Distribution of vape stores relative to educational institutions in the District of Columbia: a mapping study

Authors

Amna Aijaz, George Washington University Milken Institute School of Public Health, Department of Biostatistics, Washington, DC 20052, USA.
Gigi Baer, Department of Public Health, The George Washington University Milken Institute School of Public Health, 950 New Hampshire Ave NW #2, Washington, DC 20037, USA.
Katie Li, Department of Biological Sciences, The George Washington University Columbian College of Arts and Sciences, 800 22nd St. NWSuite 6000, Washington, DC 20052, USA.
Yousuf Aijaz Wahid, Department of Medical College, The Aga Khan University Medical College Pakistan, Karachi, Sindh 74800, Pakistan.
Saad Farooq, Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA.
Nino Paichadze, Center on Commercial Determinants of Health and Department of Global Health, The George Washington University Milken Institute School of Public Health, Washington, DC 20052, USA.

Document Type

Journal Article

Publication Date

11-21-2025

Journal

Journal of public health (Oxford, England)

DOI

10.1093/pubmed/fdaf148

Keywords

Addiction; Geography; Young people

Abstract

BACKGROUND: E-cigarette companies target youth by selling vaping products (VPs) near educational Institutions (EIs). We aim to assess if vape stores (VS) are spatially related to EIs in DC. METHODS: Using ArcGIS, we displayed EIs and VS over the DC wards map. We computed spatial features and statistics. We made thematic maps, representing counts, spatial risks, and population risks of EIs, VS, and VS near EIs. RESULTS: The highest spatial risk of EIs, VS, and VS near EIs were in Wards 1, 2, and 6. A Hot Spot Analysis confirmed that 'hotter' EIs (those with more VS near them) were in Wards 1, 2, and 6. These wards had the greatest at-risk population (most Whites, least unemployed aged > = 16 years, least with low education attainment, and highest median household income). The average nearest neighbor distance between VS near EIs was 225.7 meters. This represented a clustered pattern of VS near EIs (P < .0001). CONCLUSION: VS and EIs in DC appear spatially related, in clustered patterns. VS near EIs were most densely located in Wards 1, 2, and 6, (the more affluent wards). Bans on the sale of VPs near EIs must be enforced.

APA Citation

Aijaz, Amna; Baer, Gigi; Li, Katie; Aijaz Wahid, Yousuf; Farooq, Saad; and Paichadze, Nino, "Distribution of vape stores relative to educational institutions in the District of Columbia: a mapping study" (2025). GW Authored Works. Paper 8076.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/8076

Department

Global Health