cannabis retailer concentration and sociodemographic disparities. Findings can help target
tobacco and cannabis control enforcement efforts, help target health campaigns about e-cigarette
and cannabis use, and inform future policies on undue concentration and zoning laws that can
limit tobacco and cannabis retailer density.
Study 2 examined 2500 cannabis retailer posts to Instagram by retailers located in Los
Angeles to describe marketing themes used on social media sites. All 16 themes, including
cannabis plants/flowers, flavors, electronic cannabis products, cannabis concentrates, other
cannabis products, product use, user experience, health claims, and promotions were observed.
Cannabis retailers are using a variety of marketing strategies to reach cannabis users and
potential users on a social media platform utilized primarily by youth and young adults. It is
critical for public health professionals and policymakers to counter these pro-cannabis messages
with evidence-based information about the risks of cannabis use, especially high potency
products. Study 1 describes the built retailer environment in Los Angeles, while Study 2 builds
on this research by examining the social media marketing strategies of cannabis retailers in Los
Angeles identified in Study 1. Findings from Study 1 and 2 demonstrate how exposure to vape
and cannabis retailer storefronts and retailer marketing can be influenced by demographic
factors, such as race/ethnicity, income level, place of birth, and age.
84
Study 3 extended the research on e-cigarette product placement in popular media by
measuring unprimed recall of e-cigarette marketing exposure in music videos and engagement
with music videos featuring e-cigarette marketing, rather than passive exposure alone among
young adults in California. This approach allows for a more nuanced examination of how
impactful product placement can be on popular media platforms among young adult populations.
Findings indicate that recall of e-cigarette promotion or imagery was associated with lifetime e-
cigarette use and any engagement with music videos promoting or featuring e-cigarettes was
associated with past-month e-cigarette use. Given the lack of restrictions on e-cigarette
marketing practices, findings from this study should be used to inform future policies restricting
e-cigarette product placement in music videos and other media platforms popular among youth
and young adults. Like Study 2, Study 3 also examines the online environment and how
interaction with and recall of e-cigarette marketing content online can impact offline
consequences like e-cigarette use. Each study represents a different source of e-cigarette or
cannabis product marketing exposure. Though each source is distinct, these exposures in the
built and online environments may be cumulative and can influence social norms, personal
perceptions, and intentions to use. All three study findings indicate that demographic
characteristics may influence the intensity or degree of marketing exposure to retailer storefronts,
social media marketing, and consumption of popular music videos featuring e-cigarette
promotion and imagery. Retailer storefronts, social media marketing, and product placement in
popular media can serve as visual cues that trigger substance-related thoughts, desires, and urges,
which can influence substance use behaviors. Collectively, Study 1, Study 2, and Study 3 move
forward the literature on e-cigarette and cannabis marketing strategies, product availability, and
marketing exposure among priority and vulnerable populations.
85
2 References
Agaku, I. T., Egbe, C. O., & Ayo-Yusuf, O. A. (2021). Geospatial spread of e-cigarette vape
shops in South Africa and the relationship with tobacco product use among adults. Health
& Place, 68, 102507.
Aleyan, S., Cole, A., Qian, W., & Leatherdale, S. T. (2018). Risky business: a longitudinal study
examining cigarette smoking initiation among susceptible and non-susceptible e-cigarette
users in Canada. BMJ open, 8(5), e021080.
Allem, J. P., Chu, K. H., Cruz, T. B., & Unger, J. B. (2017c). Waterpipe promotion and use on
Instagram:# hookah. Nicotine & Tobacco Research, 19(10), 1248-1252.
Allem, J. P., Escobedo, P., & Dharmapuri, L. (2020). Cannabis surveillance with Twitter data:
emerging topics and social bots. American journal of public health, 110(3), 357-362.
Allem, J. P., Escobedo, P., Chu, K. H., Cruz, T. B., & Unger, J. B. (2017b). Images of little
cigars and cigarillos on Instagram identified by the hashtag# swisher: thematic
analysis. Journal of medical Internet research, 19(7), e255.
Allem, J. P., Escobedo, P., Cruz, T. B., & Unger, J. B. (2017a). Vape pen product placement in
popular music videos. Addictive behaviors, 93, 263-264.
Allem, J. P., Unger, J. B., Garcia, R., Baezconde-Garbanati, L., & Sussman, S. (2015). Tobacco
attitudes and behaviors of vape shop retailers in Los Angeles. American Journal of
Health Behavior, 39(6), 794-798.
Ali, F. R. M., Diaz, M. C., Vallone, D., Tynan, M. A., Cordova, J., Seaman, E. L., ... & King, B.
A. (2020). E-cigarette unit sales, by product and flavor type—United States, 2014–
2020. Morbidity and Mortality Weekly Report, 69(37), 1313.
86
Anderson, M., & Jiang, J. (2018). Teens, social media & technology 2018. Pew Research
Center, 31(2018), 1673-1689.
Asquith, K. (2021). The visual clichés of legal cannabis promotion on social media. Critical
Studies in Media Communication, 1-14.
Auxier, B., & Anderson, M. (2021, April 7). Social media use in 2021. Pew Research Center.
https://www.pewresearch.org/internet/2021/04/07/social-media-use-in-2021/
Ayers, J. W., Althouse, B. M., Allem, J. P., Leas, E. C., Dredze, M., & Williams, R. S. (2016).
Revisiting the rise of electronic nicotine delivery systems using search query
surveillance. American journal of preventive medicine, 50(6), e173-e181.
Ballard, J. (2019, October 25). Teens use these social media platforms the most. YouGov.
https://today.yougov.com/topics/lifestyle/articles-reports/2019/10/25/teens-social-media-
use-online-survey-poll-youth
Barrus D, Capogrossi K, Cates S, et al. Tasty THC: Promises and Challenges of Cannabis
Edibles. Research Triangle Park, NC: Methods Rep RTI Press; 2016
Bartlett, L. (2021, January 29). Cannabis Sales in California Reach $4.4 Billion in 2020:
‘Essential’, Edibles, And the Election. Forbes.
https://www.forbes.com/sites/lindseybartlett/2021/01/29/cannabis-sales-in-california-
reach-44-billion-in-2020-essential-edibles-and-the-election/?sh=21080f34313c
Berg, C. J., Barker, D. C., Meyers, C., Weber, A., Park, A. J., Patterson, A., ... & Henriksen, L.
(2021). Exploring the Point-of-Sale among Vape shops across the United States: audits
integrating a mystery shopper approach. Nicotine and Tobacco Research, 23(3), 495-504.
87
Berg, C. J., Getachew, B., Pulvers, K., Sussman, S., Wagener, T. L., Meyers, C., ... & Henriksen,
L. (2020a). Vape shop owners’/managers’ attitudes about CBD, THC, and marijuana
legal markets. Preventive Medicine Reports, 20, 101208.
Berg, C. J., Schleicher, N. C., Johnson, T. O., Barker, D. C., Getachew, B., Weber, A., ... &
Henriksen, L. (2020b). Vape shop identification, density and place characteristics in six
metropolitan areas across the US. Preventive medicine reports, 19, 101137.
Biener, L., & Siegel, M. (2000). Tobacco marketing and adolescent smoking: more support for a
causal inference. American journal of public health, 90(3), 407.
Bierut, T., Krauss, M. J., Sowles, S. J., & Cavazos-Rehg, P. A. (2017). Exploring marijuana
advertising on Weedmaps, a popular online directory. Prevention Science, 18(2), 183-
192.
Blattberg, E. (2015, April 24). The demographics of YouTube in 5 charts. Digiday.
https://digiday.com/media/demographics-youtube-5-charts/
Blood, M. R. (2020, August 7). California, cities battle over marijuana home-delivery rule.
Chicago Tribune. https://www.chicagotribune.com/marijuana/sns-california-marijuana-
delivery-rule-20200807-wvcbeinnbna75fa6i3p3istkci-story.html
Bostean, G., Sanchez, L., & Lippert, A. M. (2018). Sociodemographic disparities in e-cigarette
retail environment: Vape stores and census tract characteristics in Orange County,
CA. Health & place, 50, 65-72.
Bourque, A. (2019, May 6). Under the Influence of Instagram: Cannabis in the age of social
media. Forbes. https://www.forbes.com/sites/andrebourque/2019/05/06/under-the-
influence-of-instagram-cannabis-in-the-age-of-social-media/?sh=5e1348884746
88
Burbank, A. D., Thrul, J., & Ling, P. M. (2016). A pilot study of retail ‘Vape Shops’ in the San
Francisco bay area. Tobacco prevention & cessation, 2(Suppl).
California Bureau of Cannabis Control (BCC). (2019). Cannabis Retailer (Storefront) Fact
Sheet. BCC. https://bcc.ca.gov/about_us/documents/19-078_retail_storefront.pdf
California Bureau of Cannabis Control (BCC). (2020a). Instructions for completing the cannabis
retailer application. BCC. https://bcc.ca.gov/clear/retailer_instructions.pdf
California Bureau of Cannabis Control (BCC). (2020b). Cannabis Retailer License Application.
BCC. https://bcc.ca.gov/clear/retailer_application.pdf
California Cannabis Portal. (2021). Cannabis Legislation. https://cannabis.ca.gov/cannabis-
legislation/#:~:text=2016%20%E2%80%93%20California%20voters%20passed%20Prop
osition,medicinal%20purposes%2C%20with%20certain%20restrictions.
California Department of Housing and Community Development (HCD). (2020, April 30). 2020
State Income Limits Briefing Materials California Code of Regulations, Title 25, Section
6932. HCD. https://www.hcd.ca.gov/grants-funding/income-limits/state-and-federal-
income-limits/docs/income-limits-2020.pdf
California Department of Tax and Fee Administration (CDTFA). (n.d.). Cigarette and Tobacco
Product Licensing Registration and Renewal Information. CDTFA.
https://www.cdtfa.ca.gov/taxes-and-fees/cig-n-tob-prod-lic-reg.htm
California Legislative Information. (2016a). California Law: Code Section Group. Business and
Professions Code- BPC, Division 10, Chapter 15. Advertising and Marketing Restrictions
[26150 – 26156].
https://leginfo.legislature.ca.gov/faces/codes_displayText.xhtml?lawCode=BPC&divisio
n=10.&title=&part=&chapter=15.&article=
89
California Legislative Information. (2016b). California Law: Code Section Group. Business and
Professions Code- BPC, Division 10. Cannabis [26000 – 26260].
https://leginfo.legislature.ca.gov/faces/codes_displayText.xhtml?lawCode=BPC&divisio
n=10.&title=&part=&chapter=5.&article=
Campaign for Tobacco Free Kids. (2020, April 16). Tobacco and Socioeconomic Status.
Campaign for Tobacco Free Kids.
https://www.tobaccofreekids.org/assets/factsheets/0260.pdf
Cavazos-Rehg, P. A., Krauss, M. J., Sowles, S. J., & Bierut, L. J. (2016). Marijuana-related posts
on Instagram. Prevention Science, 17(6), 710-720.
Centers for Disease Control and Prevention (CDC). (2018). Is it possible to “overdose” or have
a “bad reaction” to marijuana? CDC. https://www.cdc.gov/marijuana/faqs/overdose-
bad-reaction.html
Centers for Disease Control and Prevention (CDC). (2020a). Outbreak of lung injury associated
with e-cigarette or vaping. CDC. https://www.cdc.gov/tobacco/basic_information/e-
cigarettes/severe-lung-disease.html
Centers for Disease Control and Prevention (CDC). (2020b). Electronic Cigarette Use Among
U.S. Adults, 2018. CDC. https://www.cdc.gov/nchs/products/databriefs/db365.htm
Centers for Disease Control and Prevention (CDC). (n.d.). CDC: E-cigarette, or vaping product
visual dictionary. CDC. https://www.cdc.gov/tobacco/basic_information/e-
cigarettes/pdfs/ecigarette-or-vaping-products-visual-dictionary-508.pdf
Chaffee, B. W., Couch, E. T., Urata, J., Cash, D., Werts, M., & Halpern-Felsher, B. (2020).
Electronic cigarette and moist snuff product characteristics independently associated with
youth tobacco product perceptions. Tobacco induced diseases, 18.
90
Chandra, S., Radwan, M. M., Majumdar, C. G., Church, J. C., Freeman, T. P., & ElSohly, M. A.
(2019). New trends in cannabis potency in USA and Europe during the last decade
(2008–2017). European archives of psychiatry and clinical neuroscience, 269(1), 5-15.
Chaloupka, F. J., Cummings, K. M., Morley, C., & Horan, J.. (2002). Tax, price and cigarette
smoking: evidence from the tobacco documents and implications for tobacco company
marketing strategies. Tobacco Control, 11(Supplement 1), i62–i72.
Chapman, R. (2015, January). State Health Officers Report on E-Cigarettes: A Community
Health Threat. California Department of Public Health, California Tobacco Control
Program. California Department of Public Health. http://tobaccofreeca.com/wp-
content/uploads/2016/07/State-Health-e-cig-report_digital.pdf
Choi, K., Chen, J. C., Tan, A. S., Soneji, S., & Moran, M. B. (2019). Receipt of tobacco direct
mail/email discount coupons and trajectories of cigarette smoking behaviours in a
nationally representative longitudinal cohort of US adults. Tobacco control, 28(3), 282-
288.
Collins, L., Glasser, A. M., Abudayyeh, H., Pearson, J. L., & Villanti, A. C. (2019). E-cigarette
marketing and communication: how e-cigarette companies market e-cigarettes and the
public engages with e-cigarette information. Nicotine and Tobacco Research, 21(1), 14-
24.
Cranwell, J., Murray, R., Lewis, S., Leonardi‐Bee, J., Dockrell, M., & Britton, J. (2015).
Adolescents’ exposure to tobacco and alcohol content in YouTube music
videos. Addiction, 110(4), 703-711.
91
Craven, C. B., Wawryk, N., Jiang, P., Liu, Z., & Li, X. F. (2019). Pesticides and trace elements
in cannabis: analytical and environmental challenges and opportunities. Journal of
Environmental Sciences, 85, 82-93.
Cullen, K. A., Ambrose, B. K., Gentzke, A. S., Apelberg, B. J., Jamal, A., & King, B. A. (2018).
Notes from the field: use of electronic cigarettes and any tobacco product among middle
and high school students—United States, 2011–2018. Morbidity and Mortality Weekly
Report, 67(45), 1276.
D’Amico, E. J., Rodriguez, A., Tucker, J. S., Pedersen, E. R., & Shih, R. A. (2018). Planting the
seed for marijuana use: changes in exposure to medical marijuana advertising and
subsequent adolescent marijuana use, cognitions, and consequences over seven
years. Drug and alcohol dependence, 188, 385-391.
Dahlgren, G., & Whitehead, M. (1991). Policies and strategies to promote social equity in
health. Background document to WHO-Strategy paper for Europe (No. 2007: 14).
Institute for Futures Studies.
Dai, H., Hao, J., & Catley, D. (2017). Vape shop density and socio-demographic disparities: a
US census tract analysis. Nicotine & Tobacco Research, 19(11), 1338-1344.
Dal Cin, S., Gibson, B., Zanna, M. P., Shumate, R., & Fong, G. T. (2007). Smoking in movies,
implicit associations of smoking with the self, and intentions to smoke. Psychological
Science, 18(7), 559-563.
Dalton, M. A., Sargent, J. D., Beach, M. L., Titus-Ernstoff, L., Gibson, J. J., Ahrens, M. B., ... &
Heatherton, T. F. (2003). Effect of viewing smoking in movies on adolescent smoking
initiation: a cohort study. The Lancet, 362(9380), 281-285.
92
DiFranza, J. R., Wellman, R. J., Sargent, J. D., Weitzman, M., Hipple, B. J., & Winickoff, J. P.
(2006). Tobacco promotion and the initiation of tobacco use: assessing the evidence for
causality. Pediatrics, 117(6), e1237-e1248.
ElSohly, M. A., Chandra, S., Radwan, M., Gon, C., & Church, J. C. (2021). A comprehensive
review of cannabis potency in the USA in the last decade. Biological Psychiatry:
Cognitive Neuroscience and Neuroimaging. doi: 10.1016/j.bpsc.2020.12.016.
Escobedo, P., Cruz, T. B., Tsai, K. Y., Allem, J. P., Soto, D. W., Kirkpatrick, M. G., ... & Unger,
J. B. (2018). Monitoring tobacco brand websites to understand marketing strategies
aimed at tobacco product users and potential users. Nicotine and Tobacco
Research, 20(11), 1393-1400.
Escobedo, P., Rosenthal, E. L., Saucier, C. J., Unger, J. B., Cruz, T. B., Kirkpatrick, M., &
Allem, J. P. (2021). Electronic Cigarette Product Placement and Imagery in Popular
Music Videos. Nicotine & Tobacco Research.
Escobedo, P., Tsai, K. Y., Majmundar, A., Allem, J. P., Soto, D. W., Pattarroyo, M., ... & Cruz,
T. B. (2020). Do tobacco industry websites target content to specific demographic
groups?. Drug and alcohol dependence, 208, 107852.
Esri (n.d.). ArcGIS Pro, Density toolset concepts, how kernel density works. Esri.
https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-analyst/how-kernel-
density-works.htm
Eysenbach, G. (2011). Infodemiology and infoveillance: tracking online health information and
cyberbehavior for public health. American journal of preventive medicine, 40(5), S154-
S158.
93
Galimov, A., Galstyan, E., Yu, S., Smiley, S. L., Meza, L., Baezconde-Garbanati, L., ... &
Sussman, S. (2020a). Predictors of vape shops going out of business in Southern
California. Tobacco Regulatory Science, 6(3), 187-195.
Galimov, A., Meza, L., Unger, J. B., Baezconde-Garbanati, L., Cruz, T. B., & Sussman, S.
(2020b). Vape Shop Employees: Do They Act as Smoking Cessation
Counselors?. Nicotine & Tobacco Research.
Galstyan, E., Galimov, A., & Sussman, S. (2019). Commentary: the emergence of pod mods at
vape shops. Evaluation & the health professions, 42(1), 118-124.
Garcia, R., Allem, J. P., Baezconde-Garbanati, L., Unger, J. B., & Sussman, S. (2016a).
Employee and customer handling of nicotine-containing e-liquids in vape shops. Tobacco
prevention & cessation, 2(Suppl).
Garcίa, R., Sidhu, A., Allem, J. P., Baezconde-Garbanati, L., Unger, J. B., & Sussman, S.
(2016b). Marketing activities of vape shops across racial/ethnic communities. Tobacco
prevention & cessation, 2(Suppl).
Gilbert, P. A., Kava, C. M., & Afifi, R. (2021). High-school students rarely use e-cigarettes
alone: A sociodemographic analysis of polysubstance use among adolescents in the
United States. Nicotine and Tobacco Research, 23(3), 505-510.
Giovenco, D. P. (2018). Smoke shop misclassification may cloud studies on vape shop
density. Nicotine and Tobacco Research, 20(8), 1025-1026.
Giovenco, D. P., Duncan, D. T., Coups, E. J., Lewis, M. J., & Delnevo, C. D. (2016). Census
tract correlates of vape shop locations in New Jersey. Health & Place, 40, 123-128.
94
Graham, M. (2019, December 18). Instagram bans influencers from getting paid to promote
vaping and guns. CNBC. https://www.cnbc.com/2019/12/18/instagram-to-ban-
influencers-from-promoting-vaping-and-guns.html
Heatherton, T. F., & Sargent, J. D. (2009). Does watching smoking in movies promote teenage
smoking?. Current Directions in Psychological Science, 18(2), 63-67.
Hrywna, M., Delnevo, C. D., & Lewis, M. J. (2007). Adult recall of tobacco advertising on the
Internet. Nicotine & Tobacco Research, 9(11), 1103-1107
https://www.pewresearch.org/internet/2021/04/07/social-media-use-in-2021/
Huh, J., Meza, L., Galstyan, E., Galimov, A., Yu, S., Unger, J. B., ... & Sussman, S. (2020).
Signs and customer behaviors at vape shops: Multivariate multilevel model
analysis. Addictive Behaviors Reports, 12, 100299.
Hyland, A., Travers, M. J., Cummings, K. M., Bauer, J., Alford, T., & Wieczorek, W. F. (2003).
Tobacco outlet density and demographics in Erie County, New York. American Journal
of Public Health, 93(7), 1075-1076.
Instagram. (2021). What is Instagram’s policy on the sale of marijuana?
https://help.instagram.com/789164081427334?helpref=search&sr=1&query=marijuana&
search_session_id=fad9f649771a6dd66cc7bad5b47927e6
Institute of Medicine (IOM). (2002). The future of the public’s health in the 21
st
century. The
National Academies Press. https://www.ncbi.nlm.nih.gov/books/NBK221239/
Jenkins, M. C., Kelly, L., Binger, K., & Moreno, M. A. (2021). Cyber-ethnography of cannabis
marketing on social media. Substance abuse treatment, prevention, and policy, 16(1), 1-
10.
95
Kaur, G., Lungarella, G., & Rahman, I. (2020). SARS-CoV-2 COVID-19 susceptibility and lung
inflammatory storm by smoking and vaping. Journal of Inflammation, 17(1), 1-8.
Keyes, K. M., Wall, M., Feng, T., Cerdá, M., & Hasin, D. S. (2017). Race/ethnicity and
marijuana use in the United States: Diminishing differences in the prevalence of use,
2006–2015. Drug and alcohol dependence, 179, 379-386.
Khan, M. L. (2017). Social media engagement: What motivates user participation and
consumption on YouTube?. Computers in human behavior, 66, 236-247.
Knutzen, K. E., Moran, M. B., & Soneji, S. (2018). Combustible and electronic tobacco and
marijuana products in hip-hop music videos, 2013-2017. JAMA internal
medicine, 178(12), 1608-1615.
Kong, A. Y., Eaddy, J. L., Morrison, S. L., Asbury, D., Lindell, K. M., & Ribisl, K. M. (2017a).
Using the Vape Shop Standardized Tobacco Assessment for Retail Settings (V-STARS)
to assess product availability, price promotions, and messaging in New Hampshire vape
shop retailers. Tobacco regulatory science, 3(2), 174-182.
Kong, G., Unger, J., Baezconde-Garbanati, L., & Sussman, S. (2017b). The associations between
Yelp online reviews and vape shops closing or remaining open one year later. Tobacco
prevention & cessation, 2(Suppl).
Kowitt, S. D., Meernik, C., Baker, H. M., Osman, A., Huang, L. L., & Goldstein, A. O. (2017).
Perceptions and experiences with flavored non-menthol tobacco products: a systematic
review of qualitative studies. International journal of environmental research and public
health, 14(4), 338.
96
Laws, M. B., Whitman, J., Bowser, D. M., & Krech, L. (2002). Tobacco availability and point of
sale marketing in demographically contrasting districts of Massachusetts. Tobacco
control, 11(suppl 2), ii71-ii73.
Lee, D. C., Crosier, B. S., Borodovsky, J. T., Sargent, J. D., & Budney, A. J. (2016). Online
survey characterizing vaporizer use among cannabis users. Drug and alcohol
dependence, 159, 227-233.
Lee, J. G., Orlan, E. N., Sewell, K. B., & Ribisl, K. M. (2018). A new form of nicotine retailers:
a systematic review of the sales and marketing practices of vape shops. Tobacco
control, 27(e1), e70-e75.
Leung, J., Chiu, C. Y. V., Stjepanović, D., & Hall, W. (2018). Has the legalisation of medical
and recreational cannabis use in the USA affected the prevalence of cannabis use and
cannabis use disorders?. Current Addiction Reports, 5(4), 403-417.
Lindsay, K. (2017, August 30). Do teens still watch music videos? Refinery29.
https://www.refinery29.com/en-us/2017/08/169943/music-videos-history-popular-2017
Los Angeles City Attorney. (2021, April 19). Feuer secures injunction, $1.2-million penalty
against vape company for youth targeted marketing.
https://www.lacityattorney.org/post/feuer-secures-injunction-1-2-million-penalty-against-
vape-company-for-youth-targeted-marketing
Los Angeles Housing Department (LAHD). (2007). Zip Codes Within the City of Los Angeles.
https://media.metro.net/about_us/pla/images/lazipcodes.pdf
Los Angeles Municipal Code (2017a). Article 4 Cannabis Procedures.
https://cannabis.lacity.org/sites/g/files/wph1081/f/Cannabis%20Procedures%20Ordinanc
e%20Eff.%207.23.18.pdf
97
Los Angeles Municipal Code (2017b). Article 5 Commercial Cannabis Activity.
http://clkrep.lacity.org/onlinedocs/2014/14-0366-S4_ORD_185345_12-19-2017.pdf
Mair, C., Freisthler, B., Ponicki, W. R., & Gaidus, A. (2015). The impacts of marijuana
dispensary density and neighborhood ecology on marijuana abuse and dependence. Drug
Alcohol Depend, 154, 111-116.
Majmundar, A., Kirkpatrick, M., Cruz, T. B., Unger, J. B., & Allem, J. P. (2020). Characterising
KandyPens-related posts to Instagram: implications for nicotine and cannabis
use. Tobacco control, 29(4), 472-474.
Majmundar, Anuja, et al. "Exposure to E-Cigarette Product Placement in Music Videos Is
Associated With Vaping Among Young Adults." Health Education & Behavior (2021):
10901981211003867.
Mantey, D. S., Cooper, M. R., Clendennen, S. L., Pasch, K. E., & Perry, C. L. (2016). E-
Cigarette Marketing Exposure Is Associated With E-Cigarette Use Among US Youth. J
Adolesc Health, 58(6), 686-690. doi:10.1016/j.jadohealth.2016.03.003
McGreevy, P. (2019a, August 15). California now has the biggest legal marijuana market in the
world. Its black market is even bigger. Los Angeles Times.
https://www.latimes.com/california/story/2019-08-14/californias-biggest-legal-
marijuana-market
Moreno, M. A., Gower, A. D., Jenkins, M. C., Kerr, B., & Gritton, J. (2018). Marijuana
promotions on social media: adolescents’ views on prevention strategies. Substance
abuse treatment, prevention, and policy, 13(1), 1-8.
98
Morrison, C., Gruenewald, P. J., Freisthler, B., Ponicki, W. R., & Remer, L. G. (2014). The
economic geography of medical cannabis dispensaries in California. International
Journal of Drug Policy, 25(3), 508-515.
Muthumalage, T., Lamb, T., Friedman, M. R., & Rahman, I. (2019). E-cigarette flavored pods
induce inflammation, epithelial barrier dysfunction, and DNA damage in lung epithelial
cells and monocytes. Scientific reports, 9(1), 1-11.
National Academies of Sciences, Engineering and Medicine. (2017). The Health Effects of
Cannabis and Cannabinoids: The Current State of Evidence and Recommendation for
Research. The National Academies Press.
https://www.ncbi.nlm.nih.gov/books/NBK423845/
National Cancer Institute (NCI). (2008). The Role of the Media in Promoting and Reducing
Tobacco Use. Tobacco Control Monograph 19. U.S. Department of Health and Human
Services, National Institutes of Health, National Cancer Institute. NIH Publication
Number 07-6242; 2008. https://cancercontrol.cancer.gov/sites/default/files/2020-
06/m19_complete_0.pdf
National Center for Complementary and Integrative Health (NCCIH). (2019). Cannabis
(Marijuana) and Cannabinoids: What you need to know. National Institutes of Health.
https://www.nccih.nih.gov/health/cannabis-marijuana-and-cannabinoids-what-you-need-
to-know
National Conference of State Legislatures (NCSL). (2021). State Medical Marijuana Laws.
https://www.ncsl.org/research/health/state-medical-marijuana-laws.aspx
National Institute on Drug Abuse (NIDA). (n.d.). Marijuana. National Institutes of Health.
https://www.drugabuse.gov/drug-topics/marijuana
99
National Institutes of Health (NIH). (n.d.). Population Assessment of Tobacco and Health
(PATH).NIH. https://pathstudyinfo.nih.gov/landing
Nicholas W., Greenwell L., Washburn F., Caesar E., Lee G., Loprieno D., Vidyanti I., Stroud L.,
Jan M. (2019, July 1). Los Angeles County Department of Public Health, Center for
Health Impact Evaluation; July 2019. Health Equity Implications of Retail Cannabis
Regulation In LA County. Los Angeles County Department of Public Health.
http://publichealth.lacounty.gov/chie/reports/Cannabis_HIA_Final_7_15.pdf
Olsen, M. C., & Smith, K. M. (2020). The cannabis industry: A natural laboratory for marketing
strategy research. Marketing Letters, 31(1), 7-12.
O'Sullivan, D., & Unwin, D. (2010). Geographic Information Analysis, 2nd Edition. John Wiley
& Sons.
Pedersen, E. R., Zander-Cotugno, M., Shih, R. A., Tucker, J. S., Dunbar, M. S., & D’Amico, E.
J. (2018). Online methods for locating medical marijuana dispensaries: practical
considerations for future research. Cannabis (Research Society on Marijuana), 1(2), 22.
Perrin, A. & Anderson, M. (2019, April 10). Share of U.S. adults using social media, including
Facebook, is mostly unchanged since 2018. Pew Research Center.
https://www.pewresearch.org/fact-tank/2019/04/10/share-of-u-s-adults-using-social-
media-including-facebook-is-mostly-unchanged-since-2018/
Peterson, N. A., Lowe, J. B., & Reid, R. J. (2005). Tobacco outlet density, cigarette smoking
prevalence, and demographics at the county level of analysis. Substance use &
misuse, 40(11), 1627-1635.
100
Peterson, N. A., Yu, D., Morton, C. M., Reid, R. J., Sheffer, M. A., & Schneider, J. E. (2011).
Tobacco outlet density and demographics at the tract level of analysis in New Jersey: a
statewide analysis. Drugs: education, prevention and policy, 18(1), 47-52.
Pew Research Center. (2021, April 7). Social Media Fact Sheet. Pew Research Center, Internet
& Technology. https://www.pewresearch.org/internet/fact-sheet/social-media/
Pew Research Center. (2020, December 14). How accurate will the 2020 U.S. census be? We’ll
know more soon. Pew Research Center. https://www.pewresearch.org/fact-
tank/2020/12/14/how-accurate-will-the-2020-u-s-census-be-well-know-more-soon/
Pierce, J. P., & Gilpin, E. A. (1995). A historical analysis of tobacco marketing and the uptake of
smoking by youth in the United States: 1890–1977. Health Psychology, 14(6), 500.
Public Health Law Center (2021, June 15). U.S. E-cigarette Regulations – 50 State Review.
Public Health Law Center. https://www.publichealthlawcenter.org/resources/us-e-
cigarette-regulations-50-state-review
Queally, J. & Welsh, B. (2019, May 29). Black market cannabis shops thrive in L.A. even as city
cracks down. Los Angeles Times. https://www.latimes.com/local/lanow/la-me-weed-pot-
dispensaries-illegal-marijuana-weedmaps-black-market-los-angeles-20190529-story.html
Rath, J. M., Bennett, M., Vallone, D., & Hair, E. C. (2020). Content analysis of tobacco in
episodic programming popular among youth and young adults. Tobacco control, 29(4),
475-479.
Reid, R. J., Peterson, N. A., Lowe, J. B., & Hughey, J. (2005). Tobacco outlet density and
smoking prevalence: Does racial concentration matter?. Drugs: education, prevention
and policy, 12(3), 233-238.
101
Rigotti, N. A., Moran, S. E., & Wechsler, H. (2005). US college students’ exposure to tobacco
promotions: prevalence and association with tobacco use. American journal of public
health, 95(1), 138-144.
Roditis, M. L., Delucchi, K., Chang, A., & Halpern-Felsher, B. (2016). Perceptions of social
norms and exposure to pro-marijuana messages are associated with adolescent marijuana
use. Preventive medicine, 93, 171-176.
Rodriguez, D., Carlos, H. A., Adachi-Mejia, A. M., Berke, E. M., & Sargent, J. D. (2013).
Predictors of tobacco outlet density nationwide: a geographic analysis. Tobacco
control, 22(5), 349-355.
Roeseler, A., Vuong, T. D., Henriksen, L., & Zhang, X. (2019). Assessment of underage sales
violations in tobacco stores and vape shops. JAMA pediatrics, 173(8), 795-797.
Romero, D. (2020, March 27). In California confusion over what businesses quality as
‘essential’. NBC News. https://www.nbcnews.com/business/business-news/california-
confusion-over-what-businesses-qualify-essential-n1170031
Rup, J., Goodman, S., & Hammond, D. (2020). Cannabis advertising, promotion and branding:
differences in consumer exposure between ‘legal’and ‘illegal’markets in Canada and the
US. Preventive medicine, 133, 106013.
Sargent, J. D., Beach, M. L., Adachi-Mejia, A. M., Gibson, J. J., Titus-Ernstoff, L. T., Carusi, C.
P., ... & Dalton, M. A. (2005). Exposure to movie smoking: its relation to smoking
initiation among US adolescents. Pediatrics, 116(5), 1183-1191.
Sargent, J. D., Beach, M. L., Dalton, M. A., Mott, L. A., Tickle, J. J., Ahrens, M. B., &
Heatherton, T. F. (2001). Effect of seeing tobacco use in films on trying smoking among
adolescents: cross sectional study. Bmj, 323(7326), 1394.
102
Sargent, J. D., Tanski, S. E., & Gibson, J. (2007). Exposure to movie smoking among US
adolescents aged 10 to 14 years: a population estimate. Pediatrics, 119(5), e1167-e1176.
Sarvet, A. L., Wall, M. M., Keyes, K. M., Cerdá, M., Schulenberg, J. E., O’Malley, P. M., ... &
Hasin, D. S. (2018). Recent rapid decrease in adolescents’ perception that marijuana is
harmful, but no concurrent increase in use. Drug and alcohol dependence, 186, 68-74.
Schier, J. G., Meiman, J. G., Layden, J., Mikosz, C. A., VanFrank, B., King, B. A., ... &
Meaney-Delman, D. (2019). Severe pulmonary disease associated with electronic-
cigarette–product use—interim guidance. Morbidity and Mortality Weekly
Report, 68(36), 787.
Schiff, S., Liu, F., Cruz, T. B., Unger, J. B., Cwalina, S., Leventhal, A., ... & Barrington-Trimis,
J. (2021). E-cigarette and cigarette purchasing among young adults before and after
implementation of California’s tobacco 21 policy. Tobacco control, 30(2), 206-211.
Schneider, J. E., Reid, R. J., Peterson, N. A., Lowe, J. B., & Hughey, J. (2005). Tobacco outlet
density and demographics at the tract level of analysis in Iowa: implications for
environmentally based prevention initiatives. Prevention Science, 6(4), 319-325.
Shi, S., Brant, A. R., Sabolch, A., & Pollom, E. (2019). False news of a cannabis cancer
cure. Cureus, 11(1).
Shih, R. A., Rodriguez, A., Parast, L., Pedersen, E. R., Tucker, J. S., Troxel, W. M., ... &
D'Amico, E. J. (2019). Associations between young adult marijuana outcomes and
availability of medical marijuana dispensaries and storefront signage. Addiction, 114(12),
2162-2170.
103
Smart, R., Caulkins, J. P., Kilmer, B., Davenport, S., & Midgette, G. (2017). Variation in
cannabis potency and prices in a newly legal market: evidence from 30 million cannabis
sales in Washington state. Addiction, 112(12), 2167-2177.
Soneji, S., Barrington-Trimis, J. L., Wills, T. A., Leventhal, A. M., Unger, J. B., Gibson, L. A.,
... & Sargent, J. D. (2017). Association between initial use of e-cigarettes and subsequent
cigarette smoking among adolescents and young adults: a systematic review and meta-
analysis. JAMA pediatrics, 171(8), 788-797.
Song, A. V., Ling, P. M., Neilands, T. B., & Glantz, S. A. (2007). Smoking in movies and
increased smoking among young adults. American journal of preventive medicine, 33(5),
396-403.
Spillane, T. E., Wong, B. A., & Giovenco, D. P. (2020). Content analysis of instagram posts by
leading cannabis vaporizer brands. Drug and Alcohol Dependence, 218, 108353.
Stacy, A. W., Ames, S. L., Sussman, S., & Dent, C. W. (1996). Implicit cognition in adolescent
drug use. Psychology of Addictive Behaviors, 10(3), 190.
Staggs, B. (2019, October 17). Weedmaps facing pressure to work only with legal cannabis
shops, lays off quarter of its workforce. Orange County Register.
https://www.ocregister.com/2019/10/17/weedmaps-facing-pressure-to-work-only-with-
legal-cannabis-shops-lays-off-a-quarter-of-its-workforce/
Statista. (2021, February). Most popular YouTube videos based on total global views as of
February 2021. Statista. https://www.statista.com/statistics/249396/top-youtubevideos-
views/.
Stockwell, T., & Gruenewald, P. J. (2004). Controls on the physical availability of alcohol. The
essential handbook of treatment and prevention of alcohol problems, 213-233.
104
Subritzky, T., Pettigrew, S., & Lenton, S. (2016). Issues in the implementation and evolution of
the commercial recreational cannabis market in Colorado. International Journal of Drug
Policy, 27, 1- 12.
Substance Abuse and Mental Health Services Administration (SAMHSA). (2019). The National
Survey on Drug Use and Health: 2018 (NSDUH). SAMHSA.
https://www.samhsa.gov/data/sites/default/files/cbhsq-reports/Assistant-Secretary-
nsduh2018_presentation.pdf
Substance Abuse and Mental Health Services Administration (SAMHSA). (2020). Results from
the 2018 National Survey on Drug Use and Health: Detailed Tables. U.S. Department of
Health and Human Services. SAMHSA.
https://www.samhsa.gov/data/sites/default/files/cbhsq-
reports/NSDUHDetailedTabs2018R2/NSDUHDetailedTabs2018.pdf
Sussman, S., & Barker, D. (2017). Vape shops: the e-cigarette marketplace. Tobacco Prevention
& Cessation, 2(Supplement).
Sussman, S., Allem, J. P., Garcia, J., Unger, J. B., Cruz, T. B., Garcia, R., & Baezconde-
Garbanati, L. (2016). Who walks into vape shops in Southern California?: a naturalistic
observation of customers. Tobacco induced diseases, 14(1), 1-5.
Sussman, S., Garcia, R., Cruz, T. B., Baezconde-Garbanati, L., Pentz, M. A., & Unger, J. B.
(2014). Consumers’ perceptions of vape shops in Southern California: an analysis of
online Yelp reviews. Tobacco induced diseases, 12(1), 1-9.
Tankovska, H. (2021). Most popular YouTube videos based on total global views as of February
2021. Statista. https://www.statista.com/statistics/249396/top-youtube-videos-views/
105
Thomas, C., & Freisthler, B. (2016). Examining the locations of medical marijuana dispensaries
in Los Angeles. Drug and alcohol review, 35(3), 334-337.
Thomas, C., & Freisthler, B. (2017). Evaluating the change in medical marijuana dispensary
locations in Los Angeles following the passage of local legislation. The journal of
primary prevention, 38(3), 265-277.
Tickle, J. J., Sargent, J. D., Dalton, M. A., Beach, M. L., & Heatherton, T. F. (2001). Favourite
movie stars, their tobacco use in contemporary movies, and its association with
adolescent smoking. Tobacco control, 10(1), 16-22.
Tobacco Business. (2019). YouTube Updates Advertising Policy to Block Tobacco Content.
https://tobaccobusiness.com/youtube-updates-advertising-policy-to-block-tobacco-
content/2/tract correlates of vape shop locations in New Jersey. Health & Place, 40, 123-
128.
Trangenstein, P. J., Whitehill, J. M., Jenkins, M. C., Jernigan, D. H., & Moreno, M. A. (2019).
Active cannabis marketing and adolescent past-year cannabis use. Drug and alcohol
dependence, 204, 107548.
Truth Initiative. (2016, September 27). Teen-rated video game with smoking set for wider
distribution. Truth Initiative. https://truthinitiative.org/research-resources/smoking-pop-
culture/teen-rated-video-game-smoking-set-wider-distribution
Truth Initiative. (2018a, December 11). Some video games glamorize smoking so much that
cigarettes can help players win. Truth Initiative. https://truthinitiative.org/research-
resources/tobacco-pop-culture/some-video-games-glamorize-smoking-so-much-
cigarettes-can
106
Truth Initiative. (2019a, June). While you were streaming: tobacco use sees a renormalization in
on-demand digital content, diluting progress in broadcast & theaters. Truth Initiative.
https://truthinitiative.org/sites/default/files/media/files/2019/07/WUWS-SOD-FINAL.pdf
Truth Initiative. (2019b). How much nicotine is in JUUL? Truth Initiative.
https://truthinitiative.org/research-resources/emerging-tobacco-products/how-much-
nicotine-juul
Truth Initiative. (n.d.) Master Settlement Agreement. Truth Initiative.
https://truthinitiative.org/who-we-are/our-history/master-settlement-agreement
U.S. Census. (n.d.). Census Tracts and Block Numbering Areas.
https://www2.census.gov/geo/pdfs/reference/GARM/Ch10GARM.pdf
U.S. Census Bureau. (2009). A Compass for Understanding and Using American Community
Survey Data: What State and Local Governments Need to Know. U.S. Census Bureau.
https://www.census.gov/content/dam/Census/library/publications/2009/acs/ACSstateLoca
l.pdf
U.S. Department of Health and Human Services (HHS). (2016). E-Cigarette Use Among Youth
and Young Adults: A Report of the Surgeon General—Executive Summary. HHS.
https://e-cigarettes.surgeongeneral.gov/documents/2016_SGR_Exec_Summ_508.pdf
U.S. Department of Health and Human Services (HHS). (2019). The National Survey on Drug
Use and Health: 2018. U.S. Department of Health and Human Services.
https://www.samhsa.gov/data/sites/default/files/cbhsq-reports/Assistant-Secretary-
nsduh2018_presentation.pdf
107
U.S. Department of Housing and Urban Development (HUD). (2019). Methodology for
Determining Section 8 Income Limits. HUD.
https://www.huduser.gov/portal/datasets/il/il19/IncomeLimitsMethodology-FY19.pdf
U.S. Food and Drug Administration (FDA). (2018). Retailers: Chart of required warning
statements on tobacco product packaging and advertising. FDA.
https://www.fda.gov/tobacco-products/retail-sales-tobacco-products/retailers-chart-
required-warning-statements-tobacco-product-packaging-and-advertising
U.S. Food and Drug Administration (FDA). (2016). The “Deeming Rule”: Vape Shops. FDA.
https://www.fda.gov/media/97760/download#:~:text=WHAT%20IS%20A%20VAPE%2
0SHOP%3F&text=flavored%20e%2Dliquids%2C%20and%20other%20ENDS%2Drelat
ed%20products.&text=or%20modify%20aerosolizing%20apparatus%20for,tobacco%20p
roduct%20manufacturer%2C%20or%20both.
U.S. Food and Drug Administration (FDA). (2020). FDA’s deeming regulations for e-cigarettes,
cigars and all other tobacco products. FDA. https://www.fda.gov/tobacco-
products/rules-regulations-and-guidance/fdas-deeming-regulations-e-cigarettes-cigars-
and-all-other-tobacco-products
Unger, J. B., Vos, R. O., Wu, J. S., Hardaway, K., Sarain, A. Y. L., Soto, D. W., ... & Steinberg,
J. (2020). Locations of licensed and unlicensed cannabis retailers in California: A threat
to health equity?. Preventive medicine reports, 19, 101165.
Van Dam, S. (2019). Trump’s vaping crackdown could help Juul by ending the decade’s biggest
small-business success story. The Washington Post.
https://www.washingtonpost.com/business/2019/09/23/trumps-vaping-crackdown-could-
help-juul-by-ending-decades-biggest-small-business-success-story/
108
Varadarajan, P. R., & Jayachandran, S. (1999). Marketing strategy: an assessment of the state of
the field and outlook. Journal of the academy of marketing science, 27(2), 120-143.
Vasilenko, S. A., Evans-Polce, R. J., & Lanza, S. T. (2017). Age trends in rates of substance use
disorders across ages 18–90: Differences by gender and race/ethnicity. Drug and alcohol
dependence, 180, 260-264.
Vena, A., Miloslavich, K., Cao, D., & King, A. (2020). Cue salience of the use of an electronic
nicotine delivery system (ENDS) device marketed to women. Addictive behaviors, 100,
106116.
Villarroel, M. A., Cha, A. E., Vahratian, A. (2020, April). Electronic Cigarette Use Among U.S.
Adults, 2018. NCHS Data Brief, no 365.U.S. Department of Health and Human Services.
https://www.cdc.gov/nchs/data/databriefs/db365-h.pdf
Wagoner, K. G., Berman, M., Rose, S. W., Song, E., Ross, J. C., Klein, E. G., ... & Sutfin, E. L.
(2019). Health claims made in vape shops: an observational study and content
analysis. Tobacco control, 28(e2), e119-e125.
Wang, R. J., Bhadriraju, S., & Glantz, S. A. (2021). E-cigarette use and adult cigarette smoking
cessation: a meta-analysis. American Journal of Public Health, 111(2), 230-246.
Wang, T. W., Gentzke, A. S., Creamer, M. R., Cullen, K. A., Holder-Hayes, E., Sawdey, M. D.,
... & Neff, L. J. (2019). Tobacco product use and associated factors among middle and
high school students—United States, 2019. MMWR Surveillance Summaries, 68(12), 1.
Wellman, R. J., Sugarman, D. B., DiFranza, J. R., & Winickoff, J. P. (2006). The extent to which
tobacco marketing and tobacco use in films contribute to children's use of tobacco: a
meta-analysis. Archives of pediatrics & adolescent medicine, 160(12), 1285-1296.
109
Werts, M., Urata, J., Watkins, S. L., & Chaffee, B. W. (2021). Peer Reviewed: Flavored
Cannabis Product Use Among Adolescents in California. Preventing Chronic
Disease, 18.
Whitehill, J. M., Trangenstein, P. J., Jenkins, M. C., Jernigan, D. H., & Moreno, M. A. (2020).
Exposure to cannabis marketing in social and traditional media and past-year use among
adolescents in states with legal retail cannabis. Journal of Adolescent Health, 66(2), 247-
254.
Yakowicz, W. (2021, March 3). U.S. Cannabis sales hit record $17.5 billion as Americans
consume more marijuana than ever before. Forbes.
https://www.forbes.com/sites/willyakowicz/2021/03/03/us-cannabis-sales-hit-record-175-
billion-as-americans-consume-more-marijuana-than-ever-before/?sh=2e1b7df72bcf
YouTube. (2017, December 22). Farruko, Nicki Minaj, Bad Bunny – Krippy Kush (Remix) ft.
Travis Scott, Rvssian. https://www.youtube.com/watch?v=3ATQvgkXT9E
YouTube. (n.d.). Age-restricted content. YouTube.
https://support.google.com/youtube/answer/2802167?hl=en#:~:text=If%20your%20conte
nt%20is%20age%2Drestricted%2C%20you'll%20see,restricted%20below%20the%20vid
eo%20description.
Yu, B., Chen, X., Chen, X., & Yan, H. (2020). Marijuana legalization and historical trends in
marijuana use among US residents aged 12–25: results from the 1979–2016 National
Survey on drug use and health. BMC public health, 20(1), 1-10.
110
Zhu, S., Shuang, Y., Lee, J., Cole A., Braden, K., Wolfson, T., Gamst, A. (2019). Tobacco use
among high school students in Los Angeles County. Findings from the 2017-2018
California Student Tobacco Survey. Center for Research and Intervention in Tobacco
Control (CRITC), University of California, San Diego.
http://www.publichealth.lacounty.gov/tob/pdf/Tobacco_Use_among_High_School_Stude
nts_in_Los_Angeles_County_Findings_from_the_2017-18_CSTS.pdf
Abstract (if available)
Abstract
The aims of the three papers are to examine the marketing strategies of e-cigarette and cannabis retailers by examining two key distribution channels: retailer storefronts and digital media platforms. Study 1 built on the growing body of research that has examined tobacco retailer density and neighborhood socio-demographics by examining the spatial distribution of vape shops and cannabis retailers in Los Angeles, California. This study described the current methodological problems commonly found among research examining retailer density and demonstrated a different approach using spatial analytic techniques to examine and measure demographic characteristics of retailer clusters. Study 2 examined how cannabis retailers in Los Angeles market their products on social media sites like Instagram, which allows users of all ages to follow retailer accounts, view and like images without health warnings or age verification. Study 2 builds on Study 1 by examining the social media marketing strategies of cannabis retailers in Los Angeles identified in Study 1. Finally, Study 3 extended the research on e-cigarette product placement in popular media by measuring active recall of e-cigarette marketing exposure in music videos and engagement with music videos featuring e-cigarette marketing, rather than passive exposure alone among young adults in California. This approach allows for a more nuanced examination of how impactful product placement can be on popular media platforms among young adult populations. Each study represents a different source of e-cigarette or cannabis product marketing exposure. Though each source is distinct, these exposures in the built and online environments are cumulative and can influence social norms, personal perceptions, and intentions to use. All three study findings indicate that demographic characteristics may influence the intensity or degree of marketing exposure to retailer storefronts, social media marketing, and consumption of popular music videos featuring e-cigarette promotion and imagery. Retailer storefronts, social media marketing, and product placement in popular media can serve as a visual cue that triggers substance-related thoughts, desires, and urges, which in turn can influence substance use behaviors. Collectively, Study 1, Study 2, and Study 3 move forward the literature on e-cigarette and cannabis availability and marketing exposure among priority and vulnerable populations.
Linked assets
University of Southern California Dissertations and Theses
Conceptually similar
PDF
Tobacco and marijuana surveillance using Twitter data
PDF
Role transitions, past life events, and their associations with multiple categories of substance use among emerging adults
PDF
Exploring the role of peer influence, linguistic acculturation, and social networks in substance use
PDF
Smoke-free housing policies and secondhand smoke exposure in low income multiunit housing in Los Angeles County
PDF
Normative and network influences on electronic cigarette use among adolescents
PDF
Energy drink consumption, substance use and attention-deficit/hyperactivity disorder among adolescents
PDF
The effect of an educational fotonovela on the prevention of secondhand smoke
PDF
Effects of flavorings in electronic cigarettes on the use and appeal of e-cigarettes among youth and adults
PDF
Anxiety symptoms and nicotine use among adolescents and young adults
PDF
Evaluating social networks and impact of micro-influencers who promote e-cigarettes on social media
PDF
Cultural risk and protective factors for tobacco use behaviors and depressive symptoms among American Indian adolescents in California
PDF
A network analysis of online and offline social influence processes in relation to adolescent smoking and alcohol use
PDF
Relationship between L.A. County residents' demographics and willingness to take the COVID-19 vaccine
PDF
Examining tobacco regulation opinions and policy acceptance among key opinion leaders and tobacco retailers in low socioeconomic status African American, Hispanic, and non-Hispanic White communities
PDF
Substance use disparities in adolescents of lower socioeconomic status: emerging trends in electronic cigarettes, alternative tobacco products, marijuana, and prescription drug use
PDF
The role of social support in the relationship between adverse childhood experiences and addictive behaviors across adolescence and young adulthood
PDF
Adolescent social networks, smoking, and loneliness
PDF
The influence of contextual factors on the processes of adoption and implementation of evidence-based substance use prevention and tobacco cessation programs in schools
PDF
The role of dyadic and triadic factors on psychosocial wellbeing and healthcare interactions among childhood cancer survivors, parents, and medical providers
PDF
Friendship network position on adolescent behaviors: an examination of a broker position and the likelihood of alcohol and cigarette use
Asset Metadata
Creator
Escobedo, Patricia
(author)
Core Title
Examining the built and online environments to understand cannabis and e-cigarette availability, marketing, and product use in Southern California
School
Keck School of Medicine
Degree
Doctor of Philosophy
Degree Program
Preventive Medicine (Health Behavior Research)
Publication Date
11/11/2023
Defense Date
08/31/2021
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
cannabis,e-cigarette,health disparities,Internet,Marketing,OAI-PMH Harvest,social media,substance use,tobacco,vaping
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Baezconde-Garbanati, Lourdes (
committee chair
)
Creator Email
pat.escobedo@gmail.com
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-oUC17138497
Unique identifier
UC17138497
Legacy Identifier
etd-EscobedoPa-10175
Document Type
Dissertation
Rights
Escobedo, Patricia
Type
texts
Source
20211115-wayne-usctheses-batch-896-nissen
(batch),
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given.
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Repository Email
cisadmin@lib.usc.edu
Tags
cannabis
e-cigarette
health disparities
Internet
social media
substance use
vaping