Article Text
Abstract
Introduction Dollar stores are rapidly altering the retail landscape for tobacco. Two of the three largest chains sell tobacco products in more than 24 000 stores across the USA. We sought to examine whether dollar stores are more likely to be located in disadvantaged neighbourhoods and whether dollar stores charge less for cigarettes than other tobacco retailers.
Methods Data were collected from a statewide random sample of licensed tobacco retailers in California (n=7678) in 2019. Logistic regression modelled odds of a census tract containing at least one dollar store as a function of tract demographics. Linear mixed models compared price of the cheapest cigarette pack by store type, controlling for tract demographics.
Results Census tracts with lower median household income, rural status and higher proportions of school-age youth were more likely to contain at least one dollar store. The cheapest cigarette pack cost less in dollar stores compared with all store types examined except tobacco shops. Estimated price differences ranged from $0.32 (95% CI: 0.14 to 0.51) more in liquor stores and $0.39 (95% CI: 0.22 to 0.57) more in convenience stores, to $0.82 (95% CI: 0.64 to 1.01) more in small markets and $1.86 (95% CI: 1.61 to 2.11) more in stores classified as ‘other’.
Conclusions Dollar stores may exacerbate smoking-related inequities by contributing to the availability of cheaper cigarettes in neighbourhoods that are lower income, rural and have greater proportions of youth. Pro-equity retail policies, such as minimum price laws and density reduction policies, could mitigate the health consequences of dollar stores’ rapid expansion.
- disparities
- environment
- price
- socioeconomic status
Data availability statement
Data are available upon reasonable request to the California Tobacco Control Program.
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Introduction
In the USA, dollar store chains now outnumber Walmart locations five to one.1 Two of the largest chains, Family Dollar and Dollar General, began selling tobacco products in 2012 and 2013, respectively. Since that time, they have opened over 5400 new store locations,2–5 and now operate over 24 000 stores across the USA.2 4 Moreover, the dollar store phenomenon is not unique to the USA. Countries across Asia,6 Europe7 and North America8 are witnessing similar growth in the discount retail sector. For example, Poundland operates nearly 900 stores in the UK and Ireland, serving an estimated 7 000 000 customers per week.9 The stores are a source of inexpensive flavoured nicotine e-liquids, sold at £1.10 Through their rapid expansion and business strategy of selling products at the lowest possible price to the most price-sensitive consumers, dollar stores are quickly altering the retail landscape for tobacco. Lower cigarette prices remove barriers to smoking initiation and disincentivise quitting, particularly among low-income and younger consumers.11 12 Dollar stores may exacerbate tobacco-related inequities by increasing retail access to tobacco in already inundated communities and offering tobacco products at lower prices than competitors.
Prior research has documented higher tobacco retailer density in neighbourhoods with larger proportions of low-income,13 African American14 and Hispanic residents.14 Higher density and proximity are associated with various smoking behaviours, including current and lifetime smoking,15–17 lower odds of quitting18 and higher risk of relapse.18 19 As a result, density reduction policies, some of which explicitly seek to reduce the inequitable distribution of tobacco retailers across communities,20 have become an increasingly popular approach to tobacco control.21 The high density and continued expansion of dollar stores pose a challenge to these efforts. Popular media reports indicate that dollar stores typically locate in low-income, rural, and predominantly racial and ethnic minority communities, and one recent study found closer dollar store proximity in higher poverty and majority racial and ethnic minority neighbourhoods in US metropolitan areas.22 23 However, save for the aforementioned study, these associations have yet to be examined in the scientific literature. Generating such evidence can support local policymakers in developing effective pro-equity density reduction policies.
Price is one of the main drivers of tobacco use, and the tobacco industry uses multiple strategies to maintain low cigarette prices and retain price-sensitive consumers.24 Prior evidence suggests that among all types of tobacco retailers, cigarette prices are lower, and price discounts more common, in tobacco shops, pharmacies and convenience stores, even after controlling for neighbourhood sociodemographic characteristics.25–28 For example, a 2012 study of US tobacco retailers found that single-pack prices for Marlboro Red, Newport, and the cheapest pack of cigarettes (regardless of brand) were lower in pharmacies than in liquor stores, small grocery stores, supermarkets, and convenience stores, but were not significantly different in tobacco shops.25 In a 2016 California study, the price of the cheapest pack of cigarettes (regardless of brand) in convenience stores ranged from $0.13 lower than in gas kiosks to $0.75 lower than in supermarkets, but was $0.40 higher than in tobacco shops.27 In a 2019 US study, the price of the cheapest pack of cigarettes (regardless of brand) was lower in convenience stores than in all other store types examined except tobacco shops and mass merchandise stores.26 Dollar stores were not examined separately in the aforementioned studies, and require investigation as a unique retail category.
To fill these research gaps, the current study examines whether neighbourhoods with higher proportions of priority populations—defined by higher rates of tobacco use and tobacco-related disease and disproportionate targeting by the tobacco industry, including low-income residents, rural residents, racial and ethnic minorities, and school-age children and young adults—are more likely to contain dollar stores. We then examine the price of the cheapest cigarette pack (regardless of brand) and the availability of cigarette price discounts as a function of store type (dollar stores, convenience stores, small markets, liquor stores, supermarkets, gas station booths, tobacco shops, drug stores/pharmacies and other). Conducted in a statewide random sample of tobacco retailers in California, this study is the first to examine the sociodemographic characteristics of the communities where dollar stores that sell tobacco are located and to compare cigarette prices in dollar stores and other tobacco retailers. Understanding whether and where dollar stores increase the availability and accessibility of low-cost cigarettes among priority populations can inform the development of pro-equity tobacco control policies.
Methods
Store-level data are from California’s Healthy Stores for a Healthy Community (HSHC) campaign, a statewide collaboration between tobacco control, alcohol use prevention, nutrition and sexual health partners.29 The campaign’s marketing surveillance is designed to monitor the availability and marketing of healthy and unhealthy products in the retail environment, inform the development of local healthy retail policies and evaluate the campaign’s impact over time. Data were collected between March and June 2019 by California’s 61 county and municipal Local Lead Agencies (LLAs; designees from each of California’s 61 local health jurisdictions (58 counties and 3 cities) responsible for developing comprehensive tobacco control plans) and their local partners.
Sample
The sampling frame was the California Department of Tax and Fee Administration’s (CDTFA) list of all tobacco retailers in California that had applied and paid for a state license as of October 2018 (n=31 100 retailers). The sample excluded stores that prohibited youth (eg, bars, nightclubs), required paid membership or entry (eg, Costco, state parks), or were restricted to the public (eg, military bases). The state tobacco control programme determined a target sample size for each LLA, based on total number of retailers, to achieve a margin of error ranging from 0.05 to 0.10. Zip codes were randomly sampled within each LLA jurisdiction (county or city) and all eligible tobacco retailers were included until the target was reached. For five LLAs, the target sample size to achieve the required margin of error was a census of tobacco retailers. In addition, to fulfil local programmatic needs, 26 LLAs opted to conduct a census of tobacco retailers and 19 LLAs elected to randomly select additional zip codes beyond their required sample, but did not complete a census.
Data collection
Data were collected using the SurveyPocket application, which allows for offline, mobile data collection on handheld devices (eg, iPod Touch, iPad, cell phones). A train-the-trainers model was used to train more than 700 data collectors statewide.27 Leaders from each LLA attended in-person training and field practice, and then recruited and trained additional data collectors using standardised training materials. Data collectors were provided with a pocket guide and access to a technical assistance hotline for questions that arose in the field. Data collectors completed surveys at 7969 retailers (94% completion rate). Tobacco retailers that did not sell cigarettes (n=273, 3.4% of total) were excluded from this analysis as were tobacco retailers located in census tracts for which tract-level sociodemographic data were not available (n=18, 0.2% of total). The final analytical sample included 7678 tobacco retailers.
Measures
Store type
Data collectors recorded the store type for each retailer visited, choosing from 1 of 11 categories: convenience store; drug store/pharmacy; small market/deli/produce market; supermarket/large grocery store; discount store/supercentre; liquor store; gas station booth; hookah bar/café; tobacco store/head shop; vaping product store; and other (specify). During training, data collectors were provided with standardised definitions for each store type. After data collection, all stores in the original ‘discount store/supercentre’ category were reclassified. We created a new category for dollar stores by searching the store name variable for various text strings (eg, ‘Dollar’; ‘99 Cents’) and extracting the identified retailers. Walmart (n=78) was reclassified into the supermarket category (renamed supermarket/large grocery store/supercentre), and the remaining 39 stores were reclassified using the store name variable and Google Images searches. We also reviewed the descriptions entered by data collectors in the ‘other’ category and reclassified 77 stores where the description entered matched an existing store type. One author reclassified retailers and a second author reviewed all decisions; any disagreements were resolved through discussion. Finally, we combined tobacco specialty shops and head shops to create a single tobacco shop category. The final store type variable consisted of nine categories: dollar store; convenience store; drug store/pharmacy; small market/deli/produce market; supermarket/large grocery store/supercentre; liquor store; gas station booth; tobacco shop; and other (eg, doughnut shops, water stores, and bait and tackle shops).
Price of the cheapest single pack of cigarettes
Data collectors recorded the price of the cheapest single pack of cigarettes, regardless of brand, and indicated whether sales tax was included in the price. Data collectors were instructed to ask the store clerk ‘What’s the cheapest single pack of cigarettes? How much is it?’. If the store clerk refused to answer, data collectors were instructed to compare advertised prices to find the lowest price. Data collectors then indicated whether sales tax was included in the price, selecting ‘yes’, ‘no’ or ‘unable to verify’. Following procedures in other research, we geocoded retailers to jurisdiction, obtained jurisdiction-specific sales tax rates30 and analysed price before sales tax as sales tax rates in California vary by jurisdiction.31 We removed outliers where price excluding sales tax was less than $3.89 (sum of state and federal excise tax=$3.88). Valid data for price (with sales tax information) were available for 7211 retailers (94% of total). While we did not assess inter-rater reliability in the present study, the training and data collection protocols described above are similar to those used in prior publications, with intraclass correlation coefficients ranging from 0.8132 to 0.88.33
Cigarette price discounts
Data collectors recorded whether any price discounts for cigarettes were advertised inside the store (yes/no). These were defined as temporary ‘special’ or ‘sale’ prices and multipack discounts (eg, buy two packs, get one pack free). Advertisements with general statements about price (eg, ‘everyday low price’) and promotions for cigarette cartons were not considered price discounts.
Census tract sociodemographics
We geocoded retailers to census tracts and obtained tract-level sociodemographic data from the American Community Survey 2013–2017 5-year estimates. Although zip codes were the sampling unit, we examined neighbourhood characteristics of interest at the census tract level because zip codes can be large and generally poor representations of the local neighbourhoods within which retailers are located.34 Socio-demographic characteristics included: race/ethnicity (% non-Hispanic (NH) African American; % NH white; % NH Asian/Pacific Islander; % NH multiple races/American Indian and Alaska Native (AIAN)/other races; % Hispanic of any race); age (% school-age youth (ages 5-17 years); % young adults (ages 18-24 years)); and median household income. All variables were standardised based on the sample data (n=2,317 unique census tracts) to allow for easier interpretation.
|nere standardised based on the sample data (n=2317 unique census tracts)) to allow for easier interpretation.
Census tract rural/urban classification
We used 2010 Rural–Urban Commuting Area (RUCA) codes to classify census tracts into one of three categories: urban; large rural city/town; or small and isolated small rural town. We used primary and secondary RUCA codes to classify census tracts according to the Rural Health Research Center’s categorisation scheme B.
Analysis
We used the CDTFA’s list of all tobacco retailers in California (n=31 100) to test whether census tracts with higher proportions of residents that belong to priority populations were more likely to contain dollar stores. To do this, we fit logistic regression models at the census tract level to examine the association between tract sociodemographic characteristics and odds of at least one dollar store being located in the tract. We removed census tracts for which tract-level sociodemographic data were not available (n=30, 0.4% of total) resulting in a final analytical sample of 6716 census tracts. First, we assessed bivariate associations with each sociodemographic characteristic and then fit a final model adjusting for all sociodemographic characteristics.
Data for the store-level outcome models are conceptualised as forming two two-level hierarchies: stores within census tracts (M=3.3 stores/tract, SD=2.5, range=1–17) and stores within zip codes (M=10.6 stores/zip code, SD=11.6, range=1–71). Because stores are clustered within census tracts and zip codes, and census tracts do not form a hierarchy with zip codes, we used cross-classified linear and generalised linear mixed models to examine price of the cheapest single pack of cigarettes and the availability of in-store price discounts for cigarettes, respectively, as a function of store type. We fit multilevel models specifying two random intercepts (one for tract and one for zip code) for each price outcome: (1) unadjusted models including the level one store type predictor (reference=dollar store), and (2) adjusted models including store type plus level two covariates (ie, tract-level sociodemographic characteristics).
Sensitivity analyses
We conducted two sensitivity analyses to determine whether the findings were unique to the: (1) major chain dollar stores and (2) price of cigarettes. First, we replicated all analyses restricting the dollar store category to the two major chains, Family Dollar and Dollar General (n=128; 73.1% of all dollar stores in the analytical sample; n=341; 57.2% of all dollar stores on the CDTFA list). For store-level analyses, non-chain dollar stores were recategorised as ‘other’. Second, to assess whether pricing in dollar stores was unique to cigarettes, we replicated the linear mixed model examining price of the cheapest single pack of cigarettes using price (per unit) of the least expensive pack of condoms as the outcome. This item was added by sexual health partners and was the only other price measure available in the dataset. Data collectors recorded the price of the least expensive pack of condoms and the number of condoms in the pack, which was used to calculate price per unit. Data collectors did not indicate whether price was inclusive of sales tax. We assume that the vast majority of recorded prices for condoms did not include sales tax, as was true for cigarettes. The analysis was restricted to retailers that sold condoms and for which data collectors were able to obtain information on price and pack size (86% of stores were verified to sell condoms; of those, 95% had price and pack size available; final analytical n=6250, or 81% of full HSHC analytical sample).
We did not use weighting variables because the analytical sample was restricted to the subset of stores that sold cigarettes (or subset of stores that also sold condoms for the sensitivity analysis). We assessed all models for collinearity and did not identify any issues (ie, all Variance Inflation Factors <3). All analyses were conducted using SAS software, V.9.4 (copyright 2016 by SAS Institute).
Results
Table 1 summarises retailer and census tract characteristics for the analytical sample. Convenience stores were the most prevalent store type (n=3332; 43.4%) in the sample, followed by small markets (n=1003; 13.1%) and liquor stores (n=936; 12.2%). The least common store types were pharmacies (n=350; 4.6%), dollar stores (n=175; 2.3%) and other store types (n=146; 1.9%). The majority of dollar stores (n=128; 73.1%) were either Dollar General or Family Dollar stores.
Census tract correlates of dollar store locations
There were 596 dollar stores on the CDTFA list, and there was at least one dollar store present in 524 of the 6716 census tracts. The first two columns in table 2 present descriptive statistics for census tracts containing at least one dollar store and census tracts without a dollar store, respectively. Census tracts in which dollar stores were located had higher percentages of Hispanic residents and school-age youth, were more frequently classified as large or small rural towns and less frequently classified as urban, and had lower median household income, and lower percentages of NH white and NH Asian/Pacific Islander residents than census tracts without a dollar store.
In adjusted models (table 2), there were lower odds of a census tract containing at least one dollar for each SD increase in the proportion of Asian/Pacific Islander residents (adjusted OR (aOR)=0.62, 95% CI=0.52 to 0.75); residents who identified as multiple races, American Indian and Alaska Native, or other races (aOR=0.79, 95% CI=0.69 to 0.92); and median household income (aOR=0.31, 95% CI=0.25 to 0.38). In contrast, odds of a census tract containing at least one dollar store were 51% higher (aOR=1.51, 95% CI=1.33 to 1.72) for each SD increase in the proportion of school-age youth; 75% higher for census tracts classified as large rural versus urban (aOR=1.75, 95% CI=1.18 to 2.61); and more than 3.6 times higher for census tracts classified as small rural versus urban (aOR=3.61, 95% CI=2.39 to 5.46).
Differences in cheapest cigarette pack price and price discount availability by store type
The observed price of the cheapest pack of cigarettes (regardless of brand) was lowest in tobacco shops (M=$6.29, SD=1.08) and dollar stores (M=$6.44, SD=0.76) and most expensive in small markets (M=$7.56, SD=1.50) and stores categorised as ‘other’ (M=$8.64, SD=2.18) (table 3). As shown in table 3, price differences by store type persisted in adjusted models that controlled for tract demographics. Compared with dollar stores, the cheapest cigarette pack cost more in nearly all store types. Estimated price differences ranged from $0.32 (95% CI: 0.14 to 0.51) more in liquor stores and $0.39 (95% CI: 0.22 to 0.57) more in convenience stores, to $0.82 (95% CI: 0.64 to 1.01) more in small markets and $1.86 (95% CI: 1.61 to 2.11) more in stores classified as ‘other’. Only in tobacco shops did the cheapest cigarette pack cost less than in dollar stores (b=−$0.32, 95% CI: −0.52 to –0.11).
As shown in table 4, price discounts were available in 31.4% of dollar stores. In adjusted models, compared with dollar stores, the odds of in-store price discounts for cigarettes were higher in tobacco shops (aOR=1.59, 95% CI=1.04 to 2.43), convenience stores (aOR=2.03, 95% CI=1.41 to 2.92) and pharmacies (aOR=1.59, 95% CI=1.04 to 2.43), and lower in small markets (aOR=0.57, 95% CI=0.38 to 0.84).
Sensitivity analyses
Overall, results were similar when we restricted the dollar store category to major chains only. However, in analyses examining census tract correlates of dollar store locations (online supplemental table 1), there were also lower odds of a census tract containing at least one dollar store for each SD increase in the proportion of NH African American and Hispanic residents. Again, in adjusted analyses, the cheapest cigarette pack cost more in all store types except tobacco shops, ranging from $0.47 (95% CI: 0.26 to 0.69) more in liquor stores, to $1.64 (95% CI: 1.38 to 1.89) more in stores classified as ‘other’. However, the estimated price difference between tobacco shops and dollar stores was no longer significant (b=−$0.17, 95% CI: −0.40 to 0.06) (online supplemental table 2). Interpretations and overall conclusions from analyses examining the availability of in-store price discounts (online supplemental table 3) did not differ from those of the primary analyses.
Supplemental material
To assess whether lower pricing in dollar stores was unique to cigarettes, we replicated the analyses presented in table 3 using price of the least expensive pack of condoms as the outcome. The observed price per unit for the least expensive pack of condoms was lowest in dollar stores (M=$0.78, SD=0.25) and most expensive in pharmacies (M=$1.97, SD=0.33). In adjusted models, compared with dollar stores, condoms (price per unit) cost more in all other store types, ranging from $0.27 (95% CI: 0.21 to 0.33) more in supermarkets to $1.10 (95% CI: 1.04 to 1.17) more in pharmacies (online supplemental table 4).
Discussion
In a statewide sample of California tobacco retailers, census tracts with lower median household income, rural status and higher proportions of school-age youth were more likely to contain dollar stores. Further, the price of the cheapest pack of cigarettes was significantly lower in dollar stores compared with all other tobacco retailers except tobacco shops. Dollar stores were not more likely than other store types to offer price discounts on cigarettes, which suggests that their lower cigarette prices are not attributable to temporary discounts. Our findings suggest that dollar stores contribute to the availability of cheap cigarettes among tobacco-related priority populations, including people who have low income, rural residents and youth.
The propensity of dollar stores to locate in low-income and rural areas has been widely discussed in the popular media and documented by non-profit organisations such as the Institute for Local Self-Reliance (ILSR).22 35 Our study confirms these findings and provides an important foundation for researchers and practitioners seeking to examine geographical patterns in other states and localities. That tracts with a higher proportion of school-age youth were more likely to contain dollar stores has important implications for youth smoking prevention efforts. It highlights the need to investigate additional ways in which dollar stores may facilitate youth access to tobacco, such as underage sales violations. In 2019, the US Food and Drug Administration (FDA) sent a warning letter to the Chief Executive Officer of Family Dollar identifying the chain as having one of the highest rates of illegal sales to minors (~23%).36 Additional research on how dollar stores may contribute to rural–urban disparities in tobacco retailer density is also needed. A recent study by Hall et al observed much larger net increases in the number of tobacco retailers per 10 000 adults in rural counties compared with urban counties in the southeastern USA, following CVS Pharmacy’s decision to discontinue tobacco sales in 2014 and the decisions of Family Dollar and Dollar General to begin selling tobacco in 2012 and 2013, respectively.37
Notably, in this sample, we did not find evidence that tracts with higher proportions of racial/ethnicity minority populations were more likely to contain dollar stores. Maps produced by ILSR in 2019 showed a greater number of dollar stores in neighbourhoods with a higher proportion of black or African American residents.38 These findings may reflect the sociodemographic composition of the cities examined, including Atlanta, Georgia, Newark, New Jersey, and Washington, DC, which have substantially larger African American populations than California, where African Americans comprised 6.5% of the state population in 2019.39
Our findings highlight dollar stores as a burgeoning source of low-cost cigarettes in lower income, rural and communities with higher proportions of youth. It is notable that the estimated price of the cheapest pack of cigarettes was significantly lower in dollar stores compared with convenience stores and pharmacies, as prior research has identified the latter store types as among the cheapest retail sources for cigarettes.25–27 Further, when we restricted the dollar store category to major chains, the estimated price of the cheapest cigarette pack was as low in dollar stores as tobacco shops. As price is a key determinant of smoking initiation, consumption and quitting behaviours, particularly among lower income and younger consumers,11 12 action is warranted to address the potential for dollar stores to exacerbate smoking-related inequities. Explicitly pro-equity strategies may include product-focused policies, such as minimum price laws,12 eliminating price discounts or coupon redemption, and place-based policies, such as limitations on the issuance of tobacco sales licenses40 or other density reduction policies that restrict where dollar stores can locate.20
Given the dollar store business model of offering deep price discounts on all merchandise, we were not surprised to find that the price of the least expensive pack of condoms was lowest in dollar stores. Still, this finding highlights the complicated role that dollar stores may play in underserved areas: some argue that they bring affordable goods, such as groceries, to otherwise neglected communities,41 while others contend that dollar stores harm local economies by putting small, independently owned retailers out of business.35 Several cities, such as Tulsa, Oklahoma, Kansas City, Kansas, and New Orleans, Louisiana, have adopted dispersal policies, requiring new dollar stores to be located a minimum distance from other dollar stores. Some policies also include provisions to increase access to healthy foods.42 For example, Birmingham, Alabama’s dollar store dispersal policy includes incentives for grocery stores, mobile grocers and farmers’ markets to operate in areas where dollar stores are restricted.43 Collaboration among tobacco and food researchers and practitioners may help prevent unintended consequences resulting from siloed policy proposals, and increase the likelihood of policy adoption and implementation.
Strengths and limitations
To our knowledge, this study is the first to assess the sociodemographic characteristics of communities in which dollar stores are located and to compare cigarette prices in dollar stores and other tobacco retailers. Although the data represent a large, statewide sample of licensed tobacco retailers, the results may not generalise to states outside of California, particularly where there are large differences in sociodemographic composition,tobacco-related policy landscapes and the concentration of dollar stores. Other limitations include a lack of brand-specific cigarette prices; future studies should explore whether findings are consistent across premium and discount brands as dollar stores may be more likely to carry discount brands. Finally, although census tracts are widely used to define store neighbourhoods, administratively defined areal units are subject to several limitations, including the assumption that populations are uniformly distributed throughout the unit. Future research may wish to assess whether the use of alternate definitions of neighbourhoods or assessments of racial segregation impact findings.
Conclusion
By contributing to the availability of low-cost cigarettes in lower income, rural and communities with higher proportions of youth, the expanding presence of dollar stores is poised to exacerbate inequities in tobacco use. Future research should examine additional features of the retail environment for tobacco in dollar stores in the USA and globally, such as the availability and pricing of e-cigarettes and other flavoured tobacco products, point-of-sale advertising, underage sales violations and compliance with other retail policies. Ultimately, pro-equity policies, designed in collaboration with other public health sectors, are needed to mitigate the health consequences of dollar stores’ rapid expansion and support the development of healthy communities.
What this paper adds
What is already known on this subject
In the USA, dollar store chains now outnumber Walmart locations five to one.
Two of the three largest chains, Family Dollar and Dollar General, began selling tobacco products in 2012 and 2013, respectively, and now operate more than 24 000 stores across the USA.
What important gaps in knowledge exist on this topic
Although popular media reports indicate that dollar stores typically locate in low-income, rural, suburban, and predominantly racial and ethnic minority communities, these associations have received almost no attention in the scientific literature.
Price is a key determinant of smoking-related behaviours, yet it is unknown whether dollar stores charge less for cigarettes than other tobacco retailers.
Understanding if and how dollar stores increase the availability of low-cost cigarettes among priority populations can inform the development of pro-equity tobacco control policies.
What this paper adds
Dollar stores that sell tobacco are located in neighbourhoods that are lower income, rural and have greater proportions of youth.
The cheapest pack of cigarettes costs less in dollar stores compared with all other tobacco retailers except tobacco shops.
Data availability statement
Data are available upon reasonable request to the California Tobacco Control Program.
Ethics statements
Patient consent for publication
Acknowledgments
We gratefully acknowledge Tam Vuong and Xueying Zhang of the California Department of Public Health, California Tobacco Control Program for assisting with data analysis, and the Local Lead Agencies for managing local data collection.
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Contributors IGR and LH conceptualised the research questions. EA-R, LH, and NCS oversaw the study design and data collection. IGR led the analysis and drafted the manuscript. NCS and MV supported data analysis. All authors critically revised the manuscript for important intellectual content.
Funding This study was funded by California Department of Public Health (California Tobacco Control Program #17-10041), and National Heart, Lung, and Blood Institute (T32HL007034).
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.